diff --git "a/val.jsonl" "b/val.jsonl" new file mode 100644--- /dev/null +++ "b/val.jsonl" @@ -0,0 +1,2700 @@ +{"id": "T1_all_20230601_0001", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-06-01", "context_summary": "ADA-USD over past 60 days: cumulative return -1.9%, annualized vol 35.4%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.38, end=0.37, cumulative_return=-1.9%, annualized_volatility=35.4%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.76, 't10y3m_spread': -1.68, 'breakeven_10y': 2.18, 'hy_oas': 4.69, 'ig_oas': 1.42, 'ted_spread': 0.09, 'mortgage_30y': 6.57, 'vix': 17.940000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-31] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.20402, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-06-01 was -20.40%, which classifies as 'negative'.", "metadata": {"future_return": -0.20402, "horizon_days": 21, "hist_return": -0.019253, "annualized_vol": 0.354275, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231219_0003", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-12-19", "context_summary": "MATIC-USD over past 60 days: cumulative return +49.3%, annualized vol 65.3%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.54, end=0.80, cumulative_return=+49.3%, annualized_volatility=65.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.48, 't10y3m_spread': -1.51, 'breakeven_10y': 2.21, 'hy_oas': 3.51, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.5600004196167}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-18] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.053176, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-12-19 was +5.32%, which classifies as 'positive'.", "metadata": {"future_return": 0.053176, "horizon_days": 21, "hist_return": 0.492931, "annualized_vol": 0.652939, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230407_0006", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2023-04-07", "context_summary": "SGOV over past 60 days: cumulative return +0.8%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=86.60, end=87.31, cumulative_return=+0.8%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.52, 't10y3m_spread': -1.61, 'breakeven_10y': 2.24, 'hy_oas': 4.84, 'ig_oas': 1.46, 'ted_spread': 0.09, 'mortgage_30y': 6.28, 'vix': 18.39999961853028}\nMarket regime: sideways\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002392, "explanation": "The actual 21-day forward return for SGOV starting 2023-04-07 was +0.24%, which classifies as 'flat'.", "metadata": {"future_return": 0.002392, "horizon_days": 21, "hist_return": 0.008207, "annualized_vol": 0.002278, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230517_0009", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-05-17", "context_summary": "QQQ over past 60 days: cumulative return +11.4%, annualized vol 17.8%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=288.46, end=321.46, cumulative_return=+11.4%, annualized_volatility=17.8%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.52, 't10y3m_spread': -1.68, 'breakeven_10y': 2.19, 'hy_oas': 4.79, 'ig_oas': 1.49, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 17.989999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-16] [\"Tesla to meet Indian officials this week - source By Aditya Kalra and Aditi Shah NEW DELHI, May 16 (Reuters) - Senior Tesla Inc TSLA.O executives will meet Indian government officials on Wednesday and Thursday to discuss local procurement of parts and other issues, a source with direct knowledge of the matter told Reuters. The electric carmaker's renewed interest in India comes nearly a year after it put on hold plans to sell cars in the country after failing to secure lower import taxes, which its CEO Elon Musk said are among the highest in the world. Tesla and an Indian government spokesperson did not immediately respond to a request for comment. Tesla wanted lower tariffs to be able to test the local market with cars imported from the U.S. and China, but the Indian government wanted it to commit to manufacturing locally before cutting import taxes on cars that can run as high as 100%. The electric carmaker had hired a local team and begun a search for showroom space, but that was also abandoned last year. Local sourcing aligns with Modi's pitch to attract manufacturers with his \\\"Make in India\\\" campaign, especially as companies look to diversify their supply chains beyond China. The meeting comes weeks ahead of Prime Minister Narendra Modi's visit to the United States in June. Bloomberg News first reported the meeting plan. (Reporting by Aditya Kalra; Additional reporting by Aditi Shah; Editing by Jan Harvey) ((aditi.shah@tr.com; +91-11-4954 8023, +91-11-3015 8023; Reuters Messaging: twitter: @aditishahsays)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Pre-Market Most Active for May 16, 2023 : SQQQ, APLD, HZNP, AAPL, FUTU, MRVL, AGL, NU, SE, HD, CL, AI The NASDAQ 100 Pre-Market Indicator is down -18.87 to 13,394.64. The total Pre-Market volume is currently 25,120,169 shares traded. The following are the most active stocks for the pre-market session: ProShares UltraPro Short QQQ (SQQQ) is +0.05 at $27.95, with 1,833,307 shares traded. This represents a .54% increase from its 52 Week Low. Applied Digital Corporation (APLD) is +1.275 at $4.69, with 1,816,264 shares traded. As reported by Zacks, the current mean recommendation for APLD is in the \\\"buy range\\\". Horizon Therapeutics Public Limited Company (HZNP) is -20.25 at $92.00, with 1,704,565 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $1.6. HZNP's current last sale is 78.97% of the target price of $116.5. Apple Inc. (AAPL) is -0.07 at $172.00, with 1,566,401 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $2.17. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". Futu Holdings Limited (FUTU) is -4.05 at $39.10, with 1,558,667 sh\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.111168, "explanation": "The actual 21-day forward return for QQQ starting 2023-05-17 was +11.12%, which classifies as 'positive'.", "metadata": {"future_return": 0.111168, "horizon_days": 21, "hist_return": 0.114398, "annualized_vol": 0.177844, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230919_0012", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-09-19", "context_summary": "IWM over past 60 days: cumulative return +1.0%, annualized vol 15.0%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=174.71, end=176.47, cumulative_return=+1.0%, annualized_volatility=15.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.73, 't10y3m_spread': -1.23, 'breakeven_10y': 2.36, 'hy_oas': 3.82, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 14.0}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-18] [\"2 Stocks That Are Cash Flow Machines to Buy Now While a profit metric like net income shouldn't be ignored, it's ultimately an accounting figure. Free cash flow, which is the amount of cash a business generates from operations after subtracting capital expenditures, is what fuels growth investments, dividend payments, share buybacks, and debt reduction. You can't spend net income. Investing in companies that are solid cash flow producers is often a good idea, assuming the price is reasonable. Two cash flow machines that trade at pessimistic valuations are AT&T (NYSE: T) and IBM (NYSE: IBM). Both stocks look like bargains. AT&T With Apple's iPhone 15 family officially announced, the major wireless carriers are using promotions to attract new customers and retain existing customers. AT&T, for example, is offering as much as $1,000 off the iPhone 15 Pro with an eligible trade-in for customers on its Unlimited plans. While this promotional activity appears aggressive, AT&T CFO Pascal Desroches noted during a recent conference that promotional activity is largely unchanged across the industry. \\\"I would characterize the environment as really healthy. The competitive dynamics is very, very healthy, very rational,\\\" Desroches said. During the same conference, Desroches reiterated AT&T's guidance calling for at least $16 billion of free cash flow this year, even as subscriber gains have slowed. Free cash flow could move higher in 2024 and beyond as AT&T pulls back a bit on capital spending. The company has been investing heavily in its 5G and fiber networks, pushing capital spending up. This year is expected to mark the peak of that spending. AT&T is valued at about $109 billion. Based on the free cash guidance, the stock's price-to-free-cash-flow ratio is around 6.8. That's an extremely pessimistic valuation. AT&T stock certainly doesn't deserve to trade at a premium: Growth will be slow at best, debt levels are still elevated, and competitive pressures could ramp up if economic conditions deteriorate. But the pessimism seems overdone. AT&T stock trades lower than it did during the dot-com bubble, the financial crisis, and the pandemic. For patient investors, this cash flow machine looks like a bargain. IBM While IBM is a complex company that spans hardware, software, and services, the tech giant ultimately offers customers solutions that aim to boost productivity and cut costs. In a tough and uncertain economy, that pitch should resonate with customers. IBM's cloud strategy is centered around hybrid cloud computing. While some companies will go all-in on the public cloud, that's not realistic for major enterprises with sprawling IT infrastructures. IBM's hybrid cloud platform, powered by Red Hat software, provides a path for customers to modernize their infrastructure and take advantage of cloud computing while minimizing disruption and keeping an eye on costs. On top of software, IBM's consulting arm provides guidance and help in navigating the move\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.052432, "explanation": "The actual 21-day forward return for IWM starting 2023-09-19 was -5.24%, which classifies as 'negative'.", "metadata": {"future_return": -0.052432, "horizon_days": 21, "hist_return": 0.010079, "annualized_vol": 0.149683, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240626_0015", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-06-26", "context_summary": "ETH-USD over past 60 days: cumulative return +4.4%, annualized vol 48.1%. Market regime: bull.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3252.17, end=3395.03, cumulative_return=+4.4%, annualized_volatility=48.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.42, 't10y3m_spread': -1.26, 'breakeven_10y': 2.22, 'hy_oas': 3.19, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 12.84000015258789}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.005721, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-06-26 was +0.57%, which classifies as 'flat'.", "metadata": {"future_return": 0.005721, "horizon_days": 21, "hist_return": 0.043928, "annualized_vol": 0.48097, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231122_0018", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-11-22", "context_summary": "XLV over past 60 days: cumulative return -3.4%, annualized vol 11.3%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=128.87, end=124.50, cumulative_return=-3.4%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.45, 't10y3m_spread': -1.12, 'breakeven_10y': 2.25, 'hy_oas': 3.95, 'ig_oas': 1.17, 'ted_spread': 0.09, 'mortgage_30y': 7.44, 'vix': 13.350000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-21] [\"AAPL Quantitative Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"EXPLAINER-What is Black Friday? And will shoppers find bargains this year? By Juveria Tabassum, Savyata Mishra Nov 16 (Reuters) - Retailers are preparing for what they hope will be yet another record-setting global shopping spree on Black Friday, the fourth Friday of November, which this year is Nov. 24. Known for crowds lining up at big-box stores to pounce on doorbuste\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.039826, "explanation": "The actual 21-day forward return for XLV starting 2023-11-22 was +3.98%, which classifies as 'positive'.", "metadata": {"future_return": 0.039826, "horizon_days": 21, "hist_return": -0.033928, "annualized_vol": 0.113186, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230505_0021", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-05-05", "context_summary": "XLRE over past 60 days: cumulative return -8.2%, annualized vol 21.9%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=36.21, end=33.25, cumulative_return=-8.2%, annualized_volatility=21.9%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.38, 't10y3m_spread': -1.68, 'breakeven_10y': 2.19, 'hy_oas': 4.95, 'ig_oas': 1.51, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 20.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-04] [\"Apple (AAPL) Q2 Earnings: How Key Metrics Compare to Wall Street Estimates For the quarter ended March 2023, Apple (AAPL) reported revenue of $94.84 billion, down 2.5% over the same period last year. EPS came in at $1.52, compared to $1.52 in the year-ago quarter. The reported revenue compares to the Zacks Consensus Estimate of $93.32 billion, representing a surprise of +1.63%. The company delivered an EPS surprise of +5.56%, with the consensus EPS estimate being $1.44. While investors closely watch year-over-year changes in headline numbers -- revenue and earnings -- and how they compare to Wall Street expectations to determine their next course of action, some key metrics always provide a better insight into a company's underlying performance. As these metrics influence top- and bottom-line performance, comparing them to the year-ago numbers and what analysts estimated helps investors project a stock's price performance more accurately. Here is how Apple performed in the just reported quarter in terms of the metrics most widely monitored and projected by Wall Street analysts: Revenue- Wearables, Home and Accessories: $8.76 billion versus the nine-analyst average estimate of $8.66 billion. Revenue- iPhone: $51.33 billion versus $49.40 billion estimated by nine analysts on average. Compared to the year-ago quarter, this number represents a +1.5% change. Net Sales- Services: $20.91 billion versus $20.86 billion estimated by nine analysts on average. Compared to the year-ago quarter, this number represents a +5.5% change. Revenue- Mac: $7.17 billion versus the nine-analyst average estimate of $7.82 billion. The reported number represents a year-over-year change of -31.3%. Net Sales- Products: $73.93 billion compared to the $72.30 billion average estimate based on nine analysts. The reported number represents a change of -4.6% year over year. Revenue- iPad: $6.67 billion versus the nine-analyst average estimate of $6.72 billion. The reported number represents a year-over-year change of -12.8%. Gross margin- Services: $14.84 billion versus $14.80 billion estimated by six analysts on average. Gross margin- Products: $27.13 billion versus the six-analyst average estimate of $26.20 billion. View all Key Company Metrics for Apple here>>> Shares of Apple have returned +2.3% over the past month versus the Zacks S&P 500 composite's -0.7% change. The stock currently has a Zacks Rank #3 (Hold), indicating that it could perform in line with the broader market in the near term. Top 5 ChatGPT Stocks Revealed Zacks Senior Stock Strategist, Kevin Cook names 5 hand-picked stocks with sky-high growth potential in a brilliant sector of Artificial Intelligence. By 2030, the AI industry is predicted to have an internet and iPhone-scale economic impact of $15.7 Trillion. Today you can invest in the wave of the future, an automation that answers follow-up questions \\u2026 admits mistakes \\u2026 challenges incorrect premises \\u2026 rejects inappropriate requests. As one\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.021368, "explanation": "The actual 21-day forward return for XLRE starting 2023-05-05 was -2.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.021368, "horizon_days": 21, "hist_return": -0.081564, "annualized_vol": 0.219179, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240423_0024", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2024-04-23", "context_summary": "FXI over past 60 days: cumulative return +8.1%, annualized vol 25.7%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=21.65, end=23.40, cumulative_return=+8.1%, annualized_volatility=25.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.35, 't10y3m_spread': -0.8, 'breakeven_10y': 2.41, 'hy_oas': 3.29, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 7.1, 'vix': 16.940000534057617}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of FXI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.137097, "explanation": "The actual 21-day forward return for FXI starting 2024-04-23 was +13.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.137097, "horizon_days": 21, "hist_return": 0.080531, "annualized_vol": 0.256899, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230124_0027", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-01-24", "context_summary": "AVAX-USD over past 60 days: cumulative return +40.4%, annualized vol 73.3%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=12.83, end=18.01, cumulative_return=+40.4%, annualized_volatility=73.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.69, 't10y3m_spread': -1.21, 'breakeven_10y': 2.28, 'hy_oas': 4.27, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.15, 'vix': 19.809999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-23] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.066261, "explanation": "The actual 21-day forward return for AVAX-USD starting 2023-01-24 was +6.63%, which classifies as 'positive'.", "metadata": {"future_return": 0.066261, "horizon_days": 21, "hist_return": 0.403662, "annualized_vol": 0.733452, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230728_0030", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-07-28", "context_summary": "XRP-USD over past 60 days: cumulative return +44.4%, annualized vol 83.2%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.49, end=0.71, cumulative_return=+44.4%, annualized_volatility=83.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.9, 't10y3m_spread': -1.5, 'breakeven_10y': 2.37, 'hy_oas': 3.78, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 14.40999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-27] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.289752, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-07-28 was -28.98%, which classifies as 'negative'.", "metadata": {"future_return": -0.289752, "horizon_days": 21, "hist_return": 0.444186, "annualized_vol": 0.832493, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240202_0033", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-02-02", "context_summary": "SOL-USD over past 60 days: cumulative return +59.0%, annualized vol 87.0%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=61.53, end=97.85, cumulative_return=+59.0%, annualized_volatility=87.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.33, 't10y3m_spread': -1.55, 'breakeven_10y': 2.19, 'hy_oas': 3.56, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 13.880000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.004837, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-02-02 was -0.48%, which classifies as 'flat'.", "metadata": {"future_return": -0.004837, "horizon_days": 21, "hist_return": 0.590315, "annualized_vol": 0.870322, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231013_0035", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-10-13", "context_summary": "AVAX-USD over past 60 days: cumulative return -26.2%, annualized vol 42.2%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=12.35, end=9.12, cumulative_return=-26.2%, annualized_volatility=42.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.36, 't10y3m_spread': -0.93, 'breakeven_10y': 2.34, 'hy_oas': 4.25, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 16.690000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-12] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.322638, "explanation": "The actual 21-day forward return for AVAX-USD starting 2023-10-13 was +32.26%, which classifies as 'positive'.", "metadata": {"future_return": 0.322638, "horizon_days": 21, "hist_return": -0.261953, "annualized_vol": 0.422492, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231024_0038", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-10-24", "context_summary": "IVV over past 60 days: cumulative return -7.8%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=443.21, end=408.66, cumulative_return=-7.8%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.19, 't10y3m_spread': -0.72, 'breakeven_10y': 2.41, 'hy_oas': 4.51, 'ig_oas': 1.33, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 20.3700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-23] [\"Why the Market Dipped But Apple (AAPL) Gained Today Apple (AAPL) closed at $173 in the latest trading session, marking a +0.07% move from the prior day. The stock exceeded the S&P 500, which registered a loss of 0.17% for the day. On the other hand, the Dow registered a loss of 0.58%, and the technology-centric Nasdaq increased by 0.27%. Heading into today, shares of the maker of iPhones, iPads and other products had lost 1.09% over the past month, outpacing the Computer and Technology sector's loss of 2.16% and the S&P 500's loss of 3.95% in that time. The upcoming earnings release of Apple will be of great interest to investors. The company's earnings report is expected on November 2, 2023. The company is forecasted to report an EPS of $1.39, showcasing a 7.75% upward movement from the corresponding quarter of the prior year. Alongside, our most recent consensus estimate is anticipating revenue of $88.93 billion, indicating a 1.34% downward movement from the same quarter last year. Investors should also pay attention to any latest changes in analyst estimates for Apple. Recent revisions tend to reflect the latest near-term business trends. As such, positive estimate revisions reflect analyst optimism about the company's business and profitability. Based on our research, we believe these estimate revisions are directly related to near-team stock moves. To utilize this, we have created the Zacks Rank, a proprietary model that integrates these estimate changes and provides a functional rating system. The Zacks Rank system ranges from #1 (Strong Buy) to #5 (Strong Sell). It has a remarkable, outside-audited track record of success, with #1 stocks delivering an average annual return of +25% since 1988. Over the past month, the Zacks Consensus EPS estimate has shifted 0.39% downward. Apple presently features a Zacks Rank of #3 (Hold). In terms of valuation, Apple is presently being traded at a Forward P/E ratio of 26.36. This expresses a premium compared to the average Forward P/E of 11.78 of its industry. It's also important to note that AAPL currently trades at a PEG ratio of 2.32. This metric is used similarly to the famous P/E ratio, but the PEG ratio also takes into account the stock's expected earnings growth rate. The average PEG ratio for the Computer - Mini computers industry stood at 2.32 at the close of the market yesterday. The Computer - Mini computers industry is part of the Computer and Technology sector. This group has a Zacks Industry Rank of 54, putting it in the top 22% of all 250+ industries. The Zacks Industry Rank is ordered from best to worst in terms of the average Zacks Rank of the individual companies within each of these sectors. Our research shows that the top 50% rated industries outperform the bottom half by a factor of 2 to 1. Keep in mind to rely on Zacks.com to watch all these stock-impacting metrics, and more, in the succeeding trading sessions. 7 Best Stocks for the Next 30 Days Just released: Experts distill 7 el\n\nPredict whether the return of IVV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.074114, "explanation": "The actual 21-day forward return for IVV starting 2023-10-24 was +7.41%, which classifies as 'positive'.", "metadata": {"future_return": 0.074114, "horizon_days": 21, "hist_return": -0.077941, "annualized_vol": 0.119027, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240815_0041", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-15", "context_summary": "SPY over past 60 days: cumulative return +2.9%, annualized vol 13.9%. Market regime: sideways.", "question": "Asset: SPY\nHistorical prices (past 60 trading days): start=517.47, end=532.54, cumulative_return=+2.9%, annualized_volatility=13.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.11, 't10y3m_spread': -1.49, 'breakeven_10y': 2.06, 'hy_oas': 3.46, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.47, 'vix': 16.190000534057617}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 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2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-06-30 0000731766 unh:ProductsAndServicesMember 2024-06-30 0000731766 unh:ProductsAndServicesMember 2023-12-31 0000731766 2024-07-01 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2024-06-30 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2024-06-30 0000731766 us-gaap:CorporateDebtSecuritiesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nPredict whether the return of SPY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.016164, "explanation": "The actual 21-day forward return for SPY starting 2024-08-15 was +1.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.016164, "horizon_days": 21, "hist_return": 0.029137, "annualized_vol": 0.139032, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230626_0044", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-06-26", "context_summary": "XRP-USD over past 60 days: cumulative return +5.0%, annualized vol 37.9%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.47, end=0.49, cumulative_return=+5.0%, annualized_volatility=37.9%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.67, 'breakeven_10y': 2.21, 'hy_oas': 4.4, 'ig_oas': 1.35, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 13.4399995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-25] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.542157, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-06-26 was +54.22%, which classifies as 'positive'.", "metadata": {"future_return": 0.542157, "horizon_days": 21, "hist_return": 0.05014, "annualized_vol": 0.378688, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230928_0047", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-09-28", "context_summary": "XLE over past 60 days: cumulative return +14.7%, annualized vol 18.3%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=37.01, end=42.47, cumulative_return=+14.7%, annualized_volatility=18.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.49, 't10y3m_spread': -0.97, 'breakeven_10y': 2.34, 'hy_oas': 4.03, 'ig_oas': 1.21, 'ted_spread': 0.09, 'mortgage_30y': 7.19, 'vix': 18.21999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-27] [\"Is ProShares S&P Technology Dividend Aristocrats ETF (TDV) a Strong ETF Right Now? Launched on 11/05/2019, the ProShares S&P Technology Dividend Aristocrats ETF (TDV) is a smart beta exchange traded fund offering broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Because market cap weighted indexes provide a low-cost, convenient, and transparent way of replicating market returns, they work well for investors who believe in market efficiency. If you're the kind of investor who would rather try and beat the market through good stock selection, then smart beta funds are your best choice; this fund class is known for tracking non-cap weighted strategies. These indexes attempt to select stocks that have better chances of risk-return performance, based on certain fundamental characteristics or a combination of such characteristics. While this space offers a number of choices to investors, including simplest equal-weighting, fundamental weighting and volatility/momentum based weighting methodologies, not all these strategies have been able to deliver superior results. Fund Sponsor & Index The fund is managed by Proshares. TDV has been able to amass assets over $203.91 million, making it one of the average sized ETFs in the Technology ETFs. TDV seeks to match the performance of the S&P TECHNOLOGY DIVIDEND ARISTOCRATS INDX before fees and expenses. The S&P Technology Dividend Aristocrats Index targets companies from information technology, internet and direct marketing retail, interactive home entertainment, and interactive media and services segments of the economy. Cost & Other Expenses When considering an ETF's total return, expense ratios are an important factor. And, cheaper funds can significantly outperform their more expensive cousins in the long term if all other factors remain equal. Operating expenses on an annual basis are 0.45% for TDV, making it one of the cheaper products in the space. It has a 12-month trailing dividend yield of 1.38%. Performance and Risk The ETF return is roughly 12.29% and is up about 21.22% so far this year and in the past one year (as of 09/27/2023), respectively. TDV has traded between $49.99 and $67.88 during this last 52-week period. The fund has a beta of 1.05 and standard deviation of 20.40% for the trailing three-year period. With about 39 holdings, it has more concentrated exposure than peers. Alternatives ProShares S&P Technology Dividend Aristocrats ETF is an excellent option for investors seeking to outperform the Technology ETFs segment of the market. There are other ETFs in the space which investors could consider as well. IShares Core Dividend Growth ETF (DGRO) tracks Morningstar US Dividend Growth Index and the Vanguard Dividend Appreciation ETF (VIG) tracks NASDAQ US Dividend Achievers Select Index. ISha\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.082602, "explanation": "The actual 21-day forward return for XLE starting 2023-09-28 was -8.26%, which classifies as 'negative'.", "metadata": {"future_return": -0.082602, "horizon_days": 21, "hist_return": 0.147324, "annualized_vol": 0.182517, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230531_0050", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-05-31", "context_summary": "XLK over past 60 days: cumulative return +17.9%, annualized vol 19.7%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=68.81, end=81.13, cumulative_return=+17.9%, annualized_volatility=19.7%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.77, 't10y3m_spread': -1.68, 'breakeven_10y': 2.22, 'hy_oas': 4.58, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.57, 'vix': 17.459999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-30] [\"The 25 Best Growth Stocks for the Next 5 Years InvestorPlace - Stock Market News, Stock Advice & Trading Tips Looking for the best growth stocks to buy will take much more scrutiny in the current market environment. I wrote a column on Dec. 31, 2022 about 25 tech stocks to \\u201cbuy before they take off in 2023.\\u201d Almost all of them have rallied and are up substantially since they changed hands for peanuts back then. However, the situation now is very different after the rally this year, and most growth stocks do not provide compelling entry points. This does not mean that investors should shun all growth names. There are still high-quality growth stocks with excellent long-term potential, and jumping on board is a good idea no matter the market conditions. Of course, one may say there are risks of a recession, a debt default, etc. But there will always be some hubbub, and it\\u2019s not the best idea to always put too much thought into the worst-case scenarios. For example, investors who feared the worst in the summer of 2022 and closed their positions on a loss likely regret that decision now. No one has a crystal ball, and trying to avoid near-term losses will likely lead to losing out on future gains. That\\u2019s why most well-respected investors have made their fortunes through time in the market, not timing. Naturally, blindly buying does not apply to all growth stocks, and I will not include stocks with price targets too low from the current price point. That said, let\\u2019s look at the 25 best growth stocks to buy for the next five years in no particular order: Alphabet (GOOG, GOOGL) Source: salarko / Shutterstock.com Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) has repeatedly proven that it can continue competing in all sectors and catch up with new trends. The ad market slowdown since mid-2022 and then OpenAI\\u2019s ChatGPT integration with Bing caused panic about Google\\u2019s future, and the company did make a blunder by rushing Bard. However, it has since improved on Bard, and the chatbot is now a serious contender to ChatGPT. It is trained on a larger dataset and can theoretically perform more tasks. In addition, the initial hype surrounding Bing seems to be nothing more than a fad. Google\\u2019s search engine market share has only grown while Bing\\u2019s has declined. Alphabet\\u2019s ad revenue still lags behind but that will eventually recover in the long run. Thus, I see GOOG as a strong buy at this level. Microsoft (MSFT) Source: NYCStock / Shutterstock.com Things are only looking up for Microsoft (NASDAQ:MSFT) as the company fires on all cylinders. Microsoft is chipping away at the businesses of other tech giants and is looking to expand and threaten others. For example, Azure has grown to become a major AWS competitor, while Bing has kept Google tense. It is also spearheading development in AI with its investments in OpenAI. Microsoft is also investing massively in quantum computing, gaming and mixed reality, all of which are hi\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.060532, "explanation": "The actual 21-day forward return for XLK starting 2023-05-31 was +6.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.060532, "horizon_days": 21, "hist_return": 0.179076, "annualized_vol": 0.197063, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241212_0053", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2024-12-12", "context_summary": "EWJ over past 60 days: cumulative return +2.4%, annualized vol 16.9%. Market regime: bull.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=65.33, end=66.91, cumulative_return=+2.4%, annualized_volatility=16.9%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.11, 't10y3m_spread': -0.12, 'breakeven_10y': 2.3, 'hy_oas': 2.66, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.579999923706056}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 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us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.058419, "explanation": "The actual 21-day forward return for EWJ starting 2024-12-12 was -5.84%, which classifies as 'negative'.", "metadata": {"future_return": -0.058419, "horizon_days": 21, "hist_return": 0.024211, "annualized_vol": 0.16913, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230117_0056", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-01-17", "context_summary": "IWM over past 60 days: cumulative return +9.8%, annualized vol 23.6%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=163.83, end=179.82, cumulative_return=+9.8%, annualized_volatility=23.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.73, 't10y3m_spread': -1.18, 'breakeven_10y': 2.18, 'hy_oas': 4.19, 'ig_oas': 1.32, 'ted_spread': 0.09, 'mortgage_30y': 6.33, 'vix': 18.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-13] [\"Tim Cook\\u2019s pay re-enters earth\\u2019s atmosphere Reuters Reuters NEW YORK (Reuters Breakingviews) - How to compensate Apple Chief Executive Tim Cook is one of the more puzzling questions for corporate governance experts. His pay has been out of this world, but then so has the iPhone maker\\u2019s share price performance. Nonetheless Apple, its investors and its board have agreed Cook\\u2019s pay should orbit closer to Earth in 2023. The $2.1 trillion company has comfortably outperformed rivals over the past three years, with shareholder returns including reinvested dividends in the top percentile among its peers, according to Institutional Shareholder Services. Likewise, his annual compensation of $99 million in 2022 was over 4 times the median of peers, who include Amazon.com\\u2019s Andrew Jassy and AT&T\\u2019s John Stankey. On Friday, Apple said Cook\\u2019s targeted pay will fall to $49 million. That\\u2019s an improvement, but still generous. Apple says it will target his pay between 80th and 90th percentile among peers in future years. A bigger improvement is making Cook\\u2019s pay less of a giveaway. In 2022, half of his award of Apple stock paid out automatically over time \\u2013 so all he had to do is wait. Now it\\u2019s 75% performance-based, and his unvested time-based awards lapse if he retires. This is hardly space-age stuff, but at least Apple\\u2019s pay is no longer stuck in the past. (By Robert Cyran) Follow @Breakingviews on Twitter Capital Calls - More concise insights on global finance: BlackRock edges closer to its Blackstone roots The fog lifts for Didi's path to normalcy Inflation drop gives Fed leeway to save jobs Gaming\\u2019s winter of discontent bolsters M&A logic TSMC foots the bill for global chip supremacy (Editing by John Foley and Amanda Gomez) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Don't Ignore These Companies' Cash-Generating Abilities It goes without saying that searching for stocks can be challenging, especially with an extensive list of options available. However, one way to cut out the bad apples is by focusing on stocks with strong free cash flow. But what is free cash flow, and why does it matter? In its simplest form, free cash flow is the amount of cash a company keeps after paying for operating costs and capital expenditures. A high free cash flow allows for more growth opportunities, a greater potential for share buybacks, consistent dividend payouts, and the ability to pay off debt easily. Three companies \\u2013 Apple AAPL, Alphabet GOOGL, and Verizon Communications VZ \\u2013 all generate substantial cash. Below is a chart illustrating the performance of all three stocks over the last year, with the S&P 500 blended in as a benchmark. Image Source: Zacks Investment Research Let\\u2019s take a closer look at each one. Apple We\\u2019re all familiar with the legendary Apple, the company that\\u2019s entirely ch\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.040895, "explanation": "The actual 21-day forward return for IWM starting 2023-01-17 was +4.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.040895, "horizon_days": 21, "hist_return": 0.097559, "annualized_vol": 0.235756, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240610_0059", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-06-10", "context_summary": "XLB over past 60 days: cumulative return -0.7%, annualized vol 12.2%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=43.51, end=43.20, cumulative_return=-0.7%, annualized_volatility=12.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.44, 't10y3m_spread': -1.09, 'breakeven_10y': 2.3, 'hy_oas': 3.15, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.99, 'vix': 12.220000267028809}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.004092, "explanation": "The actual 21-day forward return for XLB starting 2024-06-10 was +0.41%, which classifies as 'flat'.", "metadata": {"future_return": 0.004092, "horizon_days": 21, "hist_return": -0.007134, "annualized_vol": 0.121641, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240201_0061", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-02-01", "context_summary": "XLRE over past 60 days: cumulative return +9.8%, annualized vol 17.9%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=32.23, end=35.37, cumulative_return=+9.8%, annualized_volatility=17.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.28, 't10y3m_spread': -1.43, 'breakeven_10y': 2.26, 'hy_oas': 3.59, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 14.350000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K BA 2024-01-31] ba-20231231 FALSE 2023 FY BOEING CO 0000012927 http://fasb.org/us-gaap/2023#Revenues http://fasb.org/us-gaap/2023#Revenues http://fasb.org/us-gaap/2023#Revenues http://fasb.org/us-gaap/2023#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2023#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2023#LiabilitiesCurrent http://fasb.org/us-gaap/2023#LiabilitiesCurrent http://fasb.org/us-gaap/2023#OtherLiabilitiesNoncurrent 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us-gaap:BankOverdraftsMember 2023-12-31 0000012927 us-gaap:BankOverdraftsMember 2022-12-31 0000012927 srt:MinimumMember us-gaap:LandAndLandImprovementsMember 2023-12-31 0000012927 srt:MaximumMember us-gaap:LandAndLandImprovementsMember 2023-12-31 0000012927 srt:MinimumMember us-gaap:MachineryAndEquipmentMember 2023-12-31 0000012927 srt:MaximumMember us-gaap:MachineryAndEquipmentMember 2023-12-31 0000012927 us-gaap:SoftwareAndSoftwareDevelopmentCostsMember 2023-12-31 0000012927 srt:MaximumMember sic:Z7372 2023-12-31 0000012927 srt:MinimumMember us-gaap:DevelopedTechnologyRightsMember 2023-12-31 0000012927 [...TRUNCATED...] 02 of Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 97 The Bo eing C ompany Clawback Policy 99.1 Commercial Program Method of Accounting (Exhibit (99)(i) to the Company’s Form 10-K for the year ended December 31, 1997) 101.SCH XBRL Taxonomy Extension Schema Document 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF XBRL Taxonomy Extension Definition Linkbase Document 101.LAB XBRL Taxonomy Extension Label Linkbase Document 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page XBRL tags are embedded within the Inline XBRL document contained in Exhibit 101 * Management contract or compensatory plan In accordance with Item 601(b)(4)(iii)(A) of Regulation S-K, copies of certain instruments defining the rights of holders of long-term debt of the Company are not filed herewith. Pursuant to this regulation, we hereby agree to furnish a copy of any such instrument to the SEC upon request. Item 16. Form 10-K Summary None. 126 Table of Contents Signatures Pursuant to the requirements of Section 13 of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on January 31, 2024. THE BOEING COMPANY (Registrant) By:   /s/ Michael J. Cleary   Michael J. Cleary – Senior Vice President and Controller 127 Table of Contents Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated on January 31, 2024. /s/ David L. Calhoun /s/ Akhil Johri David L. Calhoun – President and Chief Executive Officer and Director Akhil Johri – Director (Principal Executive Officer) /s/ Brian J. West /s/ David L. Joyce Brian J. West – Executive Vice President and Chief Financial Officer David L. Joyce – Director (Principal Financial Officer) /s/ Michael J. Cleary /s/ Lawrence W. Kellner Michael J. Cleary – Senior Vice President and Controller Lawrence W. Kellner – Chair of the Board (Principal Accounting Officer) /s/ Robert A. Bradway /s/ Steven M. Mollenkopf Robert A. Bradway – Director Steven M. Mollenkopf – Director /s/ Lynne M. Doughtie /s/ John M. Richardson Lynne M. Doughtie – Director John M. Richardson – Director /s/ David L. Gitlin /s/ Sabrina Soussan David L. Gitlin – Director Sabrina Soussan – Director /s/ Lynn J. Good /s/ Ronald A. Williams Lynn J. Good – Director Ronald A. Williams – Director /s/ Stayce D. Harris Stayce D. Harris – Director 128\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.019072, "explanation": "The actual 21-day forward return for XLRE starting 2024-02-01 was +1.91%, which classifies as 'positive'.", "metadata": {"future_return": 0.019072, "horizon_days": 21, "hist_return": 0.097567, "annualized_vol": 0.179426, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20241225_0063", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2024-12-25", "context_summary": "DBA over past 60 days: cumulative return +8.1%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=23.69, end=25.61, cumulative_return=+8.1%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.3, 't10y3m_spread': 0.19, 'breakeven_10y': 2.35, 'hy_oas': 2.86, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 14.270000457763672}\nMarket regime: sideways\n\nPredict whether the return of DBA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.042286, "explanation": "The actual 21-day forward return for DBA starting 2024-12-25 was +4.23%, which classifies as 'positive'.", "metadata": {"future_return": 0.042286, "horizon_days": 21, "hist_return": 0.080805, "annualized_vol": 0.11875, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230920_0066", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-09-20", "context_summary": "SOL-USD over past 60 days: cumulative return -18.3%, annualized vol 49.0%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=24.54, end=20.04, cumulative_return=-18.3%, annualized_volatility=49.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.71, 't10y3m_spread': -1.17, 'breakeven_10y': 2.37, 'hy_oas': 3.82, 'ig_oas': 1.21, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 14.109999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.083846, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-09-20 was +8.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.083846, "horizon_days": 21, "hist_return": -0.183365, "annualized_vol": 0.489698, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230512_0069", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-05-12", "context_summary": "BNB-USD over past 60 days: cumulative return -0.4%, annualized vol 38.0%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=308.91, end=307.70, cumulative_return=-0.4%, annualized_volatility=38.0%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.5, 't10y3m_spread': -1.68, 'breakeven_10y': 2.16, 'hy_oas': 4.81, 'ig_oas': 1.49, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 16.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-11] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.003821, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-05-12 was -0.38%, which classifies as 'flat'.", "metadata": {"future_return": -0.003821, "horizon_days": 21, "hist_return": -0.003938, "annualized_vol": 0.37986, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230504_0072", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-05-04", "context_summary": "ETH-USD over past 60 days: cumulative return +21.7%, annualized vol 46.1%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1564.47, end=1904.65, cumulative_return=+21.7%, annualized_volatility=46.1%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.51, 't10y3m_spread': -1.68, 'breakeven_10y': 2.2, 'hy_oas': 4.79, 'ig_oas': 1.45, 'ted_spread': 0.09, 'mortgage_30y': 6.43, 'vix': 18.34000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-03] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.038212, "explanation": "The actual 21-day forward return for ETH-USD starting 2023-05-04 was -3.82%, which classifies as 'negative'.", "metadata": {"future_return": -0.038212, "horizon_days": 21, "hist_return": 0.217443, "annualized_vol": 0.46096, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240620_0074", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-06-20", "context_summary": "BTC-USD over past 60 days: cumulative return +0.1%, annualized vol 37.9%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=64926.64, end=64960.30, cumulative_return=+0.1%, annualized_volatility=37.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.47, 't10y3m_spread': -1.28, 'breakeven_10y': 2.21, 'hy_oas': 3.24, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.300000190734863}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.115439, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-06-20 was -11.54%, which classifies as 'negative'.", "metadata": {"future_return": -0.115439, "horizon_days": 21, "hist_return": 0.000518, "annualized_vol": 0.378832, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240503_0077", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2024-05-03", "context_summary": "TLH over past 60 days: cumulative return -3.0%, annualized vol 10.5%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=95.12, end=92.22, cumulative_return=-3.0%, annualized_volatility=10.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.29, 't10y3m_spread': -0.88, 'breakeven_10y': 2.37, 'hy_oas': 3.16, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 14.68000030517578}\nMarket regime: sideways\n\nPredict whether the return of TLH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.019278, "explanation": "The actual 21-day forward return for TLH starting 2024-05-03 was +1.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.019278, "horizon_days": 21, "hist_return": -0.030448, "annualized_vol": 0.104828, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230410_0080", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-04-10", "context_summary": "BNB-USD over past 60 days: cumulative return +2.3%, annualized vol 41.6%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=305.96, end=312.87, cumulative_return=+2.3%, annualized_volatility=41.6%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.58, 't10y3m_spread': -1.56, 'breakeven_10y': 2.25, 'hy_oas': 4.84, 'ig_oas': 1.46, 'ted_spread': 0.09, 'mortgage_30y': 6.28, 'vix': 18.39999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-09] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.032493, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-04-10 was +3.25%, which classifies as 'positive'.", "metadata": {"future_return": 0.032493, "horizon_days": 21, "hist_return": 0.022591, "annualized_vol": 0.41552, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230911_0083", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-09-11", "context_summary": "XLP over past 60 days: cumulative return -2.2%, annualized vol 9.4%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=68.05, end=66.55, cumulative_return=-2.2%, annualized_volatility=9.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.72, 't10y3m_spread': -1.29, 'breakeven_10y': 2.33, 'hy_oas': 3.85, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.12, 'vix': 13.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-08] [\"What Lies Ahead for Apple ETFs After iPhone Use Ban? The tech giant Apple Inc. AAPL shed nearly $200 billion in market value in just two days amid the reports of China planning to expand a ban on the use of iPhones to government-backed agencies and state companies. Notably, China is Apple\\u2019s third-largest market, accounting for 18% of the company\\u2019s total revenues last year. The Wall Street Journal disclosed on Wednesday that Beijing had issued a directive instructing officials within central government agencies not to bring iPhones into their workplaces or use them for professional purposes. Bloomberg News later reported that this prohibition could extend to employees of state-owned enterprises and government-affiliated institutions. Bernstein analyst believes an iPhone ban on all Chinese government employees could cut Apple's phone sales in China by as much as 5%. However, most analysts are also calling the reaction overblown, considering China is a much larger market beyond government agencies. Wedbush Securities thinks the ban would affect less than 5,00,000 iPhones of the roughly 45 million he expects to be sold in the country over the next 12 months. The rumored restriction on iPhones comes closely after Huawei, a Chinese tech giant, launched its new premium smartphone. Bank of America analysts found the timing of these events to be noteworthy. Growth Prospects One of the primary motivations to invest in Apple is its dominant presence in the consumer tech landscape, positioning it favorably for expansion into rapidly growing sectors like artificial intelligence (AI) and virtual/augmented reality (VR/AR). These areas are anticipated to see compound annual growth rates exceeding 30% until 2030 (read: Guide to Artificial Intelligence ETFs). Historically, Apple has demonstrated an ability to penetrate new markets and swiftly capture significant market share. With the recent launch of its VR/AR headset, the Vision Pro, in June, Apple's growth potential seems even more promising. Additionally, the iPhone maker is expanding into new markets. Apple's Services segment, which includes the App Store, iCloud, Apple Music, Apple TV+ and Apple Arcade, has been a significant growth driver. With a growing global user base, these services are expected to generate massive revenues. Solid Zacks Estimates Apple boasts the world\\u2019s highest stock market valuation, at nearly $2.8 trillion. It has seen positive earnings estimate revision of a penny for both the current and the next fiscal year over the past 30 days. Apple currently has an average brokerage recommendation (ABR) of 1.64 on a scale of 1 to 5 (Strong Buy to Strong Sell), calculated based on the actual recommendations made by 29 brokerage firms. The current ABR compares to an ABR of 1.64 a month ago based on 29 recommendations. Of the 29 recommendations deriving the current ABR, 18 are Strong Buy and three are Buy. Strong Buy and Buy, respectively, account for 62.07% and 10.34% of all rec\n\nPredict whether the return of XLP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.061576, "explanation": "The actual 21-day forward return for XLP starting 2023-09-11 was -6.16%, which classifies as 'negative'.", "metadata": {"future_return": -0.061576, "horizon_days": 21, "hist_return": -0.022093, "annualized_vol": 0.094207, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240411_0086", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-04-11", "context_summary": "MATIC-USD over past 60 days: cumulative return +6.3%, annualized vol 71.6%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.83, end=0.89, cumulative_return=+6.3%, annualized_volatility=71.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.42, 't10y3m_spread': -0.9, 'breakeven_10y': 2.4, 'hy_oas': 3.1, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.82, 'vix': 15.800000190734863}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.179827, "explanation": "The actual 21-day forward return for MATIC-USD starting 2024-04-11 was -17.98%, which classifies as 'negative'.", "metadata": {"future_return": -0.179827, "horizon_days": 21, "hist_return": 0.062645, "annualized_vol": 0.716064, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230929_0088", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-09-29", "context_summary": "DOT-USD over past 60 days: cumulative return -20.2%, annualized vol 28.1%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=5.11, end=4.07, cumulative_return=-20.2%, annualized_volatility=28.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.45, 't10y3m_spread': -0.97, 'breakeven_10y': 2.39, 'hy_oas': 4.09, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.31, 'vix': 17.34000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-28] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.08731, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-09-29 was -8.73%, which classifies as 'negative'.", "metadata": {"future_return": -0.08731, "horizon_days": 21, "hist_return": -0.202355, "annualized_vol": 0.281261, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231106_0091", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-11-06", "context_summary": "LINK-USD over past 60 days: cumulative return +91.5%, annualized vol 64.8%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=6.38, end=12.23, cumulative_return=+91.5%, annualized_volatility=64.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.26, 't10y3m_spread': -0.96, 'breakeven_10y': 2.39, 'hy_oas': 4.04, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 14.90999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-05] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.09163, "explanation": "The actual 21-day forward return for LINK-USD starting 2023-11-06 was +9.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.09163, "horizon_days": 21, "hist_return": 0.915209, "annualized_vol": 0.647545, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240619_0092", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["UNG"], "decision_date": "2024-06-19", "context_summary": "UNG over past 60 days: cumulative return +39.0%, annualized vol 59.2%. Market regime: bull.", "question": "Asset: UNG\nHistorical prices (past 60 trading days): start=14.35, end=19.94, cumulative_return=+39.0%, annualized_volatility=59.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.47, 't10y3m_spread': -1.28, 'breakeven_10y': 2.21, 'hy_oas': 3.24, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.300000190734863}\nMarket regime: bull\n\nPredict whether the return of UNG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.292377, "explanation": "The actual 21-day forward return for UNG starting 2024-06-19 was -29.24%, which classifies as 'negative'.", "metadata": {"future_return": -0.292377, "horizon_days": 21, "hist_return": 0.389547, "annualized_vol": 0.592009, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231102_0095", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-11-02", "context_summary": "BNB-USD over past 60 days: cumulative return +6.3%, annualized vol 20.0%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=214.40, end=228.00, cumulative_return=+6.3%, annualized_volatility=20.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.18, 't10y3m_spread': -0.8, 'breakeven_10y': 2.41, 'hy_oas': 4.47, 'ig_oas': 1.33, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 16.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-01] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.008816, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-11-02 was +0.88%, which classifies as 'flat'.", "metadata": {"future_return": 0.008816, "horizon_days": 21, "hist_return": 0.063434, "annualized_vol": 0.199859, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230126_0097", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-01-26", "context_summary": "ADA-USD over past 60 days: cumulative return +19.5%, annualized vol 50.0%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.31, end=0.37, cumulative_return=+19.5%, annualized_volatility=50.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.65, 't10y3m_spread': -1.26, 'breakeven_10y': 2.29, 'hy_oas': 4.35, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.15, 'vix': 19.07999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-25] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.020636, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-01-26 was +2.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.020636, "horizon_days": 21, "hist_return": 0.195088, "annualized_vol": 0.499554, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230503_0100", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2023-05-03", "context_summary": "VLUE over past 60 days: cumulative return -6.7%, annualized vol 16.8%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=89.29, end=83.30, cumulative_return=-6.7%, annualized_volatility=16.8%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.53, 't10y3m_spread': -1.68, 'breakeven_10y': 2.2, 'hy_oas': 4.7, 'ig_oas': 1.44, 'ted_spread': 0.09, 'mortgage_30y': 6.43, 'vix': 17.780000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-02] [\"Top Stocks To Buy Now? 3 Dow Stocks In Focus Today The Dow Jones Industrial Average (DJIA), commonly known as \\u201cthe Dow,\\u201d is a prominent stock market index that monitors the performance of 30 leading blue-chip companies listed on the New York Stock Exchange (NYSE) and the NASDAQ. The DJIA stands as one of the oldest and most respected market indices globally. The index acts as a gauge of the U.S. economy\\u2019s well-being, offering investors a broad overview of market performance while reflecting the robustness of various sectors, including technology, finance, healthcare, and consumer goods. In addition, Dow 30 stocks encompass the 30 constituent firms of the DJIA, chosen to portray a diverse array of industries and regarded as some of the most stable and established corporations in the United States. It is crucial to understand that the DJIA is a price-weighted index, which means the index\\u2019s value is determined by the sum of its constituents\\u2019 stock prices, adjusted for stock splits and dividends. This calculation method may result in greater influence from higher-priced stocks, rendering the index less representative of the overall market than other indices, such as the market-cap-weighted S&P 500. Bearing that in mind, let\\u2019s explore Dow Jones stocks to watch today. Dow Stocks To Watch Today Apple, Inc. (NASDAQ: AAPL) Nike, Inc. (NYSE: NKE) Honeywell International Inc. (NASDAQ: HON) Apple (AAPL Stock) Apple, Inc. (AAPL) is a globally renowned technology company that designs, manufactures, and markets consumer electronics, software, and online services. Best known for its flagship products such as the iPhone, iPad, Mac computers, and Apple Watch. Meanwhile, this week Apple is set to report its second quarter 2023 financial results. In detail, the company will release its Q2 2023 earnings results this Thursday, May 4, 2023, after the U.S. stock market closes. To recap, in Q1 2023, Apple reported earnings of $1.88 per share, with revenue of $117.2 billion. Year-to-date, shares of Apple stock have increased by 34.68% thus far. While, during Tuesday\\u2019s mid-morning trading session, AAPL stock is trading at $168.42 per share. Source: TD Ameritrade TOS [Read More] Good Stocks To Buy Right Now? 3 Tech Stocks In Focus Nike (NKE Stock) Next, Nike, Inc. (NKE) is a multinational corporation specializing in the design, development, manufacturing, and marketing of athletic footwear, apparel, equipment, and accessories. For a sense of scale, Nike is one of the world\\u2019s largest suppliers of athletic shoes and apparel. Back in March, Nike reported its most recent 3rd quarter of 2023 financial results. Diving in, the company posted an EPS of $0.79 on revenue of $12.4 billion. This came in better than analysts\\u2019 consensus estimate for the quarter which was earnings of $0.52 per share, with revenue estimates of $11.5 billion. Additionally, Nike also reported that revenue grew by 14.0% versus the same period, the prior year. In \n\nPredict whether the return of VLUE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.012996, "explanation": "The actual 21-day forward return for VLUE starting 2023-05-03 was +1.30%, which classifies as 'positive'.", "metadata": {"future_return": 0.012996, "horizon_days": 21, "hist_return": -0.067077, "annualized_vol": 0.168128, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230130_0103", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-01-30", "context_summary": "XLV over past 60 days: cumulative return +0.4%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=125.35, end=125.89, cumulative_return=+0.4%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.67, 't10y3m_spread': -1.21, 'breakeven_10y': 2.33, 'hy_oas': 4.23, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 6.13, 'vix': 18.51000022888184}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K BA 2023-01-27] ba-20221231 FALSE 2022 FY BOEING CO 0000012927 http://fasb.org/us-gaap/2022#CostOfGoodsAndServicesSold http://fasb.org/us-gaap/2022#Revenues http://fasb.org/us-gaap/2022#Revenues http://fasb.org/us-gaap/2022#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2022#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2022#LiabilitiesCurrent http://fasb.org/us-gaap/2022#LiabilitiesCurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2022#DebtCurrent http://fasb.org/us-gaap/2022#DebtCurrent http://fasb.org/us-gaap/2022#OtherAssetsCurrent http://fasb.org/us-gaap/2022#OtherAssetsCurrent http://fasb.org/us-gaap/2022#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2022#AccruedLiabilitiesCurrent 0000012927 2022-01-01 2022-12-31 0000012927 2022-06-30 iso4217:USD 0000012927 2023-01-20 xbrli:shares 0000012927 us-gaap:ProductMember 2022-01-01 2022-12-31 0000012927 us-gaap:ProductMember 2021-01-01 2021-12-31 0000012927 us-gaap:ProductMember 2020-01-01 2020-12-31 0000012927 us-gaap:ServiceMember 2022-01-01 2022-12-31 0000012927 us-gaap:ServiceMember 2021-01-01 2021-12-31 0000012927 us-gaap:ServiceMember 2020-01-01 2020-12-31 0000012927 2021-01-01 2021-12-31 0000012927 2020-01-01 2020-12-31 iso4217:USD xbrli:shares 0000012927 2022-12-31 0000012927 2021-12-31 0000012927 2020-12-31 0000012927 2019-12-31 0000012927 us-gaap:CommonStockMember 2019-12-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2019-12-31 0000012927 us-gaap:TreasuryStockMember 2019-12-31 0000012927 us-gaap:RetainedEarningsMember 2019-12-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-12-31 0000012927 us-gaap:NoncontrollingInterestMember 2019-12-31 0000012927 us-gaap:RetainedEarningsMember 2020-01-01 2020-12-31 0000012927 us-gaap:NoncontrollingInterestMember 2020-01-01 2020-12-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-01-01 2020-12-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2020-01-01 2020-12-31 0000012927 us-gaap:TreasuryStockMember 2020-01-01 2020-12-31 0000012927 us-gaap:CommonStockMember 2020-12-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2020-12-31 0000012927 us-gaap:TreasuryStockMember 2020-12-31 0000012927 us-gaap:RetainedEarningsMember 2020-12-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-12-31 0000012927 us-gaap:NoncontrollingInterestMember 2020-12-31 0000012927 us-gaap:RetainedEarningsMember 2021-01-01 2021-12-31 0000012927 us-gaap:NoncontrollingInterestMember 2021-01-01 2021-12-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-01-01 2021-12-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2021-01-01 2021-12-31 0000012927 us-gaap:TreasuryStockMember 2021-01-01 2021-12-31 0000012927 us-gaap:CommonStockMember 2021-12-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2021-12-31 0000012927 us-gaap:TreasuryStockMember 2021-12-31 0000012927 us-gaap:RetainedEarningsMember 2021-12-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-12-31 0000012927 us-gaap:NoncontrollingInterestMember 2021-12-31 0000012927 us-gaap:RetainedEarningsMember 2022-01-01 2022-12-31 0000012927 us-gaap:NoncontrollingInterestMember 2022-01-01 2022-12-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-01-01 2022-12-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2022-01-01 2022-12-31 0000012927 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2020-01-01 2020-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:GlobalServicesMember 2022-01-01 2022-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:GlobalServicesMember 2021-01-01 2021-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:GlobalServicesMember 2020-01-01 2020-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:BoeingCapitalCorporationMember 2022-01-01 2022-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:BoeingCapitalCorporationMember 2021-01-01 2021-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:BoeingCapitalCorporationMember 2020-01-01 2020-12-31 0000012927 ba:CorporateReconcilingItemsAndEliminationsMember 2022-01-01 2022-12-31 0000012927 ba:CorporateReconcilingItemsAndEliminationsMember 2021-01-01 2021-12-31 0000012927 ba:CorporateReconcilingItemsAndEliminationsMember 2020-01-01 2020-12-31 0000012927 us-gaap:OperatingSegmentsMember 2022-01-01 2022-12-31 0000012927 us-gaap:OperatingSegmentsMember 2021-01-01 2021-12-31 0000012927 us-gaap:OperatingSegmentsMember 2020-01-01 2020-12-31 ba:segment 0000012927 ba:BidAndProposalCostsMember 2022-01-01 2022-12-31 0000012927 ba:BidAndProposalCostsMember 2021-01-01 2021-12-31 0000012927 ba:BidAndProposalCostsMember 2020-01-01 2020-12-31 0000012927 us-gaap:BankOverdraftsMember 2022-12-31 0000012927 us-gaap:BankOverdraftsMember 2021-12-31 0000012927 us-gaap:LandAndLandImprovementsMember srt:MinimumMember 2022-01-01 2022-12-31 0000012927 srt:MaximumMember us-gaap:LandAndLandImprovementsMember 2022-01-01 2022-12-31 0000012927 us-gaap:MachineryAndEquipmentMember srt: [...TRUNCATED...] rm 130 Table of Contents 31.1 Certification of Chief Executive Officer pursuant to Section 302 of Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 99.1 Commercial Program Method of Accounting (Exhibit (99)(i) to the Company’s Form 10-K for the year ended December 31, 1997) 101.SCH XBRL Taxonomy Extension Schema Document 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF XBRL Taxonomy Extension Definition Linkbase Document 101.LAB XBRL Taxonomy Extension Label Linkbase Document 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page XBRL tags are embedded within the Inline XBRL document contained in Exhibit 101 * Management contract or compensatory plan In accordance with Item 601(b)(4)(iii)(A) of Regulation S-K, copies of certain instruments defining the rights of holders of long-term debt of the Company are not filed herewith. Pursuant to this regulation, we hereby agree to furnish a copy of any such instrument to the SEC upon request. Item 16. Form 10-K Summary None. 131 Table of Contents Signatures Pursuant to the requirements of Section 13 of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on January 27, 2023. THE BOEING COMPANY (Registrant) By:   /s/ Carol J. Hibbard   Carol J. Hibbard – Senior Vice President and Controller 132 Table of Contents Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated on January 27, 2023. /s/ David L. Calhoun /s/ Stayce D. Harris David L. Calhoun – President and Chief Executive Officer and Director Stayce D. Harris – Director (Principal Executive Officer) /s/ Brian J. West /s/ Akhil Johri Brian J. West – Executive Vice President and Chief Financial Officer Akhil Johri – Director (Principal Financial Officer) /s/ Carol J. Hibbard /s/ David L. Joyce Carol J. Hibbard – Senior Vice President and Controller David L. Joyce – Director (Principal Accounting Officer) /s/ Robert A. Bradway /s/ Lawrence W. Kellner Robert A. Bradway – Director Lawrence W. Kellner – Chair of the Board /s/ Lynne M. Doughtie /s/ Steven M. Mollenkopf Lynne M. Doughtie – Director Steven M. Mollenkopf – Director /s/ David L. Gitlin /s/ John M. Richardson David L. Gitlin – Director John M. Richardson – Director /s/ Lynn J. Good /s/ Ronald A. Williams Lynn J. Good – Director Ronald A. Williams – Director 133\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.035698, "explanation": "The actual 21-day forward return for XLV starting 2023-01-30 was -3.57%, which classifies as 'negative'.", "metadata": {"future_return": -0.035698, "horizon_days": 21, "hist_return": 0.004346, "annualized_vol": 0.142513, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20230810_0105", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-08-10", "context_summary": "ADA-USD over past 60 days: cumulative return +10.5%, annualized vol 61.1%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.27, end=0.30, cumulative_return=+10.5%, annualized_volatility=61.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.79, 't10y3m_spread': -1.55, 'breakeven_10y': 2.34, 'hy_oas': 3.94, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 15.960000038146973}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-09] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.137632, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-08-10 was -13.76%, which classifies as 'negative'.", "metadata": {"future_return": -0.137632, "horizon_days": 21, "hist_return": 0.104574, "annualized_vol": 0.611249, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231030_0108", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-10-30", "context_summary": "MATIC-USD over past 60 days: cumulative return +16.2%, annualized vol 42.4%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.55, end=0.64, cumulative_return=+16.2%, annualized_volatility=42.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.15, 't10y3m_spread': -0.75, 'breakeven_10y': 2.42, 'hy_oas': 4.53, 'ig_oas': 1.31, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 21.270000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-29] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.248628, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-10-30 was +24.86%, which classifies as 'positive'.", "metadata": {"future_return": 0.248628, "horizon_days": 21, "hist_return": 0.161677, "annualized_vol": 0.424351, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241129_0111", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2024-11-29", "context_summary": "IGOV over past 60 days: cumulative return -3.9%, annualized vol 8.7%. Market regime: bull.", "question": "Asset: IGOV\nHistorical prices (past 60 trading days): start=40.64, end=39.07, cumulative_return=-3.9%, annualized_volatility=8.7%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.06, 't10y3m_spread': -0.35, 'breakeven_10y': 2.26, 'hy_oas': 2.69, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 14.100000381469728}\nMarket regime: bull\n\nPredict whether the return of IGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.035797, "explanation": "The actual 21-day forward return for IGOV starting 2024-11-29 was -3.58%, which classifies as 'negative'.", "metadata": {"future_return": -0.035797, "horizon_days": 21, "hist_return": -0.038601, "annualized_vol": 0.086931, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230411_0114", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2023-04-11", "context_summary": "MORT over past 60 days: cumulative return -13.8%, annualized vol 27.3%. Market regime: sideways.", "question": "Asset: MORT\nHistorical prices (past 60 trading days): start=8.70, end=7.49, cumulative_return=-13.8%, annualized_volatility=27.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.59, 't10y3m_spread': -1.67, 'breakeven_10y': 2.27, 'hy_oas': 4.7, 'ig_oas': 1.45, 'ted_spread': 0.09, 'mortgage_30y': 6.28, 'vix': 18.96999931335449}\nMarket regime: sideways\n\nPredict whether the return of MORT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.030698, "explanation": "The actual 21-day forward return for MORT starting 2023-04-11 was -3.07%, which classifies as 'negative'.", "metadata": {"future_return": -0.030698, "horizon_days": 21, "hist_return": -0.138431, "annualized_vol": 0.272966, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231107_0117", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-11-07", "context_summary": "BNB-USD over past 60 days: cumulative return +18.7%, annualized vol 23.2%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=214.56, end=254.63, cumulative_return=+18.7%, annualized_volatility=23.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.26, 't10y3m_spread': -0.89, 'breakeven_10y': 2.42, 'hy_oas': 4.0, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 14.890000343322754}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-06] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.067787, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-11-07 was -6.78%, which classifies as 'negative'.", "metadata": {"future_return": -0.067787, "horizon_days": 21, "hist_return": 0.186765, "annualized_vol": 0.232436, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240617_0119", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-06-17", "context_summary": "ETH-USD over past 60 days: cumulative return +18.1%, annualized vol 47.9%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3066.03, end=3620.56, cumulative_return=+18.1%, annualized_volatility=47.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.47, 't10y3m_spread': -1.31, 'breakeven_10y': 2.17, 'hy_oas': 3.29, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.65999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.1403, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-06-17 was -14.03%, which classifies as 'negative'.", "metadata": {"future_return": -0.1403, "horizon_days": 21, "hist_return": 0.180865, "annualized_vol": 0.479309, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231201_0122", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-12-01", "context_summary": "ADA-USD over past 60 days: cumulative return +44.8%, annualized vol 43.1%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.26, end=0.38, cumulative_return=+44.8%, annualized_volatility=43.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.36, 't10y3m_spread': -1.08, 'breakeven_10y': 2.23, 'hy_oas': 3.84, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 12.920000076293944}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-30] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.624708, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-12-01 was +62.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.624708, "horizon_days": 21, "hist_return": 0.448463, "annualized_vol": 0.431377, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231113_0125", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-11-13", "context_summary": "CSHI over past 60 days: cumulative return +1.0%, annualized vol 0.8%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=43.35, end=43.80, cumulative_return=+1.0%, annualized_volatility=0.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.43, 't10y3m_spread': -0.92, 'breakeven_10y': 2.32, 'hy_oas': 4.03, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 14.170000076293944}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003318, "explanation": "The actual 21-day forward return for CSHI starting 2023-11-13 was +0.33%, which classifies as 'flat'.", "metadata": {"future_return": 0.003318, "horizon_days": 21, "hist_return": 0.010339, "annualized_vol": 0.008189, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231116_0127", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-11-16", "context_summary": "MATIC-USD over past 60 days: cumulative return +78.2%, annualized vol 53.7%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.52, end=0.92, cumulative_return=+78.2%, annualized_volatility=53.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.37, 't10y3m_spread': -1.0, 'breakeven_10y': 2.31, 'hy_oas': 3.89, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 14.18000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-15] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.004887, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-11-16 was -0.49%, which classifies as 'flat'.", "metadata": {"future_return": -0.004887, "horizon_days": 21, "hist_return": 0.781764, "annualized_vol": 0.537274, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241111_0130", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2024-11-11", "context_summary": "EMB over past 60 days: cumulative return +1.0%, annualized vol 6.2%. Market regime: sideways.", "question": "Asset: EMB\nHistorical prices (past 60 trading days): start=84.15, end=84.99, cumulative_return=+1.0%, annualized_volatility=6.2%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.04, 't10y3m_spread': -0.33, 'breakeven_10y': 2.35, 'hy_oas': 2.66, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 14.9399995803833}\nMarket regime: sideways\n\nPredict whether the return of EMB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.011576, "explanation": "The actual 21-day forward return for EMB starting 2024-11-11 was +1.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.011576, "horizon_days": 21, "hist_return": 0.009889, "annualized_vol": 0.06174, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240305_0133", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-03-05", "context_summary": "XLF over past 60 days: cumulative return +13.5%, annualized vol 10.8%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=34.39, end=39.02, cumulative_return=+13.5%, annualized_volatility=10.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.26, 'breakeven_10y': 2.34, 'hy_oas': 3.26, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 13.489999771118164}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 0000731766 2023-06-30 iso4217:USD 0000731766 2024-01-31 xbrli:shares 0000731766 2023-12-31 0000731766 2022-12-31 iso4217:USD xbrli:shares 0000731766 2022-01-01 2022-12-31 0000731766 2021-01-01 2021-12-31 0000731766 us-gaap:ProductMember 2023-01-01 2023-12-31 0000731766 us-gaap:ProductMember 2022-01-01 2022-12-31 0000731766 us-gaap:ProductMember 2021-01-01 2021-12-31 0000731766 us-gaap:ServiceMember 2023-01-01 2023-12-31 0000731766 us-gaap:ServiceMember 2022-01-01 2022-12-31 0000731766 us-gaap:ServiceMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2020-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2020-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2020-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2020-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2020-12-31 0000731766 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2021-01-01 2021-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2021-01-01 2021-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2021-01-01 2021-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2021-01-01 2021-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2021-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2021-12-31 0000731766 us-gaap:RetainedEarningsMember 2021-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2021-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2021-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2021-12-31 0000731766 2021-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-01-01 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-01-01 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-01-01 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-01-01 2022-12-31 0000731766 us-gaap:CommonStockMember 2022-01-01 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-01-01 2022-12-31 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-12-31 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-12-31 0000731766 us-gaap:CommonStockMember 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-12-31 0000731766 unh:EmployeeStockPurchasePlanESPPMember 2023-01-01 2023-12-31 xbrli:pure 0000731766 2024-01-01 2023-12-31 0000731766 unh:ProductsandservicesMember 2023-12-31 0000731766 unh:ProductsandservicesMember 2022-12-31 0000731766 us-gaap:HealthInsuranceProductLineMember 2023-12-31 0000731766 unh:PharmaceuticalManufacturerRebatesReceivableMember 2023-12-31 0000731766 unh:PharmaceuticalManufacturerRebatesReceivableMember 2022-12-31 0000731766 unh:UsefulLifeMember 2023-01-01 2023-12-31 0000731766 us-gaap:FurnitureAndFixturesMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:FurnitureAndFixturesMember 2023-12-31 0000731766 us-gaap:BuildingMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:BuildingMember 2023-12-31 0000731766 unh:CapitalizedsoftwareMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember unh:CapitalizedsoftwareMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2021-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-01-01 2023-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-01-01 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-12-31 0000731766 us-gaap:RestrictedStockMember 2023-01-01 2023-12-31 0000731766 unh:StockOptionsandSARsMember 2023-01-01 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2022-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2022-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nPredict whether the return of XLF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.023144, "explanation": "The actual 21-day forward return for XLF starting 2024-03-05 was +2.31%, which classifies as 'positive'.", "metadata": {"future_return": 0.023144, "horizon_days": 21, "hist_return": 0.134749, "annualized_vol": 0.107986, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230302_0135", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-03-02", "context_summary": "DOT-USD over past 60 days: cumulative return +49.5%, annualized vol 65.5%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.37, end=6.53, cumulative_return=+49.5%, annualized_volatility=65.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.88, 't10y3m_spread': -0.89, 'breakeven_10y': 2.44, 'hy_oas': 4.17, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 20.57999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-01] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.000228, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-03-02 was -0.02%, which classifies as 'flat'.", "metadata": {"future_return": -0.000228, "horizon_days": 21, "hist_return": 0.494957, "annualized_vol": 0.655175, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241015_0138", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-10-15", "context_summary": "USMV over past 60 days: cumulative return +8.1%, annualized vol 9.4%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=83.65, end=90.45, cumulative_return=+8.1%, annualized_volatility=9.4%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.13, 't10y3m_spread': -0.65, 'breakeven_10y': 2.33, 'hy_oas': 2.97, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 19.700000762939453}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of USMV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.009757, "explanation": "The actual 21-day forward return for USMV starting 2024-10-15 was +0.98%, which classifies as 'flat'.", "metadata": {"future_return": 0.009757, "horizon_days": 21, "hist_return": 0.081299, "annualized_vol": 0.093973, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240701_0141", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-07-01", "context_summary": "VEA over past 60 days: cumulative return +0.7%, annualized vol 12.3%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=46.52, end=46.85, cumulative_return=+0.7%, annualized_volatility=12.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.35, 't10y3m_spread': -1.12, 'breakeven_10y': 2.28, 'hy_oas': 3.21, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 12.4399995803833}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 2026-01-01 us-gaap:InvestmentAdviceMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of VEA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.029317, "explanation": "The actual 21-day forward return for VEA starting 2024-07-01 was +2.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.029317, "horizon_days": 21, "hist_return": 0.007087, "annualized_vol": 0.123065, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240313_0144", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-03-13", "context_summary": "BNB-USD over past 60 days: cumulative return +78.0%, annualized vol 48.3%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=302.23, end=537.87, cumulative_return=+78.0%, annualized_volatility=48.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.42, 't10y3m_spread': -1.32, 'breakeven_10y': 2.3, 'hy_oas': 3.2, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 13.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.108699, "explanation": "The actual 21-day forward return for BNB-USD starting 2024-03-13 was -10.87%, which classifies as 'negative'.", "metadata": {"future_return": -0.108699, "horizon_days": 21, "hist_return": 0.779673, "annualized_vol": 0.483355, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230526_0147", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-05-26", "context_summary": "MATIC-USD over past 60 days: cumulative return -15.0%, annualized vol 40.1%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=1.05, end=0.89, cumulative_return=-15.0%, annualized_volatility=40.1%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.67, 't10y3m_spread': -1.55, 'breakeven_10y': 2.25, 'hy_oas': 4.58, 'ig_oas': 1.42, 'ted_spread': 0.09, 'mortgage_30y': 6.57, 'vix': 19.13999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-25] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.35296, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-05-26 was -35.30%, which classifies as 'negative'.", "metadata": {"future_return": -0.35296, "horizon_days": 21, "hist_return": -0.149916, "annualized_vol": 0.400631, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230727_0149", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2023-07-27", "context_summary": "VCIT over past 60 days: cumulative return -0.6%, annualized vol 6.4%. Market regime: sideways.", "question": "Asset: VCIT\nHistorical prices (past 60 trading days): start=70.53, end=70.11, cumulative_return=-0.6%, annualized_volatility=6.4%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.65, 'breakeven_10y': 2.36, 'hy_oas': 3.91, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 13.1899995803833}\nMarket regime: sideways\n\nPredict whether the return of VCIT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.010259, "explanation": "The actual 21-day forward return for VCIT starting 2023-07-27 was -1.03%, which classifies as 'negative'.", "metadata": {"future_return": -0.010259, "horizon_days": 21, "hist_return": -0.005828, "annualized_vol": 0.064435, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230627_0152", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-06-27", "context_summary": "VTI over past 60 days: cumulative return +6.9%, annualized vol 12.2%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=193.12, end=206.50, cumulative_return=+6.9%, annualized_volatility=12.2%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.68, 'breakeven_10y': 2.18, 'hy_oas': 4.45, 'ig_oas': 1.36, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 14.25}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-26] [\"Is Trending Stock Apple Inc. (AAPL) a Buy Now? Apple (AAPL) has been one of the most searched-for stocks on Zacks.com lately. So, you might want to look at some of the facts that could shape the stock's performance in the near term. Shares of this maker of iPhones, iPads and other products have returned +6.4% over the past month versus the Zacks S&P 500 composite's +5% change. The Zacks Computer - Mini computers industry, to which Apple belongs, has gained 8.7% over this period. Now the key question is: Where could the stock be headed in the near term? Although media reports or rumors about a significant change in a company's business prospects usually cause its stock to trend and lead to an immediate price change, there are always certain fundamental factors that ultimately drive the buy-and-hold decision. Earnings Estimate Revisions Here at Zacks, we prioritize appraising the change in the projection of a company's future earnings over anything else. That's because we believe the present value of its future stream of earnings is what determines the fair value for its stock. We essentially look at how sell-side analysts covering the stock are revising their earnings estimates to reflect the impact of the latest business trends. And if earnings estimates go up for a company, the fair value for its stock goes up. A higher fair value than the current market price drives investors' interest in buying the stock, leading to its price moving higher. This is why empirical research shows a strong correlation between trends in earnings estimate revisions and near-term stock price movements. Apple is expected to post earnings of $1.18 per share for the current quarter, representing a year-over-year change of -1.7%. Over the last 30 days, the Zacks Consensus Estimate has changed +0.1%. For the current fiscal year, the consensus earnings estimate of $5.99 points to a change of -2% from the prior year. Over the last 30 days, this estimate has remained unchanged. For the next fiscal year, the consensus earnings estimate of $6.64 indicates a change of +10.8% from what Apple is expected to report a year ago. Over the past month, the estimate has changed -0.1%. Having a strong externally audited track record, our proprietary stock rating tool, the Zacks Rank, offers a more conclusive picture of a stock's price direction in the near term, since it effectively harnesses the power of earnings estimate revisions. Due to the size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, Apple is rated Zacks Rank #3 (Hold). The chart below shows the evolution of the company's forward 12-month consensus EPS estimate: 12 Month EPS Projected Revenue Growth While earnings growth is arguably the most superior indicator of a company's financial health, nothing happens as such if a business isn't able to grow its revenues. After all, it's nearly impossible for a company to increase its earnings for an extended period witho\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.039253, "explanation": "The actual 21-day forward return for VTI starting 2023-06-27 was +3.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.039253, "horizon_days": 21, "hist_return": 0.069316, "annualized_vol": 0.121931, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240819_0155", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-08-19", "context_summary": "ETH-USD over past 60 days: cumulative return -25.6%, annualized vol 58.7%. Market regime: bull.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3511.09, end=2613.36, cumulative_return=-25.6%, annualized_volatility=58.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.17, 't10y3m_spread': -1.44, 'breakeven_10y': 2.08, 'hy_oas': 3.29, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.49, 'vix': 14.800000190734863}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.105723, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-08-19 was -10.57%, which classifies as 'negative'.", "metadata": {"future_return": -0.105723, "horizon_days": 21, "hist_return": -0.255684, "annualized_vol": 0.586536, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230102_0157", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-01-02", "context_summary": "AVAX-USD over past 60 days: cumulative return -39.8%, annualized vol 80.5%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=18.05, end=10.87, cumulative_return=-39.8%, annualized_volatility=80.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.53, 't10y3m_spread': -0.54, 'breakeven_10y': 2.3, 'hy_oas': 4.81, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 21.670000076293945}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-01] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.614417, "explanation": "The actual 21-day forward return for AVAX-USD starting 2023-01-02 was +61.44%, which classifies as 'positive'.", "metadata": {"future_return": 0.614417, "horizon_days": 21, "hist_return": -0.397932, "annualized_vol": 0.804991, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240702_0160", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2024-07-02", "context_summary": "EWJ over past 60 days: cumulative return -2.3%, annualized vol 14.7%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=65.30, end=63.82, cumulative_return=-2.3%, annualized_volatility=14.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.29, 't10y3m_spread': -0.99, 'breakeven_10y': 2.32, 'hy_oas': 3.21, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 12.220000267028809}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.019024, "explanation": "The actual 21-day forward return for EWJ starting 2024-07-02 was -1.90%, which classifies as 'negative'.", "metadata": {"future_return": -0.019024, "horizon_days": 21, "hist_return": -0.022595, "annualized_vol": 0.146838, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240814_0163", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-08-14", "context_summary": "AVAX-USD over past 60 days: cumulative return -28.6%, annualized vol 77.6%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=29.99, end=21.40, cumulative_return=-28.6%, annualized_volatility=77.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.08, 't10y3m_spread': -1.47, 'breakeven_10y': 2.09, 'hy_oas': 3.54, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.47, 'vix': 18.1200008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.044199, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-08-14 was +4.42%, which classifies as 'positive'.", "metadata": {"future_return": 0.044199, "horizon_days": 21, "hist_return": -0.286235, "annualized_vol": 0.77637, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231121_0166", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-11-21", "context_summary": "CSHI over past 60 days: cumulative return +1.1%, annualized vol 0.8%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=43.37, end=43.84, cumulative_return=+1.1%, annualized_volatility=0.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.47, 't10y3m_spread': -1.12, 'breakeven_10y': 2.3, 'hy_oas': 3.92, 'ig_oas': 1.18, 'ted_spread': 0.09, 'mortgage_30y': 7.44, 'vix': 13.40999984741211}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.001481, "explanation": "The actual 21-day forward return for CSHI starting 2023-11-21 was +0.15%, which classifies as 'flat'.", "metadata": {"future_return": 0.001481, "horizon_days": 21, "hist_return": 0.010763, "annualized_vol": 0.007781, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230110_0168", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2023-01-10", "context_summary": "SGOV over past 60 days: cumulative return +0.6%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=85.80, end=86.32, cumulative_return=+0.6%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.66, 't10y3m_spread': -1.17, 'breakeven_10y': 2.22, 'hy_oas': 4.37, 'ig_oas': 1.37, 'ted_spread': 0.09, 'mortgage_30y': 6.48, 'vix': 21.96999931335449}\nMarket regime: sideways\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002495, "explanation": "The actual 21-day forward return for SGOV starting 2023-01-10 was +0.25%, which classifies as 'flat'.", "metadata": {"future_return": 0.002495, "horizon_days": 21, "hist_return": 0.006008, "annualized_vol": 0.00249, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240510_0170", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-05-10", "context_summary": "XRP-USD over past 60 days: cumulative return -27.4%, annualized vol 68.0%. Market regime: bull.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.72, end=0.52, cumulative_return=-27.4%, annualized_volatility=68.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.35, 't10y3m_spread': -1.01, 'breakeven_10y': 2.32, 'hy_oas': 3.14, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 12.6899995803833}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.03078, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-05-10 was +3.08%, which classifies as 'positive'.", "metadata": {"future_return": 0.03078, "horizon_days": 21, "hist_return": -0.274369, "annualized_vol": 0.680247, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230227_0173", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-02-27", "context_summary": "BNB-USD over past 60 days: cumulative return +25.4%, annualized vol 39.2%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=246.48, end=309.00, cumulative_return=+25.4%, annualized_volatility=39.2%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.83, 't10y3m_spread': -0.91, 'breakeven_10y': 2.38, 'hy_oas': 4.28, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 21.670000076293945}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-26] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.092067, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-02-27 was +9.21%, which classifies as 'positive'.", "metadata": {"future_return": 0.092067, "horizon_days": 21, "hist_return": 0.253641, "annualized_vol": 0.392467, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240104_0176", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2024-01-04", "context_summary": "UNG over past 60 days: cumulative return -31.1%, annualized vol 47.1%. Market regime: sideways.", "question": "Asset: UNG\nHistorical prices (past 60 trading days): start=31.60, end=21.76, cumulative_return=-31.1%, annualized_volatility=47.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.42, 't10y3m_spread': -1.57, 'breakeven_10y': 2.2, 'hy_oas': 3.71, 'ig_oas': 1.09, 'ted_spread': 0.09, 'mortgage_30y': 6.61, 'vix': 14.039999961853027}\nMarket regime: sideways\n\nPredict whether the return of UNG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.161178, "explanation": "The actual 21-day forward return for UNG starting 2024-01-04 was -16.12%, which classifies as 'negative'.", "metadata": {"future_return": -0.161178, "horizon_days": 21, "hist_return": -0.311392, "annualized_vol": 0.471249, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230807_0179", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-08-07", "context_summary": "BTC-USD over past 60 days: cumulative return +9.6%, annualized vol 26.9%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=26508.22, end=29041.86, cumulative_return=+9.6%, annualized_volatility=26.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.73, 't10y3m_spread': -1.49, 'breakeven_10y': 2.38, 'hy_oas': 4.01, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 17.100000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-06] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.105359, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-08-07 was -10.54%, which classifies as 'negative'.", "metadata": {"future_return": -0.105359, "horizon_days": 21, "hist_return": 0.095579, "annualized_vol": 0.268523, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240325_0181", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["INDS"], "decision_date": "2024-03-25", "context_summary": "INDS over past 60 days: cumulative return -6.5%, annualized vol 15.7%. Market regime: bull.", "question": "Asset: INDS\nHistorical prices (past 60 trading days): start=39.16, end=36.62, cumulative_return=-6.5%, annualized_volatility=15.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.37, 't10y3m_spread': -1.24, 'breakeven_10y': 2.35, 'hy_oas': 3.08, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 13.0600004196167}\nMarket regime: bull\n\nPredict whether the return of INDS over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.079308, "explanation": "The actual 21-day forward return for INDS starting 2024-03-25 was -7.93%, which classifies as 'negative'.", "metadata": {"future_return": -0.079308, "horizon_days": 21, "hist_return": -0.06477, "annualized_vol": 0.156514, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240101_0183", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2024-01-01", "context_summary": "XLY over past 60 days: cumulative return +12.3%, annualized vol 18.1%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=78.11, end=87.73, cumulative_return=+12.3%, annualized_volatility=18.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.35, 't10y3m_spread': -1.52, 'breakeven_10y': 2.16, 'hy_oas': 3.39, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.61, 'vix': 12.449999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-29] [\"2 Overheated Stocks That Could Tumble in 2024 No one can predict what the stock market, or any individual stock, will do in 2024. The stock market surged in 2023, which was probably not on many investors' bingo cards in January. But one thing investors can do is avoid investments where the odds are stacked against them. Paying too high a price for even the best company can lead to subpar results. Two stocks that look far too expensive going into 2024 are Nvidia (NASDAQ: NVDA) and Apple (NASDAQ: AAPL). Nvidia Nvidia is the leader of artificial intelligence. The company's data center GPUs are selling faster than they can be made. Training advanced large language models, like those that power ChatGPT, requires incredible computational horsepower. Nvidia's proprietary CUDA compute platform has been around since 2007, pairing with its world-class hardware to create a competitive advantage that has been difficult for anyone to overcome so far. While Nvidia may appear untouchable, its days of absolute dominance won't last. If estimates for how big the AI accelerator market will become are close to accurate, there will be mammoth incentives for the tech industry to ensure that there are options beyond Nvidia. AMD expects the market for AI chips to grow nearly tenfold by 2027 to $400 billion. Nvidia's market share is almost certain to shrink as alternatives balloon, and as buyers of AI accelerators optimize for total cost of ownership. Nvidia's growth has been incredible in 2023, and its profits have soared even faster than revenue. The company's profit margins are the highest they've ever been. But the shortage of AI chips won't last forever as competitors race to bring alternatives to market, and neither will the gold rush mentality surrounding AI. Nvidia's software advantage will be chipped away, although that process may take a while. Nvidia is valued at around $1.22 trillion. That's about 40 times the average analyst estimate for earnings. That valuation doesn't seem unreasonable at first glance, but you must be willing to assume that Nvidia's incredible profit margins and growth rate will persist. What if they don't? What if the companies spending big to train large language models find that turning those models into sustainable businesses is tougher than expected? What if competing chips from AMD, Intel, and others provide viable alternatives to Nvidia's pricey products? Taking current growth rates and extrapolating out years is a dangerous thing to do, especially in a very new market. ChatGPT, which kicked off the AI frenzy, has only existed for about a year. If there's any sign that Nvidia is running into trouble in 2024, the stock has a long way to fall. Apple What's Apple's growth story? After a big surge during the pandemic's height, revenue has essentially stagnated in the post-pandemic period. Revenue slipped 1% year over year in the fiscal fourth quarter, which ended on Sept. 30, and an import ban on the Apple Watch isn't going to help ma\n\nPredict whether the return of XLY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.016596, "explanation": "The actual 21-day forward return for XLY starting 2024-01-01 was -1.66%, which classifies as 'negative'.", "metadata": {"future_return": -0.016596, "horizon_days": 21, "hist_return": 0.123142, "annualized_vol": 0.181452, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230811_0186", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-08-11", "context_summary": "XLE over past 60 days: cumulative return +16.0%, annualized vol 19.9%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=34.91, end=40.50, cumulative_return=+16.0%, annualized_volatility=19.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.73, 't10y3m_spread': -1.45, 'breakeven_10y': 2.33, 'hy_oas': 3.83, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 15.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-10] [\"Invest Like Warren Buffett with These Stocks & ETFs (1:30) - How Did Warren Buffett Get Started In Investing? (7:10) - How Has Berkshire Hathaway\\u2019s Investing Changed Over The Years? (12:20) - Breaking Down Warren Buffett\\u2019s Current Portfolio Holdings (19:30) - Creating Your Own Mini Berkshire Hathaway Portfolio: What Stocks Should You Consider? (23:40) - First Trust RBA American Industrial Renaissance ETF: AIRR (28:50) - Episode Roundup: FAST,MTZ, URI, MOAT, VOO, IVV, SPLG, QUS Podcast@Zacks.com In this episode of ETF Spotlight, I speak with Tracey Ryniec, Zacks Senior Equity Strategist, about investing like Warren Buffett, one of the greatest and most respected investors of all time. Berkshire Hathaway (BRK.A) reported excellent earnings last week, sending its class A shares to an all-time high. The stock is up more than 25,000 times since Buffett took control of the company in 1965, according to Barron's. Most investors would like to emulate Buffett's investing style in their portfolios, which is not easy, but we can certainly learn from his strategies. In the past, Buffett invested in undervalued companies with great potential, which he called \\\"cigar butts.\\\" However, his thinking later evolved to \\\"it's far better to buy a wonderful company at a fair price than a fair company at a wonderful price.\\\" The Oracle of Omaha avoided investing in tech companies earlier in his career but changed his stance later. Apple AAPL, which is now Berkshire's largest stock investment, was praised by Buffett as \\\"a better business than any we own.\\\" The SPDR MSCI USA StrategicFactors ETF QUS seeks to invest in high-quality firms with durable balance sheets and stable cash flows, trading at reasonable valuations. The legendary investor likes companies with \\\"economic moats,\\\" that allow a company to outperform others in the same industry over time. The VanEck Morningstar Wide Moat ETF MOAT invests in attractively priced companies with sustainable competitive advantages. Buffett has long recommended that most investors should stick with low-cost index funds. The iShares Core S&P 500 ETF IVV and Vanguard S&P 500 ETF VOO charge just 0.03% each, but SPDR Portfolio S&P 500 ETF SPLG's new fee of 0.02% makes it the cheapest in the space. Fastenal FAST, MasTec MTZ and United Rentals URI are among Berkshire-like companies that investors may want to consider. Tune in to the podcast to learn more. Make sure to be on the lookout for the next edition of the ETF Spotlight and remember to subscribe! If you have any comments or questions, please email podcast@zacks.com. Want key ETF info delivered straight to your inbox? Zacks\\u2019 free Fund Newsletter will brief you on top news and analysis, as well as top-performing ETFs, each week. Get it free >> Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Apple Inc. (AAPL) : Free Stock Analysis Report Fastenal Company (\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.010456, "explanation": "The actual 21-day forward return for XLE starting 2023-08-11 was +1.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.010456, "horizon_days": 21, "hist_return": 0.1603, "annualized_vol": 0.198918, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241211_0188", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-12-11", "context_summary": "XRP-USD over past 60 days: cumulative return +339.1%, annualized vol 113.9%. Market regime: bull.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.54, end=2.37, cumulative_return=+339.1%, annualized_volatility=113.9%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.07, 't10y3m_spread': -0.19, 'breakeven_10y': 2.29, 'hy_oas': 2.67, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 14.18000030517578}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.032386, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-12-11 was -3.24%, which classifies as 'negative'.", "metadata": {"future_return": -0.032386, "horizon_days": 21, "hist_return": 3.390911, "annualized_vol": 1.138923, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240222_0191", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-02-22", "context_summary": "ACWI over past 60 days: cumulative return +8.2%, annualized vol 10.2%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=93.76, end=101.46, cumulative_return=+8.2%, annualized_volatility=10.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.32, 't10y3m_spread': -1.12, 'breakeven_10y': 2.34, 'hy_oas': 3.34, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 15.34000015258789}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K NVDA 2024-02-21] nvda-20240128 0001045810 2024 FY false 350 P3Y P4Y P5Y P1Y P3Y P3Y P1Y http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent 0001045810 2023-01-30 2024-01-28 0001045810 2023-07-28 iso4217:USD 0001045810 2024-02-16 xbrli:shares 0001045810 nvda:JohnO.DabiriMember 2023-10-30 2024-01-28 0001045810 2023-10-30 2024-01-28 0001045810 nvda:JohnO.DabiriMember 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Form 10-K Summary Not Applicable. 83 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on February 21, 2024. NVIDIA Corporation By: /s/ Jen-Hsun Huang    Jen-Hsun Huang   President and Chief Executive Officer Power of Attorney KNOW ALL PERSONS BY THESE PRESENTS, that each person whose signature appears below constitutes and appoints Jen-Hsun Huang and Colette M. Kress, and each or any one of them, his true and lawful attorney-in-fact and agent, with full power of substitution and resubstitution, for him and in his name, place and stead, in any and all capacities, to sign any and all amendments to this report, and to file the same, with all exhibits thereto, and other documents in connection therewith, with the Securities and Exchange Commission, granting unto said attorneys-in-facts and agents, and each of them, full power and authority to do and perform each and every act and thing requisite and necessary to be done in connection therewith, as fully to all intents and purposes as he might or could do in person, hereby ratifying and confirming all that said attorneys-in-fact and agents, or any of them, or their or his substitutes or substitutes, may lawfully do or cause to be done by virtue hereof. 84 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated. Signature Title Date /s/ JEN-HSUN HUANG  President, Chief Executive Officer and Director (Principal Executive Officer) February 21, 2024 Jen-Hsun Huang   /s/ COLETTE M. KRESS  Executive Vice President and Chief Financial Officer (Principal Financial Officer) February 21, 2024 Colette M. Kress   /s/ DONALD ROBERTSON Vice President and Chief Accounting Officer (Principal Accounting Officer) February 21, 2024 Donald Robertson /s/ ROBERT BURGESS Director February 21, 2024 Robert Burgess /s/ TENCH COXE   Director February 21, 2024 Tench Coxe    /s/ JOHN O. DABIRI Director February 21, 2024 John O. Dabiri   /s/ PERSIS DRELL Director February 21, 2024 Persis Drell /s/ DAWN HUDSON Director February 21, 2024 Dawn Hudson /s/ HARVEY C. JONES  Director February 21, 2024 Harvey C. Jones   /s/ MELISSA B. LORA Director February 21, 2024 Melissa B. Lora /s/ MICHAEL MCCAFFERY Director February 21, 2024 Michael McCaffery /s/ STEPHEN C. NEAL Director February 21, 2024 Stephen C. Neal /s/ MARK L. PERRY  Director February 21, 2024 Mark L. Perry    /s/ A. BROOKE SEAWELL Director February 21, 2024 A. Brooke Seawell  /s/ AARTI SHAH Director February 21, 2024 Aarti Shah /s/ MARK STEVENS Director February 21, 2024 Mark Stevens    85\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.028015, "explanation": "The actual 21-day forward return for ACWI starting 2024-02-22 was +2.80%, which classifies as 'positive'.", "metadata": {"future_return": 0.028015, "horizon_days": 21, "hist_return": 0.082116, "annualized_vol": 0.10153, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240425_0194", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-04-25", "context_summary": "QQQ over past 60 days: cumulative return +0.4%, annualized vol 16.8%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=420.12, end=421.88, cumulative_return=+0.4%, annualized_volatility=16.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.24, 't10y3m_spread': -0.81, 'breakeven_10y': 2.41, 'hy_oas': 3.19, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 7.1, 'vix': 15.970000267028809}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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0000104169 wmt:SamsClubMember 2023-01-31 0000104169 wmt:WalmartUSMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartInternationalMember 2023-02-01 2024-01-31 0000104169 wmt:SamsClubMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartUSMember 2024-01-31 0000104169 wmt:WalmartInternationalMember 2024-01-31 0000104169 wmt:SamsClubMember 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2023-02-01 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2022-02-01 2023-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.078926, "explanation": "The actual 21-day forward return for QQQ starting 2024-04-25 was +7.89%, which classifies as 'positive'.", "metadata": {"future_return": 0.078926, "horizon_days": 21, "hist_return": 0.004171, "annualized_vol": 0.167999, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240430_0197", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-04-30", "context_summary": "^VIX over past 60 days: cumulative return +5.9%, annualized vol 84.1%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=13.85, end=14.67, cumulative_return=+5.9%, annualized_volatility=84.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.34, 't10y3m_spread': -0.82, 'breakeven_10y': 2.41, 'hy_oas': 3.12, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 7.17, 'vix': 14.670000076293944}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.075399, "explanation": "The actual 21-day forward return for ^VIX starting 2024-04-30 was -7.54%, which classifies as 'negative'.", "metadata": {"future_return": -0.075399, "horizon_days": 21, "hist_return": 0.059206, "annualized_vol": 0.840865, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230915_0199", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-09-15", "context_summary": "SOL-USD over past 60 days: cumulative return -29.9%, annualized vol 49.5%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=26.87, end=18.84, cumulative_return=-29.9%, annualized_volatility=49.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.71, 't10y3m_spread': -1.26, 'breakeven_10y': 2.34, 'hy_oas': 3.78, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 12.81999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-14] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.222007, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-09-15 was +22.20%, which classifies as 'positive'.", "metadata": {"future_return": 0.222007, "horizon_days": 21, "hist_return": -0.298982, "annualized_vol": 0.495088, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230912_0202", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-09-12", "context_summary": "EEM over past 60 days: cumulative return -4.5%, annualized vol 16.3%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=38.39, end=36.68, cumulative_return=-4.5%, annualized_volatility=16.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.68, 't10y3m_spread': -1.26, 'breakeven_10y': 2.35, 'hy_oas': 3.82, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.12, 'vix': 13.800000190734863}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-11] [\"Notable Monday Option Activity: AAPL, GS, SJM Among the underlying components of the S&P 500 index, we saw noteworthy options trading volume today in Apple Inc (Symbol: AAPL), where a total of 604,734 contracts have traded so far, representing approximately 60.5 million underlying shares. That amounts to about 107% of AAPL's average daily trading volume over the past month of 56.5 million shares. Particularly high volume was seen for the $180 strike call option expiring September 15, 2023, with 83,977 contracts trading so far today, representing approximately 8.4 million underlying shares of AAPL. Below is a chart showing AAPL's trailing twelve month trading history, with the $180 strike highlighted in orange: Goldman Sachs Group Inc (Symbol: GS) options are showing a volume of 15,558 contracts thus far today. That number of contracts represents approximately 1.6 million underlying shares, working out to a sizeable 90.5% of GS's average daily trading volume over the past month, of 1.7 million shares. Particularly high volume was seen for the $400 strike put option expiring January 19, 2024, with 1,280 contracts trading so far today, representing approximately 128,000 underlying shares of GS. Below is a chart showing GS's trailing twelve month trading history, with the $400 strike highlighted in orange: And J.M. Smucker Co. (Symbol: SJM) options are showing a volume of 7,373 contracts thus far today. That number of contracts represents approximately 737,300 underlying shares, working out to a sizeable 73% of SJM's average daily trading volume over the past month, of 1.0 million shares. Particularly high volume was seen for the $140 strike call option expiring October 20, 2023, with 1,210 contracts trading so far today, representing approximately 121,000 underlying shares of SJM. Below is a chart showing SJM's trailing twelve month trading history, with the $140 strike highlighted in orange: For the various different available expirations for AAPL options, GS options, or SJM options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb Also see: \\u0095 Dow Average Annual Return \\u0095 ZLS shares outstanding history \\u0095 Funds Holding USMR The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The 3 Most Undervalued AI Chip Stocks to Buy in September 2023 InvestorPlace - Stock Market News, Stock Advice & Trading Tips Artificial intelligence has been around for a while, but tools like ChatGPT have brought this innovative technology into the spotlight. A growing number of companies want to create their own AI-powered tools. When many companies and consumers rush toward a technological innovation, it presents an opportunity for investors. Some publicly-traded companies stand to immensely benefit from the surge of artificial intelligence tools. Other have plenty of runway to generate robust gains for investors. With that said, art\n\nPredict whether the return of EEM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.016381, "explanation": "The actual 21-day forward return for EEM starting 2023-09-12 was -1.64%, which classifies as 'negative'.", "metadata": {"future_return": -0.016381, "horizon_days": 21, "hist_return": -0.044612, "annualized_vol": 0.163211, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240827_0204", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VTI"], "decision_date": "2024-08-27", "context_summary": "VTI over past 60 days: cumulative return +6.7%, annualized vol 14.9%. Market regime: bull.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=253.99, end=270.99, cumulative_return=+6.7%, annualized_volatility=14.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.09, 't10y3m_spread': -1.42, 'breakeven_10y': 2.15, 'hy_oas': 3.15, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.46, 'vix': 16.149999618530273}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 us-gaap:ProductMember 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us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.021866, "explanation": "The actual 21-day forward return for VTI starting 2024-08-27 was +2.19%, which classifies as 'positive'.", "metadata": {"future_return": 0.021866, "horizon_days": 21, "hist_return": 0.066933, "annualized_vol": 0.148943, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20241010_0206", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-10-10", "context_summary": "MATIC-USD over past 60 days: cumulative return -8.2%, annualized vol 57.9%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.40, end=0.37, cumulative_return=-8.2%, annualized_volatility=57.9%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.07, 't10y3m_spread': -0.69, 'breakeven_10y': 2.29, 'hy_oas': 2.94, 'ig_oas': 0.85, 'ted_spread': 0.09, 'mortgage_30y': 6.12, 'vix': 20.86000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.135374, "explanation": "The actual 21-day forward return for MATIC-USD starting 2024-10-10 was -13.54%, which classifies as 'negative'.", "metadata": {"future_return": -0.135374, "horizon_days": 21, "hist_return": -0.081675, "annualized_vol": 0.578785, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241209_0209", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-12-09", "context_summary": "ACWI over past 60 days: cumulative return +5.9%, annualized vol 9.4%. Market regime: bull.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=113.32, end=120.06, cumulative_return=+5.9%, annualized_volatility=9.4%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.05, 't10y3m_spread': -0.27, 'breakeven_10y': 2.24, 'hy_oas': 2.67, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 12.770000457763672}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.02948, "explanation": "The actual 21-day forward return for ACWI starting 2024-12-09 was -2.95%, which classifies as 'negative'.", "metadata": {"future_return": -0.02948, "horizon_days": 21, "hist_return": 0.059461, "annualized_vol": 0.094447, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240920_0212", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2024-09-20", "context_summary": "VNQ over past 60 days: cumulative return +19.3%, annualized vol 14.1%. Market regime: sideways.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=76.95, end=91.80, cumulative_return=+19.3%, annualized_volatility=14.1%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.14, 't10y3m_spread': -1.07, 'breakeven_10y': 2.17, 'hy_oas': 3.1, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.09, 'vix': 16.329999923706055}\nMarket regime: sideways\n\nPredict whether the return of VNQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.014162, "explanation": "The actual 21-day forward return for VNQ starting 2024-09-20 was -1.42%, which classifies as 'negative'.", "metadata": {"future_return": -0.014162, "horizon_days": 21, "hist_return": 0.192997, "annualized_vol": 0.140949, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230120_0215", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLT"], "decision_date": "2023-01-20", "context_summary": "TLT over past 60 days: cumulative return +11.6%, annualized vol 20.6%. Market regime: sideways.", "question": "Asset: TLT\nHistorical prices (past 60 trading days): start=85.05, end=94.88, cumulative_return=+11.6%, annualized_volatility=20.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.7, 't10y3m_spread': -1.32, 'breakeven_10y': 2.2, 'hy_oas': 4.39, 'ig_oas': 1.3, 'ted_spread': 0.09, 'mortgage_30y': 6.15, 'vix': 20.520000457763672}\nMarket regime: sideways\n\nPredict whether the return of TLT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.03349, "explanation": "The actual 21-day forward return for TLT starting 2023-01-20 was -3.35%, which classifies as 'negative'.", "metadata": {"future_return": -0.03349, "horizon_days": 21, "hist_return": 0.115582, "annualized_vol": 0.205859, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231019_0217", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2023-10-19", "context_summary": "VNQI over past 60 days: cumulative return -10.9%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: VNQI\nHistorical prices (past 60 trading days): start=36.96, end=32.95, cumulative_return=-10.9%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.28, 't10y3m_spread': -0.7, 'breakeven_10y': 2.44, 'hy_oas': 4.32, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 19.21999931335449}\nMarket regime: sideways\n\nPredict whether the return of VNQI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.091275, "explanation": "The actual 21-day forward return for VNQI starting 2023-10-19 was +9.13%, which classifies as 'positive'.", "metadata": {"future_return": 0.091275, "horizon_days": 21, "hist_return": -0.10867, "annualized_vol": 0.135022, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230414_0220", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2023-04-14", "context_summary": "IYR over past 60 days: cumulative return -4.4%, annualized vol 21.1%. Market regime: sideways.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=81.81, end=78.17, cumulative_return=-4.4%, annualized_volatility=21.1%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.51, 't10y3m_spread': -1.65, 'breakeven_10y': 2.29, 'hy_oas': 4.49, 'ig_oas': 1.42, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 17.799999237060547}\nMarket regime: sideways\n\nPredict whether the return of IYR over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.011678, "explanation": "The actual 21-day forward return for IYR starting 2023-04-14 was +1.17%, which classifies as 'positive'.", "metadata": {"future_return": 0.011678, "horizon_days": 21, "hist_return": -0.044449, "annualized_vol": 0.210601, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230106_0223", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-01-06", "context_summary": "IWM over past 60 days: cumulative return +4.0%, annualized vol 24.7%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=160.49, end=166.96, cumulative_return=+4.0%, annualized_volatility=24.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.74, 't10y3m_spread': -0.95, 'breakeven_10y': 2.22, 'hy_oas': 4.58, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.48, 'vix': 22.459999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-05] [\"POLL-Taiwan exports seen declining for fourth straight month in December For poll data click: reuters://realtime/verb=Open/url=cpurl://apps.cp./Apps/econ-polls?RIC=TWCPIY%3DECI Exports median forecast -13.3% y/y (prior month -13.1%) Imports median forecast -10.2% y/y (prior month -8.6%) Balance median forecast $3.45 bln (prior month $3.43 bln) CPI median forecast +2.5% y/y (prior month +2.35%) Trade due Saturday, Jan. 7, 4:00 p.m. (0800 GMT) CPI due Friday, Jan. 6, 4:00 p.m. (0800 GMT) TAIPEI, Jan 5 (Reuters) - Taiwan's exports in December likely dropped from a year earlier for the fourth month in a row amid fears of a global recession, uncertainties due to the war in Ukraine, and COVID-19 controls in China, according to a Reuters poll. Taiwan, a global hub for chip production and a key supplier to Apple Inc AAPL.O, is one of Asia's leading exporters of technology goods. The trade data is seen as an important gauge of world demand for tech gadgets. Exports last month were estimated to have dropped 13.3% from a year earlier, a Reuters poll of 12 analysts showed on Thursday, slightly faster than the 13.1% annual contraction seen in November. The export forecasts varied widely, projecting a contraction of between 7.9% and 19.5%. The variation reflected uncertainties over the global economy, supply chain disruptions due to pandemic lockdowns in China, and the fallout of Russia and Ukraine war. Taiwan's finance ministry said last month December exports could be down by 8% to 12% from a year earlier. Separately, the consumer price index was expected to have been 2.5% higher in December than a year earlier, rising faster than the 2.35% annual rate seen in November, according to the poll. The inflation data will be released on Friday followed by the trade data on Saturday. (Reporting By Yimou Lee; Polling by Anant Chandak; Editing by Bradley Perrett) ((yimou.lee@thomsonreuters.com; +886-2-8729-5122;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Qualcomm, Iridium partner to bring satellite-based messaging to Android phones Jan 5 (Reuters) - Qualcomm Inc QCOM.O has partnered with Iridium Communications Inc IRDM.O to provide a satellite-based messaging service on premium smartphones running Google's Android operating system, the chipmaker said on Thursday. The partnership comes months after Apple Inc AAPL.O unveiled a similar feature allowing iPhone 14 models to send emergency messages via satellite in some countries such as the United States and Canada. Those phones also contain a Qualcomm chip that can talk to satellites when there is no Wi-Fi or cellular data connection. Qualcomm said on Thursday the new service, Snapdragon Satellite, will be available in certain regions from the second half of 2023 starting devices using the second generation Snapdragon 8 mobile platform. Snapdragon Satellite can also be enabled on other devices including laptops, vehicles and\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.093254, "explanation": "The actual 21-day forward return for IWM starting 2023-01-06 was +9.33%, which classifies as 'positive'.", "metadata": {"future_return": 0.093254, "horizon_days": 21, "hist_return": 0.040314, "annualized_vol": 0.247436, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241224_0225", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-12-24", "context_summary": "AVAX-USD over past 60 days: cumulative return +56.8%, annualized vol 98.6%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=24.89, end=39.03, cumulative_return=+56.8%, annualized_volatility=98.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.29, 't10y3m_spread': 0.23, 'breakeven_10y': 2.32, 'hy_oas': 2.85, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 16.780000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.114291, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-12-24 was -11.43%, which classifies as 'negative'.", "metadata": {"future_return": -0.114291, "horizon_days": 21, "hist_return": 0.567851, "annualized_vol": 0.985692, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240614_0228", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-06-14", "context_summary": "^VIX over past 60 days: cumulative return -8.4%, annualized vol 85.2%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=13.04, end=11.94, cumulative_return=-8.4%, annualized_volatility=85.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.44, 't10y3m_spread': -1.27, 'breakeven_10y': 2.21, 'hy_oas': 3.2, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 11.9399995803833}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.036335, "explanation": "The actual 21-day forward return for ^VIX starting 2024-06-14 was +3.63%, which classifies as 'positive'.", "metadata": {"future_return": 0.036335, "horizon_days": 21, "hist_return": -0.084356, "annualized_vol": 0.852284, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240725_0231", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-07-25", "context_summary": "XLF over past 60 days: cumulative return +4.9%, annualized vol 11.7%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=39.52, end=41.45, cumulative_return=+4.9%, annualized_volatility=11.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.09, 't10y3m_spread': -1.12, 'breakeven_10y': 2.28, 'hy_oas': 3.1, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 18.040000915527344}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q GOOGL 2024-07-24] goog-20240630 FALSE 2024 Q2 0001652044 --12-31 50 50 http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 467 1004 360 461 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:EUR 0001652044 2024-01-01 2024-06-30 0001652044 us-gaap:CommonClassAMember 2024-01-01 2024-06-30 0001652044 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Compensatory Arrangements of Certain Officers On April 16, 2024, the Leadership Development, Inclusion and Compensation Committee of the Board of Directors of Alphabet approved the accrual of dividend equivalent units to holders of all unvested stock units, subject to the approval of a dividend declaration by the Board of Directors of the company (which was announced on July 23, 2024). As stock units are not outstanding shares of stock and thus would not otherwise be entitled to participate in any dividends (including the one referenced above), the crediting of dividend equivalent units is intended to preserve the equity-based incentives intended by the company when the stock units were granted and to treat the holders of stock units consistently with all stockholders. 50 ITEM 6. EXHIBITS Exhibit Number    Description Incorporated by reference herein Form Date 10.01 ♦ Letter Agreement, dated June 3, 2024, between Anat Ashkenazi and Alphabet Inc. Current Report on Form 8-K (File No. 001-37580 June 7, 2024 31.01 * Certification of Chief Executive Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.02 * Certification of Chief Financial Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.01 ‡ Certifications of Chief Executive Officer and Chief Financial Officer pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS * Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH * Inline XBRL Taxonomy Extension Schema Document 101.CAL * Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF * Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB * Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE * Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 * Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) __________________________  ♦ Indicates management compensatory plan, contract, or arrangement. * Filed herewith. ‡ Furnished herewith. 51 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. ALPHABET INC. July 23, 2024 By: /s/    RUTH M. PORAT         Ruth M. Porat President and Chief Investment Officer; Chief Financial Officer ALPHABET INC. July 23, 2024 By: /s/    AMIE THUENER O'TOOLE         Amie Thuener O'Toole Vice President, Corporate Controller and Principal Accounting Officer 52\n\nPredict whether the return of XLF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.039541, "explanation": "The actual 21-day forward return for XLF starting 2024-07-25 was +3.95%, which classifies as 'positive'.", "metadata": {"future_return": 0.039541, "horizon_days": 21, "hist_return": 0.048788, "annualized_vol": 0.116918, "has_text": true, "text_chars": 9047}} +{"id": "T1_all_20240212_0234", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-02-12", "context_summary": "SOL-USD over past 60 days: cumulative return +42.2%, annualized vol 81.5%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=75.62, end=107.50, cumulative_return=+42.2%, annualized_volatility=81.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.31, 't10y3m_spread': -1.27, 'breakeven_10y': 2.25, 'hy_oas': 3.33, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 12.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.189314, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-02-12 was +18.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.189314, "horizon_days": 21, "hist_return": 0.421513, "annualized_vol": 0.815309, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241021_0237", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-10-21", "context_summary": "XLB over past 60 days: cumulative return +4.2%, annualized vol 14.7%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=44.15, end=45.99, cumulative_return=+4.2%, annualized_volatility=14.7%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.13, 't10y3m_spread': -0.65, 'breakeven_10y': 2.31, 'hy_oas': 2.88, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.44, 'vix': 18.030000686645508}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PG 2024-10-18] pg-20240930 0000080424 6/30 2025 Q1 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares pg:segment xbrli:pure pg:country pg:taxable_jurisdiction pg:audit 0000080424 2024-07-01 2024-09-30 0000080424 us-gaap:CommonStockMember 2024-07-01 2024-09-30 0000080424 pg:A0.500NotesDue2024Member 2024-07-01 2024-09-30 0000080424 pg:A0.625NotesDue2024Member 2024-07-01 2024-09-30 0000080424 pg:A1.375NotesDue2025Member 2024-07-01 2024-09-30 0000080424 pg:A0.110NotesDue2026Member 2024-07-01 2024-09-30 0000080424 pg:A3.250EURNotesDue2026Member 2024-07-01 2024-09-30 0000080424 pg:A4.875EURNotesDueMay2027Member 2024-07-01 2024-09-30 0000080424 pg:A1.200NotesDue2028Member 2024-07-01 2024-09-30 0000080424 pg:A3.150EURONotesDue2028Member 2024-07-01 2024-09-30 0000080424 pg:A1.250NotesDue2029Member 2024-07-01 2024-09-30 0000080424 pg:A1.800NotesDue2029Member 2024-07-01 2024-09-30 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pg:FabricHomeCareSegmentMember pg:HomeCareMember 2024-07-01 2024-09-30 0000080424 us-gaap:ProductConcentrationRiskMember us-gaap:SalesRevenueNetMember pg:FabricHomeCareSegmentMember pg:HomeCareMember 2023-07-01 2023-09-30 0000080424 us-gaap:ProductConcentrationRiskMember us-gaap:SalesRevenueNetMember pg:BabyFeminineFamilyCareSegmentMember pg:BabyCareMember 2024-07-01 2024-09-30 0000080424 us-gaap:ProductConcentrationRiskMember us-gaap:SalesRevenueNetMember pg:BabyFeminineFamilyCareSegmentMember pg:BabyCareMember 2023-07-01 2023-09-30 0000080424 us-gaap:ProductConcentrationRiskMember us-gaap:SalesRevenueNetMembe [...TRUNCATED...] tion and benefit plans. Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended September 30, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. The Procter & Gamble Company 25 Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 10.1 Company's Form of Separation Agreement & Release *+ 10.2 The Procter & Gamble Performance Stock Program Summary *+ 10.3 Performance Stock Program related correspondence and terms and conditions *+ 10.4 Long-Term Incentive Program related correspondence and terms and conditions *+ 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) * Compensatory plan or arrangement + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY October 18, 2024 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.031989, "explanation": "The actual 21-day forward return for XLB starting 2024-10-21 was -3.20%, which classifies as 'negative'.", "metadata": {"future_return": -0.031989, "horizon_days": 21, "hist_return": 0.041747, "annualized_vol": 0.147032, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20230425_0240", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-04-25", "context_summary": "ADA-USD over past 60 days: cumulative return +4.9%, annualized vol 56.6%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.37, end=0.38, cumulative_return=+4.9%, annualized_volatility=56.6%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.6, 't10y3m_spread': -1.68, 'breakeven_10y': 2.28, 'hy_oas': 4.48, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 16.889999389648438}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-24] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.068594, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-04-25 was -6.86%, which classifies as 'negative'.", "metadata": {"future_return": -0.068594, "horizon_days": 21, "hist_return": 0.04947, "annualized_vol": 0.566301, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240111_0242", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-01-11", "context_summary": "EFA over past 60 days: cumulative return +9.8%, annualized vol 12.8%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=63.73, end=70.00, cumulative_return=+9.8%, annualized_volatility=12.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.33, 't10y3m_spread': -1.42, 'breakeven_10y': 2.22, 'hy_oas': 3.5, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 12.6899995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.007223, "explanation": "The actual 21-day forward return for EFA starting 2024-01-11 was +0.72%, which classifies as 'flat'.", "metadata": {"future_return": 0.007223, "horizon_days": 21, "hist_return": 0.09833, "annualized_vol": 0.127567, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230711_0244", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-07-11", "context_summary": "IVV over past 60 days: cumulative return +6.8%, annualized vol 12.0%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=398.71, end=425.67, cumulative_return=+6.8%, annualized_volatility=12.0%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.84, 't10y3m_spread': -1.47, 'breakeven_10y': 2.25, 'hy_oas': 4.13, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 15.06999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-10] [\"EU seals new US data transfer pact but challenge ahead By Foo Yun Chee BRUSSELS, July 10 (Reuters) - The European Commission announced a new data transfer pact with the United States on Monday, seeking to end the legal uncertainty plaguing thousands of companies which transfer personal data across the Atlantic. However, the move was immediately criticised by non-profit group noyb, led by privacy activist Max Schrems, which said it would challenge the agreement. The Commission and the United States had been struggling to reach a new agreement after Europe's top court annulled two previous pacts that underpinned the transfer of personal data across the Atlantic for services ranging from cloud infrastructure to payroll and banking. The EU executive said measures taken by the United States ensured an adequate level of protection for Europeans' personal data transferred across the Atlantic for commercial use. It said new binding safeguards, such as that limiting U.S. intelligence services' access to EU data to what is \\\"necessary and proportionate\\\" and the setting up of a Data Protection Review Court for Europeans, address the concerns raised by Europe's top court. EU justice chief Didier Reynders said he was confident of fending off any legal challenge. \\\"The principles of the data privacy framework are solid and I am convinced that we have made significant progress which meets the requirements of the European Court of Justice case law,\\\" he told a news conference. \\\"I am very confident of fighting, defending the new data agreement.\\\" Schrems said the latest revision was inadequate. \\\"Just announcing that something is 'new', 'robust' or 'effective' does not cut it before the Court of Justice. We would need changes in U.S. surveillance law to make this work,\\\" he said in a statement. \\\"We have various options for a challenge already in the drawer, although we are sick and tired of this legal ping-pong. We currently expect this to be back at the Court of Justice by the beginning of next year,\\\" Schrems added. Lobbying group DigitalEurope, whose members include Airbus AIR.PA, Amazon AMZN.O, Apple AAPL.O, Ericsson ERICb.ST, Nokia NOKIA.HE, Philips PHG.AS and Samsung 005930.KS welcomed the deal. \\\"Data flows underpin the EU's annual 1 trillion euros of service exports to the United States, and this decision will give companies more confidence to conduct business and help our economies to grow,\\\" its Director-General Cecilia Bonefeld-Dahl said. Earlier this year, EU privacy watchdog the European Data Protection Board said the latest data agreement still fell short and urged the Commission to do more to protect Europeans' privacy rights. Europe's top court scuppered the previous two deals after challenges by Schrems because of concerns about U.S. intelligence agencies accessing European citizens' private data. (Reporting by Foo Yun Chee; editing by Philip Blenkinsop and Christina Fincher) ((foo.yunchee@thomsonreuters.com; +32 2 585 2866; Reuters Messagin\n\nPredict whether the return of IVV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.007124, "explanation": "The actual 21-day forward return for IVV starting 2023-07-11 was +0.71%, which classifies as 'flat'.", "metadata": {"future_return": 0.007124, "horizon_days": 21, "hist_return": 0.06762, "annualized_vol": 0.119838, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241210_0248", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-12-10", "context_summary": "SOL-USD over past 60 days: cumulative return +41.9%, annualized vol 62.8%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=145.38, end=206.25, cumulative_return=+41.9%, annualized_volatility=62.8%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.07, 't10y3m_spread': -0.22, 'breakeven_10y': 2.27, 'hy_oas': 2.67, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 14.1899995803833}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.082367, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-12-10 was -8.24%, which classifies as 'negative'.", "metadata": {"future_return": -0.082367, "horizon_days": 21, "hist_return": 0.418705, "annualized_vol": 0.627736, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230908_0251", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-09-08", "context_summary": "ICSH over past 60 days: cumulative return +1.0%, annualized vol 0.5%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=43.90, end=44.33, cumulative_return=+1.0%, annualized_volatility=0.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.67, 't10y3m_spread': -1.26, 'breakeven_10y': 2.32, 'hy_oas': 3.9, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.12, 'vix': 14.399999618530272}\nMarket regime: sideways\n\nPredict whether the return of ICSH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002787, "explanation": "The actual 21-day forward return for ICSH starting 2023-09-08 was +0.28%, which classifies as 'flat'.", "metadata": {"future_return": 0.002787, "horizon_days": 21, "hist_return": 0.009859, "annualized_vol": 0.004857, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241118_0253", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-11-18", "context_summary": "XLF over past 60 days: cumulative return +12.7%, annualized vol 14.9%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=43.25, end=48.73, cumulative_return=+12.7%, annualized_volatility=14.9%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.12, 't10y3m_spread': -0.17, 'breakeven_10y': 2.33, 'hy_oas': 2.72, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 16.139999389648438}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2024-11-07] cvx-20240930 0000093410 12/31 2024 Q3 false 102 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:State cvx:tribe cvx:parish 0000093410 2024-01-01 2024-09-30 0000093410 2024-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2023-07-01 2023-09-30 0000093410 2023-01-01 2023-09-30 0000093410 2023-12-31 0000093410 2022-12-31 0000093410 2023-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-06-30 0000093410 us-gaap:RetainedEarningsMember 2023-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2023-06-30 0000093410 us-gaap:ParentMember 2023-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2023-06-30 0000093410 2023-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-07-01 2023-09-30 0000093410 us-gaap:ParentMember 2023-07-01 2023-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2023-07-01 2023-09-30 0000093410 us-gaap:RetainedEarningsMember 2023-07-01 2023-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2023-07-01 2023-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-01 2023-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-09-30 0000093410 us-gaap:RetainedEarningsMember 2023-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2023-09-30 0000093410 us-gaap:ParentMember 2023-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2023-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-06-30 0000093410 us-gaap:ParentMember 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-06-30 0000093410 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-07-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-07-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-07-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-09-30 0000093410 us-gaap:ParentMember 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2022-12-31 0000093410 us-gaap:RetainedEarningsMember 2022-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2022-12-31 0000093410 us-gaap:ParentMember 2022-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2022-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-01-01 2023-09-30 0000093410 us-gaap:ParentMember 2023-01-01 2023-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2023-01-01 2023-09-30 0000093410 us-gaap:RetainedEarningsMember 2023-01-01 2023-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-01 2023-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-12-31 0000093410 us-gaap:RetainedEarningsMember 2023-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2023-12-31 0000093410 us-gaap:ParentMember 2023-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2023-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-01-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-01-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-01 2023-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-01-01 2023-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 000009 [...TRUNCATED...] ATION ISSUER PURCHASES OF EQUITY SECURITIES   Period Total Number of Shares Purchased (*) Average Price Paid per Share Total Number of Shares Purchased as Part of Publicly Announced Program Approximate Dollar Value of Shares that May Yet Be Purchased Under the 2023 Program (*) (Billions of dollars) July 1 - July 31, 2024 7,923,000  $156.56 7,923,000  $56.6 August 1 - August 31, 2024 12,057,000  $146.20 12,057,000  $54.8 September 1 - September 30, 2024 12,229,398  $142.84 12,229,398  $53.1 Total 32,209,398   $147.47 32,209,398   (*) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections A. Nigel Hearne , Executive Vice President, Senior Advisor , entered into a pre-arranged stock trading plan on August 19, 2024 . Mr. Hearne’s plan provides for the potential exercise of vested stock options and the associated sale of up to 60,468 shares of Chevron common stock between November 18, 2024, and February 28, 2025 . The trading plan was entered into during an open insider trading window and is intended to satisfy the affirmative defense of Rule 10b5-1(c) under the Securities Exchange Act of 1934, as amended, and Chevron’s policies regarding transactions in Chevron securities. 44 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 10.1+* Chevron Incentive Plan, amended and restated effective October 2, 2023 (refi l ed to correct formatting in the previo usly filed version) . 10.2+* Chevron Corporation Retirement Restoration Plan, amended and restated effective August 1, 2024. 10.3+* Chevron Corporation ESIP Restoration Plan, amended and restated effective August 1, 2024. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ +     Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 45 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 7, 2024 46\n\nPredict whether the return of XLF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.047781, "explanation": "The actual 21-day forward return for XLF starting 2024-11-18 was -4.78%, which classifies as 'negative'.", "metadata": {"future_return": -0.047781, "horizon_days": 21, "hist_return": 0.126511, "annualized_vol": 0.148691, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240802_0256", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-08-02", "context_summary": "ETH-USD over past 60 days: cumulative return -15.0%, annualized vol 38.8%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3766.39, end=3201.56, cumulative_return=-15.0%, annualized_volatility=38.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.17, 't10y3m_spread': -1.38, 'breakeven_10y': 2.2, 'hy_oas': 3.35, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.73, 'vix': 18.59000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.074201, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-08-02 was -7.42%, which classifies as 'negative'.", "metadata": {"future_return": -0.074201, "horizon_days": 21, "hist_return": -0.149965, "annualized_vol": 0.38841, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230613_0259", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-06-13", "context_summary": "XLB over past 60 days: cumulative return +5.6%, annualized vol 16.8%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=35.44, end=37.41, cumulative_return=+5.6%, annualized_volatility=16.8%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.82, 't10y3m_spread': -1.67, 'breakeven_10y': 2.17, 'hy_oas': 4.34, 'ig_oas': 1.41, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 15.010000228881836}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-12] [\"ANALYSIS-India's outsourcing giants cut hiring; disheartening for economy, students By Navamya Ganesh Acharya BENGALURU, June 12 (Reuters) - India's outsourcing giants are slashing hiring and getting projects done with existing workers, a rare pullback that could weigh on the economy and affect engineering students who have seen information technology as the sector of choice for decades. The slowdown, triggered by global uncertainty in demand, is unprecedented in an industry that is one of the biggest hirers in India's services sector since the 1990s and provides an assured career path and prosperity to hundreds of thousands of students each year. \\\"Weak IT hiring could be for two different reasons: short-term negative demand shock or a long-term displacement resulting from labour-saving technologies,\\\" said Rohit Azad, an economics professor at New Delhi's Jawaharlal Nehru University. \\\"The impact of weak hiring would depend on which is the primary cause driving it. A negative multiplier effect in the immediate would be there nevertheless,\\\" Azad added. The IT sector accounts for about 8% of India's GDP versus less than 1% about 30 years back, according to Rishad Premji, the chairman of Wipro WIPR.NS, one of the country's IT giants. Overall, the Indian tech sector employs over 5.4 million people, according to trade group Nasscom, although the number is dominated by the IT sector. About 290,000 new jobs in the tech sector were created in the financial year that ended in March, but Nasscom warned of \\\"global headwinds\\\" in the current year. With IT employees seen as big spenders on everything from cars, durables and second homes to travel and entertainment, they are likely to have had some effect on the sluggish 0.5% sequential growth in private consumption in January-March. \\\"Some slowdown in IT hiring intentions could contribute to the flat-lining in consumption that is already underway,\\\" said HDFC Bank Principal Economist Sakshi Gupta. RECESSION FEARS IT firms, which count global heavyweights such as Apple AAPL.O, Citigroup C.N and American Express AXP.N among its clients, went on a hiring binge during the pandemic that fuelled a digital services boom. However, things changed this year as recession fears gripped the world and the collapse of three U.S. regional banks and the forced sale of Europe's Credit Suisse CSGN.S to UBS UBSG.S left the global financial industry shaken, making IT clients across sectors cut spending. \\\"The post-pandemic phase saw companies ramping up production to meet new demands in the market, leading to a growth in hiring across IT companies. This boom, however, soon fizzled out in the face of the global economic crisis and a looming recession,\\\" said Sachin Alug, the CEO of staffing firm NLB Services. NLB sees a 20-25% drop in IT employee additions in the first half of the current financial year, while TeamLease Digital expects a 40% decrease for the entire year. Jobs portal Naukri.com's parent Info Edge INED.NS flag\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.030399, "explanation": "The actual 21-day forward return for XLB starting 2023-06-13 was +3.04%, which classifies as 'positive'.", "metadata": {"future_return": 0.030399, "horizon_days": 21, "hist_return": 0.055558, "annualized_vol": 0.168495, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241203_0263", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-12-03", "context_summary": "BNB-USD over past 60 days: cumulative return +16.6%, annualized vol 34.1%. Market regime: bull.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=555.38, end=647.59, cumulative_return=+16.6%, annualized_volatility=34.1%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.02, 't10y3m_spread': -0.32, 'breakeven_10y': 2.26, 'hy_oas': 2.68, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 13.34000015258789}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.024612, "explanation": "The actual 21-day forward return for BNB-USD starting 2024-12-03 was -2.46%, which classifies as 'negative'.", "metadata": {"future_return": -0.024612, "horizon_days": 21, "hist_return": 0.16603, "annualized_vol": 0.341244, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230718_0266", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-07-18", "context_summary": "BTC-USD over past 60 days: cumulative return +12.1%, annualized vol 33.7%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=26890.13, end=30145.89, cumulative_return=+12.1%, annualized_volatility=33.7%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.68, 'breakeven_10y': 2.25, 'hy_oas': 3.97, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 13.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-17] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.00305, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-07-18 was -0.31%, which classifies as 'flat'.", "metadata": {"future_return": -0.00305, "horizon_days": 21, "hist_return": 0.121076, "annualized_vol": 0.336989, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230721_0268", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-07-21", "context_summary": "XRP-USD over past 60 days: cumulative return +72.0%, annualized vol 82.0%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.46, end=0.79, cumulative_return=+72.0%, annualized_volatility=82.0%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.64, 'breakeven_10y': 2.35, 'hy_oas': 3.9, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 13.989999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-20] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.1823, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-07-21 was -18.23%, which classifies as 'negative'.", "metadata": {"future_return": -0.1823, "horizon_days": 21, "hist_return": 0.720226, "annualized_vol": 0.819882, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230822_0271", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-08-22", "context_summary": "FXI over past 60 days: cumulative return -0.4%, annualized vol 30.0%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=24.51, end=24.42, cumulative_return=-0.4%, annualized_volatility=30.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.63, 't10y3m_spread': -1.23, 'breakeven_10y': 2.34, 'hy_oas': 3.97, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 17.1299991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-21] [\"Tesla shares gain as Baird Equity adds stock to 'best ideas' list Aug 21 (Reuters) - Electric-vehicle maker Tesla's TSLA.O shares rose 4.5% on Monday, snapping a six-session losing streak, after brokerage Baird Equity Research added the stock to its \\\"best ideas\\\" list. The brokerage said price cuts and their impact on margins will drive the narrative in the second half of the year but other potential catalysts for the stock include the launch of Cybertruck, wider adoption of Full Self-Driving and expansion into new markets. Tesla's shares have risen about 85% so far this year on the back of growing sales despite a margin squeeze and hopes of wider adoption of its autonomous driving software. Bearish investors will point to lower production, said Baird, but added Tesla was still on pace to achieve its production forecast of 1.8 million vehicles this year. Tesla sparked a price war earlier this year and last week slashed prices of three models in China. It also launched a cheaper version of the Model S sedan and Model X SUV on Aug. 14 as it looks to stoke demand and grab a larger share of the market. The world's most valuable automaker's shares have a forward price-to-earnings multiple, a widely used benchmark to value stocks, of 50.15, compared to 26.58 for Apple AAPL.O and 6.14 for Ford Motor F.N, making it pricier. The brokerage also said sentiment for electric pickup truck maker Rivian Automotive's RIVN.O stock was improving, adding that cost improvements have begun to materialize as it brings production of key components in-house. (Reporting by Akash Sriram and Jaspreet Singh in Bengaluru; Editing by Krishna Chandra Eluri) ((Akash.Sriram@thomsonreuters.com; @HoodieOnVeshti on Twitter; +91-74116-87774;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple and Spotify: 2 AI Stock Plays in Music Streaming The artificial intelligence (AI) revolution is underway, and it's already made a lot of money for investors who recognized its potential early in the game. With shares of AI frontrunners like Nvidia (NVDA) doubling up many times over in a matter of months, it's not hard to see why so many investors want to stay in the tech scene, despite the potential for further interest rate increases. With so many technology companies committed to investing in their AI capabilities, investors shouldn't narrow their focus on the few AI winners that have been leading the pack in recent quarters. Arguably, investors should at least be equal-weight in the mega-cap tech heroes of the so-called \\u201cMagnificent Seven\\u201d to benefit from the continued rise of AI. At the same time, investors should also seek value in areas of the market where the long-term benefits of incorporating AI tech aren't yet fully recognized. Indeed, Nvidia stands out as one of the AI plays of the present. After such a historic ascent, though, I'm starting to think the opportunity over at Nvidia \n\nPredict whether the return of FXI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002678, "explanation": "The actual 21-day forward return for FXI starting 2023-08-22 was +0.27%, which classifies as 'flat'.", "metadata": {"future_return": 0.002678, "horizon_days": 21, "hist_return": -0.003612, "annualized_vol": 0.299595, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231023_0274", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-10-23", "context_summary": "MATIC-USD over past 60 days: cumulative return +11.3%, annualized vol 42.5%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.55, end=0.61, cumulative_return=+11.3%, annualized_volatility=42.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.14, 't10y3m_spread': -0.65, 'breakeven_10y': 2.47, 'hy_oas': 4.52, 'ig_oas': 1.33, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 21.709999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-22] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.390723, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-10-23 was +39.07%, which classifies as 'positive'.", "metadata": {"future_return": 0.390723, "horizon_days": 21, "hist_return": 0.113349, "annualized_vol": 0.424799, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240531_0277", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-05-31", "context_summary": "QQQ over past 60 days: cumulative return +3.0%, annualized vol 15.3%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=433.45, end=446.64, cumulative_return=+3.0%, annualized_volatility=15.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.37, 't10y3m_spread': -0.91, 'breakeven_10y': 2.36, 'hy_oas': 3.19, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 7.03, 'vix': 14.470000267028809}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 2026-01-01 us-gaap:InvestmentAdviceMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.070946, "explanation": "The actual 21-day forward return for QQQ starting 2024-05-31 was +7.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.070946, "horizon_days": 21, "hist_return": 0.030441, "annualized_vol": 0.152886, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240910_0279", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-09-10", "context_summary": "DOT-USD over past 60 days: cumulative return -29.7%, annualized vol 51.2%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=6.10, end=4.29, cumulative_return=-29.7%, annualized_volatility=51.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.02, 't10y3m_spread': -1.41, 'breakeven_10y': 2.04, 'hy_oas': 3.36, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 19.450000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.022846, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-09-10 was -2.28%, which classifies as 'negative'.", "metadata": {"future_return": -0.022846, "horizon_days": 21, "hist_return": -0.297295, "annualized_vol": 0.512179, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230724_0282", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-07-24", "context_summary": "XLV over past 60 days: cumulative return +3.9%, annualized vol 11.4%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=125.29, end=130.13, cumulative_return=+3.9%, annualized_volatility=11.4%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.66, 'breakeven_10y': 2.35, 'hy_oas': 3.89, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 13.600000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-21] [\"Meta Platforms (META) to Report Q2 Earnings: What to Expect Meta Platforms META is set to report its second-quarter 2023 results on Jul 26. Meta expects total revenues between $29.5 billion and $32 billion for the second quarter of 2023. Unfavorable forex is expected to hurt year-over-year top-line growth by less than 1%. The Zacks Consensus Estimate for second-quarter revenues is pegged at $30.84 billion, indicating an increase of 7.01% from the year-ago quarter\\u2019s reported figure. The consensus mark for earnings stands at $2.85 per share, up by a cent over the past 30 days, suggesting growth of 15.85% from the figure reported in the year-ago quarter. Meta Platforms, Inc. Price and EPS Surprise Meta Platforms, Inc. price-eps-surprise | Meta Platforms, Inc. Quote Meta\\u2019s earnings beat the Zacks Consensus Estimate in two of the trailing four quarters and missed twice, the average surprise being 15.46%. Meta had a terrific second quarter of 2023, outperforming the Zacks Internet Software industry. While the shares of the social media giant have returned 35.4%, the industry has risen 16.3%. Let\\u2019s see how things have shaped up for the upcoming announcement. Factors to Note Meta\\u2019s second-quarter top line is expected to have benefited from Facebook\\u2019s expanding user base (more than 3 billion daily active users) and growing adoption of reels. Higher engagement level is helping to steady its user growth across all regions, particularly Asia Pacific. Our model estimate for Asia Pacific Daily Active Users (DAUs) in the second quarter is pegged at 883 million, indicating 5.6% year-over-year growth, the fastest among the regions followed by the Rest of World, which we expect to grow 3.3% to 652 million DAUs. In terms of Monthly Active Users (MAUs), our estimate for Asia Pacific is pegged at 1.339 billion, suggesting 2.6% year-over-year growth. The Rest of World MAUs is expected to grow 2.4% to 982 million MAUs. Increased engagement for Meta\\u2019s offerings like Instagram, WhatsApp, Messenger and Facebook has been a major growth driver. Effective usage of artificial intelligence has been helping the company keep its users engaged. Our model estimate for Meta\\u2019s worldwide DAU is pegged at 2.034 billion, indicating 3.4% growth year over year. MAU is pegged at 2.985 billion, indicating a 1.7% increase year over year. Nevertheless, Meta\\u2019s top line is expected to reflect the negative impact of the challenging macroeconomic environment and high inflation that is anticipated to have kept ad spending budgets under pressure. This is likely to have weighed on ad revenues in the to-be-reported quarter. The company\\u2019s ad revenue business is facing a decline in growth due to ad targeting-related headwinds created by Apple\\u2019s AAPL iOS changes. Apple\\u2019s iOS changes have made ad targeting difficult, which has increased the cost of driving outcomes. However, measuring these outcomes is tough. In the first quarter of 2023, Meta\\u20\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.020156, "explanation": "The actual 21-day forward return for XLV starting 2023-07-24 was -2.02%, which classifies as 'negative'.", "metadata": {"future_return": -0.020156, "horizon_days": 21, "hist_return": 0.038652, "annualized_vol": 0.114456, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230424_0285", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-04-24", "context_summary": "XRP-USD over past 60 days: cumulative return +19.5%, annualized vol 73.7%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.39, end=0.47, cumulative_return=+19.5%, annualized_volatility=73.7%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.6, 't10y3m_spread': -1.57, 'breakeven_10y': 2.28, 'hy_oas': 4.46, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 16.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-23] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.073083, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-04-24 was -7.31%, which classifies as 'negative'.", "metadata": {"future_return": -0.073083, "horizon_days": 21, "hist_return": 0.195015, "annualized_vol": 0.736915, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240219_0287", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-02-19", "context_summary": "LINK-USD over past 60 days: cumulative return +31.5%, annualized vol 67.0%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=15.29, end=20.10, cumulative_return=+31.5%, annualized_volatility=67.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.34, 't10y3m_spread': -1.14, 'breakeven_10y': 2.33, 'hy_oas': 3.34, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 14.239999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.074115, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-02-19 was +7.41%, which classifies as 'positive'.", "metadata": {"future_return": 0.074115, "horizon_days": 21, "hist_return": 0.314653, "annualized_vol": 0.669913, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230703_0289", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2023-07-03", "context_summary": "STIP over past 60 days: cumulative return -0.8%, annualized vol 2.5%. Market regime: sideways.", "question": "Asset: STIP\nHistorical prices (past 60 trading days): start=90.10, end=89.40, cumulative_return=-0.8%, annualized_volatility=2.5%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.62, 'breakeven_10y': 2.22, 'hy_oas': 4.05, 'ig_oas': 1.3, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 13.59000015258789}\nMarket regime: sideways\n\nPredict whether the return of STIP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.001405, "explanation": "The actual 21-day forward return for STIP starting 2023-07-03 was +0.14%, which classifies as 'flat'.", "metadata": {"future_return": 0.001405, "horizon_days": 21, "hist_return": -0.007827, "annualized_vol": 0.025256, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230202_0292", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-02-02", "context_summary": "XLV over past 60 days: cumulative return +2.9%, annualized vol 14.2%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=123.44, end=126.96, cumulative_return=+2.9%, annualized_volatility=14.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.7, 't10y3m_spread': -1.27, 'breakeven_10y': 2.25, 'hy_oas': 4.31, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 6.13, 'vix': 17.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-01] [\"GLOBAL MARKETS-Stocks rise, dollar falls after Fed hikes as expected By Chuck Mikolajczak NEW YORK, Feb 1 (Reuters) - A gauge of global stocks rose and the U.S. dollar and Treasury yields were lower on Wednesday after the Federal Reserve raised its target interest rate by the expected 25 basis points but communicated more increases were on the horizon. The Fed said the U.S. economy was enjoying \\\"modest growth\\\" and \\\"robust\\\" job gains, with policymakers still \\\"highly attentive to inflation risks\\\" as it seeks to tighten financial conditions and reign in high prices. Markets have been pricing in the possibility of a rate cut by the Fed in the back half of the year. On Wall Street, U.S. stocks were choppy after the Fed announcement but rebounded to turn positive as Chair Jerome Powell began to speak. \\\"The key thing the Fed is focused on is wages and we are seeing wage inflation continue to ameliorate if you look at both average hourly earnings and the employment cost index which just came out, wages are beginning to soften, but they are not softening enough to get inflation down to that 2% target,\\\" said Ellen Hazen, chief market strategist at F.L.Putnam Investment Management in Wellesley, Massachusetts. \\\"They had a very slightly dovish change in the language where they previously had talked about determining the pace of future increases and now they are talking about determining the extent of future increases.\\\" Investors will now closely eye comments from Fed Chair Powell for further signals on the path of the central bank's policy. The Dow Jones Industrial Average .DJI fell 5.45 points, or 0.02%, to 34,080.59, the S&P 500 .SPX gained 30.83 points, or 0.76%, to 4,107.43 and the Nasdaq Composite .IXIC added 173.22 points, or 1.5%, to 11,757.77. Before the policy announcement, economic data painted a mixed picture, with a labor market that remains strong while manufacturing activity continues to weaken, showing contraction for a third straight month. Investors have viewed a weaker labor market as a key component to bring down stubbornly high inflation. Earnings season also continues to roll on, with Facebook owner Meta META.O reporting earnings after the closing bell on Wednesday. Later in the week will bring earnings from names such as Apple AAPL.O and Amazon .AMZN.O. Early gains for European shares faded to close virtually unchanged ahead of the Fed statement, although industrial stocks SXNP, up 0.85%, were a bright spot. On the heels of the Fed, the European Central Bank (ECB) and Bank of England will make their policy statements on Thursday, in which each is largely expected to hike by 50 basis points. The pan-European STOXX 600 index .STOXX closed down 0.03% and MSCI's gauge of stocks across the globe .MIWD00000PUS gained 0.81%. Data on Wednesday showed headline inflation in the euro zone moderated to 8.5% in January, from 9% in December, while core prices picked up to 7% from 6.9%, likely keeping pressure on the ECB to raise interest r\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.029381, "explanation": "The actual 21-day forward return for XLV starting 2023-02-02 was -2.94%, which classifies as 'negative'.", "metadata": {"future_return": -0.029381, "horizon_days": 21, "hist_return": 0.02853, "annualized_vol": 0.141582, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240315_0294", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-03-15", "context_summary": "ICSH over past 60 days: cumulative return +0.8%, annualized vol 0.5%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=45.33, end=45.68, cumulative_return=+0.8%, annualized_volatility=0.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.19, 'breakeven_10y': 2.3, 'hy_oas': 3.15, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.74, 'vix': 14.399999618530272}\nMarket regime: sideways\n\nPredict whether the return of ICSH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003534, "explanation": "The actual 21-day forward return for ICSH starting 2024-03-15 was +0.35%, which classifies as 'flat'.", "metadata": {"future_return": 0.003534, "horizon_days": 21, "hist_return": 0.007678, "annualized_vol": 0.004647, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230313_0296", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-03-13", "context_summary": "BNB-USD over past 60 days: cumulative return +0.6%, annualized vol 38.5%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=287.81, end=289.68, cumulative_return=+0.6%, annualized_volatility=38.5%\nMacro context: {'fed_funds_rate': 4.57, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.9, 't10y3m_spread': -1.31, 'breakeven_10y': 2.26, 'hy_oas': 4.61, 'ig_oas': 1.37, 'ted_spread': 0.09, 'mortgage_30y': 6.73, 'vix': 24.799999237060547}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-12] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.001132, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-03-13 was -0.11%, which classifies as 'flat'.", "metadata": {"future_return": -0.001132, "horizon_days": 21, "hist_return": 0.006474, "annualized_vol": 0.384651, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240916_0299", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-09-16", "context_summary": "ETH-USD over past 60 days: cumulative return -32.3%, annualized vol 60.8%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3426.26, end=2320.90, cumulative_return=-32.3%, annualized_volatility=60.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.09, 't10y3m_spread': -1.31, 'breakeven_10y': 2.08, 'hy_oas': 3.37, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.2, 'vix': 16.559999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.055119, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-09-16 was +5.51%, which classifies as 'positive'.", "metadata": {"future_return": 0.055119, "horizon_days": 21, "hist_return": -0.322615, "annualized_vol": 0.60836, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231031_0302", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-10-31", "context_summary": "AVAX-USD over past 60 days: cumulative return +15.4%, annualized vol 42.6%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=9.92, end=11.45, cumulative_return=+15.4%, annualized_volatility=42.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.15, 't10y3m_spread': -0.72, 'breakeven_10y': 2.44, 'hy_oas': 4.5, 'ig_oas': 1.32, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 19.75}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-30] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.68175, "explanation": "The actual 21-day forward return for AVAX-USD starting 2023-10-31 was +68.17%, which classifies as 'positive'.", "metadata": {"future_return": 0.68175, "horizon_days": 21, "hist_return": 0.153935, "annualized_vol": 0.425952, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230922_0305", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2023-09-22", "context_summary": "UNG over past 60 days: cumulative return -10.8%, annualized vol 43.8%. Market regime: sideways.", "question": "Asset: UNG\nHistorical prices (past 60 trading days): start=29.68, end=26.48, cumulative_return=-10.8%, annualized_volatility=43.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.63, 't10y3m_spread': -1.08, 'breakeven_10y': 2.38, 'hy_oas': 3.89, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 7.19, 'vix': 17.540000915527344}\nMarket regime: sideways\n\nPredict whether the return of UNG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.01194, "explanation": "The actual 21-day forward return for UNG starting 2023-09-22 was +1.19%, which classifies as 'positive'.", "metadata": {"future_return": 0.01194, "horizon_days": 21, "hist_return": -0.107817, "annualized_vol": 0.438029, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240416_0307", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-04-16", "context_summary": "VEA over past 60 days: cumulative return +4.0%, annualized vol 10.6%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=43.68, end=45.42, cumulative_return=+4.0%, annualized_volatility=10.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.3, 't10y3m_spread': -0.82, 'breakeven_10y': 2.43, 'hy_oas': 3.28, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 19.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of VEA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.07022, "explanation": "The actual 21-day forward return for VEA starting 2024-04-16 was +7.02%, which classifies as 'positive'.", "metadata": {"future_return": 0.07022, "horizon_days": 21, "hist_return": 0.03977, "annualized_vol": 0.105734, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240415_0310", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-04-15", "context_summary": "BNB-USD over past 60 days: cumulative return +59.9%, annualized vol 72.3%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=354.71, end=567.22, cumulative_return=+59.9%, annualized_volatility=72.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.38, 't10y3m_spread': -0.95, 'breakeven_10y': 2.39, 'hy_oas': 3.25, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 17.309999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.064393, "explanation": "The actual 21-day forward return for BNB-USD starting 2024-04-15 was +6.44%, which classifies as 'positive'.", "metadata": {"future_return": 0.064393, "horizon_days": 21, "hist_return": 0.599101, "annualized_vol": 0.722836, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241009_0313", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLT"], "decision_date": "2024-10-09", "context_summary": "TLT over past 60 days: cumulative return +2.6%, annualized vol 13.1%. Market regime: sideways.", "question": "Asset: TLT\nHistorical prices (past 60 trading days): start=86.70, end=88.98, cumulative_return=+2.6%, annualized_volatility=13.1%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.06, 't10y3m_spread': -0.71, 'breakeven_10y': 2.27, 'hy_oas': 2.99, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.12, 'vix': 21.420000076293945}\nMarket regime: sideways\n\nPredict whether the return of TLT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.02977, "explanation": "The actual 21-day forward return for TLT starting 2024-10-09 was -2.98%, which classifies as 'negative'.", "metadata": {"future_return": -0.02977, "horizon_days": 21, "hist_return": 0.026274, "annualized_vol": 0.130923, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230525_0316", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-05-25", "context_summary": "SOL-USD over past 60 days: cumulative return -8.4%, annualized vol 50.8%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=20.98, end=19.22, cumulative_return=-8.4%, annualized_volatility=50.8%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.58, 't10y3m_spread': -1.64, 'breakeven_10y': 2.25, 'hy_oas': 4.68, 'ig_oas': 1.44, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 20.030000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-24] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.233699, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-05-25 was -23.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.233699, "horizon_days": 21, "hist_return": -0.083519, "annualized_vol": 0.508262, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240306_0319", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-03-06", "context_summary": "ADA-USD over past 60 days: cumulative return +32.6%, annualized vol 63.4%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.52, end=0.69, cumulative_return=+32.6%, annualized_volatility=63.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.41, 't10y3m_spread': -1.34, 'breakeven_10y': 2.32, 'hy_oas': 3.31, 'ig_oas': 1.01, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 14.460000038146973}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.116293, "explanation": "The actual 21-day forward return for ADA-USD starting 2024-03-06 was -11.63%, which classifies as 'negative'.", "metadata": {"future_return": -0.116293, "horizon_days": 21, "hist_return": 0.325724, "annualized_vol": 0.633864, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231208_0321", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-12-08", "context_summary": "XLRE over past 60 days: cumulative return +3.7%, annualized vol 21.6%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=33.63, end=34.86, cumulative_return=+3.7%, annualized_volatility=21.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.44, 't10y3m_spread': -1.3, 'breakeven_10y': 2.17, 'hy_oas': 3.77, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 7.03, 'vix': 13.0600004196167}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-07] [\"US STOCKS-Nasdaq ends sharply higher as Alphabet and AMD fuel AI surge (Updated at 4:10 p.m. ET/ 2110 GMT) * Investors cheer Alphabet's new AI model * Advanced Micro Devices climbs after AI-chip market forecast * Weekly jobless claims lower than expected * Indexes: S&P 500 +0.80%, Nasdaq +1.37%, Dow +0.18% * By Noel Randewich and Shristi Achar A Dec 7 (Reuters) - The Nasdaq ended sharply higher on Thursday after Alphabet and Advanced Micro Devices sparked a megacap rally on fresh optimism about artificial intelligence. Shares of Alphabet jumped 5.3% as analysts cheered the launch of the Google-parent's newest AI model, while AMD soared nearly 10% after the company estimated the potential market for its data center AI chips could reach $45 billion this year. Other heavyweight tech-related stocks also gained, with Nvidia and Meta Platforms rising over 2%, Amazon up 1.6% and Apple 1% higher. The Philadelphia semiconductor index jumped 2.8%, increasing its 2023 gain to 48%, much of that fueled by bets about the future of AI. \\\"Today it's an AMD-Google rally. There's a contagion effect across the market. Everyone wants to get on the bandwagon,\\\" said Jay Hatfield, CEO of Infrastructure Capital Management in New York. \\\"We're kind of in this weird market, a tag-team market, where one day tech leads, and then the next day value and the broad market lead.\\\" The S&P 500 has steadily climbed since the end of October on expectations the Federal Reserve has finished its campaign of interest rate hikes and that it could begin cutting rates in March. The S&P 500 climbed 0.80% to end the session at 4,585.59 points, with 1.8 stocks in the index gaining for each one that fell. The most traded stock in the S&P 500 was Tesla , with $25.7 billion worth of shares changing hands during the session. The shares rose 1.37%. The Nasdaq Composite jumped 1.37% to 14,339.99 points, while Dow Jones Industrial Average rose 0.18% to 36,117.57 points. Volume on U.S. exchanges was relatively heavy, with 11.2 billion shares traded, compared to an average of 10.8 billion shares over the previous 20 sessions. Traders have almost fully priced in the likelihood of the Fed keeping rates unchanged at its meeting next week. Data on Thursday showed the number of Americans filing new claims for unemployment benefits increased less than expected last week to a seasonally adjusted 220,000 for the week. A Labor Department jobs report due on Friday could hint at how quickly the U.S. economy is softening and may sway expectations about when the Fed is likely to begin cutting rates. Non-farm payrolls are expected to have increased by 180,000 jobs last month after rising by 150,000 in October. Interest rate futures imply a nearly 64% chance of a rate cut as soon as March, according to the CME Group's FedWatch tool. Limiting gains in the Dow, shares of Merck fell 1.7% after the drugmaker's immunotherapy combination failed in a lung cancer study. (Reporting by Amruta Khandekar and Shristi Achar A\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.062102, "explanation": "The actual 21-day forward return for XLRE starting 2023-12-08 was +6.21%, which classifies as 'positive'.", "metadata": {"future_return": 0.062102, "horizon_days": 21, "hist_return": 0.036632, "annualized_vol": 0.215684, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240704_0324", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2024-07-04", "context_summary": "MORT over past 60 days: cumulative return +0.1%, annualized vol 19.0%. Market regime: sideways.", "question": "Asset: MORT\nHistorical prices (past 60 trading days): start=8.80, end=8.81, cumulative_return=+0.1%, annualized_volatility=19.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.35, 't10y3m_spread': -1.11, 'breakeven_10y': 2.27, 'hy_oas': 3.25, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.09000015258789}\nMarket regime: sideways\n\nPredict whether the return of MORT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.035519, "explanation": "The actual 21-day forward return for MORT starting 2024-07-04 was +3.55%, which classifies as 'positive'.", "metadata": {"future_return": 0.035519, "horizon_days": 21, "hist_return": 0.000973, "annualized_vol": 0.190058, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240502_0327", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-02", "context_summary": "SPY over past 60 days: cumulative return +1.6%, annualized vol 11.8%. Market regime: sideways.", "question": "Asset: SPY\nHistorical prices (past 60 trading days): start=480.75, end=488.46, cumulative_return=+1.6%, annualized_volatility=11.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.33, 't10y3m_spread': -0.83, 'breakeven_10y': 2.38, 'hy_oas': 3.21, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 7.17, 'vix': 15.390000343322754}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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0000104169 wmt:SamsClubMember 2023-01-31 0000104169 wmt:WalmartUSMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartInternationalMember 2023-02-01 2024-01-31 0000104169 wmt:SamsClubMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartUSMember 2024-01-31 0000104169 wmt:WalmartInternationalMember 2024-01-31 0000104169 wmt:SamsClubMember 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2023-02-01 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2022-02-01 2023-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of SPY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.044235, "explanation": "The actual 21-day forward return for SPY starting 2024-05-02 was +4.42%, which classifies as 'positive'.", "metadata": {"future_return": 0.044235, "horizon_days": 21, "hist_return": 0.016042, "annualized_vol": 0.117607, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230925_0329", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-09-25", "context_summary": "EEM over past 60 days: cumulative return -2.0%, annualized vol 15.9%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=36.74, end=36.01, cumulative_return=-2.0%, annualized_volatility=15.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.66, 't10y3m_spread': -1.12, 'breakeven_10y': 2.37, 'hy_oas': 3.93, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 7.19, 'vix': 17.200000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-22] [\"Amazon (AMZN) Bolsters Echo Portfolio With New Devices Amazon AMZN has expanded its family of Echo devices by introducing Echo Show 8, Echo Hub and Echo Frames, which are expected to deliver customized, proactive and intuitive Alexa experiences. Notably, the Echo Show 8 has been upgraded with a 13-megapixel camera, improved audio pipeline, faster processor and built-in smart home hub, offering minimized background noise, enhanced audio, video calls, and room adaptation technology. Meanwhile, Echo Hub, the Alexa-enabled wall-mountable smart home control panel, boasts features like a customizable dashboard, a thin eight-inch display, and adaptive content using infrared technology to detect nearby users, enabling easy management of devices. Further, the next-generation Echo Frames feature five styles, improved battery life and enhanced speech processing technology, allowing hands-free use of Alexa, music and smart home devices. Additionally, Amazon partnered with Safilo, a leading eyewear manufacturer, to combine Alexa's capabilities with iconic Carrera designs, providing seamless integration into customers' daily lives. We mark the latest move as Amazon\\u2019s effort to expand its smart home devices portfolio. Amazon.com, Inc. Price and Consensus Amazon.com, Inc. price-consensus-chart | Amazon.com, Inc. Quote Growth Prospects Apart from the latest launch, Amazon recently added four other devices to its Echo portfolio, namely Echo Pop, Show 5, Show 5 Kids and Echo Buds, to bolster its Echo lineup. These launches give customers more choices in how they access Alexa. Further, Amazon infused generative AI into the Fire TV ecosystem, to enable voice search, personalized recommendations and personalized content search based on specific preferences. These endeavors are likely to strengthen the company\\u2019s presence in the booming smart home devices market. Per a Future Market Insights report, the global smart home device market is expected to reach $300 billion by 2033, witnessing a CAGR of 17.8% during the period of 2023-2033. We believe Amazon\\u2019s growing prospects in the promising smart home devices markets will likely aid its overall financial performance. This, in turn, is expected to instill investor optimism in the stock. For third-quarter 2023, Amazon expects net sales between $138 billion and $143 billion. Net sales are expected to grow 9-13% from the year-ago quarter\\u2019s reported figure. The Zacks Consensus Estimate for net sales is pegged at $141.89 billion, suggesting year-over-year growth of 11.6%. Notably, AMZN\\u2019s shares have gained 54% in the year-to-date period compared with the industry\\u2019s growth of 33.2%. Stiff Competition We note that the expanding smart home devices portfolio will continue to aid Amazon to compete well with some notable industry players like Apple AAPL and Alphabet GOOGL, which are also making concerted efforts to gain a solid footing in the smart home market space. Notably, Apple\\u2019s HomePod (2nd \n\nPredict whether the return of EEM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.027937, "explanation": "The actual 21-day forward return for EEM starting 2023-09-25 was -2.79%, which classifies as 'negative'.", "metadata": {"future_return": -0.027937, "horizon_days": 21, "hist_return": -0.019872, "annualized_vol": 0.159075, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230113_0332", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["GLD"], "decision_date": "2023-01-13", "context_summary": "GLD over past 60 days: cumulative return +16.6%, annualized vol 15.3%. Market regime: sideways.", "question": "Asset: GLD\nHistorical prices (past 60 trading days): start=151.45, end=176.64, cumulative_return=+16.6%, annualized_volatility=15.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.69, 't10y3m_spread': -1.23, 'breakeven_10y': 2.21, 'hy_oas': 4.29, 'ig_oas': 1.33, 'ted_spread': 0.09, 'mortgage_30y': 6.33, 'vix': 18.82999992370605}\nMarket regime: sideways\n\nPredict whether the return of GLD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.035131, "explanation": "The actual 21-day forward return for GLD starting 2023-01-13 was -3.51%, which classifies as 'negative'.", "metadata": {"future_return": -0.035131, "horizon_days": 21, "hist_return": 0.166326, "annualized_vol": 0.153073, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240328_0333", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2024-03-28", "context_summary": "VNQ over past 60 days: cumulative return -2.8%, annualized vol 16.9%. Market regime: bull.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=81.60, end=79.30, cumulative_return=-2.8%, annualized_volatility=16.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.34, 't10y3m_spread': -1.25, 'breakeven_10y': 2.32, 'hy_oas': 3.15, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 12.779999732971191}\nMarket regime: bull\n\nPredict whether the return of VNQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.073081, "explanation": "The actual 21-day forward return for VNQ starting 2024-03-28 was -7.31%, which classifies as 'negative'.", "metadata": {"future_return": -0.073081, "horizon_days": 21, "hist_return": -0.028233, "annualized_vol": 0.169205, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230223_0336", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-02-23", "context_summary": "BTC-USD over past 60 days: cumulative return +43.6%, annualized vol 38.7%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=16841.99, end=24188.84, cumulative_return=+43.6%, annualized_volatility=38.7%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.73, 't10y3m_spread': -0.91, 'breakeven_10y': 2.41, 'hy_oas': 4.41, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 22.290000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-22] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.046155, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-02-23 was +4.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.046155, "horizon_days": 21, "hist_return": 0.436223, "annualized_vol": 0.386549, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240808_0339", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2024-08-08", "context_summary": "PALL over past 60 days: cumulative return -12.4%, annualized vol 34.1%. Market regime: sideways.", "question": "Asset: PALL\nHistorical prices (past 60 trading days): start=93.01, end=81.44, cumulative_return=-12.4%, annualized_volatility=34.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.04, 't10y3m_spread': -1.38, 'breakeven_10y': 2.11, 'hy_oas': 3.57, 'ig_oas': 1.07, 'ted_spread': 0.09, 'mortgage_30y': 6.73, 'vix': 27.850000381469727}\nMarket regime: sideways\n\nPredict whether the return of PALL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.020336, "explanation": "The actual 21-day forward return for PALL starting 2024-08-08 was +2.03%, which classifies as 'positive'.", "metadata": {"future_return": 0.020336, "horizon_days": 21, "hist_return": -0.124395, "annualized_vol": 0.341203, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230209_0342", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-02-09", "context_summary": "MATIC-USD over past 60 days: cumulative return +46.0%, annualized vol 59.9%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.89, end=1.30, cumulative_return=+46.0%, annualized_volatility=59.9%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.82, 't10y3m_spread': -1.09, 'breakeven_10y': 2.34, 'hy_oas': 4.07, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 6.09, 'vix': 19.6299991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-08] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.002906, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-02-09 was -0.29%, which classifies as 'flat'.", "metadata": {"future_return": -0.002906, "horizon_days": 21, "hist_return": 0.459832, "annualized_vol": 0.599257, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231002_0345", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-10-02", "context_summary": "BTC-USD over past 60 days: cumulative return -4.1%, annualized vol 28.4%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=29178.68, end=27983.75, cumulative_return=-4.1%, annualized_volatility=28.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.44, 't10y3m_spread': -0.96, 'breakeven_10y': 2.35, 'hy_oas': 4.03, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 7.31, 'vix': 17.520000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-01] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.20179, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-10-02 was +20.18%, which classifies as 'positive'.", "metadata": {"future_return": 0.20179, "horizon_days": 21, "hist_return": -0.040952, "annualized_vol": 0.283997, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240105_0348", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-01-05", "context_summary": "VLUE over past 60 days: cumulative return +10.7%, annualized vol 15.1%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=85.27, end=94.36, cumulative_return=+10.7%, annualized_volatility=15.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.49, 'breakeven_10y': 2.22, 'hy_oas': 3.69, 'ig_oas': 1.09, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 14.130000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-04] [\"Intel Will Take Another Swing at Nvidia and AMD in 2024 The graphics card market is no longer a duopoly. Intel (NASDAQ: INTC) launched its first discrete family of graphics cards in late 2022. While the launch was bumpy, the company managed to offer a compelling value proposition for gamers in the budget portion of the market. Nvidia (NASDAQ: NVDA) is still the market leader by far, and Advanced Micro Devices (NASDAQ: AMD) is in a distant second place. Intel has gained a small foothold, but only in the budget portion of the market. The company's issues with buggy software drivers, particularly soon after launch, have likely driven some gamers away. Another shot in 2024 Intel's first generation of graphics cards made no attempt to compete with Nvidia and AMD at higher price points. The Arc A750 sells today for around $210, and the Arc A770 goes for around $320, although prices have dipped lower at times. These cards are competitive for the price, although performance can be inconsistent due to nagging driver issues. Helping Intel in 2023 were lackluster mid-range graphics card launches from both Nvidia and AMD. Nvidia's RTX 4060 and RTX 4060 Ti came with limitations and high price tags. Tom's Hardware concluded that the priciest variant was \\\"overpriced for what you get, much like most of the rest of Nvidia's current RTX 40-series lineup.\\\" AMD's efforts weren't much better. The RX 7600 wasn't much of an upgrade over previous models, and the value proposition, compared to last-gen products, was weak, even after a last-minute price cut. While Nvidia is expected to roll out a product refresh soon, genuinely new mid-range graphics cards from Nvidia and AMD likely won't be coming until 2025. The gap between Nvidia's RTX 3060 and RTX 4060 was more than two years, and the RTX 4060 has only been on the market since mid-2023. AMD may fill in some gaps in its lineup in 2024, but next-generation products are likely a ways off. Intel's next-generation graphics cards, codenamed Battlemage, are expected to arrive sometime in 2024. With Battlemage, Intel is expected to move up into the enthusiast portions of the market that its first-generation products avoided. While Intel probably won't be going toe-to-toe with Nvidia's highest-end products, Battlemage should appeal to a broader swath of gamers. Intel proved with its first-generation products that it can produce capable graphics hardware. With its second-generation products, it must prove that it's committed enough to the market to continually improve its software and eliminate the bugs and inconsistencies that have been holding it back. A multibillion-dollar opportunity Jon Peddie Research expects the market for discrete graphics cards to grow to $39 billion by 2026. That estimate was thrown out in late 2022 before the artificial intelligence (AI) bonanza caused demand for data center GPUs to explode. Considering just the market for graphics cards aimed at gaming, however, that's likely still a reasonable \n\nPredict whether the return of VLUE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.004685, "explanation": "The actual 21-day forward return for VLUE starting 2024-01-05 was -0.47%, which classifies as 'flat'.", "metadata": {"future_return": -0.004685, "horizon_days": 21, "hist_return": 0.106581, "annualized_vol": 0.150978, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231109_0351", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-11-09", "context_summary": "ETH-USD over past 60 days: cumulative return +16.9%, annualized vol 28.4%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1616.83, end=1889.32, cumulative_return=+16.9%, annualized_volatility=28.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.44, 't10y3m_spread': -1.05, 'breakeven_10y': 2.34, 'hy_oas': 4.08, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 14.449999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-08] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.032069, "explanation": "The actual 21-day forward return for ETH-USD starting 2023-11-09 was -3.21%, which classifies as 'negative'.", "metadata": {"future_return": -0.032069, "horizon_days": 21, "hist_return": 0.168536, "annualized_vol": 0.284263, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230329_0354", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2023-03-29", "context_summary": "SCHH over past 60 days: cumulative return -4.0%, annualized vol 22.8%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=17.42, end=16.73, cumulative_return=-4.0%, annualized_volatility=22.8%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.47, 't10y3m_spread': -1.25, 'breakeven_10y': 2.31, 'hy_oas': 5.01, 'ig_oas': 1.52, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 19.96999931335449}\nMarket regime: sideways\n\nPredict whether the return of SCHH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.037155, "explanation": "The actual 21-day forward return for SCHH starting 2023-03-29 was +3.72%, which classifies as 'positive'.", "metadata": {"future_return": 0.037155, "horizon_days": 21, "hist_return": -0.039531, "annualized_vol": 0.227745, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231026_0357", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-10-26", "context_summary": "BTC-USD over past 60 days: cumulative return +32.2%, annualized vol 34.5%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=26089.69, end=34502.82, cumulative_return=+32.2%, annualized_volatility=34.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.13, 't10y3m_spread': -0.64, 'breakeven_10y': 2.43, 'hy_oas': 4.37, 'ig_oas': 1.3, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 20.190000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-25] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.058499, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-10-26 was +5.85%, which classifies as 'positive'.", "metadata": {"future_return": 0.058499, "horizon_days": 21, "hist_return": 0.322469, "annualized_vol": 0.344623, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230314_0360", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-03-14", "context_summary": "XLE over past 60 days: cumulative return -4.8%, annualized vol 25.9%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=38.17, end=36.33, cumulative_return=-4.8%, annualized_volatility=25.9%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.48, 't10y3m_spread': -1.32, 'breakeven_10y': 2.24, 'hy_oas': 5.03, 'ig_oas': 1.51, 'ted_spread': 0.09, 'mortgage_30y': 6.73, 'vix': 26.520000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-13] [\"Apple's (AAPL) Animation Film Emerges Winner at 2023 Oscars Apple AAPL continues its winning stride at the Academy Awards with its animation movie The Boy, the Mole, the Fox and the Horse winning an Oscar for Best Animated Short Film. Last year, Apple won three Academy Awards for CODA. Based on the book by Charlie Mackesy, The Boy, the Mole, the Fox and the Horse has already won a BAFTA award, four Annie Awards including Best Special Production, and an NAACP Image Awards nomination for Outstanding Short Form (Animated) film. Apple\\u2019s impressive run at the Oscars has been instrumental in driving recognition of Apple TV+ in the saturated streaming market currently dominated by the likes of Amazon AMZN Prime Video, Netflix NFLX and Disney\\u2019s DIS Disney+. Nevertheless, the growing popularity of Apple TV+ and services like Fitness+ have been beneficial for Apple\\u2019s Services business, which has become a major revenue-generating source in recent times. The Services portfolio currently has more than 935 million paid subscribers and accounted for 17.7% of sales in the fiscal first quarter. Services revenues increased 6.4% from the year-ago quarter to $20.77 billion. Apple Inc. Price, Consensus and EPS Surprise Apple Inc. price-consensus-eps-surprise-chart | Apple Inc. Quote For the fiscal second quarter, Services revenues are expected to grow year over year despite challenging macroeconomic conditions, as well as weakness in digital advertising and gaming. Apple shares have outperformed the Zacks Computer and Technology sector in the past year. While AAPL shares have declined 1.4%, Netflix, Disney and Amazon shares have declined 11.5%, 27.4% and 36%, respectively. Estimates on the Rise The Zacks Consensus Estimate for Apple\\u2019s fiscal second-quarter earnings has increased by a penny to $1.44 over the past 30 days. Apple expects the fiscal second quarter\\u2019s year-over-year revenue growth to be similar to that of the December (fiscal first) quarter due to unfavorable forex. In the previous quarter, net sales decreased 5.5% year over year to $117.15 billion. Unfavorable forex hurt revenues by more than 800 basis points. For iPhone, Apple expects the March quarter\\u2019s year-over-year revenue growth to accelerate relative to the December quarter\\u2019s year-over-year revenue growth. For Mac and iPad, this Zacks Rank #3 (Hold) company expects revenues to decline double digits on a year-over-year basis due to challenging comparison and macroeconomic headwinds. You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. Free Report Reveals How You Could Profit from the Growing Electric Vehicle Industry Globally, electric car sales continue their remarkable growth even after breaking records in 2021. High gas prices have fueled his demand, but so has evolving EV comfort, features and technology. So, the fervor for EVs will be around long after gas prices normalize. Not only are manufacturers seeing record-high profit\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.076192, "explanation": "The actual 21-day forward return for XLE starting 2023-03-14 was +7.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.076192, "horizon_days": 21, "hist_return": -0.048252, "annualized_vol": 0.259219, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240311_0363", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-03-11", "context_summary": "EEM over past 60 days: cumulative return +6.0%, annualized vol 14.8%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=36.74, end=38.93, cumulative_return=+6.0%, annualized_volatility=14.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.37, 'breakeven_10y': 2.28, 'hy_oas': 3.26, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 14.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 0000731766 2023-06-30 iso4217:USD 0000731766 2024-01-31 xbrli:shares 0000731766 2023-12-31 0000731766 2022-12-31 iso4217:USD xbrli:shares 0000731766 2022-01-01 2022-12-31 0000731766 2021-01-01 2021-12-31 0000731766 us-gaap:ProductMember 2023-01-01 2023-12-31 0000731766 us-gaap:ProductMember 2022-01-01 2022-12-31 0000731766 us-gaap:ProductMember 2021-01-01 2021-12-31 0000731766 us-gaap:ServiceMember 2023-01-01 2023-12-31 0000731766 us-gaap:ServiceMember 2022-01-01 2022-12-31 0000731766 us-gaap:ServiceMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2020-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2020-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2020-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2020-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2020-12-31 0000731766 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2021-01-01 2021-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2021-01-01 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2022-12-31 0000731766 us-gaap:CommonStockMember 2022-01-01 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-01-01 2022-12-31 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-12-31 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-12-31 0000731766 us-gaap:CommonStockMember 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-12-31 0000731766 unh:EmployeeStockPurchasePlanESPPMember 2023-01-01 2023-12-31 xbrli:pure 0000731766 2024-01-01 2023-12-31 0000731766 unh:ProductsandservicesMember 2023-12-31 0000731766 unh:ProductsandservicesMember 2022-12-31 0000731766 us-gaap:HealthInsuranceProductLineMember 2023-12-31 0000731766 unh:PharmaceuticalManufacturerRebatesReceivableMember 2023-12-31 0000731766 unh:PharmaceuticalManufacturerRebatesReceivableMember 2022-12-31 0000731766 unh:UsefulLifeMember 2023-01-01 2023-12-31 0000731766 us-gaap:FurnitureAndFixturesMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:FurnitureAndFixturesMember 2023-12-31 0000731766 us-gaap:BuildingMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:BuildingMember 2023-12-31 0000731766 unh:CapitalizedsoftwareMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember unh:CapitalizedsoftwareMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2021-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-01-01 2023-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-01-01 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-12-31 0000731766 us-gaap:RestrictedStockMember 2023-01-01 2023-12-31 0000731766 unh:StockOptionsandSARsMember 2023-01-01 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2022-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2022-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nPredict whether the return of EEM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.007822, "explanation": "The actual 21-day forward return for EEM starting 2024-03-11 was +0.78%, which classifies as 'flat'.", "metadata": {"future_return": 0.007822, "horizon_days": 21, "hist_return": 0.059668, "annualized_vol": 0.14806, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230321_0365", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-03-21", "context_summary": "USMV over past 60 days: cumulative return -2.4%, annualized vol 12.6%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=68.61, end=66.97, cumulative_return=-2.4%, annualized_volatility=12.6%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.45, 't10y3m_spread': -1.34, 'breakeven_10y': 2.14, 'hy_oas': 5.15, 'ig_oas': 1.62, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 24.14999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-20] [\"Kremlin tells officials to stop using iPhones - Kommersant newspaper Adds Kremlin quote, recasts lead MOSCOW, March 20 (Reuters) - The Kremlin told officials involved in preparations for Russia's 2024 presidential election to stop using Apple AAPL.O iPhones because of concerns that the devices are vulnerable to Western intelligence agencies, the Kommersant newspaper reported. At a Kremlin-organised seminar for officials involved in domestic politics, Sergei Kiriyenko, first deputy head of the presidential administration, told officials to change their phones by April 1, Kommersant said, citing unidentified sources. \\\"It's all over for the iPhone: either throw it away or give it to the children,\\\" Kommersant quoted one of the participants of the meeting as saying. \\\"Everyone will have to do it in March.\\\" When asked about the issue on Monday, Kremlin spokesman Dmitry Peskov said he could not confirm the report. \\\"Smartphones should not be used for official business,\\\" Peskov told reporters. \\\"Any smartphone has a fairly transparent mechanism, no matter what operating system it has \\u2013 Android or iOS. Naturally, they are not used for official purposes.\\\" Apple did not immediately respond to a request for comment. The Kremlin may provide other devices with different operating systems to replace the iPhones, Kommersant said, adding that the order to cease using iPhones had been directed at those involved in domestic politics - for which Kiriyenko is responsible. President Vladimir Putin has always said he has no smartphone, though Peskov has said Putin does use the Internet from time to time. Shortly after Russia sent its troops into Ukraine last year, U.S. and British spies claimed a scoop by uncovering - and going public with - intelligence that Putin was planning to invade. It is unclear how the spies obtained such intelligence. (Reporting by Guy Faulconbridge; Editing by Mark Trevelyan and Gareth Jones) ((guy.faulconbridge@thomsonreuters.com; 07825218698;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple (AAPL) Outpaces Stock Market Gains: What You Should Know Apple (AAPL) closed at $157.40 in the latest trading session, marking a +1.55% move from the prior day. This move outpaced the S&P 500's daily gain of 0.89%. At the same time, the Dow added 1.2%, and the tech-heavy Nasdaq lost 0.68%. Coming into today, shares of the maker of iPhones, iPads and other products had gained 1.61% in the past month. In that same time, the Computer and Technology sector gained 2.42%, while the S&P 500 lost 3.9%. Investors will be hoping for strength from Apple as it approaches its next earnings release. On that day, Apple is projected to report earnings of $1.44 per share, which would represent a year-over-year decline of 5.26%. Our most recent consensus estimate is calling for quarterly revenue of $93.39 billion, down 4% from the year-ago period. Looking at the ful\n\nPredict whether the return of USMV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.043008, "explanation": "The actual 21-day forward return for USMV starting 2023-03-21 was +4.30%, which classifies as 'positive'.", "metadata": {"future_return": 0.043008, "horizon_days": 21, "hist_return": -0.023993, "annualized_vol": 0.125878, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230804_0368", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-08-04", "context_summary": "SOL-USD over past 60 days: cumulative return +12.8%, annualized vol 75.7%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=20.08, end=22.64, cumulative_return=+12.8%, annualized_volatility=75.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.7, 't10y3m_spread': -1.34, 'breakeven_10y': 2.37, 'hy_oas': 3.98, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 15.920000076293944}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-03] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.105332, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-08-04 was -10.53%, which classifies as 'negative'.", "metadata": {"future_return": -0.105332, "horizon_days": 21, "hist_return": 0.127571, "annualized_vol": 0.756504, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230828_0371", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-08-28", "context_summary": "XLU over past 60 days: cumulative return -0.5%, annualized vol 14.6%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=29.40, end=29.26, cumulative_return=-0.5%, annualized_volatility=14.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.78, 't10y3m_spread': -1.36, 'breakeven_10y': 2.33, 'hy_oas': 3.9, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.23, 'vix': 15.68000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-25] [\"After Hours Most Active for Aug 25, 2023 : AAPL, VHNA, QQQ, JNJ, MSFT, TNET, CSX, SWN, GOOG, PFE, NEE, XOM The NASDAQ 100 After Hours Indicator is down -7.75 to 14,934.08. The total After hours volume is currently 60,938,515 shares traded. The following are the most active stocks for the after hours session: Apple Inc. (AAPL) is -0.1 at $178.51, with 4,158,333 shares traded. Over the last four weeks they have had 5 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2023. The consensus EPS forecast is $1.38. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". Vahanna Tech Edge Acquisition I Corp. (VHNA) is +1.13 at $10.78, with 2,686,719 shares traded. Invesco QQQ Trust, Series 1 (QQQ) is -0.03 at $363.99, with 2,155,255 shares traded. This represents a 43.16% increase from its 52 Week Low. Johnson & Johnson (JNJ) is +0.16 at $166.41, with 1,768,190 shares traded. JNJ's current last sale is 90.44% of the target price of $184. Microsoft Corporation (MSFT) is -0.28 at $322.70, with 1,758,809 shares traded. Over the last four weeks they have had 12 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2023. The consensus EPS forecast is $2.65. As reported by Zacks, the current mean recommendation for MSFT is in the \\\"buy range\\\". TriNet Group, Inc. (TNET) is unchanged at $106.06, with 1,657,714 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2023. The consensus EPS forecast is $1.2. TNET's current last sale is 93.44% of the target price of $113.5. CSX Corporation (CSX) is unchanged at $30.91, with 1,500,775 shares traded. As reported by Zacks, the current mean recommendation for CSX is in the \\\"buy range\\\". Southwestern Energy Company (SWN) is unchanged at $6.47, with 1,331,729 shares traded. Over the last four weeks they have had 6 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $0.16. SWN's current last sale is 80.88% of the target price of $8. Alphabet Inc. (GOOG) is -0.11 at $130.58, with 1,250,516 shares traded. Over the last four weeks they have had 6 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2023. The consensus EPS forecast is $1.45. As reported by Zacks, the current mean recommendation for GOOG is in the \\\"buy range\\\". Pfizer, Inc. (PFE) is +0.01 at $36.39, with 1,125,794 shares traded. PFE's current last sale is 81.78% of the target price of $44.5. NextEra Energy, Inc. (NEE) is unchanged at $67.96, with 898,026 shares traded. As reported by Zacks, the current mean recommendation for NEE is in the \\\"buy range\\\". Exxon Mobil Corporation (XOM) is -0.14 at $108.11, with 892,337 shares traded. Over the last four weeks they have had 4 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $2.09. XOM's current last sale is 86.49% of the targe\n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.047198, "explanation": "The actual 21-day forward return for XLU starting 2023-08-28 was -4.72%, which classifies as 'negative'.", "metadata": {"future_return": -0.047198, "horizon_days": 21, "hist_return": -0.004782, "annualized_vol": 0.14593, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230123_0374", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-01-23", "context_summary": "BTC-USD over past 60 days: cumulative return +36.8%, annualized vol 31.9%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=16604.46, end=22720.42, cumulative_return=+36.8%, annualized_volatility=31.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.66, 't10y3m_spread': -1.24, 'breakeven_10y': 2.23, 'hy_oas': 4.35, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.15, 'vix': 19.850000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-22] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.049111, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-01-23 was -4.91%, which classifies as 'negative'.", "metadata": {"future_return": -0.049111, "horizon_days": 21, "hist_return": 0.368332, "annualized_vol": 0.318679, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231120_0377", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-11-20", "context_summary": "XLI over past 60 days: cumulative return -0.5%, annualized vol 14.6%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=102.29, end=101.81, cumulative_return=-0.5%, annualized_volatility=14.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.44, 't10y3m_spread': -1.06, 'breakeven_10y': 2.28, 'hy_oas': 3.99, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 7.44, 'vix': 13.800000190734863}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-17] [\"After Hours Most Active for Nov 17, 2023 : MMM, QQQ, MATV, AAPL, NU, VCSH, MSFT, STRO, AMZN, KEY, VZ, BAC The NASDAQ 100 After Hours Indicator is down -17.07 to 15,820.92. The total After hours volume is currently 90,330,083 shares traded. The following are the most active stocks for the after hours session: 3M Company (MMM) is unchanged at $95.34, with 4,398,341 shares traded. MMM's current last sale is 90.37% of the target price of $105.5. Invesco QQQ Trust, Series 1 (QQQ) is -0.27 at $385.77, with 3,562,042 shares traded. This represents a 48.53% increase from its 52 Week Low. Mativ Holdings, Inc. (MATV) is unchanged at $13.71, with 3,402,922 shares traded. As reported by Zacks, the current mean recommendation for MATV is in the \\\"strong buy range\\\". Apple Inc. (AAPL) is +0.09 at $189.78, with 3,138,577 shares traded. Over the last four weeks they have had 4 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2024. The consensus EPS forecast is $1.59. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". Nu Holdings Ltd. (NU) is unchanged at $8.07, with 2,492,283 shares traded. As reported by Zacks, the current mean recommendation for NU is in the \\\"buy range\\\". Vanguard Short-Term Corporate Bond ETF (VCSH) is unchanged at $75.77, with 2,294,246 shares traded. This represents a 1.8% increase from its 52 Week Low. Microsoft Corporation (MSFT) is -1.59 at $368.26, with 2,231,678 shares traded. Over the last four weeks they have had 13 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $2.75. As reported by Zacks, the current mean recommendation for MSFT is in the \\\"buy range\\\". Sutro Biopharma, Inc. (STRO) is unchanged at $2.69, with 1,857,662 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $-0.81. As reported by Zacks, the current mean recommendation for STRO is in the \\\"buy range\\\". Amazon.com, Inc. (AMZN) is -0.09 at $145.09, with 1,804,116 shares traded. Over the last four weeks they have had 12 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $0.77. As reported by Zacks, the current mean recommendation for AMZN is in the \\\"buy range\\\". KeyCorp (KEY) is -0.02 at $12.30, with 1,493,925 shares traded. Over the last four weeks they have had 4 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2024. The consensus EPS forecast is $0.26. KEY's current last sale is 94.62% of the target price of $13. Verizon Communications Inc. (VZ) is +0.04 at $36.27, with 1,489,000 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2024. The consensus EPS forecast is $1.17. VZ's current last sale is 88.46% of the target price of $41. Bank of America Corporation (BAC) is -0.\n\nPredict whether the return of XLI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.057771, "explanation": "The actual 21-day forward return for XLI starting 2023-11-20 was +5.78%, which classifies as 'positive'.", "metadata": {"future_return": 0.057771, "horizon_days": 21, "hist_return": -0.004691, "annualized_vol": 0.14551, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240205_0379", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-02-05", "context_summary": "QUAL over past 60 days: cumulative return +13.8%, annualized vol 10.5%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=132.55, end=150.88, cumulative_return=+13.8%, annualized_volatility=10.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.33, 't10y3m_spread': -1.4, 'breakeven_10y': 2.21, 'hy_oas': 3.47, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 13.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent 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us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-09-30 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2022-12-31 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2023-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2022-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2023-12-31 0001018724 amzn:VendorAccountsReceivableMember 2022-12-31 0001018724 amzn:VendorAccountsReceivableMember 2023-12-31 0001018724 us-gaap:LoansReceivableMember 2022-12-31 0001018724 us-gaap:LoansReceivableMember 2023-12-31 00 [...TRUNCATED...] tents 32.2 Certification of Brian T. Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.048375, "explanation": "The actual 21-day forward return for QUAL starting 2024-02-05 was +4.84%, which classifies as 'positive'.", "metadata": {"future_return": 0.048375, "horizon_days": 21, "hist_return": 0.138258, "annualized_vol": 0.104908, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240513_0382", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-05-13", "context_summary": "XLI over past 60 days: cumulative return +6.2%, annualized vol 10.8%. Market regime: bull.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=115.09, end=122.19, cumulative_return=+6.2%, annualized_volatility=10.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.37, 't10y3m_spread': -0.97, 'breakeven_10y': 2.34, 'hy_oas': 3.12, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 12.550000190734863}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.015821, "explanation": "The actual 21-day forward return for XLI starting 2024-05-13 was -1.58%, which classifies as 'negative'.", "metadata": {"future_return": -0.015821, "horizon_days": 21, "hist_return": 0.061718, "annualized_vol": 0.108245, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20231129_0385", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-11-29", "context_summary": "XLP over past 60 days: cumulative return -0.7%, annualized vol 11.6%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=66.38, end=65.90, cumulative_return=-0.7%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.39, 't10y3m_spread': -1.13, 'breakeven_10y': 2.22, 'hy_oas': 3.9, 'ig_oas': 1.14, 'ted_spread': 0.09, 'mortgage_30y': 7.29, 'vix': 12.6899995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-28] [\"AAPL Quantitative Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple to end credit-card partnership with Goldman Sachs - WSJ Adds details on the contract in paragraph 2 Nov 28 (Reuters) - Apple AAPL.O is pulling the plug on its credit-card partnership with Goldman Sachs Group GS.N, the Wall Street Journal reported on Tuesday. The tech giant recently sent a proposal to the Wall Street bank to exit the contract in the next roughly 12 \n\nPredict whether the return of XLP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.037394, "explanation": "The actual 21-day forward return for XLP starting 2023-11-29 was +3.74%, which classifies as 'positive'.", "metadata": {"future_return": 0.037394, "horizon_days": 21, "hist_return": -0.007159, "annualized_vol": 0.116442, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240527_0388", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-05-27", "context_summary": "QUAL over past 60 days: cumulative return +2.8%, annualized vol 12.5%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=158.78, end=163.20, cumulative_return=+2.8%, annualized_volatility=12.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.47, 't10y3m_spread': -1.0, 'breakeven_10y': 2.32, 'hy_oas': 3.11, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 11.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.030921, "explanation": "The actual 21-day forward return for QUAL starting 2024-05-27 was +3.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.030921, "horizon_days": 21, "hist_return": 0.027832, "annualized_vol": 0.125419, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230808_0391", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2023-08-08", "context_summary": "SGOV over past 60 days: cumulative return +0.8%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=88.05, end=88.76, cumulative_return=+0.8%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.67, 't10y3m_spread': -1.47, 'breakeven_10y': 2.41, 'hy_oas': 3.97, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 15.770000457763672}\nMarket regime: sideways\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00319, "explanation": "The actual 21-day forward return for SGOV starting 2023-08-08 was +0.32%, which classifies as 'flat'.", "metadata": {"future_return": 0.00319, "horizon_days": 21, "hist_return": 0.008089, "annualized_vol": 0.002086, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240206_0394", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-02-06", "context_summary": "XLB over past 60 days: cumulative return +5.7%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=36.71, end=38.82, cumulative_return=+5.7%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.29, 't10y3m_spread': -1.25, 'breakeven_10y': 2.27, 'hy_oas': 3.5, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 13.670000076293944}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent 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Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.090523, "explanation": "The actual 21-day forward return for XLB starting 2024-02-06 was +9.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.090523, "horizon_days": 21, "hist_return": 0.057389, "annualized_vol": 0.14265, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240124_0397", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-01-24", "context_summary": "USMV over past 60 days: cumulative return +12.4%, annualized vol 8.9%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=68.51, end=77.03, cumulative_return=+12.4%, annualized_volatility=8.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.17, 't10y3m_spread': -1.31, 'breakeven_10y': 2.29, 'hy_oas': 3.51, 'ig_oas': 1.01, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 12.550000190734863}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nPredict whether the return of USMV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.028675, "explanation": "The actual 21-day forward return for USMV starting 2024-01-24 was +2.87%, which classifies as 'positive'.", "metadata": {"future_return": 0.028675, "horizon_days": 21, "hist_return": 0.124374, "annualized_vol": 0.08899, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240418_0400", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-04-18", "context_summary": "ADA-USD over past 60 days: cumulative return -28.2%, annualized vol 74.1%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.62, end=0.44, cumulative_return=-28.2%, annualized_volatility=74.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.34, 't10y3m_spread': -0.86, 'breakeven_10y': 2.39, 'hy_oas': 3.42, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 18.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.011693, "explanation": "The actual 21-day forward return for ADA-USD starting 2024-04-18 was +1.17%, which classifies as 'positive'.", "metadata": {"future_return": 0.011693, "horizon_days": 21, "hist_return": -0.281929, "annualized_vol": 0.740701, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230719_0403", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-07-19", "context_summary": "LINK-USD over past 60 days: cumulative return +6.3%, annualized vol 59.7%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=6.51, end=6.92, cumulative_return=+6.3%, annualized_volatility=59.7%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.68, 'breakeven_10y': 2.23, 'hy_oas': 3.9, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 13.300000190734863}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-18] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.112293, "explanation": "The actual 21-day forward return for LINK-USD starting 2023-07-19 was +11.23%, which classifies as 'positive'.", "metadata": {"future_return": 0.112293, "horizon_days": 21, "hist_return": 0.063049, "annualized_vol": 0.596866, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230816_0405", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-08-16", "context_summary": "XRP-USD over past 60 days: cumulative return +27.1%, annualized vol 79.7%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.48, end=0.61, cumulative_return=+27.1%, annualized_volatility=79.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.71, 't10y3m_spread': -1.35, 'breakeven_10y': 2.32, 'hy_oas': 3.85, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 16.459999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-15] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.144622, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-08-16 was -14.46%, which classifies as 'negative'.", "metadata": {"future_return": -0.144622, "horizon_days": 21, "hist_return": 0.270554, "annualized_vol": 0.797433, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230116_0407", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-01-16", "context_summary": "VEA over past 60 days: cumulative return +22.8%, annualized vol 18.3%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=33.13, end=40.68, cumulative_return=+22.8%, annualized_volatility=18.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.73, 't10y3m_spread': -1.18, 'breakeven_10y': 2.18, 'hy_oas': 4.21, 'ig_oas': 1.32, 'ted_spread': 0.09, 'mortgage_30y': 6.33, 'vix': 18.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-13] [\"Tim Cook\\u2019s pay re-enters earth\\u2019s atmosphere Reuters Reuters NEW YORK (Reuters Breakingviews) - How to compensate Apple Chief Executive Tim Cook is one of the more puzzling questions for corporate governance experts. His pay has been out of this world, but then so has the iPhone maker\\u2019s share price performance. Nonetheless Apple, its investors and its board have agreed Cook\\u2019s pay should orbit closer to Earth in 2023. The $2.1 trillion company has comfortably outperformed rivals over the past three years, with shareholder returns including reinvested dividends in the top percentile among its peers, according to Institutional Shareholder Services. Likewise, his annual compensation of $99 million in 2022 was over 4 times the median of peers, who include Amazon.com\\u2019s Andrew Jassy and AT&T\\u2019s John Stankey. On Friday, Apple said Cook\\u2019s targeted pay will fall to $49 million. That\\u2019s an improvement, but still generous. Apple says it will target his pay between 80th and 90th percentile among peers in future years. A bigger improvement is making Cook\\u2019s pay less of a giveaway. In 2022, half of his award of Apple stock paid out automatically over time \\u2013 so all he had to do is wait. Now it\\u2019s 75% performance-based, and his unvested time-based awards lapse if he retires. This is hardly space-age stuff, but at least Apple\\u2019s pay is no longer stuck in the past. (By Robert Cyran) Follow @Breakingviews on Twitter Capital Calls - More concise insights on global finance: BlackRock edges closer to its Blackstone roots The fog lifts for Didi's path to normalcy Inflation drop gives Fed leeway to save jobs Gaming\\u2019s winter of discontent bolsters M&A logic TSMC foots the bill for global chip supremacy (Editing by John Foley and Amanda Gomez) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Don't Ignore These Companies' Cash-Generating Abilities It goes without saying that searching for stocks can be challenging, especially with an extensive list of options available. However, one way to cut out the bad apples is by focusing on stocks with strong free cash flow. But what is free cash flow, and why does it matter? In its simplest form, free cash flow is the amount of cash a company keeps after paying for operating costs and capital expenditures. A high free cash flow allows for more growth opportunities, a greater potential for share buybacks, consistent dividend payouts, and the ability to pay off debt easily. Three companies \\u2013 Apple AAPL, Alphabet GOOGL, and Verizon Communications VZ \\u2013 all generate substantial cash. Below is a chart illustrating the performance of all three stocks over the last year, with the S&P 500 blended in as a benchmark. Image Source: Zacks Investment Research Let\\u2019s take a closer look at each one. Apple We\\u2019re all familiar with the legendary Apple, the company that\\u2019s entirely ch\n\nPredict whether the return of VEA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.005758, "explanation": "The actual 21-day forward return for VEA starting 2023-01-16 was +0.58%, which classifies as 'flat'.", "metadata": {"future_return": 0.005758, "horizon_days": 21, "hist_return": 0.22805, "annualized_vol": 0.183482, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241023_0410", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-10-23", "context_summary": "ICSH over past 60 days: cumulative return +0.8%, annualized vol 0.4%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=46.92, end=47.30, cumulative_return=+0.8%, annualized_volatility=0.4%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.17, 't10y3m_spread': -0.52, 'breakeven_10y': 2.33, 'hy_oas': 2.92, 'ig_oas': 0.85, 'ted_spread': 0.09, 'mortgage_30y': 6.44, 'vix': 18.200000762939453}\nMarket regime: sideways\n\nPredict whether the return of ICSH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00188, "explanation": "The actual 21-day forward return for ICSH starting 2024-10-23 was +0.19%, which classifies as 'flat'.", "metadata": {"future_return": 0.00188, "horizon_days": 21, "hist_return": 0.007955, "annualized_vol": 0.003674, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230405_0412", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-04-05", "context_summary": "XLU over past 60 days: cumulative return -4.8%, annualized vol 18.4%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=32.36, end=30.82, cumulative_return=-4.8%, annualized_volatility=18.4%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.49, 't10y3m_spread': -1.53, 'breakeven_10y': 2.25, 'hy_oas': 4.73, 'ig_oas': 1.43, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 19.0}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-04] [\"Wall Street Analysts Think Apple (AAPL) Is a Good Investment: Is It? The recommendations of Wall Street analysts are often relied on by investors when deciding whether to buy, sell, or hold a stock. Media reports about these brokerage-firm-employed (or sell-side) analysts changing their ratings often affect a stock's price. Do they really matter, though? Before we discuss the reliability of brokerage recommendations and how to use them to your advantage, let's see what these Wall Street heavyweights think about Apple (AAPL). Apple currently has an average brokerage recommendation (ABR) of 1.35, on a scale of 1 to 5 (Strong Buy to Strong Sell), calculated based on the actual recommendations (Buy, Hold, Sell, etc.) made by 24 brokerage firms. An ABR of 1.35 approximates between Strong Buy and Buy. Of the 24 recommendations that derive the current ABR, 18 are Strong Buy and three are Buy. Strong Buy and Buy respectively account for 75% and 12.5% of all recommendations. Brokerage Recommendation Trends for AAPL Check price target & stock forecast for Apple here>>> The ABR suggests buying Apple, but making an investment decision solely on the basis of this information might not be a good idea. According to several studies, brokerage recommendations have little to no success guiding investors to choose stocks with the most potential for price appreciation. Do you wonder why? As a result of the vested interest of brokerage firms in a stock they cover, their analysts tend to rate it with a strong positive bias. According to our research, brokerage firms assign five \\\"Strong Buy\\\" recommendations for every \\\"Strong Sell\\\" recommendation. This means that the interests of these institutions are not always aligned with those of retail investors, giving little insight into the direction of a stock's future price movement. It would therefore be best to use this information to validate your own analysis or a tool that has proven to be highly effective at predicting stock price movements. Zacks Rank, our proprietary stock rating tool with an impressive externally audited track record, categorizes stocks into five groups, ranging from Zacks Rank #1 (Strong Buy) to Zacks Rank #5 (Strong Sell), and is an effective indicator of a stock's price performance in the near future. Therefore, using the ABR to validate the Zacks Rank could be an efficient way of making a profitable investment decision. Zacks Rank Should Not Be Confused With ABR Although both Zacks Rank and ABR are displayed in a range of 1-5, they are different measures altogether. The ABR is calculated solely based on brokerage recommendations and is typically displayed with decimals (example: 1.28). In contrast, the Zacks Rank is a quantitative model allowing investors to harness the power of earnings estimate revisions. It is displayed in whole numbers -- 1 to 5. It has been and continues to be the case that analysts employed by brokerage firms are overly optimistic with their recommendations. Because o\n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.004184, "explanation": "The actual 21-day forward return for XLU starting 2023-04-05 was -0.42%, which classifies as 'flat'.", "metadata": {"future_return": -0.004184, "horizon_days": 21, "hist_return": -0.047733, "annualized_vol": 0.18433, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241127_0415", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-11-27", "context_summary": "DOT-USD over past 60 days: cumulative return +68.1%, annualized vol 94.0%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.81, end=8.08, cumulative_return=+68.1%, annualized_volatility=94.0%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.09, 't10y3m_spread': -0.31, 'breakeven_10y': 2.28, 'hy_oas': 2.68, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.84, 'vix': 14.100000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.091613, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-11-27 was -9.16%, which classifies as 'negative'.", "metadata": {"future_return": -0.091613, "horizon_days": 21, "hist_return": 0.680879, "annualized_vol": 0.94041, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240805_0417", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-08-05", "context_summary": "XLB over past 60 days: cumulative return -0.3%, annualized vol 13.1%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=43.64, end=43.52, cumulative_return=-0.3%, annualized_volatility=13.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.08, 't10y3m_spread': -1.49, 'breakeven_10y': 2.04, 'hy_oas': 3.72, 'ig_oas': 1.06, 'ted_spread': 0.09, 'mortgage_30y': 6.73, 'vix': 23.38999938964844}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q AAPL 2024-08-02] aapl-20240629 false 2024 Q3 0000320193 --09-28 P1Y P1Y P1Y P1Y http://fasb.org/us-gaap/2023#MarketableSecuritiesCurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesNoncurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesCurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesNoncurrent http://fasb.org/us-gaap/2023#LongTermDebtCurrent http://fasb.org/us-gaap/2023#LongTermDebtNoncurrent http://fasb.org/us-gaap/2023#LongTermDebtCurrent 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repurchase program. As of June 29, 2024, remaining availability under the May 2023 program was $4.1 billion. On May 2, 2024, the Board of Directors authorized an additional program to repurchase up to $110 billion of the Company’s common stock. The programs do not obligate the Company to acquire a minimum amount of shares. Under the programs, shares may be repurchased in privately negotiated or open market transactions, including under plans complying with Rule 10b5-1 under the Exchange Act. Item 3.    Defaults Upon Senior Securities None. Item 4.    Mine Safety Disclosures Not applicable. Item 5.    Other Information Insider Trading Arrangements On May 24, 2024 , Tim Cook , the Company’s Chief Executive Officer , entered into a trading plan intended to satisfy the affirmative defense conditions of Rule 10b5-1(c) under the Exchange Act. The plan provides for the sale, subject to certain price limits, of shares vesting during the duration of the plan pursuant to certain equity awards granted to Mr. Cook, excluding shares withheld by the Company to satisfy income tax withholding and remittance obligations. Mr. Cook’s plan will expire on May 24, 2026, subject to early termination in accordance with the terms of the plan. Apple Inc. | Q3 2024 Form 10-Q | 20 Item 6.    Exhibits Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 31.1* Rule 13a-14(a) / 15d-14(a) Certification of Chief Executive Officer. 31.2* Rule 13a-14(a) / 15d-14(a) Certification of Chief Financial Officer. 32.1** Section 1350 Certifications of Chief Executive Officer and Chief Financial Officer. 101* Inline XBRL Document Set for the condensed consolidated financial statements and accompanying notes in Part I, Item 1, “Financial Statements” of this Quarterly Report on Form 10-Q. 104* Inline XBRL for the cover page of this Quarterly Report on Form 10-Q, included in the Exhibit 101 Inline XBRL Document Set. *    Filed herewith. **    Furnished herewith. Apple Inc. | Q3 2024 Form 10-Q | 21 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: August 1, 2024 Apple Inc. By: /s/ Luca Maestri Luca Maestri Senior Vice President, Chief Financial Officer Apple Inc. | Q3 2024 Form 10-Q | 22\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.042372, "explanation": "The actual 21-day forward return for XLB starting 2024-08-05 was +4.24%, which classifies as 'positive'.", "metadata": {"future_return": 0.042372, "horizon_days": 21, "hist_return": -0.002768, "annualized_vol": 0.131006, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240904_0420", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2024-09-04", "context_summary": "SOYB over past 60 days: cumulative return -10.0%, annualized vol 18.8%. Market regime: bull.", "question": "Asset: SOYB\nHistorical prices (past 60 trading days): start=24.63, end=22.17, cumulative_return=-10.0%, annualized_volatility=18.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.04, 't10y3m_spread': -1.35, 'breakeven_10y': 2.11, 'hy_oas': 3.31, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 20.71999931335449}\nMarket regime: bull\n\nPredict whether the return of SOYB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.024631, "explanation": "The actual 21-day forward return for SOYB starting 2024-09-04 was +2.46%, which classifies as 'positive'.", "metadata": {"future_return": 0.024631, "horizon_days": 21, "hist_return": -0.099878, "annualized_vol": 0.187918, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241004_0423", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2024-10-04", "context_summary": "VTI over past 60 days: cumulative return +2.6%, annualized vol 16.5%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=267.99, end=274.91, cumulative_return=+2.6%, annualized_volatility=16.5%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.15, 't10y3m_spread': -0.83, 'breakeven_10y': 2.21, 'hy_oas': 3.04, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.12, 'vix': 20.489999771118164}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.003643, "explanation": "The actual 21-day forward return for VTI starting 2024-10-04 was -0.36%, which classifies as 'flat'.", "metadata": {"future_return": -0.003643, "horizon_days": 21, "hist_return": 0.025833, "annualized_vol": 0.164933, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20241230_0426", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-12-30", "context_summary": "BTC-USD over past 60 days: cumulative return +33.2%, annualized vol 46.3%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=70215.19, end=93530.23, cumulative_return=+33.2%, annualized_volatility=46.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.31, 't10y3m_spread': 0.31, 'breakeven_10y': 2.34, 'hy_oas': 2.84, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 15.949999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.101178, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-12-30 was +10.12%, which classifies as 'positive'.", "metadata": {"future_return": 0.101178, "horizon_days": 21, "hist_return": 0.332051, "annualized_vol": 0.462732, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230621_0429", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2023-06-21", "context_summary": "UNG over past 60 days: cumulative return -0.7%, annualized vol 58.2%. Market regime: sideways.", "question": "Asset: UNG\nHistorical prices (past 60 trading days): start=27.60, end=27.40, cumulative_return=-0.7%, annualized_volatility=58.2%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.65, 'breakeven_10y': 2.22, 'hy_oas': 4.22, 'ig_oas': 1.35, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.880000114440918}\nMarket regime: sideways\n\nPredict whether the return of UNG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.019608, "explanation": "The actual 21-day forward return for UNG starting 2023-06-21 was -1.96%, which classifies as 'negative'.", "metadata": {"future_return": -0.019608, "horizon_days": 21, "hist_return": -0.007246, "annualized_vol": 0.581505, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240116_0431", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-01-16", "context_summary": "ETH-USD over past 60 days: cumulative return +28.0%, annualized vol 46.1%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1961.28, end=2511.36, cumulative_return=+28.0%, annualized_volatility=46.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.18, 't10y3m_spread': -1.49, 'breakeven_10y': 2.27, 'hy_oas': 3.54, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.66, 'vix': 12.699999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.083275, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-01-16 was -8.33%, which classifies as 'negative'.", "metadata": {"future_return": -0.083275, "horizon_days": 21, "hist_return": 0.280471, "annualized_vol": 0.461401, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240723_0434", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-07-23", "context_summary": "ETH-USD over past 60 days: cumulative return -7.7%, annualized vol 36.6%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3726.93, end=3440.42, cumulative_return=-7.7%, annualized_volatility=36.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.24, 't10y3m_spread': -1.17, 'breakeven_10y': 2.3, 'hy_oas': 3.05, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 14.90999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.223528, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-07-23 was -22.35%, which classifies as 'negative'.", "metadata": {"future_return": -0.223528, "horizon_days": 21, "hist_return": -0.076877, "annualized_vol": 0.365736, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240221_0437", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-02-21", "context_summary": "AVAX-USD over past 60 days: cumulative return -19.8%, annualized vol 74.1%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=48.07, end=38.53, cumulative_return=-19.8%, annualized_volatility=74.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.32, 't10y3m_spread': -1.17, 'breakeven_10y': 2.32, 'hy_oas': 3.37, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 15.420000076293944}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.460013, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-02-21 was +46.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.460013, "horizon_days": 21, "hist_return": -0.198466, "annualized_vol": 0.740787, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231130_0440", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-11-30", "context_summary": "DOT-USD over past 60 days: cumulative return +21.3%, annualized vol 51.0%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.26, end=5.17, cumulative_return=+21.3%, annualized_volatility=51.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.37, 't10y3m_spread': -1.18, 'breakeven_10y': 2.21, 'hy_oas': 3.8, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 7.29, 'vix': 12.979999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-29] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.529788, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-11-30 was +52.98%, which classifies as 'positive'.", "metadata": {"future_return": 0.529788, "horizon_days": 21, "hist_return": 0.212879, "annualized_vol": 0.510455, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241014_0443", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2024-10-14", "context_summary": "SCHH over past 60 days: cumulative return +7.3%, annualized vol 13.3%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=20.04, end=21.50, cumulative_return=+7.3%, annualized_volatility=13.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.13, 't10y3m_spread': -0.65, 'breakeven_10y': 2.33, 'hy_oas': 2.98, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 20.459999084472656}\nMarket regime: sideways\n\nPredict whether the return of SCHH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.017652, "explanation": "The actual 21-day forward return for SCHH starting 2024-10-14 was -1.77%, which classifies as 'negative'.", "metadata": {"future_return": -0.017652, "horizon_days": 21, "hist_return": 0.073195, "annualized_vol": 0.133182, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230829_0446", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-08-29", "context_summary": "SOL-USD over past 60 days: cumulative return +8.8%, annualized vol 62.9%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=18.90, end=20.56, cumulative_return=+8.8%, annualized_volatility=62.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.78, 't10y3m_spread': -1.38, 'breakeven_10y': 2.3, 'hy_oas': 3.86, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.23, 'vix': 15.079999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-28] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.080097, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-08-29 was -8.01%, which classifies as 'negative'.", "metadata": {"future_return": -0.080097, "horizon_days": 21, "hist_return": 0.087831, "annualized_vol": 0.62911, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230413_0449", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-04-13", "context_summary": "BNB-USD over past 60 days: cumulative return +1.9%, annualized vol 39.4%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=312.93, end=318.95, cumulative_return=+1.9%, annualized_volatility=39.4%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.54, 't10y3m_spread': -1.61, 'breakeven_10y': 2.27, 'hy_oas': 4.62, 'ig_oas': 1.43, 'ted_spread': 0.09, 'mortgage_30y': 6.28, 'vix': 19.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-12] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.003173, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-04-13 was -0.32%, which classifies as 'flat'.", "metadata": {"future_return": -0.003173, "horizon_days": 21, "hist_return": 0.019251, "annualized_vol": 0.393539, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240816_0451", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-08-16", "context_summary": "ADA-USD over past 60 days: cumulative return -19.0%, annualized vol 61.7%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.40, end=0.33, cumulative_return=-19.0%, annualized_volatility=61.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.16, 't10y3m_spread': -1.42, 'breakeven_10y': 2.12, 'hy_oas': 3.31, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.49, 'vix': 15.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.047671, "explanation": "The actual 21-day forward return for ADA-USD starting 2024-08-16 was -4.77%, which classifies as 'negative'.", "metadata": {"future_return": -0.047671, "horizon_days": 21, "hist_return": -0.190177, "annualized_vol": 0.616966, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230622_0454", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-06-22", "context_summary": "XLY over past 60 days: cumulative return +16.7%, annualized vol 17.9%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=69.22, end=80.80, cumulative_return=+16.7%, annualized_volatility=17.9%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.68, 'breakeven_10y': 2.21, 'hy_oas': 4.32, 'ig_oas': 1.35, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.199999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-21] [\"Quality Dividend Growth ETF DGRW Hits Ten Years While the three-year ETF milestone has plenty of importance, consider the power of the ten year ETF birthday. That\\u2019s the news for the WisdomTree U.S. Quality Dividend Growth Fund (DGRW) which had its ten year birthday in May. As part of its birthday celebrations, the strategy also added $268.6 million in net inflows, enough to lift the quality dividend ETF above $9 billion in AUM. That should invite advisors to consider the potent combination of quality and dividends. DGRW tracks the WisdomTree U.S. Quality Dividend Growth Index for a 28 basis point fee, and offers a 2.01% annual dividend yield as of May. The index tracks the performance of large and mid-cap dividend-paying U.S. stocks that fit a growth framework. DGRW focuses on dividend growth potential rather than just looking backwards at past dividend increases. It does so by looking at forward-looking earnings estimates based on things like historical return on assets (ROA) and return on equity (ROE). That approach has helped the quality dividend growth ETF outperform the S&P 500 Index by 0.22% annually over the last ten years. The strategy goes back to some solid research from the firm\\u2019s now Global CIO Jeremy Schwartz and Global Head of Research Christopher Gannatti. Those white papers focused on the rationale behind using ROE and ROA with a forward-looking dividend growth screen. Combining the two has helped DGRW limit reliance on superficially high ROE figures caused by firms taking on leverage, for example. Together, that\\u2019s helped its index look forward compared to the NASDAQ U.S. Dividend Achievers Select Index which requires ten consecutive years of dividend growth. That requirement, DGRW\\u2019s managers fear, may fail to capture growth opportunities. See more: \\u201cDigging Into Up-and-Coming Quality Growth ETF QGRW\\u201d For example, Apple (AAPL) joined the WisdomTree U.S. Dividend Growth Index back in 2013, but wasn\\u2019t eligible for the NASDAQ index until 2023, per an old WisdomTree blog. Taken together, those research lessons have helped DGRW return 21% over the last year and 15.5% over the last three years. That\\u2019s helped DGRW outperform its ETF Database Category and Factset Segment averages in those time frames. For investors looking for a quality dividend growth ETF, DGRW stands out as one to consider. For more news, information, and analysis, visit the Modern Alpha Channel. Read more on ETFtrends.com. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Turnkey Tech Investing: May 2023 Market Brief For some time, markets have been grappling with a handful of counteracting dynamics, including the clash between the bulls and the bears, the interplay between stimulus and inflation, and the delicate balance between growth and rate hikes. Adding to the mix in May was the US debt-ceiling conundrum and, of course, the \\u2018emerge\n\nPredict whether the return of XLY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.021447, "explanation": "The actual 21-day forward return for XLY starting 2023-06-22 was +2.14%, which classifies as 'positive'.", "metadata": {"future_return": 0.021447, "horizon_days": 21, "hist_return": 0.167354, "annualized_vol": 0.179364, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240813_0456", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-08-13", "context_summary": "QUAL over past 60 days: cumulative return +2.0%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=162.27, end=165.51, cumulative_return=+2.0%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.11, 't10y3m_spread': -1.43, 'breakeven_10y': 2.11, 'hy_oas': 3.52, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.47, 'vix': 20.709999084472656}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-01-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-04-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-04-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-01-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2024-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-03-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-03-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-03-31 0000731766 us-gaap:NoncontrollingInterestMember 2024-03-31 0000731766 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-04-01 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-04-01 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-04-01 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-04-01 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-04-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000731766 us-gaap:RetainedEarningsMember 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-06-30 0000731766 us-gaap:CommonStockMember 2023-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-03-31 0000731766 us-gaap:RetainedEarningsMember 2023-03-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-03-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-03-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-03-31 0000731766 2023-03-31 0000731766 us-gaap:RetainedEarningsMember 2023-04-01 2023-06-30 0000731766 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us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2024-01-01 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-01-01 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-06-30 0000731766 unh:ProductsAndServicesMember 2024-06-30 0000731766 unh:ProductsAndServicesMember 2023-12-31 0000731766 2024-07-01 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2024-06-30 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2024-06-30 0000731766 us-gaap:CorporateDebtSecuritiesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.02929, "explanation": "The actual 21-day forward return for QUAL starting 2024-08-13 was +2.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.02929, "horizon_days": 21, "hist_return": 0.020022, "annualized_vol": 0.142937, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230104_0458", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-01-04", "context_summary": "QUAL over past 60 days: cumulative return +7.7%, annualized vol 22.9%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=101.78, end=109.62, cumulative_return=+7.7%, annualized_volatility=22.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.61, 't10y3m_spread': -0.74, 'breakeven_10y': 2.26, 'hy_oas': 4.7, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 22.89999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-03] [\"US STOCKS-Wall St starts the year with a dip; Apple, Tesla shares drag By Sin\\u00e9ad Carew and Amruta Khandekar Jan 3 (Reuters) - Wall Street's main indexes closed lower on the first trading day of 2023 with the biggest drags from Tesla and Apple, while investors worried about the Federal Reserve's interest-rate hiking path as they awaited minutes from its December meeting. Shares in electric vehicle maker Tesla Inc TSLA.O closed down 12% after hitting their lowest level since August 2020 and put pressure on the consumer discretionary sector .SPLRCD following a miss on Wall Street estimates for fourth-quarter deliveries. Apple Inc AAPL.O shares sank 3.7%, with the iPhone maker hitting its lowest level since June 2021, after a report from Nikkei Asia pointed to weaker demand. In addition, an analyst downgraded their rating of the stock due to production cuts in COVID-19-hit China. The energy sector .SPNY, which logged stellar gains in 2022, closed down 3.6% in the year's first trading day as oil prices fell on bleak business activity data from China and concerns about the global economic outlook. O/R. The main U.S. stock indexes in 2022 showed their steepest annual losses since 2008 following the Fed's fastest pace of rate hikes since the 1980s to stamp out decades-high inflation. \\\"2022 was a terrible year for equity markets. Some of the reasons for that haven't dissipated because we turned the calendar,\\\" said Michael James, managing director of equity trading at Wedbush Securities in Los Angeles. \\\"There's still elevated anxiety, uncertainty about the Fed and inflation. Until there's clarity on that, it's going to be tough to make any upside headway in equity markets.\\\" Given Apple and Tesla's clout in the market, James also cited specific concerns about them for broader S&P weakness Tuesday. The Dow Jones Industrial Average .DJI fell 10.88 points, or 0.03%, to 33,136.37; the S&P 500 .SPX lost 15.36 points, or 0.40%, to 3,824.14; and the Nasdaq Composite .IXIC dropped 79.50 points, or 0.76%, to 10,386.99. The S&P 500 had shed 19.4% in 2022, marking a roughly $8 trillion decline in market capitalization, while the Nasdaq fell 33.1%, dragged down by growth stocks. Among the S&P 500's 11 major sectors, behind energy, technology was the second biggest decliner, losing 1%, with Apple hastening the decline as it ended the day with a market valuation below $2 trillion for the first time since March 2021. Tesla's biggest daily percentage drop since September 2020 helped make the consumer discretionary index .SPLRCD the S&P's third weakest sector on the day with a 0.6% drop. The benchmark's biggest gainer on the day was communications services .SPLRCL, with Facebook parent Meta Platforms Inc META.O leading the advancers there with a gain of 3.7%. Investors on Wednesday will closely monitor the minutes of the Fed's December policy meeting, when the central bank raised interest rates by 50 basis points after four straight 75 basis points hikes and sign\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.088949, "explanation": "The actual 21-day forward return for QUAL starting 2023-01-04 was +8.89%, which classifies as 'positive'.", "metadata": {"future_return": 0.088949, "horizon_days": 21, "hist_return": 0.077038, "annualized_vol": 0.229153, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241217_0461", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2024-12-17", "context_summary": "MTUM over past 60 days: cumulative return +6.8%, annualized vol 12.7%. Market regime: bull.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=199.43, end=213.03, cumulative_return=+6.8%, annualized_volatility=12.7%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.14, 't10y3m_spread': 0.02, 'breakeven_10y': 2.32, 'hy_oas': 2.69, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 14.6899995803833}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 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us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of MTUM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.021814, "explanation": "The actual 21-day forward return for MTUM starting 2024-12-17 was +2.18%, which classifies as 'positive'.", "metadata": {"future_return": 0.021814, "horizon_days": 21, "hist_return": 0.068176, "annualized_vol": 0.126555, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230821_0463", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-08-21", "context_summary": "SOL-USD over past 60 days: cumulative return +30.8%, annualized vol 67.5%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=16.64, end=21.77, cumulative_return=+30.8%, annualized_volatility=67.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.66, 't10y3m_spread': -1.29, 'breakeven_10y': 2.32, 'hy_oas': 4.02, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 17.299999237060547}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-20] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.163573, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-08-21 was -16.36%, which classifies as 'negative'.", "metadata": {"future_return": -0.163573, "horizon_days": 21, "hist_return": 0.308284, "annualized_vol": 0.675373, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230713_0466", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-07-13", "context_summary": "XLK over past 60 days: cumulative return +16.9%, annualized vol 18.3%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=73.07, end=85.38, cumulative_return=+16.9%, annualized_volatility=18.3%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.86, 't10y3m_spread': -1.61, 'breakeven_10y': 2.26, 'hy_oas': 3.95, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 13.539999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-12] [\"Better Buy: AMD vs. Apple Tech stocks have enjoyed a rally this year after falling out of favor in 2022. The market appears to be in recovery mode after last year's macroeconomic headwinds led to reductions in consumer spending. As a result, many stocks are trending up, making now an excellent time to invest in some of the industry's leaders before their stocks climb any higher. Advanced Micro Devices (NASDAQ: AMD) and Apple (NASDAQ: AAPL) are two attractive options, with one producing powerful chips for multiple companies and the other the king of consumer tech. AMD and Apple's stocks have soared 75% and 47% since the start of the year. However, a potential bull market suggests they could have more room to rise. Meanwhile, advances in technologies like artificial intelligence (AI) and virtual/augmented reality (VR/AR) could further bolster the companies. AMD and Apple are compelling investment options. However, before adding both to your portfolio, it's wise to get the most out of your investment by understanding which is currently the better buy. So, let's examine whether AMD or Apple's stock is the best option. Advanced Micro Devices Chipmakers like AMD have become a favorite on Wall Street this year thanks to the endless potential of markets like AI and cloud computing. These industries require high-powered chips to develop, with AMD one of a handful of companies producing the necessary hardware. The company seemed to start 2023 at a disadvantage, with its biggest competitor, Nvidia, getting a head start in AI. However, the AI market is expected to expand at a compound annual growth rate (CAGR) of 37% through 2030, indicating there will be plenty of opportunities for AMD to snap up market share over the long term. Meanwhile, many of Nvidia's clients are rooting for AMD as more competition means lower prices for AI chips. As a result, cloud giant Microsoft has stepped in to support AMD's AI chip expansion by providing financial and engineering resources with the aim of creating an alternative to Nvidia. The collaboration is promising, considering Microsoft holds exclusive licenses on multiple OpenAI models. The Windows company's guidance will likely prove invaluable to AMD. It will take time for AMD to catch up to Nvidia. However, it has a better chance than most with its successful chip business and massive support from other tech companies. Apple This year, Apple has become the first company to achieve a market capitalization of $3 trillion. The achievement highlights the stability of Apple's stock over the years, with its shares rising over 1,000% in the last decade. The company's priority on quality products presented with an easy-to-use design language has created immense brand loyalty worldwide and allowed Apple to charge a premium for its devices. As a result, the tech giant's annual revenue has risen 48% since 2018, with operating income up 68%. Meanwhile, Apple has achieved a leading market share in multiple areas, including smartph\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.05305, "explanation": "The actual 21-day forward return for XLK starting 2023-07-13 was -5.30%, which classifies as 'negative'.", "metadata": {"future_return": -0.05305, "horizon_days": 21, "hist_return": 0.168606, "annualized_vol": 0.183358, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230619_0469", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-06-19", "context_summary": "QUAL over past 60 days: cumulative return +11.8%, annualized vol 13.2%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=115.89, end=129.56, cumulative_return=+11.8%, annualized_volatility=13.2%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.57, 'breakeven_10y': 2.22, 'hy_oas': 4.15, 'ig_oas': 1.35, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.539999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-16] [\"3 Stocks to Buy for Long-Term, Life-Changing Returns InvestorPlace - Stock Market News, Stock Advice & Trading Tips Investors are always on the hunt for long-term wealth stocks. You know, the kind that you can buy and hold for years (or decades) and generate market-beating returns. We\\u2019re all after that \\u2014 that\\u2019s why we read articles like this one. When investing for the future, readers have to look under the hood and find high-quality businesses. At the same time, it can be hard when looking for long-term investment stocks. That\\u2019s because so many of the best stocks have already generated the life-changing returns that investors are currently looking for. A stock like Apple (NASDAQ:AAPL) is an amazing business. But with a near-$3 trillion market valuation, there is a concern that its bigger growth days are behind it. Or take Johnson & Johnson (NYSE:JNJ). I love the company, but with a $425 billion market cap and only modest growth, it\\u2019s hard to imagine it outperforming the S&P 500 year-in and year-out. So what are some long-term wealth stocks to buy now? Investing for the Future: The Trade Desk (TTD) Source: Tada Images / Shutterstock.com There is absolutely nothing wrong with the businesses above (Apple and J&J). Almost any investor could make a case for them. However, I am looking for stocks that can generate outsized market returns over the long haul from here, not stocks that have already created those returns. One such stock? The Trade Desk (NASDAQ:TTD): The Trade Desk is a digital advertising firm that utilizes a demand-side platform. This not only drives efficiency for the customer, but drives profit for the company. Further, The Trade Desk makes it easy for customers to leverage connected TVs, audio, video, mobile and other mediums for their advertising needs. Before the pandemic, after the pandemic and through the 2022 bear market, investors experienced a lot of volatility in TTD stock. However, the company remained incredibly stable. It\\u2019s able to operate around the world (China included) and continues to churn out steady growth. Consensus expectations call for more than 20% revenue growth this year and next year, to go alongside 17% earnings growth in 2023 and 20.5% growth in 2024. Long-Term Wealth Stocks: PayPal (PYPL) Source: Michael Vi / Shutterstock.com PayPal (NASDAQ:PYPL): This fintech company is a controversial pick when it comes to long-term wealth stocks. The biggest reason? Because the stock has fallen out of favor with the market and suffered a peak-to-trough decline in excess of 80%. The stock has only recently hit a 52-week low. While many large cap and high growth stocks have come back to life, that has not been the case with PayPal. To be frank, I\\u2019m not sure why that\\u2019s been the case. PayPal has a solid brand and has been one of the market\\u2019s favorite stocks over the years. From the time it was spun off in mid-2015 to its high in February 2020 (just before the Covid-19 selloff), \n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.036792, "explanation": "The actual 21-day forward return for QUAL starting 2023-06-19 was +3.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.036792, "horizon_days": 21, "hist_return": 0.117954, "annualized_vol": 0.13215, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230720_0472", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-07-20", "context_summary": "IVV over past 60 days: cumulative return +10.7%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=397.88, end=440.59, cumulative_return=+10.7%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.68, 'breakeven_10y': 2.22, 'hy_oas': 3.89, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 13.760000228881836}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-19] [\"Technology Sector Update for 07/19/2023: AAPL, U, MSFT, ATVI Tech stocks were lower Wednesday afternoon with the Technology Select Sector SPDR Fund (XLK) decreasing 0.5% and the Philadelphia Semiconductor index falling 1.1%. In company news, Apple (AAPL) has been working on generative artificial intelligence tools to catch up with rivals, but it hasn't decided yet how to release the new technology to consumers, Bloomberg reported Wednesday. Apple shares were adding 0.5%. Unity Software (U) was up 1.7% after the company launched its beta program for visionOS, the operating system that powers Apple's Vision Pro. Microsoft (MSFT) and Activision Blizzard (ATVI) revised some terms of their planned deal and extended the time period by which the companies must close the deal as they seek to resolve the remaining regulatory hurdles. Microsoft shares fell1.9% and Activision dropped 0.5%. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple tests generative AI tools to rival OpenAI's ChatGPT - Bloomberg News Updates shares, adds details from the report and background July 19 (Reuters) - Apple AAPL.O is working on artificial intelligence(AI) offerings similar to OpenAI's ChatGPT and Google's Bard, Bloomberg News reported on Wednesday, sending its shares up as much as 2% to a record high. The iPhone maker has built its own framework, known as \\\"Ajax\\\", to create large language models (LLMs) and is also testing a chatbot that some engineers call \\\"Apple GPT\\\", the report said,citing people with knowledge of the matter. The company did not respond to a Reuters request for comment. Apple has so far held back from any big moves in AI and even avoided mentioning the buzzword at its developer conference in June - in stark contrast to other tech giants such as Alphabet GOOGL.O and Microsoft MSFT.Owhich have made bold moves to incorporate the breakthrough technology. Shares of Microsoft, Nvidia NVDA.O and Alphabet dropped more than 1% after the report. Apple has, however, subtly pushed advanced AI in some of its products such as Apple Photos, on device texting, and the recently launched mixed-reality headset Vision Pro. Still, analysts say the company is behind peers in incorporating the new technology. Apple's core AI product, voice assistant Siri, has also stagnated over the years. The Bloomberg report said several teams are involved in the latest AI effort, which is led by John Giannandrea, the company's head of machine learning and AI, andCraig Federighi, Apple's top software engineering executive. Apple's new virtual assistant summarizes text and answers questions based on data it has been trained with, and is being used internally for product prototyping, according to the report. Employees say the tool essentially replicates Bard, ChatGPT and Bing AI, and works as a web application. Apple does not yet have a concrete plan for the tools it is developing, but it is aiming\n\nPredict whether the return of IVV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.035019, "explanation": "The actual 21-day forward return for IVV starting 2023-07-20 was -3.50%, which classifies as 'negative'.", "metadata": {"future_return": -0.035019, "horizon_days": 21, "hist_return": 0.107331, "annualized_vol": 0.118921, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231222_0475", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2023-12-22", "context_summary": "SHV over past 60 days: cumulative return +1.3%, annualized vol 0.3%. Market regime: sideways.", "question": "Asset: SHV\nHistorical prices (past 60 trading days): start=98.25, end=99.54, cumulative_return=+1.3%, annualized_volatility=0.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.44, 't10y3m_spread': -1.53, 'breakeven_10y': 2.19, 'hy_oas': 3.41, 'ig_oas': 1.07, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 13.649999618530272}\nMarket regime: sideways\n\nPredict whether the return of SHV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003909, "explanation": "The actual 21-day forward return for SHV starting 2023-12-22 was +0.39%, which classifies as 'flat'.", "metadata": {"future_return": 0.003909, "horizon_days": 21, "hist_return": 0.013168, "annualized_vol": 0.002672, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230815_0477", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-08-15", "context_summary": "SOL-USD over past 60 days: cumulative return +64.2%, annualized vol 65.7%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=15.31, end=25.14, cumulative_return=+64.2%, annualized_volatility=65.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.77, 't10y3m_spread': -1.37, 'breakeven_10y': 2.36, 'hy_oas': 3.79, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 14.81999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-14] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.151662, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-08-15 was -15.17%, which classifies as 'negative'.", "metadata": {"future_return": -0.151662, "horizon_days": 21, "hist_return": 0.642436, "annualized_vol": 0.656879, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240326_0480", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IEF"], "decision_date": "2024-03-26", "context_summary": "IEF over past 60 days: cumulative return -1.4%, annualized vol 6.8%. Market regime: bull.", "question": "Asset: IEF\nHistorical prices (past 60 trading days): start=88.40, end=87.21, cumulative_return=-1.4%, annualized_volatility=6.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.29, 't10y3m_spread': -1.21, 'breakeven_10y': 2.33, 'hy_oas': 3.11, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 13.1899995803833}\nMarket regime: bull\n\nPredict whether the return of IEF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.026827, "explanation": "The actual 21-day forward return for IEF starting 2024-03-26 was -2.68%, which classifies as 'negative'.", "metadata": {"future_return": -0.026827, "horizon_days": 21, "hist_return": -0.013522, "annualized_vol": 0.067585, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241227_0483", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-12-27", "context_summary": "DOT-USD over past 60 days: cumulative return +67.7%, annualized vol 109.6%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.13, end=6.93, cumulative_return=+67.7%, annualized_volatility=109.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.28, 't10y3m_spread': 0.23, 'breakeven_10y': 2.35, 'hy_oas': 2.86, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 14.729999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.089145, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-12-27 was +8.91%, which classifies as 'positive'.", "metadata": {"future_return": 0.089145, "horizon_days": 21, "hist_return": 0.677467, "annualized_vol": 1.096462, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240118_0485", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2024-01-18", "context_summary": "XHB over past 60 days: cumulative return +32.1%, annualized vol 22.1%. Market regime: sideways.", "question": "Asset: XHB\nHistorical prices (past 60 trading days): start=69.55, end=91.88, cumulative_return=+32.1%, annualized_volatility=22.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.24, 't10y3m_spread': -1.37, 'breakeven_10y': 2.3, 'hy_oas': 3.62, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.66, 'vix': 14.789999961853027}\nMarket regime: sideways\n\nPredict whether the return of XHB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.04011, "explanation": "The actual 21-day forward return for XHB starting 2024-01-18 was +4.01%, which classifies as 'positive'.", "metadata": {"future_return": 0.04011, "horizon_days": 21, "hist_return": 0.321138, "annualized_vol": 0.221005, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240726_0488", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-07-26", "context_summary": "XRP-USD over past 60 days: cumulative return +12.4%, annualized vol 53.0%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.53, end=0.60, cumulative_return=+12.4%, annualized_volatility=53.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.14, 't10y3m_spread': -1.12, 'breakeven_10y': 2.28, 'hy_oas': 3.08, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 18.459999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.065476, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-07-26 was -6.55%, which classifies as 'negative'.", "metadata": {"future_return": -0.065476, "horizon_days": 21, "hist_return": 0.123731, "annualized_vol": 0.53023, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230522_0491", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2023-05-22", "context_summary": "ACWI over past 60 days: cumulative return +5.5%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=83.59, end=88.16, cumulative_return=+5.5%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.58, 't10y3m_spread': -1.59, 'breakeven_10y': 2.24, 'hy_oas': 4.62, 'ig_oas': 1.45, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 16.809999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-19] [\"Warren Buffett on Apple, Banks, and Value Investing In this podcast, Motley Fool senior analyst Jason Moser discusses: Berkshire Hathaway's first-quarter results and highlights from the annual meeting. Buffett's comments about Apple and the banking industry. Charlie Munger's warning about overdiversification. Motley Fool senior analyst Jim Gillies talks about the vibe at the Berkshire Hathaway annual meeting. To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. To get started investing, check out our quick-start guide to investing in stocks. A full transcript follows the video. 10 stocks we like better than Berkshire Hathaway When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now\\u2026 and Berkshire Hathaway wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of May 8, 2023 This video was recorded on May 8, 2023. Chris Hill: Omaha, somewhere in Middle America. We're going to get right to the heart of the matter of the Berkshire Hathaway Annual Meeting. Motley Fool Money starts now. [music] I'm Chris Hill. Joining me in studio: Motley Fool Senior Analyst Jason Moser. Thanks for being here. Jason Moser: Hey, thanks for having me. Chris Hill: Let's talk a little about Berkshire Hathaway, shall we? Jason Moser: Sure. Chris Hill: We're going to get to the Q&A in a second. I do just want to point out, I think it's a sign of what an event the Berkshire Hathaway Annual Meeting is and how much attention is paid to the marathon Q&A session that Buffett and Charlie Munger do that we basically all, as an investment community, just basically missed the fact that they reported first-quarter earnings. Jason Moser: That is so secondary. Chris Hill: It's just like, oh, by the way, the results were better than expected. Geico is profitable again after a year and a half of not being profitable. Berkshire Hathaway now has $130 billion in cash. That aside... Jason Moser: They're in a good spot, Chris. Chris Hill: Let's get to some of the highlights from the Q&A session. And the thing that stood out to me, both as a Berkshire Hathaway shareholder and as a shareholder of Apple, is the flowers that Buffett was throwing at Apple, basically saying, this is the best business we invest in. Jason Moser: For the longest time, they really steered clear of \\\"tech stocks\\\" because they just felt like it was outside of their circle of competence, so to speak. I think Apple transcends that. I have always said Apple is literally a company that could stamp its brand on a rock and sell 3 million, no questions asked. It is that powerful, and I'm not even kidding. I absolutely believe that. Chris Hill: The iRock. Jason Moser: People just say, hey, it's a special r\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.029523, "explanation": "The actual 21-day forward return for ACWI starting 2023-05-22 was +2.95%, which classifies as 'positive'.", "metadata": {"future_return": 0.029523, "horizon_days": 21, "hist_return": 0.05456, "annualized_vol": 0.134796, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240624_0493", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2024-06-24", "context_summary": "XLY over past 60 days: cumulative return -1.0%, annualized vol 14.8%. Market regime: bull.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=90.70, end=89.79, cumulative_return=-1.0%, annualized_volatility=14.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.45, 't10y3m_spread': -1.24, 'breakeven_10y': 2.23, 'hy_oas': 3.21, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 13.199999809265137}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.000771, "explanation": "The actual 21-day forward return for XLY starting 2024-06-24 was -0.08%, which classifies as 'flat'.", "metadata": {"future_return": -0.000771, "horizon_days": 21, "hist_return": -0.010029, "annualized_vol": 0.148328, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20231220_0495", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-12-20", "context_summary": "LINK-USD over past 60 days: cumulative return +58.3%, annualized vol 84.5%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=8.90, end=14.10, cumulative_return=+58.3%, annualized_volatility=84.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.48, 't10y3m_spread': -1.5, 'breakeven_10y': 2.19, 'hy_oas': 3.46, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.529999732971191}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.056717, "explanation": "The actual 21-day forward return for LINK-USD starting 2023-12-20 was +5.67%, which classifies as 'positive'.", "metadata": {"future_return": 0.056717, "horizon_days": 21, "hist_return": 0.583091, "annualized_vol": 0.84503, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241226_0498", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2024-12-26", "context_summary": "IAU over past 60 days: cumulative return -1.6%, annualized vol 15.5%. Market regime: sideways.", "question": "Asset: IAU\nHistorical prices (past 60 trading days): start=50.20, end=49.39, cumulative_return=-1.6%, annualized_volatility=15.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.3, 't10y3m_spread': 0.19, 'breakeven_10y': 2.35, 'hy_oas': 2.86, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 14.270000457763672}\nMarket regime: sideways\n\nPredict whether the return of IAU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.052092, "explanation": "The actual 21-day forward return for IAU starting 2024-12-26 was +5.21%, which classifies as 'positive'.", "metadata": {"future_return": 0.052092, "horizon_days": 21, "hist_return": -0.016135, "annualized_vol": 0.155393, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231127_0501", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-11-27", "context_summary": "XRP-USD over past 60 days: cumulative return +21.1%, annualized vol 45.1%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.51, end=0.62, cumulative_return=+21.1%, annualized_volatility=45.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.45, 't10y3m_spread': -1.07, 'breakeven_10y': 2.26, 'hy_oas': 3.85, 'ig_oas': 1.14, 'ted_spread': 0.09, 'mortgage_30y': 7.29, 'vix': 12.460000038146973}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-26] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.013866, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-11-27 was +1.39%, which classifies as 'positive'.", "metadata": {"future_return": 0.013866, "horizon_days": 21, "hist_return": 0.210577, "annualized_vol": 0.451376, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230203_0504", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2023-02-03", "context_summary": "XHB over past 60 days: cumulative return +27.6%, annualized vol 26.0%. Market regime: sideways.", "question": "Asset: XHB\nHistorical prices (past 60 trading days): start=55.15, end=70.40, cumulative_return=+27.6%, annualized_volatility=26.0%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.69, 't10y3m_spread': -1.26, 'breakeven_10y': 2.22, 'hy_oas': 3.94, 'ig_oas': 1.21, 'ted_spread': 0.09, 'mortgage_30y': 6.09, 'vix': 18.729999542236328}\nMarket regime: sideways\n\nPredict whether the return of XHB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.043393, "explanation": "The actual 21-day forward return for XHB starting 2023-02-03 was -4.34%, which classifies as 'negative'.", "metadata": {"future_return": -0.043393, "horizon_days": 21, "hist_return": 0.2764, "annualized_vol": 0.260072, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241206_0506", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-12-06", "context_summary": "BTC-USD over past 60 days: cumulative return +55.2%, annualized vol 43.1%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=62236.66, end=96593.57, cumulative_return=+55.2%, annualized_volatility=43.1%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.02, 't10y3m_spread': -0.29, 'breakeven_10y': 2.25, 'hy_oas': 2.66, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.539999961853027}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.057604, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-12-06 was -5.76%, which classifies as 'negative'.", "metadata": {"future_return": -0.057604, "horizon_days": 21, "hist_return": 0.552037, "annualized_vol": 0.43064, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240919_0511", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-09-19", "context_summary": "XLV over past 60 days: cumulative return +6.0%, annualized vol 12.4%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=142.33, end=150.80, cumulative_return=+6.0%, annualized_volatility=12.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.09, 't10y3m_spread': -1.14, 'breakeven_10y': 2.12, 'hy_oas': 3.21, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.2, 'vix': 18.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.014231, "explanation": "The actual 21-day forward return for XLV starting 2024-09-19 was -1.42%, which classifies as 'negative'.", "metadata": {"future_return": -0.014231, "horizon_days": 21, "hist_return": 0.059538, "annualized_vol": 0.123607, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240715_0514", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-07-15", "context_summary": "VLUE over past 60 days: cumulative return +6.5%, annualized vol 10.3%. Market regime: bull.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=95.98, end=102.26, cumulative_return=+6.5%, annualized_volatility=10.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.27, 't10y3m_spread': -1.25, 'breakeven_10y': 2.24, 'hy_oas': 3.19, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 12.460000038146973}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of VLUE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.046952, "explanation": "The actual 21-day forward return for VLUE starting 2024-07-15 was -4.70%, which classifies as 'negative'.", "metadata": {"future_return": -0.046952, "horizon_days": 21, "hist_return": 0.065387, "annualized_vol": 0.102517, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240514_0517", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-14", "context_summary": "SPY over past 60 days: cumulative return +4.6%, annualized vol 11.6%. Market regime: bull.", "question": "Asset: SPY\nHistorical prices (past 60 trading days): start=486.13, end=508.53, cumulative_return=+4.6%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.37, 't10y3m_spread': -0.97, 'breakeven_10y': 2.33, 'hy_oas': 3.14, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 13.600000381469728}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of SPY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.036595, "explanation": "The actual 21-day forward return for SPY starting 2024-05-14 was +3.66%, which classifies as 'positive'.", "metadata": {"future_return": 0.036595, "horizon_days": 21, "hist_return": 0.046082, "annualized_vol": 0.116266, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230217_0520", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2023-02-17", "context_summary": "HAUZ over past 60 days: cumulative return +6.0%, annualized vol 15.6%. Market regime: sideways.", "question": "Asset: HAUZ\nHistorical prices (past 60 trading days): start=18.34, end=19.45, cumulative_return=+6.0%, annualized_volatility=15.6%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.76, 't10y3m_spread': -0.98, 'breakeven_10y': 2.37, 'hy_oas': 4.24, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 20.170000076293945}\nMarket regime: sideways\n\nPredict whether the return of HAUZ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.055, "explanation": "The actual 21-day forward return for HAUZ starting 2023-02-17 was -5.50%, which classifies as 'negative'.", "metadata": {"future_return": -0.055, "horizon_days": 21, "hist_return": 0.060108, "annualized_vol": 0.156009, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230510_0523", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2023-05-10", "context_summary": "USO over past 60 days: cumulative return -6.0%, annualized vol 35.6%. Market regime: sideways.", "question": "Asset: USO\nHistorical prices (past 60 trading days): start=69.02, end=64.87, cumulative_return=-6.0%, annualized_volatility=35.6%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.48, 't10y3m_spread': -1.68, 'breakeven_10y': 2.23, 'hy_oas': 4.74, 'ig_oas': 1.49, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 17.709999084472656}\nMarket regime: sideways\n\nPredict whether the return of USO over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.014443, "explanation": "The actual 21-day forward return for USO starting 2023-05-10 was -1.44%, which classifies as 'negative'.", "metadata": {"future_return": -0.014443, "horizon_days": 21, "hist_return": -0.060127, "annualized_vol": 0.355912, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241119_0526", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-11-19", "context_summary": "MATIC-USD over past 60 days: cumulative return +13.5%, annualized vol 72.7%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.40, end=0.45, cumulative_return=+13.5%, annualized_volatility=72.7%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.13, 't10y3m_spread': -0.21, 'breakeven_10y': 2.34, 'hy_oas': 2.72, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 15.579999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.341801, "explanation": "The actual 21-day forward return for MATIC-USD starting 2024-11-19 was +34.18%, which classifies as 'positive'.", "metadata": {"future_return": 0.341801, "horizon_days": 21, "hist_return": 0.134895, "annualized_vol": 0.727351, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230926_0529", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-09-26", "context_summary": "^VIX over past 60 days: cumulative return +24.4%, annualized vol 83.8%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=13.59, end=16.90, cumulative_return=+24.4%, annualized_volatility=83.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.54, 't10y3m_spread': -1.03, 'breakeven_10y': 2.37, 'hy_oas': 3.97, 'ig_oas': 1.19, 'ted_spread': 0.09, 'mortgage_30y': 7.19, 'vix': 16.899999618530273}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-25] [\"OpenAI's ChatGPT will 'see, hear and speak' in major update Sept 25 (Reuters) - OpenAI's ChatGPT is getting a major update that will enable the viral chatbot to have voice conversations with users and interact using images, moving it closer to popular artificial intelligence (AI) assistants like Apple's AAPL.O Siri. The voice feature \\\"opens doors to many creative and accessibility-focused applications\\\", OpenAI said in a blog post on Monday. Similar AI services like Siri, Google GOOGL.O voice assistant and Amazon.com's AMZN.O Alexa are integrated with the devices they run on and are often used to set alarms and reminders, and deliver information off the internet. Since its debut last year, ChatGPT has been adopted by companies for a wide range of tasks from summarizing documents to writing computer code, setting off a race amongst Big Tech companies to launch their own offerings based on generative AI. ChatGPT's new voice feature can also narrate bedtime stories, settle debates at the dinner table, and speak out loud text input from users. The technology behind it is being used by Spotify SPOT.N for the platform's podcasters to translate their content in different languages, OpenAI said. With images support, users can take pictures of things around them and ask the chatbot to \\\"troubleshoot why your grill won't start, explore the contents of your fridge to plan a meal, or analyze a complex graph for work-related data\\\". Alphabet's Google Lens is currently the popular choice to gain information on images. The new ChatGPT features will be released for subscribers of its Plus and Enterprise plans over the next two weeks. (Reporting by Zaheer Kachwala and Yuvraj Malik in Bengaluru; Editing by Devika Syamnath) ((yuvraj.malik@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Netflix (NFLX) Expands Portfolio With New Italian Content Netflix NFLX is having a steady run in 2023, with shares rising 28.8% year to date compared with the Zacks Consumer Discretionary sector\\u2019s increase of 4.6%. The upside can be attributed to an expanding subscriber base and robust content offerings. Netflix continues to bolster its international content portfolio. Italy plays a prominent role in this endeavour through an extensive lineup that includes a wide range of series, films, docuseries and unscripted shows spanning diverse genres, formats and languages. Netflix recently announced four captivating new projects, including Il treno dei bambini, an in-depth exploration of postwar Italy and Fabbricante di lacrime, based on a popular book. Additionally, two fresh series, Storia della mia famiglia and Adorazione, provide deep explorations of intricate family dynamics and young adult experiences. Expanding Portfolio Aids Growth Netflix is anticipated to gain from its diversified content portfolio, driven by substantial investments in producing and distributing lo\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.065998, "explanation": "The actual 21-day forward return for ^VIX starting 2023-09-26 was +6.60%, which classifies as 'positive'.", "metadata": {"future_return": 0.065998, "horizon_days": 21, "hist_return": 0.243561, "annualized_vol": 0.838122, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230208_0532", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-02-08", "context_summary": "SOL-USD over past 60 days: cumulative return +75.7%, annualized vol 111.1%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=13.58, end=23.86, cumulative_return=+75.7%, annualized_volatility=111.1%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.8, 't10y3m_spread': -1.04, 'breakeven_10y': 2.31, 'hy_oas': 3.99, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 6.09, 'vix': 18.65999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-07] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.029589, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-02-08 was -2.96%, which classifies as 'negative'.", "metadata": {"future_return": -0.029589, "horizon_days": 21, "hist_return": 0.757484, "annualized_vol": 1.110881, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240731_0535", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2024-07-31", "context_summary": "VTI over past 60 days: cumulative return +6.3%, annualized vol 10.3%. 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in Exhibit 101   X                                   * Indicates a management contract or compensatory plan or arrangement. ** Furnished, not filed. 109 PART IV Item 16   ITEM 16. FORM 10-K SUMMARY None. 110   SIGNAT URES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned; thereunto duly authorized, in the City of Redmond, State of Washington, on July 30, 2024.   M ICROSOFT  C ORPORATION   /s/ A LICE  L. J OLLA Alice L. Jolla Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer)   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of Registrant and in the capacities indicated on July 30, 2024.   Signature Title   /s/ S ATYA  N ADELLA Chairman and Chief Executive Officer (Principal Executive Officer) Satya Nadella     /s/ R EID  H OFFMAN   Director Reid Hoffman     /s/ H UGH  F. J OHNSTON Director Hugh F. Johnston     /s/ T ERI L. L IST Director Teri L. List     /s/ C ATHERINE  M AC G REGOR   Director Catherine MacGregor         /s/ M ARK  A. L. M ASON   Director Mark A. L. Mason         /s/ S ANDRA  E. P ETERSON Lead Independent Director Sandra E. Peterson       /s/ P ENNY S. P RITZKER   Director Penny S. Pritzker       /s/ C ARLOS A. R ODRIGUEZ   Director Carlos A. Rodriguez       /s/ C HARLES  W. S CHARF Director Charles W. Scharf     /s/ J OHN  W. S TANTON Director John W. Stanton       /s/ E MMA  N. W ALMSLEY   Director Emma N. Walmsley     /s/ A MY  E. H OOD Executive Vice President and Chief Financial Officer (Principal Financial Officer) Amy E. Hood     /s/ A LICE  L. J OLLA Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer) Alice L. Jolla     111\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.011557, "explanation": "The actual 21-day forward return for VTI starting 2024-07-31 was +1.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.011557, "horizon_days": 21, "hist_return": 0.063158, "annualized_vol": 0.102884, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240612_0538", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2024-06-12", "context_summary": "FXI over past 60 days: cumulative return +10.5%, annualized vol 22.5%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=23.02, end=25.44, cumulative_return=+10.5%, annualized_volatility=22.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.42, 't10y3m_spread': -1.13, 'breakeven_10y': 2.27, 'hy_oas': 3.19, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.99, 'vix': 12.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of FXI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.03067, "explanation": "The actual 21-day forward return for FXI starting 2024-06-12 was +3.07%, which classifies as 'positive'.", "metadata": {"future_return": 0.03067, "horizon_days": 21, "hist_return": 0.105051, "annualized_vol": 0.225208, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230710_0541", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2023-07-10", "context_summary": "SCHP over past 60 days: cumulative return -2.0%, annualized vol 5.3%. Market regime: sideways.", "question": "Asset: SCHP\nHistorical prices (past 60 trading days): start=24.08, end=23.59, cumulative_return=-2.0%, annualized_volatility=5.3%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.88, 't10y3m_spread': -1.4, 'breakeven_10y': 2.27, 'hy_oas': 4.08, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 14.829999923706056}\nMarket regime: sideways\n\nPredict whether the return of SCHP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.006623, "explanation": "The actual 21-day forward return for SCHP starting 2023-07-10 was +0.66%, which classifies as 'flat'.", "metadata": {"future_return": 0.006623, "horizon_days": 21, "hist_return": -0.020232, "annualized_vol": 0.053404, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231204_0544", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-12-04", "context_summary": "DOT-USD over past 60 days: cumulative return +37.9%, annualized vol 51.1%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.02, end=5.55, cumulative_return=+37.9%, annualized_volatility=51.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.34, 't10y3m_spread': -1.21, 'breakeven_10y': 2.22, 'hy_oas': 3.87, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 12.630000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-03] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.640264, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-12-04 was +64.03%, which classifies as 'positive'.", "metadata": {"future_return": 0.640264, "horizon_days": 21, "hist_return": 0.378806, "annualized_vol": 0.511078, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231218_0547", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-12-18", "context_summary": "LINK-USD over past 60 days: cumulative return +91.8%, annualized vol 83.9%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=7.31, end=14.02, cumulative_return=+91.8%, annualized_volatility=83.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.53, 't10y3m_spread': -1.53, 'breakeven_10y': 2.22, 'hy_oas': 3.51, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.279999732971191}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-17] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.03337, "explanation": "The actual 21-day forward return for LINK-USD starting 2023-12-18 was -3.34%, which classifies as 'negative'.", "metadata": {"future_return": -0.03337, "horizon_days": 21, "hist_return": 0.917786, "annualized_vol": 0.838605, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240404_0550", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-04-04", "context_summary": "ADA-USD over past 60 days: cumulative return +15.6%, annualized vol 66.6%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.49, end=0.57, cumulative_return=+15.6%, annualized_volatility=66.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.32, 't10y3m_spread': -1.06, 'breakeven_10y': 2.36, 'hy_oas': 3.23, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 14.329999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.192013, "explanation": "The actual 21-day forward return for ADA-USD starting 2024-04-04 was -19.20%, which classifies as 'negative'.", "metadata": {"future_return": -0.192013, "horizon_days": 21, "hist_return": 0.155834, "annualized_vol": 0.665887, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241002_0553", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-10-02", "context_summary": "^VIX over past 60 days: cumulative return +54.0%, annualized vol 153.6%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=12.51, end=19.26, cumulative_return=+54.0%, annualized_volatility=153.6%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.13, 't10y3m_spread': -0.97, 'breakeven_10y': 2.19, 'hy_oas': 3.07, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.08, 'vix': 19.26000022888184}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.225397, "explanation": "The actual 21-day forward return for ^VIX starting 2024-10-02 was +22.54%, which classifies as 'positive'.", "metadata": {"future_return": 0.225397, "horizon_days": 21, "hist_return": 0.539568, "annualized_vol": 1.535562, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230913_0556", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-09-13", "context_summary": "XRP-USD over past 60 days: cumulative return -32.6%, annualized vol 46.4%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.71, end=0.48, cumulative_return=-32.6%, annualized_volatility=46.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.71, 't10y3m_spread': -1.29, 'breakeven_10y': 2.34, 'hy_oas': 3.84, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.12, 'vix': 14.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-12] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.101609, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-09-13 was +10.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.101609, "horizon_days": 21, "hist_return": -0.326017, "annualized_vol": 0.46443, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240801_0558", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-08-01", "context_summary": "ADA-USD over past 60 days: cumulative return -12.9%, annualized vol 52.4%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.45, end=0.39, cumulative_return=-12.9%, annualized_volatility=52.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.2, 't10y3m_spread': -1.32, 'breakeven_10y': 2.24, 'hy_oas': 3.25, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 16.360000610351562}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.041176, "explanation": "The actual 21-day forward return for ADA-USD starting 2024-08-01 was -4.12%, which classifies as 'negative'.", "metadata": {"future_return": -0.041176, "horizon_days": 21, "hist_return": -0.129276, "annualized_vol": 0.524298, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230630_0561", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-06-30", "context_summary": "ETH-USD over past 60 days: cumulative return +1.1%, annualized vol 36.0%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1831.95, end=1852.23, cumulative_return=+1.1%, annualized_volatility=36.0%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.61, 'breakeven_10y': 2.2, 'hy_oas': 4.14, 'ig_oas': 1.31, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 13.539999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-29] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.021265, "explanation": "The actual 21-day forward return for ETH-USD starting 2023-06-30 was -2.13%, which classifies as 'negative'.", "metadata": {"future_return": -0.021265, "horizon_days": 21, "hist_return": 0.011066, "annualized_vol": 0.359549, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230731_0564", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-07-31", "context_summary": "MTUM over past 60 days: cumulative return +5.6%, annualized vol 11.3%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=135.52, end=143.10, cumulative_return=+5.6%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.56, 'breakeven_10y': 2.38, 'hy_oas': 3.82, 'ig_oas': 1.19, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 13.329999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-28] [\"Wall St Week Ahead-Hopes of 'Goldilocks' economy, rate peak buoy US stocks By David Randall NEW YORK, July 28 (Reuters) - A resilient U.S. economy and expectations of a nearing peak in the Federal Reserve\\u2019s monetary policy tightening cycle are emboldening stock investors, even as worries persist over rising valuations and the potential for inflation to rebound. The S&P 500 is up nearly 19% this year after gaining around 1% in the past week. It has risen nearly 10 percentage points since June 1, over which time the U.S. government avoided a debt ceiling default and consumer prices cooled, while growth stayed resilient. One key factor driving stocks higher has been the view that the economy is moving towards a so-called Goldilocks scenario of ebbing consumer prices and strong growth that many believe is a healthy backdrop for stocks. That view gained further traction in the past week, when Chair Jerome Powell said the central bank's staff no longer forecasts a U.S. recession and that inflation had a shot of returning to its 2% target without high levels of job losses. Policymakers raised rates by another 25 basis points to their highest level since 2007 at the central bank's July 26 meeting and left the door open to another increase in September. \\\"The market has fully accepted the narrative that it wanted, which is Goldilocks. Until we see some set of data that scares them it's hard to see how that changes,\\\" said Bob Kalman, senior portfolio manager at Miramar Capital. At the same time, investors believe the Fed is unlikely to deliver much more of the monetary policy tightening that shook markets last year. Futures markets on Friday priced a nearly 73% chance that rates don\\u2019t rise above current levels through the end of the year, according to CME\\u2019s FedWatch tool, up from 24% a month ago. A test of the economy comes next week, when the U.S. reports employment numbers for July. While comparatively strong employment data has been a driver of this year\\u2019s stock rally, signs that the economy is growing at too rapid a pace could spark worries that the Fed will need to raise rates more than expected. \\\"For markets to continue to trade higher, the soft landing must be a soft landing, not a reacceleration, because if housing and consumer spending accelerate from here, the Fed will have to raise rates a lot more,\\\" wrote Torsten Slok, chief economist at Apollo Global Management. Kalman, of Miramar Capital, believes there\\u2019s a growing chance the Fed may need to raise rates beyond their current 5.50% threshold and hold them there for longer than expected, an outcome he worries could dampen the economy and hurt risk assets. \\\"It's a 50-50 chance that we'll get Goldilocks or we'll get a stronger downturn,\\\" he said. Many are also assessing the durability of a rally in tech stocks, which has been fueled in part by excitement over developments in artificial intelligence. The tech-heavy Nasdaq 100 is up nearly 44% year-to-date, while the \n\nPredict whether the return of MTUM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.000204, "explanation": "The actual 21-day forward return for MTUM starting 2023-07-31 was +0.02%, which classifies as 'flat'.", "metadata": {"future_return": 0.000204, "horizon_days": 21, "hist_return": 0.055907, "annualized_vol": 0.112923, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230818_0567", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-08-18", "context_summary": "DOT-USD over past 60 days: cumulative return -1.9%, annualized vol 39.1%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.52, end=4.44, cumulative_return=-1.9%, annualized_volatility=39.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.64, 't10y3m_spread': -1.26, 'breakeven_10y': 2.33, 'hy_oas': 3.95, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 17.889999389648438}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-17] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.058051, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-08-18 was -5.81%, which classifies as 'negative'.", "metadata": {"future_return": -0.058051, "horizon_days": 21, "hist_return": -0.018675, "annualized_vol": 0.390654, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240925_0569", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-09-25", "context_summary": "LINK-USD over past 60 days: cumulative return -10.4%, annualized vol 67.7%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=13.57, end=12.16, cumulative_return=-10.4%, annualized_volatility=67.7%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.25, 't10y3m_spread': -0.95, 'breakeven_10y': 2.19, 'hy_oas': 3.21, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.09, 'vix': 15.390000343322754}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.072069, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-09-25 was -7.21%, which classifies as 'negative'.", "metadata": {"future_return": -0.072069, "horizon_days": 21, "hist_return": -0.103581, "annualized_vol": 0.676544, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241016_0572", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-10-16", "context_summary": "LINK-USD over past 60 days: cumulative return +12.7%, annualized vol 53.4%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=10.15, end=11.44, cumulative_return=+12.7%, annualized_volatility=53.4%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.08, 't10y3m_spread': -0.7, 'breakeven_10y': 2.28, 'hy_oas': 2.93, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 20.63999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.082738, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-10-16 was +8.27%, which classifies as 'positive'.", "metadata": {"future_return": 0.082738, "horizon_days": 21, "hist_return": 0.126721, "annualized_vol": 0.533742, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240229_0574", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2024-02-29", "context_summary": "IAU over past 60 days: cumulative return +0.3%, annualized vol 10.7%. Market regime: sideways.", "question": "Asset: IAU\nHistorical prices (past 60 trading days): start=38.36, end=38.48, cumulative_return=+0.3%, annualized_volatility=10.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.37, 't10y3m_spread': -1.18, 'breakeven_10y': 2.33, 'hy_oas': 3.31, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 13.84000015258789}\nMarket regime: sideways\n\nPredict whether the return of IAU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.086934, "explanation": "The actual 21-day forward return for IAU starting 2024-02-29 was +8.69%, which classifies as 'positive'.", "metadata": {"future_return": 0.086934, "horizon_days": 21, "hist_return": 0.003128, "annualized_vol": 0.106927, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240417_0577", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-04-17", "context_summary": "ETH-USD over past 60 days: cumulative return +10.7%, annualized vol 60.8%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=2786.67, end=3084.92, cumulative_return=+10.7%, annualized_volatility=60.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.3, 't10y3m_spread': -0.78, 'breakeven_10y': 2.43, 'hy_oas': 3.36, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 18.39999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.003709, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-04-17 was -0.37%, which classifies as 'flat'.", "metadata": {"future_return": -0.003709, "horizon_days": 21, "hist_return": 0.107026, "annualized_vol": 0.60846, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241017_0580", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-10-17", "context_summary": "MATIC-USD over past 60 days: cumulative return -9.3%, annualized vol 54.7%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.41, end=0.37, cumulative_return=-9.3%, annualized_volatility=54.7%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.09, 't10y3m_spread': -0.7, 'breakeven_10y': 2.27, 'hy_oas': 2.9, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 19.57999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.056004, "explanation": "The actual 21-day forward return for MATIC-USD starting 2024-10-17 was -5.60%, which classifies as 'negative'.", "metadata": {"future_return": -0.056004, "horizon_days": 21, "hist_return": -0.093102, "annualized_vol": 0.547415, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241204_0583", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-12-04", "context_summary": "BTC-USD over past 60 days: cumulative return +54.6%, annualized vol 42.4%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=62089.95, end=96002.16, cumulative_return=+54.6%, annualized_volatility=42.4%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.06, 't10y3m_spread': -0.26, 'breakeven_10y': 2.28, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 13.300000190734863}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.005373, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-12-04 was +0.54%, which classifies as 'flat'.", "metadata": {"future_return": 0.005373, "horizon_days": 21, "hist_return": 0.546179, "annualized_vol": 0.424356, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230216_0586", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2023-02-16", "context_summary": "IGOV over past 60 days: cumulative return -0.7%, annualized vol 11.5%. Market regime: sideways.", "question": "Asset: IGOV\nHistorical prices (past 60 trading days): start=38.82, end=38.54, cumulative_return=-0.7%, annualized_volatility=11.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.81, 't10y3m_spread': -0.98, 'breakeven_10y': 2.35, 'hy_oas': 4.18, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 6.12, 'vix': 18.229999542236328}\nMarket regime: sideways\n\nPredict whether the return of IGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.027992, "explanation": "The actual 21-day forward return for IGOV starting 2023-02-16 was +2.80%, which classifies as 'positive'.", "metadata": {"future_return": 0.027992, "horizon_days": 21, "hist_return": -0.007299, "annualized_vol": 0.115237, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240125_0589", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-01-25", "context_summary": "DOT-USD over past 60 days: cumulative return +21.3%, annualized vol 82.7%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=5.33, end=6.46, cumulative_return=+21.3%, annualized_volatility=82.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.16, 't10y3m_spread': -1.26, 'breakeven_10y': 2.3, 'hy_oas': 3.44, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 13.140000343322754}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.208812, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-01-25 was +20.88%, which classifies as 'positive'.", "metadata": {"future_return": 0.208812, "horizon_days": 21, "hist_return": 0.213087, "annualized_vol": 0.827102, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240403_0592", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-04-03", "context_summary": "AVAX-USD over past 60 days: cumulative return +30.4%, annualized vol 79.9%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=35.92, end=46.82, cumulative_return=+30.4%, annualized_volatility=79.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.34, 't10y3m_spread': -1.06, 'breakeven_10y': 2.36, 'hy_oas': 3.23, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 14.609999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.208453, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-04-03 was -20.85%, which classifies as 'negative'.", "metadata": {"future_return": -0.208453, "horizon_days": 21, "hist_return": 0.30359, "annualized_vol": 0.79895, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240112_0595", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-01-12", "context_summary": "DOT-USD over past 60 days: cumulative return +52.2%, annualized vol 84.1%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=5.37, end=8.17, cumulative_return=+52.2%, annualized_volatility=84.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.28, 't10y3m_spread': -1.48, 'breakeven_10y': 2.22, 'hy_oas': 3.55, 'ig_oas': 1.03, 'ted_spread': 0.09, 'mortgage_30y': 6.66, 'vix': 12.4399995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.083634, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-01-12 was -8.36%, which classifies as 'negative'.", "metadata": {"future_return": -0.083634, "horizon_days": 21, "hist_return": 0.521913, "annualized_vol": 0.841009, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240208_0598", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-02-08", "context_summary": "ADA-USD over past 60 days: cumulative return -15.5%, annualized vol 71.8%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.59, end=0.50, cumulative_return=-15.5%, annualized_volatility=71.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.32, 't10y3m_spread': -1.34, 'breakeven_10y': 2.23, 'hy_oas': 3.43, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 12.829999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.238777, "explanation": "The actual 21-day forward return for ADA-USD starting 2024-02-08 was +23.88%, which classifies as 'positive'.", "metadata": {"future_return": 0.238777, "horizon_days": 21, "hist_return": -0.155485, "annualized_vol": 0.718313, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240730_0601", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-07-30", "context_summary": "AVAX-USD over past 60 days: cumulative return -24.9%, annualized vol 66.5%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=36.06, end=27.08, cumulative_return=-24.9%, annualized_volatility=66.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.19, 't10y3m_spread': -1.24, 'breakeven_10y': 2.25, 'hy_oas': 3.13, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 16.600000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.148603, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-07-30 was -14.86%, which classifies as 'negative'.", "metadata": {"future_return": -0.148603, "horizon_days": 21, "hist_return": -0.248857, "annualized_vol": 0.665397, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240710_0603", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-07-10", "context_summary": "ETH-USD over past 60 days: cumulative return +5.2%, annualized vol 48.9%. Market regime: bull.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=2911.60, end=3064.03, cumulative_return=+5.2%, annualized_volatility=48.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.32, 't10y3m_spread': -1.16, 'breakeven_10y': 2.26, 'hy_oas': 3.21, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.510000228881836}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.041608, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-07-10 was +4.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.041608, "horizon_days": 21, "hist_return": 0.052353, "annualized_vol": 0.489425, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241022_0606", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-10-22", "context_summary": "AVAX-USD over past 60 days: cumulative return +4.6%, annualized vol 59.3%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=26.52, end=27.75, cumulative_return=+4.6%, annualized_volatility=59.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.17, 't10y3m_spread': -0.54, 'breakeven_10y': 2.31, 'hy_oas': 2.88, 'ig_oas': 0.85, 'ted_spread': 0.09, 'mortgage_30y': 6.44, 'vix': 18.3700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.233406, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-10-22 was +23.34%, which classifies as 'positive'.", "metadata": {"future_return": 0.233406, "horizon_days": 21, "hist_return": 0.046385, "annualized_vol": 0.59307, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240320_0609", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-03-20", "context_summary": "AVAX-USD over past 60 days: cumulative return +63.1%, annualized vol 80.5%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=32.81, end=53.53, cumulative_return=+63.1%, annualized_volatility=80.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.38, 't10y3m_spread': -1.18, 'breakeven_10y': 2.3, 'hy_oas': 3.1, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.74, 'vix': 13.81999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.170417, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-03-20 was -17.04%, which classifies as 'negative'.", "metadata": {"future_return": -0.170417, "horizon_days": 21, "hist_return": 0.631468, "annualized_vol": 0.804572, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230328_0612", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-03-28", "context_summary": "ETH-USD over past 60 days: cumulative return +7.3%, annualized vol 49.3%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1598.16, end=1715.46, cumulative_return=+7.3%, annualized_volatility=49.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.41, 't10y3m_spread': -1.38, 'breakeven_10y': 2.24, 'hy_oas': 5.03, 'ig_oas': 1.52, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 20.600000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-27] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.187136, "explanation": "The actual 21-day forward return for ETH-USD starting 2023-03-28 was +18.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.187136, "horizon_days": 21, "hist_return": 0.0734, "annualized_vol": 0.493267, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230606_0614", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2023-06-06", "context_summary": "BIL over past 60 days: cumulative return +0.7%, annualized vol 0.3%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=79.70, end=80.26, cumulative_return=+0.7%, annualized_volatility=0.3%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.77, 't10y3m_spread': -1.68, 'breakeven_10y': 2.19, 'hy_oas': 4.39, 'ig_oas': 1.39, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 14.729999542236328}\nMarket regime: sideways\n\nPredict whether the return of BIL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002951, "explanation": "The actual 21-day forward return for BIL starting 2023-06-06 was +0.30%, which classifies as 'flat'.", "metadata": {"future_return": 0.002951, "horizon_days": 21, "hist_return": 0.007055, "annualized_vol": 0.003123, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240227_0616", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2024-02-27", "context_summary": "XLE over past 60 days: cumulative return +3.7%, annualized vol 18.2%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=38.72, end=40.13, cumulative_return=+3.7%, annualized_volatility=18.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.41, 't10y3m_spread': -1.19, 'breakeven_10y': 2.31, 'hy_oas': 3.23, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 13.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CVX 2024-02-26] cvx-20231231 0000093410 false 2023 FY 336 353 277 http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2023#ShortTermBorrowings 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us-gaap:AccumulatedTranslationAdjustmentMember 2021-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2021-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2021-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2021-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-01-01 2022-12-31 0000093410 us [...TRUNCATED...] ubsidiaries of Chevron Corporation (page E-1). 22.1* Subsidiary Issuer of Guaranteed Securities. 23.1* Consent of PricewaterhouseCoopers LLP (page E-2). 24.1* Power of Attorney for certain directors of Chevron Corporation, authorizing the signing of the Annual Report on Form 10-K on their behalf. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer (page E-3). 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer (page E-4).   32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer (page E-5).   32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer (page E-6). 97.1+* Chevron Corporation Dodd-Frank Clawback Policy. 99.1* Definitions of Selected Energy and Financial Terms (pages E-7 through E-10). 101* Interactive data files (formatted as Inline XBRL). 104* Cover Page Interactive Data File (contained in Exhibit 101).   ___________________________________________ + Indicates a management contract or compensatory plan or arrangement. *      Filed herewith. **      Furnished herewith. Pursuant to Item 601(b)(4) of Regulation S-K, certain instruments with respect to the company’s long-term debt are not filed with this Annual Report on Form 10-K. A copy of any such instrument will be furnished to the Securities and Exchange Commission upon request. 118 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on the 26th day of February, 2024.  Chevron Corporation   By: /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities indicated on the 26th day of February, 2024.   Principal Executive Officer (and Director) /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer Principal Financial Officer /s/ PIERRE R. BREBER Pierre R. Breber, Vice President and Chief Financial Officer Principal Accounting Officer /s/ ALANA K. KNOWLES Alana K. Knowles, Vice President and Controller * By:  /s/ MARY A. FRANCIS Mary A. Francis, Attorney-in-Fact Directors WANDA M. AUSTIN * Wanda M. Austin JOHN B. FRANK * John B. Frank ALICE P. GAST * Alice P. Gast ENRIQUE HERNANDEZ, JR. * Enrique Hernandez, Jr. MARILLYN A. HEWSON * Marillyn A. Hewson JON M. HUNTSMAN JR. * Jon M. Huntsman Jr. CHARLES W. MOORMAN * Charles W. Moorman DAMBISA F. MOYO * Dambisa F. Moyo DEBRA REED-KLAGES * Debra Reed-Klages D. JAMES UMPLEBY III * D. James Umpleby III CYNTHIA J. WARNER * Cynthia J. Warner 119\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.096225, "explanation": "The actual 21-day forward return for XLE starting 2024-02-27 was +9.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.096225, "horizon_days": 21, "hist_return": 0.036522, "annualized_vol": 0.182336, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240312_0619", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-03-12", "context_summary": "BTC-USD over past 60 days: cumulative return +68.3%, annualized vol 45.4%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=42853.17, end=72123.91, cumulative_return=+68.3%, annualized_volatility=45.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.41, 't10y3m_spread': -1.38, 'breakeven_10y': 2.27, 'hy_oas': 3.26, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 15.220000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.084418, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-03-12 was -8.44%, which classifies as 'negative'.", "metadata": {"future_return": -0.084418, "horizon_days": 21, "hist_return": 0.683047, "annualized_vol": 0.45436, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241007_0622", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-10-07", "context_summary": "XRP-USD over past 60 days: cumulative return -13.6%, annualized vol 44.9%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.62, end=0.53, cumulative_return=-13.6%, annualized_volatility=44.9%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.05, 't10y3m_spread': -0.75, 'breakeven_10y': 2.23, 'hy_oas': 2.89, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.12, 'vix': 19.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.020204, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-10-07 was -2.02%, which classifies as 'negative'.", "metadata": {"future_return": -0.020204, "horizon_days": 21, "hist_return": -0.135991, "annualized_vol": 0.449271, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240109_0624", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-01-09", "context_summary": "QQQ over past 60 days: cumulative return +9.7%, annualized vol 16.0%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=364.51, end=400.02, cumulative_return=+9.7%, annualized_volatility=16.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.35, 't10y3m_spread': -1.48, 'breakeven_10y': 2.22, 'hy_oas': 3.63, 'ig_oas': 1.08, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 13.079999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-08] [\"4 Electronics Semiconductor Stocks to Escape Macro Headwinds The challenging global macroeconomic environment and end-market volatility have affected the Zacks Electronics - Semiconductors industry. Geo-political tensions, unfavorable forex and rising inflationary pressure also weigh heavily on the industry\\u2019s prospects. Nevertheless, industry players like Advanced Micro Devices AMD, ASE Technology ASX, Cirrus Logic CRUS and QuickLogic QUIK have been benefiting from the increasing demand for high-volume consumer electronic devices, such as digital media players, smartphones and tablets, and the strong uptake of efficient packaging, machine vision solutions and robotics. Additionally, the growing proliferation of AI, Machine Learning, Blockchain, Internet of Things, Augmented Reality/Virtual Reality (AR/VR) and industrial revolution 4.0 (which focuses on interconnectivity and automation) should continue to drive the industry\\u2019s growth. Easing supply-chain constraints are also benefiting the industry participants. Industry Description The Zacks Electronics \\u2013 Semiconductors industry comprises firms that provide a wide range of semiconductor technologies. Their offerings include packaging and test services, wafer cleaning, factory automation, face detection and image-recognition capabilities to develop intelligent and connected products. The participants primarily cater to end-markets constituting consumer electronics, communications, computing, industrial and automotive. These companies are raising their spending on research and development to stay afloat in an era of technological advancements and changing industry standards. The underlined industry is experiencing solid demand for advanced electronic equipment, helping these firms increase their investments in cost-effective process technologies. What's Shaping the Future of the Electronics - Semiconductors Industry? Macroeconomic Headwinds Pose Concerns: Rising inflationary pressure and fears of global recession have negatively impacted the rate of deal wins. Due to the challenging macroeconomic scenario, enterprises are reluctant to sign multi-year deals worldwide. These trends do not bode well for the industry participants. Geo-political Tensions Are Worrisome: The ongoing Russia-Ukraine war and, most importantly, the souring relationship between the United States and China are creating headwinds. Increasing dependency on AI-backed electronic devices on semiconductors and current restrictions ordered by the United States on trading with China, the main hub for chip production, is a significant negative for the underlined industry. Smart Devices Aiding Computing Demand: Smart devices need computing and learning capabilities to perform face detection, image recognition and video analytics capabilities. These require high processing power, speed and memory; low power consumption; and better graphic processors and solutions, which bode well for the industry. Graphic solutions help in\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.066642, "explanation": "The actual 21-day forward return for QQQ starting 2024-01-09 was +6.66%, which classifies as 'positive'.", "metadata": {"future_return": 0.066642, "horizon_days": 21, "hist_return": 0.09743, "annualized_vol": 0.160363, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231011_0627", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-10-11", "context_summary": "BTC-USD over past 60 days: cumulative return -6.9%, annualized vol 28.9%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=29415.96, end=27391.02, cumulative_return=-6.9%, annualized_volatility=28.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.3, 't10y3m_spread': -0.95, 'breakeven_10y': 2.32, 'hy_oas': 4.26, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 17.030000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-10] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.318678, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-10-11 was +31.87%, which classifies as 'positive'.", "metadata": {"future_return": 0.318678, "horizon_days": 21, "hist_return": -0.068838, "annualized_vol": 0.289051, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240628_0630", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-06-28", "context_summary": "DOT-USD over past 60 days: cumulative return -4.7%, annualized vol 53.1%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=6.59, end=6.28, cumulative_return=-4.7%, annualized_volatility=53.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.41, 't10y3m_spread': -1.2, 'breakeven_10y': 2.26, 'hy_oas': 3.21, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 12.239999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.027781, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-06-28 was +2.78%, which classifies as 'positive'.", "metadata": {"future_return": 0.027781, "horizon_days": 21, "hist_return": -0.047072, "annualized_vol": 0.530735, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230316_0632", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-03-16", "context_summary": "SOL-USD over past 60 days: cumulative return -15.7%, annualized vol 86.0%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=22.87, end=19.29, cumulative_return=-15.7%, annualized_volatility=86.0%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.42, 't10y3m_spread': -1.24, 'breakeven_10y': 2.29, 'hy_oas': 5.2, 'ig_oas': 1.64, 'ted_spread': 0.09, 'mortgage_30y': 6.73, 'vix': 26.13999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-15] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.04458, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-03-16 was +4.46%, which classifies as 'positive'.", "metadata": {"future_return": 0.04458, "horizon_days": 21, "hist_return": -0.156616, "annualized_vol": 0.860123, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240523_0635", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-05-23", "context_summary": "XLI over past 60 days: cumulative return +4.2%, annualized vol 10.5%. Market regime: bull.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=116.92, end=121.83, cumulative_return=+4.2%, annualized_volatility=10.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.43, 't10y3m_spread': -1.02, 'breakeven_10y': 2.33, 'hy_oas': 3.11, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.02, 'vix': 12.289999961853027}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.006945, "explanation": "The actual 21-day forward return for XLI starting 2024-05-23 was -0.69%, which classifies as 'flat'.", "metadata": {"future_return": -0.006945, "horizon_days": 21, "hist_return": 0.042007, "annualized_vol": 0.105361, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20241008_0638", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-10-08", "context_summary": "XLU over past 60 days: cumulative return +15.0%, annualized vol 14.4%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=33.07, end=38.03, cumulative_return=+15.0%, annualized_volatility=14.4%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.04, 't10y3m_spread': -0.74, 'breakeven_10y': 2.27, 'hy_oas': 2.95, 'ig_oas': 0.86, 'ted_spread': 0.09, 'mortgage_30y': 6.12, 'vix': 22.63999938964844}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 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2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.024283, "explanation": "The actual 21-day forward return for XLU starting 2024-10-08 was -2.43%, which classifies as 'negative'.", "metadata": {"future_return": -0.024283, "horizon_days": 21, "hist_return": 0.150271, "annualized_vol": 0.14387, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240401_0640", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-04-01", "context_summary": "AVAX-USD over past 60 days: cumulative return +60.0%, annualized vol 78.2%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=33.83, end=54.11, cumulative_return=+60.0%, annualized_volatility=78.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.26, 'breakeven_10y': 2.32, 'hy_oas': 3.15, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 13.010000228881836}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.237597, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-04-01 was -23.76%, which classifies as 'negative'.", "metadata": {"future_return": -0.237597, "horizon_days": 21, "hist_return": 0.59955, "annualized_vol": 0.781528, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230427_0643", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-04-27", "context_summary": "XLV over past 60 days: cumulative return -0.9%, annualized vol 13.4%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=126.37, end=125.29, cumulative_return=-0.9%, annualized_volatility=13.4%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.47, 't10y3m_spread': -1.68, 'breakeven_10y': 2.25, 'hy_oas': 4.63, 'ig_oas': 1.41, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 18.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-26] [\"Unusual Call Option Trade in Apple (AAPL) Worth $3,040.50K On April 26, 2023 at 15:31:16 ET an unusually large $3,040.50K block of Call contracts in Apple (AAPL) was sold, with a strike price of $167.50 / share, expiring in 23 day(s) (on May 19, 2023). Fintel tracks all large options trades, and the premium spent on this trade was 3.98 sigmas above the mean, placing it in the 100.00th percentile of all recent large trades made in AAPL options. This trade was first picked up on Fintel's real time Options Flow tool, where unusual option trades are highlighted. What is the Fund Sentiment? There are 6408 funds or institutions reporting positions in Apple. This is an increase of 189 owner(s) or 3.04% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 2.79%, a decrease of 26.22%. Total shares owned by institutions increased in the last three months by 0.12% to 10,139,399K shares. The put/call ratio of AAPL is 1.00, indicating a bullish outlook. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. Analyst Price Forecast Suggests 6.19% Upside As of April 24, 2023, the average one-year price target for Apple is $173.91. The forecasts range from a low of $117.16 to a high of $215.25. The average price target represents an increase of 6.19% from its latest reported closing price of $163.77. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is $413,641MM, an increase of 6.74%. The projected annual non-GAAP EPS is $6.36. What are Other Shareholders Doing? MAINSTAY VP FUNDS TRUST - MainStay VP T. Rowe Price Equity Income Portfolio Initial Class holds 144K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 150K shares, representing a decrease of 4.30%. The firm decreased its portfolio allocation in AAPL by 14.11% over the last quarter. Benchmark Investment Advisors holds 51K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 52K shares, representing a decrease of 1.70%. The firm decreased its portfolio allocation in AAPL by 9.34% over the last quarter. Lowery Thomas holds 2K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 3K shares, representing a decrease of 17.45%. The firm decreased its portfolio allocation in AAPL by 17.98% over the last quarter. Rbo & Co holds 105K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 104K shares, representing an increase of 0.40%. The firm decreased its portfolio allocation in AAPL by 99.92% over the last quarter. Invst holds 58K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 60K shares, representing a decrease of 2.99%. The firm decreased its portfolio allocation in AAPL by 99.91% over the last quarter. Apple Background Information (This descr\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.036782, "explanation": "The actual 21-day forward return for XLV starting 2023-04-27 was -3.68%, which classifies as 'negative'.", "metadata": {"future_return": -0.036782, "horizon_days": 21, "hist_return": -0.00852, "annualized_vol": 0.134175, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240207_0645", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-02-07", "context_summary": "ETH-USD over past 60 days: cumulative return +1.3%, annualized vol 44.6%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=2341.18, end=2372.20, cumulative_return=+1.3%, annualized_volatility=44.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.3, 't10y3m_spread': -1.35, 'breakeven_10y': 2.24, 'hy_oas': 3.52, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 13.0600004196167}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.396889, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-02-07 was +39.69%, which classifies as 'positive'.", "metadata": {"future_return": 0.396889, "horizon_days": 21, "hist_return": 0.013253, "annualized_vol": 0.445665, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230907_0648", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2023-09-07", "context_summary": "WEAT over past 60 days: cumulative return -11.8%, annualized vol 35.0%. Market regime: sideways.", "question": "Asset: WEAT\nHistorical prices (past 60 trading days): start=34.30, end=30.25, cumulative_return=-11.8%, annualized_volatility=35.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.71, 't10y3m_spread': -1.25, 'breakeven_10y': 2.3, 'hy_oas': 3.86, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 14.449999809265137}\nMarket regime: sideways\n\nPredict whether the return of WEAT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.023451, "explanation": "The actual 21-day forward return for WEAT starting 2023-09-07 was -2.35%, which classifies as 'negative'.", "metadata": {"future_return": -0.023451, "horizon_days": 21, "hist_return": -0.118076, "annualized_vol": 0.350369, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241218_0651", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-12-18", "context_summary": "IVV over past 60 days: cumulative return +5.8%, annualized vol 10.4%. Market regime: bull.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=563.25, end=595.79, cumulative_return=+5.8%, annualized_volatility=10.4%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.15, 't10y3m_spread': 0.02, 'breakeven_10y': 2.31, 'hy_oas': 2.75, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 15.869999885559082}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 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us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of IVV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.022137, "explanation": "The actual 21-day forward return for IVV starting 2024-12-18 was +2.21%, which classifies as 'positive'.", "metadata": {"future_return": 0.022137, "horizon_days": 21, "hist_return": 0.057768, "annualized_vol": 0.103905, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240402_0654", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-04-02", "context_summary": "XRP-USD over past 60 days: cumulative return +19.8%, annualized vol 62.9%. Market regime: bull.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.51, end=0.61, cumulative_return=+19.8%, annualized_volatility=62.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.39, 't10y3m_spread': -1.11, 'breakeven_10y': 2.35, 'hy_oas': 3.12, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 13.649999618530272}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.068846, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-04-02 was -6.88%, which classifies as 'negative'.", "metadata": {"future_return": -0.068846, "horizon_days": 21, "hist_return": 0.197578, "annualized_vol": 0.62893, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241223_0657", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-12-23", "context_summary": "ACWI over past 60 days: cumulative return -0.3%, annualized vol 10.7%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=116.59, end=116.19, cumulative_return=-0.3%, annualized_volatility=10.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.22, 't10y3m_spread': 0.18, 'breakeven_10y': 2.29, 'hy_oas': 2.86, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 18.36000061035156}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 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us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.027093, "explanation": "The actual 21-day forward return for ACWI starting 2024-12-23 was +2.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.027093, "horizon_days": 21, "hist_return": -0.003358, "annualized_vol": 0.107408, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20241105_0660", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-11-05", "context_summary": "BTC-USD over past 60 days: cumulative return +25.7%, annualized vol 32.0%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=53948.75, end=67811.51, cumulative_return=+25.7%, annualized_volatility=32.0%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.14, 't10y3m_spread': -0.34, 'breakeven_10y': 2.28, 'hy_oas': 2.87, 'ig_oas': 0.86, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 21.979999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.32621, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-11-05 was +32.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.32621, "horizon_days": 21, "hist_return": 0.256962, "annualized_vol": 0.320194, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240913_0663", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2024-09-13", "context_summary": "CSHI over past 60 days: cumulative return +1.0%, annualized vol 1.9%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=45.40, end=45.84, cumulative_return=+1.0%, annualized_volatility=1.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.04, 't10y3m_spread': -1.38, 'breakeven_10y': 2.05, 'hy_oas': 3.39, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.2, 'vix': 17.06999969482422}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00422, "explanation": "The actual 21-day forward return for CSHI starting 2024-09-13 was +0.42%, which classifies as 'flat'.", "metadata": {"future_return": 0.00422, "horizon_days": 21, "hist_return": 0.009718, "annualized_vol": 0.018811, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240917_0666", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2024-09-17", "context_summary": "SCHH over past 60 days: cumulative return +18.7%, annualized vol 14.1%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=18.74, end=22.25, cumulative_return=+18.7%, annualized_volatility=14.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.07, 't10y3m_spread': -1.33, 'breakeven_10y': 2.09, 'hy_oas': 3.32, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.2, 'vix': 17.139999389648438}\nMarket regime: sideways\n\nPredict whether the return of SCHH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.000889, "explanation": "The actual 21-day forward return for SCHH starting 2024-09-17 was -0.09%, which classifies as 'flat'.", "metadata": {"future_return": -0.000889, "horizon_days": 21, "hist_return": 0.187468, "annualized_vol": 0.140842, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241120_0669", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-11-20", "context_summary": "ETH-USD over past 60 days: cumulative return +18.9%, annualized vol 50.6%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=2615.86, end=3111.38, cumulative_return=+18.9%, annualized_volatility=50.6%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.12, 't10y3m_spread': -0.23, 'breakeven_10y': 2.34, 'hy_oas': 2.69, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 16.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.247587, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-11-20 was +24.76%, which classifies as 'positive'.", "metadata": {"future_return": 0.247587, "horizon_days": 21, "hist_return": 0.189432, "annualized_vol": 0.506491, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231016_0672", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2023-10-16", "context_summary": "TLH over past 60 days: cumulative return -9.2%, annualized vol 14.5%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=97.42, end=88.50, cumulative_return=-9.2%, annualized_volatility=14.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.41, 't10y3m_spread': -0.99, 'breakeven_10y': 2.34, 'hy_oas': 4.3, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 19.31999969482422}\nMarket regime: sideways\n\nPredict whether the return of TLH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.020607, "explanation": "The actual 21-day forward return for TLH starting 2023-10-16 was +2.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.020607, "horizon_days": 21, "hist_return": -0.091591, "annualized_vol": 0.144889, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241202_0674", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-12-02", "context_summary": "AVAX-USD over past 60 days: cumulative return +82.9%, annualized vol 76.3%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=24.65, end=45.09, cumulative_return=+82.9%, annualized_volatility=76.3%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.05, 't10y3m_spread': -0.4, 'breakeven_10y': 2.26, 'hy_oas': 2.74, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 13.510000228881836}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.253943, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-12-02 was -25.39%, which classifies as 'negative'.", "metadata": {"future_return": -0.253943, "horizon_days": 21, "hist_return": 0.829025, "annualized_vol": 0.762707, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230220_0677", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-02-20", "context_summary": "DOT-USD over past 60 days: cumulative return +64.4%, annualized vol 62.9%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.53, end=7.44, cumulative_return=+64.4%, annualized_volatility=62.9%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.78, 't10y3m_spread': -1.02, 'breakeven_10y': 2.36, 'hy_oas': 4.38, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 20.020000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.189189, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-02-20 was -18.92%, which classifies as 'negative'.", "metadata": {"future_return": -0.189189, "horizon_days": 21, "hist_return": 0.644069, "annualized_vol": 0.628551, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240329_0679", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-03-29", "context_summary": "^VIX over past 60 days: cumulative return -7.3%, annualized vol 70.2%. Market regime: bull.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=14.04, end=13.01, cumulative_return=-7.3%, annualized_volatility=70.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.26, 'breakeven_10y': 2.32, 'hy_oas': 3.12, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 13.010000228881836}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 wmt:A4875NotesDue2029Member 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2024-01-31 0000104169 srt:MaximumMember us-gaap:FurnitureAndFixturesMember 2024-01-31 0000104169 us-gaap:FurnitureAndFixturesMember 2024-01-31 0000104169 us-gaap:FurnitureAndFixturesMember 2023-01-31 0000104169 us-gaap:TransportationEquipmentMember srt:MinimumMember 2024-01-31 0000104169 srt:MaximumMember us-gaap:TransportationEquipmentMember 2024-01-31 0000104169 us-gaap:TransportationEquipmentMember 2024-01-31 0000104169 us-gaap:TransportationEquipmentMember 2023-01-31 0000104169 us-gaap:ConstructionInProgressMember 2024-01-31 0000104169 us-gaap:ConstructionInProgressMember 2023-01-31 0000104169 wmt:WalmartUSMember 2022-01-31 0000104169 wmt:WalmartInternationalMember 2022-01-31 0000104169 wmt:SamsClubMember 2022-01-31 0000104169 wmt:WalmartUSMember 2022-02-01 2023-01-31 0000104169 wmt:WalmartInternationalMember 2022-02-01 2023-01-31 0000104169 wmt:SamsClubMember 2022-02-01 2023-01-31 0000104169 wmt:WalmartUSMember 2023-01-31 0000104169 wmt:WalmartInternationalMember 2023-01-31 0000104169 wmt:SamsClubMember 2023-01-31 0000104169 wmt:WalmartUSMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartInternationalMember 2023-02-01 2024-01-31 0000104169 wmt:SamsClubMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartUSMember 2024-01-31 0000104169 wmt:WalmartInternationalMember 2024-01-31 0000104169 wmt:SamsClubMember 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2023-02-01 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2022-02-01 2023-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.074725, "explanation": "The actual 21-day forward return for ^VIX starting 2024-03-29 was +7.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.074725, "horizon_days": 21, "hist_return": -0.073362, "annualized_vol": 0.701895, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240703_0682", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-07-03", "context_summary": "LINK-USD over past 60 days: cumulative return +0.6%, annualized vol 58.1%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=14.32, end=14.40, cumulative_return=+0.6%, annualized_volatility=58.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.31, 't10y3m_spread': -1.04, 'breakeven_10y': 2.3, 'hy_oas': 3.23, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 12.029999732971191}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.016541, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-07-03 was -1.65%, which classifies as 'negative'.", "metadata": {"future_return": -0.016541, "horizon_days": 21, "hist_return": 0.006004, "annualized_vol": 0.581139, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240522_0685", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-05-22", "context_summary": "MATIC-USD over past 60 days: cumulative return -25.6%, annualized vol 67.2%. Market regime: bull.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.98, end=0.73, cumulative_return=-25.6%, annualized_volatility=67.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.41, 't10y3m_spread': -1.04, 'breakeven_10y': 2.32, 'hy_oas': 3.07, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.02, 'vix': 11.859999656677246}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.109027, "explanation": "The actual 21-day forward return for MATIC-USD starting 2024-05-22 was -10.90%, which classifies as 'negative'.", "metadata": {"future_return": -0.109027, "horizon_days": 21, "hist_return": -0.256354, "annualized_vol": 0.671797, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240508_0688", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-05-08", "context_summary": "MATIC-USD over past 60 days: cumulative return -40.1%, annualized vol 75.3%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=1.16, end=0.69, cumulative_return=-40.1%, annualized_volatility=75.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.35, 't10y3m_spread': -0.98, 'breakeven_10y': 2.32, 'hy_oas': 3.06, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 13.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.047598, "explanation": "The actual 21-day forward return for MATIC-USD starting 2024-05-08 was +4.76%, which classifies as 'positive'.", "metadata": {"future_return": 0.047598, "horizon_days": 21, "hist_return": -0.401405, "annualized_vol": 0.753329, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230614_0690", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-06-14", "context_summary": "XLK over past 60 days: cumulative return +18.9%, annualized vol 18.6%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=70.29, end=83.58, cumulative_return=+18.9%, annualized_volatility=18.6%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.83, 't10y3m_spread': -1.52, 'breakeven_10y': 2.2, 'hy_oas': 4.18, 'ig_oas': 1.39, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 14.609999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-13] [\"US STOCKS-S&P 500, Nasdaq hit fresh 1-yr highs as inflation data boosts rate pause hopes By Shristi Achar A and Sruthi Shankar June 13 (Reuters) - The S&P 500 and Nasdaq rose to fresh one-year highs on Tuesday after data showed consumer prices rose modestly in May, boosting hopes that the Federal Reserve could skip raising interest rates at the end of its policy meeting on Wednesday. The U.S. Labor Department report showed consumer price index(CPI) rose 0.1% last month compared with a 0.4% jump in April, with core inflation remaining unchanged at 0.4%. On a year-on-year basis, headline inflation increased by a lower-than-estimated 4.0%, reflecting declines in the cost of energy products and services, including gasoline and electricity. \\\"The data basically came within consensus estimates, except that core inflation remained stubbornly high,\\\" said Quincy Krosby, chief global strategist at LPL Financial. \\\"For tomorrow, the market is not expecting a rate hike and hoping that when we come to July 26, core inflation will come down in a more material way.\\\" Traders have priced in a 92% chance that the U.S. central bank will hold interest rates at the 5%-5.25% range on Wednesday but see a 60% chance of another 25-basis-point hike in July, according to the CME Fedwatch tool. The S&P 500 and Nasdaq have hit fresh highs for the year in the past few sessions, lifted by market heavyweights such as Amazon.com AMZN.O, Apple AAPL.O and Tesla TSLA.O. The benchmark S&P 500 has risen 21% from its October 2022 lows, heralding a bull market according to some investors. The rally, which has largely been driven by gains in megacap stocks, has broadened recently to include economy-linked sectors such as energy .SPNY and materials .SPLRCM as well as small-cap stocks. The two sectors were up 1.5% and 2.2%, respectively, as commodity prices including those of oil and copper climbed against a falling dollar, also underpinned by hopes of more support for China's slowing economy. O/RMET/L The small-cap Russell 2000 index .RUT jumped 1.4% to hit a fresh three-month high. \\\"Having the Russell 2000 compliment the move in the Nasdaq is helpful to push back concerns that this is still a very narrow led market,\\\" Krosby said. U.S.-listed shares of Chinese companies including JD.com JD.O, Alibaba Group BABA.N, Baidu BIDU.O and Netease NTES.O rose, tracking gains in Shanghai markets, after China's central bank lowered its short-term lending rate for the first time in 10 months. At 12:49 p.m. ET, the Dow Jones Industrial Average .DJI was up 171.66 points, or 0.50%, at 34,237.99, the S&P 500 .SPX was up 30.07 points, or 0.69%, at 4,369.00, and the Nasdaq Composite .IXIC was up 97.95 points, or 0.73%, at 13,559.87. OracleORCL.N rose 1%, having hit a record high earlier on upbeat quarterly revenue and forecast, while IntelINTC.O gained 1.8% on talks with SoftBank Group Corp's 9984.T Arm to be an anchor investor in its initial public offering. Bunge Ltd BG.N added 1.8% after the U.S.\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.022903, "explanation": "The actual 21-day forward return for XLK starting 2023-06-14 was +2.29%, which classifies as 'positive'.", "metadata": {"future_return": 0.022903, "horizon_days": 21, "hist_return": 0.18895, "annualized_vol": 0.185695, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230904_0693", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-09-04", "context_summary": "ADA-USD over past 60 days: cumulative return -8.5%, annualized vol 59.1%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.28, end=0.26, cumulative_return=-8.5%, annualized_volatility=59.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.69, 't10y3m_spread': -1.35, 'breakeven_10y': 2.26, 'hy_oas': 3.81, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 13.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-03] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.040075, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-09-04 was -4.01%, which classifies as 'negative'.", "metadata": {"future_return": -0.040075, "horizon_days": 21, "hist_return": -0.085474, "annualized_vol": 0.59081, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241101_0696", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-11-01", "context_summary": "QUAL over past 60 days: cumulative return +5.8%, annualized vol 12.8%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=164.24, end=173.78, cumulative_return=+5.8%, annualized_volatility=12.8%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.12, 't10y3m_spread': -0.36, 'breakeven_10y': 2.33, 'hy_oas': 2.88, 'ig_oas': 0.86, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 23.15999984741211}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q META 2024-10-31] meta-20240930 false 2024 Q3 0001326801 12/31 545 287 xbrli:shares iso4217:USD iso4217:USD xbrli:shares meta:employee xbrli:pure meta:objector meta:appeal iso4217:EUR meta:classAction meta:notice meta:reportable_segment 0001326801 2024-01-01 2024-09-30 0001326801 us-gaap:CommonClassAMember 2024-10-25 0001326801 us-gaap:CommonClassBMember 2024-10-25 0001326801 2024-09-30 0001326801 2023-12-31 0001326801 us-gaap:CommonClassAMember 2024-09-30 0001326801 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The plan will terminate on February 13, 2026 , subject to early termination for certain specified events set forth in the plan. 91 Table of Contents Item 6. Exhibits Exhibit Number Incorporated by Reference Filed Herewith Exhibit Description Form File No. Exhibit Filing Date 3.1 Amended and Restated Bylaws. 8-K 001-35551 3.1 September 10, 2024 4.1 Third Supplemental Indenture, dated as of August 9, 2024, by and between Meta Platforms, Inc. and U.S. Bank Trust Company, National Association, as trustee . 8-K 001-35551 4.1 August 9, 2024 10.1* F orm of Director Aircraft Time Sharing Agreement. X 31.1 Certification of Mark Zuckerberg, Chief Executive Officer, pursuant to Rule 13a-14(a)/15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 . X 31.2 Certification of Susan Li, Chief Financial Officer, pursuant to Rule 13a-14(a)/15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002. X 32.1# Certification of Mark Zuckerberg, Chief Executive Officer, pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 . X 32.2# Certification of Susan Li, Chief Financial Officer, pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002. X 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document). X 101.SCH Inline XBRL Taxonomy Extension Schema Document. X 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. X 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. X 101.LAB Inline XBRL Taxonomy Extension Labels Linkbase Document. X 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. X 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101). X * Certain portions of this exhibit have been omitted pursuant to Item 601(b)(10) of Regulation S-K. # This certification is deemed not filed for purposes of Section 18 of the Securities Exchange Act of 1934, as amended (Exchange Act), or otherwise subject to the liability of that section, nor shall it be deemed incorporated by reference into any filing under the Securities Act of 1933, as amended, or the Exchange Act. 92 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Quarterly Report on Form 10-Q to be signed on its behalf by the undersigned, thereunto duly authorized, in the City of Menlo Park, State of California, on this 30th day of October 2024.     META PLATFORMS, INC. Date: October 30, 2024 /s/ SUSAN LI Susan Li Chief Financial Officer (Principal Financial Officer) Date: October 30, 2024 /s/ AARON ANDERSON Aaron Anderson Chief Accounting Officer (Principal Accounting Officer) 93\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.0502, "explanation": "The actual 21-day forward return for QUAL starting 2024-11-01 was +5.02%, which classifies as 'positive'.", "metadata": {"future_return": 0.0502, "horizon_days": 21, "hist_return": 0.058099, "annualized_vol": 0.128035, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240820_0699", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-08-20", "context_summary": "DOT-USD over past 60 days: cumulative return -20.1%, annualized vol 59.7%. Market regime: bull.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=5.61, end=4.48, cumulative_return=-20.1%, annualized_volatility=59.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.2, 't10y3m_spread': -1.45, 'breakeven_10y': 2.07, 'hy_oas': 3.21, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.49, 'vix': 14.649999618530272}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.061195, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-08-20 was -6.12%, which classifies as 'negative'.", "metadata": {"future_return": -0.061195, "horizon_days": 21, "hist_return": -0.200897, "annualized_vol": 0.597215, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231027_0702", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-10-27", "context_summary": "DOT-USD over past 60 days: cumulative return -8.0%, annualized vol 37.0%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.61, end=4.24, cumulative_return=-8.0%, annualized_volatility=37.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.16, 't10y3m_spread': -0.73, 'breakeven_10y': 2.42, 'hy_oas': 4.5, 'ig_oas': 1.3, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 20.68000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-26] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.266428, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-10-27 was +26.64%, which classifies as 'positive'.", "metadata": {"future_return": 0.266428, "horizon_days": 21, "hist_return": -0.080244, "annualized_vol": 0.369688, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231128_0705", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-11-28", "context_summary": "QQQ over past 60 days: cumulative return +3.2%, annualized vol 17.0%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=371.52, end=383.47, cumulative_return=+3.2%, annualized_volatility=17.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.45, 't10y3m_spread': -1.1, 'breakeven_10y': 2.21, 'hy_oas': 3.89, 'ig_oas': 1.14, 'ted_spread': 0.09, 'mortgage_30y': 7.29, 'vix': 12.6899995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-27] [\"Australia to amend law to regulate digital payments like Apple, Google Pay SYDNEY, Nov 27 (Reuters) - Australia's government said on Monday it would bring Apple Pay, Google Pay and other digital payment services under the same regulatory umbrella as credit cards and other payments as part of legislation set to be introduced to parliament this week. Digital wallets from the likes of Apple AAPL.O, Google GOOGL.O and WeChat developer Tencent 0700.HK have exploded in popularity but are not captured by Australian payments law. The legislation, first flagged last month, will broaden the legislation that empowers the Reserve Bank of Australia to regulate payments so that it applies to new and emerging technology. \\\"We are modernising Australia's payments system to ensure it meets the needs of our economy now and into the future,\\\" Treasurer Jim Chalmers said in a statement. \\\"We want to make sure the increasing use of digital payments occurs in a way that helps promote greater competition, innovation and productivity across our entire economy.\\\" Legislation is set to be introduced on Wednesday or Thursday, according to Chalmers' office. Regulators are responding to the rapid growth of digital wallets, especially among the young. Transactions from a digital wallet hit 35% of all card transactions in the June quarter, up from 10% in early 2020. Two-thirds of Australians aged between 18 and 29 use mobile payments. Before the pandemic it was less than 20%. The amendments will also give a relevant minister power to subject a system or platform to special oversight in the event it presents a risk of \\\"national significance.\\\" (Reporting by Lewis Jackson; Editing by Jamie Freed) ((lewis.jackson@thomsonreuters.com; +61477406822; Reuters Messaging: @lewjackk)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"3 Stocks to Add to Your Portfolio in a Market Pullback \\\"Be prepared, work hard, and hope for a little luck. Recognize that the harder you work and the better prepared you are, the more luck you might have.\\\" -- Ed Bradley Those words of wisdom apply to many aspects of life, such as sports and your career. They apply very much to investing as well. If you work hard -- perhaps by reading widely -- you can become a savvy investor, able to spot red flags and green flags in financial statements and identify high-quality, growing companies. Ideally, though, you don't want to invest in those companies at just any price. Instead, aim to buy when they're undervalued -- say, after a market pullback -- thus giving you a margin of safety. Below are three such contenders to consider. If you like any of them, add them to a watch list and wait for a better price. 1. Apple Apple (NASDAQ: AAPL) is one of the biggest companies in the world with a recent market value near $3 trillion and a lofty mission: \\\"Apple's more than 100,000 employees are dedicated to making the best products on E\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.056763, "explanation": "The actual 21-day forward return for QQQ starting 2023-11-28 was +5.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.056763, "horizon_days": 21, "hist_return": 0.03216, "annualized_vol": 0.169652, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231214_0708", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-12-14", "context_summary": "IWM over past 60 days: cumulative return +8.0%, annualized vol 21.1%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=174.02, end=187.93, cumulative_return=+8.0%, annualized_volatility=21.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.42, 't10y3m_spread': -1.4, 'breakeven_10y': 2.16, 'hy_oas': 3.79, 'ig_oas': 1.08, 'ted_spread': 0.09, 'mortgage_30y': 7.03, 'vix': 12.1899995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-13] [\"Zacks Investment Ideas feature highlights: Tesla, Apple and Rivian For Immediate Release Chicago, IL \\u2013 December 15, 2023 \\u2013 Today, Zacks Investment Ideas feature highlights Tesla TSLA, Apple AAPL and Rivian RIVN. Why Tesla's Cheap (2024 Outlook) An Up and Down Year for Tesla Tesla is the undisputed market leader in battery-powered electric car sales in the United States, enjoying roughly a 70% market share. Over the years, Tesla has shifted from developing niche products for affluent buyers to more affordable EVs for the masses. The firm's three-pronged business model approach of direct sales, servicing, and charging sets it apart from other carmakers. Year-to-date, shares are higher by 128%. However, investor concerns are mounting, including: \\u00b7 Valuation: The EV king's market capitalization is more than the combined value of all legacy automakers. \\u00b7 Underperformance: Though Tesla has more than doubled this year, it has underperformed the market and \\\"Magnificent 7\\\" recently. \\u00b7 Recall: This week, news broke that Tesla must recall more than 2 million vehicles. Below, I will debunk the most common investor concerns and lay out my bull case for the stock: Don't Judge a Book By its Cover: Tesla Valuation is Cheap The price-to-book ratio (P/B ratio) is a financial metric that compares a company's market value (its stock price) to its book value (the net value of its assets minus liabilities). P/B is calculated by dividing the market price per share by the book value per share. A low P/B ratio may suggest that a stock is undervalued, while a high ratio may indicate overvaluation. Investors use this ratio to assess a company's relative worth in the market compared to its accounting value. Tesla currently has a book value of 14.03. Compare that to another mainstream stock like Apple, whose book value is 49.54, and Tesla suddenly looks cheap. Furthermore, it is essential to remember that Wall Street is a discounting device. Over the past twelve years, Tesla has achieved a stunning compound annual growth rate (CAGR) of 72%, earning its premium above slower-growing legacy automakers. Rallying on Negative Recall News Earlier this week, Tesla was forced to recall over two million vehicles over autopilot safety concerns. As I always like to remind investors, the reaction to negative news supersedes the news itself. In the case of TSLA, the stock shook off the bad news and is green for the week. Technical \\\"Shakeout\\\" and Price Rotation Higher Savvy investors understand that price movement is the ultimate arbiter of decisions, because after all, price is the only thing that pays. TSLA shares sliced below the 50-day moving average on the recall news and then ripped higher. Such price action indicates a shakeout, where weak hands get stopped out of their positions, clearing the way for the next move higher. Now, TSLA is triggering a bullish swing trade signal by clearing last week's highs. Cybertruck Hype Real Many Tesla bears suggest t\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.024013, "explanation": "The actual 21-day forward return for IWM starting 2023-12-14 was -2.40%, which classifies as 'negative'.", "metadata": {"future_return": -0.024013, "horizon_days": 21, "hist_return": 0.079937, "annualized_vol": 0.211255, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230502_0710", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-05-02", "context_summary": "MTUM over past 60 days: cumulative return +1.7%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=136.52, end=138.82, cumulative_return=+1.7%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.55, 't10y3m_spread': -1.68, 'breakeven_10y': 2.23, 'hy_oas': 4.45, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.43, 'vix': 16.079999923706055}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-01] [\"B of A Securities Maintains Apple (AAPL) Neutral Recommendation Fintel reports that on May 1, 2023, B of A Securities maintained coverage of Apple (NASDAQ:AAPL) with a Neutral recommendation. Analyst Price Forecast Suggests 2.49% Upside As of April 24, 2023, the average one-year price target for Apple is 173.91. The forecasts range from a low of 117.16 to a high of $215.25. The average price target represents an increase of 2.49% from its latest reported closing price of 169.68. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is 413,641MM, an increase of 6.74%. The projected annual non-GAAP EPS is 6.36. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. What is the Fund Sentiment? There are 6412 funds or institutions reporting positions in Apple. This is an increase of 218 owner(s) or 3.52% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 2.90%, a decrease of 12.63%. Total shares owned by institutions increased in the last three months by 0.01% to 10,120,461K shares. The put/call ratio of AAPL is 1.01, indicating a bearish outlook. What are Other Shareholders Doing? Berkshire Hathaway holds 895,136K shares representing 5.66% ownership of the company. In it's prior filing, the firm reported owning 894,802K shares, representing an increase of 0.04%. The firm decreased its portfolio allocation in AAPL by 6.86% over the last quarter. VTSMX - Vanguard Total Stock Market Index Fund Investor Shares holds 459,387K shares representing 2.90% ownership of the company. In it's prior filing, the firm reported owning 455,109K shares, representing an increase of 0.93%. The firm decreased its portfolio allocation in AAPL by 12.36% over the last quarter. VFINX - Vanguard 500 Index Fund Investor Shares holds 345,686K shares representing 2.18% ownership of the company. In it's prior filing, the firm reported owning 342,454K shares, representing an increase of 0.94%. The firm decreased its portfolio allocation in AAPL by 12.57% over the last quarter. Geode Capital Management holds 282,750K shares representing 1.79% ownership of the company. In it's prior filing, the firm reported owning 279,759K shares, representing an increase of 1.06%. The firm decreased its portfolio allocation in AAPL by 12.15% over the last quarter. Price T Rowe Associates holds 226,281K shares representing 1.43% ownership of the company. In it's prior filing, the firm reported owning 224,864K shares, representing an increase of 0.63%. The firm decreased its portfolio allocation in AAPL by 7.53% over the last quarter. Apple Background Information (This description is provided by the company.) Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services. It is considered one of the Big Five companies in the U.S. informat\n\nPredict whether the return of MTUM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.024173, "explanation": "The actual 21-day forward return for MTUM starting 2023-05-02 was -2.42%, which classifies as 'negative'.", "metadata": {"future_return": -0.024173, "horizon_days": 21, "hist_return": 0.016896, "annualized_vol": 0.143023, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230704_0712", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-07-04", "context_summary": "VEA over past 60 days: cumulative return +3.0%, annualized vol 12.7%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=41.12, end=42.35, cumulative_return=+3.0%, annualized_volatility=12.7%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.58, 'breakeven_10y': 2.25, 'hy_oas': 3.99, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 13.56999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-03] [\"Unity Software Stock Skyrockets 46% in June as AI Buzz Takes Over What happened Shares of Unity Software (NYSE: U) skyrocketed 46.1% in June, according to data provided by S&P Global Market Intelligence. The month started off with fireworks from Apple that are relevant to Unity shareholders. And it ended with a bang related to artificial intelligence (AI), Wall Street's favorite subject at the moment. So what To give this story some context, I want to point out that the market had lost a lot of confidence in Unity Software stock. When they first went public, shares regularly traded above a price-to-sales (P/S) ratio of 30. By comparison, they traded below a P/S of 7 at the start of June. That's still high in absolute terms. But in relative terms, this valuation was more than 80% below where it had routinely traded. Unity's own revenue growth was ample reason for the market's pessimism. And even though its growth has since rebounded, as the chart below shows, this is largely due to an acquisition. Its organic growth is still challenged. U Revenue (quarterly YoY growth) data by YCharts; YoY = year over year. But on June 5, Apple announced its upcoming Vision Pro headset, and this has reinvigorated investors' excitement for Unity's potential. Apple is looking for apps to be built for the headset between now and its launch in 2024. And for this, the company has partnered with Unity. Developers use Unity for building top-notch video games. And Apple has created a software development kit that will allow Unity users to modify their creations for the Vision Pro. Then on June 27, Unity announced a marketplace for AI applications. The marketplace has 10 apps available at launch that can be used in the video game space. And when the company announced this new focus on AI, the market celebrated by pushing the stock higher. So the stock started June with low expectations, but Apple and AI have investors rethinking the long-term potential. Now what When it comes to the AI space, I'm inclined to disregard most news as overhyped clickbait. But with Unity Software stock, I do believe that AI -- specifically generative AI -- could play an important role for the business. Many investors like Unity's potential in virtual reality and the metaverse. Its software creates realistic 3D images, and realism is needed to make these experiences something that consumers actually want. When building digital worlds, the problem is how big these need to be -- it's labor intensive for developers. And the workload is probably too much to physically handle at scale, which is where generative AI can help. Much of what Unity is doing involves generative AI, which I believe is just what the space needs. So as virtual reality and the metaverse grow -- perhaps thanks to Apple's Vision Pro headset -- the use cases for Unity Software could open up as well. That's good reason for optimism for a stock that's still down almost 80% from its all-time high. 10 stocks we like better than Unit\n\nPredict whether the return of VEA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.006338, "explanation": "The actual 21-day forward return for VEA starting 2023-07-04 was +0.63%, which classifies as 'flat'.", "metadata": {"future_return": 0.006338, "horizon_days": 21, "hist_return": 0.029945, "annualized_vol": 0.126648, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230213_0714", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-02-13", "context_summary": "DOT-USD over past 60 days: cumulative return +18.2%, annualized vol 59.7%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=5.23, end=6.18, cumulative_return=+18.2%, annualized_volatility=59.7%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.76, 't10y3m_spread': -1.05, 'breakeven_10y': 2.33, 'hy_oas': 4.24, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 6.12, 'vix': 20.530000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-12] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.032468, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-02-13 was -3.25%, which classifies as 'negative'.", "metadata": {"future_return": -0.032468, "horizon_days": 21, "hist_return": 0.181737, "annualized_vol": 0.597086, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230523_0715", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-05-23", "context_summary": "BTC-USD over past 60 days: cumulative return -2.3%, annualized vol 30.7%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=27493.29, end=26851.28, cumulative_return=-2.3%, annualized_volatility=30.7%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.57, 't10y3m_spread': -1.68, 'breakeven_10y': 2.24, 'hy_oas': 4.54, 'ig_oas': 1.44, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 17.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-22] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.048006, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-05-23 was -4.80%, which classifies as 'negative'.", "metadata": {"future_return": -0.048006, "horizon_days": 21, "hist_return": -0.023351, "annualized_vol": 0.307055, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240604_0717", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-06-04", "context_summary": "ACWI over past 60 days: cumulative return +3.0%, annualized vol 10.5%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=104.50, end=107.63, cumulative_return=+3.0%, annualized_volatility=10.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.41, 't10y3m_spread': -1.11, 'breakeven_10y': 2.33, 'hy_oas': 3.17, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 7.03, 'vix': 13.109999656677246}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.040239, "explanation": "The actual 21-day forward return for ACWI starting 2024-06-04 was +4.02%, which classifies as 'positive'.", "metadata": {"future_return": 0.040239, "horizon_days": 21, "hist_return": 0.029888, "annualized_vol": 0.1048, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230615_0719", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-06-15", "context_summary": "IWM over past 60 days: cumulative return +5.9%, annualized vol 20.1%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=169.82, end=179.88, cumulative_return=+5.9%, annualized_volatility=20.1%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.53, 'breakeven_10y': 2.21, 'hy_oas': 4.18, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 13.880000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-14] [\"The Zacks Analyst Blog Highlights Apple, UnitedHealth, Eli Lilly, Walmart and Becton, Dickinson For Immediate Release Chicago, IL \\u2013 June 14, 2023 \\u2013 Zacks.com announces the list of stocks featured in the Analyst Blog. Every day the Zacks Equity Research analysts discuss the latest news and events impacting stocks and the financial markets. Stocks recently featured in the blog include: Apple Inc. AAPL, UnitedHealth Group Incorporated UNH, Eli Lilly and Company LLY, Walmart Inc. WMT and Becton, Dickinson and Company BDX. Here are highlights from Tuesday\\u2019s Analyst Blog: Top Stock Reports for Apple, UnitedHealth & Eli Lilly The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc., UnitedHealth Group Incorporated and Eli Lilly and Company. These research reports have been hand-picked from the roughly 70 reports published by our analyst team today. You can see all of today\\u2019s research reports here >>> Apple shares have outperformed the Zacks Tech sector (+40.4% vs. +34.9%) as well as the broader market (+40.4% vs. +14.1%) this year. The company is benefiting from steady demand for iPhone 14 and 14 Plus as well as expanding footprint in emerging markets. Growing services subscriber base and improving customer engagement are tailwinds for the services business. Apple is expanding service offerings with the new features and enhancements in its upcoming iOS 17, iPadOS 17, macOS Sonoma, watchOS 10, and tvOS 17. Expanding content on Apple TV+ bodes well for Apple. Growing footprint in enterprise market is encouraging. However, services\\u2019 revenue growth in the fiscal third quarter is expected to be similar to the fiscal second quarter. Apple expects services to be negatively impacted by challenging macroeconomic conditions, as well as continued weakness in digital advertising and mobile gaming. (You can read the full research report on Apple here >>>) Shares of UnitedHealth have gained +8.2% over the past year against the Zacks Medical - HMOs industry\\u2019s gain of +10.0%. Company\\u2019s top line remains well-poised for growth on the back of a strong market position, new deals, renewed agreements, and expansion of service offerings. The Zacks analyst expect the top line to grow 11.1% year over year in 2023. Its solid health services segment provides diversification benefits. The Government business remains well-poised for growth. A sturdy balance sheet enables business investments and prudent deployment of capital. However, membership in its global business continues to decline. High operating costs are hurting margins. As such, the stock warrants a cautious stance. (You can read the full research report on UnitedHealth here >>>) Eli Lilly shares have outperformed the Zacks Large Cap Pharmaceuticals industry over the past year (+55.0% vs. +19.1%). The company boasts a solid portfolio of core drugs in diabetes, autoimmun\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.02182, "explanation": "The actual 21-day forward return for IWM starting 2023-06-15 was +2.18%, which classifies as 'positive'.", "metadata": {"future_return": 0.02182, "horizon_days": 21, "hist_return": 0.059229, "annualized_vol": 0.200963, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230306_0721", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-03-06", "context_summary": "ETH-USD over past 60 days: cumulative return +25.1%, annualized vol 44.3%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1250.44, end=1564.47, cumulative_return=+25.1%, annualized_volatility=44.3%\nMacro context: {'fed_funds_rate': 4.57, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.89, 't10y3m_spread': -0.94, 'breakeven_10y': 2.52, 'hy_oas': 4.05, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 18.489999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-05] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.094464, "explanation": "The actual 21-day forward return for ETH-USD starting 2023-03-06 was +9.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.094464, "horizon_days": 21, "hist_return": 0.251136, "annualized_vol": 0.442762, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240327_0723", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-03-27", "context_summary": "BNB-USD over past 60 days: cumulative return +89.7%, annualized vol 67.3%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=305.82, end=580.15, cumulative_return=+89.7%, annualized_volatility=67.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.32, 't10y3m_spread': -1.22, 'breakeven_10y': 2.32, 'hy_oas': 3.15, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 13.239999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.069791, "explanation": "The actual 21-day forward return for BNB-USD starting 2024-03-27 was -6.98%, which classifies as 'negative'.", "metadata": {"future_return": -0.069791, "horizon_days": 21, "hist_return": 0.897003, "annualized_vol": 0.673032, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240822_0725", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-08-22", "context_summary": "EEM over past 60 days: cumulative return +2.3%, annualized vol 15.7%. Market regime: bull.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=40.97, end=41.92, cumulative_return=+2.3%, annualized_volatility=15.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.13, 't10y3m_spread': -1.47, 'breakeven_10y': 2.07, 'hy_oas': 3.27, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.49, 'vix': 16.270000457763672}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-01-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-04-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-04-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-01-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2024-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-03-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-03-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-03-31 0000731766 us-gaap:NoncontrollingInterestMember 2024-03-31 0000731766 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-04-01 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-04-01 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-04-01 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-04-01 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-04-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000731766 us-gaap:RetainedEarningsMember 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-06-30 0000731766 us-gaap:CommonStockMember 2023-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-03-31 0000731766 us-gaap:RetainedEarningsMember 2023-03-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-03-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-03-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-03-31 0000731766 2023-03-31 0000731766 us-gaap:RetainedEarningsMember 2023-04-01 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-04-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-04-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-04-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-04-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-04-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-06-30 0000731766 us-gaap:RetainedEarningsMember 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-06-30 0000731766 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2024-01-01 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-01-01 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-06-30 0000731766 unh:ProductsAndServicesMember 2024-06-30 0000731766 unh:ProductsAndServicesMember 2023-12-31 0000731766 2024-07-01 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2024-06-30 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2024-06-30 0000731766 us-gaap:CorporateDebtSecuritiesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nPredict whether the return of EEM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.013219, "explanation": "The actual 21-day forward return for EEM starting 2024-08-22 was +1.32%, which classifies as 'positive'.", "metadata": {"future_return": 0.013219, "horizon_days": 21, "hist_return": 0.023312, "annualized_vol": 0.157497, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240724_0727", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-07-24", "context_summary": "LINK-USD over past 60 days: cumulative return -20.2%, annualized vol 60.8%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=17.44, end=13.92, cumulative_return=-20.2%, annualized_volatility=60.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.15, 't10y3m_spread': -1.16, 'breakeven_10y': 2.29, 'hy_oas': 3.02, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 14.720000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.223515, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-07-24 was -22.35%, which classifies as 'negative'.", "metadata": {"future_return": -0.223515, "horizon_days": 21, "hist_return": -0.201894, "annualized_vol": 0.607768, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230602_0728", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-06-02", "context_summary": "XLK over past 60 days: cumulative return +18.6%, annualized vol 19.6%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=68.52, end=81.27, cumulative_return=+18.6%, annualized_volatility=19.6%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.72, 't10y3m_spread': -1.68, 'breakeven_10y': 2.16, 'hy_oas': 4.65, 'ig_oas': 1.42, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 15.649999618530272}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-01] [\"GRAPHIC-Nvidia runaway winner in market cap addition in May June 1 (Reuters) - Nvidia Corp's NVDA.OQ market capitalisation jumped the most in May among the top 20 global companies by market value, adding $248 billion, with a majority of the gains coming in the last four sessions, according to Refinitiv data. The chipmaker briefly joined the $1 trillion valuation club, as investors bet on its potential to become a major beneficiary of a boom in artificial intelligence following a revenue forecast that was more than 50% above the Wall Street estimate The company's shares are up 159% so far this year. Taiwan Semiconductor Manufacturing Co Ltd 2330.TW, a key manufacturer of Nvidia's chips, also saw a big jump in its market cap last month. Saudi Arabian Oil 2222.SE and Exxon Mobil Corp XOM.N were the biggest losers in terms of market cap, hit by a decline in oil prices last month. Apple AAPL.OQ and Microsoft MSFT.OQ led the list with the highest market capitalisation in the world. Top 20 companies in the world by market cap https://tmsnrt.rs/45JVJXt Change in market cap in May https://tmsnrt.rs/3qgKBRH (Reporting By Patturaja Murugaboopathy and Gaurav Dogra in Bengaluru; Editing by Sriraj Kalluvila) ((patturaja.muruga@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Meta's Zuckerberg unveils Quest 3 mixed reality headset NEW YORK, June 1 (Reuters) - Meta Platforms META.O CEO Mark Zuckerberg revealed the company's next generation mixed reality headset, the Quest 3, in an Instagram post on Thursday as part of its annual gaming conference. The announcement came less than a week before tech rival Apple AAPL.O was expected to unveil its first mixed reality device, which combines augmented and virtual reality elements. Meta currently dominates the market for AR/VR devices, with a nearly 80% share of the 8.8 million headsets sold in 2022, according to an estimate by market research firm IDC. (Reporting by Katie Paul; Editing by Lisa Shumaker) ((Katie.Paul@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Meta's Zuckerberg unveils Quest 3 mixed reality headset By Katie Paul NEW YORK, June 1 (Reuters) - Meta Platforms META.O CEO Mark Zuckerberg revealed the company's next generation mixed reality headset, the Quest 3, in an Instagram post on Thursday as part of its annual gaming conference. Priced starting at $499, the device will be 40% thinner than the company's previous device and feature color mixed reality, which combines augmented and virtual reality elements, Zuckerberg said in his post. The Quest 3 also will have a new Qualcomm chipset with twice the graphics performance, Zuckerberg said, and promised more details at the company's virtual reality conference in September. Zuckerberg's announcement came less than a week before tech rival\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.041662, "explanation": "The actual 21-day forward return for XLK starting 2023-06-02 was +4.17%, which classifies as 'positive'.", "metadata": {"future_return": 0.041662, "horizon_days": 21, "hist_return": 0.186194, "annualized_vol": 0.196391, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240826_0730", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-08-26", "context_summary": "SOL-USD over past 60 days: cumulative return +6.3%, annualized vol 78.9%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=149.45, end=158.91, cumulative_return=+6.3%, annualized_volatility=78.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.09, 't10y3m_spread': -1.44, 'breakeven_10y': 2.13, 'hy_oas': 3.19, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.46, 'vix': 15.859999656677246}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.163856, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-08-26 was -16.39%, which classifies as 'negative'.", "metadata": {"future_return": -0.163856, "horizon_days": 21, "hist_return": 0.063304, "annualized_vol": 0.789333, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240108_0732", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-01-08", "context_summary": "LINK-USD over past 60 days: cumulative return -10.2%, annualized vol 70.9%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=14.64, end=13.14, cumulative_return=-10.2%, annualized_volatility=70.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.35, 't10y3m_spread': -1.42, 'breakeven_10y': 2.22, 'hy_oas': 3.68, 'ig_oas': 1.09, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 13.350000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.058717, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-01-08 was +5.87%, which classifies as 'positive'.", "metadata": {"future_return": 0.058717, "horizon_days": 21, "hist_return": -0.102186, "annualized_vol": 0.70946, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240812_0734", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-08-12", "context_summary": "AVAX-USD over past 60 days: cumulative return -34.1%, annualized vol 78.1%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=30.98, end=20.43, cumulative_return=-34.1%, annualized_volatility=78.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.11, 't10y3m_spread': -1.39, 'breakeven_10y': 2.1, 'hy_oas': 3.49, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.47, 'vix': 20.3700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.050699, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-08-12 was +5.07%, which classifies as 'positive'.", "metadata": {"future_return": 0.050699, "horizon_days": 21, "hist_return": -0.340658, "annualized_vol": 0.781389, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231103_0736", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-11-03", "context_summary": "XRP-USD over past 60 days: cumulative return +19.3%, annualized vol 31.4%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.51, end=0.61, cumulative_return=+19.3%, annualized_volatility=31.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.31, 't10y3m_spread': -0.87, 'breakeven_10y': 2.4, 'hy_oas': 4.15, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 15.65999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-02] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.014484, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-11-03 was +1.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.014484, "horizon_days": 21, "hist_return": 0.192897, "annualized_vol": 0.31432, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231215_0738", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-12-15", "context_summary": "IWM over past 60 days: cumulative return +12.7%, annualized vol 21.7%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=171.32, end=193.16, cumulative_return=+12.7%, annualized_volatility=21.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.45, 't10y3m_spread': -1.51, 'breakeven_10y': 2.22, 'hy_oas': 3.47, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-14] [\"3 No-Brainer Dividend Stocks to Buy and Hold for 20 Years Successful investing is not as complicated as some make it out to be. Sticking with the brands you use every day, and holding for many years, is a great place to start. Top stocks, such as Apple (NASDAQ: AAPL), Starbucks (NASDAQ: SBUX), and Costco Wholesale (NASDAQ: COST), have a long record of beating the market's average return. The best part is that these companies are so consistent in generating profitable growth from their businesses that they dish out a steady stream of growing dividends to shareholders. Let's find out more why three Motley Fool contributors believe these stocks are no-brainer buys for the next 20 years. Apple has massive cash resources to fund a growing dividend John Ballard (Apple): Investors shouldn't focus only on buying stocks with high yields, since companies that pay high yields are either struggling financially or lacking growth. A smart way to build up dividend income you'll need for retirement is focusing on companies that offer dividend growth. A company that has a long record of raising its dividend payment usually reflects growing demand for the company's products. Moreover, a multiyear record of dividend increases reflects management's confidence in the future of the company. Apple is a great example. Over the past 10 years, its annual dividend grew by 130%, or more than double its fiscal 2013 dividend payment. It has increased the dividend for 12 consecutive years, and because it only pays out 14% of its earnings, Apple can continue increasing the dividend even if earnings are down during an investment year or recession. While the dividend yield on Apple stock is below average at just 0.49% right now, its yield could increase over the next two decades. If Apple doubles its dividend in each decade through 2043, investors who buys shares today could potentially earn a dividend yield on their cost basis approaching 2%. If Apple also doubles its payout closer to 30% of its earnings, the yield could approach 4%. Apple has attractive long-term growth prospects. It should continue to grow through expanding its installed base of active devices, launching new products (e.g., Vision Pro in 2024), and continuing to expand its services business, which should be a great source of profitable growth to help fund future dividend increases. The iPhone, which makes up half of the company's annual revenue, has made Apple one of the most profitable companies in the world. Apple generated $99 billion in free cash flow on $383 billion of revenue over the past year. The resources it has will pave the way for more new products, more profitable growth, and growing dividends for years to come. A buy-on-the-dip dividend opportunity Jennifer Saibil (Starbucks): Starbucks doesn't have any competition as the leader in coffee shops, and it's opening new stores, innovating with beverages, and making other important changes to keep its top spot. The company hired a new CEO this year\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.015741, "explanation": "The actual 21-day forward return for IWM starting 2023-12-15 was -1.57%, which classifies as 'negative'.", "metadata": {"future_return": -0.015741, "horizon_days": 21, "hist_return": 0.127479, "annualized_vol": 0.216923, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240722_0739", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-07-22", "context_summary": "BNB-USD over past 60 days: cumulative return +0.5%, annualized vol 48.0%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=598.67, end=601.85, cumulative_return=+0.5%, annualized_volatility=48.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.24, 't10y3m_spread': -1.18, 'breakeven_10y': 2.32, 'hy_oas': 3.09, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 16.520000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.118013, "explanation": "The actual 21-day forward return for BNB-USD starting 2024-07-22 was -11.80%, which classifies as 'negative'.", "metadata": {"future_return": -0.118013, "horizon_days": 21, "hist_return": 0.005312, "annualized_vol": 0.480385, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240130_0741", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-01-30", "context_summary": "XLB over past 60 days: cumulative return +9.7%, annualized vol 13.9%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=36.23, end=39.75, cumulative_return=+9.7%, annualized_volatility=13.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.21, 't10y3m_spread': -1.34, 'breakeven_10y': 2.3, 'hy_oas': 3.41, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.600000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.051141, "explanation": "The actual 21-day forward return for XLB starting 2024-01-30 was +5.11%, which classifies as 'positive'.", "metadata": {"future_return": 0.051141, "horizon_days": 21, "hist_return": 0.097233, "annualized_vol": 0.139114, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240213_0743", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2024-02-13", "context_summary": "MORT over past 60 days: cumulative return +1.9%, annualized vol 23.5%. Market regime: sideways.", "question": "Asset: MORT\nHistorical prices (past 60 trading days): start=8.32, end=8.47, cumulative_return=+1.9%, annualized_volatility=23.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.29, 't10y3m_spread': -1.26, 'breakeven_10y': 2.24, 'hy_oas': 3.35, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 13.93000030517578}\nMarket regime: sideways\n\nPredict whether the return of MORT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.043233, "explanation": "The actual 21-day forward return for MORT starting 2024-02-13 was +4.32%, which classifies as 'positive'.", "metadata": {"future_return": 0.043233, "horizon_days": 21, "hist_return": 0.018812, "annualized_vol": 0.235079, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240718_0744", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-07-18", "context_summary": "QUAL over past 60 days: cumulative return +11.4%, annualized vol 9.9%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=152.77, end=170.11, cumulative_return=+11.4%, annualized_volatility=9.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.26, 't10y3m_spread': -1.27, 'breakeven_10y': 2.26, 'hy_oas': 3.09, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 14.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.014878, "explanation": "The actual 21-day forward return for QUAL starting 2024-07-18 was +1.49%, which classifies as 'positive'.", "metadata": {"future_return": 0.014878, "horizon_days": 21, "hist_return": 0.113515, "annualized_vol": 0.099298, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20231115_0746", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-11-15", "context_summary": "ICSH over past 60 days: cumulative return +1.0%, annualized vol 0.5%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=44.36, end=44.79, cumulative_return=+1.0%, annualized_volatility=0.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.36, 't10y3m_spread': -1.08, 'breakeven_10y': 2.28, 'hy_oas': 3.92, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 14.15999984741211}\nMarket regime: sideways\n\nPredict whether the return of ICSH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.004497, "explanation": "The actual 21-day forward return for ICSH starting 2023-11-15 was +0.45%, which classifies as 'flat'.", "metadata": {"future_return": 0.004497, "horizon_days": 21, "hist_return": 0.009792, "annualized_vol": 0.004542, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230725_0748", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-07-25", "context_summary": "DOT-USD over past 60 days: cumulative return -0.6%, annualized vol 44.6%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=5.25, end=5.22, cumulative_return=-0.6%, annualized_volatility=44.6%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.65, 'breakeven_10y': 2.38, 'hy_oas': 3.82, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 13.90999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-24] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.070318, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-07-25 was -7.03%, which classifies as 'negative'.", "metadata": {"future_return": -0.070318, "horizon_days": 21, "hist_return": -0.006268, "annualized_vol": 0.446476, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230418_0750", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SLV"], "decision_date": "2023-04-18", "context_summary": "SLV over past 60 days: cumulative return +5.8%, annualized vol 26.2%. Market regime: sideways.", "question": "Asset: SLV\nHistorical prices (past 60 trading days): start=21.76, end=23.02, cumulative_return=+5.8%, annualized_volatility=26.2%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.58, 't10y3m_spread': -1.61, 'breakeven_10y': 2.32, 'hy_oas': 4.41, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 16.950000762939453}\nMarket regime: sideways\n\nPredict whether the return of SLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.057451, "explanation": "The actual 21-day forward return for SLV starting 2023-04-18 was -5.75%, which classifies as 'negative'.", "metadata": {"future_return": -0.057451, "horizon_days": 21, "hist_return": 0.057904, "annualized_vol": 0.262203, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231207_0752", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-12-07", "context_summary": "XLU over past 60 days: cumulative return -0.1%, annualized vol 19.3%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=29.56, end=29.51, cumulative_return=-0.1%, annualized_volatility=19.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.48, 't10y3m_spread': -1.33, 'breakeven_10y': 2.14, 'hy_oas': 3.79, 'ig_oas': 1.12, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 12.970000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-06] [\"ROKU Collaborates With Tennis Channel to Launch T2 in the US Roku Inc. ROKU has announced a collaboration with Tennis Channel to launch T2, the sports network's second channel, on The Roku Channel in the United States. T2 is set to provide free and year-round access to live coverage of top tennis players and signature events for the vast audience of The Roku Channel, reaching an estimated 100 million people. For convenient access, viewers can easily navigate T2 through the Sports Experience on Roku's Home Screen. This feature simplifies the discovery and access of live, upcoming and on-demand sports content, enhancing engagement and awareness for Roku's content partners while providing a personalized viewing experience. T2's yearly live and encore calendar aligns with most tournaments covered by Tennis Channel, showcasing different matches and players. This unique approach allows viewers with access to both channels to choose between simultaneous competitions from prestigious events, such as the BNP Paribas Open, Roland Garros, Miami Open, Monte-Carlo Masters, Italian Open, Canadian Open, Davis Cup and the Billie Jean King Cup. Shares of this Zacks Rank #3 (Hold) company have gained 158.5% year to date compared with the Zacks Consumer Discretionary sector\\u2019s rise of 12.4% due to its extensive collection of content. You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. Roku, Inc. Price and Consensus Roku, Inc. price-consensus-chart | Roku, Inc. Quote ROKU\\u2019s Recent Efforts to Boost Streaming Hours The company recently unveiled two fresh additions to the Roku Home Screen, such as All Things Food and All Things Home. These new destinations bring together top-notch food, home and lifestyle content from various sources on the platform, creating seamless and engaging discovery experiences. These new features are expected to boost streaming hours as well as platform revenues in the upcoming quarters. The Zacks Consensus Estimate for ROKU\\u2019s 2023 streaming hours is pegged at 105.33 billion, indicating a year-over-year increase of 340.7%. The consensus estimate for 2023 platform revenues is pegged at $2.9 billion, indicating a year-over-year increase of 7.38%. Designed for user convenience, these hubs offer straightforward navigation and personalized recommendations, simplifying the exploration and viewing of genre entertainment directly from the home screen. Both All Things Food and All Things Home will showcase a diverse array of streaming options within their respective categories, encompassing free and subscription-based services, live and linear TV, Premium Subscriptions, Roku Originals and more. These features were added due to a recent survey commissioned by Roku. This recent survey revealed that 64% of streamers rely on genre-based searches when looking for new content, emphasizing the significance of genre preferences in content discovery. According to the survey, nearly 73% of streamers feel that the\n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.025309, "explanation": "The actual 21-day forward return for XLU starting 2023-12-07 was +2.53%, which classifies as 'positive'.", "metadata": {"future_return": 0.025309, "horizon_days": 21, "hist_return": -0.001463, "annualized_vol": 0.192854, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230530_0754", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-05-30", "context_summary": "QQQ over past 60 days: cumulative return +16.4%, annualized vol 18.3%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=294.00, end=342.33, cumulative_return=+16.4%, annualized_volatility=18.3%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.74, 't10y3m_spread': -1.54, 'breakeven_10y': 2.23, 'hy_oas': 4.54, 'ig_oas': 1.41, 'ted_spread': 0.09, 'mortgage_30y': 6.57, 'vix': 17.950000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-26] [\"Alphabet CEO Sundar Pichai Commits to \\\"AI Pact\\\": What Does This Really Mean? The world of artificial intelligence (AI) is moving at a breakneck speed, and top corporate and political leaders are trying to safely guide its evolution. Alphabet (NASDAQ: GOOG) (NASDAQ: GOOGL) CEO Sundar Pichai met with European Commissioner for the internal market Thierry Breton on Wednesday to discuss the progression of AI and map out possible actions to help ensure the emerging technology doesn't get out of hand. In the meeting, Pichai promised that his company would join an \\\"AI pact\\\" and collaborate with other players in the artificial intelligence space on a volunteer basis to shape and abide by guidelines for tech development. But while there's seemingly a lot to like about the prospect of guardrails being put on AI, it's not clear that voluntary pacts or even strict laws will be able to address many of the potential problems that could arise. Could an AI pact help stave off potential disasters? While detailed specifics of what rules and guidelines members of an AI pact would be adhering to haven't been made available, Pichai's discussion with other members of the European Commission suggest that privacy standards and fighting misinformation could be key focuses. The rapid progression for artificial intelligence tech over the last year is unprecedented, and continued advances could be unwieldy. Because legislative bodies can be slow to act and laws vary between territories, it could be important for technology leaders to attempt to establish some kind of presiding framework for artificial intelligence initiatives. Taking a proactive approach to the problems and questions raised by incredible leaps forward for artificial intelligence could help minimize the possibility of disastrous outcomes stemming from the tech. The AI pact mentioned by Pichai at the meeting with Breton seems to be a step in this direction. But there's a risk that rules surrounding AI might not amount to much. For one, it's possible that voluntary AI guidelines and restrictions will be followed very loosely or only in the most nominal senses. It's also possible that those who don't abide by rules for the artificial intelligence project, whether self-imposed or through regulations, could actually gain significant competitive advantages. Controlling AI could be incredibly difficult The European Parliament is currently finalizing a new set of rules and restrictions that will govern AI technologies. The EU AI Act isn't officially law yet, but it's seemingly headed in that direction and could be a landmark response that plays a big role in the tech's evolution in Europe. But it might not be enough, and it may have unintended consequences. Developing ways to work around restrictions could be incentivized by the proposed regulations, and the speed at which AI tech has been progressing will make it difficult for regulators to keep up. Additionally, there are already signs that influential player\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.040942, "explanation": "The actual 21-day forward return for QQQ starting 2023-05-30 was +4.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.040942, "horizon_days": 21, "hist_return": 0.164373, "annualized_vol": 0.182633, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230109_0756", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2023-01-09", "context_summary": "DBA over past 60 days: cumulative return -2.0%, annualized vol 8.9%. Market regime: sideways.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=17.70, end=17.34, cumulative_return=-2.0%, annualized_volatility=8.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.69, 't10y3m_spread': -1.12, 'breakeven_10y': 2.21, 'hy_oas': 4.47, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.48, 'vix': 21.1299991607666}\nMarket regime: sideways\n\nPredict whether the return of DBA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.021905, "explanation": "The actual 21-day forward return for DBA starting 2023-01-09 was +2.19%, which classifies as 'positive'.", "metadata": {"future_return": 0.021905, "horizon_days": 21, "hist_return": -0.020165, "annualized_vol": 0.088697, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230609_0758", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-06-09", "context_summary": "FXI over past 60 days: cumulative return +2.2%, annualized vol 28.2%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=25.39, end=25.96, cumulative_return=+2.2%, annualized_volatility=28.2%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.79, 't10y3m_spread': -1.65, 'breakeven_10y': 2.2, 'hy_oas': 4.39, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 13.649999618530272}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-08] [\"US STOCKS-Wall Street ends up amid record low volatility ahead of eventful week By Shristi Achar A and David Carnevali June 8 (Reuters) - U.S. stocks closed higher on Thursday regaining some of their momentum thanks to a rebound by technology stocks, while volatility dropped to record lows ahead of an eventful economic and policy calendar next week. The CBOE Volatility index .VIX, also known as Wall Street's fear gauge, dropped to a fresh post-pandemic record low. \\\"What you are really seeing in the vol market is an unwillingness to engage,\\\" said David Bianco, Americas chief investment officer for asset manager DWS Group. \\\"You've just got paralysis in investors.\\\" Investors were sitting on the sidelines ahead of inflation data and a Federal Reserve policy meeting next week. Traders have priced in a 73% chance of the U.S. central bank holding interest rates at the current 5%-5.25% range during its monetary policy meeting on June 13-14, according to CMEGroup's Fedwatch tool. However, they see a 50% chance of a rate hike in July. The two-year Treasury yield US2YT=RR, which tends to move in step with short-term rate expectations, slipped from one-week highs to 4.51% after a sharp jump in weekly jobless claims signaled a softening labor market. The U.S. Labor Department is due to release inflation data on June 13, the first day of the Fed meeting. The numbers are expected to show consumer prices cooled slightly in May but core prices remained sticky. Meanwhile, a rebound by technology and megacap stocks helped major indexes regain their footing amid thin volumes. Heavyweight Amazon.com Inc AMZN.O gained 2.49% as Wells Fargo initiated coverage on the company with an \\\"overweight\\\" rating, while Nvidia Corp NVDA.O, Apple Inc AAPL.O and Tesla Inc TSLA.O rose between 1.55% and 4.58%. GameStop Corp GME.N tanked 17.89% as billionaire investor Ryan Cohen took over as executive chairman after the video-game retailer ousted its CEO and posted a bigger-than-expected quarterly loss. The Dow Jones Industrial Average .DJI rose 168.59 points, or 0.5%, to 33,833.61, the S&P 500 .SPX gained 26.41 points, or 0.62%, to 4,293.93 and the Nasdaq Composite .IXIC added 133.63 points, or 1.02%, to 13,238.52. Among the 11 major S&P sectors, consumer discretionary .SPLRCD led the charge, while real estate .SPLRCR and energy .SPNY indexes slipped, with the latter being hit by a drop in oil prices. Adobe ADBE.O jumped 4.95% after Piper Sandler raised its prices target on the stock to $500. The Photoshop software maker said it was offering its AI tool \\\"Firefly\\\" to large businesses. Lucid Group LCID.O tumbled 1.88% after the U.S. luxury electric-vehicle maker's head of China operations, Zhu Jiang, said the company was preparing to enter the world's largest auto market. Advancing issues outnumbered declining ones on the NYSE by a 1.16-to-1 ratio; on Nasdaq, a 1.02-to-1 ratio favored advancers. The S&P 500 posted 12 new 52-week highs and two new lows; the Nasdaq Composite reco\n\nPredict whether the return of FXI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.023724, "explanation": "The actual 21-day forward return for FXI starting 2023-06-09 was -2.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.023724, "horizon_days": 21, "hist_return": 0.022457, "annualized_vol": 0.281768, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240906_0760", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2024-09-06", "context_summary": "XLP over past 60 days: cumulative return +8.0%, annualized vol 10.0%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=73.56, end=79.47, cumulative_return=+8.0%, annualized_volatility=10.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.02, 't10y3m_spread': -1.42, 'breakeven_10y': 2.03, 'hy_oas': 3.29, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 19.89999961853028}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of XLP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.022911, "explanation": "The actual 21-day forward return for XLP starting 2024-09-06 was -2.29%, which classifies as 'negative'.", "metadata": {"future_return": -0.022911, "horizon_days": 21, "hist_return": 0.080297, "annualized_vol": 0.099811, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230412_0761", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-04-12", "context_summary": "MATIC-USD over past 60 days: cumulative return -11.0%, annualized vol 62.6%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=1.25, end=1.11, cumulative_return=-11.0%, annualized_volatility=62.6%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.6, 't10y3m_spread': -1.61, 'breakeven_10y': 2.29, 'hy_oas': 4.63, 'ig_oas': 1.44, 'ted_spread': 0.09, 'mortgage_30y': 6.28, 'vix': 19.100000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-11] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.093699, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-04-12 was -9.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.093699, "horizon_days": 21, "hist_return": -0.109895, "annualized_vol": 0.625535, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230831_0763", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-08-31", "context_summary": "BTC-USD over past 60 days: cumulative return -10.9%, annualized vol 26.5%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=30620.77, end=27297.27, cumulative_return=-10.9%, annualized_volatility=26.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.78, 't10y3m_spread': -1.44, 'breakeven_10y': 2.26, 'hy_oas': 3.8, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.23, 'vix': 13.880000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-30] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.024532, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-08-31 was +2.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.024532, "horizon_days": 21, "hist_return": -0.108538, "annualized_vol": 0.265188, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231212_0765", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2023-12-12", "context_summary": "WEAT over past 60 days: cumulative return -1.4%, annualized vol 25.9%. Market regime: sideways.", "question": "Asset: WEAT\nHistorical prices (past 60 trading days): start=29.35, end=28.95, cumulative_return=-1.4%, annualized_volatility=25.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.48, 't10y3m_spread': -1.24, 'breakeven_10y': 2.19, 'hy_oas': 3.79, 'ig_oas': 1.1, 'ted_spread': 0.09, 'mortgage_30y': 7.03, 'vix': 12.630000114440918}\nMarket regime: sideways\n\nPredict whether the return of WEAT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.021922, "explanation": "The actual 21-day forward return for WEAT starting 2023-12-12 was -2.19%, which classifies as 'negative'.", "metadata": {"future_return": -0.021922, "horizon_days": 21, "hist_return": -0.013629, "annualized_vol": 0.25919, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230222_0767", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-02-22", "context_summary": "DOT-USD over past 60 days: cumulative return +62.8%, annualized vol 63.5%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.45, end=7.25, cumulative_return=+62.8%, annualized_volatility=63.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.72, 't10y3m_spread': -0.91, 'breakeven_10y': 2.42, 'hy_oas': 4.49, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 22.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-21] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.180595, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-02-22 was -18.06%, which classifies as 'negative'.", "metadata": {"future_return": -0.180595, "horizon_days": 21, "hist_return": 0.627569, "annualized_vol": 0.634838, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241107_0769", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-11-07", "context_summary": "DOT-USD over past 60 days: cumulative return -1.1%, annualized vol 44.8%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.16, end=4.12, cumulative_return=-1.1%, annualized_volatility=44.8%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.15, 't10y3m_spread': -0.22, 'breakeven_10y': 2.38, 'hy_oas': 2.74, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 16.270000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 1.070831, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-11-07 was +107.08%, which classifies as 'positive'.", "metadata": {"future_return": 1.070831, "horizon_days": 21, "hist_return": -0.011147, "annualized_vol": 0.448133, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231211_0771", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2023-12-11", "context_summary": "DBB over past 60 days: cumulative return -1.5%, annualized vol 14.8%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=15.98, end=15.74, cumulative_return=-1.5%, annualized_volatility=14.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.48, 't10y3m_spread': -1.21, 'breakeven_10y': 2.21, 'hy_oas': 3.75, 'ig_oas': 1.1, 'ted_spread': 0.09, 'mortgage_30y': 7.03, 'vix': 12.350000381469728}\nMarket regime: sideways\n\nPredict whether the return of DBB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.030644, "explanation": "The actual 21-day forward return for DBB starting 2023-12-11 was +3.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.030644, "horizon_days": 21, "hist_return": -0.015143, "annualized_vol": 0.148016, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241213_0773", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-12-13", "context_summary": "EEM over past 60 days: cumulative return +0.5%, annualized vol 18.7%. Market regime: bull.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=42.04, end=42.24, cumulative_return=+0.5%, annualized_volatility=18.7%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.14, 't10y3m_spread': -0.03, 'breakeven_10y': 2.32, 'hy_oas': 2.66, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 13.920000076293944}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 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us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of EEM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.057484, "explanation": "The actual 21-day forward return for EEM starting 2024-12-13 was -5.75%, which classifies as 'negative'.", "metadata": {"future_return": -0.057484, "horizon_days": 21, "hist_return": 0.004797, "annualized_vol": 0.186506, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230307_0775", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-03-07", "context_summary": "XLI over past 60 days: cumulative return +4.7%, annualized vol 16.3%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=94.12, end=98.55, cumulative_return=+4.7%, annualized_volatility=16.3%\nMacro context: {'fed_funds_rate': 4.57, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.91, 't10y3m_spread': -0.95, 'breakeven_10y': 2.49, 'hy_oas': 3.97, 'ig_oas': 1.24, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 18.61000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-06] [\"After Hours Most Active for Mar 6, 2023 : VALE, BAC, AMZN, QQQ, MRK, AAPL, IQ, MSFT, PFE, KO, ALIT, WDC The NASDAQ 100 After Hours Indicator is down -10.89 to 12,291.59. The total After hours volume is currently 79,432,799 shares traded. The following are the most active stocks for the after hours session: VALE S.A. (VALE) is -0.01 at $16.68, with 6,521,728 shares traded. VALE's current last sale is 87.79% of the target price of $19. Bank of America Corporation (BAC) is unchanged at $34.09, with 3,492,820 shares traded. BAC's current last sale is 89.71% of the target price of $38. Amazon.com, Inc. (AMZN) is -0.09 at $93.66, with 3,173,777 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Jun 2023. The consensus EPS forecast is $0.28. As reported by Zacks, the current mean recommendation for AMZN is in the \\\"buy range\\\". Invesco QQQ Trust, Series 1 (QQQ) is +1.21 at $301.23, with 3,064,552 shares traded. This represents a 18.47% increase from its 52 Week Low. Merck & Company, Inc. (MRK) is -0.09 at $111.01, with 2,632,264 shares traded. As reported by Zacks, the current mean recommendation for MRK is in the \\\"buy range\\\". Apple Inc. (AAPL) is -0.15 at $153.68, with 2,211,853 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2023. The consensus EPS forecast is $1.43. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". iQIYI, Inc. (IQ) is +0.0604 at $7.65, with 1,819,482 shares traded. As reported by Zacks, the current mean recommendation for IQ is in the \\\"buy range\\\". Microsoft Corporation (MSFT) is -0.02 at $256.85, with 1,791,083 shares traded. As reported by Zacks, the current mean recommendation for MSFT is in the \\\"buy range\\\". Pfizer, Inc. (PFE) is -0.0101 at $41.10, with 1,556,995 shares traded. PFE's current last sale is 82.2% of the target price of $50. Coca-Cola Company (The) (KO) is -0.01 at $60.35, with 1,519,857 shares traded. Over the last four weeks they have had 6 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2023. The consensus EPS forecast is $0.64. As reported by Zacks, the current mean recommendation for KO is in the \\\"buy range\\\". Alight, Inc. (ALIT) is unchanged at $9.81, with 1,492,772 shares traded. As reported by Zacks, the current mean recommendation for ALIT is in the \\\"buy range\\\". Western Digital Corporation (WDC) is unchanged at $37.78, with 1,388,099 shares traded. WDC's current last sale is 75.56% of the target price of $50. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-S&P 500 ends slightly higher ahead of Powell testimony, upcoming data By Sin\\u00e9ad Carew and Bansari Mayur Kamdar March 6 (Reuters) - The S&P 500 made little progress on Monday, closing slightly lower than its session high as U.S. \n\nPredict whether the return of XLI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.038656, "explanation": "The actual 21-day forward return for XLI starting 2023-03-07 was -3.87%, which classifies as 'negative'.", "metadata": {"future_return": -0.038656, "horizon_days": 21, "hist_return": 0.047069, "annualized_vol": 0.163409, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230201_0777", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-02-01", "context_summary": "EFA over past 60 days: cumulative return +23.0%, annualized vol 16.4%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=52.82, end=64.96, cumulative_return=+23.0%, annualized_volatility=16.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.69, 't10y3m_spread': -1.18, 'breakeven_10y': 2.24, 'hy_oas': 4.3, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 6.13, 'vix': 19.39999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-31] [\"Apple (AAPL) to Report Q1 Earnings: What's in the Offing? Apple AAPL is set to report its first-quarter fiscal 2023 results on Feb 2. Apple expects year-over-year revenue growth to decelerate in the fiscal first quarter compared with the fiscal fourth quarter (the September-end quarter) due to an unfavorable year-over-year impact from the forex of roughly 10%. The Zacks Consensus Estimate for revenues is pegged at $121.21 billion, indicating a decline of 2.21% from the year-ago quarter\\u2019s reported figure. The consensus mark for earnings is pegged at $1.93 per share, unchanged over the past 30 days and indicating an 8.1% decrease from the figure reported in the year-ago quarter. Apple Inc. Price and EPS Surprise Apple Inc. price-eps-surprise | Apple Inc. Quote Apple\\u2019s earnings beat the Zacks Consensus Estimate in all the trailing four quarters, the earnings surprise being 6.26% on average. Let\\u2019s see how things have shaped up for the upcoming announcement. iPhone Revenues to Suffer From China Disruptions Apple\\u2019s fortunes are heavily reliant on the iPhone, which is by far its biggest revenue contributor. The device accounted for 47% of net sales in the last reported quarter, wherein sales increased 9.7% year over year to $42.63 billion. Our estimate for fiscal first-quarter iPhone net sales is pegged at $60.96 billion, down 14.9% year over year. Apple is expected to have suffered from disruptions at its China partner Foxconn\\u2019s factory in Zhengzhou, as well as shrinking demand. We expect Apple to have shipped roughly 70 million iPhones in the first quarter of fiscal 2023. Per the latest Canalys report on worldwide smartphone shipments, Apple expanded its market share to 25% in fourth-quarter 2022, beating Samsung\\u2019s 20%. Services Growth to Slow Down in Q1 Apple expects Services revenue growth to be negatively impacted by challenging macroeconomic conditions, unfavorable forex, and weakness in digital advertising and gaming. In the fiscal fourth quarter, Services revenues grew 5% from the year-ago quarter to $19.19 billion and accounted for 21.3% of sales. Nevertheless, an expanding paid subscriber base has been a key catalyst for the Services business, which is riding on the increasing popularity of the App Store. Apple has more than 900 million paid subscribers across its Services portfolio. App Store has been grabbing the attention of prominent developers from around the world, helping the company to offer exciting apps that drive traffic. Services like Apple TV+, Apple Arcade, Apple News+, Apple Card, Apple Fitness+ and Apple One bundle are expected to have contributed to overall growth. Apple TV+ has been gaining recognition due to award-winning shows despite strong competition from Netflix NFLX, as well as services from Disney DIS and Amazon AMZN. Per a report by JustWatch, Amazon prime video is the leader in the streaming market in the United States with a 21% market share, trailed by Netflix at a 20% market share \n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.018147, "explanation": "The actual 21-day forward return for EFA starting 2023-02-01 was -1.81%, which classifies as 'negative'.", "metadata": {"future_return": -0.018147, "horizon_days": 21, "hist_return": 0.229873, "annualized_vol": 0.163752, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230620_0779", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-06-20", "context_summary": "IWM over past 60 days: cumulative return +9.5%, annualized vol 18.9%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=164.27, end=179.90, cumulative_return=+9.5%, annualized_volatility=18.9%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.57, 'breakeven_10y': 2.22, 'hy_oas': 4.15, 'ig_oas': 1.35, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.539999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-16] [\"3 Stocks to Buy for Long-Term, Life-Changing Returns InvestorPlace - Stock Market News, Stock Advice & Trading Tips Investors are always on the hunt for long-term wealth stocks. You know, the kind that you can buy and hold for years (or decades) and generate market-beating returns. We\\u2019re all after that \\u2014 that\\u2019s why we read articles like this one. When investing for the future, readers have to look under the hood and find high-quality businesses. At the same time, it can be hard when looking for long-term investment stocks. That\\u2019s because so many of the best stocks have already generated the life-changing returns that investors are currently looking for. A stock like Apple (NASDAQ:AAPL) is an amazing business. But with a near-$3 trillion market valuation, there is a concern that its bigger growth days are behind it. Or take Johnson & Johnson (NYSE:JNJ). I love the company, but with a $425 billion market cap and only modest growth, it\\u2019s hard to imagine it outperforming the S&P 500 year-in and year-out. So what are some long-term wealth stocks to buy now? Investing for the Future: The Trade Desk (TTD) Source: Tada Images / Shutterstock.com There is absolutely nothing wrong with the businesses above (Apple and J&J). Almost any investor could make a case for them. However, I am looking for stocks that can generate outsized market returns over the long haul from here, not stocks that have already created those returns. One such stock? The Trade Desk (NASDAQ:TTD): The Trade Desk is a digital advertising firm that utilizes a demand-side platform. This not only drives efficiency for the customer, but drives profit for the company. Further, The Trade Desk makes it easy for customers to leverage connected TVs, audio, video, mobile and other mediums for their advertising needs. Before the pandemic, after the pandemic and through the 2022 bear market, investors experienced a lot of volatility in TTD stock. However, the company remained incredibly stable. It\\u2019s able to operate around the world (China included) and continues to churn out steady growth. Consensus expectations call for more than 20% revenue growth this year and next year, to go alongside 17% earnings growth in 2023 and 20.5% growth in 2024. Long-Term Wealth Stocks: PayPal (PYPL) Source: Michael Vi / Shutterstock.com PayPal (NASDAQ:PYPL): This fintech company is a controversial pick when it comes to long-term wealth stocks. The biggest reason? Because the stock has fallen out of favor with the market and suffered a peak-to-trough decline in excess of 80%. The stock has only recently hit a 52-week low. While many large cap and high growth stocks have come back to life, that has not been the case with PayPal. To be frank, I\\u2019m not sure why that\\u2019s been the case. PayPal has a solid brand and has been one of the market\\u2019s favorite stocks over the years. From the time it was spun off in mid-2015 to its high in February 2020 (just before the Covid-19 selloff), \n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.053746, "explanation": "The actual 21-day forward return for IWM starting 2023-06-20 was +5.37%, which classifies as 'positive'.", "metadata": {"future_return": 0.053746, "horizon_days": 21, "hist_return": 0.095183, "annualized_vol": 0.189377, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240319_0781", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-03-19", "context_summary": "IVV over past 60 days: cumulative return +9.9%, annualized vol 11.4%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=456.71, end=502.08, cumulative_return=+9.9%, annualized_volatility=11.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.14, 'breakeven_10y': 2.31, 'hy_oas': 3.13, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.74, 'vix': 14.329999923706056}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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2024-01-31 0000104169 srt:MaximumMember us-gaap:FurnitureAndFixturesMember 2024-01-31 0000104169 us-gaap:FurnitureAndFixturesMember 2024-01-31 0000104169 us-gaap:FurnitureAndFixturesMember 2023-01-31 0000104169 us-gaap:TransportationEquipmentMember srt:MinimumMember 2024-01-31 0000104169 srt:MaximumMember us-gaap:TransportationEquipmentMember 2024-01-31 0000104169 us-gaap:TransportationEquipmentMember 2024-01-31 0000104169 us-gaap:TransportationEquipmentMember 2023-01-31 0000104169 us-gaap:ConstructionInProgressMember 2024-01-31 0000104169 us-gaap:ConstructionInProgressMember 2023-01-31 0000104169 wmt:WalmartUSMember 2022-01-31 0000104169 wmt:WalmartInternationalMember 2022-01-31 0000104169 wmt:SamsClubMember 2022-01-31 0000104169 wmt:WalmartUSMember 2022-02-01 2023-01-31 0000104169 wmt:WalmartInternationalMember 2022-02-01 2023-01-31 0000104169 wmt:SamsClubMember 2022-02-01 2023-01-31 0000104169 wmt:WalmartUSMember 2023-01-31 0000104169 wmt:WalmartInternationalMember 2023-01-31 0000104169 wmt:SamsClubMember 2023-01-31 0000104169 wmt:WalmartUSMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartInternationalMember 2023-02-01 2024-01-31 0000104169 wmt:SamsClubMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartUSMember 2024-01-31 0000104169 wmt:WalmartInternationalMember 2024-01-31 0000104169 wmt:SamsClubMember 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2023-02-01 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2022-02-01 2023-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of IVV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.031476, "explanation": "The actual 21-day forward return for IVV starting 2024-03-19 was -3.15%, which classifies as 'negative'.", "metadata": {"future_return": -0.031476, "horizon_days": 21, "hist_return": 0.099354, "annualized_vol": 0.113771, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230419_0784", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-04-19", "context_summary": "MATIC-USD over past 60 days: cumulative return -21.2%, annualized vol 54.8%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=1.49, end=1.17, cumulative_return=-21.2%, annualized_volatility=54.8%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.61, 't10y3m_spread': -1.62, 'breakeven_10y': 2.28, 'hy_oas': 4.37, 'ig_oas': 1.37, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 16.829999923706055}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-18] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.191786, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-04-19 was -19.18%, which classifies as 'negative'.", "metadata": {"future_return": -0.191786, "horizon_days": 21, "hist_return": -0.21182, "annualized_vol": 0.548381, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240924_0786", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2024-09-24", "context_summary": "CSHI over past 60 days: cumulative return +1.0%, annualized vol 1.9%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=45.46, end=45.92, cumulative_return=+1.0%, annualized_volatility=1.9%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.18, 't10y3m_spread': -0.97, 'breakeven_10y': 2.17, 'hy_oas': 3.15, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.09, 'vix': 15.890000343322754}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.004019, "explanation": "The actual 21-day forward return for CSHI starting 2024-09-24 was +0.40%, which classifies as 'flat'.", "metadata": {"future_return": 0.004019, "horizon_days": 21, "hist_return": 0.010079, "annualized_vol": 0.018894, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240123_0788", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-01-23", "context_summary": "IVV over past 60 days: cumulative return +16.3%, annualized vol 11.3%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=405.89, end=471.85, cumulative_return=+16.3%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.26, 't10y3m_spread': -1.35, 'breakeven_10y': 2.31, 'hy_oas': 3.49, 'ig_oas': 1.01, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 13.1899995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nPredict whether the return of IVV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.046815, "explanation": "The actual 21-day forward return for IVV starting 2024-01-23 was +4.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.046815, "horizon_days": 21, "hist_return": 0.162524, "annualized_vol": 0.113311, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230406_0790", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-04-06", "context_summary": "BTC-USD over past 60 days: cumulative return +22.7%, annualized vol 49.9%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=22955.67, end=28177.98, cumulative_return=+22.7%, annualized_volatility=49.9%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.49, 't10y3m_spread': -1.56, 'breakeven_10y': 2.23, 'hy_oas': 4.84, 'ig_oas': 1.45, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 19.07999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-05] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.050978, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-04-06 was +5.10%, which classifies as 'positive'.", "metadata": {"future_return": 0.050978, "horizon_days": 21, "hist_return": 0.227496, "annualized_vol": 0.49877, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240621_0792", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-06-21", "context_summary": "BNB-USD over past 60 days: cumulative return -3.0%, annualized vol 40.5%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=605.58, end=587.11, cumulative_return=-3.0%, annualized_volatility=40.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.45, 't10y3m_spread': -1.25, 'breakeven_10y': 2.25, 'hy_oas': 3.23, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 13.279999732971191}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.089014, "explanation": "The actual 21-day forward return for BNB-USD starting 2024-06-21 was -8.90%, which classifies as 'negative'.", "metadata": {"future_return": -0.089014, "horizon_days": 21, "hist_return": -0.030497, "annualized_vol": 0.405207, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240530_0794", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-05-30", "context_summary": "ETH-USD over past 60 days: cumulative return +3.2%, annualized vol 58.2%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3647.86, end=3763.20, cumulative_return=+3.2%, annualized_volatility=58.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.35, 't10y3m_spread': -0.85, 'breakeven_10y': 2.36, 'hy_oas': 3.15, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 14.279999732971191}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.062923, "explanation": "The actual 21-day forward return for ETH-USD starting 2024-05-30 was -6.29%, which classifies as 'negative'.", "metadata": {"future_return": -0.062923, "horizon_days": 21, "hist_return": 0.031619, "annualized_vol": 0.582244, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230814_0796", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2023-08-14", "context_summary": "VLUE over past 60 days: cumulative return +7.6%, annualized vol 12.3%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=82.60, end=88.85, cumulative_return=+7.6%, annualized_volatility=12.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.73, 't10y3m_spread': -1.38, 'breakeven_10y': 2.36, 'hy_oas': 3.83, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 14.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-11] [\"US STOCKS-Wall St slides as growth stocks fall after producer prices data By Bansari Mayur Kamdar and Johann M Cherian Aug 11 (Reuters) - Wall Street fell on Friday as rate-sensitive technology and growth stocks dropped after hotter-than-expected producer prices data for July sent U.S. bond yields higher. U.S. producer price index (PPI) climbed 0.8% in the 12 months leading to July, up from a 0.2% rise in the previous month, as service costs increased. Economists polled by Refinitiv had expected a 0.7% gain. \\\"The PPI data shows that inflation is still a concern,\\\" said Adam Sarhan, chief executive of 50 Park Investments. Though traders broadly expect the Federal Reserve to not tighten credit conditions for the remainder of the year, bets for no rate hike in September slipped to 88.5% from 90% before the data landed.IRPR \\\"The market needs to pause and digest the inflation data which is coming in mixed, where it's not clear what the Fed's going do next. Even if the Fed pauses one time, the question becomes what will it be doing for the rest of the year,\\\" Sarhan added. Yield on the 2-year treasury note US2YT=RR, that moves in line with near-term interest rate expectations, climbed to 4.9% after the data, pressuring rate-sensitive megacap growth names. US/ Tesla TSLA.O, Nvidia NVDA.O and Apple AAPL.O lost between 0.4% and 1.8%. Benchmark U.S. indexes finished marginally higher in the previous session as worries about the U.S. economy's longer-term prospects and concerns over further growth in stocks eclipsed milder-than-feared consumer prices data that had initially sent shares soaring. At 09:48 a.m. ET, the Dow Jones Industrial Average .DJI was down 34.32 points, or 0.10%, at 35,141.83, the S&P 500 .SPX was down 19.21 points, or 0.43%, at 4,449.62, and the Nasdaq Composite .IXIC was down 101.36 points, or 0.74%, at 13,636.63. The tech-heavy Nasdaq .IXIC and the S&P 500 .SPX were on track to end their second week lower due to a drop in megacap growth and technology stocks that have led outsized gains this year. Ten of the 11 major S&P 500 sectors declined on Friday, with tech stocks .SPLRCT leading losses, down 0.8%. U.S.-listed shares of Chinese companies Alibaba BABA.N and JD.com JD.O fell 3.0% and 5.4%, respectively, as Beijing's latest stimulus measures disappointed investors, while fresh data showed that the country's post-pandemic recovery was losing steam. Declining issues outnumbered advancers by a 1.85-to-1 ratio on the NYSE and a 1.75-to-1 ratio on the Nasdaq. The S&P index recorded one new 52-week high and three new lows, while the Nasdaq recorded 18 new highs and 82 new lows. Growth stocks slide as bond yields weigh since late July https://tmsnrt.rs/3YC8Qag (Reporting by Bansari Mayur Kamdar and Johann M Cherian in Bengaluru; Additional reporting by Shashwat Chauhan; Editing by Vinay Dwivedi) ((BansariMayur.Kamdar@thomsonreuters.com)) The views and opinions expressed herein are the views and opinions of the author and do not necessar\n\nPredict whether the return of VLUE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.016139, "explanation": "The actual 21-day forward return for VLUE starting 2023-08-14 was -1.61%, which classifies as 'negative'.", "metadata": {"future_return": -0.016139, "horizon_days": 21, "hist_return": 0.075581, "annualized_vol": 0.122968, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230824_0798", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-08-24", "context_summary": "CSHI over past 60 days: cumulative return +0.9%, annualized vol 0.9%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=42.80, end=43.18, cumulative_return=+0.9%, annualized_volatility=0.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.76, 't10y3m_spread': -1.38, 'breakeven_10y': 2.35, 'hy_oas': 3.92, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 15.979999542236328}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003587, "explanation": "The actual 21-day forward return for CSHI starting 2023-08-24 was +0.36%, which classifies as 'flat'.", "metadata": {"future_return": 0.003587, "horizon_days": 21, "hist_return": 0.008851, "annualized_vol": 0.009318, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230324_0800", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-03-24", "context_summary": "XLK over past 60 days: cumulative return +18.2%, annualized vol 22.9%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=60.31, end=71.30, cumulative_return=+18.2%, annualized_volatility=22.9%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.38, 't10y3m_spread': -1.35, 'breakeven_10y': 2.19, 'hy_oas': 5.1, 'ig_oas': 1.52, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 22.61000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-23] [\"US STOCKS-Wall Street rallies on hopes of Fed policy pause For a Reuters live blog on U.S., UK and European stock markets, click LIVE/ or type LIVE/ in a news window Jobless claims remain low, new home sales rise Block Inc slides after Hindenburg discloses short position US SEC threatens to sue Coinbase, shares drop Regional banks head lower Indexes up: Dow 0.44%, S&P 0.66%, Nasdaq 1.30% New throughout, adds NEW YORK dateline, changes byline By Stephen Culp NEW YORK, March 23 (Reuters) - Wall Street advanced on Thursday as market participants looked past remarks by U.S. Federal Reserve Chairman Jerome Powell on Wednesday and weighed the possibility that the central bank will pause its restrictive interest rate hikes in the near future. All three indexes marked the three-year anniversary of the nadir of the COVID-19 crash by heading higher, with megacap growth stocks, led by Microsoft MSFT.O and Apple Inc AAPL.O, providing the most upside muscle and putting the tech-heavy Nasdaq out front. \\\"Today the market is bouncing back on what was a dovish Fed hike yesterday,\\\" said Ross Mayfield, investment strategy analyst at Baird in Louisville, Kentucky. \\\"Powell did a good job sticking to the party line on inflation and continued to jawbone hawkish even though the hike leaned dovish.\\\" \\\"It\\u2019s not too crazy for markets to see that pivot in the near future,\\\" Mayfield added. The risk-on session reversed Wednesday's late-session sell-off after the Fed's rate hike, Powell's subsequent Q&A session and Treasury Secretary Janet Yellen's testimony before congress in which she ruled out blanket protection for all deposits. In view of recent turmoil in the financial sector, which began with the failures of SVB Financial Group SIVB.O and Signature Bank SBNY.O, worries that the Fed was overtightening and pushing the economy perilously close to recession, Powell's reiterance of the Fed's determination to cool inflation sparked a late session flight to safety. Jitters among regional banks persist, with the KBW Regional Bank index .KRX sliding 2.3%. Comments from the Bank of England that inflation will probably quickly fade also helped fuel hopes of light at the end of the central bank tightening tunnel. The BoE's commentary \\\"paints a picture of a global central banking system that's ready to slow the pace of their hiking,\\\" Mayfield said. But economic data released on Thursday showed jobless claims inching lower and new home sales posting a surprise gain, providing fresh evidence that the economy is yet to show the kind of softening that would lend itself to cooling inflation. The Dow Jones Industrial Average .DJI rose 142.01 points, or 0.44%, to 32,172.12, the S&P 500 .SPX gained 26.11 points, or 0.66%, to 3,963.08 and the Nasdaq Composite .IXIC added 151.81 points, or 1.3%, to 11,821.77. Among the 11 sectors of the S&P 500, communication services .SPLRCL and tech .SPLRCT led the percentage gainers. First Republic Bank FRC.Ndropped 8.6% in volatile trading i\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.007879, "explanation": "The actual 21-day forward return for XLK starting 2023-03-24 was +0.79%, which classifies as 'flat'.", "metadata": {"future_return": 0.007879, "horizon_days": 21, "hist_return": 0.182153, "annualized_vol": 0.22936, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240318_0801", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-03-18", "context_summary": "BNB-USD over past 60 days: cumulative return +82.3%, annualized vol 62.4%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=313.29, end=571.09, cumulative_return=+82.3%, annualized_volatility=62.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.41, 't10y3m_spread': -1.17, 'breakeven_10y': 2.32, 'hy_oas': 3.16, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.74, 'vix': 14.40999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.058324, "explanation": "The actual 21-day forward return for BNB-USD starting 2024-03-18 was +5.83%, which classifies as 'positive'.", "metadata": {"future_return": 0.058324, "horizon_days": 21, "hist_return": 0.822849, "annualized_vol": 0.624069, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240520_0802", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2024-05-20", "context_summary": "EWJ over past 60 days: cumulative return -0.4%, annualized vol 14.7%. Market regime: bull.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=64.50, end=64.23, cumulative_return=-0.4%, annualized_volatility=14.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.41, 't10y3m_spread': -1.04, 'breakeven_10y': 2.32, 'hy_oas': 3.09, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.02, 'vix': 11.989999771118164}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 2026-01-01 us-gaap:InvestmentAdviceMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember 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us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 us-gaap:InvestmentAdviceMember blk:FixedIncomeMember 2024-01-01 2024-03-31 0001364742 us-gaap:InvestmentAdviceMember blk:EquityNonETFIndexMember 2023-01-01 2023-03-31 0001364742 blk:PerformanceBasedRestrictedStockUnitsMember 2023-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:InvestmentsMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 blk:InstitutionalMember blk:RevenueByClientTypeMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 blk:TwoThousandTwentyFourRevolvingCreditFacilitiesMember 2024-03-31 0001364742 us-gaap:RealEstateFundsMember us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 2023-12-31 0001364742 blk:DeferredCashCompensationPlansMember 2024-03-31 0001364742 us-gaap:CorporateDebtSecuritiesMember 2024-03-31 0001364742 srt:EuropeMember 2024-03-31 0001364742 blk:PerformanceBasedStockOptionsMember 2024-01-01 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 srt:AsiaPacificMember 2023-01-01 2023-03-31 0001364742 us-gaap:RestrictedStockUnitsRSUMember 2023-01-01 2023-03-31 0001364742 us-gaap:HedgeFundsEquityMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.032482, "explanation": "The actual 21-day forward return for EWJ starting 2024-05-20 was -3.25%, which classifies as 'negative'.", "metadata": {"future_return": -0.032482, "horizon_days": 21, "hist_return": -0.004057, "annualized_vol": 0.147278, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230111_0804", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-01-11", "context_summary": "BNB-USD over past 60 days: cumulative return -1.8%, annualized vol 48.7%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=282.34, end=277.29, cumulative_return=-1.8%, annualized_volatility=48.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.63, 't10y3m_spread': -1.12, 'breakeven_10y': 2.24, 'hy_oas': 4.33, 'ig_oas': 1.35, 'ted_spread': 0.09, 'mortgage_30y': 6.48, 'vix': 20.57999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-10] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.113757, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-01-11 was +11.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.113757, "horizon_days": 21, "hist_return": -0.017892, "annualized_vol": 0.486878, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241113_0806", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-11-13", "context_summary": "BTC-USD over past 60 days: cumulative return +46.6%, annualized vol 40.5%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=60005.12, end=87955.81, cumulative_return=+46.6%, annualized_volatility=40.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.09, 't10y3m_spread': -0.2, 'breakeven_10y': 2.35, 'hy_oas': 2.66, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 14.710000038146973}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.090351, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-11-13 was +9.04%, which classifies as 'positive'.", "metadata": {"future_return": 0.090351, "horizon_days": 21, "hist_return": 0.465805, "annualized_vol": 0.40467, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240716_0808", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-07-16", "context_summary": "XLRE over past 60 days: cumulative return +13.5%, annualized vol 14.2%. Market regime: bull.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=33.38, end=37.89, cumulative_return=+13.5%, annualized_volatility=14.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.21, 't10y3m_spread': -1.2, 'breakeven_10y': 2.27, 'hy_oas': 3.13, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 13.119999885559082}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 2026-01-01 us-gaap:InvestmentAdviceMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember 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us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 us-gaap:InvestmentAdviceMember blk:FixedIncomeMember 2024-01-01 2024-03-31 0001364742 us-gaap:InvestmentAdviceMember blk:EquityNonETFIndexMember 2023-01-01 2023-03-31 0001364742 blk:PerformanceBasedRestrictedStockUnitsMember 2023-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:InvestmentsMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 blk:InstitutionalMember blk:RevenueByClientTypeMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 blk:TwoThousandTwentyFourRevolvingCreditFacilitiesMember 2024-03-31 0001364742 us-gaap:RealEstateFundsMember us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 2023-12-31 0001364742 blk:DeferredCashCompensationPlansMember 2024-03-31 0001364742 us-gaap:CorporateDebtSecuritiesMember 2024-03-31 0001364742 srt:EuropeMember 2024-03-31 0001364742 blk:PerformanceBasedStockOptionsMember 2024-01-01 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 srt:AsiaPacificMember 2023-01-01 2023-03-31 0001364742 us-gaap:RestrictedStockUnitsRSUMember 2023-01-01 2023-03-31 0001364742 us-gaap:HedgeFundsEquityMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.036014, "explanation": "The actual 21-day forward return for XLRE starting 2024-07-16 was +3.60%, which classifies as 'positive'.", "metadata": {"future_return": 0.036014, "horizon_days": 21, "hist_return": 0.135087, "annualized_vol": 0.142425, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20241104_0810", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-11-04", "context_summary": "SGOV over past 60 days: cumulative return +0.8%, annualized vol 0.3%. Market regime: sideways.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=94.01, end=94.77, cumulative_return=+0.8%, annualized_volatility=0.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.16, 't10y3m_spread': -0.24, 'breakeven_10y': 2.33, 'hy_oas': 2.83, 'ig_oas': 0.86, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 21.8799991607666}\nMarket regime: sideways\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002491, "explanation": "The actual 21-day forward return for SGOV starting 2024-11-04 was +0.25%, which classifies as 'flat'.", "metadata": {"future_return": 0.002491, "horizon_days": 21, "hist_return": 0.008042, "annualized_vol": 0.002871, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230524_0811", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-05-24", "context_summary": "BTC-USD over past 60 days: cumulative return -1.0%, annualized vol 30.2%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=27494.71, end=27225.73, cumulative_return=-1.0%, annualized_volatility=30.2%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.56, 't10y3m_spread': -1.64, 'breakeven_10y': 2.26, 'hy_oas': 4.6, 'ig_oas': 1.44, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 18.530000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-23] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.045952, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-05-24 was -4.60%, which classifies as 'negative'.", "metadata": {"future_return": -0.045952, "horizon_days": 21, "hist_return": -0.009783, "annualized_vol": 0.302462, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240807_0812", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2024-08-07", "context_summary": "ITB over past 60 days: cumulative return +4.0%, annualized vol 28.9%. Market regime: sideways.", "question": "Asset: ITB\nHistorical prices (past 60 trading days): start=106.23, end=110.53, cumulative_return=+4.0%, annualized_volatility=28.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.09, 't10y3m_spread': -1.44, 'breakeven_10y': 2.12, 'hy_oas': 3.67, 'ig_oas': 1.08, 'ted_spread': 0.09, 'mortgage_30y': 6.73, 'vix': 27.709999084472656}\nMarket regime: sideways\n\nPredict whether the return of ITB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.070705, "explanation": "The actual 21-day forward return for ITB starting 2024-08-07 was +7.07%, which classifies as 'positive'.", "metadata": {"future_return": 0.070705, "horizon_days": 21, "hist_return": 0.040463, "annualized_vol": 0.288883, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241018_0814", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2024-10-18", "context_summary": "VTI over past 60 days: cumulative return +8.3%, annualized vol 15.6%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=260.82, end=282.49, cumulative_return=+8.3%, annualized_volatility=15.6%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.13, 't10y3m_spread': -0.65, 'breakeven_10y': 2.3, 'hy_oas': 2.89, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.44, 'vix': 19.11000061035156}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.009, "explanation": "The actual 21-day forward return for VTI starting 2024-10-18 was +0.90%, which classifies as 'flat'.", "metadata": {"future_return": 0.009, "horizon_days": 21, "hist_return": 0.083106, "annualized_vol": 0.155749, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240209_0815", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-02-09", "context_summary": "XLB over past 60 days: cumulative return +8.1%, annualized vol 14.4%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=36.77, end=39.77, cumulative_return=+8.1%, annualized_volatility=14.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.31, 't10y3m_spread': -1.29, 'breakeven_10y': 2.24, 'hy_oas': 3.38, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 12.789999961853027}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent 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Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.086841, "explanation": "The actual 21-day forward return for XLB starting 2024-02-09 was +8.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.086841, "horizon_days": 21, "hist_return": 0.08142, "annualized_vol": 0.144297, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240705_0816", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-07-05", "context_summary": "XLV over past 60 days: cumulative return +0.4%, annualized vol 9.2%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=138.52, end=139.10, cumulative_return=+0.4%, annualized_volatility=9.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.35, 't10y3m_spread': -1.11, 'breakeven_10y': 2.27, 'hy_oas': 3.25, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.016758, "explanation": "The actual 21-day forward return for XLV starting 2024-07-05 was +1.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.016758, "horizon_days": 21, "hist_return": 0.004129, "annualized_vol": 0.091532, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240405_0817", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-04-05", "context_summary": "EFA over past 60 days: cumulative return +6.0%, annualized vol 10.4%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=69.55, end=73.69, cumulative_return=+6.0%, annualized_volatility=10.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.34, 't10y3m_spread': -1.1, 'breakeven_10y': 2.34, 'hy_oas': 3.24, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.82, 'vix': 16.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.006205, "explanation": "The actual 21-day forward return for EFA starting 2024-04-05 was +0.62%, which classifies as 'flat'.", "metadata": {"future_return": 0.006205, "horizon_days": 21, "hist_return": 0.059631, "annualized_vol": 0.104059, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240719_0819", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-07-19", "context_summary": "ACWI over past 60 days: cumulative return +7.9%, annualized vol 9.5%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=103.26, end=111.40, cumulative_return=+7.9%, annualized_volatility=9.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.26, 't10y3m_spread': -1.23, 'breakeven_10y': 2.31, 'hy_oas': 3.09, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 15.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 2026-01-01 us-gaap:InvestmentAdviceMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.021676, "explanation": "The actual 21-day forward return for ACWI starting 2024-07-19 was +2.17%, which classifies as 'positive'.", "metadata": {"future_return": 0.021676, "horizon_days": 21, "hist_return": 0.078845, "annualized_vol": 0.094741, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230105_0820", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-01-05", "context_summary": "XLY over past 60 days: cumulative return -6.6%, annualized vol 26.5%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=67.81, end=63.36, cumulative_return=-6.6%, annualized_volatility=26.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.67, 't10y3m_spread': -0.86, 'breakeven_10y': 2.22, 'hy_oas': 4.62, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 22.01000022888184}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-04] [\"Apple to sign Luxshare for iPhone production in China - FT Adds details from report, background on production disruption Jan 4 (Reuters) - Apple Inc AAPL.O is set to sign up Chinese contract manufacturer Luxshare Precision Industry Co Ltd 002475.SZ to produce premium iPhone models, the Financial Times reported on Wednesday, citing sources familiar with the matter. Luxshare has been producing small numbers of the iPhone 14 Pro Max at its Kunshan plant, to make up for lost production at Foxconn's Zhengzhou factory last year, the report added. Analysts expected Apple to diversify its supplier base amid production disruptions in China due to employee unrest at a factory operated by Foxconn and COVID-19 induced lockdowns. Apple in November warned of lower shipments of its premium iPhone 14 models following significant production cuts. The iPhone maker and Luxshare did not immediately respond to Reuters requests for comment. (Reporting by Akash Sriram in Bengaluru; Editing by Shailesh Kuber) ((Akash.Sriram@thomsonreuters.com; https://twitter.com/hoodieonveshti;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"FOCUS-At CES 2023, Sony's 'Gran Turismo' flags new entertainment strategy By Dawn Chmielewski Jan 4 (Reuters) - When Sony Corp Group 6758.T teases \\u201cGran Turismo,\\u201d its long-awaited adrenaline-fueled film adaptation of Sony PlayStation\\u2019s hit car-racing franchise at the CES 2023 technology trade show this week, it will really be showing off its new identity as a content-driven company. The movie reflects the transformation of the maker of the Walkman and Bravia TVs from a primarily hardware-focused innovator to broad-based entertainment provider. It also represents a significant bridging of the divides between Sony Pictures Entertainment, Sony PlayStation and Sony Music, according to a dozen current and former senior executives interviewed by Reuters. \\u201cI defined our identity as a creative entertainment company with a solid foundation on technology,\\u201d Sony chief executive Kenichiro Yoshida said. The film\\u2019s appearance at CES on a stage typically reserved for big-screen TVs and robot pets caps $10 billion in investments in music, games and anime over the last five years. \\u201cGran Turismo\\u201d is one of 10 game-inspired film and television projects in various stages of development. HBO's \\u201cThe Last of Us,\\u201d about a man hired to smuggle a 14-year-old girl across a pandemic-plagued America, debuts on Jan. 15. \\u201cThe New Yorker\\u201d suggested the series could break the curse of bad video-game adaptations. Sony\\u2019s \\u201ccreative entertainment\\u201d company approach extends beyond content. A Sony-Honda electric vehicle, scheduled to reach consumers by 2026, is being framed as a rolling showcase of Sony\\u2019s entertainment, gaming and camera sensor prowess. It will also generate recurring subscription revenue like other c\n\nPredict whether the return of XLY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.172892, "explanation": "The actual 21-day forward return for XLY starting 2023-01-05 was +17.29%, which classifies as 'positive'.", "metadata": {"future_return": 0.172892, "horizon_days": 21, "hist_return": -0.065625, "annualized_vol": 0.264619, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230628_0821", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-06-28", "context_summary": "QQQ over past 60 days: cumulative return +13.5%, annualized vol 16.9%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=315.34, end=357.98, cumulative_return=+13.5%, annualized_volatility=16.9%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.91, 't10y3m_spread': -1.67, 'breakeven_10y': 2.2, 'hy_oas': 4.3, 'ig_oas': 1.34, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 13.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-27] [\"After Hours Most Active for Jun 27, 2023 : NIO, QQQ, GOOGL, AAPL, SNAP, CPNG, TAL, GOOG, SIRI, INTC, ADC, PCG The NASDAQ 100 After Hours Indicator is down -16.52 to 14,929.39. The total After hours volume is currently 105,872,964 shares traded. The following are the most active stocks for the after hours session: NIO Inc. (NIO) is +0.01 at $9.35, with 5,738,261 shares traded. NIO's current last sale is 81.3% of the target price of $11.5. Invesco QQQ Trust, Series 1 (QQQ) is -0.42 at $363.41, with 3,325,196 shares traded. This represents a 42.93% increase from its 52 Week Low. Alphabet Inc. (GOOGL) is -0.22 at $118.11, with 3,182,605 shares traded. As reported by Zacks, the current mean recommendation for GOOGL is in the \\\"buy range\\\". Apple Inc. (AAPL) is -0.18 at $187.88, with 2,765,802 shares traded., following a 52-week high recorded in today's regular session. Snap Inc. (SNAP) is -0.02 at $11.46, with 2,566,014 shares traded. SNAP's current last sale is 114.6% of the target price of $10. Coupang, Inc. (CPNG) is unchanged at $17.32, with 2,390,584 shares traded. As reported by Zacks, the current mean recommendation for CPNG is in the \\\"buy range\\\". TAL Education Group (TAL) is unchanged at $6.04, with 2,356,934 shares traded. TAL's current last sale is 97.42% of the target price of $6.2. Alphabet Inc. (GOOG) is -0.21 at $118.80, with 2,278,956 shares traded. As reported by Zacks, the current mean recommendation for GOOG is in the \\\"buy range\\\". Sirius XM Holdings Inc. (SIRI) is +0.0194 at $4.11, with 2,267,460 shares traded. As reported in the last short interest update the days to cover for SIRI is 12.306221; this calculation is based on the average trading volume of the stock. Intel Corporation (INTC) is +0.01 at $34.11, with 2,190,518 shares traded. INTC's current last sale is 108.29% of the target price of $31.5. Agree Realty Corporation (ADC) is unchanged at $65.56, with 1,741,185 shares traded. As reported by Zacks, the current mean recommendation for ADC is in the \\\"buy range\\\". Pacific Gas & Electric Co. (PCG) is unchanged at $16.94, with 1,632,926 shares traded. As reported by Zacks, the current mean recommendation for PCG is in the \\\"buy range\\\". The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Wall Street closes higher as upbeat economic data allays slowdown fears By Sin\\u00e9ad Carew, Sruthi Shankar and Johann M Cherian June 27 (Reuters) - U.S. stock indexes rebounded on Tuesday from a recent losing streak as upbeat economic data soothed investor worries about an imminent recession triggered by the Federal Reserve's aggressive interest rate hikes. Separate reports showed new orders for key U.S.-manufactured capital goods unexpectedly rose in May, and sales of new single-family homes surged in the same month, while U.S. consumer confidence increased to a near 1-1/2 year high in June. While the economic data was encouraging, Rhys Williams, chief\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.051956, "explanation": "The actual 21-day forward return for QQQ starting 2023-06-28 was +5.20%, which classifies as 'positive'.", "metadata": {"future_return": 0.051956, "horizon_days": 21, "hist_return": 0.135229, "annualized_vol": 0.16906, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230421_0823", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-04-21", "context_summary": "VTI over past 60 days: cumulative return +2.3%, annualized vol 15.9%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=192.32, end=196.72, cumulative_return=+2.3%, annualized_volatility=15.9%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.6, 't10y3m_spread': -1.58, 'breakeven_10y': 2.26, 'hy_oas': 4.54, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.39, 'vix': 17.170000076293945}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-20] [\"Prediction: These Will Be 3 of the Most Valuable Stocks by 2050 The U.S. economy has evolved over the course of centuries. The industries that created the most value 100 years ago are not the same as the industries generating the most value today. For example, United States Steel became the world's first $1 billion company in 1901. But the world's largest company today is technology giant Apple, which has amassed a $2.6 trillion valuation. Which industries might drive the U.S. economy forward in the future, and how can investors benefit? Technologies like electric vehicles (EVs) and artificial intelligence (AI) are still in the very early stages of adoption, yet they hold significant potential as value creators. With that in mind, I predict the following three stocks will be among the world's most valuable by 2050. 1. Tesla Tesla (NASDAQ: TSLA) is the world's largest producer of electric vehicles (EVs), but its biggest opportunity might actually be elsewhere. Make no mistake, the EV market is set to be enormous with BloombergNEF projecting it could be worth $46 trillion by 2050, but Tesla is operating in other areas like artificial intelligence, which has the potential to dwarf that figure. Cathie Wood's Ark Investment Management thinks the technology could generate $90 trillion in enterprise value as soon as 2030, adding $200 trillion to global economic output. Tesla stock is the largest overall holding at Ark Investment Management for that reason. The firm thinks it could soar to $1,533 as soon as 2026 (from $185 as of this writing) which would value Tesla at $5.3 trillion. The basis for that prediction is the company's self-driving software, which could power a fleet of fully autonomous robotaxis in the future. Of course, AI is the force behind that technology. The value from autonomous car sales might overlap somewhat with the projected value of the EV market, because it's not clear what portion of miles will be driven by self-driving ride-hailing services, for example. On that note, Ark believes autonomous ride-sharing on its own could generate $14 trillion in enterprise value by 2027, and Tesla is already the leader by a wide margin with 2.7 million vehicles on the road collecting data today. But cars aren't the be-all and end-all of Tesla's business. It's applying AI in robotics, too, and its first mass-market product could be released by the end of this decade. It's called Optimus, a humanoid robot that could reshape the workforce by completing low-skilled jobs like manufacturing and manual labor. Tesla is worth $586 billion right now, making it the world's eighth-largest company. Given the sheer value of its opportunities ahead, there's a clear case for it catapulting its way up the rankings between now and 2050. 2. Microsoft Microsoft (NASDAQ: MSFT) might be the most conservative pick of this bunch, given it's the second-largest company in the world today with a valuation of $2.2 trillion. And that's nothing new -- it has been at the \n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.014878, "explanation": "The actual 21-day forward return for VTI starting 2023-04-21 was +1.49%, which classifies as 'positive'.", "metadata": {"future_return": 0.014878, "horizon_days": 21, "hist_return": 0.022851, "annualized_vol": 0.158601, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231009_0825", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2023-10-09", "context_summary": "LQD over past 60 days: cumulative return -6.3%, annualized vol 8.7%. Market regime: sideways.", "question": "Asset: LQD\nHistorical prices (past 60 trading days): start=95.52, end=89.47, cumulative_return=-6.3%, annualized_volatility=8.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.3, 't10y3m_spread': -0.85, 'breakeven_10y': 2.31, 'hy_oas': 4.33, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 17.450000762939453}\nMarket regime: sideways\n\nPredict whether the return of LQD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.013203, "explanation": "The actual 21-day forward return for LQD starting 2023-10-09 was +1.32%, which classifies as 'positive'.", "metadata": {"future_return": 0.013203, "horizon_days": 21, "hist_return": -0.063243, "annualized_vol": 0.087184, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231117_0826", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-11-17", "context_summary": "BNB-USD over past 60 days: cumulative return +12.4%, annualized vol 27.3%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=216.00, end=242.76, cumulative_return=+12.4%, annualized_volatility=27.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.38, 't10y3m_spread': -1.06, 'breakeven_10y': 2.27, 'hy_oas': 4.02, 'ig_oas': 1.21, 'ted_spread': 0.09, 'mortgage_30y': 7.44, 'vix': 14.31999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-16] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.023818, "explanation": "The actual 21-day forward return for BNB-USD starting 2023-11-17 was -2.38%, which classifies as 'negative'.", "metadata": {"future_return": -0.023818, "horizon_days": 21, "hist_return": 0.123863, "annualized_vol": 0.272574, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230404_0827", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-04-04", "context_summary": "IWM over past 60 days: cumulative return +0.9%, annualized vol 22.3%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=170.71, end=172.21, cumulative_return=+0.9%, annualized_volatility=22.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.54, 't10y3m_spread': -1.47, 'breakeven_10y': 2.29, 'hy_oas': 4.58, 'ig_oas': 1.43, 'ted_spread': 0.09, 'mortgage_30y': 6.32, 'vix': 18.549999237060547}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-03] [\"Top Research Reports for Apple, Meta Platforms & Visa Monday, April 3, 2023 The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc. (AAPL), Meta Platforms, Inc. (META) and Visa Inc. (V). These research reports have been hand-picked from the roughly 70 reports published by our analyst team today. You can see all of today\\u2019s research reports here >>> Apple shares are up +26.7% in the year-to-dater period vs. the Zacks Tech sector's 20.6% gain and the S&P 500 index's +7.4% gain. The company expects the March quarter\\u2019s year-over-year revenue growth to be similar to that of the December quarter due to unfavorable forex. For iPhone, Apple expects the March quarter\\u2019s year-over-year revenue growth to accelerate relative to the December quarter\\u2019s year-over-year revenue growth. For Mac and iPad, revenues are expected to decline in double digits on a year-over-year basis due to challenging comparison and macroeconomic headwinds. Services revenue growth is expected to be negatively impacted by challenging macroeconomic conditions, as well as weakness in digital advertising and gaming. However, revenues are expected to grow year over year. Growing services subscriber base and a strong liquidity position are key catalysts for Apple\\u2019s prospects. (You can read the full research report on Apple here >>>) Shares of Meta Platforms have outperformed the Zacks Internet - Software industry over the past six months (+51.1% vs. +14.1%). The company is benefiting from steady user growth across all regions, particularly Asia Pacific. Increased engagement for its products like Instagram, WhatsApp, Messenger, and Facebook has been a major growth driver. Its restructuring plan is expected to reduce expenses driving profitability. However, challenging macroeconomic conditions is negatively impacting Meta\\u2019s advertising revenues. Unfavorable forex, targeting and measurement headwinds due to Apple\\u2019s iOS changes, normalization of e-commerce after the pandemic peak and higher inflation hurt growth in the reported quarter. Meta\\u2019s first-quarter guidance reflects macroeconomic and forex concerns. Weak advertising demand is a headwind. Meta expects Reels to monetize much slower than feed or stories, which is a concern. (You can read the full research report on Meta Platforms here >>>) Visa shares have outperformed the Zacks Financial Transaction Services industry over the past six months (+22.0% vs. +15.2%). The company\\u2019s numerous buyouts and alliances paved the way for long-term growth and consistently drove its revenues. For fiscal 2023, net revenues are estimated to rise in the high single digits on a reported nominal dollar basis. Constant investments in technology are solidifying its position in the payments market. A shift in payments to the digital mode is a boon for Visa. Steady domestic volumes and transactions ris\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.02823, "explanation": "The actual 21-day forward return for IWM starting 2023-04-04 was -2.82%, which classifies as 'negative'.", "metadata": {"future_return": -0.02823, "horizon_days": 21, "hist_return": 0.008777, "annualized_vol": 0.222586, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230607_0829", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-06-07", "context_summary": "BTC-USD over past 60 days: cumulative return -2.5%, annualized vol 34.4%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=27947.79, end=27238.78, cumulative_return=-2.5%, annualized_volatility=34.4%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.81, 't10y3m_spread': -1.68, 'breakeven_10y': 2.2, 'hy_oas': 4.39, 'ig_oas': 1.39, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 13.960000038146973}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-06] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.141966, "explanation": "The actual 21-day forward return for BTC-USD starting 2023-06-07 was +14.20%, which classifies as 'positive'.", "metadata": {"future_return": 0.141966, "horizon_days": 21, "hist_return": -0.025369, "annualized_vol": 0.344168, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230707_0831", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2023-07-07", "context_summary": "DBA over past 60 days: cumulative return +0.1%, annualized vol 13.3%. Market regime: sideways.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=18.80, end=18.82, cumulative_return=+0.1%, annualized_volatility=13.3%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.41, 'breakeven_10y': 2.27, 'hy_oas': 4.1, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 15.4399995803833}\nMarket regime: sideways\n\nPredict whether the return of DBA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.020321, "explanation": "The actual 21-day forward return for DBA starting 2023-07-07 was +2.03%, which classifies as 'positive'.", "metadata": {"future_return": 0.020321, "horizon_days": 21, "hist_return": 0.000943, "annualized_vol": 0.133052, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240507_0833", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-05-07", "context_summary": "LINK-USD over past 60 days: cumulative return -26.5%, annualized vol 66.6%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=19.74, end=14.50, cumulative_return=-26.5%, annualized_volatility=66.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.33, 't10y3m_spread': -0.96, 'breakeven_10y': 2.35, 'hy_oas': 3.03, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 13.489999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.322287, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-05-07 was +32.23%, which classifies as 'positive'.", "metadata": {"future_return": 0.322287, "horizon_days": 21, "hist_return": -0.265403, "annualized_vol": 0.66613, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241030_0835", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2024-10-30", "context_summary": "LQD over past 60 days: cumulative return +0.9%, annualized vol 5.7%. Market regime: sideways.", "question": "Asset: LQD\nHistorical prices (past 60 trading days): start=101.34, end=102.27, cumulative_return=+0.9%, annualized_volatility=5.7%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.17, 't10y3m_spread': -0.42, 'breakeven_10y': 2.3, 'hy_oas': 2.85, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.54, 'vix': 19.34000015258789}\nMarket regime: sideways\n\nPredict whether the return of LQD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00961, "explanation": "The actual 21-day forward return for LQD starting 2024-10-30 was +0.96%, which classifies as 'flat'.", "metadata": {"future_return": 0.00961, "horizon_days": 21, "hist_return": 0.009165, "annualized_vol": 0.057308, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230322_0837", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-03-22", "context_summary": "XLF over past 60 days: cumulative return -4.9%, annualized vol 21.6%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=32.01, end=30.45, cumulative_return=-4.9%, annualized_volatility=21.6%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.58, 't10y3m_spread': -1.19, 'breakeven_10y': 2.23, 'hy_oas': 4.85, 'ig_oas': 1.52, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 21.3799991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-21] [\"Meta Stock: Bull vs. Bear Meta Platforms (NASDAQ: META) has taken investors for a wild ride over the past year or two. The stock soared through much of 2020 and 2021, riding a boom in digital advertising like other tech stocks, but that gave way to an epic collapse last year as revenue growth ground to a halt, and its ambitious project in the metaverse turned into a massive money pit. However, the stock has rebounded aggressively this year, doubling in the last few months after Zuckerberg promised investors that 2023 would be a \\\"year of efficiency\\\" and has since announced two rounds of layoffs. After so much tumult, Meta now appears to be at a crossroads as it cuts costs and realigns its business. So is it a buy today? To answer that question, we asked two of our writers to give their bull and bear cases for the stock. Image source: Meta Platforms. Meta Platforms' profitability cannot be ignored. Parkev Tatevosian: Meta Platforms may be facing a host of meaningful challenges, but that shouldn't deter investors from considering the social media giant turned metaverse hopeful. Rising competition from TikTok, privacy policy changes from Apple (NASDAQ: AAPL), and the raging war in Ukraine are each hurting Meta's prospects in the near term. However, I will argue investors are overreacting to those difficulties. Meta's stock is down 54% off its recent highs in 2021. Further, Mark Zuckerberg and his team at Meta have proven adept at finding answers to difficult situations. When people converted their social media use away from computers and onto mobile devices, the market worried Meta would suffer. Between 2015 and 2022, years of exponentially increasing mobile phone use, Meta's revenue soared from $17.9 billion to $116.6 billion. This revenue growth did not come at the expense of profits like many tech companies. Meta's operating income jumped from $6.2 billion to $28.9 billion in the years mentioned above. META PE Ratio (Forward) data by YCharts. It remains to be seen if Meta will take these current challenges and convert them into higher revenue and profits over the next several years. However, at a forward price-to-earnings ratio of 18.9, investors are getting a favorable risk-versus-reward from a company that has proven itself capable. Too many questions Jeremy Bowman: I've been impressed with Zuckerberg's ability to take back the narrative in the stock and drive a rebound in the share price, but the company still faces a number of challenges as it attempts to recapture the growth stock magic dust of old. Those include declining revenue, competition from TikTok, a maturing digital ad market, a massive misjudgment in the metaverse, and the threat of an extended recession. In other words, Meta is no longer the company it was a few years ago when it was growing rapidly and generating operating margins in the 40% range. However, Meta is unlikely to return to that previous growth rate. In fact, the company has posted a decline in revenue in each of \n\nPredict whether the return of XLF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.064061, "explanation": "The actual 21-day forward return for XLF starting 2023-03-22 was +6.41%, which classifies as 'positive'.", "metadata": {"future_return": 0.064061, "horizon_days": 21, "hist_return": -0.048619, "annualized_vol": 0.215719, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231228_0838", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-12-28", "context_summary": "EEM over past 60 days: cumulative return +9.2%, annualized vol 15.2%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=34.87, end=38.07, cumulative_return=+9.2%, annualized_volatility=15.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.41, 't10y3m_spread': -1.65, 'breakeven_10y': 2.15, 'hy_oas': 3.34, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 12.43000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-27] [\"Rate Volatility Spurs Global Broker BGC to Move Into Yen Swaps (Bloomberg) -- BGC Group Inc. is making a big push into the yen interest-rate derivatives business as speculation over Japan\\u2019s monetary policy fuels record volumes of transactions to hedge against potential changes in borrowing costs.Most Read from BloombergHow Were So Many Economists So Wrong About the Recession?Tesla Plans Revamp of Smash Hit Model Y From China PlantApple to Fight Watch Ban in Court After White House Declines to ActS&P 500 Trades Within a Whisker of All-Time High: Markets Wrap\", \"Property Wins Big, Adani Lags in Stellar Year for Indian Stocks (Bloomberg) -- Indian equities are set to cap a record eighth straight year of gains, with the drivers of the rally transcending the nation\\u2019s largest companies.Most Read from BloombergHow Were So Many Economists So Wrong About the Recession?Tesla Plans Revamp of Smash Hit Model Y From China PlantApple to Fight Watch Ban in Court After White House Declines to ActS&P 500 Trades Within a Whisker of All-Time High: Markets WrapGoldman\\u2019s Painful 2023 Lesson on China Forces Rethink of Emerging MarketsR\", \"BOJ Summary Suggests Ueda Can Wait for Wage Results Before Hike (Bloomberg) -- Bank of Japan board members discussed the potential timing of ending the negative rate policy during their meeting last week, with several members indicating they see no rush to make the move.Most Read from BloombergHow Were So Many Economists So Wrong About the Recession?Tesla Plans Revamp of Smash Hit Model Y From China PlantApple to Fight Watch Ban in Court After White House Declines to ActS&P 500 Trades Within a Whisker of All-Time High: Markets WrapGoldman\\u2019s Painful 2023 Less\", \"SoftBank Surges 7% After Getting $8 Billion of T-Mobile Stock (Bloomberg) -- SoftBank Group Corp. rose its most since June after snagging roughly $7.6 billion worth of stock in T-Mobile US Inc., as part of an agreement struck when the wireless carrier merged with rival Sprint Corp. in 2020.Most Read from BloombergHow Were So Many Economists So Wrong About the Recession?S&P 500 Trades Within a Whisker of All-Time High: Markets WrapApple to Fight Watch Ban in Court After White House Declines to ActGoldman\\u2019s Painful 2023 Lesson on China Forces Rethink of Emer\", \"SoftBank Surges 7% After Getting $8 Billion of T-Mobile Stock (Bloomberg) -- SoftBank Group Corp. rose its most since June after snagging roughly $7.6 billion worth of stock in T-Mobile US Inc., as part of an agreement struck when the wireless carrier merged with rival Sprint Corp. in 2020.Most Read from BloombergHow Were So Many Economists So Wrong About the Recession?Tesla Plans Revamp of Smash Hit Model Y From China PlantApple to Fight Watch Ban in Court After White House Declines to ActS&P 500 Trades Within a Whisker of All-Time High: Markets WrapGoldm\", \"A Detour of 8,000 Kilometers Highlights Shipping\\u2019s Chokepoints (Bloomberg) -- A gas tanker\\u2019s long, circuitous journey is highlig\n\nPredict whether the return of EEM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.033308, "explanation": "The actual 21-day forward return for EEM starting 2023-12-28 was -3.33%, which classifies as 'negative'.", "metadata": {"future_return": -0.033308, "horizon_days": 21, "hist_return": 0.091652, "annualized_vol": 0.151875, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231227_0840", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-12-27", "context_summary": "VTI over past 60 days: cumulative return +12.6%, annualized vol 13.1%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=205.27, end=231.09, cumulative_return=+12.6%, annualized_volatility=13.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.37, 't10y3m_spread': -1.56, 'breakeven_10y': 2.18, 'hy_oas': 3.37, 'ig_oas': 1.06, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 12.989999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-26] [\"Apple Watch ban goes into effect, Bristol Myers buying RayzeBio: Yahoo Finance Live Apple (AAPL) is appealing a ban on US sales of its Apple Watch Series 9 and Ultra 2. The ban stems from a patent dispute over pulse oximetry technology that is used in the watches. There is also deal news, with shares of RayzeBio (RYZB) doubling after it was announced Bristol Myers Squibb (BMY) was buying the company in a $4.1 billion agreement. Also on Yahoo Finance at 4 p.m. ET, Ark Invest\\u2019s Cathie Wood talks Tesla (TSLA) and the potential for a spot bitcoin ETF to be approved. Trending tickers on Yahoo Finance include Intel (INTC), Nio (NIO), and Nvidia (NVDA).Top guests on Yahoo Finance Live today include:3:05 p.m. ET - Tom Hainlin, U.S. Bank Wealth Management Senior Investment Strategist3:25 p.m. ET - Greg Martin, Managing Director of Rainmaker Securities3:50 p.m. ET - Shehzad Qazi, China Beige Book International Managing Director4:05 p.m. ET - Nick Powills, Mainland CEO, 1851 Franchise Publisher, and The Melting Pot Board Member\", \"Apple seeks a path to getting 2 of its best watches back on shelves during a bitter patent dispute Apple filed an emergency motion seeking court permission to begin selling two of its most popular watches again until a final decision on its broader appeal in a bitter patent dispute is decided. The company cut off sales right before the Christmas holiday and in a motion filed Tuesday, Apple said it would suffer \\u201cirreparable harm\\u201d if previous court orders remain for the two weeks that it said the U.S. International Trade Commission will take to respond to its appeal. The disruption will likely cost Apple about $300-400 million in holiday-season sales, estimated Wedbush Securities analyst Dan Ives.\", \"Bitcoin Dips Below $42,000 While Memecoin Rally Shows Signs of Stalling (Bloomberg) -- Bitcoin dropped below $42,000 for the first time in a week and the recent rally in memecoins has started to show signs of stalling. Most Read from BloombergGoldman\\u2019s Painful 2023 Lesson on China Forces Rethink of Emerging MarketsS&P 500 Trades Within a Whisker of All-Time High: Markets WrapApple to Fight Watch Ban in Court After White House Declines to ActHow Were So Many Economists So Wrong About the Recession?Ethiopia Fails to Pay Coupon, Becoming Latest African DefaulterThe lar\", \"25 Technologies That Have Changed the World In this article, we will be analyzing the evolution of technology while covering the 25 technologies that have changed the world. If you wish to skip our detailed analysis, you can move directly to the 5 Technologies That Have Changed the World. Technology Over the Years Following the dot com bubble burst, technology successfully rebounded. [\\u2026]\", \"South Korea\\u2019s Consumers Turn Less Pessimistic as Inflation Eases (Bloomberg) -- South Korean consumers turned less pessimistic this month as inflation eased and exports improved.Most Read from BloombergS&P 500 Trades Within a Whisker of All-Time High: Ma\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.016244, "explanation": "The actual 21-day forward return for VTI starting 2023-12-27 was +1.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.016244, "horizon_days": 21, "hist_return": 0.125821, "annualized_vol": 0.1311, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240102_0842", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-01-02", "context_summary": "AVAX-USD over past 60 days: cumulative return +245.7%, annualized vol 100.7%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=12.11, end=41.86, cumulative_return=+245.7%, annualized_volatility=100.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.35, 't10y3m_spread': -1.52, 'breakeven_10y': 2.16, 'hy_oas': 3.39, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.61, 'vix': 12.449999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.247346, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-01-02 was -24.73%, which classifies as 'negative'.", "metadata": {"future_return": -0.247346, "horizon_days": 21, "hist_return": 2.456682, "annualized_vol": 1.007486, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240314_0843", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-03-14", "context_summary": "XLU over past 60 days: cumulative return +0.8%, annualized vol 16.6%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=29.65, end=29.89, cumulative_return=+0.8%, annualized_volatility=16.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.42, 't10y3m_spread': -1.29, 'breakeven_10y': 2.3, 'hy_oas': 3.15, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.88, 'vix': 13.75}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 0000731766 2023-06-30 iso4217:USD 0000731766 2024-01-31 xbrli:shares 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0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2022-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2022-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.021468, "explanation": "The actual 21-day forward return for XLU starting 2024-03-14 was +2.15%, which classifies as 'positive'.", "metadata": {"future_return": 0.021468, "horizon_days": 21, "hist_return": 0.008, "annualized_vol": 0.166113, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240126_0845", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-01-26", "context_summary": "XRP-USD over past 60 days: cumulative return -15.0%, annualized vol 38.2%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.60, end=0.51, cumulative_return=-15.0%, annualized_volatility=38.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.14, 't10y3m_spread': -1.3, 'breakeven_10y': 2.29, 'hy_oas': 3.45, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 13.449999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.061578, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-01-26 was +6.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.061578, "horizon_days": 21, "hist_return": -0.149874, "annualized_vol": 0.381834, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230118_0847", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-01-18", "context_summary": "QUAL over past 60 days: cumulative return +12.8%, annualized vol 21.2%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=101.89, end=114.93, cumulative_return=+12.8%, annualized_volatility=21.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.65, 't10y3m_spread': -1.18, 'breakeven_10y': 2.17, 'hy_oas': 4.19, 'ig_oas': 1.3, 'ted_spread': 0.09, 'mortgage_30y': 6.33, 'vix': 19.36000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-17] [\"FAANG Stocks Look Ready to Soar Later This Month. Here's Why. FAANG stocks got crushed last year as a combination of slowing growth and compressing valuations hit even the mightiest tech stocks like Amazon (NASDAQ: AMZN), Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG), and Apple (NASDAQ: AAPL). 2023 offers investors the chance at a new beginning, and stocks jumped out of the gate on data showing that inflation is cooling while the economy remains stable. Looking ahead to earnings season, there's another reason why the stock market, and especially FAANG stocks, could get a boost. The dollar has weakened substantially over the last few months, which makes international revenue more valuable. Image source: Getty Images. The FX effect When big tech stocks reported third-quarter earnings nearly three months ago, a stronger dollar was a major headwind because all of these companies derive a significant percentage of their revenue from outside the U.S. In Amazon's third-quarter earnings report, the company reported 15% revenue growth, but it rose 19% in constant currency. Alphabet reported 6% revenue growth in its third quarter, or 11% in constant currency, and Netflix's (NASDAQ: NFLX) revenue rose 6%, or 13% in constant currency. As you can see from the chart below, the dollar index hit a 10-year high a few months ago, but the dollar cooled rapidly since then as interest rates have fallen and investors expect the Fed to stop hiking interest rates soon. ^DJFXCMD data by YCharts The chart below shows that the dollar plateaued in late September and October before falling sharply when the CPI report came out in November showing inflation falling faster than expected. It's continued to fall since then and now is the lowest it's been since last May. ^DJFXCMD data by YCharts Most multinational companies expected currency headwinds to strengthen from the third quarter to the fourth quarter. However, based on the chart above and the year-over-year comparisons, those currency headwinds seem to have actually weakened from the third quarter to the fourth, though they'll still weigh on results. That's a good indicator that FAANG results will beat guidance since these companies made their forecasts based on the value of the dollar in late October. Amazon, for example, called for 460 basis points of currency headwinds in its fourth quarter, but currency headwinds will almost certainly be more favorable than that. Similarly, Netflix, which gets most of its revenue from outside the U.S., expected nearly 8 percentage points of currency headwinds. Not only will these companies benefit from the weaker dollar in the fourth quarter, but their guidance is also likely to get a lift from the falling dollar. In fact, currency exchange could become a tailwind within a couple of quarters and for 2023 as a whole if the dollar continues to weaken. The weakening dollar is also a tailwind because of its impact on the bottom line. These companies typically have most of their expenses in U.\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.041284, "explanation": "The actual 21-day forward return for QUAL starting 2023-01-18 was +4.13%, which classifies as 'positive'.", "metadata": {"future_return": 0.041284, "horizon_days": 21, "hist_return": 0.127994, "annualized_vol": 0.211766, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230119_0849", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-01-19", "context_summary": "LINK-USD over past 60 days: cumulative return +10.0%, annualized vol 50.3%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=5.77, end=6.35, cumulative_return=+10.0%, annualized_volatility=50.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.69, 't10y3m_spread': -1.32, 'breakeven_10y': 2.12, 'hy_oas': 4.25, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.33, 'vix': 20.34000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-18] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.07203, "explanation": "The actual 21-day forward return for LINK-USD starting 2023-01-19 was +7.20%, which classifies as 'positive'.", "metadata": {"future_return": 0.07203, "horizon_days": 21, "hist_return": 0.100203, "annualized_vol": 0.503178, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241121_0850", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2024-11-21", "context_summary": "XLE over past 60 days: cumulative return +6.7%, annualized vol 19.8%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=42.44, end=45.27, cumulative_return=+6.7%, annualized_volatility=19.8%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.1, 't10y3m_spread': -0.21, 'breakeven_10y': 2.35, 'hy_oas': 2.67, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 17.15999984741211}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 2024-01-28 0001045810 us-gaap:CommonStockMember 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us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.114026, "explanation": "The actual 21-day forward return for XLE starting 2024-11-21 was -11.40%, which classifies as 'negative'.", "metadata": {"future_return": -0.114026, "horizon_days": 21, "hist_return": 0.066651, "annualized_vol": 0.198017, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240429_0852", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2024-04-29", "context_summary": "MTUM over past 60 days: cumulative return +6.7%, annualized vol 20.1%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=165.45, end=176.60, cumulative_return=+6.7%, annualized_volatility=20.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.29, 't10y3m_spread': -0.79, 'breakeven_10y': 2.43, 'hy_oas': 3.16, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 7.17, 'vix': 15.029999732971191}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of MTUM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.057194, "explanation": "The actual 21-day forward return for MTUM starting 2024-04-29 was +5.72%, which classifies as 'positive'.", "metadata": {"future_return": 0.057194, "horizon_days": 21, "hist_return": 0.067402, "annualized_vol": 0.200916, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20231226_0853", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-12-26", "context_summary": "SOL-USD over past 60 days: cumulative return +281.7%, annualized vol 102.4%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=31.74, end=121.15, cumulative_return=+281.7%, annualized_volatility=102.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.41, 't10y3m_spread': -1.54, 'breakeven_10y': 2.19, 'hy_oas': 3.39, 'ig_oas': 1.07, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 13.029999732971191}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.133566, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-12-26 was -13.36%, which classifies as 'negative'.", "metadata": {"future_return": -0.133566, "horizon_days": 21, "hist_return": 2.816875, "annualized_vol": 1.024116, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240927_0855", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-09-27", "context_summary": "XLF over past 60 days: cumulative return +8.7%, annualized vol 15.3%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=40.45, end=43.99, cumulative_return=+8.7%, annualized_volatility=15.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.19, 't10y3m_spread': -0.89, 'breakeven_10y': 2.16, 'hy_oas': 3.14, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.08, 'vix': 15.369999885559082}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of XLF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.045626, "explanation": "The actual 21-day forward return for XLF starting 2024-09-27 was +4.56%, which classifies as 'positive'.", "metadata": {"future_return": 0.045626, "horizon_days": 21, "hist_return": 0.087443, "annualized_vol": 0.153363, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20241003_0857", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-10-03", "context_summary": "XRP-USD over past 60 days: cumulative return +3.1%, annualized vol 61.9%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.52, end=0.54, cumulative_return=+3.1%, annualized_volatility=61.9%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 315.631, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.16, 't10y3m_spread': -0.9, 'breakeven_10y': 2.21, 'hy_oas': 3.06, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.08, 'vix': 18.89999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.018791, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-10-03 was +1.88%, which classifies as 'positive'.", "metadata": {"future_return": 0.018791, "horizon_days": 21, "hist_return": 0.031401, "annualized_vol": 0.6193, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230612_0858", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-06-12", "context_summary": "MATIC-USD over past 60 days: cumulative return -44.0%, annualized vol 54.1%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=1.13, end=0.64, cumulative_return=-44.0%, annualized_volatility=54.1%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.84, 't10y3m_spread': -1.62, 'breakeven_10y': 2.2, 'hy_oas': 4.29, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 13.829999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-11] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.109918, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-06-12 was +10.99%, which classifies as 'positive'.", "metadata": {"future_return": 0.109918, "horizon_days": 21, "hist_return": -0.440306, "annualized_vol": 0.540544, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231006_0860", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-10-06", "context_summary": "ICSH over past 60 days: cumulative return +0.9%, annualized vol 0.4%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=44.10, end=44.50, cumulative_return=+0.9%, annualized_volatility=0.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.31, 't10y3m_spread': -0.89, 'breakeven_10y': 2.31, 'hy_oas': 4.38, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 18.489999771118164}\nMarket regime: sideways\n\nPredict whether the return of ICSH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003186, "explanation": "The actual 21-day forward return for ICSH starting 2023-10-06 was +0.32%, which classifies as 'flat'.", "metadata": {"future_return": 0.003186, "horizon_days": 21, "hist_return": 0.009132, "annualized_vol": 0.004123, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231003_0862", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-10-03", "context_summary": "SOL-USD over past 60 days: cumulative return +2.5%, annualized vol 51.5%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=22.79, end=23.37, cumulative_return=+2.5%, annualized_volatility=51.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.43, 't10y3m_spread': -0.93, 'breakeven_10y': 2.35, 'hy_oas': 4.11, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 7.31, 'vix': 17.610000610351562}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-02] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.280174, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-10-03 was +28.02%, which classifies as 'positive'.", "metadata": {"future_return": 0.280174, "horizon_days": 21, "hist_return": 0.025362, "annualized_vol": 0.515438, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230605_0864", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2023-06-05", "context_summary": "XHB over past 60 days: cumulative return +8.8%, annualized vol 22.3%. Market regime: sideways.", "question": "Asset: XHB\nHistorical prices (past 60 trading days): start=65.27, end=70.98, cumulative_return=+8.8%, annualized_volatility=22.3%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.81, 't10y3m_spread': -1.68, 'breakeven_10y': 2.18, 'hy_oas': 4.37, 'ig_oas': 1.39, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 14.600000381469728}\nMarket regime: sideways\n\nPredict whether the return of XHB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.081732, "explanation": "The actual 21-day forward return for XHB starting 2023-06-05 was +8.17%, which classifies as 'positive'.", "metadata": {"future_return": 0.081732, "horizon_days": 21, "hist_return": 0.087509, "annualized_vol": 0.223495, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240515_0866", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-05-15", "context_summary": "SOL-USD over past 60 days: cumulative return -21.9%, annualized vol 80.8%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=181.88, end=142.03, cumulative_return=-21.9%, annualized_volatility=80.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.36, 't10y3m_spread': -0.99, 'breakeven_10y': 2.33, 'hy_oas': 3.14, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 13.420000076293944}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.096696, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-05-15 was +9.67%, which classifies as 'positive'.", "metadata": {"future_return": 0.096696, "horizon_days": 21, "hist_return": -0.2191, "annualized_vol": 0.807991, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230905_0868", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-09-05", "context_summary": "XLE over past 60 days: cumulative return +11.9%, annualized vol 17.6%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=37.08, end=41.51, cumulative_return=+11.9%, annualized_volatility=17.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.69, 't10y3m_spread': -1.35, 'breakeven_10y': 2.26, 'hy_oas': 3.81, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 13.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-01] [\"Should You Buy the Dow Stock Outperforming Apple? When you think of top-performing Dow stocks to buy, you might automatically think of Apple (AAPL) - it's the world\\u2019s most valuable company, a favorite of legendary investor Warren Buffett, and a leader in consumer technology. But what if we told you there is another Dow Jones Industrial Average ($DOWI) component that has been crushing Apple on the charts over several time frames - and it's not even a tech stock? That stock is none other than Caterpillar (CAT), the world\\u2019s largest manufacturer of construction and mining equipment and a true old-school industrial name. And while CAT hasn't exactly collected AI stock-sized gains in 2023, it's worth taking a look at the stock's performance from a few different perspectives to get a sense of its real technical muscle. CAT's Long-Term Technical Dominance To be sure, Apple stock is outpacing comfortably CAT on a year-to-date basis - but let's not forget how much room for recovery Apple and its tech stock peers had after a brutal finish to 2022. Looking over the past 52 weeks, Caterpillar stock has gained nearly 60%, while AAPL is only 20% higher. The broader Dow, for perspective, is up about 10% in this time frame. www.barchart.com More recently, focusing in on the last three months, AAPL's impressive momentum from the first half of 2023 has slowed considerably, with the shares netting a return of less than 5% over this period. Meanwhile, CAT has gained more than 25%, powered in part by well-received Q2 earnings (by contrast, Apple missed iPhone sales estimates in its recent quarterly report). www.barchart.com So with CAT clearly holding its own against this tech powerhouse on the charts, let's take a look at the fundamentals. CAT\\u2019s Earnings Beat Expectations In its second-quarter earnings report, CAT reported revenue of $14.4 billion, marking a 29% surge compared to the previous year. Earnings per share also impressed, up 74% year-over-year to reach $5.55. Notably, both figures outperformed analysts' expectations, which were projected at $13.9 billion and $4.51 per share, respectively. Caterpillar also raised its full-year revenue and earnings guidance, and the stock led Dow gainers after the report with a rally of more than 8%. www.barchart.com CAT attributed its results to a global increase in infrastructure spending and investment. This surge in demand spanned all segments, with its construction, resource, and energy and transportation divisions all posting significant growth. The construction segment reported a 45% revenue increase, buoyed by higher sales volume and the introduction of new products like the electric mini excavator and autonomous dozer. At the same time, resource segment revenue was up 41%, driven by elevated sales volume in mining and entry into emerging markets like lithium and rare earths. Plus, the energy and transportation segment contributed 16% revenue growth, propelled by increased sales volume and innovative\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.053028, "explanation": "The actual 21-day forward return for XLE starting 2023-09-05 was -5.30%, which classifies as 'negative'.", "metadata": {"future_return": -0.053028, "horizon_days": 21, "hist_return": 0.119335, "annualized_vol": 0.175589, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230608_0870", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2023-06-08", "context_summary": "INDS over past 60 days: cumulative return +2.8%, annualized vol 17.7%. Market regime: sideways.", "question": "Asset: INDS\nHistorical prices (past 60 trading days): start=35.43, end=36.41, cumulative_return=+2.8%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.77, 't10y3m_spread': -1.63, 'breakeven_10y': 2.21, 'hy_oas': 4.33, 'ig_oas': 1.39, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 13.9399995803833}\nMarket regime: sideways\n\nPredict whether the return of INDS over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.020086, "explanation": "The actual 21-day forward return for INDS starting 2023-06-08 was -2.01%, which classifies as 'negative'.", "metadata": {"future_return": -0.020086, "horizon_days": 21, "hist_return": 0.027815, "annualized_vol": 0.177323, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230803_0871", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-08-03", "context_summary": "AVAX-USD over past 60 days: cumulative return -15.2%, annualized vol 57.1%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=14.78, end=12.54, cumulative_return=-15.2%, annualized_volatility=57.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.8, 't10y3m_spread': -1.45, 'breakeven_10y': 2.36, 'hy_oas': 3.96, 'ig_oas': 1.21, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 16.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-02] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.18744, "explanation": "The actual 21-day forward return for AVAX-USD starting 2023-08-03 was -18.74%, which classifies as 'negative'.", "metadata": {"future_return": -0.18744, "horizon_days": 21, "hist_return": -0.151878, "annualized_vol": 0.571469, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230616_0872", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-06-16", "context_summary": "XLE over past 60 days: cumulative return +2.9%, annualized vol 24.2%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=35.68, end=36.72, cumulative_return=+2.9%, annualized_volatility=24.2%\nMacro context: {'fed_funds_rate': 5.07, 'cpi_yoy': 304.014, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.9, 't10y3m_spread': -1.61, 'breakeven_10y': 2.21, 'hy_oas': 4.21, 'ig_oas': 1.37, 'ted_spread': 0.09, 'mortgage_30y': 6.69, 'vix': 14.5}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-15] [\"US STOCKS-Wall St edges up as yields slip after economic data By Shristi Achar A and Sruthi Shankar June 15 (Reuters) - Wall Street's main indexes inched higher on Thursday as megacap stocks rose on lower Treasury yields, lifting investor sentiment soured by Federal Reserve's hawkish comments on interest rate hikes this year. U.S. retail sales unexpectedly rose in May as consumers spent on a range of goods including vehicles, which could help support the economy this quarter. Another set of numbers showed initial claims for state unemployment benefits were steady at a seasonally adjusted 262,0000 for the week ended June 10. Economists polled by Reuters had forecast 249,000 claims for the latest week. U.S. Treasury yields pulled back, lifting shares of rate-sensitive growth stocks. Apple AAPL.O, Microsoft MSFT.O and Meta Platforms META.O gained between 0.8% and 1.3%. US/ The Fed left rates unchanged at the 5%-5.25% range on Wednesday, but indicated they could rise by at least half a percentage point this year as inflation remains stubbornly persistent and the U.S. economy stays resilient. \\\"What has been encouraging is that the rate market has significantly reassessed the trajectory of expected interest rates but the equity market has largely ignored that and, if anything, continued to rise on the belief that the Fed is at or near the end of the rate hike cycle,\\\" said Ronald Temple, chief market strategist at Lazard. \\\"Yesterday's message was a bit of a splash of cold water on equity markets.\\\" Traders see a nearly 65% chance of a 25-basis-point rate hike in July, up from around 60% a day earlier, according to the CME Fedwatch tool. Energy stocks .SPNY led gains among the 11 major S&P 500 sectors, up 1.4%, tracking higher crude prices. O/R At 10:06 a.m. ET, the Dow Jones Industrial Average .DJI was up 188.05 points, or 0.55%, at 34,167.38, the S&P 500 .SPX was up 16.85 points, or 0.39%, at 4,389.44, and the Nasdaq Composite .IXIC was up 25.76 points, or 0.19%, at 13,652.23. Kroger CoKR.N dropped 3.9% after the big-box retailer missed first-quarter revenue estimates. Kohls Corp KSS.N added 3.1% after TD Cowen upgraded the department store operator to \\\"outperform\\\" from \\\"market perform\\\". U.S.-listed shares of Chinese companies including Alibaba Group BABA.N and JD.com JD.O rose almost 3% after the People's Bank of China cut the borrowing cost for its medium-term policy loans for the first time in 10 months. Advancing issues outnumbered decliners by a 1.90-to-1 ratio on the NYSE and a 1.46-to-1 ratio on the Nasdaq. The S&P index recorded 20 new 52-week highs and no new low, while the Nasdaq recorded 32 new highs and 38 new lows. (Reporting by Shristi Achar A and Sruthi Shankar in Bengaluru Editing by Vinay Dwivedi) ((Shristi.AcharA@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-Wall Street rallies as yields slip after econom\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.014173, "explanation": "The actual 21-day forward return for XLE starting 2023-06-16 was +1.42%, which classifies as 'positive'.", "metadata": {"future_return": 0.014173, "horizon_days": 21, "hist_return": 0.029232, "annualized_vol": 0.241777, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240424_0874", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-04-24", "context_summary": "SGOV over past 60 days: cumulative return +0.8%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=91.42, end=92.19, cumulative_return=+0.8%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.25, 't10y3m_spread': -0.84, 'breakeven_10y': 2.41, 'hy_oas': 3.2, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 7.1, 'vix': 15.6899995803833}\nMarket regime: sideways\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003071, "explanation": "The actual 21-day forward return for SGOV starting 2024-04-24 was +0.31%, which classifies as 'flat'.", "metadata": {"future_return": 0.003071, "horizon_days": 21, "hist_return": 0.008394, "annualized_vol": 0.001851, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240521_0876", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-05-21", "context_summary": "SOL-USD over past 60 days: cumulative return +7.0%, annualized vol 74.3%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=174.36, end=186.52, cumulative_return=+7.0%, annualized_volatility=74.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.38, 't10y3m_spread': -1.01, 'breakeven_10y': 2.33, 'hy_oas': 3.07, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 7.02, 'vix': 12.149999618530272}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.161059, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-05-21 was -16.11%, which classifies as 'negative'.", "metadata": {"future_return": -0.161059, "horizon_days": 21, "hist_return": 0.069721, "annualized_vol": 0.742842, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230516_0878", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-05-16", "context_summary": "XLI over past 60 days: cumulative return -3.6%, annualized vol 17.1%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=98.12, end=94.63, cumulative_return=-3.6%, annualized_volatility=17.1%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.49, 't10y3m_spread': -1.68, 'breakeven_10y': 2.19, 'hy_oas': 4.77, 'ig_oas': 1.49, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 17.1200008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-15] [\"Capitalize on the Emerging Age of AI for Hefty Profits InvestorPlace - Stock Market News, Stock Advice & Trading Tips Editor\\u2019s note: \\u201cCapitalize on the Emerging Age of AI for Hefty Profits\\u201d was previously published in March 2023. It has since been updated to include the most relevant information available. Crisis creates opportunity. And big crises create big opportunities. For example, did you know that the Internet Economy \\u2013 which created the world\\u2019s first trillion-dollar companies, churning out multiple 1,000% stock market winners \\u2013 was born amid the 2008 financial crisis? Technically, the internet was born in the 1990s \\u2013 the World Wide Web launched on Aug. 6, 1991. But it wasn\\u2019t until Apple (AAPL) released the first iPhone in 2007 \\u2013 and put the power of the internet literally in the palms of everyone\\u2019s hands \\u2013 that the Internet Economy really started to blossom. Just look at how the revenue growth trajectories for internet titans like Amazon (AMZN), Alphabet (GOOGL), and Netflix (NFLX) dramatically changed after the iPhone\\u2019s launch. Before the iPhone, internet companies were growing. After, they started to spread like wildfire and take over the world. It was a critical inflection point \\u2013 the \\u201ctipping point\\u201d for the internet revolution\\u2026 The moment when everything changed. Of course, at the time, it didn\\u2019t feel like that. The financial economy was collapsing because of the subprime loan meltdown. Unemployment rates were soaring. Stocks were crashing. Companies were going bankrupt. Home foreclosures were happening left and right. It felt like the end times, even for internet stocks like Amazon, Netflix, Alphabet, and the iPhone\\u2019s maker, Apple. All those stocks dropped between 50% and 60% in 2008 \\u2013 the year after the iPhone launched. What a crisis\\u2026 And what an opportunity. Crisis Begets Opportunity For investors who were able to zoom out and look at the big picture, the financial crisis created the opportunity of a lifetime. It left internet stocks trading at dirt-cheap valuations just months after the emergence of the Internet Economy\\u2019s biggest catalyst of all time \\u2013 the iPhone. Those \\u201cbig-picture\\u201d investors were able to recognize that the economy wasn\\u2019t going to collapse and that the 2008 crisis \\u2013 like all financial crises before it \\u2013 would pass. They were able to identify the iPhone\\u2019s significance as a critical inflection point for the Internet Economy that would spark 10-plus years of super-charged growth. They were able to see the deep value in internet stocks. And they were smart enough to buy the dip in names like Amazon, Netflix, Apple, and Alphabet. As a result, those \\u201cbig-picture\\u201d investors have since made fortunes. Every $10,000 invested in Alphabet stock in late 2008 would be worth nearly $140,000 today. A $10,000 investment in Amazon or Apple stock in late 2008 would be worth nearly $\n\nPredict whether the return of XLI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.08195, "explanation": "The actual 21-day forward return for XLI starting 2023-05-16 was +8.20%, which classifies as 'positive'.", "metadata": {"future_return": 0.08195, "horizon_days": 21, "hist_return": -0.035562, "annualized_vol": 0.170723, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240122_0881", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-01-22", "context_summary": "BTC-USD over past 60 days: cumulative return +11.4%, annualized vol 39.3%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=37289.62, end=41545.79, cumulative_return=+11.4%, annualized_volatility=39.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.24, 't10y3m_spread': -1.3, 'breakeven_10y': 2.34, 'hy_oas': 3.54, 'ig_oas': 1.01, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 13.300000190734863}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.264529, "explanation": "The actual 21-day forward return for BTC-USD starting 2024-01-22 was +26.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.264529, "horizon_days": 21, "hist_return": 0.114138, "annualized_vol": 0.392707, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240829_0883", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-08-29", "context_summary": "AVAX-USD over past 60 days: cumulative return -20.1%, annualized vol 79.0%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=29.36, end=23.46, cumulative_return=-20.1%, annualized_volatility=79.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.062, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.01, 't10y3m_spread': -1.37, 'breakeven_10y': 2.15, 'hy_oas': 3.19, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.46, 'vix': 17.110000610351562}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.163683, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-08-29 was +16.37%, which classifies as 'positive'.", "metadata": {"future_return": 0.163683, "horizon_days": 21, "hist_return": -0.20083, "annualized_vol": 0.790211, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230207_0885", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-02-07", "context_summary": "XLRE over past 60 days: cumulative return +14.3%, annualized vol 23.3%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=31.88, end=36.45, cumulative_return=+14.3%, annualized_volatility=23.3%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.81, 't10y3m_spread': -1.08, 'breakeven_10y': 2.25, 'hy_oas': 3.99, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 6.09, 'vix': 19.43000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-06] [\"A Rare Earnings Miss Couldn\\u2019t Stop Apple Stock (NASDAQ:AAPL) Shares of Apple (NASDAQ:AAPL) are fresh off a quarterly earnings miss, with sales slipping 5% year-over-year, marking the worst quarterly top-line decline in years. Still, Apple stock was resilient following the disappointing number, closing off Friday's session up 2.4% in a bloody day for tech stocks. I remain bullish as Apple stock shrugs off its forgettable quarter and moves on from headwinds that are bound to fade in time. The recent round of quarterly results themselves was nothing to write home about (weakness was broadly spread across categories). It was likely the words of management that helped soothed investor nerves, helping Apple stock outperform some FAANG rivals that also reported the previous day. The company didn't give formal guidance for Fiscal 2023 due to macro uncertainty. It's noteworthy that the words \\\"macro headwinds\\\" were used quite a bit throughout the conference call. In any case, I think it's only prudent not to attempt to provide any sort of concrete guidance with recession headwinds up ahead. Despite the lack of guidance, management didn't leave investors in the dark. CEO Tim Cook called for year-over-year sales growth to be \\\"similar to the December quarter.\\\" Such words, I believe, set the bar quite low for the coming quarter and could set the stage to impress. He also stated that \\\"from a supply chain point of view, we're now at a point where production is what we need it to be.\\\" That alone was likely enough to help Apple investors breathe a sigh of relief. Apple: The Worst of the Production Issues May Have Passed My takeaway from Cook's comments was that the worst of production headwinds may already be in the rearview mirror. Indeed, the next quarter could see iPhone revenue growth in the red. However, the second half could see Apple make up for lost time as production gets up to full speed while Apple users finally look to upgrade. Indeed, Apple can afford to have some sizeable supply-side hiccups without losing too much business. At the end of the day, customer loyalty is unparalleled, with many Apple users that will opt not to switch to a competing product, even if it means having to endure longer wait times. Lockdowns in China have weighed heavily on operations. Still, I am confident that Cook can promptly bring production back in order. The man is an operational genius who's effectively ironed out supply-chain wrinkles in the past. Once Apple moves past the current barrage of headwinds, it'll likely be right back to gaining meaningful market share in the smartphone market again. Further, amping up efforts to expand into India, a market where Apple is reportedly enjoying double-digit growth, could help fuel such market gains. Apple's Rough Quarter is Easy to Forgive There's no question that Apple was up against it going into what many expected would be a rough quarter. Going into the quarter, estimates were muted, thanks in part to manufact\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.080168, "explanation": "The actual 21-day forward return for XLRE starting 2023-02-07 was -8.02%, which classifies as 'negative'.", "metadata": {"future_return": -0.080168, "horizon_days": 21, "hist_return": 0.143392, "annualized_vol": 0.233378, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230906_0886", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2023-09-06", "context_summary": "SCHP over past 60 days: cumulative return -1.2%, annualized vol 6.0%. Market regime: sideways.", "question": "Asset: SCHP\nHistorical prices (past 60 trading days): start=23.81, end=23.53, cumulative_return=-1.2%, annualized_volatility=6.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.67, 't10y3m_spread': -1.28, 'breakeven_10y': 2.29, 'hy_oas': 3.83, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 14.010000228881836}\nMarket regime: sideways\n\nPredict whether the return of SCHP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.019041, "explanation": "The actual 21-day forward return for SCHP starting 2023-09-06 was -1.90%, which classifies as 'negative'.", "metadata": {"future_return": -0.019041, "horizon_days": 21, "hist_return": -0.011625, "annualized_vol": 0.06025, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231012_0888", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-10-12", "context_summary": "ADA-USD over past 60 days: cumulative return -14.3%, annualized vol 30.3%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.29, end=0.25, cumulative_return=-14.3%, annualized_volatility=30.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.41, 't10y3m_spread': -1.03, 'breakeven_10y': 2.32, 'hy_oas': 4.25, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 16.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-11] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.314002, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-10-12 was +31.40%, which classifies as 'positive'.", "metadata": {"future_return": 0.314002, "horizon_days": 21, "hist_return": -0.143439, "annualized_vol": 0.302731, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230823_0889", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-08-23", "context_summary": "XLK over past 60 days: cumulative return +2.1%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=80.70, end=82.41, cumulative_return=+2.1%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.68, 't10y3m_spread': -1.23, 'breakeven_10y': 2.35, 'hy_oas': 3.93, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 7.09, 'vix': 16.969999313354492}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-22] [\"Apple\\u2019s Buyback Blunder: 3 Reasons It\\u2019s Not a Win for AAPL Shareholders InvestorPlace - Stock Market News, Stock Advice & Trading Tips If there\\u2019s one thing that feels like Christmas to Warren Buffett is when Apple (NASDAQ:AAPL) repurchases AAPL stock. After all, the more Apple stock the iPhone maker buys back, the more significant percentage of Apple Berkshire Hathaway (NYSE:BRK.B) owns. In Berkshire\\u2019s 2021 shareholder letter, Buffett mentions that his company spent no money to increase its ownership stake to 5.5% from 5.39% in 2020. Share repurchases by Apple in 2021 added $1.1 billion in earnings controlled by Berkshire\\u2019s investment. \\u201cIt\\u2019s important to understand that only dividends from Apple are counted in the GAAP earnings Berkshire reports \\u2013 and last year, Apple paid us $785 million of those. Yet our \\u2018share\\u2019 of Apple\\u2019s earnings amounted to a staggering $5.6 billion,\\u201d Berkshire\\u2019s 2021 shareholder letter stated. \\u201cMuch of what the company retained was used to repurchase Apple shares, an act we applaud.\\u201d Warren Buffett might like the Apple buybacks, but the average investor has three reasons to consider why it\\u2019s not a win for regular AAPL stock investors. It Significantly Overpaid for AAPL Stock Source: Shutterstock Apple has spent more than $500 billion in share repurchases since 2012. The company had 929.4 million shares as of Oct. 14, 2011. On Oct. 14, 2023, it had 15.91 billion shares. Apple\\u2019s stock has split on two occasions over this period \\u2014 a 7-for-1 split on June 9, 2014, and a 4-for-1 split on Aug. 28, 2020 \\u2014 which increased the share count. Considering the two splits, it reduced its share count by 39% [929.4M x 7 x 4 minus 15.91B divided by 26.02B]. That seems like a great deal for Apple shareholders. Have you ever considered what it could have paid for these shares? In fiscal 2022, the company repurchased $90.2 billion of its stock at an average price of $158.52. It is the most repurchased in a single year in the company\\u2019s history. Based on its current share price, it has a 10.1% return on its investment. In the 12 months between Sept. 22, 2021, and Sept. 23, 2022, Apple\\u2019s high was $182.94 in January 2022, while its low was $129.04 in June 2022. The average of the high and low during the year was $155.99. It paid $2.53 more per share than the average. Conservatively, that\\u2019s over $1 billion too much. I would bet dollars to donuts; it\\u2019s done this every year since 2012. Reinvestment of Funds Used Could Have Developed a New Killer Product Source: Vit-Mar/Shutterstock Despite the possibility of a virtual reality (VR) headset and driverless car, the iPhone remains Apple\\u2019s key product and revenue generator. ZDNet reminded its readers in September 2022 that only 11.2 million VR headsets were shipped in 2021 compared to 1.3 billion smartphones. That\\u2019s 116x as many. In June this year, AAPL stock launched the Apple Vis\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.036202, "explanation": "The actual 21-day forward return for XLK starting 2023-08-23 was -3.62%, which classifies as 'negative'.", "metadata": {"future_return": -0.036202, "horizon_days": 21, "hist_return": 0.02119, "annualized_vol": 0.172457, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231020_0891", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-10-20", "context_summary": "^VIX over past 60 days: cumulative return +48.5%, annualized vol 99.7%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=14.41, end=21.40, cumulative_return=+48.5%, annualized_volatility=99.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.16, 't10y3m_spread': -0.62, 'breakeven_10y': 2.49, 'hy_oas': 4.37, 'ig_oas': 1.31, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 21.39999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-19] [\"Google to manufacture smartphones in India starting with Pixel 8 Adds quote in paragraph 3, context from paragraph 4 NEW DELHI, Oct 19 (Reuters) - Alphabet Inc GOOGL.O will start manufacturing in India and will partner with international and domestic manufacturers to produce its Pixel smartphones locally, starting with Pixel 8, an executive said on Thursday. The devices are expected to be rolled out in 2024, Rick Osterloh, senior vice president of devices and services, said at a Google event. \\\"India is a priority market for Pixel smartphones, and we\\u2019re committed to bringing the best of our hardware and underlying built-in software capabilities to people across the country,\\\" Osterloh said. India is aiming to become a manufacturing powerhouse, amid a greater push for Prime Minister Narendra Modi's \\\"Make in India\\\" initiative. Apple AAPL.O, which has been touting India as its next big growth driver, is projected to account for 7% of all smartphone sales in the country from July to December, up from 5% in the first half of 2023, according to data from market researcher Counterpoint. U.S. memory chip firm Micron Technology MU.O recently announced plans to set up its first semiconductor plant in the country. (Reporting by Tanvi Mehta and Blassy Boben; Editing by Muralikumar Anantharaman) ((blassy.boben@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"TSMC Q3 profit falls 24.9%, beats market forecasts Q3 profit T$211 bln vs T$195.5 bln analyst view Q3 revenue down 14.6% on year at $17.3 bln Q3 capex $7.1 bln vs Q2 $8.17 bln Adds details and share prices in paragraphs 4-7 TAIPEI, Oct 19 (Reuters) - Taiwanese chipmaker TSMC 2330.TW posted a 24.9% fall in third-quarter net profit on Thursday as global economic woes hit demand for chips used in applications from cars to cellphones and servers and coming off a high base last year. Taiwan Semiconductor Manufacturing Co Ltd (TSMC) TSM.N, the world's largest contract chipmaker and a major Apple Inc AAPL.O supplier, saw July-September net profit fall to T$211 billion from T$280.9 billion a year earlier. The profit beat a T$195.5 billion LSEG SmartEstimate, which is weighted toward forecasts from analysts who are more consistently accurate. TSMC, Asia's most valuable listed company, said third-quarter revenue dropped 14.6% to $17.3 billion, in line with the company's previous forecast of $16.7 billion to $17.5 billion. Capital expenditure in the third quarter was $7.1 billion, TSMC said, compared with $8.17 billion in the previous quarter. As the biggest maker of advanced chips, TSMC must navigate an uncertain industry outlook and a U.S.-China chip spat that could make it vulnerable. TSMC's Taipei-listed shares fell 27.1% in 2022, but are up around 22% so far this year, giving the chipmaker a market value of $432.3 billion. The stock rose 1.1% on Thursday versus a flat benchmark index .TWII. (Re\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.382312, "explanation": "The actual 21-day forward return for ^VIX starting 2023-10-20 was -38.23%, which classifies as 'negative'.", "metadata": {"future_return": -0.382312, "horizon_days": 21, "hist_return": 0.48508, "annualized_vol": 0.997313, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240909_0893", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2024-09-09", "context_summary": "TLH over past 60 days: cumulative return +5.9%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=97.26, end=102.98, cumulative_return=+5.9%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.06, 't10y3m_spread': -1.41, 'breakeven_10y': 2.03, 'hy_oas': 3.39, 'ig_oas': 0.99, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 22.3799991607666}\nMarket regime: sideways\n\nPredict whether the return of TLH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.032907, "explanation": "The actual 21-day forward return for TLH starting 2024-09-09 was -3.29%, which classifies as 'negative'.", "metadata": {"future_return": -0.032907, "horizon_days": 21, "hist_return": 0.058873, "annualized_vol": 0.118972, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240301_0895", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-03-01", "context_summary": "XLRE over past 60 days: cumulative return +3.4%, annualized vol 17.7%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=35.08, end=36.28, cumulative_return=+3.4%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.39, 't10y3m_spread': -1.2, 'breakeven_10y': 2.33, 'hy_oas': 3.29, 'ig_oas': 1.0, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 13.399999618530272}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 0000731766 2023-06-30 iso4217:USD 0000731766 2024-01-31 xbrli:shares 0000731766 2023-12-31 0000731766 2022-12-31 iso4217:USD xbrli:shares 0000731766 2022-01-01 2022-12-31 0000731766 2021-01-01 2021-12-31 0000731766 us-gaap:ProductMember 2023-01-01 2023-12-31 0000731766 us-gaap:ProductMember 2022-01-01 2022-12-31 0000731766 us-gaap:ProductMember 2021-01-01 2021-12-31 0000731766 us-gaap:ServiceMember 2023-01-01 2023-12-31 0000731766 us-gaap:ServiceMember 2022-01-01 2022-12-31 0000731766 us-gaap:ServiceMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2020-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2020-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2020-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2020-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2020-12-31 0000731766 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2021-01-01 2021-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2021-01-01 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srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:BuildingMember 2023-12-31 0000731766 unh:CapitalizedsoftwareMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember unh:CapitalizedsoftwareMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2021-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-01-01 2023-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-01-01 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-12-31 0000731766 us-gaap:RestrictedStockMember 2023-01-01 2023-12-31 0000731766 unh:StockOptionsandSARsMember 2023-01-01 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2022-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2022-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.011016, "explanation": "The actual 21-day forward return for XLRE starting 2024-03-01 was -1.10%, which classifies as 'negative'.", "metadata": {"future_return": -0.011016, "horizon_days": 21, "hist_return": 0.034171, "annualized_vol": 0.176624, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230706_0896", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-07-06", "context_summary": "XLRE over past 60 days: cumulative return +3.4%, annualized vol 17.3%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=33.63, end=34.77, cumulative_return=+3.4%, annualized_volatility=17.3%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.49, 'breakeven_10y': 2.26, 'hy_oas': 4.01, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 14.18000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-05] [\"MORNING BID ASIA-Yellen in China By Jamie McGeever July 6 (Reuters) - A look at the day ahead in Asian markets from Jamie McGeever, financial markets columnist. U.S. Treasury Secretary Janet Yellen touches down in Beijing on Thursday for a three-day visit just as trade tensions between the world's two superpowers ratchet up another notch, while a Malaysian interest rate decision tops the region's economic calendar. Australian trade data and Taiwanese inflation figures are on tap too, and equity investors will digest a mixed earnings report from Taiwan's Foxconn2317.TW, a major iPhone assembler for Apple Inc AAPL.O. Asian stocks go into Thursday's session on the defensive, underperforming on Wednesday after figures showed that China's service sector activity expanded at the slowest pace in five months in June. Foxconn's results may help lift the gloom, after the firm on Wednesday forecast a brighter third quarter ahead of peak shopping season at the end of the year. But that is only relative to a near 14% drop in Q2 revenue year-on-year. China remains front and center for investors. U.S.-China trade tensions appear to be intensifying by the day - the latest flare up coming over Beijing's restrictions on exports of some metals - not the best backdrop for Yellen's visit on Thursday. U.S. officials says they expect \\\"candid\\\" discussions, and Washington has said it \\\"firmly\\\" opposes the new export controls on gallium and germanium, which go into producing semiconductors and other electronics. However well - or otherwise - Yellen's visit goes, there will be no quick fix. Former Vice Commerce Minister Wei Jianguo said the controls are \\\"just a start\\\". In Malaysia, meanwhile, the central bank on Thursday is expected to leave key rates unchanged at 3.00% and keep them there for the rest of the year, putting it in line with regional peers in India, South Korea, Indonesia and New Zealand who have already ended their tightening cycles. Headline inflation eased to a one-year low of 2.8% in May, but core inflation moderated only a bit to 3.5%, suggesting Bank Negara Malaysia (BNM) will hold its key rate higher for longer. The central bank delivered a surprise hike in May. Last week, it said it would intervene in the foreign exchange market to stabilize the ringgit to counter what it said were \\\"excessive\\\" recent losses. The ringgit was one of Asia's worst-performing currencies in the first half of the year, losing almost 6% of its value against the dollar. Here are key developments that could provide more direction to markets on Thursday: - U.S. Treasury Secretary Janet Yellen visits China - Australia trade (May) - Taiwan inflation (June) Malaysian interest rates https://tmsnrt.rs/3XBEzYx Asian FX vs U.S. dollar this year https://tmsnrt.rs/3NYLzvp (By Jamie McGeever; Editing by Lisa Shumaker) ((jamie.mcgeever@thomsonreuters.com; Reuters Messaging: jamie.mcgeever.thomsonreuters.com@reuters.net, Twitter: @ReutersJamie)) The views and opinions expressed her\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.023703, "explanation": "The actual 21-day forward return for XLRE starting 2023-07-06 was -2.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.023703, "horizon_days": 21, "hist_return": 0.033713, "annualized_vol": 0.172657, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231017_0897", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-10-17", "context_summary": "IWM over past 60 days: cumulative return -10.8%, annualized vol 15.0%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=188.61, end=168.19, cumulative_return=-10.8%, annualized_volatility=15.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.38, 't10y3m_spread': -0.9, 'breakeven_10y': 2.38, 'hy_oas': 4.27, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 17.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-16] [\"US STOCKS-Wall St jumps 1% to kick-start earnings and data-heavy week, megacaps rise By Ankika Biswas and Shashwat Chauhan Oct 16 (Reuters) - Wall Street's main indexes jumped more than 1% on Monday as megacaps rose to kick-start a week packed with corporate earnings and economic data, while investors also monitored the Israel-Hamas conflict. The Dow touched a near four-week high and was on course for its best day in more than two months, while the S&P 500 and the Nasdaq were headed for their best days in nearly two weeks. Megacaps Microsoft MSFT.O, Meta Platforms META.O, Alphabet GOOGL.O and Amazon.com AMZN.O rose between 1% and 2%. Consumer discretionary .SPLRCD and materials .SPLRCM led the gains across major S&P 500 sectors, while utilities .SPLRCU and energy stocks .SPNY lagged behind. \\\"There's a little bit of risk-on sentiment coming from a pretty solid start to their earnings season,\\\" said Ross Mayfield, investment strategy analyst at Baird. \\\"It says that what the economic data is also saying, which is that the economy is stronger than we were giving it credit for at the year's start, certainly not recessionary.\\\" Results from large banks Goldman Sachs GS.N, Bank of America BAC.N, Morgan Stanley MS.N, pharmaceutical giant Johnson & Johnson JNJ.N, EV maker Tesla TSLA.O and video-streaming pioneer Netflix NFLX.O are due this week. Third-quarter earnings for S&P 500 companies are estimated to grow 2.2% year-on-year, LSEG data showed on Friday. Long-dated Treasury yields rose amid increased U.S. government debt issuance while a possible Israeli ground offensive in Gaza has led to uncertainty in the bond market. Investors also await economic data including retail sales for September and the Philly Fed Business Index for October later this week. Latest data showed the NY Fed's \\\"Empire State\\\" index, a gauge of manufacturing activity in New York State, fell to -4.60 in October, against expectations of a drop to -7. The Dow Jones Transport Average index .DJT, seen as an indicator of economic prosperity, was on track for its best day in nearly three months. Investors are focused on Federal Reserve Chair Jerome Powell's comments on Thursday, before Fed officials enter a blackout period starting Oct. 21 ahead of their policy meeting. Philadelphia Fed President Patrick Harker reiterated his view from Friday that the U.S. central bank was likely done with its rate-hike cycle. Among stocks, Apple AAPL.O bucked the trend among its growth peers, dipping 0.1% on a report the company's iPhones were off to a disappointing start in China. Lululemon AthleticaLULU.O added 9.6% as the sportswear apparel maker is set to join the S&P 500 index this week, replacing Activision Blizzard ATVI.O. ModernaMRNA.O reaffirmed its forecast of $6 billion to $8 billion in COVID vaccine sales for the year. The company's shares fell 5.0%. Charles SchwabSCHW.N jumped 4.8% as the brokerage posted a smaller-than-expected drop in quarterly profit. Advancing issues outnumbered \n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.021835, "explanation": "The actual 21-day forward return for IWM starting 2023-10-17 was +2.18%, which classifies as 'positive'.", "metadata": {"future_return": 0.021835, "horizon_days": 21, "hist_return": -0.108279, "annualized_vol": 0.150037, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241106_0899", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2024-11-06", "context_summary": "STIP over past 60 days: cumulative return +0.8%, annualized vol 1.8%. Market regime: sideways.", "question": "Asset: STIP\nHistorical prices (past 60 trading days): start=95.11, end=95.90, cumulative_return=+0.8%, annualized_volatility=1.8%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.07, 't10y3m_spread': -0.38, 'breakeven_10y': 2.27, 'hy_oas': 2.86, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 20.489999771118164}\nMarket regime: sideways\n\nPredict whether the return of STIP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.005356, "explanation": "The actual 21-day forward return for STIP starting 2024-11-06 was +0.54%, which classifies as 'flat'.", "metadata": {"future_return": 0.005356, "horizon_days": 21, "hist_return": 0.008296, "annualized_vol": 0.01827, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240506_0901", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-05-06", "context_summary": "EEM over past 60 days: cumulative return +7.8%, annualized vol 13.6%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=37.58, end=40.50, cumulative_return=+7.8%, annualized_volatility=13.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.31, 't10y3m_spread': -0.95, 'breakeven_10y': 2.35, 'hy_oas': 3.08, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 13.489999771118164}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 2023-02-01 2024-01-31 0000104169 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0000104169 wmt:SamsClubMember 2023-01-31 0000104169 wmt:WalmartUSMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartInternationalMember 2023-02-01 2024-01-31 0000104169 wmt:SamsClubMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartUSMember 2024-01-31 0000104169 wmt:WalmartInternationalMember 2024-01-31 0000104169 wmt:SamsClubMember 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2023-02-01 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2022-02-01 2023-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nPredict whether the return of EEM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.004705, "explanation": "The actual 21-day forward return for EEM starting 2024-05-06 was -0.47%, which classifies as 'flat'.", "metadata": {"future_return": -0.004705, "horizon_days": 21, "hist_return": 0.077645, "annualized_vol": 0.13598, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20231018_0903", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-10-18", "context_summary": "VEA over past 60 days: cumulative return -7.2%, annualized vol 12.5%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=43.38, end=40.23, cumulative_return=-7.2%, annualized_volatility=12.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.36, 't10y3m_spread': -0.79, 'breakeven_10y': 2.41, 'hy_oas': 4.25, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 17.8799991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-17] [\"Dow Movers: INTC, BA In early trading on Tuesday, shares of Boeing topped the list of the day's best performing Dow Jones Industrial Average components, trading up 1.4%. Year to date, Boeing has lost about 1.6% of its value. And the worst performing Dow component thus far on the day is Intel, trading down 3.4%. Intel is showing a gain of 33.7% looking at the year to date performance. Two other components making moves today are Apple, trading down 2.0%, and Chevron, trading up 0.9% on the day. VIDEO: Dow Movers: INTC, BA The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The \\\"Magnificent Seven\\\" Have Made the S&P 500 More Concentrated Than Ever. Historically, That's Bad News for Stocks. When examined over multidecade periods, Wall Street's three major stock indexes -- the Dow Jones Industrial Average (DJINDICES: ^DJI), S&P 500 (SNPINDEX: ^GSPC), and Nasdaq Composite (NASDAQINDEX: ^IXIC) -- are undeniable moneymakers. But when explored over shorter spans, the performance of these indexes becomes unpredictable. Since this decade began, the major stock indexes have teetered between bull and bear markets on a number of occasions. While 2023 has been a relatively good year for the benchmark S&P 500 and growth stock-fueled Nasdaq Composite, a number of potential warning flags have emerged. Perhaps none is waving more frantically than the steadily increasing concentration of the S&P 500. Image source: Getty Images. The Magnificent Seven are responsible for nearly all the S&P 500's gains in 2023 The S&P 500 is widely viewed as the best benchmark of Wall Street's \\\"health.\\\" It's a market cap-weighted index comprised of 500 generally profitable, time-tested companies, a few of which have multiple classes of shares. All told, the S&P 500 has 503 components, with representation from all sectors and most industries. You'd think that a 500-company index would be fairly diverse and act as an accurate barometer for Wall Street, but this simply isn't the case, thanks to the rise of the Magnificent Seven. In order of largest to smallest market cap, as of Oct. 13, the Magnificent Seven stocks are: Apple (NASDAQ: AAPL) Microsoft (NASDAQ: MSFT) Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG) Amazon (NASDAQ: AMZN) Nvidia (NASDAQ: NVDA) Meta Platforms (NASDAQ: META) Tesla (NASDAQ: TSLA) The Magnificent Seven bring two attributes to the table that make them irresistible to many investors. First, they're industry leaders with relatively sustained moats and/or competitive edges: Apple accounts for a little over half of all U.S. smartphone market share and has the most robust capital-return program among publicly traded companies in the U.S. Microsoft is enjoying a blend of the old with the new. Its legacy Windows operating system still dominates on desktops, while its cloud infrastructure service, Azure, ranks second inglobal marketshare. Alphabet's Google has tallied at least 90% of worldwid\n\nPredict whether the return of VEA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.047308, "explanation": "The actual 21-day forward return for VEA starting 2023-10-18 was +4.73%, which classifies as 'positive'.", "metadata": {"future_return": 0.047308, "horizon_days": 21, "hist_return": -0.072436, "annualized_vol": 0.125416, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20241001_0905", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-10-01", "context_summary": "ICSH over past 60 days: cumulative return +0.9%, annualized vol 0.5%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=46.76, end=47.20, cumulative_return=+0.9%, annualized_volatility=0.5%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.15, 't10y3m_spread': -0.92, 'breakeven_10y': 2.18, 'hy_oas': 3.03, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.08, 'vix': 16.729999542236328}\nMarket regime: sideways\n\nPredict whether the return of ICSH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.001781, "explanation": "The actual 21-day forward return for ICSH starting 2024-10-01 was +0.18%, which classifies as 'flat'.", "metadata": {"future_return": 0.001781, "horizon_days": 21, "hist_return": 0.00939, "annualized_vol": 0.004777, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230529_0906", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-05-29", "context_summary": "VTI over past 60 days: cumulative return +2.8%, annualized vol 15.4%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=194.74, end=200.12, cumulative_return=+2.8%, annualized_volatility=15.4%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 303.334, 'unemployment': 3.6, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.74, 't10y3m_spread': -1.54, 'breakeven_10y': 2.23, 'hy_oas': 4.53, 'ig_oas': 1.41, 'ted_spread': 0.09, 'mortgage_30y': 6.57, 'vix': 17.950000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-26] [\"Alphabet CEO Sundar Pichai Commits to \\\"AI Pact\\\": What Does This Really Mean? The world of artificial intelligence (AI) is moving at a breakneck speed, and top corporate and political leaders are trying to safely guide its evolution. Alphabet (NASDAQ: GOOG) (NASDAQ: GOOGL) CEO Sundar Pichai met with European Commissioner for the internal market Thierry Breton on Wednesday to discuss the progression of AI and map out possible actions to help ensure the emerging technology doesn't get out of hand. In the meeting, Pichai promised that his company would join an \\\"AI pact\\\" and collaborate with other players in the artificial intelligence space on a volunteer basis to shape and abide by guidelines for tech development. But while there's seemingly a lot to like about the prospect of guardrails being put on AI, it's not clear that voluntary pacts or even strict laws will be able to address many of the potential problems that could arise. Could an AI pact help stave off potential disasters? While detailed specifics of what rules and guidelines members of an AI pact would be adhering to haven't been made available, Pichai's discussion with other members of the European Commission suggest that privacy standards and fighting misinformation could be key focuses. The rapid progression for artificial intelligence tech over the last year is unprecedented, and continued advances could be unwieldy. Because legislative bodies can be slow to act and laws vary between territories, it could be important for technology leaders to attempt to establish some kind of presiding framework for artificial intelligence initiatives. Taking a proactive approach to the problems and questions raised by incredible leaps forward for artificial intelligence could help minimize the possibility of disastrous outcomes stemming from the tech. The AI pact mentioned by Pichai at the meeting with Breton seems to be a step in this direction. But there's a risk that rules surrounding AI might not amount to much. For one, it's possible that voluntary AI guidelines and restrictions will be followed very loosely or only in the most nominal senses. It's also possible that those who don't abide by rules for the artificial intelligence project, whether self-imposed or through regulations, could actually gain significant competitive advantages. Controlling AI could be incredibly difficult The European Parliament is currently finalizing a new set of rules and restrictions that will govern AI technologies. The EU AI Act isn't officially law yet, but it's seemingly headed in that direction and could be a landmark response that plays a big role in the tech's evolution in Europe. But it might not be enough, and it may have unintended consequences. Developing ways to work around restrictions could be incentivized by the proposed regulations, and the speed at which AI tech has been progressing will make it difficult for regulators to keep up. Additionally, there are already signs that influential player\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.050002, "explanation": "The actual 21-day forward return for VTI starting 2023-05-29 was +5.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.050002, "horizon_days": 21, "hist_return": 0.027648, "annualized_vol": 0.153604, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240627_0907", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-06-27", "context_summary": "SGOV over past 60 days: cumulative return +0.8%, annualized vol 0.2%. Market regime: bull.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=92.26, end=93.03, cumulative_return=+0.8%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.39, 't10y3m_spread': -1.18, 'breakeven_10y': 2.26, 'hy_oas': 3.18, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 12.550000190734863}\nMarket regime: bull\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003181, "explanation": "The actual 21-day forward return for SGOV starting 2024-06-27 was +0.32%, which classifies as 'flat'.", "metadata": {"future_return": 0.003181, "horizon_days": 21, "hist_return": 0.008373, "annualized_vol": 0.002467, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20230308_0909", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-03-08", "context_summary": "VTI over past 60 days: cumulative return +1.4%, annualized vol 17.3%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=188.84, end=191.58, cumulative_return=+1.4%, annualized_volatility=17.3%\nMacro context: {'fed_funds_rate': 4.57, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.91, 't10y3m_spread': -1.07, 'breakeven_10y': 2.38, 'hy_oas': 3.98, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 19.59000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-07] [\"Better Ad Tech Stock: The Trade Desk vs. Magnite The Trade Desk (NASDAQ: TTD) and Magnite (NASDAQ: MGNI) are both independent ad tech companies that operate in the shadows of diversified advertising giants like Alphabet's (NASDAQ: GOOG) (NASDAQ: GOOGL) Google and Meta Platforms (NASDAQ: META). Unlike those larger advertising companies, The Trade Desk and Magnite don't lock publishers and advertisers into their walled gardens. Instead, both companies make it easier to purchase ads on desktop, mobile, and connected TV (CTV) platforms across the \\\"open\\\" internet, which doesn't operate under those big tech umbrellas. But over the past 12 months, The Trade Desk's stock declined 28% as Magnite's stock dropped 17%. Image source: Getty Images. Both stocks lost their luster as rising rates and other macro headwinds caused companies to curb their spending on ads. Cautious investors also abandoned higher-growth tech stocks in favor of cheaper value plays. But could either of these fallen ad tech stocks bounce back this year? The differences between The Trade Desk and Magnite The Trade Desk and Magnite are both independent platforms, but they sit at opposite ends of the advertising supply chain. The Trade Desk is a demand-side platform (DSP), which allows advertisers to bid on ad space across a wide range of platforms, while Magnite operates a sell-side platform (SSP), which helps publishers sell their own ad inventories. These two companies are the largest independent players in their respective markets. DSPs typically work in tandem with SSPs to sell digital ads. Google and Meta bundle together DSPs, SSPs, and other advertising services, but they're not independent platforms. However, The Trade Desk recently launched OpenPath, a new feature that bypasses SSPs like Magnite to connect publishers to advertisers. That feature could make it a more diversified advertising company like Google or Meta, but it could also hurt Magnite and other SSPs. The Trade Desk hasn't made any acquisitions since it bought the assets of the ad tech company AdBrain in 2017. Meanwhile, Magnite was created by the merger of two smaller companies, The Rubicon Project and Telaria, in 2020. It then bought the video advertising companies SpotX and SpringServe, as well as the publisher monetization firm Carbon. Therefore, it's fairly easy for investors to track The Trade Desk's growth. Magnite's growth rates need to be reviewed more carefully due to its inorganic growth rates and ex-TAC (excluding traffic acquisition costs) revenues -- which it started using as its core growth metric after its purchase of SpotX in 2021. Which company is growing faster? The Trade Desk's revenue rose 26% in 2020, even as the pandemic throttled the market's demand for digital ads. But in 2021, its revenue increased 43% as the advertising market recovered. In 2022, its revenue rose 32% to $1.58 billion, even as inflation rattled the markets and Apple's (NASDAQ: AAPL) iOS update prevented many advertisers -\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.017392, "explanation": "The actual 21-day forward return for VTI starting 2023-03-08 was +1.74%, which classifies as 'positive'.", "metadata": {"future_return": 0.017392, "horizon_days": 21, "hist_return": 0.014496, "annualized_vol": 0.173228, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230125_0911", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2023-01-25", "context_summary": "IAU over past 60 days: cumulative return +17.4%, annualized vol 15.2%. Market regime: sideways.", "question": "Asset: IAU\nHistorical prices (past 60 trading days): start=31.29, end=36.75, cumulative_return=+17.4%, annualized_volatility=15.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.66, 't10y3m_spread': -1.26, 'breakeven_10y': 2.27, 'hy_oas': 4.33, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.15, 'vix': 19.200000762939453}\nMarket regime: sideways\n\nPredict whether the return of IAU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.063887, "explanation": "The actual 21-day forward return for IAU starting 2023-01-25 was -6.39%, which classifies as 'negative'.", "metadata": {"future_return": -0.063887, "horizon_days": 21, "hist_return": 0.174497, "annualized_vol": 0.151642, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240524_0912", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-05-24", "context_summary": "LINK-USD over past 60 days: cumulative return -14.2%, annualized vol 64.9%. Market regime: bull.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=19.36, end=16.61, cumulative_return=-14.2%, annualized_volatility=64.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.44, 't10y3m_spread': -0.99, 'breakeven_10y': 2.3, 'hy_oas': 3.1, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 12.770000457763672}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.145308, "explanation": "The actual 21-day forward return for LINK-USD starting 2024-05-24 was -14.53%, which classifies as 'negative'.", "metadata": {"future_return": -0.145308, "horizon_days": 21, "hist_return": -0.14228, "annualized_vol": 0.649111, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240729_0914", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PPLT"], "decision_date": "2024-07-29", "context_summary": "PPLT over past 60 days: cumulative return -4.4%, annualized vol 26.2%. Market regime: sideways.", "question": "Asset: PPLT\nHistorical prices (past 60 trading days): start=90.00, end=86.01, cumulative_return=-4.4%, annualized_volatility=26.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.16, 't10y3m_spread': -1.18, 'breakeven_10y': 2.27, 'hy_oas': 3.1, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 16.389999389648438}\nMarket regime: sideways\n\nPredict whether the return of PPLT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.01008, "explanation": "The actual 21-day forward return for PPLT starting 2024-07-29 was +1.01%, which classifies as 'positive'.", "metadata": {"future_return": 0.01008, "horizon_days": 21, "hist_return": -0.044333, "annualized_vol": 0.261681, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20231004_0916", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-10-04", "context_summary": "MTUM over past 60 days: cumulative return -3.7%, annualized vol 13.0%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=139.98, end=134.77, cumulative_return=-3.7%, annualized_volatility=13.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.34, 't10y3m_spread': -0.81, 'breakeven_10y': 2.36, 'hy_oas': 4.26, 'ig_oas': 1.28, 'ted_spread': 0.09, 'mortgage_30y': 7.31, 'vix': 19.780000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-03] [\"Russian court rejects Apple appeal against abuse of dominant market position - RIA Oct 3 (Reuters) - A Russian court rejected Apple's AAPL.O appeal against the alleged abuse of its dominant market position in terms of in-app payments, for which it was fined 1.2 billion roubles ($12.1 million) in January, the RIA news agency reported on Tuesday. Apple did not immediately respond to an emailed request for comment. Russia's federal anti-monopoly service (FAS) fined Apple in January over what it said was the U.S. company's abuse of its dominant market position. In a statement, the regulator said it had previously found that Apple forced Russian developers to use Apple's payment services with the iOS App Store, in violation of Russia's competition rules. The FAS's decision entered legal force in May after it was approved by a Moscow court, RIA reported. Apple was appealing both the decision and the fine. The rouble has depreciated sharply since January. In dollar terms, the fine has decreased by more than $5 million since then. ($1 = 99.1990 roubles) (Reporting by Reuters; Editing by Mark Trevelyan) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"This Is One of the Top-Rated and Most-Upgraded Stocks Another week has passed with shares of Meta Platforms (NASDAQ: META) outperforming the overall market, closing the prior week up 0.38% while the overall market was down almost 1%. META recently made headlines after the company hosted its annual Connect product conference. It has continued to buck the overall market trend and remain firmly above its critical support. The company also finds itself on the Top-Rated Stocks list, a list of 100 companies that have received the highest average rating among equities research analysts in the last twelve months, and is one of the Most-Upgraded Stocks, a list of companies that have been upgraded by Wall Street analysts most frequently during the previous 90 days. So, as the fourth quarter begins, could META be a top pick and smart investment choice? Let's take a closer look at the news and technical setup. META Announces Product Updates and Launch During Connect Meta Connect 2023 spotlighted the Meta Quest 3, which received significant attention in the tech community. This new mixed-reality device aims to compete with Apple's Vision Pro headset, capitalizing on Apple's reported production delays. Alongside this announcement, Meta unveiled a range of innovations, including the well-received Ray-Ban Meta smart glasses, the Emu text-to-image model, Meta AI for chatbots, and AI Studio for custom chatbot development. These developments underscore Meta's commitment to making metaverse technology affordable and accessible. Mark Zuckerberg, Meta's CEO, emphasized this aspect during his keynote address, highlighting the importance of inclusivity as the company works toward its metaverse ambitions. Analysts are Bullish on META A host of \n\nPredict whether the return of MTUM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.024952, "explanation": "The actual 21-day forward return for MTUM starting 2023-10-04 was +2.50%, which classifies as 'positive'.", "metadata": {"future_return": 0.024952, "horizon_days": 21, "hist_return": -0.037263, "annualized_vol": 0.129896, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230901_0917", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-09-01", "context_summary": "ADA-USD over past 60 days: cumulative return -13.8%, annualized vol 59.5%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.30, end=0.26, cumulative_return=-13.8%, annualized_volatility=59.5%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.76, 't10y3m_spread': -1.47, 'breakeven_10y': 2.24, 'hy_oas': 3.85, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 13.56999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-31] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.040218, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-09-01 was -4.02%, which classifies as 'negative'.", "metadata": {"future_return": -0.040218, "horizon_days": 21, "hist_return": -0.138159, "annualized_vol": 0.594539, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231123_0919", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-11-23", "context_summary": "ADA-USD over past 60 days: cumulative return +56.6%, annualized vol 42.9%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.24, end=0.38, cumulative_return=+56.6%, annualized_volatility=42.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.47, 't10y3m_spread': -1.12, 'breakeven_10y': 2.26, 'hy_oas': 3.9, 'ig_oas': 1.15, 'ted_spread': 0.09, 'mortgage_30y': 7.29, 'vix': 12.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-22] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.664131, "explanation": "The actual 21-day forward return for ADA-USD starting 2023-11-23 was +66.41%, which classifies as 'positive'.", "metadata": {"future_return": 0.664131, "horizon_days": 21, "hist_return": 0.566334, "annualized_vol": 0.428924, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240517_0921", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-05-17", "context_summary": "EFA over past 60 days: cumulative return +5.3%, annualized vol 10.8%. Market regime: bull.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=72.37, end=76.17, cumulative_return=+5.3%, annualized_volatility=10.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.4, 't10y3m_spread': -1.07, 'breakeven_10y': 2.31, 'hy_oas': 3.08, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.02, 'vix': 12.420000076293944}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.026167, "explanation": "The actual 21-day forward return for EFA starting 2024-05-17 was -2.62%, which classifies as 'negative'.", "metadata": {"future_return": -0.026167, "horizon_days": 21, "hist_return": 0.052523, "annualized_vol": 0.107537, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230705_0922", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-07-05", "context_summary": "XLK over past 60 days: cumulative return +16.6%, annualized vol 18.7%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=73.01, end=85.14, cumulative_return=+16.6%, annualized_volatility=18.7%\nMacro context: {'fed_funds_rate': 5.08, 'cpi_yoy': 304.609, 'unemployment': 3.5, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.91, 't10y3m_spread': -1.58, 'breakeven_10y': 2.25, 'hy_oas': 3.99, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 6.71, 'vix': 13.56999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-03] [\"Unity Software Stock Skyrockets 46% in June as AI Buzz Takes Over What happened Shares of Unity Software (NYSE: U) skyrocketed 46.1% in June, according to data provided by S&P Global Market Intelligence. The month started off with fireworks from Apple that are relevant to Unity shareholders. And it ended with a bang related to artificial intelligence (AI), Wall Street's favorite subject at the moment. So what To give this story some context, I want to point out that the market had lost a lot of confidence in Unity Software stock. When they first went public, shares regularly traded above a price-to-sales (P/S) ratio of 30. By comparison, they traded below a P/S of 7 at the start of June. That's still high in absolute terms. But in relative terms, this valuation was more than 80% below where it had routinely traded. Unity's own revenue growth was ample reason for the market's pessimism. And even though its growth has since rebounded, as the chart below shows, this is largely due to an acquisition. Its organic growth is still challenged. U Revenue (quarterly YoY growth) data by YCharts; YoY = year over year. But on June 5, Apple announced its upcoming Vision Pro headset, and this has reinvigorated investors' excitement for Unity's potential. Apple is looking for apps to be built for the headset between now and its launch in 2024. And for this, the company has partnered with Unity. Developers use Unity for building top-notch video games. And Apple has created a software development kit that will allow Unity users to modify their creations for the Vision Pro. Then on June 27, Unity announced a marketplace for AI applications. The marketplace has 10 apps available at launch that can be used in the video game space. And when the company announced this new focus on AI, the market celebrated by pushing the stock higher. So the stock started June with low expectations, but Apple and AI have investors rethinking the long-term potential. Now what When it comes to the AI space, I'm inclined to disregard most news as overhyped clickbait. But with Unity Software stock, I do believe that AI -- specifically generative AI -- could play an important role for the business. Many investors like Unity's potential in virtual reality and the metaverse. Its software creates realistic 3D images, and realism is needed to make these experiences something that consumers actually want. When building digital worlds, the problem is how big these need to be -- it's labor intensive for developers. And the workload is probably too much to physically handle at scale, which is where generative AI can help. Much of what Unity is doing involves generative AI, which I believe is just what the space needs. So as virtual reality and the metaverse grow -- perhaps thanks to Apple's Vision Pro headset -- the use cases for Unity Software could open up as well. That's good reason for optimism for a stock that's still down almost 80% from its all-time high. 10 stocks we like better than Unit\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00638, "explanation": "The actual 21-day forward return for XLK starting 2023-07-05 was +0.64%, which classifies as 'flat'.", "metadata": {"future_return": 0.00638, "horizon_days": 21, "hist_return": 0.166253, "annualized_vol": 0.187066, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231225_0923", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2023-12-25", "context_summary": "VNQ over past 60 days: cumulative return +17.4%, annualized vol 21.6%. Market regime: sideways.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=68.44, end=80.31, cumulative_return=+17.4%, annualized_volatility=21.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.41, 't10y3m_spread': -1.54, 'breakeven_10y': 2.19, 'hy_oas': 3.39, 'ig_oas': 1.07, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 13.029999732971191}\nMarket regime: sideways\n\nPredict whether the return of VNQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.035989, "explanation": "The actual 21-day forward return for VNQ starting 2023-12-25 was -3.60%, which classifies as 'negative'.", "metadata": {"future_return": -0.035989, "horizon_days": 21, "hist_return": 0.173561, "annualized_vol": 0.215833, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240117_0925", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-01-17", "context_summary": "XLK over past 60 days: cumulative return +15.8%, annualized vol 15.8%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=82.02, end=94.99, cumulative_return=+15.8%, annualized_volatility=15.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.15, 't10y3m_spread': -1.38, 'breakeven_10y': 2.3, 'hy_oas': 3.58, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.66, 'vix': 13.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.066121, "explanation": "The actual 21-day forward return for XLK starting 2024-01-17 was +6.61%, which classifies as 'positive'.", "metadata": {"future_return": 0.066121, "horizon_days": 21, "hist_return": 0.158223, "annualized_vol": 0.158167, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240529_0927", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-05-29", "context_summary": "XLV over past 60 days: cumulative return -2.0%, annualized vol 10.2%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=140.77, end=137.94, cumulative_return=-2.0%, annualized_volatility=10.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.4, 't10y3m_spread': -0.92, 'breakeven_10y': 2.34, 'hy_oas': 3.09, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 12.920000076293944}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.033633, "explanation": "The actual 21-day forward return for XLV starting 2024-05-29 was +3.36%, which classifies as 'positive'.", "metadata": {"future_return": 0.033633, "horizon_days": 21, "hist_return": -0.020085, "annualized_vol": 0.101905, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230327_0929", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-03-27", "context_summary": "XLU over past 60 days: cumulative return -6.4%, annualized vol 19.3%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=32.00, end=29.96, cumulative_return=-6.4%, annualized_volatility=19.3%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.38, 't10y3m_spread': -1.36, 'breakeven_10y': 2.22, 'hy_oas': 5.22, 'ig_oas': 1.54, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 21.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-24] [\"Notable Friday Option Activity: ENPH, AAPL, COST Among the underlying components of the S&P 500 index, we saw noteworthy options trading volume today in Enphase Energy Inc. (Symbol: ENPH), where a total of 37,713 contracts have traded so far, representing approximately 3.8 million underlying shares. That amounts to about 102.2% of ENPH's average daily trading volume over the past month of 3.7 million shares. Especially high volume was seen for the $195 strike put option expiring March 24, 2023, with 2,408 contracts trading so far today, representing approximately 240,800 underlying shares of ENPH. Below is a chart showing ENPH's trailing twelve month trading history, with the $195 strike highlighted in orange: Apple Inc (Symbol: AAPL) saw options trading volume of 655,112 contracts, representing approximately 65.5 million underlying shares or approximately 97.5% of AAPL's average daily trading volume over the past month, of 67.2 million shares. Especially high volume was seen for the $160 strike call option expiring March 24, 2023, with 74,927 contracts trading so far today, representing approximately 7.5 million underlying shares of AAPL. Below is a chart showing AAPL's trailing twelve month trading history, with the $160 strike highlighted in orange: And Costco Wholesale Corp (Symbol: COST) saw options trading volume of 19,640 contracts, representing approximately 2.0 million underlying shares or approximately 89% of COST's average daily trading volume over the past month, of 2.2 million shares. Especially high volume was seen for the $495 strike call option expiring March 24, 2023, with 1,539 contracts trading so far today, representing approximately 153,900 underlying shares of COST. Below is a chart showing COST's trailing twelve month trading history, with the $495 strike highlighted in orange: For the various different available expirations for ENPH options, AAPL options, or COST options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb Also see: \\u0095 ONCS Insider Buying \\u0095 MDP Stock Predictions \\u0095 WTI Stock Predictions The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Wall St Week Ahead-Strength in megacap stocks masks broader U.S. market woes By Lewis Krauskopf NEW YORK, March 24 (Reuters) - Investors are relying on an old strategy to navigate the current tumult in asset prices: buying shares of the massive U.S. companies that led markets higher for years. Shares of the top five companies by market value -- Apple AAPL.O, Microsoft MSFT.O, Alphabet GOOGL.O, Amazon AMZN.O and Nvidia NVDA.O -- have gained between 4.5% and 12% since March 8, when troubles at Silicon Valley Bank set off banking system worries. In that period, the S&P 500 has fallen 0.5%. Megagaps are attracting bets because of strong balance sheets, robust profit margins and business models expected to hold up better if recession hits, \n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.037859, "explanation": "The actual 21-day forward return for XLU starting 2023-03-27 was +3.79%, which classifies as 'positive'.", "metadata": {"future_return": 0.037859, "horizon_days": 21, "hist_return": -0.063617, "annualized_vol": 0.192963, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20230830_0931", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-08-30", "context_summary": "ETH-USD over past 60 days: cumulative return -10.1%, annualized vol 28.1%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1924.57, end=1729.73, cumulative_return=-10.1%, annualized_volatility=28.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.75, 't10y3m_spread': -1.44, 'breakeven_10y': 2.29, 'hy_oas': 3.87, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.23, 'vix': 14.449999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-29] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.048221, "explanation": "The actual 21-day forward return for ETH-USD starting 2023-08-30 was -4.82%, which classifies as 'negative'.", "metadata": {"future_return": -0.048221, "horizon_days": 21, "hist_return": -0.101239, "annualized_vol": 0.281136, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230112_0933", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-01-12", "context_summary": "XLB over past 60 days: cumulative return +19.5%, annualized vol 23.6%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=32.59, end=38.95, cumulative_return=+19.5%, annualized_volatility=23.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.66, 't10y3m_spread': -1.18, 'breakeven_10y': 2.23, 'hy_oas': 4.3, 'ig_oas': 1.34, 'ted_spread': 0.09, 'mortgage_30y': 6.48, 'vix': 21.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-11] [\"Is Apple a Screaming Buy Right Now? For much of 2022, Apple (NASDAQ: AAPL) resisted the market sell-off, but eventually, it succumbed. The tech giant finished the year down 27%, ahead of the Nasdaq but behind the S&P 500. Despite its retreat, the iPhone maker delivered a better performance than most of its big tech peers, reporting revenue growth of 8% for the quarter and the year, even as it faced stiff headwinds from a stronger dollar. Earnings per share growth was slower, up in the fiscal fourth quarter from $1.24 to $1.29, as the company faced inflationary pressure in areas like wages and logistics. However, after the sell-off, Apple stock looks surprisingly well priced. It currently trades at a price-to-earnings ratio of 21, the cheapest it has been since the pandemic started, only slightly more expensive than that of the S&P 500 at 20.2. Is Apple a screaming buy? Let's take a look at the debate. Image source: Getty Images. Why Apple stock has fallen There isn't anything particularly alarming in Apple's recent results, but there are a number of reasons why the stock has tumbled over the last few months. First, the market is increasingly betting on a recession this year as the Federal Reserve continues to raise interest rates. As a seller of higher-end discretionary tech hardware, Apple is at risk of a recession, which would lead consumers to spend less on discretionary products. Even if they needed a new smartphone or computer, they could trade down to a cheaper Apple model or buy one from another company altogether. Second, Apple has faced a number of challenges in its manufacturing in China. The company said in November that its iPhone factory in Zhengzhou was operating at significantly limited capacity, meaning it expected shipments of its iPhone 14 Pro and Pro Max to be lower in the fiscal first quarter than originally anticipated. The company did say that demand for those phones remains strong. The COVID-19 lockdowns that caused those delays have since ended, so the problem should be temporary. However, Apple also announced plans to move more production out of China. Finally, the company's revenue approached $400 billion in fiscal 2022, and its growth is expected to be moderate. On such a large base of revenue, it will be difficult to put up 20% revenue growth. However, the valuation seems to reflect the dialed-down growth expectations. The good news With an earnings valuation on par with the S&P 500, Apple doesn't need to put up high growth numbers in order to justify its valuation. In fact, the company could easily grow earnings per share by double digits with just modest revenue and share buybacks. Apple has been committed to share buybacks, having reduced shares outstanding by more than 20% over the last five years. With the stock price down, it could get more aggressive with repurchases. The company's economic moat has also never looked as strong. Apple has gained market share on Android and now claims a majority of market share \n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.015009, "explanation": "The actual 21-day forward return for XLB starting 2023-01-12 was -1.50%, which classifies as 'negative'.", "metadata": {"future_return": -0.015009, "horizon_days": 21, "hist_return": 0.195013, "annualized_vol": 0.236171, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240611_0935", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-06-11", "context_summary": "XRP-USD over past 60 days: cumulative return -9.4%, annualized vol 46.8%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.55, end=0.50, cumulative_return=-9.4%, annualized_volatility=46.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.4, 't10y3m_spread': -1.05, 'breakeven_10y': 2.31, 'hy_oas': 3.15, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.99, 'vix': 12.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.008744, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-06-11 was +0.87%, which classifies as 'flat'.", "metadata": {"future_return": 0.008744, "horizon_days": 21, "hist_return": -0.094429, "annualized_vol": 0.468366, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240912_0937", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-09-12", "context_summary": "AVAX-USD over past 60 days: cumulative return -11.7%, annualized vol 74.9%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=26.37, end=23.30, cumulative_return=-11.7%, annualized_volatility=74.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.03, 't10y3m_spread': -1.45, 'breakeven_10y': 2.04, 'hy_oas': 3.44, 'ig_oas': 1.01, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 17.690000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.025993, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-09-12 was +2.60%, which classifies as 'positive'.", "metadata": {"future_return": 0.025993, "horizon_days": 21, "hist_return": -0.116515, "annualized_vol": 0.748562, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241126_0939", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-11-26", "context_summary": "XLRE over past 60 days: cumulative return +3.1%, annualized vol 14.8%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=41.18, end=42.45, cumulative_return=+3.1%, annualized_volatility=14.8%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.06, 't10y3m_spread': -0.35, 'breakeven_10y': 2.29, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.84, 'vix': 14.600000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 2024-01-28 0001045810 us-gaap:CommonStockMember 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us-gaap:USTreasurySecuritiesMember 2024-10-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2024-10-27 0001045810 us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-10-27 0001045810 us-gaap:CertificatesOfDepositMember 2024-10-27 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-10-27 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-29 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-07-29 2024-10-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2024-01-28 0001045810 us-gaap:USTreasurySecuritiesMember 2024-01-28 0001045810 us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-01-28 0001045810 us-gaap:CertificatesOfDepositMember 2024-01-28 0001045810 us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.087395, "explanation": "The actual 21-day forward return for XLRE starting 2024-11-26 was -8.74%, which classifies as 'negative'.", "metadata": {"future_return": -0.087395, "horizon_days": 21, "hist_return": 0.030772, "annualized_vol": 0.14759, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20241128_0941", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-11-28", "context_summary": "XRP-USD over past 60 days: cumulative return +129.4%, annualized vol 92.5%. Market regime: bull.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.64, end=1.47, cumulative_return=+129.4%, annualized_volatility=92.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.06, 't10y3m_spread': -0.35, 'breakeven_10y': 2.26, 'hy_oas': 2.69, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 14.100000381469728}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.459047, "explanation": "The actual 21-day forward return for XRP-USD starting 2024-11-28 was +45.90%, which classifies as 'positive'.", "metadata": {"future_return": 0.459047, "horizon_days": 21, "hist_return": 1.294289, "annualized_vol": 0.925201, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230103_0943", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-01-03", "context_summary": "LINK-USD over past 60 days: cumulative return -34.9%, annualized vol 85.9%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=8.74, end=5.69, cumulative_return=-34.9%, annualized_volatility=85.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.53, 't10y3m_spread': -0.54, 'breakeven_10y': 2.3, 'hy_oas': 4.81, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.42, 'vix': 21.670000076293945}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-02] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.184489, "explanation": "The actual 21-day forward return for LINK-USD starting 2023-01-03 was +18.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.184489, "horizon_days": 21, "hist_return": -0.349357, "annualized_vol": 0.859086, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230417_0945", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-04-17", "context_summary": "DOT-USD over past 60 days: cumulative return +7.9%, annualized vol 60.6%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=6.33, end=6.83, cumulative_return=+7.9%, annualized_volatility=60.6%\nMacro context: {'fed_funds_rate': 4.83, 'cpi_yoy': 302.845, 'unemployment': 3.4, 'gdp_growth_qoq': 22580.499, 't10y2y_spread': -0.56, 't10y3m_spread': -1.62, 'breakeven_10y': 2.3, 'hy_oas': 4.43, 'ig_oas': 1.39, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 17.06999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-16] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.197094, "explanation": "The actual 21-day forward return for DOT-USD starting 2023-04-17 was -19.71%, which classifies as 'negative'.", "metadata": {"future_return": -0.197094, "horizon_days": 21, "hist_return": 0.078813, "annualized_vol": 0.605713, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241219_0947", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-19", "context_summary": "SPY over past 60 days: cumulative return +2.8%, annualized vol 11.6%. Market regime: sideways.", "question": "Asset: SPY\nHistorical prices (past 60 trading days): start=560.00, end=575.96, cumulative_return=+2.8%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.15, 't10y3m_spread': 0.14, 'breakeven_10y': 2.32, 'hy_oas': 2.73, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 27.6200008392334}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 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The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of SPY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.023019, "explanation": "The actual 21-day forward return for SPY starting 2024-12-19 was +2.30%, which classifies as 'positive'.", "metadata": {"future_return": 0.023019, "horizon_days": 21, "hist_return": 0.028489, "annualized_vol": 0.115556, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240226_0949", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-02-26", "context_summary": "VLUE over past 60 days: cumulative return +10.5%, annualized vol 12.9%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=87.60, end=96.83, cumulative_return=+10.5%, annualized_volatility=12.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.41, 't10y3m_spread': -1.2, 'breakeven_10y': 2.3, 'hy_oas': 3.23, 'ig_oas': 0.95, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 13.75}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K BLK 2024-02-23] 10-K FY false --12-31 0001364742 http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-03 2023-03 2024-03 http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense P5Y 2028 - 03 1 1 1 1 1 1 1 one year 2024-01-31 2023-01-31 P0Y P0Y 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:InvestmentAdviceMember 2021-01-01 2021-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:CarryingReportedAmountFairValueDisclosureMember 2022-12-31 0001364742 srt:AsiaPacificMember 2023-01-01 2023-12-31 0001364742 blk:EquityProductMember us-gaap:InvestmentPerformanceMember 2021-01-01 2021-12-31 0001364742 us-gaap:TrademarksAndTradeNamesMember 2023-12-31 0001364742 blk:DeferredCompensationPlansMember us-gaap:SubsequentEventMember 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These amounts are aggregated on a legal entity basis and do not necessarily reflect where the customer resides or affiliated services are provided. (in millions) 2023     2022     2021   Revenue                 Americas $ 11,899     $ 11,931     $ 12,399   Europe   5,209       5,164       6,105   Asia-Pacific   751       778       870   Total revenue $ 17,859     $ 17,873     $ 19,374   See Note 16, Revenue , for further information on the Company’s sources of revenue. The following table illustrates long-lived assets that consist of goodwill and property and equipment at December 31, 2023 and 2022 by geographic region. These amounts are aggregated on a legal entity basis and do not necessarily reflect where the asset is physically located. (in millions) 2023     2022   Long-lived Assets           Americas $ 15,017     $ 14,945   Europe   1,521       1,329   Asia-Pacific   98       98   Total long-lived assets $ 16,636     $ 16,372   Americas is primarily comprised of the US, Latin America and Canada. Europe is primarily comprised of the UK, the Netherlands, Switzerland, France, Ireland and Luxembourg. Asia-Pacific is primarily comprised of Hong Kong, Australia, Japan and Singapore. 27 . Subsequent Events In January 2024, BlackRock announced that it had entered into a definitive agreement to acquire 100 % of the business and assets of Global Infrastructure Management LLC (referred to herein as Global Infrastructure Partners (“GIP”)), a leading independent infrastructure fund manager, for $ 3 billion in cash and approximately 12 million shares of BlackRock common stock. Approximately 30 % of the total consideration, all in stock, will be deferred and will be issued subject to the satisfaction of certain post-closing events. The Company intends to fund the cash consideration through $ 3 billion of additional debt. The Company believes the combination of GIP with BlackRock’s complementary infrastructure offerings will create a broad global infrastructure franchise with differentiated origination and asset management capabilities. The GIP Transaction is expected to close in the third quarter of 2024 subject to customary regulatory approvals and other closing conditions. On January 12, 2024 , the Company announced that the Board of Directors approved BlackRock’s quarterly dividend of $ 5.10 per share to be paid on March 22, 2024 to stockholders of record at the close of business on March 7, 2024 . The Company conducted a review for additional subsequent events and determined that no subsequent events had occurred that would require accrual or additional disclosures. F- 36\n\nPredict whether the return of VLUE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.0455, "explanation": "The actual 21-day forward return for VLUE starting 2024-02-26 was +4.55%, which classifies as 'positive'.", "metadata": {"future_return": 0.0455, "horizon_days": 21, "hist_return": 0.105323, "annualized_vol": 0.12913, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20231114_0951", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-11-14", "context_summary": "XLV over past 60 days: cumulative return -4.6%, annualized vol 11.3%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=127.68, end=121.81, cumulative_return=-4.6%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.148, 'unemployment': 3.7, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.39, 't10y3m_spread': -0.92, 'breakeven_10y': 2.31, 'hy_oas': 4.03, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 14.760000228881836}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-13] [\"Google's expert in US antitrust trial defends billions paid to device makers By Diane Bartz WASHINGTON, Nov 13 (Reuters) - The multi-billion dollar payments that Alphabet's GOOGL.O Google makes to Apple AAPL.O, wireless carriers and others are normal competitive behavior and not an abuse of monopoly, an expert called by Google testified on Monday in a blockbuster antitrust trial. In what is expected to be the last week of trial, Kevin Murphy, who teaches at the University of Chicago Booth School of Business, argued Apple and others played Google and Microsoft MSFT.O, which has the Bing search engine, off against each other in order to win big payments from Google. The government, which has filed four major antitrust lawsuits against three Big Tech companies since 2020, has accused Google of paying billions - $26.3 billion in 2021 - to ensure that its search is the default on smartphones and browsers and to keep its market share in the stratosphere. It alleges the payments are an abuse of monopoly. \\\"The payments that Google makes reflect that competition,\\\" he said. Further, Murphy argued that while Microsoft had virtually all the preinstalled browser defaults in early 2010s, its Bing search engine got just 15% of search queries. He said that there was \\\"some truth\\\" to the argument that changing defaults on devices might be complex for some but those same people often get around that difficulty by switching to a different browser or another workaround. Why is the US suing Google for antitrust violations? https://www.reuters.com/legal/why-is-us-suing-google-antitrust-violations-2023-09-11/ (Reporting by Diane Bartz Editing by Marguerita Choy) ((Diane.Bartz@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The 3 Best Robinhood Stocks for Beginning Investors InvestorPlace - Stock Market News, Stock Advice & Trading Tips Embarking on the Robinhood (NASDAQ:HOOD) investing journey unlocks the stock market\\u2019s secrets, especially when focusing on the best Robinhood stocks for beginning investors. For beginners, choosing the right stocks is crucial. This includes beginner-friendly stocks, low-risk options, and affordable choices in the realm of best Robinhood stocks for beginning investors. These elements are key to financial literacy for new investors, and understanding the best Robinhood stocks for beginning investors can be a significant first step. We aim to empower you with Robinhood trading tips and basic stock analysis skills. You\\u2019ll learn to build a diverse portfolio, balancing dividend and growth stocks. This approach is essential for long-term investment success. Our focus also includes tech stocks and value investing strategies, perfect for beginners. These categories offer a mix of innovation and intrinsic value. Using Robinhood, these strategies become more accessible, aiding in effective retirement planning. Safe stocks to\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.058267, "explanation": "The actual 21-day forward return for XLV starting 2023-11-14 was +5.83%, which classifies as 'positive'.", "metadata": {"future_return": 0.058267, "horizon_days": 21, "hist_return": -0.046002, "annualized_vol": 0.113016, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20231101_0952", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-11-01", "context_summary": "LINK-USD over past 60 days: cumulative return +90.6%, annualized vol 62.2%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=5.97, end=11.38, cumulative_return=+90.6%, annualized_volatility=62.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.19, 't10y3m_spread': -0.71, 'breakeven_10y': 2.42, 'hy_oas': 4.42, 'ig_oas': 1.32, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 18.13999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-31] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.224742, "explanation": "The actual 21-day forward return for LINK-USD starting 2023-11-01 was +22.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.224742, "horizon_days": 21, "hist_return": 0.906361, "annualized_vol": 0.621876, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240119_0954", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-01-19", "context_summary": "SGOV over past 60 days: cumulative return +0.9%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=90.13, end=90.93, cumulative_return=+0.9%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 309.698, 'unemployment': 3.7, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.2, 't10y3m_spread': -1.31, 'breakeven_10y': 2.34, 'hy_oas': 3.58, 'ig_oas': 1.01, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 14.130000114440918}\nMarket regime: sideways\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00307, "explanation": "The actual 21-day forward return for SGOV starting 2024-01-19 was +0.31%, which classifies as 'flat'.", "metadata": {"future_return": 0.00307, "horizon_days": 21, "hist_return": 0.008887, "annualized_vol": 0.002483, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240509_0956", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-05-09", "context_summary": "ACWI over past 60 days: cumulative return +5.7%, annualized vol 11.7%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=100.06, end=105.77, cumulative_return=+5.7%, annualized_volatility=11.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.36, 't10y3m_spread': -0.97, 'breakeven_10y': 2.31, 'hy_oas': 3.1, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 13.0}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.01763, "explanation": "The actual 21-day forward return for ACWI starting 2024-05-09 was +1.76%, which classifies as 'positive'.", "metadata": {"future_return": 0.01763, "horizon_days": 21, "hist_return": 0.057118, "annualized_vol": 0.11686, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230320_0958", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-03-20", "context_summary": "XLI over past 60 days: cumulative return -0.6%, annualized vol 17.5%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=92.61, end=92.06, cumulative_return=-0.6%, annualized_volatility=17.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.42, 't10y3m_spread': -1.13, 'breakeven_10y': 2.1, 'hy_oas': 5.17, 'ig_oas': 1.62, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 25.51000022888184}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2023-03-17] wmt-20230131 0000104169 2023 FY false P1Y P5Y 0000104169 2022-02-01 2023-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2022-02-01 2023-01-31 0000104169 wmt:A2.550NotesDue2026Member 2022-02-01 2023-01-31 0000104169 2022-07-29 iso4217:USD 0000104169 2023-03-15 xbrli:shares 0000104169 2021-02-01 2022-01-31 0000104169 2020-02-01 2021-01-31 iso4217:USD xbrli:shares 0000104169 2023-01-31 0000104169 2022-01-31 0000104169 us-gaap:CommonStockMember 2020-01-31 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us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:CommonStockMember 2022-01-31 0000104169 wmt:MassmartMember 2022-02-01 2023-01-31 0000104169 wmt:MassmartMember 2022-01-31 0000104169 wmt:AlertInnovationMember 2022-02-01 2023-01-31 0000104169 wmt:PhonePeMember 2022-01-31 0000104169 wmt:PhonePeMember 2022-02-01 2023-01-31 0000104169 wmt:PhonePeMember 2023-01-31 0000104169 wmt:FlipkartMember 2021-01-31 0000104169 wmt:FlipkartMember 2021-02-01 2022-01-31 0000104169 us-gaap:RestrictedStockMember 2022-02-01 2023-01-31 0000104169 us-gaap:RestrictedStockMem [...TRUNCATED...] esentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 17, 2023   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 17, 2023   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 17, 2023   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 17, 2023   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 17, 2023   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2023 86 Date: March 17, 2023   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 17, 2023 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 17, 2023 By /s/ Sarah Friar Sarah Friar Director Date: March 17, 2023 By /s/ Carla A. Harris Carla A. Harris Director Date: March 17, 2023 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 17, 2023 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 17, 2023 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 17, 2023   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 17, 2023   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2023 87\n\nPredict whether the return of XLI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.035571, "explanation": "The actual 21-day forward return for XLI starting 2023-03-20 was +3.56%, which classifies as 'positive'.", "metadata": {"future_return": 0.035571, "horizon_days": 21, "hist_return": -0.005862, "annualized_vol": 0.17508, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230809_0960", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-08-09", "context_summary": "CSHI over past 60 days: cumulative return +0.8%, annualized vol 0.7%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=42.72, end=43.08, cumulative_return=+0.8%, annualized_volatility=0.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.72, 't10y3m_spread': -1.55, 'breakeven_10y': 2.36, 'hy_oas': 4.0, 'ig_oas': 1.23, 'ted_spread': 0.09, 'mortgage_30y': 6.9, 'vix': 15.989999771118164}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002524, "explanation": "The actual 21-day forward return for CSHI starting 2023-08-09 was +0.25%, which classifies as 'flat'.", "metadata": {"future_return": 0.002524, "horizon_days": 21, "hist_return": 0.008257, "annualized_vol": 0.006852, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240215_0962", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-02-15", "context_summary": "XLF over past 60 days: cumulative return +12.2%, annualized vol 10.4%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=33.65, end=37.77, cumulative_return=+12.2%, annualized_volatility=10.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 310.967, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.29, 't10y3m_spread': -1.16, 'breakeven_10y': 2.3, 'hy_oas': 3.38, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 14.380000114440918}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent 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Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nPredict whether the return of XLF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.025647, "explanation": "The actual 21-day forward return for XLF starting 2024-02-15 was +2.56%, which classifies as 'positive'.", "metadata": {"future_return": 0.025647, "horizon_days": 21, "hist_return": 0.122353, "annualized_vol": 0.104183, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20241122_0964", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-11-22", "context_summary": "EFA over past 60 days: cumulative return -6.7%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=78.91, end=73.59, cumulative_return=-6.7%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.09, 't10y3m_spread': -0.2, 'breakeven_10y': 2.34, 'hy_oas': 2.66, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.84, 'vix': 16.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 2024-01-28 0001045810 us-gaap:CommonStockMember 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us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.01212, "explanation": "The actual 21-day forward return for EFA starting 2024-11-22 was -1.21%, which classifies as 'negative'.", "metadata": {"future_return": -0.01212, "horizon_days": 21, "hist_return": -0.067471, "annualized_vol": 0.134518, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20240607_0966", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-06-07", "context_summary": "DOT-USD over past 60 days: cumulative return -21.0%, annualized vol 62.4%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=9.04, end=7.14, cumulative_return=-21.0%, annualized_volatility=62.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.44, 't10y3m_spread': -1.23, 'breakeven_10y': 2.28, 'hy_oas': 3.2, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.99, 'vix': 12.579999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.072572, "explanation": "The actual 21-day forward return for DOT-USD starting 2024-06-07 was -7.26%, which classifies as 'negative'.", "metadata": {"future_return": -0.072572, "horizon_days": 21, "hist_return": -0.21036, "annualized_vol": 0.623564, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240918_0968", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-09-18", "context_summary": "EFA over past 60 days: cumulative return +4.0%, annualized vol 15.3%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=74.84, end=77.85, cumulative_return=+4.0%, annualized_volatility=15.3%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 314.732, 'unemployment': 4.1, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': 0.06, 't10y3m_spread': -1.3, 'breakeven_10y': 2.12, 'hy_oas': 3.25, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.2, 'vix': 17.610000610351562}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 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2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.000982, "explanation": "The actual 21-day forward return for EFA starting 2024-09-18 was -0.10%, which classifies as 'flat'.", "metadata": {"future_return": -0.000982, "horizon_days": 21, "hist_return": 0.040219, "annualized_vol": 0.153497, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230303_0970", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-03-03", "context_summary": "SOL-USD over past 60 days: cumulative return +95.0%, annualized vol 112.5%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=11.27, end=21.98, cumulative_return=+95.0%, annualized_volatility=112.5%\nMacro context: {'fed_funds_rate': 4.57, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.81, 't10y3m_spread': -0.83, 'breakeven_10y': 2.48, 'hy_oas': 4.18, 'ig_oas': 1.27, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 19.59000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-02] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.033669, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-03-03 was -3.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.033669, "horizon_days": 21, "hist_return": 0.95023, "annualized_vol": 1.124644, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240408_0972", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2024-04-08", "context_summary": "BNDX over past 60 days: cumulative return +0.2%, annualized vol 4.2%. Market regime: sideways.", "question": "Asset: BNDX\nHistorical prices (past 60 trading days): start=44.81, end=44.90, cumulative_return=+0.2%, annualized_volatility=4.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.023, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.34, 't10y3m_spread': -1.04, 'breakeven_10y': 2.37, 'hy_oas': 3.18, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.82, 'vix': 16.030000686645508}\nMarket regime: sideways\n\nPredict whether the return of BNDX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.001227, "explanation": "The actual 21-day forward return for BNDX starting 2024-04-08 was +0.12%, which classifies as 'flat'.", "metadata": {"future_return": 0.001227, "horizon_days": 21, "hist_return": 0.001885, "annualized_vol": 0.041616, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20241114_0973", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-11-14", "context_summary": "XLV over past 60 days: cumulative return -4.7%, annualized vol 9.4%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=150.14, end=143.05, cumulative_return=-4.7%, annualized_volatility=9.4%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.17, 't10y3m_spread': -0.16, 'breakeven_10y': 2.35, 'hy_oas': 2.66, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.79, 'vix': 14.020000457763672}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2024-11-07] cvx-20240930 0000093410 12/31 2024 Q3 false 102 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:State cvx:tribe cvx:parish 0000093410 2024-01-01 2024-09-30 0000093410 2024-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2023-07-01 2023-09-30 0000093410 2023-01-01 2023-09-30 0000093410 2023-12-31 0000093410 2022-12-31 0000093410 2023-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-06-30 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us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 000009 [...TRUNCATED...] ATION ISSUER PURCHASES OF EQUITY SECURITIES   Period Total Number of Shares Purchased (*) Average Price Paid per Share Total Number of Shares Purchased as Part of Publicly Announced Program Approximate Dollar Value of Shares that May Yet Be Purchased Under the 2023 Program (*) (Billions of dollars) July 1 - July 31, 2024 7,923,000  $156.56 7,923,000  $56.6 August 1 - August 31, 2024 12,057,000  $146.20 12,057,000  $54.8 September 1 - September 30, 2024 12,229,398  $142.84 12,229,398  $53.1 Total 32,209,398   $147.47 32,209,398   (*) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections A. Nigel Hearne , Executive Vice President, Senior Advisor , entered into a pre-arranged stock trading plan on August 19, 2024 . Mr. Hearne’s plan provides for the potential exercise of vested stock options and the associated sale of up to 60,468 shares of Chevron common stock between November 18, 2024, and February 28, 2025 . The trading plan was entered into during an open insider trading window and is intended to satisfy the affirmative defense of Rule 10b5-1(c) under the Securities Exchange Act of 1934, as amended, and Chevron’s policies regarding transactions in Chevron securities. 44 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 10.1+* Chevron Incentive Plan, amended and restated effective October 2, 2023 (refi l ed to correct formatting in the previo usly filed version) . 10.2+* Chevron Corporation Retirement Restoration Plan, amended and restated effective August 1, 2024. 10.3+* Chevron Corporation ESIP Restoration Plan, amended and restated effective August 1, 2024. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ +     Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 45 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 7, 2024 46\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.024425, "explanation": "The actual 21-day forward return for XLV starting 2024-11-14 was -2.44%, which classifies as 'negative'.", "metadata": {"future_return": -0.024425, "horizon_days": 21, "hist_return": -0.047209, "annualized_vol": 0.094042, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230914_0975", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-09-14", "context_summary": "SOL-USD over past 60 days: cumulative return -32.8%, annualized vol 49.1%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=27.38, end=18.40, cumulative_return=-32.8%, annualized_volatility=49.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.71, 't10y3m_spread': -1.3, 'breakeven_10y': 2.35, 'hy_oas': 3.85, 'ig_oas': 1.24, 'ted_spread': 0.09, 'mortgage_30y': 7.12, 'vix': 13.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-13] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.204681, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-09-14 was +20.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.204681, "horizon_days": 21, "hist_return": -0.327967, "annualized_vol": 0.491436, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230301_0977", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-03-01", "context_summary": "EFA over past 60 days: cumulative return +2.7%, annualized vol 14.2%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=61.28, end=62.96, cumulative_return=+2.7%, annualized_volatility=14.2%\nMacro context: {'fed_funds_rate': 4.57, 'cpi_yoy': 301.45, 'unemployment': 3.6, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.89, 't10y3m_spread': -0.96, 'breakeven_10y': 2.43, 'hy_oas': 4.22, 'ig_oas': 1.3, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 20.700000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-28] [\"The Zacks Analyst Blog Highlights Apple, Linde, Marsh & McLennan Companies, GSK and Expedia For Immediate Release Chicago, IL \\u2013 February 28, 2023 \\u2013 Zacks.com announces the list of stocks featured in the Analyst Blog. Every day the Zacks Equity Research analysts discuss the latest news and events impacting stocks and the financial markets. Stocks recently featured in the blog include: Apple Inc. AAPL, Linde plc LIN, Marsh & McLennan Companies, Inc. MMC, GSK plc GSK and Expedia Group, Inc. EXPE. Here are highlights from Monday\\u2019s Analyst Blog: Top Analyst Reports from Apple, Linde and Marsh & McLennan The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc., Linde plc and Marsh & McLennan Companies, Inc. These research reports have been hand-picked from the roughly 70 reports published by our analyst team today. You can see all of today\\u2019s research reports here >>> Shares of Apple have roughly matched the broader market over the past year (-10.4% for Apple vs. -10.9% for the S&P 500 index), but handily outperformed the Zacks Tech sector (down - 19.8%). The Zacks analyst covering Apple expects year-over-year revenue growth to decelerate in the fiscal first quarter compared with the fiscal fourth quarter due to unfavorable forex. Mac revenues are expected to be negatively impacted by forex. Apple expects Mac revenues to decline substantially year over year during the December quarter. Services revenue growth is expected to be negatively impacted by challenging macroeconomic conditions, unfavorable forex, as well as weakness in digital advertising and gaming. Nevertheless, a growing subscriber base in the Services business and a strong liquidity position are key catalysts. (You can read the full research report on Apple here >>>) Linde shares have outperformed the Zacks Chemical - Diversified industry over the past year (+18.6% vs. +10.3%). The company\\u2019s wide range of applications for its industrial gases, Linde is making the world more productive by the day. The company\\u2019s primary products in industrial gases include oxygen, which is used as life support in hospitals. Its process gas, like hydrogen, is being utilized for clean fuels, while its high-purity and specialty gases are employed to manufacture electronics. Linde has long-term contracts with on-site customers backed by minimum purchase requirements, thereby securing stable cashflows. In the profitable industrial gas market, the merger of Praxair and Linde has created an efficient player with considerable size advantages. However, the cost of sales continues to increase, hurting the firm\\u2019s bottom line. The firm has mostly been paying a lower dividend yield than the industry\\u2019s composite stocks over the past two years. (You can read the full research report on Linde here >>>) Marsh & McLennan shares have outperformed the Zacks Insurance - Bro\n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.020654, "explanation": "The actual 21-day forward return for EFA starting 2023-03-01 was +2.07%, which classifies as 'positive'.", "metadata": {"future_return": 0.020654, "horizon_days": 21, "hist_return": 0.027417, "annualized_vol": 0.141639, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20240709_0979", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2024-07-09", "context_summary": "DBC over past 60 days: cumulative return +0.5%, annualized vol 12.9%. Market regime: sideways.", "question": "Asset: DBC\nHistorical prices (past 60 trading days): start=21.44, end=21.55, cumulative_return=+0.5%, annualized_volatility=12.9%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.34, 't10y3m_spread': -1.18, 'breakeven_10y': 2.27, 'hy_oas': 3.2, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.369999885559082}\nMarket regime: sideways\n\nPredict whether the return of DBC over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.060944, "explanation": "The actual 21-day forward return for DBC starting 2024-07-09 was -6.09%, which classifies as 'negative'.", "metadata": {"future_return": -0.060944, "horizon_days": 21, "hist_return": 0.005141, "annualized_vol": 0.129039, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20240307_0981", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-03-07", "context_summary": "^VIX over past 60 days: cumulative return +17.4%, annualized vol 71.0%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=12.35, end=14.50, cumulative_return=+17.4%, annualized_volatility=71.0%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 312.345, 'unemployment': 3.9, 'gdp_growth_qoq': 23082.119, 't10y2y_spread': -0.44, 't10y3m_spread': -1.36, 'breakeven_10y': 2.3, 'hy_oas': 3.27, 'ig_oas': 1.01, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 14.5}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 0000731766 2023-06-30 iso4217:USD 0000731766 2024-01-31 xbrli:shares 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Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.110111, "explanation": "The actual 21-day forward return for ^VIX starting 2024-03-07 was +11.01%, which classifies as 'positive'.", "metadata": {"future_return": 0.110111, "horizon_days": 21, "hist_return": 0.174089, "annualized_vol": 0.710313, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20231025_0983", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-10-25", "context_summary": "ETH-USD over past 60 days: cumulative return +8.4%, annualized vol 29.8%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1646.31, end=1784.44, cumulative_return=+8.4%, annualized_volatility=29.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.696, 'unemployment': 3.9, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.19, 't10y3m_spread': -0.75, 'breakeven_10y': 2.4, 'hy_oas': 4.41, 'ig_oas': 1.31, 'ted_spread': 0.09, 'mortgage_30y': 7.49, 'vix': 18.96999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-24] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.152742, "explanation": "The actual 21-day forward return for ETH-USD starting 2023-10-25 was +15.27%, which classifies as 'positive'.", "metadata": {"future_return": 0.152742, "horizon_days": 21, "hist_return": 0.083903, "annualized_vol": 0.298391, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20231206_0984", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-12-06", "context_summary": "XRP-USD over past 60 days: cumulative return +19.2%, annualized vol 43.4%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.52, end=0.62, cumulative_return=+19.2%, annualized_volatility=43.4%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 308.741, 'unemployment': 3.8, 'gdp_growth_qoq': 23033.78, 't10y2y_spread': -0.39, 't10y3m_spread': -1.27, 'breakeven_10y': 2.17, 'hy_oas': 3.8, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 7.22, 'vix': 12.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-05] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.008553, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-12-06 was -0.86%, which classifies as 'flat'.", "metadata": {"future_return": -0.008553, "horizon_days": 21, "hist_return": 0.19178, "annualized_vol": 0.43418, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230131_0985", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-01-31", "context_summary": "SOL-USD over past 60 days: cumulative return +74.6%, annualized vol 110.7%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=13.72, end=23.95, cumulative_return=+74.6%, annualized_volatility=110.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 300.42, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.7, 't10y3m_spread': -1.17, 'breakeven_10y': 2.29, 'hy_oas': 4.26, 'ig_oas': 1.25, 'ted_spread': 0.09, 'mortgage_30y': 6.13, 'vix': 19.940000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-30] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.041583, "explanation": "The actual 21-day forward return for SOL-USD starting 2023-01-31 was +4.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.041583, "horizon_days": 21, "hist_return": 0.745914, "annualized_vol": 1.107289, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241205_0987", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-12-05", "context_summary": "SOL-USD over past 60 days: cumulative return +40.8%, annualized vol 60.7%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=146.44, end=206.25, cumulative_return=+40.8%, annualized_volatility=60.7%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.06, 't10y3m_spread': -0.28, 'breakeven_10y': 2.29, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 13.449999809265137}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.087441, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-12-05 was -8.74%, which classifies as 'negative'.", "metadata": {"future_return": -0.087441, "horizon_days": 21, "hist_return": 0.408424, "annualized_vol": 0.607053, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240528_0989", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-05-28", "context_summary": "XLB over past 60 days: cumulative return +4.2%, annualized vol 11.8%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=42.16, end=43.95, cumulative_return=+4.2%, annualized_volatility=11.8%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.175, 'unemployment': 3.9, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.47, 't10y3m_spread': -1.0, 'breakeven_10y': 2.32, 'hy_oas': 3.12, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 11.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 2026-01-01 us-gaap:InvestmentAdviceMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember 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us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 us-gaap:InvestmentAdviceMember blk:FixedIncomeMember 2024-01-01 2024-03-31 0001364742 us-gaap:InvestmentAdviceMember blk:EquityNonETFIndexMember 2023-01-01 2023-03-31 0001364742 blk:PerformanceBasedRestrictedStockUnitsMember 2023-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:InvestmentsMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 blk:InstitutionalMember blk:RevenueByClientTypeMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 blk:TwoThousandTwentyFourRevolvingCreditFacilitiesMember 2024-03-31 0001364742 us-gaap:RealEstateFundsMember us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 2023-12-31 0001364742 blk:DeferredCashCompensationPlansMember 2024-03-31 0001364742 us-gaap:CorporateDebtSecuritiesMember 2024-03-31 0001364742 srt:EuropeMember 2024-03-31 0001364742 blk:PerformanceBasedStockOptionsMember 2024-01-01 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 srt:AsiaPacificMember 2023-01-01 2023-03-31 0001364742 us-gaap:RestrictedStockUnitsRSUMember 2023-01-01 2023-03-31 0001364742 us-gaap:HedgeFundsEquityMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.024713, "explanation": "The actual 21-day forward return for XLB starting 2024-05-28 was -2.47%, which classifies as 'negative'.", "metadata": {"future_return": -0.024713, "horizon_days": 21, "hist_return": 0.042385, "annualized_vol": 0.117847, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20230918_0990", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-09-18", "context_summary": "XRP-USD over past 60 days: cumulative return -37.9%, annualized vol 42.2%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.79, end=0.49, cumulative_return=-37.9%, annualized_volatility=42.2%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 307.276, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.69, 't10y3m_spread': -1.23, 'breakeven_10y': 2.35, 'hy_oas': 3.79, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 7.18, 'vix': 13.789999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-17] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 4.8e-05, "explanation": "The actual 21-day forward return for XRP-USD starting 2023-09-18 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 4.8e-05, "horizon_days": 21, "hist_return": -0.379087, "annualized_vol": 0.421918, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20240606_0991", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-06-06", "context_summary": "^VIX over past 60 days: cumulative return -8.7%, annualized vol 86.6%. Market regime: bull.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=13.84, end=12.63, cumulative_return=-8.7%, annualized_volatility=86.6%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.044, 'unemployment': 4.1, 'gdp_growth_qoq': 23286.508, 't10y2y_spread': -0.43, 't10y3m_spread': -1.22, 'breakeven_10y': 2.3, 'hy_oas': 3.2, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 7.03, 'vix': 12.630000114440918}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nPredict whether the return of ^VIX over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.007949, "explanation": "The actual 21-day forward return for ^VIX starting 2024-06-06 was -0.79%, which classifies as 'flat'.", "metadata": {"future_return": -0.007949, "horizon_days": 21, "hist_return": -0.087428, "annualized_vol": 0.865593, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20240711_0993", "template": "T1", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-07-11", "context_summary": "SOL-USD over past 60 days: cumulative return -1.1%, annualized vol 69.1%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=143.52, end=141.97, cumulative_return=-1.1%, annualized_volatility=69.1%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 313.569, 'unemployment': 4.2, 'gdp_growth_qoq': 23478.57, 't10y2y_spread': -0.34, 't10y3m_spread': -1.18, 'breakeven_10y': 2.27, 'hy_oas': 3.17, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 12.850000381469728}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.233943, "explanation": "The actual 21-day forward return for SOL-USD starting 2024-07-11 was +23.39%, which classifies as 'positive'.", "metadata": {"future_return": 0.233943, "horizon_days": 21, "hist_return": -0.010772, "annualized_vol": 0.690971, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20241115_0995", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-11-15", "context_summary": "AVAX-USD over past 60 days: cumulative return +32.5%, annualized vol 67.9%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=23.52, end=31.16, cumulative_return=+32.5%, annualized_volatility=67.9%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 316.528, 'unemployment': 4.2, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.09, 't10y3m_spread': -0.18, 'breakeven_10y': 2.33, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.78, 'vix': 14.3100004196167}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.586585, "explanation": "The actual 21-day forward return for AVAX-USD starting 2024-11-15 was +58.66%, which classifies as 'positive'.", "metadata": {"future_return": 0.586585, "horizon_days": 21, "hist_return": 0.324902, "annualized_vol": 0.679058, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230802_0997", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-08-02", "context_summary": "MATIC-USD over past 60 days: cumulative return -22.0%, annualized vol 71.7%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.90, end=0.70, cumulative_return=-22.0%, annualized_volatility=71.7%\nMacro context: {'fed_funds_rate': 5.33, 'cpi_yoy': 306.082, 'unemployment': 3.7, 'gdp_growth_qoq': 22840.989, 't10y2y_spread': -0.87, 't10y3m_spread': -1.49, 'breakeven_10y': 2.37, 'hy_oas': 3.82, 'ig_oas': 1.19, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 13.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-01] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.182134, "explanation": "The actual 21-day forward return for MATIC-USD starting 2023-08-02 was -18.21%, which classifies as 'negative'.", "metadata": {"future_return": -0.182134, "horizon_days": 21, "hist_return": -0.220345, "annualized_vol": 0.71722, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20230323_0999", "template": "T1", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2023-03-23", "context_summary": "WEAT over past 60 days: cumulative return -13.6%, annualized vol 23.5%. Market regime: sideways.", "question": "Asset: WEAT\nHistorical prices (past 60 trading days): start=39.05, end=33.75, cumulative_return=-13.6%, annualized_volatility=23.5%\nMacro context: {'fed_funds_rate': 4.58, 'cpi_yoy': 301.821, 'unemployment': 3.5, 'gdp_growth_qoq': 22439.607, 't10y2y_spread': -0.48, 't10y3m_spread': -1.31, 'breakeven_10y': 2.28, 'hy_oas': 5.0, 'ig_oas': 1.5, 'ted_spread': 0.09, 'mortgage_30y': 6.6, 'vix': 22.26000022888184}\nMarket regime: sideways\n\nPredict whether the return of WEAT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002976, "explanation": "The actual 21-day forward return for WEAT starting 2023-03-23 was +0.30%, which classifies as 'flat'.", "metadata": {"future_return": 0.002976, "horizon_days": 21, "hist_return": -0.135723, "annualized_vol": 0.235267, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230601_0001", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-06-01", "context_summary": "BTC-USD: 60-day return history, mean=-0.0005, std=0.0193.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0193, min=-0.0518, max=0.0466\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-31] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0328", "answer_numeric": -0.032802, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0328 (i.e., on a bad day with 5% probability, the loss exceeds 3.28%). CVaR(95%) = -0.0421.", "metadata": {"var": -0.032802, "cvar": -0.042113, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230407_0005", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-04-07", "context_summary": "USMV: 60-day return history, mean=0.0002, std=0.0075.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0002, std=0.0075, min=-0.0177, max=0.0140\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-06] [\"Guru Fundamental Report for AAPL - Warren Buffett Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Patient Investor model based on the published strategy of Warren Buffett. This strategy seeks out firms with long-term, predictable profitability and low debt that trade at reasonable valuations. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 100% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. EARNINGS PREDICTABILITY: PASS DEBT SERVICE: PASS RETURN ON EQUITY: PASS RETURN ON TOTAL CAPITAL: PASS FREE CASH FLOW: PASS USE OF RETAINED EARNINGS: PASS SHARE REPURCHASE: PASS INITIAL RATE OF RETURN: PASS EXPECTED RETURN: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Warren Buffett Warren Buffett Portfolio Top Warren Buffett Stocks About Warren Buffett: Warren Buffett is considered by many to be the greatest investor of all time. As the chairman of Berkshire Hathaway, Buffett has consistently outperformed the S&P 500 for decades, and in the process has become one of the world's richest men. (Forbes puts his net worth at $37 billion.) Despite his fortune, Buffett is known for living a modest lifestyle, by billionaire standards. His primary residence remains the gray stucco Nebraska home he purchased for $31,500 nearly 50 years ago, according to Forbes, and his folksy Midwestern manner and penchant for simple pleasures -- a cherry Coke, a good burger, and a good book are all near the top of the list -- have been well-documented. Additional Research Links Factor-Based Stock Portfolios Factor-Based ETF Portfolios Harry Browne Permanent Portfolio Ray Dalio All Weather Portfolio About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"3 Cryptos That Day Traders Love Right Now InvestorPlace - Stock Market News, Stock Advice & Trading Tips Cryptocurrencies delivered huge gains for investors during the previous bull market. Yet, more than a few got wiped o\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0123", "answer_numeric": -0.012264, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0123 (i.e., on a bad day with 5% probability, the loss exceeds 1.23%). CVaR(95%) = -0.0148.", "metadata": {"var": -0.012264, "cvar": -0.014793, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230517_0008", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-05-17", "context_summary": "FXI: 60-day return history, mean=-0.0005, std=0.0176.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0005, std=0.0176, min=-0.0376, max=0.0440\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-16] [\"Tesla to meet Indian officials this week - source By Aditya Kalra and Aditi Shah NEW DELHI, May 16 (Reuters) - Senior Tesla Inc TSLA.O executives will meet Indian government officials on Wednesday and Thursday to discuss local procurement of parts and other issues, a source with direct knowledge of the matter told Reuters. The electric carmaker's renewed interest in India comes nearly a year after it put on hold plans to sell cars in the country after failing to secure lower import taxes, which its CEO Elon Musk said are among the highest in the world. Tesla and an Indian government spokesperson did not immediately respond to a request for comment. Tesla wanted lower tariffs to be able to test the local market with cars imported from the U.S. and China, but the Indian government wanted it to commit to manufacturing locally before cutting import taxes on cars that can run as high as 100%. The electric carmaker had hired a local team and begun a search for showroom space, but that was also abandoned last year. Local sourcing aligns with Modi's pitch to attract manufacturers with his \\\"Make in India\\\" campaign, especially as companies look to diversify their supply chains beyond China. The meeting comes weeks ahead of Prime Minister Narendra Modi's visit to the United States in June. Bloomberg News first reported the meeting plan. (Reporting by Aditya Kalra; Additional reporting by Aditi Shah; Editing by Jan Harvey) ((aditi.shah@tr.com; +91-11-4954 8023, +91-11-3015 8023; Reuters Messaging: twitter: @aditishahsays)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Pre-Market Most Active for May 16, 2023 : SQQQ, APLD, HZNP, AAPL, FUTU, MRVL, AGL, NU, SE, HD, CL, AI The NASDAQ 100 Pre-Market Indicator is down -18.87 to 13,394.64. The total Pre-Market volume is currently 25,120,169 shares traded. The following are the most active stocks for the pre-market session: ProShares UltraPro Short QQQ (SQQQ) is +0.05 at $27.95, with 1,833,307 shares traded. This represents a .54% increase from its 52 Week Low. Applied Digital Corporation (APLD) is +1.275 at $4.69, with 1,816,264 shares traded. As reported by Zacks, the current mean recommendation for APLD is in the \\\"buy range\\\". Horizon Therapeutics Public Limited Company (HZNP) is -20.25 at $92.00, with 1,704,565 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $1.6. HZNP's current last sale is 78.97% of the target price of $116.5. Apple Inc. (AAPL) is -0.07 at $172.00, with 1,566,401 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2023. The consensus EPS forecast is $2.17. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". Futu Holdings Limited (FUTU) is -4.05 at $39.10, with 1,558,667 sh\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for FXI. Express as a decimal (e.g., -0.02).", "answer": "-0.0274", "answer_numeric": -0.027427, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0274 (i.e., on a bad day with 5% probability, the loss exceeds 2.74%). CVaR(95%) = -0.0320.", "metadata": {"var": -0.027427, "cvar": -0.032028, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230919_0011", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-09-19", "context_summary": "IWM: 60-day return history, mean=-0.0001, std=0.0094.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0001, std=0.0094, min=-0.0213, max=0.0170\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-18] [\"2 Stocks That Are Cash Flow Machines to Buy Now While a profit metric like net income shouldn't be ignored, it's ultimately an accounting figure. Free cash flow, which is the amount of cash a business generates from operations after subtracting capital expenditures, is what fuels growth investments, dividend payments, share buybacks, and debt reduction. You can't spend net income. Investing in companies that are solid cash flow producers is often a good idea, assuming the price is reasonable. Two cash flow machines that trade at pessimistic valuations are AT&T (NYSE: T) and IBM (NYSE: IBM). Both stocks look like bargains. AT&T With Apple's iPhone 15 family officially announced, the major wireless carriers are using promotions to attract new customers and retain existing customers. AT&T, for example, is offering as much as $1,000 off the iPhone 15 Pro with an eligible trade-in for customers on its Unlimited plans. While this promotional activity appears aggressive, AT&T CFO Pascal Desroches noted during a recent conference that promotional activity is largely unchanged across the industry. \\\"I would characterize the environment as really healthy. The competitive dynamics is very, very healthy, very rational,\\\" Desroches said. During the same conference, Desroches reiterated AT&T's guidance calling for at least $16 billion of free cash flow this year, even as subscriber gains have slowed. Free cash flow could move higher in 2024 and beyond as AT&T pulls back a bit on capital spending. The company has been investing heavily in its 5G and fiber networks, pushing capital spending up. This year is expected to mark the peak of that spending. AT&T is valued at about $109 billion. Based on the free cash guidance, the stock's price-to-free-cash-flow ratio is around 6.8. That's an extremely pessimistic valuation. AT&T stock certainly doesn't deserve to trade at a premium: Growth will be slow at best, debt levels are still elevated, and competitive pressures could ramp up if economic conditions deteriorate. But the pessimism seems overdone. AT&T stock trades lower than it did during the dot-com bubble, the financial crisis, and the pandemic. For patient investors, this cash flow machine looks like a bargain. IBM While IBM is a complex company that spans hardware, software, and services, the tech giant ultimately offers customers solutions that aim to boost productivity and cut costs. In a tough and uncertain economy, that pitch should resonate with customers. IBM's cloud strategy is centered around hybrid cloud computing. While some companies will go all-in on the public cloud, that's not realistic for major enterprises with sprawling IT infrastructures. IBM's hybrid cloud platform, powered by Red Hat software, provides a path for customers to modernize their infrastructure and take advantage of cloud computing while minimizing disruption and keeping an eye on costs. On top of software, IBM's consulting arm provides guidance and help in navigating the move\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0140", "answer_numeric": -0.013991, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0140 (i.e., on a bad day with 5% probability, the loss exceeds 1.40%). CVaR(95%) = -0.0176.", "metadata": {"var": -0.013991, "cvar": -0.017579, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240626_0014", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-06-26", "context_summary": "BNB-USD: 60-day return history, mean=-0.0003, std=0.0250.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0003, std=0.0250, min=-0.0727, max=0.0954\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0351", "answer_numeric": -0.03512, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0351 (i.e., on a bad day with 5% probability, the loss exceeds 3.51%). CVaR(95%) = -0.0510.", "metadata": {"var": -0.03512, "cvar": -0.050968, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231122_0017", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-11-22", "context_summary": "VTI: 60-day return history, mean=0.0004, std=0.0088.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0004, std=0.0088, min=-0.0169, max=0.0219\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-21] [\"AAPL Quantitative Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"EXPLAINER-What is Black Friday? And will shoppers find bargains this year? By Juveria Tabassum, Savyata Mishra Nov 16 (Reuters) - Retailers are preparing for what they hope will be yet another record-setting global shopping spree on Black Friday, the fourth Friday of November, which this year is Nov. 24. Known for crowds lining up at big-box stores to pounce on doorbuste\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VTI. Express as a decimal (e.g., -0.02).", "answer": "-0.0146", "answer_numeric": -0.01464, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0146 (i.e., on a bad day with 5% probability, the loss exceeds 1.46%). CVaR(95%) = -0.0156.", "metadata": {"var": -0.01464, "cvar": -0.015593, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230505_0020", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-05-05", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0019, std=0.0333.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0019, std=0.0333, min=-0.0851, max=0.0871\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-04] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0563", "answer_numeric": -0.056314, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0563 (i.e., on a bad day with 5% probability, the loss exceeds 5.63%). CVaR(95%) = -0.0769.", "metadata": {"var": -0.056314, "cvar": -0.076935, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240423_0023", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2024-04-23", "context_summary": "VNQI: 60-day return history, mean=-0.0000, std=0.0081.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=-0.0000, std=0.0081, min=-0.0251, max=0.0153\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VNQI. Express as a decimal (e.g., -0.02).", "answer": "-0.0126", "answer_numeric": -0.012602, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0126 (i.e., on a bad day with 5% probability, the loss exceeds 1.26%). CVaR(95%) = -0.0216.", "metadata": {"var": -0.012602, "cvar": -0.021608, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230124_0026", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2023-01-24", "context_summary": "ITB: 60-day return history, mean=0.0021, std=0.0167.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=0.0021, std=0.0167, min=-0.0381, max=0.0472\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ITB. Express as a decimal (e.g., -0.02).", "answer": "-0.0214", "answer_numeric": -0.021391, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0214 (i.e., on a bad day with 5% probability, the loss exceeds 2.14%). CVaR(95%) = -0.0331.", "metadata": {"var": -0.021391, "cvar": -0.033086, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230728_0029", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-07-28", "context_summary": "XLY: 60-day return history, mean=0.0025, std=0.0107.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0025, std=0.0107, min=-0.0347, max=0.0232\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K MSFT 2023-07-27] 10-K 0000789019 false FY --06-30 P2Y P5Y P3Y P1Y P1Y http://fasb.org/us-gaap/2023#DerivativeAssets http://fasb.org/us-gaap/2023#DerivativeAssets http://fasb.org/us-gaap/2023#DerivativeLiabilities http://fasb.org/us-gaap/2023#DerivativeLiabilities http://fasb.org/us-gaap/2023#OtherAssetsCurrent http://fasb.org/us-gaap/2023#OtherAssetsCurrent http://fasb.org/us-gaap/2023#OtherAssetsCurrent 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as Inline XBRL and contained in Exhibit 101   X                                   * Indicates a management contract or compensatory plan or arrangement. ** Furnished, not filed. 107 PART IV Item 16   ITEM 16. FORM 10-K SUMMARY None. 108   SIGNAT URES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned; thereunto duly authorized, in the City of Redmond, State of Washington, on July 27, 2023. M ICROSOFT  C ORPORATION   /s/ A LICE  L. J OLLA Alice L. Jolla Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer)   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of Registrant and in the capacities indicated on July 27, 2023. Signature Title   /s/ S ATYA  N ADELLA Chairman and Chief Executive Officer (Principal Executive Officer) Satya Nadella     /s/ R EID  H OFFMAN   Director Reid Hoffman     /s/ H UGH  F. J OHNSTON Director Hugh F. Johnston     /s/ T ERI L. L IST Director Teri L. List     /s/ S ANDRA  E. P ETERSON Lead Independent Director Sandra E. Peterson       /s/ P ENNY S. P RITZKER   Director Penny S. Pritzker       /s/ C ARLOS A. R ODRIGUEZ   Director Carlos A. Rodriguez       /s/ C HARLES  W. S CHARF Director Charles W. Scharf     /s/ J OHN  W. S TANTON Director John W. Stanton       /s/ J OHN  W. T HOMPSON   Director John W. Thompson       /s/ E MMA  N. W ALMSLEY   Director Emma N. Walmsley     /s/ P ADMASREE  W ARRIOR Director Padmasree Warrior     /s/ A MY  E. H OOD Executive Vice President and Chief Financial Officer (Principal Financial Officer) Amy E. Hood     /s/ A LICE  L. J OLLA Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer) Alice L. Jolla     109\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0121", "answer_numeric": -0.012128, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0121 (i.e., on a bad day with 5% probability, the loss exceeds 1.21%). CVaR(95%) = -0.0213.", "metadata": {"var": -0.012128, "cvar": -0.021269, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20240202_0031", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-02-02", "context_summary": "ADA-USD: 60-day return history, mean=0.0055, std=0.0529.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0055, std=0.0529, min=-0.0799, max=0.1961\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0601", "answer_numeric": -0.060131, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0601 (i.e., on a bad day with 5% probability, the loss exceeds 6.01%). CVaR(95%) = -0.0726.", "metadata": {"var": -0.060131, "cvar": -0.072619, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231013_0034", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-10-13", "context_summary": "USMV: 60-day return history, mean=-0.0004, std=0.0052.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=-0.0004, std=0.0052, min=-0.0123, max=0.0088\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-12] [\"US STOCKS-Futures rise as Treasury yields retreat ahead of inflation data For a Reuters live blog on U.S., UK and European stock markets, click LIVE/ or type LIVE/ in a news window CPI, weekly jobless claims due at 8:30 a.m. ET Fed officials adopted more cautious stance in September Israel says no exceptions to Gaza siege unless hostages freed Delta Air Lines up on quarterly profit beat Futures up: Dow 0.31%, S&P 0.37%, Nasdaq 0.35% Updated at 7:09 a.m. ET/1109 GMT By Shashwat Chauhan and Ankika Biswas Oct 12 (Reuters) - Futures tracking Wall Street's main indexes rose on Thursday as Treasury yields continued to ease, while investors looked forward to crucial inflation data to gauge the Federal Reserve's interest-rate outlook. The Labor Department report, due at 8:30 a.m. ET, is expected to show consumer prices rose 0.3% in September, according to economists polled by Reuters, from a gasoline-fueled 0.6% rise in August. Core CPI, which excludes volatile food and energy prices, is seen rising at a similar pace to last month's 0.3%. Focus will also be on weekly jobless claims for clues on the state of the labor market. The yield on the benchmark 10-year note US10YT=RR fell for the third straight day, helping megacap stocks Apple AAPL.O, Alphabet GOOGL.O, Nvidia NVDA.O, Meta Platforms META.O and Amazon.com AMZN.O advance between 0.2% and 0.7% in premarket trading. Boston Fed President Susan Collins said on Wednesday while the odds of the economy escaping a recession have grown, it's possible the central bank is not done with interest rate hikes aimed at bringing inflation back to its target. Remarks from other Fed policymakers, including Atlanta's Raphael Bostic, are also expected on Thursday. Minutes of the Fed's Sept. 19-20 meeting showed a growing sense of uncertainty around the path of the U.S. economy, with volatile data and tightening financial markets posing risks to growth. \\\"The words 'proceed carefully' and 'risks to achieving the goals had become more two-sided' speak to the view of the centrists on the FOMC,\\\" Societe Generale strategists said, referring to the Fed minutes. \\\"Barring a surprise for CPI today ... one must assume another hawkish pause or skip on Nov. 1 is now a done deal.\\\" Traders put the chance of interest rates remaining unchanged in November and December at around 91% and around 72%, respectively, according to CME's FedWatch tool. Meanwhile, Israel said there would be no humanitarian exceptions to its siege of the Gaza Strip until all its hostages were freed. Public broadcaster Kan said the Israeli death toll had risen to more than 1,300 since Saturday, while Gaza authorities said more than 1,200 people have been killed and more than 5,000 people have been wounded in retaliatory bombings. At 7:09 a.m. ET, Dow e-minis 1YMcv1 were up 105 points, or 0.31%, S&P 500 e-minis EScv1 were up 16.5 points, or 0.37%, and Nasdaq 100 e-minis NQcv1 were up 54.25 points, or 0.35%. All three major U.S. stock indexes closed higher for\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0078", "answer_numeric": -0.007761, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0078 (i.e., on a bad day with 5% probability, the loss exceeds 0.78%). CVaR(95%) = -0.0110.", "metadata": {"var": -0.007761, "cvar": -0.010973, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231024_0037", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-10-24", "context_summary": "XLP: 60-day return history, mean=-0.0020, std=0.0066.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0020, std=0.0066, min=-0.0199, max=0.0103\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-23] [\"Why the Market Dipped But Apple (AAPL) Gained Today Apple (AAPL) closed at $173 in the latest trading session, marking a +0.07% move from the prior day. The stock exceeded the S&P 500, which registered a loss of 0.17% for the day. On the other hand, the Dow registered a loss of 0.58%, and the technology-centric Nasdaq increased by 0.27%. Heading into today, shares of the maker of iPhones, iPads and other products had lost 1.09% over the past month, outpacing the Computer and Technology sector's loss of 2.16% and the S&P 500's loss of 3.95% in that time. The upcoming earnings release of Apple will be of great interest to investors. The company's earnings report is expected on November 2, 2023. The company is forecasted to report an EPS of $1.39, showcasing a 7.75% upward movement from the corresponding quarter of the prior year. Alongside, our most recent consensus estimate is anticipating revenue of $88.93 billion, indicating a 1.34% downward movement from the same quarter last year. Investors should also pay attention to any latest changes in analyst estimates for Apple. Recent revisions tend to reflect the latest near-term business trends. As such, positive estimate revisions reflect analyst optimism about the company's business and profitability. Based on our research, we believe these estimate revisions are directly related to near-team stock moves. To utilize this, we have created the Zacks Rank, a proprietary model that integrates these estimate changes and provides a functional rating system. The Zacks Rank system ranges from #1 (Strong Buy) to #5 (Strong Sell). It has a remarkable, outside-audited track record of success, with #1 stocks delivering an average annual return of +25% since 1988. Over the past month, the Zacks Consensus EPS estimate has shifted 0.39% downward. Apple presently features a Zacks Rank of #3 (Hold). In terms of valuation, Apple is presently being traded at a Forward P/E ratio of 26.36. This expresses a premium compared to the average Forward P/E of 11.78 of its industry. It's also important to note that AAPL currently trades at a PEG ratio of 2.32. This metric is used similarly to the famous P/E ratio, but the PEG ratio also takes into account the stock's expected earnings growth rate. The average PEG ratio for the Computer - Mini computers industry stood at 2.32 at the close of the market yesterday. The Computer - Mini computers industry is part of the Computer and Technology sector. This group has a Zacks Industry Rank of 54, putting it in the top 22% of all 250+ industries. The Zacks Industry Rank is ordered from best to worst in terms of the average Zacks Rank of the individual companies within each of these sectors. Our research shows that the top 50% rated industries outperform the bottom half by a factor of 2 to 1. Keep in mind to rely on Zacks.com to watch all these stock-impacting metrics, and more, in the succeeding trading sessions. 7 Best Stocks for the Next 30 Days Just released: Experts distill 7 el\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLP. Express as a decimal (e.g., -0.02).", "answer": "-0.0108", "answer_numeric": -0.010814, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0108 (i.e., on a bad day with 5% probability, the loss exceeds 1.08%). CVaR(95%) = -0.0146.", "metadata": {"var": -0.010814, "cvar": -0.014621, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240815_0039", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2024-08-15", "context_summary": "WEAT: 60-day return history, mean=-0.0043, std=0.0138.", "question": "Asset: WEAT\nDaily returns (past 60 days): mean=-0.0043, std=0.0138, min=-0.0310, max=0.0328\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for WEAT. Express as a decimal (e.g., -0.02).", "answer": "-0.0247", "answer_numeric": -0.024695, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0247 (i.e., on a bad day with 5% probability, the loss exceeds 2.47%). CVaR(95%) = -0.0283.", "metadata": {"var": -0.024695, "cvar": -0.028332, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230626_0042", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-06-26", "context_summary": "QUAL: 60-day return history, mean=0.0017, std=0.0084.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0017, std=0.0084, min=-0.0173, max=0.0233\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-23] [\"Great Stocks Are Still on Sale, but There's Something You Need to Know First It seems like investors have turned from pessimism to optimism, as the S&P 500 is approaching what many market watchers consider to be bull market territory, up over 20% since its recent low in October 2022. Inflation has been cooling for several months now, so the thinking is probably that rate hikes are coming to an end soon. Investors are reacting to this expectation by pushing stocks higher. As a result, folks might think that lucrative buying opportunities don't exist anymore given many companies' share prices have jumped higher in 2023. But this is a flawed assumption. That's because great stocks are still on sale right now. There's just something you need to know first. It's all about quality Just because a stock sells for a cheap valuation, it doesn't necessarily mean it's a good investment opportunity. A so-called value trap is a company that might have a cheap price-to-sales (P/S) or price-to-earnings (P/E) multiple, but the underlying business is facing some problems. Take Carvana, for example, which trades at a P/S multiple of 0.2 (as of June 16). The company might be showing signs of life after a difficult 2022, but it's still dealing with challenges as it relates to used car demand and the current macro environment affecting its financial situation. Some risk-tolerant investors might view this as a potential buying opportunity, though. Moreover, it's critical to always look for businesses that have strong financial positions. This means the ability to generate lots of free cash flow, as well as having a robust balance sheet. Carvana doesn't possess these attributes today, but a company like Apple does. In fact, the iPhone maker's debt-service coverage ratio, which measures its ability to pay off its obligations, was 5.1 during the first six months of its fiscal 2023. That's very good. But Apple's shares are historically expensive right now. A business that isn't a value trap and that sells at an attractive valuation is PayPal (NASDAQ: PYPL). The digital payments leader currently has 433 million active accounts and processed $1.36 trillion of total payment volume in 2022, up 9% year over year. And as of this writing, shares trade at a P/E ratio of 28.2, near their lowest multiple ever. This is a good example of a great stock on sale right now. Be prepared for volatility Now that we've discussed that finding high-quality businesses that have strong financial positions is of the utmost importance, investors should prepare themselves mentally for a bumpy ride. Investing in the stock market can lead to life-changing wealth over time, but volatility is something that can't be avoided. That's because investor sentiment can shift at the drop of a hat. But zooming out and looking at long stretches of time proves that the stock market historically goes up. A popular metric to gauge volatility is the Chicago Board Options Exchange Volatility Index, otherwise known a\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0115", "answer_numeric": -0.01148, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0115 (i.e., on a bad day with 5% probability, the loss exceeds 1.15%). CVaR(95%) = -0.0144.", "metadata": {"var": -0.01148, "cvar": -0.014417, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230928_0045", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-09-28", "context_summary": "USMV: 60-day return history, mean=-0.0003, std=0.0049.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=-0.0003, std=0.0049, min=-0.0123, max=0.0088\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-27] [\"Is ProShares S&P Technology Dividend Aristocrats ETF (TDV) a Strong ETF Right Now? Launched on 11/05/2019, the ProShares S&P Technology Dividend Aristocrats ETF (TDV) is a smart beta exchange traded fund offering broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Because market cap weighted indexes provide a low-cost, convenient, and transparent way of replicating market returns, they work well for investors who believe in market efficiency. If you're the kind of investor who would rather try and beat the market through good stock selection, then smart beta funds are your best choice; this fund class is known for tracking non-cap weighted strategies. These indexes attempt to select stocks that have better chances of risk-return performance, based on certain fundamental characteristics or a combination of such characteristics. While this space offers a number of choices to investors, including simplest equal-weighting, fundamental weighting and volatility/momentum based weighting methodologies, not all these strategies have been able to deliver superior results. Fund Sponsor & Index The fund is managed by Proshares. TDV has been able to amass assets over $203.91 million, making it one of the average sized ETFs in the Technology ETFs. TDV seeks to match the performance of the S&P TECHNOLOGY DIVIDEND ARISTOCRATS INDX before fees and expenses. The S&P Technology Dividend Aristocrats Index targets companies from information technology, internet and direct marketing retail, interactive home entertainment, and interactive media and services segments of the economy. Cost & Other Expenses When considering an ETF's total return, expense ratios are an important factor. And, cheaper funds can significantly outperform their more expensive cousins in the long term if all other factors remain equal. Operating expenses on an annual basis are 0.45% for TDV, making it one of the cheaper products in the space. It has a 12-month trailing dividend yield of 1.38%. Performance and Risk The ETF return is roughly 12.29% and is up about 21.22% so far this year and in the past one year (as of 09/27/2023), respectively. TDV has traded between $49.99 and $67.88 during this last 52-week period. The fund has a beta of 1.05 and standard deviation of 20.40% for the trailing three-year period. With about 39 holdings, it has more concentrated exposure than peers. Alternatives ProShares S&P Technology Dividend Aristocrats ETF is an excellent option for investors seeking to outperform the Technology ETFs segment of the market. There are other ETFs in the space which investors could consider as well. IShares Core Dividend Growth ETF (DGRO) tracks Morningstar US Dividend Growth Index and the Vanguard Dividend Appreciation ETF (VIG) tracks NASDAQ US Dividend Achievers Select Index. ISha\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0078", "answer_numeric": -0.007761, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0078 (i.e., on a bad day with 5% probability, the loss exceeds 0.78%). CVaR(95%) = -0.0110.", "metadata": {"var": -0.007761, "cvar": -0.010973, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230531_0048", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-05-31", "context_summary": "XLK: 60-day return history, mean=0.0028, std=0.0124.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0028, std=0.0124, min=-0.0216, max=0.0373\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-30] [\"The 25 Best Growth Stocks for the Next 5 Years InvestorPlace - Stock Market News, Stock Advice & Trading Tips Looking for the best growth stocks to buy will take much more scrutiny in the current market environment. I wrote a column on Dec. 31, 2022 about 25 tech stocks to \\u201cbuy before they take off in 2023.\\u201d Almost all of them have rallied and are up substantially since they changed hands for peanuts back then. However, the situation now is very different after the rally this year, and most growth stocks do not provide compelling entry points. This does not mean that investors should shun all growth names. There are still high-quality growth stocks with excellent long-term potential, and jumping on board is a good idea no matter the market conditions. Of course, one may say there are risks of a recession, a debt default, etc. But there will always be some hubbub, and it\\u2019s not the best idea to always put too much thought into the worst-case scenarios. For example, investors who feared the worst in the summer of 2022 and closed their positions on a loss likely regret that decision now. No one has a crystal ball, and trying to avoid near-term losses will likely lead to losing out on future gains. That\\u2019s why most well-respected investors have made their fortunes through time in the market, not timing. Naturally, blindly buying does not apply to all growth stocks, and I will not include stocks with price targets too low from the current price point. That said, let\\u2019s look at the 25 best growth stocks to buy for the next five years in no particular order: Alphabet (GOOG, GOOGL) Source: salarko / Shutterstock.com Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) has repeatedly proven that it can continue competing in all sectors and catch up with new trends. The ad market slowdown since mid-2022 and then OpenAI\\u2019s ChatGPT integration with Bing caused panic about Google\\u2019s future, and the company did make a blunder by rushing Bard. However, it has since improved on Bard, and the chatbot is now a serious contender to ChatGPT. It is trained on a larger dataset and can theoretically perform more tasks. In addition, the initial hype surrounding Bing seems to be nothing more than a fad. Google\\u2019s search engine market share has only grown while Bing\\u2019s has declined. Alphabet\\u2019s ad revenue still lags behind but that will eventually recover in the long run. Thus, I see GOOG as a strong buy at this level. Microsoft (MSFT) Source: NYCStock / Shutterstock.com Things are only looking up for Microsoft (NASDAQ:MSFT) as the company fires on all cylinders. Microsoft is chipping away at the businesses of other tech giants and is looking to expand and threaten others. For example, Azure has grown to become a major AWS competitor, while Bing has kept Google tense. It is also spearheading development in AI with its investments in OpenAI. Microsoft is also investing massively in quantum computing, gaming and mixed reality, all of which are hi\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0145", "answer_numeric": -0.014461, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0145 (i.e., on a bad day with 5% probability, the loss exceeds 1.45%). CVaR(95%) = -0.0181.", "metadata": {"var": -0.014461, "cvar": -0.018064, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20241212_0051", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2024-12-12", "context_summary": "MTUM: 60-day return history, mean=0.0013, std=0.0081.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0013, std=0.0081, min=-0.0212, max=0.0228\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MTUM. Express as a decimal (e.g., -0.02).", "answer": "-0.0103", "answer_numeric": -0.010253, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0103 (i.e., on a bad day with 5% probability, the loss exceeds 1.03%). CVaR(95%) = -0.0149.", "metadata": {"var": -0.010253, "cvar": -0.014924, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230117_0054", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-01-17", "context_summary": "LINK-USD: 60-day return history, mean=0.0016, std=0.0303.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0016, std=0.0303, min=-0.0854, max=0.0901\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-16] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0416", "answer_numeric": -0.041615, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0416 (i.e., on a bad day with 5% probability, the loss exceeds 4.16%). CVaR(95%) = -0.0653.", "metadata": {"var": -0.041615, "cvar": -0.065262, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240610_0057", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-06-10", "context_summary": "XLU: 60-day return history, mean=0.0016, std=0.0096.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0016, std=0.0096, min=-0.0173, max=0.0271\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0130", "answer_numeric": -0.01298, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0130 (i.e., on a bad day with 5% probability, the loss exceeds 1.30%). CVaR(95%) = -0.0159.", "metadata": {"var": -0.01298, "cvar": -0.015888, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240201_0059", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2024-02-01", "context_summary": "UNG: 60-day return history, mean=-0.0016, std=0.0383.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=-0.0016, std=0.0383, min=-0.0858, max=0.0843\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for UNG. Express as a decimal (e.g., -0.02).", "answer": "-0.0542", "answer_numeric": -0.054168, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0542 (i.e., on a bad day with 5% probability, the loss exceeds 5.42%). CVaR(95%) = -0.0703.", "metadata": {"var": -0.054168, "cvar": -0.070269, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241225_0062", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-12-25", "context_summary": "ACWI: 60-day return history, mean=0.0002, std=0.0069.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0002, std=0.0069, min=-0.0302, max=0.0119\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ACWI. Express as a decimal (e.g., -0.02).", "answer": "-0.0094", "answer_numeric": -0.009371, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0094 (i.e., on a bad day with 5% probability, the loss exceeds 0.94%). CVaR(95%) = -0.0186.", "metadata": {"var": -0.009371, "cvar": -0.018613, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230920_0065", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2023-09-20", "context_summary": "SCHP: 60-day return history, mean=-0.0003, std=0.0037.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=-0.0003, std=0.0037, min=-0.0074, max=0.0098\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SCHP. Express as a decimal (e.g., -0.02).", "answer": "-0.0059", "answer_numeric": -0.005902, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0059 (i.e., on a bad day with 5% probability, the loss exceeds 0.59%). CVaR(95%) = -0.0066.", "metadata": {"var": -0.005902, "cvar": -0.006575, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230512_0068", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-05-12", "context_summary": "SOL-USD: 60-day return history, mean=0.0006, std=0.0371.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0006, std=0.0371, min=-0.0861, max=0.1023\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-11] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0551", "answer_numeric": -0.055073, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0551 (i.e., on a bad day with 5% probability, the loss exceeds 5.51%). CVaR(95%) = -0.0778.", "metadata": {"var": -0.055073, "cvar": -0.077849, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230504_0071", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-05-04", "context_summary": "LINK-USD: 60-day return history, mean=0.0013, std=0.0350.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0013, std=0.0350, min=-0.0940, max=0.0825\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-03] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0547", "answer_numeric": -0.054702, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0547 (i.e., on a bad day with 5% probability, the loss exceeds 5.47%). CVaR(95%) = -0.0732.", "metadata": {"var": -0.054702, "cvar": -0.073181, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240620_0072", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-06-20", "context_summary": "IWM: 60-day return history, mean=-0.0003, std=0.0108.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0003, std=0.0108, min=-0.0268, max=0.0216\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 2026-01-01 us-gaap:InvestmentAdviceMember 2023-03-31 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blk:DeferredCashCompensationPlanEquityMethodInvestmentsMember us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 us-gaap:InvestmentAdviceMember blk:FixedIncomeMember 2024-01-01 2024-03-31 0001364742 us-gaap:InvestmentAdviceMember blk:EquityNonETFIndexMember 2023-01-01 2023-03-31 0001364742 blk:PerformanceBasedRestrictedStockUnitsMember 2023-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:InvestmentsMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 blk:InstitutionalMember blk:RevenueByClientTypeMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 blk:TwoThousandTwentyFourRevolvingCreditFacilitiesMember 2024-03-31 0001364742 us-gaap:RealEstateFundsMember us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 2023-12-31 0001364742 blk:DeferredCashCompensationPlansMember 2024-03-31 0001364742 us-gaap:CorporateDebtSecuritiesMember 2024-03-31 0001364742 srt:EuropeMember 2024-03-31 0001364742 blk:PerformanceBasedStockOptionsMember 2024-01-01 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2024-03-31 0001364742 blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 srt:AsiaPacificMember 2023-01-01 2023-03-31 0001364742 us-gaap:RestrictedStockUnitsRSUMember 2023-01-01 2023-03-31 0001364742 us-gaap:HedgeFundsEquityMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0180", "answer_numeric": -0.017986, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0180 (i.e., on a bad day with 5% probability, the loss exceeds 1.80%). CVaR(95%) = -0.0219.", "metadata": {"var": -0.017986, "cvar": -0.021944, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240503_0075", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2024-05-03", "context_summary": "BNO: 60-day return history, mean=0.0016, std=0.0115.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=0.0016, std=0.0115, min=-0.0297, max=0.0302\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNO. Express as a decimal (e.g., -0.02).", "answer": "-0.0145", "answer_numeric": -0.014493, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0145 (i.e., on a bad day with 5% probability, the loss exceeds 1.45%). CVaR(95%) = -0.0263.", "metadata": {"var": -0.014493, "cvar": -0.026254, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230410_0078", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-04-10", "context_summary": "DOT-USD: 60-day return history, mean=-0.0006, std=0.0400.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0006, std=0.0400, min=-0.0767, max=0.1491\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-09] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0573", "answer_numeric": -0.057346, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0573 (i.e., on a bad day with 5% probability, the loss exceeds 5.73%). CVaR(95%) = -0.0672.", "metadata": {"var": -0.057346, "cvar": -0.067221, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230911_0081", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-09-11", "context_summary": "XLI: 60-day return history, mean=0.0003, std=0.0072.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0003, std=0.0072, min=-0.0170, max=0.0150\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-08] [\"What Lies Ahead for Apple ETFs After iPhone Use Ban? The tech giant Apple Inc. AAPL shed nearly $200 billion in market value in just two days amid the reports of China planning to expand a ban on the use of iPhones to government-backed agencies and state companies. Notably, China is Apple\\u2019s third-largest market, accounting for 18% of the company\\u2019s total revenues last year. The Wall Street Journal disclosed on Wednesday that Beijing had issued a directive instructing officials within central government agencies not to bring iPhones into their workplaces or use them for professional purposes. Bloomberg News later reported that this prohibition could extend to employees of state-owned enterprises and government-affiliated institutions. Bernstein analyst believes an iPhone ban on all Chinese government employees could cut Apple's phone sales in China by as much as 5%. However, most analysts are also calling the reaction overblown, considering China is a much larger market beyond government agencies. Wedbush Securities thinks the ban would affect less than 5,00,000 iPhones of the roughly 45 million he expects to be sold in the country over the next 12 months. The rumored restriction on iPhones comes closely after Huawei, a Chinese tech giant, launched its new premium smartphone. Bank of America analysts found the timing of these events to be noteworthy. Growth Prospects One of the primary motivations to invest in Apple is its dominant presence in the consumer tech landscape, positioning it favorably for expansion into rapidly growing sectors like artificial intelligence (AI) and virtual/augmented reality (VR/AR). These areas are anticipated to see compound annual growth rates exceeding 30% until 2030 (read: Guide to Artificial Intelligence ETFs). Historically, Apple has demonstrated an ability to penetrate new markets and swiftly capture significant market share. With the recent launch of its VR/AR headset, the Vision Pro, in June, Apple's growth potential seems even more promising. Additionally, the iPhone maker is expanding into new markets. Apple's Services segment, which includes the App Store, iCloud, Apple Music, Apple TV+ and Apple Arcade, has been a significant growth driver. With a growing global user base, these services are expected to generate massive revenues. Solid Zacks Estimates Apple boasts the world\\u2019s highest stock market valuation, at nearly $2.8 trillion. It has seen positive earnings estimate revision of a penny for both the current and the next fiscal year over the past 30 days. Apple currently has an average brokerage recommendation (ABR) of 1.64 on a scale of 1 to 5 (Strong Buy to Strong Sell), calculated based on the actual recommendations made by 29 brokerage firms. The current ABR compares to an ABR of 1.64 a month ago based on 29 recommendations. Of the 29 recommendations deriving the current ABR, 18 are Strong Buy and three are Buy. Strong Buy and Buy, respectively, account for 62.07% and 10.34% of all rec\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLI. Express as a decimal (e.g., -0.02).", "answer": "-0.0106", "answer_numeric": -0.010614, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0106 (i.e., on a bad day with 5% probability, the loss exceeds 1.06%). CVaR(95%) = -0.0140.", "metadata": {"var": -0.010614, "cvar": -0.014012, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240411_0084", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2024-04-11", "context_summary": "HYG: 60-day return history, mean=0.0001, std=0.0031.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0001, std=0.0031, min=-0.0088, max=0.0077\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for HYG. Express as a decimal (e.g., -0.02).", "answer": "-0.0047", "answer_numeric": -0.004669, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0047 (i.e., on a bad day with 5% probability, the loss exceeds 0.47%). CVaR(95%) = -0.0072.", "metadata": {"var": -0.004669, "cvar": -0.007206, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230929_0087", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-09-29", "context_summary": "VEA: 60-day return history, mean=-0.0006, std=0.0082.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=-0.0006, std=0.0082, min=-0.0195, max=0.0190\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-28] [\"US STOCKS-Wall St set for lower open on rate jitters; Powell on deck By Ankika Biswas and Shashwat Chauhan Sept 28 (Reuters) - Wall Street's main indexes eyed a lower open on Thursday aselevated oil prices muddled the inflation outlook amid worries over prolonged restrictive monetary policy, while investors assessed data and awaited Federal Reserve chief Jerome Powell's remarks. The scope for interest rates staying higher for longer than anticipated has solidified with soaring energy prices keeping headline inflation elevated. Deepening the concerns, U.S. oil futures jumped to a more than one-year high on Thursday. Riding on the back of higher crude prices, energy .SPNY is set to emerge as the only major S&P 500 sector to notch monthly gains. Meanwhile, rate-sensitive information technology .SPLRCT and real estate .SPLRCT were on track to be the worst hit. Further, data showed the U.S. economy maintained a fairly strong pace of growth in the second quarter, the government confirmed on Thursday, and appears to have gathered momentum this quarter amid a resilient labor market. \\\"A sharp rise in unemployment and claims isn't a prerequisite for the Fed to stop raising rates,\\\" said Nancy Vanden Houten, lead U.S. economist at Oxford Economics. \\\"Fed Chair Powell made clear last week, however, that the Fed needs to see other signs that the labor market is continuing to come into better balance if it is to refrain from further rate hikes.\\\" As U.S. Treasury yields resumed their uptrend after briefly slipping following the data, megacap growth stocks including Apple AAPL.O, Microsoft MSFT.O, Amazon.com AMZN.O and Tesla TSLA.O shed between 0.1% and 1.2% in premarket trading. At 8:52 a.m. ET, Dow e-minis 1YMcv1 were down 32 points, or 0.09%, S&P 500 e-minis EScv1 were down 6.75 points, or 0.16%, and Nasdaq 100 e-minis NQcv1 were down 45 points, or 0.31%. All the three indexes are set for their first quarterly decline in 2023. Also on radar will be comments by Powell at 4 p.m. ET, as well as remarks by voting member Lisa Cook during the day. With a partial government shutdown just three days away, a procedural vote on a bipartisan short-term spending measure by the Senate on Thursday will also be closely watched. Among individual movers, Micron TechnologyMU.O dropped 2.8% after forecasting a bigger-than-expected first-quarter loss. WorkdayWDAY.O dipped 9.8% after the human resources software company lowered its subscription revenue growth outlook for the next three years. Meme darling GameStopGME.N jumped 7.3% after the company named billionaire activist investor Ryan Cohen as its CEO and chairman. (Reporting by Ankika Biswas and Shashwat Chauhan; Editing by Sriraj Kalluvila and Maju Samuel) ((Ankika.Biswas@thomsonreuters.com; Shashwat.Chauhan@thomsonreuters.com)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"SCHX ETF: A Large-Cap ETF for Large Gains The Schwab U.S.\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VEA. Express as a decimal (e.g., -0.02).", "answer": "-0.0145", "answer_numeric": -0.014467, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0145 (i.e., on a bad day with 5% probability, the loss exceeds 1.45%). CVaR(95%) = -0.0180.", "metadata": {"var": -0.014467, "cvar": -0.018046, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231106_0090", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-11-06", "context_summary": "XLY: 60-day return history, mean=-0.0010, std=0.0132.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0010, std=0.0132, min=-0.0277, max=0.0265\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AAPL 2023-11-03] aapl-20230930 false 2023 FY 0000320193 P1Y 67 P1Y 25 P1Y 7 1 http://fasb.org/us-gaap/2023#MarketableSecuritiesCurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesNoncurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesCurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesNoncurrent http://fasb.org/us-gaap/2023#LongTermDebtCurrent http://fasb.org/us-gaap/2023#LongTermDebtNoncurrent 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us-gaap:FairValueInputsLevel2Member 2023-09-30 0000320193 us-gaap:BankTimeDepositsMember us-gaap:FairValueInputsLevel2Member 2023-09-30 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CommercialPaperMember 2023-09-30 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2023-09-30 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-09-30 0000320193 us-gaap:AssetBackedSecuritiesMember us-gaap:FairValueInputsLevel2Member 2023-09-30 0000320193 us-gaap:FairValueInputsLevel2Member 2023-09-30 0000320193 us-gaap:CashMember 2022-09-24 0000320193 us [...TRUNCATED...] Document Set for the consolidated financial statements and accompanying notes in Part II, Item 8, “Financial Statements and Supplementary Data” of this Annual Report on Form 10-K. Apple Inc. | 2023 Form 10-K | 56 Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 104** Inline XBRL for the cover page of this Annual Report on Form 10-K, included in the Exhibit 101 Inline XBRL Document Set. * Indicates management contract or compensatory plan or arrangement. ** Filed herewith. *** Furnished herewith. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Registrant hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. Item 16.    Form 10-K Summary None. Apple Inc. | 2023 Form 10-K | 57 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: November 2, 2023 Apple Inc. By: /s/ Luca Maestri Luca Maestri Senior Vice President, Chief Financial Officer Power of Attorney KNOW ALL PERSONS BY THESE PRESENTS, that each person whose signature appears below constitutes and appoints Timothy D. Cook and Luca Maestri, jointly and severally, his or her attorneys-in-fact, each with the power of substitution, for him or her in any and all capacities, to sign any amendments to this Annual Report on Form 10-K, and to file the same, with exhibits thereto and other documents in connection therewith, with the Securities and Exchange Commission, hereby ratifying and confirming all that each of said attorneys-in-fact, or his substitute or substitutes, may do or cause to be done by virtue hereof. Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated: Name Title Date /s/ Timothy D. Cook Chief Executive Officer and Director (Principal Executive Officer) November 2, 2023 TIMOTHY D. COOK /s/ Luca Maestri Senior Vice President, Chief Financial Officer (Principal Financial Officer) November 2, 2023 LUCA MAESTRI /s/ Chris Kondo Senior Director of Corporate Accounting (Principal Accounting Officer) November 2, 2023 CHRIS KONDO /s/ James A. Bell Director November 2, 2023 JAMES A. BELL /s/ Al Gore Director November 2, 2023 AL GORE /s/ Alex Gorsky Director November 2, 2023 ALEX GORSKY /s/ Andrea Jung Director November 2, 2023 ANDREA JUNG /s/ Arthur D. Levinson Director and Chair of the Board November 2, 2023 ARTHUR D. LEVINSON /s/ Monica Lozano Director November 2, 2023 MONICA LOZANO /s/ Ronald D. Sugar Director November 2, 2023 RONALD D. SUGAR /s/ Susan L. Wagner Director November 2, 2023 SUSAN L. WAGNER Apple Inc. | 2023 Form 10-K | 58\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0238", "answer_numeric": -0.023792, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0238 (i.e., on a bad day with 5% probability, the loss exceeds 2.38%). CVaR(95%) = -0.0261.", "metadata": {"var": -0.023792, "cvar": -0.026061, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20240619_0093", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-06-19", "context_summary": "QUAL: 60-day return history, mean=0.0009, std=0.0071.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0009, std=0.0071, min=-0.0148, max=0.0161\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0128", "answer_numeric": -0.012758, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0128 (i.e., on a bad day with 5% probability, the loss exceeds 1.28%). CVaR(95%) = -0.0142.", "metadata": {"var": -0.012758, "cvar": -0.014151, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20231102_0096", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-11-02", "context_summary": "BTC-USD: 60-day return history, mean=0.0054, std=0.0192.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0054, std=0.0192, min=-0.0259, max=0.1031\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-01] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0163", "answer_numeric": -0.016322, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0163 (i.e., on a bad day with 5% probability, the loss exceeds 1.63%). CVaR(95%) = -0.0219.", "metadata": {"var": -0.016322, "cvar": -0.021874, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230126_0099", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-01-26", "context_summary": "LINK-USD: 60-day return history, mean=0.0000, std=0.0299.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0000, std=0.0299, min=-0.0854, max=0.0670\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-25] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0490", "answer_numeric": -0.048991, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0490 (i.e., on a bad day with 5% probability, the loss exceeds 4.90%). CVaR(95%) = -0.0689.", "metadata": {"var": -0.048991, "cvar": -0.068868, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230503_0102", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-05-03", "context_summary": "FXI: 60-day return history, mean=-0.0019, std=0.0167.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0019, std=0.0167, min=-0.0376, max=0.0407\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-02] [\"Top Stocks To Buy Now? 3 Dow Stocks In Focus Today The Dow Jones Industrial Average (DJIA), commonly known as \\u201cthe Dow,\\u201d is a prominent stock market index that monitors the performance of 30 leading blue-chip companies listed on the New York Stock Exchange (NYSE) and the NASDAQ. The DJIA stands as one of the oldest and most respected market indices globally. The index acts as a gauge of the U.S. economy\\u2019s well-being, offering investors a broad overview of market performance while reflecting the robustness of various sectors, including technology, finance, healthcare, and consumer goods. In addition, Dow 30 stocks encompass the 30 constituent firms of the DJIA, chosen to portray a diverse array of industries and regarded as some of the most stable and established corporations in the United States. It is crucial to understand that the DJIA is a price-weighted index, which means the index\\u2019s value is determined by the sum of its constituents\\u2019 stock prices, adjusted for stock splits and dividends. This calculation method may result in greater influence from higher-priced stocks, rendering the index less representative of the overall market than other indices, such as the market-cap-weighted S&P 500. Bearing that in mind, let\\u2019s explore Dow Jones stocks to watch today. Dow Stocks To Watch Today Apple, Inc. (NASDAQ: AAPL) Nike, Inc. (NYSE: NKE) Honeywell International Inc. (NASDAQ: HON) Apple (AAPL Stock) Apple, Inc. (AAPL) is a globally renowned technology company that designs, manufactures, and markets consumer electronics, software, and online services. Best known for its flagship products such as the iPhone, iPad, Mac computers, and Apple Watch. Meanwhile, this week Apple is set to report its second quarter 2023 financial results. In detail, the company will release its Q2 2023 earnings results this Thursday, May 4, 2023, after the U.S. stock market closes. To recap, in Q1 2023, Apple reported earnings of $1.88 per share, with revenue of $117.2 billion. Year-to-date, shares of Apple stock have increased by 34.68% thus far. While, during Tuesday\\u2019s mid-morning trading session, AAPL stock is trading at $168.42 per share. Source: TD Ameritrade TOS [Read More] Good Stocks To Buy Right Now? 3 Tech Stocks In Focus Nike (NKE Stock) Next, Nike, Inc. (NKE) is a multinational corporation specializing in the design, development, manufacturing, and marketing of athletic footwear, apparel, equipment, and accessories. For a sense of scale, Nike is one of the world\\u2019s largest suppliers of athletic shoes and apparel. Back in March, Nike reported its most recent 3rd quarter of 2023 financial results. Diving in, the company posted an EPS of $0.79 on revenue of $12.4 billion. This came in better than analysts\\u2019 consensus estimate for the quarter which was earnings of $0.52 per share, with revenue estimates of $11.5 billion. Additionally, Nike also reported that revenue grew by 14.0% versus the same period, the prior year. In \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for FXI. Express as a decimal (e.g., -0.02).", "answer": "-0.0278", "answer_numeric": -0.02782, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0278 (i.e., on a bad day with 5% probability, the loss exceeds 2.78%). CVaR(95%) = -0.0324.", "metadata": {"var": -0.02782, "cvar": -0.032364, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230130_0105", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2023-01-30", "context_summary": "SGOV: 60-day return history, mean=0.0001, std=0.0002.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0001, std=0.0002, min=-0.0001, max=0.0007\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "-0.0000", "answer_numeric": -5e-06, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0001.", "metadata": {"var": -5e-06, "cvar": -0.0001, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230810_0108", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-08-10", "context_summary": "BNB-USD: 60-day return history, mean=0.0005, std=0.0198.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0198, min=-0.0341, max=0.0556\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-09] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0323", "answer_numeric": -0.032325, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0323 (i.e., on a bad day with 5% probability, the loss exceeds 3.23%). CVaR(95%) = -0.0333.", "metadata": {"var": -0.032325, "cvar": -0.03335, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231030_0111", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-10-30", "context_summary": "IVV: 60-day return history, mean=-0.0014, std=0.0077.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=-0.0014, std=0.0077, min=-0.0165, max=0.0143\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-27] [\"Big Banks and Big Rates In this podcast, Motley Fool host Dylan Lewis and analysts Emily Flippen and Jason Moser discuss: What big interest rates mean for big banks and the latest insights from Jamie Dimon. Pepsi's earnings showing signs that growth might be propped up by price hikes. Atlassian's $1 billion acquisition of Loom. The market reaction to the Birkenstock IPO. Spotify's latest audio push. Two stocks worth watching: Outset Medical and Twilio. Bloomberg's Zeke Faux talks with Motley Fool host Deidre Woollard about the trial of FTX's Sam Bankman Fried. To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. To get started investing, check out our quick-start guide to investing in stocks. A full transcript follows the video. 10 stocks we like better than Walmart When our analyst team has an investing tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now... and Walmart wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of 10/16/2023 This video was recorded on Oct. 13, 2023. Dylan Lewis: We've got an update on what Big Banks are doing with big rates and one acquisition announced, another one closed. Motley Fool Money starts now. Jason Moser: From Fool Global headquarters, this is Motley Fool Money. Dylan Lewis: It's the Motley Fool Money radio show. I'm Dylan Lewis, joining me in studio, Motley Fool Senior Analysts Emily Flippen and Jason Moser. Great to have you both here. Hey. Emily Flippen: Hey. Dylan Lewis: We've got the story from the courthouse at the trial of Sam Bank, been freed. A tepid reception for a new IPO and a big deal, finally coming to a close. But first, we've got earnings, results that will have us checking in on two major stories, interest rates and pricing power. Jason, we're going to start with interest rates and the Big Banks. They reported Friday morning getting the earnings party started. What did you see in results from JP Morgan and Wells Fargo? Jason Moser: It seems on a day where the markets viewing things from the glass-half-empty perspective, these banks are at least presenting a little green for us. I think the big headline for these banks, of course, is the higher rate environment. Rates hit banks in a number of different ways. Some good, some bad. They're going to pay up for deposits as consumers shift holdings and higher yielding instruments, they benefit from higher interest payments on those mortgage loans. By the same token, higher borrowing costs tamp down demand for those loans. Then the bonds owned by these banks, they start to fall in value as these yields rise. It hits their capital positions. I think that beyond the macro stuff, I mean that's one thing to keep an eye on is the capital requirements as this lands\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IVV. Express as a decimal (e.g., -0.02).", "answer": "-0.0136", "answer_numeric": -0.013562, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0136 (i.e., on a bad day with 5% probability, the loss exceeds 1.36%). CVaR(95%) = -0.0152.", "metadata": {"var": -0.013562, "cvar": -0.015193, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20241129_0114", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-11-29", "context_summary": "EEM: 60-day return history, mean=0.0002, std=0.0116.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0002, std=0.0116, min=-0.0250, max=0.0317\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 2024-01-28 0001045810 us-gaap:CommonStockMember 2024-07-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-28 0001045810 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-29 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-07-29 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-27 0001045810 us-gaap:RetainedEarningsMember 2024-10-27 0001045810 us-gaap:CommonStockMember 2023-07-30 0001045810 us-gaap:AdditionalPaidInCapitalMember 2023-07-30 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-30 0001045810 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us-gaap:CommonStockMember 2024-01-29 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-01-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2023-01-29 0001045810 us-gaap:AdditionalPaidInCapitalMember 2023-01-29 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-29 0001045810 us-gaap:RetainedEarningsMember 2023-01-29 0001045810 2023-01-29 0001045810 us-gaap:RetainedEarningsMember 2023-01-30 2023-10-29 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-30 2023-10-29 0001045810 us-gaap:CommonStockMember 2023-01-30 2023-10-29 0001045810 us-gaap:AdditionalPaidInCapitalMember 2023-01-30 2023-10-29 0001045810 2024-05-01 2024-05-31 0001045810 2024-06-06 0001045810 2024-06-07 0001045810 us-gaap:OperatingLeaseLeaseNotYetCommencedMember 2024-10-27 0001045810 srt:MinimumMember 2024-10-27 0001045810 srt:MaximumMember 2024-10-27 0001045810 us-gaap:CostOfSalesMember 2024-07-29 2024-10-27 0001045810 us-gaap:CostOfSalesMember 2023-07-31 2023-10-29 0001045810 us-gaap:CostOfSalesMember 2024-01-29 2024-10-27 0001045810 us-gaap:CostOfSalesMember 2023-01-30 2023-10-29 0001045810 us-gaap:ResearchAndDevelopmentExpenseMember 2024-07-29 2024-10-27 0001045810 us-gaap:ResearchAndDevelopmentExpenseMember 2023-07-31 2023-10-29 0001045810 us-gaap:ResearchAndDevelopmentExpenseMember 2024-01-29 2024-10-27 0001045810 us-gaap:ResearchAndDevelopmentExpenseMember 2023-01-30 2023-10-29 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-07-29 2024-10-27 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2023-07-31 2023-10-29 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-01-29 2024-10-27 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2023-01-30 2023-10-29 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2024-01-28 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2024-01-29 2024-10-27 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2024-10-27 0001045810 us-gaap:EmployeeStockMember 2024-01-29 2024-10-27 0001045810 us-gaap:USTreasurySecuritiesMember 2024-10-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2024-10-27 0001045810 us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-10-27 0001045810 us-gaap:CertificatesOfDepositMember 2024-10-27 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-10-27 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-29 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-07-29 2024-10-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2024-01-28 0001045810 us-gaap:USTreasurySecuritiesMember 2024-01-28 0001045810 us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-01-28 0001045810 us-gaap:CertificatesOfDepositMember 2024-01-28 0001045810 us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0193", "answer_numeric": -0.019255, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0193 (i.e., on a bad day with 5% probability, the loss exceeds 1.93%). CVaR(95%) = -0.0238.", "metadata": {"var": -0.019255, "cvar": -0.023821, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20230411_0117", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-04-11", "context_summary": "ADA-USD: 60-day return history, mean=0.0022, std=0.0371.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0022, std=0.0371, min=-0.0723, max=0.1162\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-10] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0393", "answer_numeric": -0.039345, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0393 (i.e., on a bad day with 5% probability, the loss exceeds 3.93%). CVaR(95%) = -0.0581.", "metadata": {"var": -0.039345, "cvar": -0.058103, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231107_0119", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-11-07", "context_summary": "SOL-USD: 60-day return history, mean=0.0134, std=0.0415.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0134, std=0.0415, min=-0.0616, max=0.1141\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-06] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0411", "answer_numeric": -0.041066, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0411 (i.e., on a bad day with 5% probability, the loss exceeds 4.11%). CVaR(95%) = -0.0545.", "metadata": {"var": -0.041066, "cvar": -0.054483, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240617_0121", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-06-17", "context_summary": "ADA-USD: 60-day return history, mean=-0.0007, std=0.0271.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0007, std=0.0271, min=-0.0506, max=0.0792\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0369", "answer_numeric": -0.036892, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0369 (i.e., on a bad day with 5% probability, the loss exceeds 3.69%). CVaR(95%) = -0.0436.", "metadata": {"var": -0.036892, "cvar": -0.043552, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231201_0124", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-12-01", "context_summary": "XLI: 60-day return history, mean=0.0002, std=0.0088.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0002, std=0.0088, min=-0.0244, max=0.0204\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-30] [\"UK antitrust regulator wins appeal over Apple probe Adds details from ruling and CMA comment in paragraphs 4-6 LONDON, Nov 30 (Reuters) - Britain's antitrust regulator won an appeal on Thursday against a ruling blocking its investigation into Apple Inc's AAPL.O mobile browser and cloud gaming services. The Competition and Markets Authority (CMA) opened a full investigation last year into the dominance of Apple and Alphabet Inc's Google GOOGL.O in mobile browsers, and the possibility of the iPhone maker restricting the cloud gaming market through its app store. Apple argued that the CMA had \\\"no power\\\" to launch such an inquiry because it did so too late and the Competition Appeal Tribunal (CAT) ruled in Apple's favour in March, but the Court of Appeal in London overturned that decision on Thursday. Judge Nicholas Green said in a written ruling that the CAT had \\\"lost sight\\\" of the CMA's role to \\\"promote competition and protect consumers\\\". Sarah Cardell, chief executive of the CMA, welcomed the decision which she said \\\"gives the CMA the backing it needs to protect consumers and promote competition in UK\\\". She added that the CMA is ready to reopen the investigation \\\"when the legal process is complete\\\". (Reporting by Sam Tobin; editing by Michael Holden) ((Sam.Tobin@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Japan aircon king Daikin looks to custom chips for energy savings By Sam Nussey and Miho Uranaka TOKYO, Dec 1 (Reuters) - Japanese air conditioner maker Daikin Industries 6367.T is turning to custom-made semiconductors to eke out energy savings, as companies increasingly look to bespoke chip designs to enhance performance. As tech heavyweights such as Apple AAPL.O and Amazon AMZN.O spend heavily on custom cutting-edge chips, companies using legacy chips are also looking to introduce custom silicon. Osaka-headquartered Daikin, which expects to make 10 million home air conditioners in the current financial year, said it is partnering with a Japanese design company to customise logic chips for inverters used in its air conditioners. Inverters adjust the speed of an air conditioner's motor to save energy. They are standard in Japan and the European Union but less common in the United States. The custom chips, to be made by Taiwan's TSMC 2330.TW, cost more than off-the-shelf alternatives but offer better energy efficiency and allow a reduction in the use of other components, according to a Daikin executive. \\\"To bring out the full performance of an air conditioner's compressor and motor, we need to improve chip performance or we will hit a limit,\\\" Yuji Yoneda, general manger of Daikin's technology and innovation centre, said in an interview. Daikin plans to start introducing the chips in high-end air conditioners from 2025 and is looking at using them in about a fifth of units by the end of the decade. The company, which deve\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLI. Express as a decimal (e.g., -0.02).", "answer": "-0.0130", "answer_numeric": -0.013037, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0130 (i.e., on a bad day with 5% probability, the loss exceeds 1.30%). CVaR(95%) = -0.0188.", "metadata": {"var": -0.013037, "cvar": -0.01877, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231113_0127", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-11-13", "context_summary": "XLF: 60-day return history, mean=0.0000, std=0.0089.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0000, std=0.0089, min=-0.0183, max=0.0234\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-10] [\"RPT-EXPLAINER-What is China\\u2019s Singles Day, and how is it celebrated? By Granth Vanaik Nov 9 (Reuters) - Black Friday? No. Cyber Monday? Nope. Prime Day? Absolutely not. The world's biggest shopping event happens in China each year - and it's called Singles Day. Originally a holiday to celebrate being single, as a counter to Valentine's Day, the event has grown into a weeks-long online shopping festival that peaks on Nov. 11. WHEN DID THE IDEA OF SINGLES DAY ORIGINATE? The idea for Singles Day had originated at China's Nanjing University back in 1993 and was originally called \\\"Bachelor's Day.\\\" On the day, single people treat themselves with gifts and presents, while also organizing social gatherings and parties. HOW MUCH DO CONSUMERS SPEND? Last year, the total value of goods sold during the shopping bonanza - also known as \\\"Double 11\\\" - totaled 1.15 trillion yuan ($157.97 billion), according to data from consultancy firm Bain. That is more than four times the $35.3 billion U.S. shoppers spent last year during Cyber Week, the period from Black Friday to Cyber Monday, per data from Adobe Analytics. Cyber Monday immediately follows Black Friday, which falls on the day after the U.S. Thanksgiving Day holiday, the busiest shopping day of the year in the United States. But growth has been slowing even as overall sales for Singles Day hit record highs, with last year's 3% rise marking the slowest increase ever. The event has in recent years lost some of its novelty with the rise of other shopping festivals in China,including the midyear \\\"618\\\" sales that are the country's second largest. Strict COVID-19 curbs in China impacted sales last year, but several industry experts are expecting a rebound, as the economy improves and livestream sales remain robust. \\\"We're optimistic about growth this year because the recovery seems to be stabilizing and consumption is on a more clear upward trend,\\\" said Jacob Cooke, co-founder and CEO of Beijing-based WPIC Marketing + Technologies. His e-commerce consultancy firm expects sales for the Chinese shopping event to rise in the range between 14% and 18% from last year, which is higher than Adobe's projection for a 5.4% rise in Cyber Week sales. WHAT MAJOR BRANDS AND PRODUCTS ARE SHOPPERS BUYING? JD.com 9618.HK joined in 2012 and PDD Holdings-owned PDD.O Pinduoduo has also become a significant player, offering low cost products in competition with Alibaba-owned Tmall and Taobao platforms. Last year, Chinese shoppers spent more on essentials, supplements, vitamins and pet-care products. Those products are expected to stay in demand this year, along with more lifestyle-focused products such as athletic wear and sports equipment. \\\"There is enormous demand among Chinese consumers for products and services that improve their lifestyles and facilitate self-expression,\\\" Cooke said. HOW DOES SINGLES DAY COMPARE TO BLACK FRIDAY? In comparison, U.S. shoppers last year had bought more Pokemon toys, Hot Wheels, TVs,\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0160", "answer_numeric": -0.015973, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0160 (i.e., on a bad day with 5% probability, the loss exceeds 1.60%). CVaR(95%) = -0.0174.", "metadata": {"var": -0.015973, "cvar": -0.01743, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231116_0130", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-11-16", "context_summary": "BTC-USD: 60-day return history, mean=0.0061, std=0.0209.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0061, std=0.0209, min=-0.0264, max=0.1031\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-15] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0163", "answer_numeric": -0.016322, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0163 (i.e., on a bad day with 5% probability, the loss exceeds 1.63%). CVaR(95%) = -0.0220.", "metadata": {"var": -0.016322, "cvar": -0.022043, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241111_0133", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2024-11-11", "context_summary": "DBB: 60-day return history, mean=0.0008, std=0.0135.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=0.0008, std=0.0135, min=-0.0296, max=0.0276\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DBB. Express as a decimal (e.g., -0.02).", "answer": "-0.0208", "answer_numeric": -0.020818, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0208 (i.e., on a bad day with 5% probability, the loss exceeds 2.08%). CVaR(95%) = -0.0256.", "metadata": {"var": -0.020818, "cvar": -0.025631, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240305_0135", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-03-05", "context_summary": "QQQ: 60-day return history, mean=0.0023, std=0.0094.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0023, std=0.0094, min=-0.0198, max=0.0289\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 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2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2022-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2022-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QQQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0150", "answer_numeric": -0.015009, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0150 (i.e., on a bad day with 5% probability, the loss exceeds 1.50%). CVaR(95%) = -0.0175.", "metadata": {"var": -0.015009, "cvar": -0.017522, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230302_0138", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-03-02", "context_summary": "XRP-USD: 60-day return history, mean=0.0023, std=0.0249.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0023, std=0.0249, min=-0.0463, max=0.0652\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-01] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0392", "answer_numeric": -0.039216, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0392 (i.e., on a bad day with 5% probability, the loss exceeds 3.92%). CVaR(95%) = -0.0424.", "metadata": {"var": -0.039216, "cvar": -0.042417, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241015_0141", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-10-15", "context_summary": "IVV: 60-day return history, mean=0.0011, std=0.0101.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0011, std=0.0101, min=-0.0295, max=0.0229\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IVV. Express as a decimal (e.g., -0.02).", "answer": "-0.0191", "answer_numeric": -0.019079, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0191 (i.e., on a bad day with 5% probability, the loss exceeds 1.91%). CVaR(95%) = -0.0243.", "metadata": {"var": -0.019079, "cvar": -0.024282, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240701_0144", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-07-01", "context_summary": "VEA: 60-day return history, mean=-0.0000, std=0.0078.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=-0.0000, std=0.0078, min=-0.0176, max=0.0146\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 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0001364742 us-gaap:HedgeFundsEquityMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VEA. Express as a decimal (e.g., -0.02).", "answer": "-0.0142", "answer_numeric": -0.014188, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0142 (i.e., on a bad day with 5% probability, the loss exceeds 1.42%). CVaR(95%) = -0.0167.", "metadata": {"var": -0.014188, "cvar": -0.016667, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240313_0146", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-03-13", "context_summary": "SOL-USD: 60-day return history, mean=0.0090, std=0.0364.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0090, std=0.0364, min=-0.0795, max=0.1012\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0444", "answer_numeric": -0.044419, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0444 (i.e., on a bad day with 5% probability, the loss exceeds 4.44%). CVaR(95%) = -0.0708.", "metadata": {"var": -0.044419, "cvar": -0.070766, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230526_0149", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-05-26", "context_summary": "VEA: 60-day return history, mean=0.0003, std=0.0091.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0003, std=0.0091, min=-0.0276, max=0.0160\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-25] [\"Researchers find Israeli-made spyware deployed across Armenia By Raphael Satter and James Pearson LONDON, May 25 (Reuters) - Researchers have discovered Israeli-made Pegasus phone hacking software deployed against targets across Armenia, including reporters at a U.S. government-funded news organization, a report released on Thursday found. A team of researchers from digital rights group Access Now, human rights organization Amnesty International, Canadian internet watchdog Citizen Lab, Armenian digital defense group CyberHUB-AM and independent researcher Ruben Muradyan, said they had confirmed at least 12 cases in which espionage software made by Israel's NSO Group had been used against Armenian officials, journalists and organizers. What researchers were able to confirm \\\"is the tip of the iceberg,\\\" said Natalia Krapiva, the tech-legal counsel for Access Now. \\\"The targeting was quite extensive.\\\" Pegasus is one of many advanced espionage tools that affords hackers sweeping access to their targets' smartphones, allowing them to record calls, intercept messages and even transform the phones into portable listening devices. Researchers, lawmakers, and journalists have repeatedly accused the technology's maker, Israel-based NSO Group, of helping governments spy on political opponents. In 2021, the company was blacklisted by the U.S. government over human rights concerns. The company has previously disputed accusations of wrongdoing, saying its software is used to fight terrorism and serious crime. One of the alleged Armenian victims of NSO's spyware said those explanations do not reflect reality. \\\"That's a kind of ridiculous umbrella for the companies that create these products and the governments that use them,\\\" Armenian opposition broadcaster Samvel Farmanyan told Reuters. He added that his targeting was \\\"totally unacceptable (and had) nothing to do with the prevention of any type of crime or terrorism.\\\" AZERBAIJAN DENIES RESPONSIBILITY The researchers said they believed neighboring Azerbaijan, which has fought several wars with Armenia over the disputed chunk of territory known as Nagorno-Karabakh or Artsakh, was likely responsible for the hacking activity. That's in part because of \\\"extensive evidence\\\" that Azerbaijan's government has previously used Pegasus against its domestic opponents, said Amnesty's Donncha O Cearbhaill, referring to a 2021 investigation by Amnesty and other partners that found hundreds of Azeri phone numbers had been selected for targeting with Pegasus spyware. The Azeri Embassy in London said in a statement that Azerbaijan \\\"does not engage in such practices\\\" and \\\"does not spy on foreign citizens\\\". The Armenian government has in the past been implicated in the deployment of phone hacking software, including in a report published last year by Alphabet's GOOGL.O Google. While that report pointed to a different spyware, known as Predator, several Pegasus victims in Armenia said they feared their own government w\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VEA. Express as a decimal (e.g., -0.02).", "answer": "-0.0144", "answer_numeric": -0.014373, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0144 (i.e., on a bad day with 5% probability, the loss exceeds 1.44%). CVaR(95%) = -0.0206.", "metadata": {"var": -0.014373, "cvar": -0.020612, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230727_0152", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-07-27", "context_summary": "XLF: 60-day return history, mean=0.0012, std=0.0092.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0012, std=0.0092, min=-0.0229, max=0.0244\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-26] [\"Machine Learning Megatrends: 3 AI Stocks Set to Dominate InvestorPlace - Stock Market News, Stock Advice & Trading Tips There\\u2019s no denying the strength and momentum we\\u2019ve seen in AI stocks this year. In fact, the top AI stocks have played an enormous role in the stock market\\u2019s robust returns so far this year. While the S&P 500 was searching for direction in the first quarter, Microsoft (NASDAQ:MSFT) and Nvidia (NASDAQ:NVDA) were bombarding higher as catalyst after catalyst continued to pave the way for its AI advances. Together, the duo now accounts for more than $3.6 trillion in combined market capitalizations. However, they have ignited plenty of other stocks higher along the way, too. Some of these firms are well-known tech companies. Others are smaller, lesser-known entities in the high-growth space. Either way, the trend remains robust. Earlier this year, Billionaire investor Stanley Druckenmiller said AI could be as \\u201ctransformative as the internet.\\u201d If that\\u2019s the case, let\\u2019s look at a few of the top AI stocks to buy now. AI Stocks to Dominate: Nvidia (NVDA) Source: sdx15 / Shutterstock.com There\\u2019s no denying that Nvidia is the most dominant name in AI right now. In some measures, it has no competition, so while its stock gains are astronomical (and even somewhat comical), what\\u2019s going to stop Nvidia from printing money at this moment? Nothing! Shares are currently up more than 215% so far this year and up more than 300% from the 2022 lows. Going into earnings in late May, the stock was up almost 110%, and the bullish bets had been piling up. I distinctly remember most investors assuming it couldn\\u2019t go much higher, as it had made up almost all of its bear market losses and run a great deal going into the event. Then the company blew out expectations, while management guided for current-quarter revenue of roughly $11 billion vs. expectations of just $7 billion, and the stock erupted. Shares closed higher by almost 25% the next day and have now climbed 50% since that report. My point is, what if Nvidia has another massive revenue guidance this quarter? What company is stepping in to soak up the excess demand for its AI chips? For now, Nvidia remains at the forefront of AI domination. Best Machine Learning Stocks: Alphabet (GOOGL, GOOG) Source: IgorGolovniov / Shutterstock.com ChatGPT is owned by OpenAI, a firm that Microsoft had invested in previously but made another big investment in earlier this year. That\\u2019s as the company\\u2019s ChatGPT platform exploded in popularity, garnering more than 100 million active users in record time. In the minds of investors, that made Microsoft a top AI play seemingly overnight. To pour salt on the wound for Alphabet (NASDAQ:GOOGL, NASDAQ:GOOG), the company had a somewhat embarrassing gaff with its own AI chat platform, Bard. Now, there are a few things to take note of here. First, Alphabet hasn\\u2019t been the best at building out platforms outside of \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0118", "answer_numeric": -0.011764, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0118 (i.e., on a bad day with 5% probability, the loss exceeds 1.18%). CVaR(95%) = -0.0163.", "metadata": {"var": -0.011764, "cvar": -0.016314, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230627_0155", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-06-27", "context_summary": "XLRE: 60-day return history, mean=0.0004, std=0.0113.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0004, std=0.0113, min=-0.0271, max=0.0239\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-26] [\"Is Trending Stock Apple Inc. (AAPL) a Buy Now? Apple (AAPL) has been one of the most searched-for stocks on Zacks.com lately. So, you might want to look at some of the facts that could shape the stock's performance in the near term. Shares of this maker of iPhones, iPads and other products have returned +6.4% over the past month versus the Zacks S&P 500 composite's +5% change. The Zacks Computer - Mini computers industry, to which Apple belongs, has gained 8.7% over this period. Now the key question is: Where could the stock be headed in the near term? Although media reports or rumors about a significant change in a company's business prospects usually cause its stock to trend and lead to an immediate price change, there are always certain fundamental factors that ultimately drive the buy-and-hold decision. Earnings Estimate Revisions Here at Zacks, we prioritize appraising the change in the projection of a company's future earnings over anything else. That's because we believe the present value of its future stream of earnings is what determines the fair value for its stock. We essentially look at how sell-side analysts covering the stock are revising their earnings estimates to reflect the impact of the latest business trends. And if earnings estimates go up for a company, the fair value for its stock goes up. A higher fair value than the current market price drives investors' interest in buying the stock, leading to its price moving higher. This is why empirical research shows a strong correlation between trends in earnings estimate revisions and near-term stock price movements. Apple is expected to post earnings of $1.18 per share for the current quarter, representing a year-over-year change of -1.7%. Over the last 30 days, the Zacks Consensus Estimate has changed +0.1%. For the current fiscal year, the consensus earnings estimate of $5.99 points to a change of -2% from the prior year. Over the last 30 days, this estimate has remained unchanged. For the next fiscal year, the consensus earnings estimate of $6.64 indicates a change of +10.8% from what Apple is expected to report a year ago. Over the past month, the estimate has changed -0.1%. Having a strong externally audited track record, our proprietary stock rating tool, the Zacks Rank, offers a more conclusive picture of a stock's price direction in the near term, since it effectively harnesses the power of earnings estimate revisions. Due to the size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, Apple is rated Zacks Rank #3 (Hold). The chart below shows the evolution of the company's forward 12-month consensus EPS estimate: 12 Month EPS Projected Revenue Growth While earnings growth is arguably the most superior indicator of a company's financial health, nothing happens as such if a business isn't able to grow its revenues. After all, it's nearly impossible for a company to increase its earnings for an extended period witho\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLRE. Express as a decimal (e.g., -0.02).", "answer": "-0.0173", "answer_numeric": -0.017264, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0173 (i.e., on a bad day with 5% probability, the loss exceeds 1.73%). CVaR(95%) = -0.0222.", "metadata": {"var": -0.017264, "cvar": -0.02221, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240819_0158", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["STIP"], "decision_date": "2024-08-19", "context_summary": "STIP: 60-day return history, mean=0.0004, std=0.0010.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0004, std=0.0010, min=-0.0029, max=0.0028\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for STIP. Express as a decimal (e.g., -0.02).", "answer": "-0.0012", "answer_numeric": -0.001199, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0012 (i.e., on a bad day with 5% probability, the loss exceeds 0.12%). CVaR(95%) = -0.0018.", "metadata": {"var": -0.001199, "cvar": -0.001843, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230102_0160", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-01-02", "context_summary": "MATIC-USD: 60-day return history, mean=0.0007, std=0.0790.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0007, std=0.0790, min=-0.2144, max=0.3834\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-01] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0947", "answer_numeric": -0.094719, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0947 (i.e., on a bad day with 5% probability, the loss exceeds 9.47%). CVaR(95%) = -0.1654.", "metadata": {"var": -0.094719, "cvar": -0.165444, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240702_0163", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-07-02", "context_summary": "IWM: 60-day return history, mean=-0.0002, std=0.0101.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0002, std=0.0101, min=-0.0268, max=0.0182\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 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blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0166", "answer_numeric": -0.016617, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0166 (i.e., on a bad day with 5% probability, the loss exceeds 1.66%). CVaR(95%) = -0.0217.", "metadata": {"var": -0.016617, "cvar": -0.021744, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240814_0166", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-08-14", "context_summary": "ADA-USD: 60-day return history, mean=-0.0024, std=0.0387.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0387, min=-0.1079, max=0.0869\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0666", "answer_numeric": -0.06664, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0666 (i.e., on a bad day with 5% probability, the loss exceeds 6.66%). CVaR(95%) = -0.0903.", "metadata": {"var": -0.06664, "cvar": -0.090311, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231121_0169", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-11-21", "context_summary": "XRP-USD: 60-day return history, mean=0.0035, std=0.0268.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0035, std=0.0268, min=-0.0623, max=0.0822\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-20] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0305", "answer_numeric": -0.030478, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0305 (i.e., on a bad day with 5% probability, the loss exceeds 3.05%). CVaR(95%) = -0.0536.", "metadata": {"var": -0.030478, "cvar": -0.053569, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230110_0171", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2023-01-10", "context_summary": "VNQI: 60-day return history, mean=0.0020, std=0.0133.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=0.0020, std=0.0133, min=-0.0247, max=0.0246\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VNQI. Express as a decimal (e.g., -0.02).", "answer": "-0.0195", "answer_numeric": -0.019504, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0195 (i.e., on a bad day with 5% probability, the loss exceeds 1.95%). CVaR(95%) = -0.0224.", "metadata": {"var": -0.019504, "cvar": -0.022423, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240510_0173", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-05-10", "context_summary": "ICSH: 60-day return history, mean=0.0002, std=0.0002.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0002, min=-0.0006, max=0.0008\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ICSH. Express as a decimal (e.g., -0.02).", "answer": "-0.0000", "answer_numeric": -2e-06, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0003.", "metadata": {"var": -2e-06, "cvar": -0.000278, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230227_0176", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-02-27", "context_summary": "SOL-USD: 60-day return history, mean=0.0163, std=0.0703.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0163, std=0.0703, min=-0.1182, max=0.2870\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-26] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0677", "answer_numeric": -0.067742, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0677 (i.e., on a bad day with 5% probability, the loss exceeds 6.77%). CVaR(95%) = -0.0969.", "metadata": {"var": -0.067742, "cvar": -0.096892, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240104_0179", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-01-04", "context_summary": "AVAX-USD: 60-day return history, mean=0.0206, std=0.0656.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0206, std=0.0656, min=-0.1393, max=0.2132\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0871", "answer_numeric": -0.087104, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0871 (i.e., on a bad day with 5% probability, the loss exceeds 8.71%). CVaR(95%) = -0.1072.", "metadata": {"var": -0.087104, "cvar": -0.107156, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230807_0182", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-08-07", "context_summary": "EWJ: 60-day return history, mean=0.0006, std=0.0105.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0006, std=0.0105, min=-0.0260, max=0.0248\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K PG 2023-08-04] pg-20230630 0000080424 6/30 2023 FY False 2,357,306,187 357 0000080424 2022-07-01 2023-06-30 0000080424 us-gaap:CommonStockMember 2022-07-01 2023-06-30 0000080424 exch:XNYS us-gaap:CommonStockMember 2022-07-01 2023-06-30 0000080424 pg:A1125NotesDue2023Domain 2022-07-01 2023-06-30 0000080424 exch:XNYS 2022-07-01 2023-06-30 0000080424 pg:A0500NotesDue2024Domain 2022-07-01 2023-06-30 0000080424 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Document 101.DEF (1)    Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1)    Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1)    Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) (1) Pursuant to Rule 406T of Regulation S-T, these interactive data files are deemed not filed or part of a registration statement or prospectus for purposes of Sections 11 or 12 of the Securities Act of 1933 or Section 18 of the Securities Exchange Act of 1934 and otherwise are not subject to liability. * Compensatory plan or arrangement. + Filed herewith. Item 16. Form 10-K Summary. Not applicable. The Procter & Gamble Company 67 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized in the city of Cincinnati, State of Ohio. THE PROCTER & GAMBLE COMPANY By /s/ JON R. MOELLER (Jon R. Moeller) Chairman of the Board, President and Chief Executive Officer August 04, 2023 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons in the capacities and on the dates indicated. Signature Title Date /s/ JON R. MOELLER (Jon R. Moeller) Chairman of the Board, President and Chief Executive Officer (Principal Executive Officer) August 04, 2023 /s/ ANDRE SCHULTEN (Andre Schulten) Chief Financial Officer (Principal Financial Officer) August 04, 2023 /s/ MATTHEW W. JANZARUK (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer) August 04, 2023 /s/ B. MARC ALLEN (B. Marc Allen) Director August 04, 2023 /s/ SHEILA BONINI (Sheila Bonini) Director August 04, 2023 /s/ ANGELA F. BRALY (Angela F. Braly) Director August 04, 2023 /s/ AMY L. CHANG (Amy L. Chang) Director August 04, 2023 /s/ JOSEPH JIMENEZ (Joseph Jimenez) Director August 04, 2023 /s/ CHRISTOPHER J. KEMPCZINSKI (Christopher J. Kempczinski) Director August 04, 2023 /s/ DEBRA L. LEE (Debra L. Lee) Director August 04, 2023 /s/ TERRY J. LUNDGREN (Terry J. Lundgren) Director August 04, 2023 /s/ CHRISTINE M. MCCARTHY (Christine M. McCarthy) Director August 04, 2023 /s/ ROBERT J. PORTMAN (Robert J. Portman) Director August 04, 2023 /s/ RAJESH SUBRAMANIAM (Rajesh Subramaniam) Director August 04, 2023 /s/ PATRICIA A. WOERTZ (Patricia A. Woertz) Director August 04, 2023\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EWJ. Express as a decimal (e.g., -0.02).", "answer": "-0.0147", "answer_numeric": -0.014703, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0147 (i.e., on a bad day with 5% probability, the loss exceeds 1.47%). CVaR(95%) = -0.0233.", "metadata": {"var": -0.014703, "cvar": -0.023337, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20240325_0185", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-03-25", "context_summary": "VLUE: 60-day return history, mean=0.0009, std=0.0069.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0009, std=0.0069, min=-0.0190, max=0.0134\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 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0000104169 wmt:WalmartInternationalMember 2023-01-31 0000104169 wmt:SamsClubMember 2023-01-31 0000104169 wmt:WalmartUSMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartInternationalMember 2023-02-01 2024-01-31 0000104169 wmt:SamsClubMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartUSMember 2024-01-31 0000104169 wmt:WalmartInternationalMember 2024-01-31 0000104169 wmt:SamsClubMember 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2023-02-01 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2022-02-01 2023-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0100", "answer_numeric": -0.01005, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0100 (i.e., on a bad day with 5% probability, the loss exceeds 1.00%). CVaR(95%) = -0.0136.", "metadata": {"var": -0.01005, "cvar": -0.013613, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240101_0187", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-01-01", "context_summary": "XRP-USD: 60-day return history, mean=0.0005, std=0.0280.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0280, min=-0.0625, max=0.0822\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0531", "answer_numeric": -0.053079, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0531 (i.e., on a bad day with 5% probability, the loss exceeds 5.31%). CVaR(95%) = -0.0608.", "metadata": {"var": -0.053079, "cvar": -0.060848, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230811_0190", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-08-11", "context_summary": "XRP-USD: 60-day return history, mean=-0.0001, std=0.0510.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0510, min=-0.1180, max=0.3257\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-10] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0487", "answer_numeric": -0.048731, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0487 (i.e., on a bad day with 5% probability, the loss exceeds 4.87%). CVaR(95%) = -0.0818.", "metadata": {"var": -0.048731, "cvar": -0.081803, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241211_0193", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-12-11", "context_summary": "MATIC-USD: 60-day return history, mean=0.0090, std=0.0590.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0090, std=0.0590, min=-0.1702, max=0.1530\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0632", "answer_numeric": -0.063167, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0632 (i.e., on a bad day with 5% probability, the loss exceeds 6.32%). CVaR(95%) = -0.1102.", "metadata": {"var": -0.063167, "cvar": -0.110222, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240222_0195", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2024-02-22", "context_summary": "SHV: 60-day return history, mean=0.0002, std=0.0002.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, min=-0.0003, max=0.0005\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SHV. Express as a decimal (e.g., -0.02).", "answer": "-0.0000", "answer_numeric": -5e-06, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0002.", "metadata": {"var": -5e-06, "cvar": -0.000181, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240425_0198", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-04-25", "context_summary": "SOL-USD: 60-day return history, mean=0.0073, std=0.0536.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0073, std=0.0536, min=-0.1325, max=0.1267\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0849", "answer_numeric": -0.084881, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0849 (i.e., on a bad day with 5% probability, the loss exceeds 8.49%). CVaR(95%) = -0.1118.", "metadata": {"var": -0.084881, "cvar": -0.111776, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240430_0201", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-04-30", "context_summary": "LINK-USD: 60-day return history, mean=-0.0043, std=0.0438.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0043, std=0.0438, min=-0.1363, max=0.0950\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0758", "answer_numeric": -0.075805, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0758 (i.e., on a bad day with 5% probability, the loss exceeds 7.58%). CVaR(95%) = -0.1128.", "metadata": {"var": -0.075805, "cvar": -0.112843, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230915_0204", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-09-15", "context_summary": "VEA: 60-day return history, mean=-0.0001, std=0.0082.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=-0.0001, std=0.0082, min=-0.0195, max=0.0190\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-14] [\"What TSMC, ARM, AMD, Apple, and Nvidia Stock Investors Should Know About Recent Chip Updates In today's video, I discuss various semiconductor stocks and recent updates. Check out the short video to learn more, consider subscribing, and click the special offer link below. *Stock prices used were the market prices of Sept. 14, 2023. The video was published on Sept. 14, 2023. 10 stocks we like better than Taiwan Semiconductor Manufacturing When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now... and Taiwan Semiconductor Manufacturing wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of September 11, 2023 Jose Najarro has positions in Advanced Micro Devices, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Advanced Micro Devices, Apple, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy. Jose Najarro is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"SoftBank's Arm set to debut on Nasdaq after biggest IPO since 2021 Adds analyst comment on IPO enthusiasm in paragraph 7, chip stock movement in paragraph 8, background throughout Sept 14 (Reuters) - SoftBank's chip designer Arm Holdings ARM.O is set to debut on the Nasdaq on Thursday, in what is expected to be the biggest test for the U.S. IPO market after a listing drought that lasted for nearly 16 months. The company on Wednesday priced its offering of 95.5 million American Depositary shares at $51 apiece, fetching $4.87 billion for SoftBank at a valuation of $54.5 billion, with participation from cornerstone investors including Apple AAPL.O, Intel INTC.O and Alphabet GOOGL.O. Arm will be back as a publicly traded firm after seven years. Its shares used to trade on the London Stock Exchange and the Nasdaq from 1998 until 2016 when it was taken private by SoftBank in a $32 billion deal. Hopes of a revival in the IPO market largely depend on the success of the high-profile listings of Arm and other marquee startups, including grocery delivery firm Instacart and marketing firm Klaviyo. Investors have over the last year begun to pay more attention to profitability, shunning cash-burning startups that had in 2021 fetched lofty valuations on the back of a record year for deals. Arm has positioned itself as indispensable in the tech hardware ecosystem as its chip designs power nearly every smartp\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VEA. Express as a decimal (e.g., -0.02).", "answer": "-0.0141", "answer_numeric": -0.014143, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0141 (i.e., on a bad day with 5% probability, the loss exceeds 1.41%). CVaR(95%) = -0.0179.", "metadata": {"var": -0.014143, "cvar": -0.017872, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230912_0207", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-09-12", "context_summary": "LINK-USD: 60-day return history, mean=-0.0030, std=0.0366.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0030, std=0.0366, min=-0.0806, max=0.1799\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-11] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0423", "answer_numeric": -0.042264, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0423 (i.e., on a bad day with 5% probability, the loss exceeds 4.23%). CVaR(95%) = -0.0582.", "metadata": {"var": -0.042264, "cvar": -0.05819, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240827_0209", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-08-27", "context_summary": "USMV: 60-day return history, mean=0.0017, std=0.0055.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0017, std=0.0055, min=-0.0226, max=0.0137\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-01-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-04-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-04-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-01-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2024-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-03-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-03-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-03-31 0000731766 us-gaap:NoncontrollingInterestMember 2024-03-31 0000731766 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-04-01 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-04-01 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-04-01 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-04-01 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-04-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000731766 us-gaap:RetainedEarningsMember 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-06-30 0000731766 us-gaap:CommonStockMember 2023-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-03-31 0000731766 us-gaap:RetainedEarningsMember 2023-03-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-03-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-03-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-03-31 0000731766 2023-03-31 0000731766 us-gaap:RetainedEarningsMember 2023-04-01 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-04-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-04-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-04-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-04-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-04-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-06-30 0000731766 us-gaap:RetainedEarningsMember 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-06-30 0000731766 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2024-01-01 2024-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2024-01-01 2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-06-30 0000731766 unh:ProductsAndServicesMember 2024-06-30 0000731766 unh:ProductsAndServicesMember 2023-12-31 0000731766 2024-07-01 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2024-06-30 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2024-06-30 0000731766 us-gaap:CorporateDebtSecuritiesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0049", "answer_numeric": -0.004926, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0049 (i.e., on a bad day with 5% probability, the loss exceeds 0.49%). CVaR(95%) = -0.0119.", "metadata": {"var": -0.004926, "cvar": -0.011934, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241010_0212", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-10-10", "context_summary": "BTC-USD: 60-day return history, mean=0.0002, std=0.0230.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0230, min=-0.0537, max=0.0615\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0367", "answer_numeric": -0.036671, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0367 (i.e., on a bad day with 5% probability, the loss exceeds 3.67%). CVaR(95%) = -0.0441.", "metadata": {"var": -0.036671, "cvar": -0.044146, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241209_0215", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-12-09", "context_summary": "XLK: 60-day return history, mean=0.0016, std=0.0116.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0016, std=0.0116, min=-0.0326, max=0.0293\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0223", "answer_numeric": -0.02235, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0223 (i.e., on a bad day with 5% probability, the loss exceeds 2.23%). CVaR(95%) = -0.0275.", "metadata": {"var": -0.02235, "cvar": -0.027472, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240920_0218", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-09-20", "context_summary": "XLU: 60-day return history, mean=0.0020, std=0.0082.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0020, std=0.0082, min=-0.0268, max=0.0181\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0097", "answer_numeric": -0.009654, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0097 (i.e., on a bad day with 5% probability, the loss exceeds 0.97%). CVaR(95%) = -0.0209.", "metadata": {"var": -0.009654, "cvar": -0.020859, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230120_0220", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-01-20", "context_summary": "XLE: 60-day return history, mean=0.0007, std=0.0173.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0007, std=0.0173, min=-0.0481, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-19] [\"US STOCKS-Wall Street set for lower open amid recession worries By Amruta Khandekar and Shreyashi Sanyal Jan 19 (Reuters) - U.S. stock indexes were set to open lower on Thursday as recession worries crept into the foreground of the earnings season, while shares of Procter & Gamble fell as it warned of cost pressures. A surprise fall in U.S. weekly jobless claims, suggested the labor market remained tight even in a high interest rate environment. Corporate America has been hit by a challenging economic environment, with Microsoft Corp MSFT.O announcing 10,000 job cuts on Wednesday. With the quarterly reporting season underway, analysts noted that earnings estimates could decline even further as risks of a potential recession increase. \\\"The earnings picture is also looking weak and pointing to a recession,\\\" said Sam Stovall, chief investment strategist at CFRA research. \\\"Expectations are that earnings will fall in the fourth quarter of 2022 as well as the first two quarters of 2023.\\\" Analysts now expect year-over-year earnings from S&P 500 companies to decline 2.8% for the fourth quarter, according to Refinitiv data, compared with a 1.6% decline in the beginning of the year. This comes after data on Wednesday showed retail sales, producer prices and production at U.S. factories fell more than expected in December, while November output was also weaker, adding to worries of a slowdown in the economy. Leading Dow components were lower in premarket trading. Procter & Gamble Co PG.N fell 2.5% after warning of commodity costs pressuring profits, despite raising its full-year sales forecast. The S&P 500 .SPX and the Dow .DJI logged their biggest daily percentage declines in over a month in the previous session, with comments from Federal Reserve officials that highlighted the disparity between the central bank's estimate of its terminal rate and market expectations. St. Louis Fed President James Bullard and Cleveland Fed President Loretta Mester stressed on the need to raise rates beyond 5% to bring inflation to heel, while money markets see the rate peaking at 4.85% by June, with a 25-basis point rate hike baked in for February. FEDWATCH At 8:58 a.m. ET, Dow e-minis 1YMcv1 were down 245 points, or 0.73%, S&P 500 e-minis EScv1 were down 27.75 points, or 0.70%, and Nasdaq 100 e-minis NQcv1 were down 85.5 points, or 0.75%. Netflix Inc NFLX.O is expected to report its slowest quarterly revenue growth after markets close on Thursday. The company's shares fell 0.9%. Tesla Inc TSLA.O fell 1.8%, leading declines among its growth peers Apple Inc AAPL.O, Amazon.com Inc AMZN.O and Microsoft Corp MSFT.O, whose shares were down between 0.7% and 1.4%. Piper Sandler cut the target price on electric-vehicle maker Tesla's stock to $300 from $340. (Reporting by Shubham Batra in Bengaluru; Editing by Shounak Dasgupta) ((Shubham.Batra@thomsonreuters.com)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect t\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLE. Express as a decimal (e.g., -0.02).", "answer": "-0.0279", "answer_numeric": -0.027929, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0279 (i.e., on a bad day with 5% probability, the loss exceeds 2.79%). CVaR(95%) = -0.0380.", "metadata": {"var": -0.027929, "cvar": -0.037987, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231019_0222", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2023-10-19", "context_summary": "DBC: 60-day return history, mean=0.0005, std=0.0081.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=0.0005, std=0.0081, min=-0.0280, max=0.0264\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DBC. Express as a decimal (e.g., -0.02).", "answer": "-0.0108", "answer_numeric": -0.010763, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0108 (i.e., on a bad day with 5% probability, the loss exceeds 1.08%). CVaR(95%) = -0.0183.", "metadata": {"var": -0.010763, "cvar": -0.018327, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230414_0225", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-04-14", "context_summary": "IWM: 60-day return history, mean=-0.0007, std=0.0138.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0007, std=0.0138, min=-0.0300, max=0.0240\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-13] [\"Canaccord Genuity Maintains Apple (AAPL) Buy Recommendation Fintel reports that on April 13, 2023, Canaccord Genuity maintained coverage of Apple (NASDAQ:AAPL) with a Buy recommendation. Analyst Price Forecast Suggests 8.49% Upside As of April 6, 2023, the average one-year price target for Apple is $173.69. The forecasts range from a low of $119.18 to a high of $215.25. The average price target represents an increase of 8.49% from its latest reported closing price of $160.10. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is $413,641MM, an increase of 6.74%. The projected annual non-GAAP EPS is $6.36. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. What are Other Shareholders Doing? Iyo Bank holds 67K shares representing 0.00% ownership of the company. No change in the last quarter. Keb Asset Management holds 9K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 10K shares, representing a decrease of 5.83%. The firm decreased its portfolio allocation in AAPL by 99.93% over the last quarter. NSFBX - Natixis Sustainable Future 2015 Fund Class N holds 0K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 0K shares, representing an increase of 11.96%. The firm decreased its portfolio allocation in AAPL by 13.12% over the last quarter. Saxon Interests holds 35K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 36K shares, representing a decrease of 1.41%. The firm increased its portfolio allocation in AAPL by 23.77% over the last quarter. Bank Julius Baer & Co. Ltd, Zurich holds 3,989K shares representing 0.03% ownership of the company. In it's prior filing, the firm reported owning 3,932K shares, representing an increase of 1.43%. The firm decreased its portfolio allocation in AAPL by 99.91% over the last quarter. What is the Fund Sentiment? There are 6408 funds or institutions reporting positions in Apple. This is an increase of 203 owner(s) or 3.27% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 2.31%, a decrease of 40.18%. Total shares owned by institutions increased in the last three months by 0.35% to 10,154,214K shares. The put/call ratio of AAPL is 1.01, indicating a bearish outlook. Apple Background Information (This description is provided by the company.) Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services. It is considered one of the Big Five companies in the U.S. information technology industry, along with Amazon, Google, Microsoft, and Facebook. Its hardware products include the iPhone smartphone, the iPad tablet computer, the Mac personal computer, the iPod portable media player, the Apple Watch smartwatc\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0282", "answer_numeric": -0.028236, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0282 (i.e., on a bad day with 5% probability, the loss exceeds 2.82%). CVaR(95%) = -0.0293.", "metadata": {"var": -0.028236, "cvar": -0.029328, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230106_0228", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-01-06", "context_summary": "SOL-USD: 60-day return history, mean=-0.0075, std=0.0760.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0075, std=0.0760, min=-0.2453, max=0.2683\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-05] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1202", "answer_numeric": -0.120196, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1202 (i.e., on a bad day with 5% probability, the loss exceeds 12.02%). CVaR(95%) = -0.1848.", "metadata": {"var": -0.120196, "cvar": -0.18484, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241224_0231", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-12-24", "context_summary": "EEM: 60-day return history, mean=-0.0013, std=0.0101.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0013, std=0.0101, min=-0.0250, max=0.0219\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0216", "answer_numeric": -0.021559, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0216 (i.e., on a bad day with 5% probability, the loss exceeds 2.16%). CVaR(95%) = -0.0245.", "metadata": {"var": -0.021559, "cvar": -0.02452, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240614_0234", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-06-14", "context_summary": "ADA-USD: 60-day return history, mean=-0.0014, std=0.0273.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0014, std=0.0273, min=-0.0506, max=0.0792\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0369", "answer_numeric": -0.036892, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0369 (i.e., on a bad day with 5% probability, the loss exceeds 3.69%). CVaR(95%) = -0.0436.", "metadata": {"var": -0.036892, "cvar": -0.043552, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240725_0236", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2024-07-25", "context_summary": "STIP: 60-day return history, mean=0.0003, std=0.0010.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0003, std=0.0010, min=-0.0029, max=0.0024\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for STIP. Express as a decimal (e.g., -0.02).", "answer": "-0.0010", "answer_numeric": -0.001033, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0010 (i.e., on a bad day with 5% probability, the loss exceeds 0.10%). CVaR(95%) = -0.0017.", "metadata": {"var": -0.001033, "cvar": -0.001745, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240212_0239", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-02-12", "context_summary": "BNB-USD: 60-day return history, mean=0.0044, std=0.0276.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0044, std=0.0276, min=-0.0405, max=0.1146\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0306", "answer_numeric": -0.0306, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0306 (i.e., on a bad day with 5% probability, the loss exceeds 3.06%). CVaR(95%) = -0.0379.", "metadata": {"var": -0.0306, "cvar": -0.037886, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241021_0242", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-10-21", "context_summary": "ADA-USD: 60-day return history, mean=0.0002, std=0.0283.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0283, min=-0.0613, max=0.0660\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0471", "answer_numeric": -0.047064, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0471 (i.e., on a bad day with 5% probability, the loss exceeds 4.71%). CVaR(95%) = -0.0563.", "metadata": {"var": -0.047064, "cvar": -0.056276, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230425_0245", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-04-25", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0046, std=0.0352.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0046, std=0.0352, min=-0.0851, max=0.0871\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-24] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0658", "answer_numeric": -0.065835, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0658 (i.e., on a bad day with 5% probability, the loss exceeds 6.58%). CVaR(95%) = -0.0769.", "metadata": {"var": -0.065835, "cvar": -0.076935, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240111_0248", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2024-01-11", "context_summary": "XLY: 60-day return history, mean=0.0018, std=0.0117.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0018, std=0.0117, min=-0.0259, max=0.0331\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0204", "answer_numeric": -0.020404, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0204 (i.e., on a bad day with 5% probability, the loss exceeds 2.04%). CVaR(95%) = -0.0233.", "metadata": {"var": -0.020404, "cvar": -0.023349, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230711_0251", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-07-11", "context_summary": "ETH-USD: 60-day return history, mean=0.0010, std=0.0206.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0206, min=-0.0509, max=0.0552\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-10] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0331", "answer_numeric": -0.033115, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0331 (i.e., on a bad day with 5% probability, the loss exceeds 3.31%). CVaR(95%) = -0.0468.", "metadata": {"var": -0.033115, "cvar": -0.046752, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231205_0254", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-12-05", "context_summary": "BNB-USD: 60-day return history, mean=0.0020, std=0.0231.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0020, std=0.0231, min=-0.1070, max=0.0487\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-04] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0275", "answer_numeric": -0.027528, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0275 (i.e., on a bad day with 5% probability, the loss exceeds 2.75%). CVaR(95%) = -0.0609.", "metadata": {"var": -0.027528, "cvar": -0.06091, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241210_0255", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["PPLT"], "decision_date": "2024-12-10", "context_summary": "PPLT: 60-day return history, mean=-0.0003, std=0.0151.", "question": "Asset: PPLT\nDaily returns (past 60 days): mean=-0.0003, std=0.0151, min=-0.0337, max=0.0322\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for PPLT. Express as a decimal (e.g., -0.02).", "answer": "-0.0224", "answer_numeric": -0.022365, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0224 (i.e., on a bad day with 5% probability, the loss exceeds 2.24%). CVaR(95%) = -0.0288.", "metadata": {"var": -0.022365, "cvar": -0.028845, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230908_0257", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-09-08", "context_summary": "ADA-USD: 60-day return history, mean=-0.0013, std=0.0369.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0013, std=0.0369, min=-0.0807, max=0.2212\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-07] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0374", "answer_numeric": -0.037441, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0374 (i.e., on a bad day with 5% probability, the loss exceeds 3.74%). CVaR(95%) = -0.0623.", "metadata": {"var": -0.037441, "cvar": -0.062347, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241118_0259", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-11-18", "context_summary": "ETH-USD: 60-day return history, mean=0.0048, std=0.0319.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0048, std=0.0319, min=-0.0592, max=0.1245\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0419", "answer_numeric": -0.041889, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0419 (i.e., on a bad day with 5% probability, the loss exceeds 4.19%). CVaR(95%) = -0.0516.", "metadata": {"var": -0.041889, "cvar": -0.051631, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240802_0261", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2024-08-02", "context_summary": "JNK: 60-day return history, mean=0.0006, std=0.0025.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=0.0006, std=0.0025, min=-0.0040, max=0.0055\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for JNK. Express as a decimal (e.g., -0.02).", "answer": "-0.0036", "answer_numeric": -0.003565, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0036 (i.e., on a bad day with 5% probability, the loss exceeds 0.36%). CVaR(95%) = -0.0038.", "metadata": {"var": -0.003565, "cvar": -0.003815, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231213_0266", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-12-13", "context_summary": "SOL-USD: 60-day return history, mean=0.0211, std=0.0628.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0211, std=0.0628, min=-0.1169, max=0.2464\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-12] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0758", "answer_numeric": -0.075808, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0758 (i.e., on a bad day with 5% probability, the loss exceeds 7.58%). CVaR(95%) = -0.0921.", "metadata": {"var": -0.075808, "cvar": -0.092092, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241203_0268", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-12-03", "context_summary": "IWM: 60-day return history, mean=0.0022, std=0.0110.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0022, std=0.0110, min=-0.0177, max=0.0349\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 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us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0151", "answer_numeric": -0.015071, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0151 (i.e., on a bad day with 5% probability, the loss exceeds 1.51%). CVaR(95%) = -0.0168.", "metadata": {"var": -0.015071, "cvar": -0.016771, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20230718_0271", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-07-18", "context_summary": "XRP-USD: 60-day return history, mean=0.0046, std=0.0508.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0508, min=-0.1180, max=0.3257\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-17] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0480", "answer_numeric": -0.047996, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0480 (i.e., on a bad day with 5% probability, the loss exceeds 4.80%). CVaR(95%) = -0.0833.", "metadata": {"var": -0.047996, "cvar": -0.083298, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230721_0274", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-07-21", "context_summary": "BTC-USD: 60-day return history, mean=0.0020, std=0.0212.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0020, std=0.0212, min=-0.0501, max=0.0600\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-20] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0327", "answer_numeric": -0.032726, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0327 (i.e., on a bad day with 5% probability, the loss exceeds 3.27%). CVaR(95%) = -0.0397.", "metadata": {"var": -0.032726, "cvar": -0.039723, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230822_0277", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-08-22", "context_summary": "MTUM: 60-day return history, mean=0.0007, std=0.0075.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0007, std=0.0075, min=-0.0167, max=0.0149\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-21] [\"Tesla shares gain as Baird Equity adds stock to 'best ideas' list Aug 21 (Reuters) - Electric-vehicle maker Tesla's TSLA.O shares rose 4.5% on Monday, snapping a six-session losing streak, after brokerage Baird Equity Research added the stock to its \\\"best ideas\\\" list. The brokerage said price cuts and their impact on margins will drive the narrative in the second half of the year but other potential catalysts for the stock include the launch of Cybertruck, wider adoption of Full Self-Driving and expansion into new markets. Tesla's shares have risen about 85% so far this year on the back of growing sales despite a margin squeeze and hopes of wider adoption of its autonomous driving software. Bearish investors will point to lower production, said Baird, but added Tesla was still on pace to achieve its production forecast of 1.8 million vehicles this year. Tesla sparked a price war earlier this year and last week slashed prices of three models in China. It also launched a cheaper version of the Model S sedan and Model X SUV on Aug. 14 as it looks to stoke demand and grab a larger share of the market. The world's most valuable automaker's shares have a forward price-to-earnings multiple, a widely used benchmark to value stocks, of 50.15, compared to 26.58 for Apple AAPL.O and 6.14 for Ford Motor F.N, making it pricier. The brokerage also said sentiment for electric pickup truck maker Rivian Automotive's RIVN.O stock was improving, adding that cost improvements have begun to materialize as it brings production of key components in-house. (Reporting by Akash Sriram and Jaspreet Singh in Bengaluru; Editing by Krishna Chandra Eluri) ((Akash.Sriram@thomsonreuters.com; @HoodieOnVeshti on Twitter; +91-74116-87774;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple and Spotify: 2 AI Stock Plays in Music Streaming The artificial intelligence (AI) revolution is underway, and it's already made a lot of money for investors who recognized its potential early in the game. With shares of AI frontrunners like Nvidia (NVDA) doubling up many times over in a matter of months, it's not hard to see why so many investors want to stay in the tech scene, despite the potential for further interest rate increases. With so many technology companies committed to investing in their AI capabilities, investors shouldn't narrow their focus on the few AI winners that have been leading the pack in recent quarters. Arguably, investors should at least be equal-weight in the mega-cap tech heroes of the so-called \\u201cMagnificent Seven\\u201d to benefit from the continued rise of AI. At the same time, investors should also seek value in areas of the market where the long-term benefits of incorporating AI tech aren't yet fully recognized. Indeed, Nvidia stands out as one of the AI plays of the present. After such a historic ascent, though, I'm starting to think the opportunity over at Nvidia \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MTUM. Express as a decimal (e.g., -0.02).", "answer": "-0.0100", "answer_numeric": -0.010041, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0100 (i.e., on a bad day with 5% probability, the loss exceeds 1.00%). CVaR(95%) = -0.0134.", "metadata": {"var": -0.010041, "cvar": -0.013374, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231023_0280", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-10-23", "context_summary": "QQQ: 60-day return history, mean=-0.0010, std=0.0106.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0010, std=0.0106, min=-0.0222, max=0.0216\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-20] [\"Earnings Preview of \\\"Magnificent Seven\\\": ETFs in Focus The \\\"Magnificent Seven\\\" typically refers to the 1960 Western film, but today\\u2019s stock market investors recognize the term as the set of seven big tech stocks, namely Apple AAPL, Microsoft MSFT, Alphabet GOOGL, Amazon AMZN, Nvidia NVDA, Meta Platforms META and Tesla TSLA. With the third-quarter earnings season underway, investors\\u2019 eyes will be glued to the \\\"Magnificent Seven\\\" earnings. While Tesla has already posted a weak Q3 earnings (missing estimates on both fronts), others are yet to report (read: Tesla Posts Weak Q3 Earnings: ETFs in Focus). Investors should note that according to our methodology, the combination of a positive Earnings ESP and a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 increases the chances of an earnings beat. You can uncover the best stocks to buy or sell before they\\u2019re reported with our Earnings ESP Filter. Earnings Whispers Microsoft is expected to report on Oct 24. The stock has an Earnings ESP of 0.00% and a Zacks Rank #3 (Hold). In the past 90 days, Microsoft\\u2019s earnings for the September quarter rose by 8 cents to $2.65 per share. Alphabet is expected to report on Oct 24. The stock has an Earnings ESP of +0.89% and a Zacks Rank #3. In the past 90 days, Alphabet\\u2019s earnings for the September quarter rose by 11 cents to $1.45 per share. Meta is expected to report on Oct 25. The stock has an Earnings ESP of +3.98% and a Zacks Rank #3. In the past 90 days, Meta\\u2019s earnings for the September quarter surged from $2.99 to $3.57 per share. Amazon is expected to report on Oct 26. The stock has an Earnings ESP of 0.00% and a Zacks Rank #2 (Buy). In the past 90 days, Amazon\\u2019s earnings for the September quarter surged from 39 cents to 58 cents per share. Apple is expected to report on Nov 2. The stock has an Earnings ESP of 0.00% and a Zacks Rank #3. In the past 90 days, Apple\\u2019s earnings for the September quarter inched up by 2 cents $1.39 per share. Nvidia is expected to report on Nov 15. The stock has an Earnings ESP of +6.93% and a Zacks Rank #1 (Strong Buy). In the past 90 days, Nvidia\\u2019s earnings for the October quarter jumped from $2.22 to $3.34 per share. Inside the Valuation of Magnificent Seven While the 'Magnificent Seven' hold industry-leading positions in areas such as Artificial Intelligence, cloud services, social networking, search engines, the metaverse, premium smartphones, and electric vehicles (which have enabled them to capture a hugeglobal marketshare), valuation remains equally important in influencing their stock performance in the near future. In this respect, Meta, Alphabet and Microsoft have a lower P/E than the concerned industry Computer Software-Services Market\\u2019s P/E, Apple\\u2019s P/E is almost in-line with the concerned industry Computer-Office Equipment Market\\u2019s P/E. However, Amazon, Tesla and Nvidia are pricey. ETFs in Focus Since some of the stocks appear overvalued and some stocks have\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QQQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0177", "answer_numeric": -0.017745, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0177 (i.e., on a bad day with 5% probability, the loss exceeds 1.77%). CVaR(95%) = -0.0208.", "metadata": {"var": -0.017745, "cvar": -0.020763, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240531_0283", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-05-31", "context_summary": "VLUE: 60-day return history, mean=-0.0001, std=0.0076.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0001, std=0.0076, min=-0.0204, max=0.0173\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 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Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0139", "answer_numeric": -0.013911, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0139 (i.e., on a bad day with 5% probability, the loss exceeds 1.39%). CVaR(95%) = -0.0187.", "metadata": {"var": -0.013911, "cvar": -0.018729, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240910_0286", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-09-10", "context_summary": "BNB-USD: 60-day return history, mean=0.0002, std=0.0295.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0295, min=-0.0652, max=0.0909\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0449", "answer_numeric": -0.044858, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0449 (i.e., on a bad day with 5% probability, the loss exceeds 4.49%). CVaR(95%) = -0.0608.", "metadata": {"var": -0.044858, "cvar": -0.060841, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230724_0289", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-07-24", "context_summary": "ICSH: 60-day return history, mean=0.0001, std=0.0005.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0001, std=0.0005, min=-0.0010, max=0.0014\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ICSH. Express as a decimal (e.g., -0.02).", "answer": "-0.0004", "answer_numeric": -0.000429, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0004 (i.e., on a bad day with 5% probability, the loss exceeds 0.04%). CVaR(95%) = -0.0010.", "metadata": {"var": -0.000429, "cvar": -0.000997, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230424_0292", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-04-24", "context_summary": "LINK-USD: 60-day return history, mean=-0.0008, std=0.0366.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0008, std=0.0366, min=-0.0940, max=0.0825\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-23] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0606", "answer_numeric": -0.06061, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0606 (i.e., on a bad day with 5% probability, the loss exceeds 6.06%). CVaR(95%) = -0.0732.", "metadata": {"var": -0.06061, "cvar": -0.073181, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240219_0294", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-02-19", "context_summary": "BTC-USD: 60-day return history, mean=0.0032, std=0.0237.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0032, std=0.0237, min=-0.0758, max=0.0689\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0353", "answer_numeric": -0.035254, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0353 (i.e., on a bad day with 5% probability, the loss exceeds 3.53%). CVaR(95%) = -0.0573.", "metadata": {"var": -0.035254, "cvar": -0.057269, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230703_0296", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-07-03", "context_summary": "DOT-USD: 60-day return history, mean=-0.0005, std=0.0265.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0265, min=-0.0915, max=0.0558\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-02] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0424", "answer_numeric": -0.042367, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0424 (i.e., on a bad day with 5% probability, the loss exceeds 4.24%). CVaR(95%) = -0.0616.", "metadata": {"var": -0.042367, "cvar": -0.061608, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230202_0299", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-02-02", "context_summary": "BNB-USD: 60-day return history, mean=0.0018, std=0.0263.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0018, std=0.0263, min=-0.1047, max=0.0528\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-01] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0374", "answer_numeric": -0.037358, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0374 (i.e., on a bad day with 5% probability, the loss exceeds 3.74%). CVaR(95%) = -0.0631.", "metadata": {"var": -0.037358, "cvar": -0.063101, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240315_0302", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-03-15", "context_summary": "AVAX-USD: 60-day return history, mean=0.0081, std=0.0454.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0081, std=0.0454, min=-0.0921, max=0.1654\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0570", "answer_numeric": -0.057041, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0570 (i.e., on a bad day with 5% probability, the loss exceeds 5.70%). CVaR(95%) = -0.0814.", "metadata": {"var": -0.057041, "cvar": -0.081394, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230313_0305", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-03-13", "context_summary": "BTC-USD: 60-day return history, mean=0.0039, std=0.0291.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0039, std=0.0291, min=-0.0624, max=0.0939\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-12] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0397", "answer_numeric": -0.039709, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0397 (i.e., on a bad day with 5% probability, the loss exceeds 3.97%). CVaR(95%) = -0.0529.", "metadata": {"var": -0.039709, "cvar": -0.052878, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240916_0308", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-09-16", "context_summary": "XLRE: 60-day return history, mean=0.0029, std=0.0090.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0029, std=0.0090, min=-0.0293, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLRE. Express as a decimal (e.g., -0.02).", "answer": "-0.0099", "answer_numeric": -0.009886, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0099 (i.e., on a bad day with 5% probability, the loss exceeds 0.99%). CVaR(95%) = -0.0191.", "metadata": {"var": -0.009886, "cvar": -0.019107, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20231031_0310", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2023-10-31", "context_summary": "BNDX: 60-day return history, mean=-0.0003, std=0.0030.", "question": "Asset: BNDX\nDaily returns (past 60 days): mean=-0.0003, std=0.0030, min=-0.0062, max=0.0070\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNDX. Express as a decimal (e.g., -0.02).", "answer": "-0.0052", "answer_numeric": -0.00524, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0052 (i.e., on a bad day with 5% probability, the loss exceeds 0.52%). CVaR(95%) = -0.0060.", "metadata": {"var": -0.00524, "cvar": -0.005968, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230922_0313", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-09-22", "context_summary": "XLY: 60-day return history, mean=-0.0004, std=0.0116.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0004, std=0.0116, min=-0.0347, max=0.0265\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-21] [\"JP Morgan Reiterates Apple (AAPL) Overweight Recommendation Fintel reports that on September 21, 2023, JP Morgan reiterated coverage of Apple (NASDAQ:AAPL) with a Overweight recommendation. Analyst Price Forecast Suggests 16.64% Upside As of August 31, 2023, the average one-year price target for Apple is 204.70. The forecasts range from a low of 150.49 to a high of $252.00. The average price target represents an increase of 16.64% from its latest reported closing price of 175.49. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is 413,641MM, an increase of 7.74%. The projected annual non-GAAP EPS is 6.36. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. What is the Fund Sentiment? There are 6414 funds or institutions reporting positions in Apple. This is an increase of 26 owner(s) or 0.41% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 4.14%, an increase of 8.66%. Total shares owned by institutions increased in the last three months by 0.28% to 9,941,590K shares. The put/call ratio of AAPL is 0.91, indicating a bullish outlook. What are Other Shareholders Doing? Berkshire Hathaway holds 915,560K shares representing 5.86% ownership of the company. No change in the last quarter. VTSMX - Vanguard Total Stock Market Index Fund Investor Shares holds 465,990K shares representing 2.98% ownership of the company. In it's prior filing, the firm reported owning 465,280K shares, representing an increase of 0.15%. The firm increased its portfolio allocation in AAPL by 8.69% over the last quarter. VFINX - Vanguard 500 Index Fund Investor Shares holds 352,024K shares representing 2.25% ownership of the company. In it's prior filing, the firm reported owning 347,041K shares, representing an increase of 1.42%. The firm increased its portfolio allocation in AAPL by 8.07% over the last quarter. Geode Capital Management holds 291,538K shares representing 1.86% ownership of the company. In it's prior filing, the firm reported owning 285,171K shares, representing an increase of 2.18%. The firm increased its portfolio allocation in AAPL by 8.78% over the last quarter. Price T Rowe Associates holds 226,651K shares representing 1.45% ownership of the company. In it's prior filing, the firm reported owning 234,017K shares, representing a decrease of 3.25%. The firm increased its portfolio allocation in AAPL by 139.25% over the last quarter. Apple Background Information (This description is provided by the company.) Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services. It is considered one of the Big Five companies in the U.S. information technology industry, along with Amazon, Google, Microsoft, and Facebook. Its hardware products include the iPhone smartphone, the iPad tablet computer,\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0182", "answer_numeric": -0.018177, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0182 (i.e., on a bad day with 5% probability, the loss exceeds 1.82%). CVaR(95%) = -0.0274.", "metadata": {"var": -0.018177, "cvar": -0.027366, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240416_0316", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-04-16", "context_summary": "ETH-USD: 60-day return history, mean=0.0023, std=0.0383.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0023, std=0.0383, min=-0.1024, max=0.1127\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0654", "answer_numeric": -0.065413, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0654 (i.e., on a bad day with 5% probability, the loss exceeds 6.54%). CVaR(95%) = -0.0836.", "metadata": {"var": -0.065413, "cvar": -0.083557, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240415_0319", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-04-15", "context_summary": "SOL-USD: 60-day return history, mean=0.0056, std=0.0511.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0056, std=0.0511, min=-0.1325, max=0.1267\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0658", "answer_numeric": -0.065798, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0658 (i.e., on a bad day with 5% probability, the loss exceeds 6.58%). CVaR(95%) = -0.1118.", "metadata": {"var": -0.065798, "cvar": -0.111776, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241009_0322", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2024-10-09", "context_summary": "PDBC: 60-day return history, mean=-0.0004, std=0.0108.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=-0.0004, std=0.0108, min=-0.0246, max=0.0226\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for PDBC. Express as a decimal (e.g., -0.02).", "answer": "-0.0156", "answer_numeric": -0.015618, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0156 (i.e., on a bad day with 5% probability, the loss exceeds 1.56%). CVaR(95%) = -0.0204.", "metadata": {"var": -0.015618, "cvar": -0.020396, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230525_0325", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-05-25", "context_summary": "XLF: 60-day return history, mean=-0.0017, std=0.0143.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=-0.0017, std=0.0143, min=-0.0372, max=0.0250\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-24] [\"7 Stocks That Could Be the First $10 Trillion-Dollar Company InvestorPlace - Stock Market News, Stock Advice & Trading Tips Let\\u2019s begin by understanding that most of the future $10 trillion companies are those that already have the highest valuations. Even the youngest among these companies have existed for 20 years. The point is that companies valued in the hundreds of billions and trillions take a long time to build: They, therefore, have the best chance of reaching the unthinkable $10 trillion mark first. To provide further context, no firm is currently valued at $5 trillion. Expectations are that the threshold will be reached in 2028. It seems that it could take decades for a company to reach a valuation twice that level. In truth, it could be a company that bursts onto the scene from relative obscurity. Some now-unknown AI companies could certainly fit the mold. But no one knows. MSFT Microsoft $313.85 GOOG GOOGL Alphabet $121.64 AAPL Apple $171.84 META Meta Platforms $249.21 NVDA Nvidia $305.38 AMZN Amazon $116.75 TSLA Tesla $182.90 Microsoft (MSFT) Source: Asif Islam / Shutterstock.com Microsoft (NASDAQ:MSFT) stock is the second highest-valued equity globally, at $2.35 trillion. It was actually worth $230 billion more at the height of the pandemic tech bubble before losing ground as rate hikes did their work. It\\u2019s another one of the future $10 trillion companies. One thing that is noteworthy about Microsoft\\u2019s market cap is just how rapidly it has grown of late. Just before the onset of the pandemic, the total value of all outstanding MSFT stock was approximately $1.3 trillion. So it has gained about $1 trillion in value since. That is primarily attributable to the fact that the pandemic put tech on steroids. Money was flowing into these companies at an extraordinary pace that no one could have anticipated. While the pandemic was a massive disaster, it was a boon for tech as everyone was forced inside. Companies like Microsoft were gifted accelerated sales and quantities of data that they couldn\\u2019t have otherwise. That acceleration of everything explains how Microsoft has grown so quickly. And now it has AI setting it up for its next growth phase. Alphabet (GOOG,GOOGL) Source: IgorGolovniov / Shutterstock.com The story of Alphabet\\u2019s (NASDAQ:GOOG,GOOGL) stock and its valuation follows a very similar arc to Microsoft\\u2019s. The same overarching catalysts apply to Alphabet and the benefits are similar too. Both companies have become much stronger as a result of the pandemic. It\\u2019s another one of the future $10 trillion companies. The difference is basically scale. Alphabet gained roughly $500 billion in value and is now valued near $1.6 trillion. The company has suffered in different ways over the past year. Mainly, Google has seen a massive slide as search revenues have declined on persistent economic fears. Companies are spending less on advertising. Yet it\\u2019s very much worth noting that Google must have co\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0273", "answer_numeric": -0.027296, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0273 (i.e., on a bad day with 5% probability, the loss exceeds 2.73%). CVaR(95%) = -0.0357.", "metadata": {"var": -0.027296, "cvar": -0.035711, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240306_0328", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-03-06", "context_summary": "SGOV: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=0.0000, max=0.0006\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = 0.0000.", "metadata": {"var": 0.0, "cvar": 0.0, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231208_0331", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2023-12-08", "context_summary": "BIL: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=0.0000, max=0.0005\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BIL. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = 0.0000.", "metadata": {"var": 0.0, "cvar": 0.0, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240704_0334", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2024-07-04", "context_summary": "FXI: 60-day return history, mean=0.0016, std=0.0148.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0016, std=0.0148, min=-0.0354, max=0.0476\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for FXI. Express as a decimal (e.g., -0.02).", "answer": "-0.0240", "answer_numeric": -0.024033, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0240 (i.e., on a bad day with 5% probability, the loss exceeds 2.40%). CVaR(95%) = -0.0284.", "metadata": {"var": -0.024033, "cvar": -0.028395, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240502_0337", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-05-02", "context_summary": "BTC-USD: 60-day return history, mean=-0.0004, std=0.0348.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0004, std=0.0348, min=-0.0834, max=0.0969\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0590", "answer_numeric": -0.059018, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0590 (i.e., on a bad day with 5% probability, the loss exceeds 5.90%). CVaR(95%) = -0.0703.", "metadata": {"var": -0.059018, "cvar": -0.070255, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230925_0340", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2023-09-25", "context_summary": "IYR: 60-day return history, mean=-0.0010, std=0.0090.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=-0.0010, std=0.0090, min=-0.0339, max=0.0186\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IYR. Express as a decimal (e.g., -0.02).", "answer": "-0.0120", "answer_numeric": -0.011955, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0120 (i.e., on a bad day with 5% probability, the loss exceeds 1.20%). CVaR(95%) = -0.0228.", "metadata": {"var": -0.011955, "cvar": -0.022774, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230113_0343", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-01-13", "context_summary": "BNB-USD: 60-day return history, mean=0.0011, std=0.0306.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0011, std=0.0306, min=-0.1047, max=0.1184\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-12] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0383", "answer_numeric": -0.038283, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0383 (i.e., on a bad day with 5% probability, the loss exceeds 3.83%). CVaR(95%) = -0.0639.", "metadata": {"var": -0.038283, "cvar": -0.063907, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240328_0346", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["STIP"], "decision_date": "2024-03-28", "context_summary": "STIP: 60-day return history, mean=0.0002, std=0.0014.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0002, std=0.0014, min=-0.0039, max=0.0034\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for STIP. Express as a decimal (e.g., -0.02).", "answer": "-0.0019", "answer_numeric": -0.00193, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0019 (i.e., on a bad day with 5% probability, the loss exceeds 0.19%). CVaR(95%) = -0.0028.", "metadata": {"var": -0.00193, "cvar": -0.002835, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230223_0349", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2023-02-23", "context_summary": "DBC: 60-day return history, mean=-0.0006, std=0.0117.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=-0.0006, std=0.0117, min=-0.0259, max=0.0225\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DBC. Express as a decimal (e.g., -0.02).", "answer": "-0.0192", "answer_numeric": -0.01915, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0192 (i.e., on a bad day with 5% probability, the loss exceeds 1.92%). CVaR(95%) = -0.0250.", "metadata": {"var": -0.01915, "cvar": -0.025009, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240808_0352", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-08-08", "context_summary": "XLK: 60-day return history, mean=-0.0007, std=0.0164.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=-0.0007, std=0.0164, min=-0.0423, max=0.0373\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CAT 2024-08-07] cat-20240630 0000018230 FALSE 12/31 2024 Q2 50 http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#Revenues 352 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cat:entity cat:group_president cat:segment 0000018230 2024-01-01 2024-06-30 0000018230 us-gaap:CommonStockMember 2024-01-01 2024-06-30 0000018230 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0000018230 us-gaap:EmployeeStockOptionMember 2023-01-01 2023-06-30 0000018230 us-gaap:EmployeeStockOptionMember 2023-06-30 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2024-01-01 2024-06-30 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2024-06-30 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2023-01-01 2023-06-30 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2023-06-30 0000018230 us-gaap:PerformanceSharesMember 2024-01-01 2024-06-30 0000018230 us-gaap:PerformanceSharesMember 2024-06-30 0000018230 us-gaap:PerformanceSharesMember 2023-01-01 2023-06-30 0000018230 us-gaap:PerformanceSharesMember 2023-06-30 0000018230 us-gaap:ForeignExchangeContractMember us-gaap:DesignatedAsHedgingInstrumentMember [...TRUNCATED...] 60;  Other Information On May 22, 2024 , Gerald Johnson , a member of the Company's Board of Directors , entered into a Rule 10b5-1 purchase plan intended to satisfy the affirmative defense of Rule 10b5-1(c) under the Securities Exchange Act of 1934, as amended. The purchase plan will be in effect until the earlier of (1) May 9, 2025 and (2) the date on which an aggregate of 400 shares of our common stock have been purchased under the plan. 78 Table of Contents Item 6. Exhibits 31.1 Certification of Chief Executive Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32 Certification of Chief Executive Officer of Caterpillar Inc. and Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document) 101.SCH   Inline XBRL Taxonomy Extension Schema Document 101.CAL   Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF   Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB   Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE   Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. 79 Table of Contents SIGNATURES   Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       CATERPILLAR INC.               August 7, 2024 /s/ D. James Umpleby III Chairman of the Board and Chief Executive Officer   D. James Umpleby III         August 7, 2024 /s/ Andrew R.J. Bonfield Chief Financial Officer   Andrew R.J. Bonfield               August 7, 2024 /s/ Derek Owens Chief Legal Officer and General Counsel   Derek Owens             August 7, 2024 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp   80\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0341", "answer_numeric": -0.034088, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0341 (i.e., on a bad day with 5% probability, the loss exceeds 3.41%). CVaR(95%) = -0.0400.", "metadata": {"var": -0.034088, "cvar": -0.039982, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230209_0355", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-02-09", "context_summary": "XLRE: 60-day return history, mean=0.0008, std=0.0141.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0008, std=0.0141, min=-0.0299, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-08] [\"3 Blue Chip Stocks To Watch In February 2023 Blue chip stocks are highly respected and established companies that have a strong reputation for stability and steady growth. Blue chip companies are typically leaders in their respective industries and have a long history of profitability, making them potentially attractive to both individual and institutional investors. Examples of blue chip stocks include large multinational corporations such as Apple (NASDAQ: AAPL), Johnson & Johnson (NYSE: JNJ), and Microsoft (NASDAQ: MSFT). These companies have proven track records of success, with a long history of consistently high earnings and steady growth. Their financial stability and reputation for reliability make them a popular choice among investors looking to build a balanced and diversified portfolio. In addition, blue chip stocks often pay dividends to shareholders, providing a steady source of income in addition to any potential capital gains. Investing in blue chip stocks can provide a solid foundation for your investment portfolio and offer peace of mind in knowing that you are investing in well-established companies with a long history of success. It\\u2019s important to note that, while these stocks are generally considered to be low-risk, no investment is completely risk-free, so it\\u2019s important to conduct your own research and due diligence. Accordingly, let\\u2019s look at three blue-chip stocks for you to watch in the stock market today. Blue Chip Stocks To Buy [Or Avoid] Today JP Morgan Chase & Co. (NYSE: JPM) The Procter & Gamble Company (NYSE: PG) The Coca-Cola Company (NYSE: KO) JP Morgan Chase & Co. (JPM Stock) To kick off this list let\\u2019s turn our attention to JP Morgan Chase & Co. (JPM). In brief, the company is one of the largest financial institutions in the United States. What\\u2019s more, JPM is organized into four major segments. These are consumer and community banking, corporate and investment banking, commercial banking, and asset and wealth management. Moving along, just last month, JPM reported its Q4 2022 financial and operating results. In the report, the company reported earnings per share of $3.57, along with $47.4 billion. For context, these numbers came in better than what analysts estimated, which was earnings of $3.11 per share and $34.2 billion in revenue. Moreover, JP Morgan Chase & Co also reported a 54.6% increase in revenue on a year-over-year basis. Looking since the beginning of 2023, shares of JPM stock have increased by 6.05%. Meanwhile, on Wednesday morning, JPM stock opened down by 0.26% and is currently trading at $143.29 a share. Source: TD Ameritrade TOS [Read More] 3 Natural Gas Stocks To Watch Today Procter & Gamble (PG Stock) Next, let\\u2019s look at consumer giant The Procter & Gamble Company (PG). This consumer goods behemoth owns popular brands like Tide, Crest, and Pampers. Additionally, PG currently operates in multiple business segments. These include Beauty, Grooming, Health Care, Fab\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLRE. Express as a decimal (e.g., -0.02).", "answer": "-0.0270", "answer_numeric": -0.027025, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0270 (i.e., on a bad day with 5% probability, the loss exceeds 2.70%). CVaR(95%) = -0.0294.", "metadata": {"var": -0.027025, "cvar": -0.029384, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231002_0357", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-10-02", "context_summary": "FXI: 60-day return history, mean=-0.0001, std=0.0173.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0001, std=0.0173, min=-0.0321, max=0.0476\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-29] [\"Is iShares Core S&P U.S. Growth ETF (IUSG) a Strong ETF Right Now? Launched on 07/24/2000, the iShares Core S&P U.S. Growth ETF (IUSG) is a smart beta exchange traded fund offering broad exposure to the Style Box - All Cap Growth category of the market. What Are Smart Beta ETFs? Products that are based on market cap weighted indexes, which are strategies designed to reflect a specific market segment or the market as a whole, have traditionally dominated the ETF industry. Investors who believe in market efficiency should consider market cap indexes, as they replicate market returns in a low-cost, convenient, and transparent way. On the other hand, some investors who believe that it is possible to beat the market by superior stock selection opt to invest in another class of funds that track non-cap weighted strategies--popularly known as smart beta. These indexes attempt to select stocks that have better chances of risk-return performance, based on certain fundamental characteristics or a combination of such characteristics. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index IUSG is managed by Blackrock, and this fund has amassed over $13.45 billion, which makes it the largest ETF in the Style Box - All Cap Growth. This particular fund, before fees and expenses, seeks to match the performance of the S&P 900 Growth Index. The S&P 900 Growth Index measures the performance of the large and mid-capitalization growth sector of the U.S. equity market. Cost & Other Expenses When considering an ETF's total return, expense ratios are an important factor. And, cheaper funds can significantly outperform their more expensive cousins in the long term if all other factors remain equal. Operating expenses on an annual basis are 0.04% for IUSG, making it one of the least expensive products in the space. It has a 12-month trailing dividend yield of 1.11%. Sector Exposure and Top Holdings While ETFs offer diversified exposure, which minimizes single stock risk, a deep look into a fund's holdings is a valuable exercise. And, most ETFs are very transparent products that disclose their holdings on a daily basis. IUSG's heaviest allocation is in the Information Technology sector, which is about 33.90% of the portfolio. Its Healthcare and Consumer Discretionary round out the top three. Looking at individual holdings, Apple Inc (AAPL) accounts for about 12.37% of total assets, followed by Microsoft Corp (MSFT) and Nvidia Corp (NVDA). Its top 10 holdings account for approximately 42.74% of IUSG's total assets under management. Performance and Risk So far this year, IUSG has added about 17.68%, and was up about 14.80% in the last one year (as of 09/29/2023). During this past 52-week period, the fund has traded between $78.\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for FXI. Express as a decimal (e.g., -0.02).", "answer": "-0.0251", "answer_numeric": -0.02509, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0251 (i.e., on a bad day with 5% probability, the loss exceeds 2.51%). CVaR(95%) = -0.0307.", "metadata": {"var": -0.02509, "cvar": -0.030712, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240105_0360", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PPLT"], "decision_date": "2024-01-05", "context_summary": "PPLT: 60-day return history, mean=0.0009, std=0.0144.", "question": "Asset: PPLT\nDaily returns (past 60 days): mean=0.0009, std=0.0144, min=-0.0269, max=0.0342\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for PPLT. Express as a decimal (e.g., -0.02).", "answer": "-0.0208", "answer_numeric": -0.020802, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0208 (i.e., on a bad day with 5% probability, the loss exceeds 2.08%). CVaR(95%) = -0.0252.", "metadata": {"var": -0.020802, "cvar": -0.025228, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231109_0362", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-11-09", "context_summary": "DOT-USD: 60-day return history, mean=0.0032, std=0.0252.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0032, std=0.0252, min=-0.0397, max=0.0967\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-08] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0323", "answer_numeric": -0.032307, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0323 (i.e., on a bad day with 5% probability, the loss exceeds 3.23%). CVaR(95%) = -0.0370.", "metadata": {"var": -0.032307, "cvar": -0.037007, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230329_0365", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2023-03-29", "context_summary": "LQD: 60-day return history, mean=0.0003, std=0.0063.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0003, std=0.0063, min=-0.0133, max=0.0126\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LQD. Express as a decimal (e.g., -0.02).", "answer": "-0.0086", "answer_numeric": -0.008554, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0086 (i.e., on a bad day with 5% probability, the loss exceeds 0.86%). CVaR(95%) = -0.0122.", "metadata": {"var": -0.008554, "cvar": -0.012217, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231026_0368", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-10-26", "context_summary": "BNB-USD: 60-day return history, mean=0.0005, std=0.0143.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0143, min=-0.0322, max=0.0487\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-25] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0172", "answer_numeric": -0.017182, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0172 (i.e., on a bad day with 5% probability, the loss exceeds 1.72%). CVaR(95%) = -0.0297.", "metadata": {"var": -0.017182, "cvar": -0.029683, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230314_0371", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-03-14", "context_summary": "BNB-USD: 60-day return history, mean=0.0015, std=0.0257.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0015, std=0.0257, min=-0.0674, max=0.0711\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-13] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0393", "answer_numeric": -0.039298, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0393 (i.e., on a bad day with 5% probability, the loss exceeds 3.93%). CVaR(95%) = -0.0564.", "metadata": {"var": -0.039298, "cvar": -0.056407, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240311_0374", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2024-03-11", "context_summary": "XLY: 60-day return history, mean=0.0007, std=0.0101.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0007, std=0.0101, min=-0.0204, max=0.0192\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 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2023-12-31 0000731766 us-gaap:BuildingMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:BuildingMember 2023-12-31 0000731766 unh:CapitalizedsoftwareMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember unh:CapitalizedsoftwareMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2021-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-01-01 2023-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-01-01 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-12-31 0000731766 us-gaap:RestrictedStockMember 2023-01-01 2023-12-31 0000731766 unh:StockOptionsandSARsMember 2023-01-01 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2022-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2022-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0184", "answer_numeric": -0.018379, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0184 (i.e., on a bad day with 5% probability, the loss exceeds 1.84%). CVaR(95%) = -0.0196.", "metadata": {"var": -0.018379, "cvar": -0.019649, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230321_0377", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CORN"], "decision_date": "2023-03-21", "context_summary": "CORN: 60-day return history, mean=-0.0009, std=0.0086.", "question": "Asset: CORN\nDaily returns (past 60 days): mean=-0.0009, std=0.0086, min=-0.0195, max=0.0200\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CORN. Express as a decimal (e.g., -0.02).", "answer": "-0.0165", "answer_numeric": -0.016503, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0165 (i.e., on a bad day with 5% probability, the loss exceeds 1.65%). CVaR(95%) = -0.0178.", "metadata": {"var": -0.016503, "cvar": -0.017782, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230804_0380", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-08-04", "context_summary": "LINK-USD: 60-day return history, mean=0.0023, std=0.0457.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0023, std=0.0457, min=-0.1245, max=0.1799\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-03] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0556", "answer_numeric": -0.055614, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0556 (i.e., on a bad day with 5% probability, the loss exceeds 5.56%). CVaR(95%) = -0.0819.", "metadata": {"var": -0.055614, "cvar": -0.081926, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230828_0382", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2023-08-28", "context_summary": "EMB: 60-day return history, mean=0.0001, std=0.0061.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0001, std=0.0061, min=-0.0143, max=0.0161\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EMB. Express as a decimal (e.g., -0.02).", "answer": "-0.0086", "answer_numeric": -0.008554, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0086 (i.e., on a bad day with 5% probability, the loss exceeds 0.86%). CVaR(95%) = -0.0113.", "metadata": {"var": -0.008554, "cvar": -0.011268, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230123_0385", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2023-01-23", "context_summary": "ACWI: 60-day return history, mean=0.0013, std=0.0115.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0013, std=0.0115, min=-0.0249, max=0.0250\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-20] [\"Apple appeals investigation by UK competition watchdog LONDON, Jan 20 (Reuters) - Technology giant Apple AAPL.O has filed an appeal against an investigation by Britain's competition watchdog into the dominance of its mobile browsers in the cloud gaming market. Last November, the Competition and Markets Authority (CMA), Britain's competition regulator, launched a full investigation into cloud gaming and mobile browsers on concerns about restrictions by iPhone-maker Apple and Google. U.S. tech giants, including Google's owner Alphabet and Apple, are drawing increasing attention from competition regulators in Brussels, London and elsewhere. Lawyers representing Apple said in a notice filed with the Competition Appeal Tribunal on Friday that the CMA's investigation should be reviewed. In its argument, lawyers said that the CMA had missed timing requirements linked to the launch of an investigation. \\\"Apple seeks 1) an Order that the MIR Decision is quashed. 2) a declaration that the MIR Decision and market investigation purportedly launched by reference to it are invalid and of no legal effect,\\\" the filing with the Appeal Tribunal showed. Responding to the appeal, the CMA said on Friday it would defend its position and continue to progress its work in line with the statutory timetable. \\\"We opened this investigation to make sure that UK consumers get a better choice of mobile web services and that UK developers can invest in innovative mobile content and services,\\\" the CMA said in an emailed statement. There is due to be a preliminary hearing on the matter on Tuesday, according to the Competition Appeal Tribunal website. (Reporting by Sarah Young) ((sarah.young@thomsonreuters.com; +44 20 7542 1109; Reuters Messaging: sarah.young.thomsonreuters@reuters.net)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Validea Daily Guru Fundamental Report for AAPL - 1/20/2023 Below is Validea's daily guru fundamental report for APPLE INC (AAPL). Of the twelve guru strategies we follow, AAPL rates highest using our Patient Investor model based on the published strategy of Warren Buffett. This strategy seeks out firms with long-term, predictable profitability and low debt that trade at reasonable valuations. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 100% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. Company Description: Apple Inc. (Apple) designs, manufactures and markets smartphones, personal computers, tablets, wearables and accessories and sells a range of related services. The Company's products include iPhone, Mac, iPad, AirPods, Apple TV, Apple Watch, Beats products, HomePod, iPod touch and accessories. The \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ACWI. Express as a decimal (e.g., -0.02).", "answer": "-0.0173", "answer_numeric": -0.017272, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0173 (i.e., on a bad day with 5% probability, the loss exceeds 1.73%). CVaR(95%) = -0.0214.", "metadata": {"var": -0.017272, "cvar": -0.021414, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231120_0387", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-11-20", "context_summary": "ETH-USD: 60-day return history, mean=0.0039, std=0.0250.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0039, std=0.0250, min=-0.0483, max=0.1224\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0331", "answer_numeric": -0.033108, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0331 (i.e., on a bad day with 5% probability, the loss exceeds 3.31%). CVaR(95%) = -0.0420.", "metadata": {"var": -0.033108, "cvar": -0.041955, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240205_0389", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-02-05", "context_summary": "XLK: 60-day return history, mean=0.0027, std=0.0100.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0027, std=0.0100, min=-0.0265, max=0.0258\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization 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us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-01-01 2023-09-30 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-09-30 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2022-12-31 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2023-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2022-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2023-12-31 0001018724 amzn:VendorAccountsReceivableMember 2022-12-31 0001018724 amzn:VendorAccountsReceivableMember 2023-12-31 0001018724 us-gaap:LoansReceivableMember 2022-12-31 0001018724 us-gaap:LoansReceivableMember 2023-12-31 00 [...TRUNCATED...] tents 32.2 Certification of Brian T. Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0124", "answer_numeric": -0.012401, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0124 (i.e., on a bad day with 5% probability, the loss exceeds 1.24%). CVaR(95%) = -0.0210.", "metadata": {"var": -0.012401, "cvar": -0.020994, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20240513_0392", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IAU"], "decision_date": "2024-05-13", "context_summary": "IAU: 60-day return history, mean=0.0028, std=0.0087.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=0.0028, std=0.0087, min=-0.0238, max=0.0194\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IAU. Express as a decimal (e.g., -0.02).", "answer": "-0.0108", "answer_numeric": -0.01079, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0108 (i.e., on a bad day with 5% probability, the loss exceeds 1.08%). CVaR(95%) = -0.0188.", "metadata": {"var": -0.01079, "cvar": -0.018795, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231129_0395", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2023-11-29", "context_summary": "XHB: 60-day return history, mean=-0.0006, std=0.0158.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=-0.0006, std=0.0158, min=-0.0388, max=0.0435\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XHB. Express as a decimal (e.g., -0.02).", "answer": "-0.0261", "answer_numeric": -0.026126, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0261 (i.e., on a bad day with 5% probability, the loss exceeds 2.61%). CVaR(95%) = -0.0364.", "metadata": {"var": -0.026126, "cvar": -0.036408, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240527_0397", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-05-27", "context_summary": "ETH-USD: 60-day return history, mean=0.0016, std=0.0366.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0016, std=0.0366, min=-0.0748, max=0.1560\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0633", "answer_numeric": -0.063268, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0633 (i.e., on a bad day with 5% probability, the loss exceeds 6.33%). CVaR(95%) = -0.0711.", "metadata": {"var": -0.063268, "cvar": -0.071075, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230808_0400", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-08-08", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0017, std=0.0436.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0017, std=0.0436, min=-0.1591, max=0.1733\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-07] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0529", "answer_numeric": -0.0529, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0529 (i.e., on a bad day with 5% probability, the loss exceeds 5.29%). CVaR(95%) = -0.1008.", "metadata": {"var": -0.0529, "cvar": -0.10075, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240206_0403", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2024-02-06", "context_summary": "REZ: 60-day return history, mean=0.0009, std=0.0125.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0009, std=0.0125, min=-0.0251, max=0.0335\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for REZ. Express as a decimal (e.g., -0.02).", "answer": "-0.0171", "answer_numeric": -0.017133, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0171 (i.e., on a bad day with 5% probability, the loss exceeds 1.71%). CVaR(95%) = -0.0220.", "metadata": {"var": -0.017133, "cvar": -0.021987, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240124_0405", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-01-24", "context_summary": "VLUE: 60-day return history, mean=0.0025, std=0.0089.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0025, std=0.0089, min=-0.0175, max=0.0264\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0093", "answer_numeric": -0.009329, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0093 (i.e., on a bad day with 5% probability, the loss exceeds 0.93%). CVaR(95%) = -0.0126.", "metadata": {"var": -0.009329, "cvar": -0.012564, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240418_0408", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-04-18", "context_summary": "BTC-USD: 60-day return history, mean=0.0035, std=0.0365.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0035, std=0.0365, min=-0.0834, max=0.0969\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0590", "answer_numeric": -0.059018, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0590 (i.e., on a bad day with 5% probability, the loss exceeds 5.90%). CVaR(95%) = -0.0703.", "metadata": {"var": -0.059018, "cvar": -0.070255, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230719_0411", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-07-19", "context_summary": "EFA: 60-day return history, mean=0.0005, std=0.0088.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0005, std=0.0088, min=-0.0175, max=0.0189\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-18] [\"Spain antitrust watchdog fines Amazon, Apple $218 million Adds CNMC quotes, detail throughout MADRID, July 18 (Reuters) - Spain's antitrust watchdog on Tuesday said it had imposed fines worth a total 194.1 million euros ($218.03 million) on Amazon AMZN.O and Apple AAPL.O for colluding to limit the online sale of devices from Apple and competitors in Spain. The two contracts the companies signed on Oct. 31, 2018 granting Amazon the status of authorized Apple dealer included anti-competitive clauses that affected the online market for electronic devices in Spain, CNMC, as the watchdog is known, said in a statement. \\\"The two companies restricted without justification the number of sellers of Apple products on the Amazon website in Spain,\\\" it said. More than 90% of the existing retailers who were using Amazon's market place to sell Apple devices were blocked as a result, CNMC added. Amazon also reduced the capacity of retailers in the European Union based outside Spain to access Spanish customers, the regulator said. It also restricted the advertising Apple's competitors were allowed to place on its website when users searched for Apple products, CNMC said. Following the deal between the two tech giants, the prices of Apple devices sold online rose in Spain, it added. Apple was fined 143.6 million euros and Amazon 50.5 million euros. The two companies have two months to appeal the decision. Representatives for Apple and Amazon did not immediately respond to requests for comment. ($1 = 0.8902 euros) (Reporting by Inti Landauro; Editing by David Latona and Jan Harvey) ((Inti.Landauro@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"AAPL Quantitative Stock Analysis - Warren Buffett Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Patient Investor model based on the published strategy of Warren Buffett. This strategy seeks out firms with long-term, predictable profitability and low debt that trade at reasonable valuations. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 100% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. EARNINGS PREDICTABILITY: PASS DEBT SERVICE: PASS RETURN ON EQUITY: PASS RETURN ON TOTAL CAPITAL: PASS FREE CASH FLOW: PASS USE OF RETAINED EARNINGS: PASS SHARE REPURCHASE: PASS INITIAL RATE OF RETURN: \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0147", "answer_numeric": -0.014711, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0147 (i.e., on a bad day with 5% probability, the loss exceeds 1.47%). CVaR(95%) = -0.0160.", "metadata": {"var": -0.014711, "cvar": -0.015965, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230816_0414", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-08-16", "context_summary": "BNB-USD: 60-day return history, mean=-0.0000, std=0.0180.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0000, std=0.0180, min=-0.0341, max=0.0511\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-15] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0323", "answer_numeric": -0.032325, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0323 (i.e., on a bad day with 5% probability, the loss exceeds 3.23%). CVaR(95%) = -0.0333.", "metadata": {"var": -0.032325, "cvar": -0.03335, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230116_0416", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-01-16", "context_summary": "AVAX-USD: 60-day return history, mean=0.0051, std=0.0449.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0051, std=0.0449, min=-0.1005, max=0.2500\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-15] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0408", "answer_numeric": -0.040796, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0408 (i.e., on a bad day with 5% probability, the loss exceeds 4.08%). CVaR(95%) = -0.0664.", "metadata": {"var": -0.040796, "cvar": -0.066351, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241023_0418", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2024-10-23", "context_summary": "LQD: 60-day return history, mean=0.0001, std=0.0039.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0001, std=0.0039, min=-0.0102, max=0.0098\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LQD. Express as a decimal (e.g., -0.02).", "answer": "-0.0065", "answer_numeric": -0.006471, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0065 (i.e., on a bad day with 5% probability, the loss exceeds 0.65%). CVaR(95%) = -0.0081.", "metadata": {"var": -0.006471, "cvar": -0.008053, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230405_0421", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-04-05", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0022, std=0.0447.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0022, std=0.0447, min=-0.1099, max=0.1115\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-04] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0658", "answer_numeric": -0.065792, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0658 (i.e., on a bad day with 5% probability, the loss exceeds 6.58%). CVaR(95%) = -0.0902.", "metadata": {"var": -0.065792, "cvar": -0.090162, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241127_0424", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-11-27", "context_summary": "XLV: 60-day return history, mean=-0.0011, std=0.0070.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0011, std=0.0070, min=-0.0187, max=0.0118\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 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us-gaap:CertificatesOfDepositMember 2024-01-28 0001045810 us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLV. Express as a decimal (e.g., -0.02).", "answer": "-0.0138", "answer_numeric": -0.013832, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0138 (i.e., on a bad day with 5% probability, the loss exceeds 1.38%). CVaR(95%) = -0.0162.", "metadata": {"var": -0.013832, "cvar": -0.016202, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20240805_0427", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-08-05", "context_summary": "EEM: 60-day return history, mean=-0.0002, std=0.0084.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0002, std=0.0084, min=-0.0176, max=0.0217\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q AAPL 2024-08-02] aapl-20240629 false 2024 Q3 0000320193 --09-28 P1Y P1Y P1Y P1Y http://fasb.org/us-gaap/2023#MarketableSecuritiesCurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesNoncurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesCurrent http://fasb.org/us-gaap/2023#MarketableSecuritiesNoncurrent http://fasb.org/us-gaap/2023#LongTermDebtCurrent http://fasb.org/us-gaap/2023#LongTermDebtNoncurrent 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2024-06-29 0000320193 us-gaap:FairValueInputsLevel1Member 2024-06-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasurySecuritiesMember 2024-06-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-06-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:ForeignGovernmentDebtSecuritiesMember 2024-06-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:BankTimeDepositsMember 2024-06-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CommercialPaperMember 2024-06-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2024-06-29 0000 [...TRUNCATED...] purchases 45,690  $ 169.74  45,690  May 5, 2024 to June 1, 2024: Open market and privately negotiated purchases 51,729  $ 188.38  51,729  June 2, 2024 to June 29, 2024: Open market and privately negotiated purchases 41,354  $ 205.54  41,354  Total 138,773  $ 114,074  (1) On May 4, 2023, the Board of Directors authorized the purchase of up to $90 billion of the Company’s common stock under a share repurchase program. As of June 29, 2024, remaining availability under the May 2023 program was $4.1 billion. On May 2, 2024, the Board of Directors authorized an additional program to repurchase up to $110 billion of the Company’s common stock. The programs do not obligate the Company to acquire a minimum amount of shares. Under the programs, shares may be repurchased in privately negotiated or open market transactions, including under plans complying with Rule 10b5-1 under the Exchange Act. Item 3.    Defaults Upon Senior Securities None. Item 4.    Mine Safety Disclosures Not applicable. Item 5.    Other Information Insider Trading Arrangements On May 24, 2024 , Tim Cook , the Company’s Chief Executive Officer , entered into a trading plan intended to satisfy the affirmative defense conditions of Rule 10b5-1(c) under the Exchange Act. The plan provides for the sale, subject to certain price limits, of shares vesting during the duration of the plan pursuant to certain equity awards granted to Mr. Cook, excluding shares withheld by the Company to satisfy income tax withholding and remittance obligations. Mr. Cook’s plan will expire on May 24, 2026, subject to early termination in accordance with the terms of the plan. Apple Inc. | Q3 2024 Form 10-Q | 20 Item 6.    Exhibits Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 31.1* Rule 13a-14(a) / 15d-14(a) Certification of Chief Executive Officer. 31.2* Rule 13a-14(a) / 15d-14(a) Certification of Chief Financial Officer. 32.1** Section 1350 Certifications of Chief Executive Officer and Chief Financial Officer. 101* Inline XBRL Document Set for the condensed consolidated financial statements and accompanying notes in Part I, Item 1, “Financial Statements” of this Quarterly Report on Form 10-Q. 104* Inline XBRL for the cover page of this Quarterly Report on Form 10-Q, included in the Exhibit 101 Inline XBRL Document Set. *    Filed herewith. **    Furnished herewith. Apple Inc. | Q3 2024 Form 10-Q | 21 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: August 1, 2024 Apple Inc. By: /s/ Luca Maestri Luca Maestri Senior Vice President, Chief Financial Officer Apple Inc. | Q3 2024 Form 10-Q | 22\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0146", "answer_numeric": -0.014639, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0146 (i.e., on a bad day with 5% probability, the loss exceeds 1.46%). CVaR(95%) = -0.0163.", "metadata": {"var": -0.014639, "cvar": -0.016339, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20240904_0430", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-09-04", "context_summary": "EFA: 60-day return history, mean=0.0002, std=0.0098.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0002, std=0.0098, min=-0.0269, max=0.0182\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0159", "answer_numeric": -0.015851, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0159 (i.e., on a bad day with 5% probability, the loss exceeds 1.59%). CVaR(95%) = -0.0216.", "metadata": {"var": -0.015851, "cvar": -0.021612, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241004_0433", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2024-10-04", "context_summary": "IAU: 60-day return history, mean=0.0014, std=0.0091.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=0.0014, std=0.0091, min=-0.0180, max=0.0222\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IAU. Express as a decimal (e.g., -0.02).", "answer": "-0.0122", "answer_numeric": -0.012229, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0122 (i.e., on a bad day with 5% probability, the loss exceeds 1.22%). CVaR(95%) = -0.0152.", "metadata": {"var": -0.012229, "cvar": -0.015197, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241230_0436", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-12-30", "context_summary": "EEM: 60-day return history, mean=-0.0015, std=0.0095.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0015, std=0.0095, min=-0.0250, max=0.0219\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0216", "answer_numeric": -0.021559, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0216 (i.e., on a bad day with 5% probability, the loss exceeds 2.16%). CVaR(95%) = -0.0245.", "metadata": {"var": -0.021559, "cvar": -0.02452, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240116_0440", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-01-16", "context_summary": "AVAX-USD: 60-day return history, mean=0.0098, std=0.0559.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0098, std=0.0559, min=-0.0947, max=0.1652\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0871", "answer_numeric": -0.087104, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0871 (i.e., on a bad day with 5% probability, the loss exceeds 8.71%). CVaR(95%) = -0.0909.", "metadata": {"var": -0.087104, "cvar": -0.090911, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240723_0443", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2024-07-23", "context_summary": "HYG: 60-day return history, mean=0.0008, std=0.0026.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0008, std=0.0026, min=-0.0040, max=0.0062\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for HYG. Express as a decimal (e.g., -0.02).", "answer": "-0.0030", "answer_numeric": -0.003021, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0030 (i.e., on a bad day with 5% probability, the loss exceeds 0.30%). CVaR(95%) = -0.0038.", "metadata": {"var": -0.003021, "cvar": -0.0038, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240221_0446", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-02-21", "context_summary": "SGOV: 60-day return history, mean=0.0002, std=0.0002.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, min=0.0000, max=0.0006\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = 0.0000.", "metadata": {"var": 0.0, "cvar": 0.0, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231130_0448", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-11-30", "context_summary": "CSHI: 60-day return history, mean=0.0002, std=0.0005.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0005, min=-0.0009, max=0.0021\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0004", "answer_numeric": -0.000407, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0004 (i.e., on a bad day with 5% probability, the loss exceeds 0.04%). CVaR(95%) = -0.0008.", "metadata": {"var": -0.000407, "cvar": -0.00076, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241014_0451", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-10-14", "context_summary": "USMV: 60-day return history, mean=0.0011, std=0.0060.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0011, std=0.0060, min=-0.0226, max=0.0130\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0078", "answer_numeric": -0.007788, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0078 (i.e., on a bad day with 5% probability, the loss exceeds 0.78%). CVaR(95%) = -0.0145.", "metadata": {"var": -0.007788, "cvar": -0.014474, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230829_0454", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-08-29", "context_summary": "XRP-USD: 60-day return history, mean=-0.0015, std=0.0536.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0015, std=0.0536, min=-0.1380, max=0.3257\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-28] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0487", "answer_numeric": -0.048731, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0487 (i.e., on a bad day with 5% probability, the loss exceeds 4.87%). CVaR(95%) = -0.1023.", "metadata": {"var": -0.048731, "cvar": -0.102251, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230413_0457", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-04-13", "context_summary": "ICSH: 60-day return history, mean=0.0003, std=0.0004.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0003, std=0.0004, min=-0.0008, max=0.0012\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ICSH. Express as a decimal (e.g., -0.02).", "answer": "-0.0004", "answer_numeric": -0.000398, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0004 (i.e., on a bad day with 5% probability, the loss exceeds 0.04%). CVaR(95%) = -0.0006.", "metadata": {"var": -0.000398, "cvar": -0.000598, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240816_0460", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-08-16", "context_summary": "ADA-USD: 60-day return history, mean=-0.0034, std=0.0389.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0034, std=0.0389, min=-0.1079, max=0.0869\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0666", "answer_numeric": -0.06664, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0666 (i.e., on a bad day with 5% probability, the loss exceeds 6.66%). CVaR(95%) = -0.0903.", "metadata": {"var": -0.06664, "cvar": -0.090311, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230622_0462", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-06-22", "context_summary": "VTI: 60-day return history, mean=0.0016, std=0.0077.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0016, std=0.0077, min=-0.0168, max=0.0186\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-21] [\"Quality Dividend Growth ETF DGRW Hits Ten Years While the three-year ETF milestone has plenty of importance, consider the power of the ten year ETF birthday. That\\u2019s the news for the WisdomTree U.S. Quality Dividend Growth Fund (DGRW) which had its ten year birthday in May. As part of its birthday celebrations, the strategy also added $268.6 million in net inflows, enough to lift the quality dividend ETF above $9 billion in AUM. That should invite advisors to consider the potent combination of quality and dividends. DGRW tracks the WisdomTree U.S. Quality Dividend Growth Index for a 28 basis point fee, and offers a 2.01% annual dividend yield as of May. The index tracks the performance of large and mid-cap dividend-paying U.S. stocks that fit a growth framework. DGRW focuses on dividend growth potential rather than just looking backwards at past dividend increases. It does so by looking at forward-looking earnings estimates based on things like historical return on assets (ROA) and return on equity (ROE). That approach has helped the quality dividend growth ETF outperform the S&P 500 Index by 0.22% annually over the last ten years. The strategy goes back to some solid research from the firm\\u2019s now Global CIO Jeremy Schwartz and Global Head of Research Christopher Gannatti. Those white papers focused on the rationale behind using ROE and ROA with a forward-looking dividend growth screen. Combining the two has helped DGRW limit reliance on superficially high ROE figures caused by firms taking on leverage, for example. Together, that\\u2019s helped its index look forward compared to the NASDAQ U.S. Dividend Achievers Select Index which requires ten consecutive years of dividend growth. That requirement, DGRW\\u2019s managers fear, may fail to capture growth opportunities. See more: \\u201cDigging Into Up-and-Coming Quality Growth ETF QGRW\\u201d For example, Apple (AAPL) joined the WisdomTree U.S. Dividend Growth Index back in 2013, but wasn\\u2019t eligible for the NASDAQ index until 2023, per an old WisdomTree blog. Taken together, those research lessons have helped DGRW return 21% over the last year and 15.5% over the last three years. That\\u2019s helped DGRW outperform its ETF Database Category and Factset Segment averages in those time frames. For investors looking for a quality dividend growth ETF, DGRW stands out as one to consider. For more news, information, and analysis, visit the Modern Alpha Channel. Read more on ETFtrends.com. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Turnkey Tech Investing: May 2023 Market Brief For some time, markets have been grappling with a handful of counteracting dynamics, including the clash between the bulls and the bears, the interplay between stimulus and inflation, and the delicate balance between growth and rate hikes. Adding to the mix in May was the US debt-ceiling conundrum and, of course, the \\u2018emerge\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VTI. Express as a decimal (e.g., -0.02).", "answer": "-0.0079", "answer_numeric": -0.007925, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0079 (i.e., on a bad day with 5% probability, the loss exceeds 0.79%). CVaR(95%) = -0.0132.", "metadata": {"var": -0.007925, "cvar": -0.013248, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240813_0465", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-08-13", "context_summary": "BNB-USD: 60-day return history, mean=-0.0019, std=0.0317.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0019, std=0.0317, min=-0.0765, max=0.0909\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0615", "answer_numeric": -0.061469, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0615 (i.e., on a bad day with 5% probability, the loss exceeds 6.15%). CVaR(95%) = -0.0707.", "metadata": {"var": -0.061469, "cvar": -0.070652, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230104_0468", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-01-04", "context_summary": "ADA-USD: 60-day return history, mean=-0.0077, std=0.0389.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0077, std=0.0389, min=-0.1452, max=0.1609\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-03] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0568", "answer_numeric": -0.056838, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0568 (i.e., on a bad day with 5% probability, the loss exceeds 5.68%). CVaR(95%) = -0.1153.", "metadata": {"var": -0.056838, "cvar": -0.115261, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241217_0471", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-12-17", "context_summary": "DOT-USD: 60-day return history, mean=0.0144, std=0.0650.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0144, std=0.0650, min=-0.1824, max=0.2770\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0608", "answer_numeric": -0.060793, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0608 (i.e., on a bad day with 5% probability, the loss exceeds 6.08%). CVaR(95%) = -0.1043.", "metadata": {"var": -0.060793, "cvar": -0.1043, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230821_0474", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-08-21", "context_summary": "XRP-USD: 60-day return history, mean=-0.0019, std=0.0537.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0019, std=0.0537, min=-0.1380, max=0.3257\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-20] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0487", "answer_numeric": -0.048731, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0487 (i.e., on a bad day with 5% probability, the loss exceeds 4.87%). CVaR(95%) = -0.1023.", "metadata": {"var": -0.048731, "cvar": -0.102251, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230713_0477", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-07-13", "context_summary": "XRP-USD: 60-day return history, mean=0.0020, std=0.0236.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0020, std=0.0236, min=-0.0767, max=0.0562\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-12] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0389", "answer_numeric": -0.038936, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0389 (i.e., on a bad day with 5% probability, the loss exceeds 3.89%). CVaR(95%) = -0.0598.", "metadata": {"var": -0.038936, "cvar": -0.059838, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230619_0479", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-06-19", "context_summary": "XLF: 60-day return history, mean=0.0012, std=0.0096.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0012, std=0.0096, min=-0.0229, max=0.0244\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-16] [\"3 Stocks to Buy for Long-Term, Life-Changing Returns InvestorPlace - Stock Market News, Stock Advice & Trading Tips Investors are always on the hunt for long-term wealth stocks. You know, the kind that you can buy and hold for years (or decades) and generate market-beating returns. We\\u2019re all after that \\u2014 that\\u2019s why we read articles like this one. When investing for the future, readers have to look under the hood and find high-quality businesses. At the same time, it can be hard when looking for long-term investment stocks. That\\u2019s because so many of the best stocks have already generated the life-changing returns that investors are currently looking for. A stock like Apple (NASDAQ:AAPL) is an amazing business. But with a near-$3 trillion market valuation, there is a concern that its bigger growth days are behind it. Or take Johnson & Johnson (NYSE:JNJ). I love the company, but with a $425 billion market cap and only modest growth, it\\u2019s hard to imagine it outperforming the S&P 500 year-in and year-out. So what are some long-term wealth stocks to buy now? Investing for the Future: The Trade Desk (TTD) Source: Tada Images / Shutterstock.com There is absolutely nothing wrong with the businesses above (Apple and J&J). Almost any investor could make a case for them. However, I am looking for stocks that can generate outsized market returns over the long haul from here, not stocks that have already created those returns. One such stock? The Trade Desk (NASDAQ:TTD): The Trade Desk is a digital advertising firm that utilizes a demand-side platform. This not only drives efficiency for the customer, but drives profit for the company. Further, The Trade Desk makes it easy for customers to leverage connected TVs, audio, video, mobile and other mediums for their advertising needs. Before the pandemic, after the pandemic and through the 2022 bear market, investors experienced a lot of volatility in TTD stock. However, the company remained incredibly stable. It\\u2019s able to operate around the world (China included) and continues to churn out steady growth. Consensus expectations call for more than 20% revenue growth this year and next year, to go alongside 17% earnings growth in 2023 and 20.5% growth in 2024. Long-Term Wealth Stocks: PayPal (PYPL) Source: Michael Vi / Shutterstock.com PayPal (NASDAQ:PYPL): This fintech company is a controversial pick when it comes to long-term wealth stocks. The biggest reason? Because the stock has fallen out of favor with the market and suffered a peak-to-trough decline in excess of 80%. The stock has only recently hit a 52-week low. While many large cap and high growth stocks have come back to life, that has not been the case with PayPal. To be frank, I\\u2019m not sure why that\\u2019s been the case. PayPal has a solid brand and has been one of the market\\u2019s favorite stocks over the years. From the time it was spun off in mid-2015 to its high in February 2020 (just before the Covid-19 selloff), \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0129", "answer_numeric": -0.012921, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0129 (i.e., on a bad day with 5% probability, the loss exceeds 1.29%). CVaR(95%) = -0.0178.", "metadata": {"var": -0.012921, "cvar": -0.017793, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230720_0482", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-07-20", "context_summary": "XLY: 60-day return history, mean=0.0031, std=0.0104.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0031, std=0.0104, min=-0.0200, max=0.0260\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-19] [\"Technology Sector Update for 07/19/2023: AAPL, U, MSFT, ATVI Tech stocks were lower Wednesday afternoon with the Technology Select Sector SPDR Fund (XLK) decreasing 0.5% and the Philadelphia Semiconductor index falling 1.1%. In company news, Apple (AAPL) has been working on generative artificial intelligence tools to catch up with rivals, but it hasn't decided yet how to release the new technology to consumers, Bloomberg reported Wednesday. Apple shares were adding 0.5%. Unity Software (U) was up 1.7% after the company launched its beta program for visionOS, the operating system that powers Apple's Vision Pro. Microsoft (MSFT) and Activision Blizzard (ATVI) revised some terms of their planned deal and extended the time period by which the companies must close the deal as they seek to resolve the remaining regulatory hurdles. Microsoft shares fell1.9% and Activision dropped 0.5%. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple tests generative AI tools to rival OpenAI's ChatGPT - Bloomberg News Updates shares, adds details from the report and background July 19 (Reuters) - Apple AAPL.O is working on artificial intelligence(AI) offerings similar to OpenAI's ChatGPT and Google's Bard, Bloomberg News reported on Wednesday, sending its shares up as much as 2% to a record high. The iPhone maker has built its own framework, known as \\\"Ajax\\\", to create large language models (LLMs) and is also testing a chatbot that some engineers call \\\"Apple GPT\\\", the report said,citing people with knowledge of the matter. The company did not respond to a Reuters request for comment. Apple has so far held back from any big moves in AI and even avoided mentioning the buzzword at its developer conference in June - in stark contrast to other tech giants such as Alphabet GOOGL.O and Microsoft MSFT.Owhich have made bold moves to incorporate the breakthrough technology. Shares of Microsoft, Nvidia NVDA.O and Alphabet dropped more than 1% after the report. Apple has, however, subtly pushed advanced AI in some of its products such as Apple Photos, on device texting, and the recently launched mixed-reality headset Vision Pro. Still, analysts say the company is behind peers in incorporating the new technology. Apple's core AI product, voice assistant Siri, has also stagnated over the years. The Bloomberg report said several teams are involved in the latest AI effort, which is led by John Giannandrea, the company's head of machine learning and AI, andCraig Federighi, Apple's top software engineering executive. Apple's new virtual assistant summarizes text and answers questions based on data it has been trained with, and is being used internally for product prototyping, according to the report. Employees say the tool essentially replicates Bard, ChatGPT and Bing AI, and works as a web application. Apple does not yet have a concrete plan for the tools it is developing, but it is aiming\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0121", "answer_numeric": -0.012128, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0121 (i.e., on a bad day with 5% probability, the loss exceeds 1.21%). CVaR(95%) = -0.0164.", "metadata": {"var": -0.012128, "cvar": -0.016385, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231222_0485", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-12-22", "context_summary": "EEM: 60-day return history, mean=0.0011, std=0.0095.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0011, std=0.0095, min=-0.0182, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-21] [\"Guru Fundamental Report for AMD Below is Validea's guru fundamental report for ADVANCED MICRO DEVICES, INC. (AMD). Of the 22 guru strategies we follow, AMD rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. ADVANCED MICRO DEVICES, INC. (AMD) is a large-cap growth stock in the Semiconductors industry. The rating using this strategy is 100% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of ADVANCED MICRO DEVICES, INC. AMD Guru Analysis AMD Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-Wall St eyes higher open after broad sell-off; Micron shines By Johann M Cherian and Shristi Achar A Dec 21 (Reuters) - U.S. stocks were set for a higher open on Thursday, recovering from a broad sell-off on Wall Street in the prior session as investors clung to hopes of borrowing costs easing next year, while chipmaker\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0133", "answer_numeric": -0.013253, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0133 (i.e., on a bad day with 5% probability, the loss exceeds 1.33%). CVaR(95%) = -0.0156.", "metadata": {"var": -0.013253, "cvar": -0.01562, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230815_0488", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-08-15", "context_summary": "ETH-USD: 60-day return history, mean=0.0019, std=0.0181.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0181, min=-0.0335, max=0.0718\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-14] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0222", "answer_numeric": -0.022152, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0222 (i.e., on a bad day with 5% probability, the loss exceeds 2.22%). CVaR(95%) = -0.0329.", "metadata": {"var": -0.022152, "cvar": -0.032855, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240326_0491", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-03-26", "context_summary": "XLF: 60-day return history, mean=0.0016, std=0.0063.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0016, std=0.0063, min=-0.0136, max=0.0170\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 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us-gaap:FurnitureAndFixturesMember srt:MinimumMember 2024-01-31 0000104169 srt:MaximumMember us-gaap:FurnitureAndFixturesMember 2024-01-31 0000104169 us-gaap:FurnitureAndFixturesMember 2024-01-31 0000104169 us-gaap:FurnitureAndFixturesMember 2023-01-31 0000104169 us-gaap:TransportationEquipmentMember srt:MinimumMember 2024-01-31 0000104169 srt:MaximumMember us-gaap:TransportationEquipmentMember 2024-01-31 0000104169 us-gaap:TransportationEquipmentMember 2024-01-31 0000104169 us-gaap:TransportationEquipmentMember 2023-01-31 0000104169 us-gaap:ConstructionInProgressMember 2024-01-31 0000104169 us-gaap:ConstructionInProgressMember 2023-01-31 0000104169 wmt:WalmartUSMember 2022-01-31 0000104169 wmt:WalmartInternationalMember 2022-01-31 0000104169 wmt:SamsClubMember 2022-01-31 0000104169 wmt:WalmartUSMember 2022-02-01 2023-01-31 0000104169 wmt:WalmartInternationalMember 2022-02-01 2023-01-31 0000104169 wmt:SamsClubMember 2022-02-01 2023-01-31 0000104169 wmt:WalmartUSMember 2023-01-31 0000104169 wmt:WalmartInternationalMember 2023-01-31 0000104169 wmt:SamsClubMember 2023-01-31 0000104169 wmt:WalmartUSMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartInternationalMember 2023-02-01 2024-01-31 0000104169 wmt:SamsClubMember 2023-02-01 2024-01-31 0000104169 wmt:WalmartUSMember 2024-01-31 0000104169 wmt:WalmartInternationalMember 2024-01-31 0000104169 wmt:SamsClubMember 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2023-02-01 2024-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2022-02-01 2023-01-31 0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0087", "answer_numeric": -0.008661, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0087 (i.e., on a bad day with 5% probability, the loss exceeds 0.87%). CVaR(95%) = -0.0125.", "metadata": {"var": -0.008661, "cvar": -0.012474, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241227_0494", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-12-27", "context_summary": "LINK-USD: 60-day return history, mean=0.0117, std=0.0650.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0117, std=0.0650, min=-0.1453, max=0.1799\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0785", "answer_numeric": -0.07855, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0785 (i.e., on a bad day with 5% probability, the loss exceeds 7.85%). CVaR(95%) = -0.1103.", "metadata": {"var": -0.07855, "cvar": -0.110322, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240118_0497", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-01-18", "context_summary": "IWM: 60-day return history, mean=0.0017, std=0.0137.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0017, std=0.0137, min=-0.0270, max=0.0349\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0165", "answer_numeric": -0.016465, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0165 (i.e., on a bad day with 5% probability, the loss exceeds 1.65%). CVaR(95%) = -0.0211.", "metadata": {"var": -0.016465, "cvar": -0.021146, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240726_0500", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-07-26", "context_summary": "ADA-USD: 60-day return history, mean=-0.0020, std=0.0320.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0320, min=-0.1079, max=0.0646\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0439", "answer_numeric": -0.043855, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0439 (i.e., on a bad day with 5% probability, the loss exceeds 4.39%). CVaR(95%) = -0.0731.", "metadata": {"var": -0.043855, "cvar": -0.073134, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230522_0502", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-05-22", "context_summary": "XLP: 60-day return history, mean=0.0007, std=0.0062.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0007, std=0.0062, min=-0.0099, max=0.0169\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-19] [\"Warren Buffett on Apple, Banks, and Value Investing In this podcast, Motley Fool senior analyst Jason Moser discusses: Berkshire Hathaway's first-quarter results and highlights from the annual meeting. Buffett's comments about Apple and the banking industry. Charlie Munger's warning about overdiversification. Motley Fool senior analyst Jim Gillies talks about the vibe at the Berkshire Hathaway annual meeting. To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. To get started investing, check out our quick-start guide to investing in stocks. A full transcript follows the video. 10 stocks we like better than Berkshire Hathaway When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now\\u2026 and Berkshire Hathaway wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of May 8, 2023 This video was recorded on May 8, 2023. Chris Hill: Omaha, somewhere in Middle America. We're going to get right to the heart of the matter of the Berkshire Hathaway Annual Meeting. Motley Fool Money starts now. [music] I'm Chris Hill. Joining me in studio: Motley Fool Senior Analyst Jason Moser. Thanks for being here. Jason Moser: Hey, thanks for having me. Chris Hill: Let's talk a little about Berkshire Hathaway, shall we? Jason Moser: Sure. Chris Hill: We're going to get to the Q&A in a second. I do just want to point out, I think it's a sign of what an event the Berkshire Hathaway Annual Meeting is and how much attention is paid to the marathon Q&A session that Buffett and Charlie Munger do that we basically all, as an investment community, just basically missed the fact that they reported first-quarter earnings. Jason Moser: That is so secondary. Chris Hill: It's just like, oh, by the way, the results were better than expected. Geico is profitable again after a year and a half of not being profitable. Berkshire Hathaway now has $130 billion in cash. That aside... Jason Moser: They're in a good spot, Chris. Chris Hill: Let's get to some of the highlights from the Q&A session. And the thing that stood out to me, both as a Berkshire Hathaway shareholder and as a shareholder of Apple, is the flowers that Buffett was throwing at Apple, basically saying, this is the best business we invest in. Jason Moser: For the longest time, they really steered clear of \\\"tech stocks\\\" because they just felt like it was outside of their circle of competence, so to speak. I think Apple transcends that. I have always said Apple is literally a company that could stamp its brand on a rock and sell 3 million, no questions asked. It is that powerful, and I'm not even kidding. I absolutely believe that. Chris Hill: The iRock. Jason Moser: People just say, hey, it's a special r\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLP. Express as a decimal (e.g., -0.02).", "answer": "-0.0085", "answer_numeric": -0.008524, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0085 (i.e., on a bad day with 5% probability, the loss exceeds 0.85%). CVaR(95%) = -0.0095.", "metadata": {"var": -0.008524, "cvar": -0.009513, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240624_0505", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-06-24", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0033, std=0.0319.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0033, std=0.0319, min=-0.0806, max=0.0982\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0537", "answer_numeric": -0.053714, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0537 (i.e., on a bad day with 5% probability, the loss exceeds 5.37%). CVaR(95%) = -0.0661.", "metadata": {"var": -0.053714, "cvar": -0.066086, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231220_0507", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-12-20", "context_summary": "XLK: 60-day return history, mean=0.0026, std=0.0098.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0026, std=0.0098, min=-0.0193, max=0.0258\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] [\"Here's Why I Just Sold These 2 Blue-Chip Stocks, Even Though They're Great Businesses One of our contributors recently sold several positions, including two absolutely incredible businesses.\", \"JPMorgan Among Winners as Latin American Wealth Flocks to Miami (Bloomberg) -- Latin America\\u2019s wealthiest investors are taking their fortunes to Miami at one of the fastest clips in history, with some fleeing regional turmoil and others lured by yields higher than they can find at home.Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Houthi Ship AttacksUS Announces New Task Force to Counter Houthi Red Sea ThreatUS Frackers Return to\", \"Demise of Small Caps Haunts Wall Street in the Age of Big Tech (Bloomberg) -- Declaring the demise of an asset class is a mistake people have made since the dawn of markets. It\\u2019s a temptation many on Wall Street succumbed to recently when small-cap stocks notched two-decade lows versus the S&P 500 \\u2013 only to rally sharply after the Federal Reserve\\u2019s dovish policy surprise last week.Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Hou\", \"Brazil Central Bank Reinforces Cautious View on Fight to Bring Inflation Back to Target (Bloomberg) -- Brazil\\u2019s central bank reinforced there\\u2019s still a long way to go to bring inflation back to target, warning that the El Nino weather pattern may have a bigger impact on food prices than initially thought. Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Houthi Ship AttacksUS Announces New Task Force to Counter Houthi Red Sea ThreatUS Frackers Return to Haun\", \"Will Taiwan Semiconductor Be a Trillion-Dollar Stock by 2030? Taiwan Semiconductor has a vital product for many of the most important tech companies.\", \"UBS Investor Cevian to Be an \\u2018Engaged Owner\\u2019 Over Long Term (Bloomberg) -- Activist investor Cevian Capital AB, which picked up a $1.3 billion stake in UBS Group AG, said it\\u2019s planning to hold the shares for the long term, betting the Swiss bank\\u2019s current strategy would help create the world\\u2019s biggest global wealth manager. Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Houthi Ship AttacksWhat If Putin Wins? US Allies Fear Defe\", \"Canadian Dollar Surges to Highest Since August as Inflation Stays Elevated (Bloomberg) -- The rate of inflation in Canada unexpectedly remained stuck at 3.1% last month, giving the central bank another reason to keep its policy rate at the highest level in two decades.Most Read from BloombergApple Races t\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0171", "answer_numeric": -0.017057, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0171 (i.e., on a bad day with 5% probability, the loss exceeds 1.71%). CVaR(95%) = -0.0182.", "metadata": {"var": -0.017057, "cvar": -0.018188, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20241226_0509", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-12-26", "context_summary": "AVAX-USD: 60-day return history, mean=0.0095, std=0.0616.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0095, std=0.0616, min=-0.1614, max=0.2028\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0622", "answer_numeric": -0.062181, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0622 (i.e., on a bad day with 5% probability, the loss exceeds 6.22%). CVaR(95%) = -0.1192.", "metadata": {"var": -0.062181, "cvar": -0.119189, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231127_0512", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-11-27", "context_summary": "EEM: 60-day return history, mean=-0.0001, std=0.0096.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0001, std=0.0096, min=-0.0175, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-24] [\"Netflix (NFLX) Drops Trailer for Gyeongseong Creature K-Drama Netflix NFLX has revealed the teaser for its upcoming Korean show, Gyeongseong Creature, which is shaping up to be an exciting and intriguing series, blending historical drama with elements of the creature genre. The teaser poster and trailer provide a glimpse into the suspenseful narrative, which is set in the spring of 1945 and the challenge of battling a monstrous entity born from human greed adds an interesting layer to the narrative. The combination of historical context and the mysterious Ongseong Hospital as a vital location adds an extra layer of depth to the story. The involvement of main characters like Jang Tae-sang and Yoon Chae-ok, played by Park Seo-joon and Han So-hee respectively, adds excitement to the storyline. The plot, with its race against time and the threat faced by Tae-sang to find the missing lover of Commissioner Ishikawa, creates a sense of urgency and intrigue. The partnership between Tae-sang and Chae-ok, both experts in their own right, includes an interesting dimension to the narrative. Aside from Park Seo-joon and Han So-hee, the new Netflix Korean original series will also feature Claudia Kim (Avengers: Age Of Ultron), Squid Game alum Wi Ha-joon, Kim Hae-sook and Jo Han-chul, among others. With the release of Part 1 on Dec 22 and Part 2 on Jan 5 exclusively on Netflix, it seems like viewers can anticipate a thrilling and suspenseful experience as they delve into the world of Gyeongseong Creature. Netflix, Inc. Price and Consensus Netflix, Inc. price-consensus-chart | Netflix, Inc. Quote Korean Content Lineup to Boost User Growth Netflix is investing heavily in Korean-language content since Korea emerged as an entertainment superpower with K-pop groups like BTS, K-dramas like All of Us Are Dead and the Oscar-winning Korean movie Parasite dominating the entertainment industry globally. NFLX is currently producing an upcoming Korean drama, The Trunk, starring Korea\\u2019s A-listers like Gong Yoo of Train to Busan and Goblin and Seo Hyun-jin, known for Another Miss Oh and The Beauty Inside. The story, written by Park Eun-young of Hwarang: The Poet Warrior Youth and directed by Kim Gyu-tae of Our Blues, revolves around a marriage arrangement service where clients are arranged into a contract marriage for a year with their most suited partner and the series of secrets that unfold after a mysterious trunk floats ashore. The company also confirmed the production of Aema, a Korean original series following the struggles of Hui-ran and Joo-ae in creating the 1980s hit film Madame Aema, set in 80s Chungmuro, showcasing the harsh realities of actors in the glitzy Korean film industry. Expanding the Korean language portfolio will strengthen the Asia-Pacific (APAC) segment\\u2019s performance in the near term. For the third quarter of 2023, the paid subscriber base for APAC jumped 17.1% from the year-ago quarter to 42.43 million. The company added 1.88 million paid\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0134", "answer_numeric": -0.013374, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0134 (i.e., on a bad day with 5% probability, the loss exceeds 1.34%). CVaR(95%) = -0.0157.", "metadata": {"var": -0.013374, "cvar": -0.015678, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230203_0515", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2023-02-03", "context_summary": "DBB: 60-day return history, mean=0.0020, std=0.0123.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=0.0020, std=0.0123, min=-0.0244, max=0.0276\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DBB. Express as a decimal (e.g., -0.02).", "answer": "-0.0155", "answer_numeric": -0.015497, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0155 (i.e., on a bad day with 5% probability, the loss exceeds 1.55%). CVaR(95%) = -0.0199.", "metadata": {"var": -0.015497, "cvar": -0.019915, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241206_0517", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-12-06", "context_summary": "BNB-USD: 60-day return history, mean=0.0041, std=0.0281.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0041, std=0.0281, min=-0.0527, max=0.1391\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0338", "answer_numeric": -0.033831, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0338 (i.e., on a bad day with 5% probability, the loss exceeds 3.38%). CVaR(95%) = -0.0416.", "metadata": {"var": -0.033831, "cvar": -0.04159, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230629_0520", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-06-29", "context_summary": "DOT-USD: 60-day return history, mean=-0.0032, std=0.0258.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0032, std=0.0258, min=-0.0915, max=0.0558\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-28] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0424", "answer_numeric": -0.042367, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0424 (i.e., on a bad day with 5% probability, the loss exceeds 4.24%). CVaR(95%) = -0.0616.", "metadata": {"var": -0.042367, "cvar": -0.061608, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240919_0523", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2024-09-19", "context_summary": "XLP: 60-day return history, mean=0.0011, std=0.0064.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0011, std=0.0064, min=-0.0199, max=0.0128\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLP. Express as a decimal (e.g., -0.02).", "answer": "-0.0072", "answer_numeric": -0.007191, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0072 (i.e., on a bad day with 5% probability, the loss exceeds 0.72%). CVaR(95%) = -0.0129.", "metadata": {"var": -0.007191, "cvar": -0.01293, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240715_0526", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-07-15", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0037, std=0.0357.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0037, std=0.0357, min=-0.0806, max=0.0982\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0617", "answer_numeric": -0.061713, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0617 (i.e., on a bad day with 5% probability, the loss exceeds 6.17%). CVaR(95%) = -0.0727.", "metadata": {"var": -0.061713, "cvar": -0.072703, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240514_0528", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-05-14", "context_summary": "BTC-USD: 60-day return history, mean=-0.0016, std=0.0327.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0016, std=0.0327, min=-0.0834, max=0.0969\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0507", "answer_numeric": -0.050652, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0507 (i.e., on a bad day with 5% probability, the loss exceeds 5.07%). CVaR(95%) = -0.0678.", "metadata": {"var": -0.050652, "cvar": -0.067798, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230217_0531", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-02-17", "context_summary": "ETH-USD: 60-day return history, mean=0.0058, std=0.0265.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0058, std=0.0265, min=-0.0632, max=0.0751\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-16] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0339", "answer_numeric": -0.033914, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0339 (i.e., on a bad day with 5% probability, the loss exceeds 3.39%). CVaR(95%) = -0.0517.", "metadata": {"var": -0.033914, "cvar": -0.051687, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230510_0534", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-05-10", "context_summary": "SOL-USD: 60-day return history, mean=0.0029, std=0.0396.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0029, std=0.0396, min=-0.0861, max=0.1144\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-09] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0551", "answer_numeric": -0.055073, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0551 (i.e., on a bad day with 5% probability, the loss exceeds 5.51%). CVaR(95%) = -0.0778.", "metadata": {"var": -0.055073, "cvar": -0.077849, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241119_0536", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-11-19", "context_summary": "BTC-USD: 60-day return history, mean=0.0064, std=0.0260.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0064, std=0.0260, min=-0.0394, max=0.1022\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0297", "answer_numeric": -0.029655, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0297 (i.e., on a bad day with 5% probability, the loss exceeds 2.97%). CVaR(95%) = -0.0371.", "metadata": {"var": -0.029655, "cvar": -0.037097, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230926_0539", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-09-26", "context_summary": "QQQ: 60-day return history, mean=-0.0002, std=0.0102.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0002, std=0.0102, min=-0.0233, max=0.0216\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-25] [\"OpenAI's ChatGPT will 'see, hear and speak' in major update Sept 25 (Reuters) - OpenAI's ChatGPT is getting a major update that will enable the viral chatbot to have voice conversations with users and interact using images, moving it closer to popular artificial intelligence (AI) assistants like Apple's AAPL.O Siri. The voice feature \\\"opens doors to many creative and accessibility-focused applications\\\", OpenAI said in a blog post on Monday. Similar AI services like Siri, Google GOOGL.O voice assistant and Amazon.com's AMZN.O Alexa are integrated with the devices they run on and are often used to set alarms and reminders, and deliver information off the internet. Since its debut last year, ChatGPT has been adopted by companies for a wide range of tasks from summarizing documents to writing computer code, setting off a race amongst Big Tech companies to launch their own offerings based on generative AI. ChatGPT's new voice feature can also narrate bedtime stories, settle debates at the dinner table, and speak out loud text input from users. The technology behind it is being used by Spotify SPOT.N for the platform's podcasters to translate their content in different languages, OpenAI said. With images support, users can take pictures of things around them and ask the chatbot to \\\"troubleshoot why your grill won't start, explore the contents of your fridge to plan a meal, or analyze a complex graph for work-related data\\\". Alphabet's Google Lens is currently the popular choice to gain information on images. The new ChatGPT features will be released for subscribers of its Plus and Enterprise plans over the next two weeks. (Reporting by Zaheer Kachwala and Yuvraj Malik in Bengaluru; Editing by Devika Syamnath) ((yuvraj.malik@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Netflix (NFLX) Expands Portfolio With New Italian Content Netflix NFLX is having a steady run in 2023, with shares rising 28.8% year to date compared with the Zacks Consumer Discretionary sector\\u2019s increase of 4.6%. The upside can be attributed to an expanding subscriber base and robust content offerings. Netflix continues to bolster its international content portfolio. Italy plays a prominent role in this endeavour through an extensive lineup that includes a wide range of series, films, docuseries and unscripted shows spanning diverse genres, formats and languages. Netflix recently announced four captivating new projects, including Il treno dei bambini, an in-depth exploration of postwar Italy and Fabbricante di lacrime, based on a popular book. Additionally, two fresh series, Storia della mia famiglia and Adorazione, provide deep explorations of intricate family dynamics and young adult experiences. Expanding Portfolio Aids Growth Netflix is anticipated to gain from its diversified content portfolio, driven by substantial investments in producing and distributing lo\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QQQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0187", "answer_numeric": -0.01865, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0187 (i.e., on a bad day with 5% probability, the loss exceeds 1.87%). CVaR(95%) = -0.0224.", "metadata": {"var": -0.01865, "cvar": -0.022373, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230208_0542", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-02-08", "context_summary": "AVAX-USD: 60-day return history, mean=0.0086, std=0.0529.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0086, std=0.0529, min=-0.1005, max=0.2500\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-07] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0553", "answer_numeric": -0.055267, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0553 (i.e., on a bad day with 5% probability, the loss exceeds 5.53%). CVaR(95%) = -0.0804.", "metadata": {"var": -0.055267, "cvar": -0.080442, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240731_0545", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-07-31", "context_summary": "LINK-USD: 60-day return history, mean=-0.0050, std=0.0366.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0050, std=0.0366, min=-0.0783, max=0.0741\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0567", "answer_numeric": -0.056663, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0567 (i.e., on a bad day with 5% probability, the loss exceeds 5.67%). CVaR(95%) = -0.0673.", "metadata": {"var": -0.056663, "cvar": -0.06733, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240612_0547", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-06-12", "context_summary": "ETH-USD: 60-day return history, mean=0.0012, std=0.0324.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0012, std=0.0324, min=-0.0734, max=0.1560\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0418", "answer_numeric": -0.041794, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0418 (i.e., on a bad day with 5% probability, the loss exceeds 4.18%). CVaR(95%) = -0.0608.", "metadata": {"var": -0.041794, "cvar": -0.060843, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230710_0550", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-07-10", "context_summary": "XLP: 60-day return history, mean=-0.0004, std=0.0062.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0004, std=0.0062, min=-0.0153, max=0.0137\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-07] [\"Here is What to Know Beyond Why Apple Inc. (AAPL) is a Trending Stock Apple (AAPL) has recently been on Zacks.com's list of the most searched stocks. Therefore, you might want to consider some of the key factors that could influence the stock's performance in the near future. Over the past month, shares of this maker of iPhones, iPads and other products have returned +6.2%, compared to the Zacks S&P 500 composite's +3.1% change. During this period, the Zacks Computer - Mini computers industry, which Apple falls in, has gained 7%. The key question now is: What could be the stock's future direction? While media releases or rumors about a substantial change in a company's business prospects usually make its stock 'trending' and lead to an immediate price change, there are always some fundamental facts that eventually dominate the buy-and-hold decision-making. Earnings Estimate Revisions Here at Zacks, we prioritize appraising the change in the projection of a company's future earnings over anything else. That's because we believe the present value of its future stream of earnings is what determines the fair value for its stock. We essentially look at how sell-side analysts covering the stock are revising their earnings estimates to reflect the impact of the latest business trends. And if earnings estimates go up for a company, the fair value for its stock goes up. A higher fair value than the current market price drives investors' interest in buying the stock, leading to its price moving higher. This is why empirical research shows a strong correlation between trends in earnings estimate revisions and near-term stock price movements. Apple is expected to post earnings of $1.20 per share for the current quarter, representing no change from the year-ago quarter. Over the last 30 days, the Zacks Consensus Estimate has changed -1.5%. The consensus earnings estimate of $6 for the current fiscal year indicates a year-over-year change of -1.8%. This estimate has changed +0.1% over the last 30 days. For the next fiscal year, the consensus earnings estimate of $6.62 indicates a change of +10.4% from what Apple is expected to report a year ago. Over the past month, the estimate has changed -0.2%. Having a strong externally audited track record, our proprietary stock rating tool, the Zacks Rank, offers a more conclusive picture of a stock's price direction in the near term, since it effectively harnesses the power of earnings estimate revisions. Due to the size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, Apple is rated Zacks Rank #3 (Hold). The chart below shows the evolution of the company's forward 12-month consensus EPS estimate: 12 Month EPS Projected Revenue Growth While earnings growth is arguably the most superior indicator of a company's financial health, nothing happens as such if a business isn't able to grow its revenues. After all, it's nearly impossible for a company to increase i\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLP. Express as a decimal (e.g., -0.02).", "answer": "-0.0086", "answer_numeric": -0.008636, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0086 (i.e., on a bad day with 5% probability, the loss exceeds 0.86%). CVaR(95%) = -0.0133.", "metadata": {"var": -0.008636, "cvar": -0.013296, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231204_0553", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-12-04", "context_summary": "EFA: 60-day return history, mean=0.0006, std=0.0086.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0006, std=0.0086, min=-0.0176, max=0.0252\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-01] [\"Best Blue Chip Stocks To Invest In Right Now? 2 In Focus Blue-chip stocks are shares of well-established, financially sound companies with a history of stable earnings. These companies are often market leaders or among the top in their sectors. Characterized by their large market capitalization, blue-chip stocks are known for their reliability and strong track record. They are often included in major stock indices. Investing in blue-chip stocks offers several advantages. These stocks typically provide consistent dividends, contributing to steady income for investors. Their long-standing market presence suggests a lower risk of volatility. This makes them a popular choice for conservative investors. However, there are also disadvantages. Blue-chip stocks may have slower growth compared to emerging companies. Their size can limit their potential for rapid expansion. When considering blue-chip stocks, investors should weigh their investment goals. These stocks can be a cornerstone for a long-term, stable portfolio. Yet, their conservative nature might not suit those seeking high growth rates. As with any investment, diversification is key. Keeping this on top of mind, let\\u2019s look at two blue chip stocks to watch in the stock market today. Blue Chip Stocks To Buy [Or Avoid] Today McDonald\\u2019s Corporation (NYSE: MCD) Apple Inc. (NASDAQ: AAPL) McDonald\\u2019s Corporation (MCD Stock) Let\\u2019s start with McDonald\\u2019s Corporation (MCD). The company is a global fast-food chain, renowned for its hamburgers, fries, and quick-service meals. McDonald\\u2019s is one of the world\\u2019s largest restaurant chains, with outlets in over 100 countries. McDonald\\u2019s is known for its standardized menu items and for pioneering the franchise model in the fast-food industry. Last month, McDonald\\u2019s Corporation announced its decision to acquire Carlyle\\u2019s minority ownership stake in the strategic partnership managing McDonald\\u2019s business in mainland China, Hong Kong, and Macau. The announcement, made on November 20, 2023, detailed that while the CITIC Consortium, primarily through CITIC Capital, would maintain its controlling 52% stake, McDonald\\u2019s would increase its stake from 20% to 48%. This move marks a significant adjustment in McDonald\\u2019s involvement in its Chinese operations. In the last month of trading action, shares of MCD have advanced by 8.36%. Meanwhile, during Friday morning\\u2019s trading session, McDonald\\u2019s stock is trading slightly higher on the day so far by 0.72%, trading at $283.88 a share. [Read More] 2 Dow 30 Stocks For Your December 2023 Watchlist Apple (AAPL Stock) Next, Apple Inc. (AAPL) is a multinational technology company that specializes in consumer electronics, software, and online services. Apple\\u2019s key products include the iPhone, iPad, Mac computers, and services like the App Store, Apple Music, and iCloud. At the beginning of last month, Apple reported better-than-expected fourth-quarter 2023 f\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0131", "answer_numeric": -0.013104, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0131 (i.e., on a bad day with 5% probability, the loss exceeds 1.31%). CVaR(95%) = -0.0164.", "metadata": {"var": -0.013104, "cvar": -0.016357, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231218_0556", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2023-12-18", "context_summary": "JNK: 60-day return history, mean=0.0010, std=0.0047.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=0.0010, std=0.0047, min=-0.0102, max=0.0143\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for JNK. Express as a decimal (e.g., -0.02).", "answer": "-0.0057", "answer_numeric": -0.005704, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0057 (i.e., on a bad day with 5% probability, the loss exceeds 0.57%). CVaR(95%) = -0.0076.", "metadata": {"var": -0.005704, "cvar": -0.007633, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240404_0559", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-04-04", "context_summary": "BNB-USD: 60-day return history, mean=0.0115, std=0.0439.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0115, std=0.0439, min=-0.0885, max=0.1723\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0507", "answer_numeric": -0.050669, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0507 (i.e., on a bad day with 5% probability, the loss exceeds 5.07%). CVaR(95%) = -0.0774.", "metadata": {"var": -0.050669, "cvar": -0.077441, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241002_0562", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-10-02", "context_summary": "LINK-USD: 60-day return history, mean=-0.0004, std=0.0431.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0004, std=0.0431, min=-0.1260, max=0.1319\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0597", "answer_numeric": -0.05968, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0597 (i.e., on a bad day with 5% probability, the loss exceeds 5.97%). CVaR(95%) = -0.0889.", "metadata": {"var": -0.05968, "cvar": -0.088853, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230913_0565", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-09-13", "context_summary": "EEM: 60-day return history, mean=-0.0008, std=0.0102.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0008, std=0.0102, min=-0.0242, max=0.0239\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-12] [\"US takes on Google in much-anticipated antitrust trial By Diane Bartz WASHINGTON, Sept 12 (Reuters) - The United States argued on Tuesday that Google GOOGL.O did not play by the rules in its efforts to keep its dominance in online search, as a trial seen as a battle for the soul of the internet got underway before a federal judge in Washington. The U.S. Justice Department accuses Google of paying billions of dollars annually to device makers like Apple Inc AAPL.O, wireless companies like AT&T T.N and browser makers like Mozilla to keep Google's search engine on top. Google's defense is simple: It argues that its overwhelmingly high market share is not because it broke the law, but because it is a fast, effective search engine. It is also free. Consumers, Google's lawyers will argue, can delete the Google app from their devices or simply type Microsoft's Bing, Yahoo or DuckDuckGo into a browser to use an alternative search engine. They will argue that consumers stick with Google because they rely on it to answer questions and are not disappointed. The trial has opening arguments on Tuesday before a packed D.C. federal court and is expected to run up to 10 weeks. It has two phases. In the first, Judge Amit Mehta will decide if Google has broken antitrust law in how it manages search and search advertising. If Google is found to have broken the law, Judge Mehta will then decide how best to resolve it. He may decide simply to order Google to stop practices he has found to be illegal or he may order Google to sell assets. The government, in its complaint, asked for \\\"structural relief as needed\\\" but did not define it. The legal fight has huge implications for Big Tech, which has been accused of buying or strangling small competitors but has insulated itself against many accusations of breaking antitrust law because the services the companies provide to users are free, as in the case of Google, or inexpensive, as in the case of Amazon.com AMZN.O. Previous major antitrust trials include Microsoft, filed in 1998, and AT&T, filed in 1974. The AT&T breakup in 1982 is credited with paving the way for the modern cell phone industry, while the fight with Microsoft is credited with opening space for Google and others on the internet. (Reporting by Diane Bartz; Editing by Jamie Freed and Chizu Nomiyama) ((Diane.Bartz@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"3 Reddit-Approved AI Stocks for Your Buy-List InvestorPlace - Stock Market News, Stock Advice & Trading Tips When it comes to identifying the pulse of contemporarystock market trends it\\u2019s tough to overlook the burgeoning influence of Reddit. Investing subreddits in particular have steered notable stock shifts and even reshaped market narratives. Among the stocks creating a buzz, AI stocks have taken center stage this year, especially with stalwarts such as Nvidia (NASDAQ:NVDA) witness\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0151", "answer_numeric": -0.015052, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0151 (i.e., on a bad day with 5% probability, the loss exceeds 1.51%). CVaR(95%) = -0.0215.", "metadata": {"var": -0.015052, "cvar": -0.021513, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240801_0568", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2024-08-01", "context_summary": "LQD: 60-day return history, mean=0.0007, std=0.0044.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0007, std=0.0044, min=-0.0090, max=0.0089\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LQD. Express as a decimal (e.g., -0.02).", "answer": "-0.0061", "answer_numeric": -0.006113, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0061 (i.e., on a bad day with 5% probability, the loss exceeds 0.61%). CVaR(95%) = -0.0073.", "metadata": {"var": -0.006113, "cvar": -0.007262, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230630_0571", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2023-06-30", "context_summary": "SOYB: 60-day return history, mean=-0.0000, std=0.0126.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=-0.0000, std=0.0126, min=-0.0257, max=0.0280\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOYB. Express as a decimal (e.g., -0.02).", "answer": "-0.0200", "answer_numeric": -0.019975, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0200 (i.e., on a bad day with 5% probability, the loss exceeds 2.00%). CVaR(95%) = -0.0236.", "metadata": {"var": -0.019975, "cvar": -0.023583, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230731_0574", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-07-31", "context_summary": "BTC-USD: 60-day return history, mean=0.0014, std=0.0201.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0014, std=0.0201, min=-0.0501, max=0.0600\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-30] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0307", "answer_numeric": -0.030743, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0307 (i.e., on a bad day with 5% probability, the loss exceeds 3.07%). CVaR(95%) = -0.0397.", "metadata": {"var": -0.030743, "cvar": -0.039723, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230818_0577", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-08-18", "context_summary": "ETH-USD: 60-day return history, mean=-0.0002, std=0.0198.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0002, std=0.0198, min=-0.0669, max=0.0718\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-17] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0324", "answer_numeric": -0.032437, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0324 (i.e., on a bad day with 5% probability, the loss exceeds 3.24%). CVaR(95%) = -0.0443.", "metadata": {"var": -0.032437, "cvar": -0.044333, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240925_0580", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-09-25", "context_summary": "XLI: 60-day return history, mean=0.0017, std=0.0104.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0017, std=0.0104, min=-0.0224, max=0.0246\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 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us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLI. Express as a decimal (e.g., -0.02).", "answer": "-0.0189", "answer_numeric": -0.018862, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0189 (i.e., on a bad day with 5% probability, the loss exceeds 1.89%). CVaR(95%) = -0.0221.", "metadata": {"var": -0.018862, "cvar": -0.022128, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241016_0583", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-10-16", "context_summary": "XLU: 60-day return history, mean=0.0023, std=0.0086.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0023, std=0.0086, min=-0.0268, max=0.0261\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0086", "answer_numeric": -0.008641, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0086 (i.e., on a bad day with 5% probability, the loss exceeds 0.86%). CVaR(95%) = -0.0199.", "metadata": {"var": -0.008641, "cvar": -0.019867, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240229_0586", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-02-29", "context_summary": "ETH-USD: 60-day return history, mean=0.0069, std=0.0276.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0069, std=0.0276, min=-0.0616, max=0.1012\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0365", "answer_numeric": -0.036534, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0365 (i.e., on a bad day with 5% probability, the loss exceeds 3.65%). CVaR(95%) = -0.0535.", "metadata": {"var": -0.036534, "cvar": -0.053464, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240417_0589", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-04-17", "context_summary": "EFA: 60-day return history, mean=0.0005, std=0.0066.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0005, std=0.0066, min=-0.0163, max=0.0118\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0101", "answer_numeric": -0.010088, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0101 (i.e., on a bad day with 5% probability, the loss exceeds 1.01%). CVaR(95%) = -0.0150.", "metadata": {"var": -0.010088, "cvar": -0.015043, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241017_0591", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-10-17", "context_summary": "ICSH: 60-day return history, mean=0.0002, std=0.0002.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0002, min=-0.0002, max=0.0006\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ICSH. Express as a decimal (e.g., -0.02).", "answer": "-0.0002", "answer_numeric": -0.000198, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0002 (i.e., on a bad day with 5% probability, the loss exceeds 0.02%). CVaR(95%) = -0.0002.", "metadata": {"var": -0.000198, "cvar": -0.000198, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241204_0593", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["FXI"], "decision_date": "2024-12-04", "context_summary": "FXI: 60-day return history, mean=0.0025, std=0.0229.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0025, std=0.0229, min=-0.0438, max=0.0476\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 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us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for FXI. Express as a decimal (e.g., -0.02).", "answer": "-0.0379", "answer_numeric": -0.037871, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0379 (i.e., on a bad day with 5% probability, the loss exceeds 3.79%). CVaR(95%) = -0.0438.", "metadata": {"var": -0.037871, "cvar": -0.043839, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20230216_0595", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-02-16", "context_summary": "XLU: 60-day return history, mean=0.0003, std=0.0108.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0003, std=0.0108, min=-0.0243, max=0.0247\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CAT 2023-02-15] cat-20221231 0000018230 FALSE 2022 FY 50 33.33 33.33 33.33 2025-08-29 2027-09-01 2023-08-31 http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent 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and arrangements required to be filed as exhibits pursuant to Item 15(b) of this report. The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. Item 16.  Form 10-K Summary. None. 130 Table of Contents Form 10-K   SIGNATURES   Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     CATERPILLAR INC.   Registrant     February 15, 2023 By: /s/ Suzette M. Long     Suzette M. Long Chief Legal Officer and General Counsel   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated.       Chairman of the Board  and Chief Executive Officer February 15, 2023 /s/ D. James Umpleby III   D. James Umpleby III       February 15, 2023 /s/ Andrew R.J. Bonfield Chief Financial Officer Andrew R.J. Bonfield     February 15, 2023 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp February 15, 2023 /s/ Kelly A. Ayotte Director   Kelly  A. Ayotte         February 15, 2023 /s/ David L. Calhoun Director   David L. Calhoun               131 Table of Contents February 15, 2023 /s/ Daniel M. Dickinson Director   Daniel M. Dickinson         February 15, 2023 /s/ Gerald Johnson Director   Gerald Johnson         February 15, 2023 /s/ David W. MacLennan Director   David W. MacLennan   February 15, 2023 /s/ Debra L. Reed-Klages Presiding Director Debra L. Reed-Klages       February 15, 2023 /s/ Edward B. Rust, Jr. Director   Edward B. Rust, Jr.               February 15, 2023 /s/ Susan C. Schwab Director   Susan C. Schwab             February 15, 2023 /s/ Rayford Wilkins, Jr. Director   Rayford Wilkins, Jr.   132\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0174", "answer_numeric": -0.01736, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0174 (i.e., on a bad day with 5% probability, the loss exceeds 1.74%). CVaR(95%) = -0.0224.", "metadata": {"var": -0.01736, "cvar": -0.022437, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240125_0598", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-01-25", "context_summary": "XLK: 60-day return history, mean=0.0040, std=0.0095.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0040, std=0.0095, min=-0.0265, max=0.0258\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0103", "answer_numeric": -0.010343, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0103 (i.e., on a bad day with 5% probability, the loss exceeds 1.03%). CVaR(95%) = -0.0180.", "metadata": {"var": -0.010343, "cvar": -0.018004, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240403_0601", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2024-04-03", "context_summary": "EWJ: 60-day return history, mean=0.0017, std=0.0084.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0017, std=0.0084, min=-0.0224, max=0.0178\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EWJ. Express as a decimal (e.g., -0.02).", "answer": "-0.0117", "answer_numeric": -0.011668, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0117 (i.e., on a bad day with 5% probability, the loss exceeds 1.17%). CVaR(95%) = -0.0167.", "metadata": {"var": -0.011668, "cvar": -0.01669, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240112_0603", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2024-01-12", "context_summary": "REZ: 60-day return history, mean=0.0011, std=0.0134.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0011, std=0.0134, min=-0.0251, max=0.0335\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for REZ. Express as a decimal (e.g., -0.02).", "answer": "-0.0201", "answer_numeric": -0.020131, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0201 (i.e., on a bad day with 5% probability, the loss exceeds 2.01%). CVaR(95%) = -0.0224.", "metadata": {"var": -0.020131, "cvar": -0.022377, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240208_0605", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-02-08", "context_summary": "LINK-USD: 60-day return history, mean=0.0035, std=0.0449.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0035, std=0.0449, min=-0.0960, max=0.1160\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0670", "answer_numeric": -0.067, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0670 (i.e., on a bad day with 5% probability, the loss exceeds 6.70%). CVaR(95%) = -0.0780.", "metadata": {"var": -0.067, "cvar": -0.077976, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240730_0607", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-07-30", "context_summary": "BTC-USD: 60-day return history, mean=-0.0002, std=0.0213.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0002, std=0.0213, min=-0.0531, max=0.0672\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0319", "answer_numeric": -0.031902, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0319 (i.e., on a bad day with 5% probability, the loss exceeds 3.19%). CVaR(95%) = -0.0471.", "metadata": {"var": -0.031902, "cvar": -0.047056, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240710_0610", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLE"], "decision_date": "2024-07-10", "context_summary": "XLE: 60-day return history, mean=-0.0015, std=0.0106.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0015, std=0.0106, min=-0.0302, max=0.0249\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLE. Express as a decimal (e.g., -0.02).", "answer": "-0.0179", "answer_numeric": -0.017893, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0179 (i.e., on a bad day with 5% probability, the loss exceeds 1.79%). CVaR(95%) = -0.0254.", "metadata": {"var": -0.017893, "cvar": -0.025372, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241022_0613", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-10-22", "context_summary": "XLRE: 60-day return history, mean=0.0013, std=0.0088.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0013, std=0.0088, min=-0.0293, max=0.0219\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PG 2024-10-18] pg-20240930 0000080424 6/30 2025 Q1 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent 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Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended September 30, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. The Procter & Gamble Company 25 Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 10.1 Company's Form of Separation Agreement & Release *+ 10.2 The Procter & Gamble Performance Stock Program Summary *+ 10.3 Performance Stock Program related correspondence and terms and conditions *+ 10.4 Long-Term Incentive Program related correspondence and terms and conditions *+ 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) * Compensatory plan or arrangement + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY October 18, 2024 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLRE. Express as a decimal (e.g., -0.02).", "answer": "-0.0098", "answer_numeric": -0.009774, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0098 (i.e., on a bad day with 5% probability, the loss exceeds 0.98%). CVaR(95%) = -0.0200.", "metadata": {"var": -0.009774, "cvar": -0.020003, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20240320_0616", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-03-20", "context_summary": "EEM: 60-day return history, mean=0.0008, std=0.0089.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0008, std=0.0089, min=-0.0245, max=0.0225\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0143", "answer_numeric": -0.014298, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0143 (i.e., on a bad day with 5% probability, the loss exceeds 1.43%). CVaR(95%) = -0.0195.", "metadata": {"var": -0.014298, "cvar": -0.019509, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230328_0618", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-03-28", "context_summary": "XLU: 60-day return history, mean=-0.0011, std=0.0121.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0011, std=0.0121, min=-0.0243, max=0.0271\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-27] [\"Technology Sector Update for 03/27/2023: PINS, AAPL, BLKB, TMPO Technology stocks were lower in late Monday afternoon trading, with the Technology Select Sector SPDR Fund (XLK) slipping 0.4% and the Philadelphia Semiconductor index down 0.7%. In company news, Pinterest's (PINS) shares were up 2.1% after analysts at UBS said, while upgrading their rating on the stock, that the company's ad-tech and partner monetization efforts could help unlock incremental demand and drive revenue higher. Apple (AAPL) Chief Executive Tim Cook met Chinese Commerce Minister Wang Wentao to discuss industrial stabilization and supply chains, according to media reports. Apple stock was down 1.2% in recent trading. Blackbaud (BLKB) was up nearly 11% after its board rejected a buyout offer from private-equity firm Clearlake Capital, which offered $71 per share in cash. Tempo Automation (TMPO) was up more than 11% after saying it has agreed to buy Optimum Design Associates for an undisclosed sum. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Technology Sector Update for 03/27/2023: AAPL, BLKB TMPO Technology stocks were lower in Monday afternoon trading, with the Technology Select Sector SPDR Fund (XLK) slipping 0.6% and the Philadelphia Semiconductor index (SOX) down 0.8%. In company news, Apple (AAPL) Chief Executive Tim Cook met Chinese Commerce Minister Wang Wentao to discuss industrial stabilization and supply chains, according to media reports. Apple stock was down 1.2% in recent trading. Blackbaud (BLKB) was up more than 12% after its board rejected a buyout offer from private-equity firm Clearlake Capital, which offered $71 per share in cash. Tempo Automation (TMPO) was up more than 10% after saying it has agreed to buy Optimum Design Associates for an undisclosed sum. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-Dow, S&P 500 up as SVB deal lifts bank shares; Nasdaq dips By Caroline Valetkevitch NEW YORK, March 27 (Reuters) - The Dow and S&P 500 were higher in afternoon trading Monday as a deal for Silicon Valley Bank's assets helped investor confidence in banks, while the Nasdaq edged lower. The S&P 500 banks index .SPXBK was up 2.8%, while the KBW regional banking index .KRX was up 1.1%. Shares of JPMorgan Chase & Co JPM.N were up 2.9%, helping to support the S&P 500 along with Bank of America BAC.N, which was up 4.4%. Shares of First Citizens BancShares Inc FCNCA.O were up more than 50% Monday after it said it would acquire the deposits and loans of Silicon Valley Bank, which failed earlier this month in the largest bank collapse since the 2008 financial crisis. Also, shares of First Republic Bank FRC.N were up about 11% after Bloomberg reported U.S. authorities were considering more support for banks, which could give the struggling First Republic more time to shore up\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0204", "answer_numeric": -0.020394, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0204 (i.e., on a bad day with 5% probability, the loss exceeds 2.04%). CVaR(95%) = -0.0224.", "metadata": {"var": -0.020394, "cvar": -0.022437, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230606_0621", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-06-06", "context_summary": "SOL-USD: 60-day return history, mean=0.0001, std=0.0336.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0001, std=0.0336, min=-0.0861, max=0.1023\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-05] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0416", "answer_numeric": -0.04156, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0416 (i.e., on a bad day with 5% probability, the loss exceeds 4.16%). CVaR(95%) = -0.0735.", "metadata": {"var": -0.04156, "cvar": -0.073452, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240227_0623", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-02-27", "context_summary": "VLUE: 60-day return history, mean=0.0016, std=0.0082.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0016, std=0.0082, min=-0.0190, max=0.0229\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CVX 2024-02-26] cvx-20231231 0000093410 false 2023 FY 336 353 277 http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2023#AccruedLiabilitiesCurrent 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us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2021-01-01 2021-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2021-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2021-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2021-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2021-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-01-01 2022-12-31 0000093410 us [...TRUNCATED...] ubsidiaries of Chevron Corporation (page E-1). 22.1* Subsidiary Issuer of Guaranteed Securities. 23.1* Consent of PricewaterhouseCoopers LLP (page E-2). 24.1* Power of Attorney for certain directors of Chevron Corporation, authorizing the signing of the Annual Report on Form 10-K on their behalf. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer (page E-3). 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer (page E-4).   32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer (page E-5).   32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer (page E-6). 97.1+* Chevron Corporation Dodd-Frank Clawback Policy. 99.1* Definitions of Selected Energy and Financial Terms (pages E-7 through E-10). 101* Interactive data files (formatted as Inline XBRL). 104* Cover Page Interactive Data File (contained in Exhibit 101).   ___________________________________________ + Indicates a management contract or compensatory plan or arrangement. *      Filed herewith. **      Furnished herewith. Pursuant to Item 601(b)(4) of Regulation S-K, certain instruments with respect to the company’s long-term debt are not filed with this Annual Report on Form 10-K. A copy of any such instrument will be furnished to the Securities and Exchange Commission upon request. 118 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on the 26th day of February, 2024.  Chevron Corporation   By: /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities indicated on the 26th day of February, 2024.   Principal Executive Officer (and Director) /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer Principal Financial Officer /s/ PIERRE R. BREBER Pierre R. Breber, Vice President and Chief Financial Officer Principal Accounting Officer /s/ ALANA K. KNOWLES Alana K. Knowles, Vice President and Controller * By:  /s/ MARY A. FRANCIS Mary A. Francis, Attorney-in-Fact Directors WANDA M. AUSTIN * Wanda M. Austin JOHN B. FRANK * John B. Frank ALICE P. GAST * Alice P. Gast ENRIQUE HERNANDEZ, JR. * Enrique Hernandez, Jr. MARILLYN A. HEWSON * Marillyn A. Hewson JON M. HUNTSMAN JR. * Jon M. Huntsman Jr. CHARLES W. MOORMAN * Charles W. Moorman DAMBISA F. MOYO * Dambisa F. Moyo DEBRA REED-KLAGES * Debra Reed-Klages D. JAMES UMPLEBY III * D. James Umpleby III CYNTHIA J. WARNER * Cynthia J. Warner 119\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0100", "answer_numeric": -0.01005, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0100 (i.e., on a bad day with 5% probability, the loss exceeds 1.00%). CVaR(95%) = -0.0157.", "metadata": {"var": -0.01005, "cvar": -0.015706, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240312_0626", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2024-03-12", "context_summary": "PDBC: 60-day return history, mean=0.0002, std=0.0072.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=0.0002, std=0.0072, min=-0.0164, max=0.0136\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for PDBC. Express as a decimal (e.g., -0.02).", "answer": "-0.0128", "answer_numeric": -0.012801, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0128 (i.e., on a bad day with 5% probability, the loss exceeds 1.28%). CVaR(95%) = -0.0154.", "metadata": {"var": -0.012801, "cvar": -0.015413, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241007_0629", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-10-07", "context_summary": "MATIC-USD: 60-day return history, mean=0.0003, std=0.0389.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0003, std=0.0389, min=-0.0838, max=0.1371\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0606", "answer_numeric": -0.060609, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0606 (i.e., on a bad day with 5% probability, the loss exceeds 6.06%). CVaR(95%) = -0.0732.", "metadata": {"var": -0.060609, "cvar": -0.073193, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240109_0632", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-01-09", "context_summary": "XLI: 60-day return history, mean=0.0014, std=0.0087.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0014, std=0.0087, min=-0.0244, max=0.0204\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-08] [\"4 Electronics Semiconductor Stocks to Escape Macro Headwinds The challenging global macroeconomic environment and end-market volatility have affected the Zacks Electronics - Semiconductors industry. Geo-political tensions, unfavorable forex and rising inflationary pressure also weigh heavily on the industry\\u2019s prospects. Nevertheless, industry players like Advanced Micro Devices AMD, ASE Technology ASX, Cirrus Logic CRUS and QuickLogic QUIK have been benefiting from the increasing demand for high-volume consumer electronic devices, such as digital media players, smartphones and tablets, and the strong uptake of efficient packaging, machine vision solutions and robotics. Additionally, the growing proliferation of AI, Machine Learning, Blockchain, Internet of Things, Augmented Reality/Virtual Reality (AR/VR) and industrial revolution 4.0 (which focuses on interconnectivity and automation) should continue to drive the industry\\u2019s growth. Easing supply-chain constraints are also benefiting the industry participants. Industry Description The Zacks Electronics \\u2013 Semiconductors industry comprises firms that provide a wide range of semiconductor technologies. Their offerings include packaging and test services, wafer cleaning, factory automation, face detection and image-recognition capabilities to develop intelligent and connected products. The participants primarily cater to end-markets constituting consumer electronics, communications, computing, industrial and automotive. These companies are raising their spending on research and development to stay afloat in an era of technological advancements and changing industry standards. The underlined industry is experiencing solid demand for advanced electronic equipment, helping these firms increase their investments in cost-effective process technologies. What's Shaping the Future of the Electronics - Semiconductors Industry? Macroeconomic Headwinds Pose Concerns: Rising inflationary pressure and fears of global recession have negatively impacted the rate of deal wins. Due to the challenging macroeconomic scenario, enterprises are reluctant to sign multi-year deals worldwide. These trends do not bode well for the industry participants. Geo-political Tensions Are Worrisome: The ongoing Russia-Ukraine war and, most importantly, the souring relationship between the United States and China are creating headwinds. Increasing dependency on AI-backed electronic devices on semiconductors and current restrictions ordered by the United States on trading with China, the main hub for chip production, is a significant negative for the underlined industry. Smart Devices Aiding Computing Demand: Smart devices need computing and learning capabilities to perform face detection, image recognition and video analytics capabilities. These require high processing power, speed and memory; low power consumption; and better graphic processors and solutions, which bode well for the industry. Graphic solutions help in\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLI. Express as a decimal (e.g., -0.02).", "answer": "-0.0130", "answer_numeric": -0.013018, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0130 (i.e., on a bad day with 5% probability, the loss exceeds 1.30%). CVaR(95%) = -0.0186.", "metadata": {"var": -0.013018, "cvar": -0.018575, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231011_0635", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2023-10-11", "context_summary": "BIL: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=-0.0001, max=0.0007\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BIL. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0000.", "metadata": {"var": 0.0, "cvar": -1.6e-05, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240628_0638", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-06-28", "context_summary": "^VIX: 60-day return history, mean=-0.0029, std=0.0538.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0029, std=0.0538, min=-0.1133, max=0.1493\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ^VIX. Express as a decimal (e.g., -0.02).", "answer": "-0.0770", "answer_numeric": -0.077048, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0770 (i.e., on a bad day with 5% probability, the loss exceeds 7.70%). CVaR(95%) = -0.0991.", "metadata": {"var": -0.077048, "cvar": -0.099073, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230316_0640", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-03-16", "context_summary": "CSHI: 60-day return history, mean=0.0002, std=0.0008.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0008, min=-0.0015, max=0.0026\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0010", "answer_numeric": -0.001024, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0010 (i.e., on a bad day with 5% probability, the loss exceeds 0.10%). CVaR(95%) = -0.0015.", "metadata": {"var": -0.001024, "cvar": -0.001536, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240523_0643", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LQD"], "decision_date": "2024-05-23", "context_summary": "LQD: 60-day return history, mean=0.0001, std=0.0042.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0001, std=0.0042, min=-0.0133, max=0.0089\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LQD. Express as a decimal (e.g., -0.02).", "answer": "-0.0075", "answer_numeric": -0.007478, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0075 (i.e., on a bad day with 5% probability, the loss exceeds 0.75%). CVaR(95%) = -0.0113.", "metadata": {"var": -0.007478, "cvar": -0.01131, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241008_0646", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-10-08", "context_summary": "QUAL: 60-day return history, mean=0.0004, std=0.0102.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0004, std=0.0102, min=-0.0296, max=0.0254\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0166", "answer_numeric": -0.016646, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0166 (i.e., on a bad day with 5% probability, the loss exceeds 1.66%). CVaR(95%) = -0.0250.", "metadata": {"var": -0.016646, "cvar": -0.024975, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240401_0649", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-04-01", "context_summary": "XLI: 60-day return history, mean=0.0019, std=0.0071.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0019, std=0.0071, min=-0.0150, max=0.0169\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLI. Express as a decimal (e.g., -0.02).", "answer": "-0.0101", "answer_numeric": -0.010139, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0101 (i.e., on a bad day with 5% probability, the loss exceeds 1.01%). CVaR(95%) = -0.0123.", "metadata": {"var": -0.010139, "cvar": -0.012308, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230427_0652", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-04-27", "context_summary": "QUAL: 60-day return history, mean=0.0003, std=0.0101.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0003, std=0.0101, min=-0.0217, max=0.0210\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-26] [\"Unusual Call Option Trade in Apple (AAPL) Worth $3,040.50K On April 26, 2023 at 15:31:16 ET an unusually large $3,040.50K block of Call contracts in Apple (AAPL) was sold, with a strike price of $167.50 / share, expiring in 23 day(s) (on May 19, 2023). Fintel tracks all large options trades, and the premium spent on this trade was 3.98 sigmas above the mean, placing it in the 100.00th percentile of all recent large trades made in AAPL options. This trade was first picked up on Fintel's real time Options Flow tool, where unusual option trades are highlighted. What is the Fund Sentiment? There are 6408 funds or institutions reporting positions in Apple. This is an increase of 189 owner(s) or 3.04% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 2.79%, a decrease of 26.22%. Total shares owned by institutions increased in the last three months by 0.12% to 10,139,399K shares. The put/call ratio of AAPL is 1.00, indicating a bullish outlook. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. Analyst Price Forecast Suggests 6.19% Upside As of April 24, 2023, the average one-year price target for Apple is $173.91. The forecasts range from a low of $117.16 to a high of $215.25. The average price target represents an increase of 6.19% from its latest reported closing price of $163.77. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is $413,641MM, an increase of 6.74%. The projected annual non-GAAP EPS is $6.36. What are Other Shareholders Doing? MAINSTAY VP FUNDS TRUST - MainStay VP T. Rowe Price Equity Income Portfolio Initial Class holds 144K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 150K shares, representing a decrease of 4.30%. The firm decreased its portfolio allocation in AAPL by 14.11% over the last quarter. Benchmark Investment Advisors holds 51K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 52K shares, representing a decrease of 1.70%. The firm decreased its portfolio allocation in AAPL by 9.34% over the last quarter. Lowery Thomas holds 2K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 3K shares, representing a decrease of 17.45%. The firm decreased its portfolio allocation in AAPL by 17.98% over the last quarter. Rbo & Co holds 105K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 104K shares, representing an increase of 0.40%. The firm decreased its portfolio allocation in AAPL by 99.92% over the last quarter. Invst holds 58K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 60K shares, representing a decrease of 2.99%. The firm decreased its portfolio allocation in AAPL by 99.91% over the last quarter. Apple Background Information (This descr\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0166", "answer_numeric": -0.016631, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0166 (i.e., on a bad day with 5% probability, the loss exceeds 1.66%). CVaR(95%) = -0.0186.", "metadata": {"var": -0.016631, "cvar": -0.018568, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240207_0654", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-02-07", "context_summary": "ICSH: 60-day return history, mean=0.0002, std=0.0003.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0003, min=-0.0004, max=0.0010\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ICSH. Express as a decimal (e.g., -0.02).", "answer": "-0.0002", "answer_numeric": -0.000209, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0002 (i.e., on a bad day with 5% probability, the loss exceeds 0.02%). CVaR(95%) = -0.0004.", "metadata": {"var": -0.000209, "cvar": -0.000397, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230907_0657", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2023-09-07", "context_summary": "VNQ: 60-day return history, mean=-0.0000, std=0.0087.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=-0.0000, std=0.0087, min=-0.0217, max=0.0231\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VNQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0124", "answer_numeric": -0.012412, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0124 (i.e., on a bad day with 5% probability, the loss exceeds 1.24%). CVaR(95%) = -0.0166.", "metadata": {"var": -0.012412, "cvar": -0.016598, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241218_0660", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2024-12-18", "context_summary": "XLY: 60-day return history, mean=0.0031, std=0.0106.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0031, std=0.0106, min=-0.0158, max=0.0315\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 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0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0144", "answer_numeric": -0.014353, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0144 (i.e., on a bad day with 5% probability, the loss exceeds 1.44%). CVaR(95%) = -0.0156.", "metadata": {"var": -0.014353, "cvar": -0.015645, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240402_0663", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-04-02", "context_summary": "XLU: 60-day return history, mean=0.0003, std=0.0105.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0003, std=0.0105, min=-0.0235, max=0.0271\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0183", "answer_numeric": -0.018294, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0183 (i.e., on a bad day with 5% probability, the loss exceeds 1.83%). CVaR(95%) = -0.0215.", "metadata": {"var": -0.018294, "cvar": -0.021489, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241223_0666", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-12-23", "context_summary": "IVV: 60-day return history, mean=0.0006, std=0.0078.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0006, std=0.0078, min=-0.0298, max=0.0245\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IVV. Express as a decimal (e.g., -0.02).", "answer": "-0.0097", "answer_numeric": -0.009658, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0097 (i.e., on a bad day with 5% probability, the loss exceeds 0.97%). CVaR(95%) = -0.0208.", "metadata": {"var": -0.009658, "cvar": -0.020811, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241105_0668", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-11-05", "context_summary": "ADA-USD: 60-day return history, mean=0.0005, std=0.0289.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0289, min=-0.0632, max=0.0660\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0455", "answer_numeric": -0.045547, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0455 (i.e., on a bad day with 5% probability, the loss exceeds 4.55%). CVaR(95%) = -0.0601.", "metadata": {"var": -0.045547, "cvar": -0.060073, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240913_0670", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2024-09-13", "context_summary": "UNG: 60-day return history, mean=-0.0039, std=0.0298.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=-0.0039, std=0.0298, min=-0.0658, max=0.0535\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for UNG. Express as a decimal (e.g., -0.02).", "answer": "-0.0519", "answer_numeric": -0.051868, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0519 (i.e., on a bad day with 5% probability, the loss exceeds 5.19%). CVaR(95%) = -0.0613.", "metadata": {"var": -0.051868, "cvar": -0.061338, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240917_0672", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-09-17", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0044, std=0.0421.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0044, std=0.0421, min=-0.0853, max=0.1371\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0734", "answer_numeric": -0.073414, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0734 (i.e., on a bad day with 5% probability, the loss exceeds 7.34%). CVaR(95%) = -0.0811.", "metadata": {"var": -0.073414, "cvar": -0.081122, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241120_0674", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-11-20", "context_summary": "LINK-USD: 60-day return history, mean=0.0051, std=0.0435.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0051, std=0.0435, min=-0.0785, max=0.1223\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0598", "answer_numeric": -0.059842, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0598 (i.e., on a bad day with 5% probability, the loss exceeds 5.98%). CVaR(95%) = -0.0694.", "metadata": {"var": -0.059842, "cvar": -0.0694, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231016_0676", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-10-16", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0028, std=0.0253.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0028, std=0.0253, min=-0.0789, max=0.0661\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-15] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0397", "answer_numeric": -0.039665, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0397 (i.e., on a bad day with 5% probability, the loss exceeds 3.97%). CVaR(95%) = -0.0598.", "metadata": {"var": -0.039665, "cvar": -0.059835, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241202_0679", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-12-02", "context_summary": "IWM: 60-day return history, mean=0.0019, std=0.0114.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0019, std=0.0114, min=-0.0192, max=0.0349\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 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us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0159", "answer_numeric": -0.015902, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0159 (i.e., on a bad day with 5% probability, the loss exceeds 1.59%). CVaR(95%) = -0.0179.", "metadata": {"var": -0.015902, "cvar": -0.017885, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20230220_0682", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-02-20", "context_summary": "XLU: 60-day return history, mean=-0.0000, std=0.0106.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0000, std=0.0106, min=-0.0243, max=0.0247\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-17] [\"Zacks Value Trader Highlights: Taiwan Semiconductor, Chevron, US Bancorp, Apple and Amazon For Immediate Release Chicago, IL \\u2013 February 17, 2023 \\u2013 Zacks Value Trader is a podcast hosted weekly by Zacks Stock Strategist Tracey Ryniec. Every week, Tracey will be joined by guests to discuss the hottest investing topics in stocks, bonds and ETFs and how it impacts your life. To listen to the podcast, click here: https://www.zacks.com/stock/news/2055570/grading-berkshire-hathaways-q4-trades) Grading Berkshire Hathaway's Q4 Trades Welcome to Episode #317 of the Value Investor Podcast. (0:15) - What Can We Learn From Berkshire Hathaways 13F? (4:30) - Breaking Down Q4 Sells and Growing Positions: How Did They Perform? (15:50) - What Was Berkshire Hathaway Buying With Their Cash Reserves? (20:35) - Episode Roundup: TSM, USB, BK, BAC, CVX, AAPL, LPX, PARA Podcast@Zacks.com Every week, Tracey Ryniec, the editor of Zacks Value Investor portfolio, shares some of her top value investing tips and stock picks. The fourth quarter 2022 13-F filings are out and that means value investors get to see what stocks Warren Buffett, and Berkshire Hathaway, are buying, or selling. Many investors follow his trades to a \\\"t\\\" even going as far as replicating them. But should you? This filing had some surprising sales and few stock purchases, even though the stock market was still selling off, and many stocks were cheap on a valuation basis, and Berkshire was still sitting on a pile of cash. What is Buffett waiting for? Is his lack of purchases a sign that he thinks stocks have further to sell-off? Or did he \\\"miss\\\" the bottom again, like he did in 2020's pandemic sell-off when he also didn't jump in to buy? Let's look at 5 of the key buys and sales in Q4. Berkshire Hathaway's Big Buys, and Sales, in the Fourth Quarter of 2022 1. Taiwan Semiconductor TSM Berkshire Hathaway first bought a position in Taiwan Semiconductor in the third quarter of 2022 to much fanfare. It was a $4.2 billion position and the first semiconductor company to be in the portfolio for years. But in the fourth quarter, just a few months later, Berkshire sold 86% of its Taiwan Semiconductor shares. It went from 60 million shares to just 8.3 million. What happened to the infamous Buffett strategy of the best time to sell is never? Even worse, shares of Taiwan Semiconductor have rallied big in 2023, adding 24.5%. Does this sale of Taiwan Semiconductor make any sense? 2. Chevron CVX Berkshire Hathaway has gone all in on the energy companies over the last 2 years, buying billions of dollars of Chevron and Occidental Petroleum. But in the fourth quarter of 2022, it sold 1%, or 2.4 million shares, of its Chevron position. This was also a head scratcher to many. What's the point of selling such a small position? Is Buffett still a big believer in Chevron? 3. US Bancorp USB Berkshire continues to sell shares of its regional banks. It first bought US Bancorp in the first quarter of 2006. But in the fo\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0174", "answer_numeric": -0.01736, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0174 (i.e., on a bad day with 5% probability, the loss exceeds 1.74%). CVaR(95%) = -0.0224.", "metadata": {"var": -0.01736, "cvar": -0.022437, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240329_0685", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-03-29", "context_summary": "IVV: 60-day return history, mean=0.0017, std=0.0069.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0017, std=0.0069, min=-0.0166, max=0.0207\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K WMT 2024-03-15] wmt-20240131 0000104169 2024 FY false http://fasb.org/us-gaap/2023#AccountsPayableCurrent http://fasb.org/us-gaap/2023#AccountsPayableCurrent P1Y P5Y 0000104169 2023-02-01 2024-01-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2023-02-01 2024-01-31 0000104169 wmt:A2.550NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1050NotesDue2026Member 2023-02-01 2024-01-31 0000104169 wmt:A1500NotesDue2028Member 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(C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IVV. Express as a decimal (e.g., -0.02).", "answer": "-0.0083", "answer_numeric": -0.008302, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0083 (i.e., on a bad day with 5% probability, the loss exceeds 0.83%). CVaR(95%) = -0.0134.", "metadata": {"var": -0.008302, "cvar": -0.01341, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240703_0688", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-07-03", "context_summary": "SOL-USD: 60-day return history, mean=0.0019, std=0.0393.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0393, min=-0.0652, max=0.1138\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0507", "answer_numeric": -0.050716, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0507 (i.e., on a bad day with 5% probability, the loss exceeds 5.07%). CVaR(95%) = -0.0588.", "metadata": {"var": -0.050716, "cvar": -0.058843, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240522_0691", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-05-22", "context_summary": "QQQ: 60-day return history, mean=0.0007, std=0.0100.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0007, std=0.0100, min=-0.0209, max=0.0199\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QQQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0167", "answer_numeric": -0.016664, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. 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blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VTI. Express as a decimal (e.g., -0.02).", "answer": "-0.0125", "answer_numeric": -0.012476, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0125 (i.e., on a bad day with 5% probability, the loss exceeds 1.25%). CVaR(95%) = -0.0158.", "metadata": {"var": -0.012476, "cvar": -0.015753, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230614_0697", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-06-14", "context_summary": "ADA-USD: 60-day return history, mean=-0.0073, std=0.0285.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0073, std=0.0285, min=-0.0889, max=0.0442\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-13] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0652", "answer_numeric": -0.065168, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0652 (i.e., on a bad day with 5% probability, the loss exceeds 6.52%). CVaR(95%) = -0.0809.", "metadata": {"var": -0.065168, "cvar": -0.080918, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230904_0700", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-09-04", "context_summary": "BNB-USD: 60-day return history, mean=-0.0016, std=0.0186.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0016, std=0.0186, min=-0.0575, max=0.0511\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-03] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0322", "answer_numeric": -0.032188, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0322 (i.e., on a bad day with 5% probability, the loss exceeds 3.22%). CVaR(95%) = -0.0412.", "metadata": {"var": -0.032188, "cvar": -0.041159, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241101_0703", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2024-11-01", "context_summary": "DBC: 60-day return history, mean=-0.0000, std=0.0113.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=-0.0000, std=0.0113, min=-0.0267, max=0.0197\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DBC. Express as a decimal (e.g., -0.02).", "answer": "-0.0192", "answer_numeric": -0.019232, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0192 (i.e., on a bad day with 5% probability, the loss exceeds 1.92%). CVaR(95%) = -0.0233.", "metadata": {"var": -0.019232, "cvar": -0.023329, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240820_0705", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-08-20", "context_summary": "LINK-USD: 60-day return history, mean=-0.0046, std=0.0443.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0046, std=0.0443, min=-0.1260, max=0.1319\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0712", "answer_numeric": -0.071175, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0712 (i.e., on a bad day with 5% probability, the loss exceeds 7.12%). CVaR(95%) = -0.0935.", "metadata": {"var": -0.071175, "cvar": -0.09349, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231027_0708", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-10-27", "context_summary": "BTC-USD: 60-day return history, mean=0.0047, std=0.0218.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0047, std=0.0218, min=-0.0500, max=0.1031\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-26] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0190", "answer_numeric": -0.018995, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0190 (i.e., on a bad day with 5% probability, the loss exceeds 1.90%). CVaR(95%) = -0.0323.", "metadata": {"var": -0.018995, "cvar": -0.032252, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231128_0711", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-11-28", "context_summary": "DOT-USD: 60-day return history, mean=0.0044, std=0.0319.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0044, std=0.0319, min=-0.0783, max=0.0967\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-27] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0372", "answer_numeric": -0.037184, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0372 (i.e., on a bad day with 5% probability, the loss exceeds 3.72%). CVaR(95%) = -0.0584.", "metadata": {"var": -0.037184, "cvar": -0.058353, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231214_0714", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2023-12-14", "context_summary": "STIP: 60-day return history, mean=0.0003, std=0.0017.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0003, std=0.0017, min=-0.0028, max=0.0045\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for STIP. Express as a decimal (e.g., -0.02).", "answer": "-0.0020", "answer_numeric": -0.002019, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0020 (i.e., on a bad day with 5% probability, the loss exceeds 0.20%). CVaR(95%) = -0.0026.", "metadata": {"var": -0.002019, "cvar": -0.002612, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230502_0716", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-05-02", "context_summary": "^VIX: 60-day return history, mean=-0.0025, std=0.0607.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0025, std=0.0607, min=-0.1284, max=0.1682\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-01] [\"B of A Securities Maintains Apple (AAPL) Neutral Recommendation Fintel reports that on May 1, 2023, B of A Securities maintained coverage of Apple (NASDAQ:AAPL) with a Neutral recommendation. Analyst Price Forecast Suggests 2.49% Upside As of April 24, 2023, the average one-year price target for Apple is 173.91. The forecasts range from a low of 117.16 to a high of $215.25. The average price target represents an increase of 2.49% from its latest reported closing price of 169.68. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is 413,641MM, an increase of 6.74%. The projected annual non-GAAP EPS is 6.36. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. What is the Fund Sentiment? There are 6412 funds or institutions reporting positions in Apple. This is an increase of 218 owner(s) or 3.52% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 2.90%, a decrease of 12.63%. Total shares owned by institutions increased in the last three months by 0.01% to 10,120,461K shares. The put/call ratio of AAPL is 1.01, indicating a bearish outlook. What are Other Shareholders Doing? Berkshire Hathaway holds 895,136K shares representing 5.66% ownership of the company. In it's prior filing, the firm reported owning 894,802K shares, representing an increase of 0.04%. The firm decreased its portfolio allocation in AAPL by 6.86% over the last quarter. VTSMX - Vanguard Total Stock Market Index Fund Investor Shares holds 459,387K shares representing 2.90% ownership of the company. In it's prior filing, the firm reported owning 455,109K shares, representing an increase of 0.93%. The firm decreased its portfolio allocation in AAPL by 12.36% over the last quarter. VFINX - Vanguard 500 Index Fund Investor Shares holds 345,686K shares representing 2.18% ownership of the company. In it's prior filing, the firm reported owning 342,454K shares, representing an increase of 0.94%. The firm decreased its portfolio allocation in AAPL by 12.57% over the last quarter. Geode Capital Management holds 282,750K shares representing 1.79% ownership of the company. In it's prior filing, the firm reported owning 279,759K shares, representing an increase of 1.06%. The firm decreased its portfolio allocation in AAPL by 12.15% over the last quarter. Price T Rowe Associates holds 226,281K shares representing 1.43% ownership of the company. In it's prior filing, the firm reported owning 224,864K shares, representing an increase of 0.63%. The firm decreased its portfolio allocation in AAPL by 7.53% over the last quarter. Apple Background Information (This description is provided by the company.) Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services. It is considered one of the Big Five companies in the U.S. informat\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ^VIX. Express as a decimal (e.g., -0.02).", "answer": "-0.1015", "answer_numeric": -0.101513, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1015 (i.e., on a bad day with 5% probability, the loss exceeds 10.15%). CVaR(95%) = -0.1205.", "metadata": {"var": -0.101513, "cvar": -0.120465, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230704_0718", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-07-04", "context_summary": "XLE: 60-day return history, mean=-0.0008, std=0.0136.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0008, std=0.0136, min=-0.0445, max=0.0300\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-03] [\"Unity Software Stock Skyrockets 46% in June as AI Buzz Takes Over What happened Shares of Unity Software (NYSE: U) skyrocketed 46.1% in June, according to data provided by S&P Global Market Intelligence. The month started off with fireworks from Apple that are relevant to Unity shareholders. And it ended with a bang related to artificial intelligence (AI), Wall Street's favorite subject at the moment. So what To give this story some context, I want to point out that the market had lost a lot of confidence in Unity Software stock. When they first went public, shares regularly traded above a price-to-sales (P/S) ratio of 30. By comparison, they traded below a P/S of 7 at the start of June. That's still high in absolute terms. But in relative terms, this valuation was more than 80% below where it had routinely traded. Unity's own revenue growth was ample reason for the market's pessimism. And even though its growth has since rebounded, as the chart below shows, this is largely due to an acquisition. Its organic growth is still challenged. U Revenue (quarterly YoY growth) data by YCharts; YoY = year over year. But on June 5, Apple announced its upcoming Vision Pro headset, and this has reinvigorated investors' excitement for Unity's potential. Apple is looking for apps to be built for the headset between now and its launch in 2024. And for this, the company has partnered with Unity. Developers use Unity for building top-notch video games. And Apple has created a software development kit that will allow Unity users to modify their creations for the Vision Pro. Then on June 27, Unity announced a marketplace for AI applications. The marketplace has 10 apps available at launch that can be used in the video game space. And when the company announced this new focus on AI, the market celebrated by pushing the stock higher. So the stock started June with low expectations, but Apple and AI have investors rethinking the long-term potential. Now what When it comes to the AI space, I'm inclined to disregard most news as overhyped clickbait. But with Unity Software stock, I do believe that AI -- specifically generative AI -- could play an important role for the business. Many investors like Unity's potential in virtual reality and the metaverse. Its software creates realistic 3D images, and realism is needed to make these experiences something that consumers actually want. When building digital worlds, the problem is how big these need to be -- it's labor intensive for developers. And the workload is probably too much to physically handle at scale, which is where generative AI can help. Much of what Unity is doing involves generative AI, which I believe is just what the space needs. So as virtual reality and the metaverse grow -- perhaps thanks to Apple's Vision Pro headset -- the use cases for Unity Software could open up as well. That's good reason for optimism for a stock that's still down almost 80% from its all-time high. 10 stocks we like better than Unit\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLE. Express as a decimal (e.g., -0.02).", "answer": "-0.0192", "answer_numeric": -0.019239, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0192 (i.e., on a bad day with 5% probability, the loss exceeds 1.92%). CVaR(95%) = -0.0307.", "metadata": {"var": -0.019239, "cvar": -0.030661, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230213_0720", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-02-13", "context_summary": "XRP-USD: 60-day return history, mean=-0.0001, std=0.0267.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0267, min=-0.0694, max=0.0652\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-12] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0392", "answer_numeric": -0.039226, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0392 (i.e., on a bad day with 5% probability, the loss exceeds 3.92%). CVaR(95%) = -0.0521.", "metadata": {"var": -0.039226, "cvar": -0.052099, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230523_0722", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-05-23", "context_summary": "LINK-USD: 60-day return history, mean=-0.0021, std=0.0293.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0021, std=0.0293, min=-0.0940, max=0.0614\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-22] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0534", "answer_numeric": -0.05336, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0534 (i.e., on a bad day with 5% probability, the loss exceeds 5.34%). CVaR(95%) = -0.0673.", "metadata": {"var": -0.05336, "cvar": -0.067325, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240604_0724", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-06-04", "context_summary": "XLRE: 60-day return history, mean=-0.0006, std=0.0113.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0006, std=0.0113, min=-0.0375, max=0.0250\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 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blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLRE. Express as a decimal (e.g., -0.02).", "answer": "-0.0177", "answer_numeric": -0.017659, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0177 (i.e., on a bad day with 5% probability, the loss exceeds 1.77%). CVaR(95%) = -0.0259.", "metadata": {"var": -0.017659, "cvar": -0.025866, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230615_0726", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-06-15", "context_summary": "LINK-USD: 60-day return history, mean=-0.0066, std=0.0308.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0066, std=0.0308, min=-0.1245, max=0.0505\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-14] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0556", "answer_numeric": -0.055614, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0556 (i.e., on a bad day with 5% probability, the loss exceeds 5.56%). CVaR(95%) = -0.0930.", "metadata": {"var": -0.055614, "cvar": -0.092967, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240327_0728", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-03-27", "context_summary": "MATIC-USD: 60-day return history, mean=0.0063, std=0.0436.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0063, std=0.0436, min=-0.0987, max=0.0827\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0740", "answer_numeric": -0.073997, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0740 (i.e., on a bad day with 5% probability, the loss exceeds 7.40%). CVaR(95%) = -0.0931.", "metadata": {"var": -0.073997, "cvar": -0.093133, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240822_0729", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-08-22", "context_summary": "XLV: 60-day return history, mean=0.0012, std=0.0078.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0012, std=0.0078, min=-0.0271, max=0.0219\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 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us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLV. Express as a decimal (e.g., -0.02).", "answer": "-0.0103", "answer_numeric": -0.010319, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0103 (i.e., on a bad day with 5% probability, the loss exceeds 1.03%). CVaR(95%) = -0.0207.", "metadata": {"var": -0.010319, "cvar": -0.02075, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240724_0730", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-07-24", "context_summary": "USMV: 60-day return history, mean=0.0009, std=0.0049.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0009, std=0.0049, min=-0.0115, max=0.0137\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 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blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0086", "answer_numeric": -0.0086, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0086 (i.e., on a bad day with 5% probability, the loss exceeds 0.86%). CVaR(95%) = -0.0104.", "metadata": {"var": -0.0086, "cvar": -0.010447, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240826_0732", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-08-26", "context_summary": "ADA-USD: 60-day return history, mean=0.0008, std=0.0396.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0008, std=0.0396, min=-0.1079, max=0.0869\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0666", "answer_numeric": -0.06664, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0666 (i.e., on a bad day with 5% probability, the loss exceeds 6.66%). CVaR(95%) = -0.0903.", "metadata": {"var": -0.06664, "cvar": -0.090311, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240108_0734", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2024-01-08", "context_summary": "SCHP: 60-day return history, mean=0.0007, std=0.0040.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0007, std=0.0040, min=-0.0086, max=0.0098\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SCHP. Express as a decimal (e.g., -0.02).", "answer": "-0.0045", "answer_numeric": -0.004535, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0045 (i.e., on a bad day with 5% probability, the loss exceeds 0.45%). CVaR(95%) = -0.0061.", "metadata": {"var": -0.004535, "cvar": -0.00607, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240812_0735", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-08-12", "context_summary": "IWM: 60-day return history, mean=0.0000, std=0.0142.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0000, std=0.0142, min=-0.0360, max=0.0349\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 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us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0223", "answer_numeric": -0.022254, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0223 (i.e., on a bad day with 5% probability, the loss exceeds 2.23%). CVaR(95%) = -0.0339.", "metadata": {"var": -0.022254, "cvar": -0.033921, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20231103_0737", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-11-03", "context_summary": "AVAX-USD: 60-day return history, mean=0.0035, std=0.0288.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0035, std=0.0288, min=-0.0553, max=0.0781\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-02] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0379", "answer_numeric": -0.037904, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0379 (i.e., on a bad day with 5% probability, the loss exceeds 3.79%). CVaR(95%) = -0.0463.", "metadata": {"var": -0.037904, "cvar": -0.046252, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231215_0739", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-12-15", "context_summary": "ETH-USD: 60-day return history, mean=0.0070, std=0.0278.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0070, std=0.0278, min=-0.0544, max=0.1224\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-14] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0373", "answer_numeric": -0.037334, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0373 (i.e., on a bad day with 5% probability, the loss exceeds 3.73%). CVaR(95%) = -0.0483.", "metadata": {"var": -0.037334, "cvar": -0.048261, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240722_0740", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-07-22", "context_summary": "ADA-USD: 60-day return history, mean=-0.0008, std=0.0313.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0008, std=0.0313, min=-0.1079, max=0.0646\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0423", "answer_numeric": -0.042315, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0423 (i.e., on a bad day with 5% probability, the loss exceeds 4.23%). CVaR(95%) = -0.0731.", "metadata": {"var": -0.042315, "cvar": -0.073134, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240130_0742", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2024-01-30", "context_summary": "SOYB: 60-day return history, mean=-0.0023, std=0.0092.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=-0.0023, std=0.0092, min=-0.0200, max=0.0267\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOYB. Express as a decimal (e.g., -0.02).", "answer": "-0.0170", "answer_numeric": -0.017031, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0170 (i.e., on a bad day with 5% probability, the loss exceeds 1.70%). CVaR(95%) = -0.0182.", "metadata": {"var": -0.017031, "cvar": -0.018237, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240213_0744", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-02-13", "context_summary": "VLUE: 60-day return history, mean=0.0018, std=0.0077.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0018, std=0.0077, min=-0.0175, max=0.0229\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization 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us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-01-01 2023-09-30 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-09-30 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2022-12-31 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2023-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2022-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2023-12-31 0001018724 amzn:VendorAccountsReceivableMember 2022-12-31 0001018724 amzn:VendorAccountsReceivableMember 2023-12-31 0001018724 us-gaap:LoansReceivableMember 2022-12-31 0001018724 us-gaap:LoansReceivableMember 2023-12-31 00 [...TRUNCATED...] tents 32.2 Certification of Brian T. Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0100", "answer_numeric": -0.010003, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0100 (i.e., on a bad day with 5% probability, the loss exceeds 1.00%). CVaR(95%) = -0.0127.", "metadata": {"var": -0.010003, "cvar": -0.012712, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20240718_0745", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-07-18", "context_summary": "ETH-USD: 60-day return history, mean=0.0013, std=0.0308.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0013, std=0.0308, min=-0.0724, max=0.1560\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0366", "answer_numeric": -0.036605, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0366 (i.e., on a bad day with 5% probability, the loss exceeds 3.66%). CVaR(95%) = -0.0546.", "metadata": {"var": -0.036605, "cvar": -0.054643, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231115_0747", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-11-15", "context_summary": "EWJ: 60-day return history, mean=0.0006, std=0.0102.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0006, std=0.0102, min=-0.0176, max=0.0197\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-14] [\"Berkshire invests in Atlanta Braves, sheds GM and other stocks Nov 14 (Reuters) - Berkshire Hathaway BRKa.N, the conglomerate run by billionaire Warren Buffett, on Tuesday said it has made a small investment in the company that indirectly owns the Atlanta Braves baseball team, and eliminated its holdings in General Motors GM.N and Procter & Gamble PG.N. The changes were disclosed in a regulatory filing that detailed Berkshire's U.S.-listed stock holdings, which comprise most of its $318.6 billion equity portfolio, as of Sept. 30. Berkshire sold $7 billion of stocks and bought just $1.7 billion in the third quarter, a down period for its stock holdings led by Apple AAPL.O, whose share price fell 12%. (Reporting by Jonathan Stempel in New York; Editing by Christian Schmollinger) ((jon.stempel@thomsonreuters.com; +1 646 223 6317; Reuters Messaging: jon.stempel.thomsonreuters.com@reuters.net)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Pilgrim's Pride and Malibu Boats have been highlighted as Zacks Bull and Bear of the Day For Immediate Release Chicago, IL \\u2013 November 14, 2023 \\u2013 Zacks Equity Research shares Pilgrim's Pride PPC as the Bull of the Day and Malibu Boats MBUU as the Bear of the Day. In addition, Zacks Equity Research provides analysis on The Walt Disney Company DIS, Apple Inc. AAPL and Amazon.com, Inc. AMZN. Here is a synopsis of all five stocks: Bull of the Day: Pilgrim's Pride is a Zacks Rank #1 (Strong Buy) that engages in the production, processing, marketing and distribution of fresh, frozen, and value-added chicken, and pork products to retailers, distributors, and foodservice operators. The stock is trading at 52-week highs after a revenue and earnings beat. While PPC is trading up about 15% on the year, it is still down 25% from 2022 highs. Investors should be looking for more upside if the stock can break the resistance level at $26.50. More About Pilgrim's Pride The company was founded in 1946 and is headquartered in Greeley, Colorado. It employs over 61,000 people and has a market cap of $6 billion. Pilgrim's Pride offers its products under the Pilgrim's, Just BARE, Gold'n Pump, Gold Kist, County Pride, Pierce Chicken, Pilgrim's Mexico, County Post, Savoro, To-Ricos, Del Dia, Moy Park, O'Kane, Richmond, Fridge Raiders, and Denny brands. The company sells its products to chain restaurants, food processors, broad-line distributors, and the retail market. PPC has a Zacks Style Score of \\\"A\\\" in Value and \\\"B\\\" in Growth. The stock has a Forward PE of 17 and pays no dividend. Q3 Earnings In late October, PPC reported a 14% earnings beat on revenues. This the seventh straight earnings beat for the company who has not missed on earnings expectations since late 2021. Q3 came in at $0.58 v $0.42 expected and revenues were $4.4B v $4.29Be. Adjusted EBITDA margins were 7.4%, which was down from the 10.3% last year. While the company e\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EWJ. Express as a decimal (e.g., -0.02).", "answer": "-0.0156", "answer_numeric": -0.015627, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0156 (i.e., on a bad day with 5% probability, the loss exceeds 1.56%). CVaR(95%) = -0.0167.", "metadata": {"var": -0.015627, "cvar": -0.016667, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230725_0749", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-07-25", "context_summary": "USMV: 60-day return history, mean=0.0009, std=0.0055.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0009, std=0.0055, min=-0.0111, max=0.0138\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-24] [\"Wells Fargo Maintains Apple (AAPL) Overweight Recommendation Fintel reports that on July 24, 2023, Wells Fargo maintained coverage of Apple (NASDAQ:AAPL) with a Overweight recommendation. Analyst Price Forecast Suggests 0.16% Upside As of July 6, 2023, the average one-year price target for Apple is 192.24. The forecasts range from a low of 141.40 to a high of $252.00. The average price target represents an increase of 0.16% from its latest reported closing price of 191.94. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is 413,641MM, an increase of 7.41%. The projected annual non-GAAP EPS is 6.36. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. What is the Fund Sentiment? There are 6390 funds or institutions reporting positions in Apple. This is a decrease of 15 owner(s) or 0.23% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 3.91%, an increase of 45.88%. Total shares owned by institutions increased in the last three months by 37.90% to 14,010,479K shares. The put/call ratio of AAPL is 0.89, indicating a bullish outlook. What are Other Shareholders Doing? Berkshire Hathaway holds 915,560K shares representing 5.82% ownership of the company. In it's prior filing, the firm reported owning 895,136K shares, representing an increase of 2.23%. The firm increased its portfolio allocation in AAPL by 19.39% over the last quarter. VTSMX - Vanguard Total Stock Market Index Fund Investor Shares holds 465,280K shares representing 2.96% ownership of the company. In it's prior filing, the firm reported owning 459,387K shares, representing an increase of 1.27%. The firm increased its portfolio allocation in AAPL by 18.69% over the last quarter. VFINX - Vanguard 500 Index Fund Investor Shares holds 347,041K shares representing 2.21% ownership of the company. In it's prior filing, the firm reported owning 345,686K shares, representing an increase of 0.39%. The firm increased its portfolio allocation in AAPL by 18.16% over the last quarter. Geode Capital Management holds 285,171K shares representing 1.81% ownership of the company. In it's prior filing, the firm reported owning 282,750K shares, representing an increase of 0.85%. The firm increased its portfolio allocation in AAPL by 18.38% over the last quarter. Price T Rowe Associates holds 234,017K shares representing 1.49% ownership of the company. In it's prior filing, the firm reported owning 226,281K shares, representing an increase of 3.31%. The firm increased its portfolio allocation in AAPL by 22.14% over the last quarter. Apple Background Information (This description is provided by the company.) Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services. It is considered one of the Big Five companies in the U.S. information \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0078", "answer_numeric": -0.007835, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0078 (i.e., on a bad day with 5% probability, the loss exceeds 0.78%). CVaR(95%) = -0.0097.", "metadata": {"var": -0.007835, "cvar": -0.009713, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230418_0751", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-04-18", "context_summary": "^VIX: 60-day return history, mean=-0.0032, std=0.0589.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0032, std=0.0589, min=-0.1284, max=0.1682\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-17] [\"Technology Sector Update for 04/17/2023: GOOG, AAPL, MSFT, GOOGL Tech stocks were lower Monday afternoon, with the Technology Select Sector SPDR Fund (XLK) decreasing 0.2% and the Philadelphia Semiconductor index falling 1%. In company news, Alphabet (GOOG) shares were shedding 3% after it was reported to be facing increasing competition from rivals in the search business and the AI race, the New York Times reported, citing a review of Google's internal documents. Apple (AAPL) said it has entered a partnership with Goldman Sachs (GS) to launch a savings account for Apple Card users. Apple was down 0.5%. Microsoft (MSFT) and Epic said they will expand their partnership to integrate artificial intelligence technology into their healthcare offerings by adding Azure's OpenAI Service to Epic's electronic health record software. Microsoft shares were edging up 0.2%. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"PREVIEW-TSMC Q1 earnings seen down 5% y/y, Q2 also looks tough By Faith Hung and Ben Blanchard TAIPEI, April 18 (Reuters) - Taiwanese chipmaker TSMC 2330.TW is expected to post a 5% fall in first-quarter net profit on Thursday, with global economic woes denting demand for semiconductors used in everything from cars to advanced computing extending into the current quarter. Taiwan Semiconductor Manufacturing Co Ltd (TSMC) TSM.N, the world's largest contract chipmaker and a major Apple Inc AAPL.O supplier, is likely to report net profit for the January-March period of T$192.5 billion ($6.30 billion), down from T$202.7 billion a year earlier, according to the average of 21 analysts polled by Reuters. \\\"Looking ahead into the second quarter, which is typically a slow season, TSMC's sales on a quarterly basis will be under pressure from inventory adjustments as major clients cut back on orders,\\\" said Alex Huang, who manages about T$5 billion for Capital Investment Trust Corp. But momentum may pick up as early as the third quarter, he added, corresponding with the improved outlooks for that quarter projected by Apple, Nvidia Corp NVDA.O and Advanced Micro Devices Inc AMD.O, some of TSMC's biggest customers. TSMC, Asia's most valuable listed company, has forecast demand will recover in the second half of this year. It will provide guidance for the second quarter and update previous forecasts on itsearnings callat 0600 GMT on Thursday. TSMC already reported its first quarter revenue of T$508.63 billion ($16.69 billion), at the bottom of a January forecast range of $16.7 billion to $17.5 billion, compared to $17.57 billion for the year-ago period. TSMC said in January its capital spending in 2023 would decrease to between $32 billion and $36 billion from $36.3 billion in 2022. The company's concentration of production in Taiwan at a time of growing military tensions with China, which claims the island as its own territory, has spooked some investors. U.S. billion\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ^VIX. Express as a decimal (e.g., -0.02).", "answer": "-0.0836", "answer_numeric": -0.0836, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0836 (i.e., on a bad day with 5% probability, the loss exceeds 8.36%). CVaR(95%) = -0.1205.", "metadata": {"var": -0.0836, "cvar": -0.120465, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231207_0753", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-12-07", "context_summary": "^VIX: 60-day return history, mean=-0.0015, std=0.0577.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0015, std=0.0577, min=-0.1157, max=0.1471\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-06] [\"ROKU Collaborates With Tennis Channel to Launch T2 in the US Roku Inc. ROKU has announced a collaboration with Tennis Channel to launch T2, the sports network's second channel, on The Roku Channel in the United States. T2 is set to provide free and year-round access to live coverage of top tennis players and signature events for the vast audience of The Roku Channel, reaching an estimated 100 million people. For convenient access, viewers can easily navigate T2 through the Sports Experience on Roku's Home Screen. This feature simplifies the discovery and access of live, upcoming and on-demand sports content, enhancing engagement and awareness for Roku's content partners while providing a personalized viewing experience. T2's yearly live and encore calendar aligns with most tournaments covered by Tennis Channel, showcasing different matches and players. This unique approach allows viewers with access to both channels to choose between simultaneous competitions from prestigious events, such as the BNP Paribas Open, Roland Garros, Miami Open, Monte-Carlo Masters, Italian Open, Canadian Open, Davis Cup and the Billie Jean King Cup. Shares of this Zacks Rank #3 (Hold) company have gained 158.5% year to date compared with the Zacks Consumer Discretionary sector\\u2019s rise of 12.4% due to its extensive collection of content. You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. Roku, Inc. Price and Consensus Roku, Inc. price-consensus-chart | Roku, Inc. Quote ROKU\\u2019s Recent Efforts to Boost Streaming Hours The company recently unveiled two fresh additions to the Roku Home Screen, such as All Things Food and All Things Home. These new destinations bring together top-notch food, home and lifestyle content from various sources on the platform, creating seamless and engaging discovery experiences. These new features are expected to boost streaming hours as well as platform revenues in the upcoming quarters. The Zacks Consensus Estimate for ROKU\\u2019s 2023 streaming hours is pegged at 105.33 billion, indicating a year-over-year increase of 340.7%. The consensus estimate for 2023 platform revenues is pegged at $2.9 billion, indicating a year-over-year increase of 7.38%. Designed for user convenience, these hubs offer straightforward navigation and personalized recommendations, simplifying the exploration and viewing of genre entertainment directly from the home screen. Both All Things Food and All Things Home will showcase a diverse array of streaming options within their respective categories, encompassing free and subscription-based services, live and linear TV, Premium Subscriptions, Roku Originals and more. These features were added due to a recent survey commissioned by Roku. This recent survey revealed that 64% of streamers rely on genre-based searches when looking for new content, emphasizing the significance of genre preferences in content discovery. According to the survey, nearly 73% of streamers feel that the\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ^VIX. Express as a decimal (e.g., -0.02).", "answer": "-0.0745", "answer_numeric": -0.07451, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0745 (i.e., on a bad day with 5% probability, the loss exceeds 7.45%). CVaR(95%) = -0.0923.", "metadata": {"var": -0.07451, "cvar": -0.092252, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230530_0755", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-05-30", "context_summary": "XRP-USD: 60-day return history, mean=-0.0010, std=0.0239.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0010, std=0.0239, min=-0.0764, max=0.0518\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-29] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0443", "answer_numeric": -0.044283, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0443 (i.e., on a bad day with 5% probability, the loss exceeds 4.43%). CVaR(95%) = -0.0592.", "metadata": {"var": -0.044283, "cvar": -0.059215, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230109_0756", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-01-09", "context_summary": "EFA: 60-day return history, mean=0.0027, std=0.0121.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0027, std=0.0121, min=-0.0259, max=0.0259\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-06] [\"Are Growth Stocks in for More Pain in 2023? By just about every metric, 2022 was a terrible year for growth stocks but a solid one for value stocks. The Dow Jones Industrial Average outperformed the Nasdaq Composite by the largest margin in over 20 years. Ark Innovation ETF, Cathie Wood's exchange-traded fund, lost 67% of its value in 2022, while Warren Buffett's Berkshire Hathaway gained 4%. And the Vanguard Growth ETF lost 34% of its value last year, while the Vanguard Value ETF fell just 5%. One of the million-dollar questions of 2023 is whether value stocks can continue outperforming growth stocks. But instead of speculating on short-term trends, there are better questions to ask: What role do you want growth stocks to play in your portfolio? Are they right for you in the first place? If so, what kind of growth stocks give you the best chance to reach your financial goals while aligning your investments with your personal risk tolerance? We'll discuss these questions and more in this article. Image source: Getty Images. Lessons from 2022 2022 was the worst year for the stock market since 2008 and the worst year in many investors' lifetimes. Yet bear markets can help lead you toward lasting wealth as long as you're invested in quality businesses, hold through volatile periods, and continue to save regularly. Last year illustrated the dangers of gambling instead of investing. Many unprofitable growth stocks and meme stocks saw their valuations balloon to nosebleed levels that could no longer be supported by their fundamentals. Once the dust settled, it was clear that many of these companies simply weren't worth that much, at least not today. Like the dot-com bust, some notable companies will emerge from the ashes and eclipse their prior all-time highs over time, but it could be many years before those stocks reverse the losses from this bear market. It took Microsoft (NASDAQ: MSFT) over 17 years to finally surpass its 1999 all-time high. And it did so by unlocking new revenue streams, reinventing its business, and becoming an industry leader in several key categories. Investors looking at growth stocks that are down 70%, 80%, or 90% from their all-time highs shouldn't buy them solely because they are down. Rather, investing only in companies you understand and believe can foster long-term value is important. Just because a company is exciting and growing doesn't mean the stock is a good buy. For a growth stock to continue outperforming the market over time, a rising stock price has to be supported by the fundamentals. Growth stocks at a good value When a company's fundamentals keep pace or even exceed its stock price, a growth stock can start to look much more like a value stock. That's exactly what's happening to Microsoft, Apple (NASDAQ: AAPL), and Alphabet (NASDAQ: GOOG) (NASDAQ: GOOGL) right now. All three stocks have beaten the market over the last five to 10 years. But their recent sell-offs, paired with incredible revenue and profit gr\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0141", "answer_numeric": -0.014083, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0141 (i.e., on a bad day with 5% probability, the loss exceeds 1.41%). CVaR(95%) = -0.0185.", "metadata": {"var": -0.014083, "cvar": -0.018532, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230609_0758", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-06-09", "context_summary": "LINK-USD: 60-day return history, mean=-0.0027, std=0.0279.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0027, std=0.0279, min=-0.0940, max=0.0505\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-08] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0534", "answer_numeric": -0.053447, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0534 (i.e., on a bad day with 5% probability, the loss exceeds 5.34%). CVaR(95%) = -0.0699.", "metadata": {"var": -0.053447, "cvar": -0.069921, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240906_0760", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2024-09-06", "context_summary": "HYG: 60-day return history, mean=0.0008, std=0.0024.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0008, std=0.0024, min=-0.0062, max=0.0053\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for HYG. Express as a decimal (e.g., -0.02).", "answer": "-0.0032", "answer_numeric": -0.003201, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0032 (i.e., on a bad day with 5% probability, the loss exceeds 0.32%). CVaR(95%) = -0.0044.", "metadata": {"var": -0.003201, "cvar": -0.004353, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230412_0761", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-04-12", "context_summary": "EWJ: 60-day return history, mean=0.0004, std=0.0087.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0004, std=0.0087, min=-0.0205, max=0.0227\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-11] [\"Apple To Open First Store In India Next Week (RTTNews) - Apple Inc. is opening its first store in India, which is being considered as the new manufacturing base for the tech major, as well as its new growth market. The gadgets major has high hopes for the second most populous country in the world, with wider markets. The iPhone maker announced its plans to open two new retail locations in India offering the latest Apple products, including the new iPhone 14. Apple BKC in India's financial capital Mumbai will be opened on April 18, and Apple Saket in Delhi, the country's political capital, on April 20. Apple Chief Executive Officer Tim Cook is scheduled to be present during the store openings, Bloomberg reported. These new retail locations in India will offer great new ways to browse, discover, and buy Apple products with exceptional service and experiences for customers. The barricade for Apple Saket features a unique design that takes inspiration from Delhi's many gates, each signifying a new chapter to the city's storied past. The colorful artwork celebrates Apple's second store in India. Beginning April 20, customers will be able to stop by to explore Apple's latest product lineup, find creative inspiration, and get personalized service and support from the store's team of Specialists, Creatives, and Geniuses. In celebration of the first Apple Store opening in India, Apple BKC announced a special Today at Apple series, \\\"Mumbai Rising\\\", running between April 18 and May 25. These sessions will offer hands-on activities with Apple's products and services that celebrate the local community and culture in Mumbai. Ahead of opening day, customers are invited to download custom Apple BKC and Apple Saket wallpapers, and specially curated playlists on Apple Music to move to the sounds of Mumbai and Delhi. Apple, which assembles most of its iPhones in China, last year announced plans to shift some production of its flagship smartphone iPhone 14 from China to India amid continuing tensions between the US and China, along with the then prevailed COVID-19 issues. Foxconn, Apple's key iPhone assembler, already manufactures iPhones at its Sriperumbudur factory on the outskirts of Chennai, India. In March, Bloomberg reported that Foxconn plans to invest $700 million to set up a new iPhone plant in India's Karnataka state, which would create 100,000 jobs. Foxconn will build a new 300-acre facility in Bengaluru as part of its ongoing effort to pivot away from China. In late March, Apple announced its plan to open its fifth retail store in South Korea. Apple opened its first store in South Korea in 2018. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Time to Buy These 3 Next Gen Big Tech Companies? Many of the biggest and most profitable companies today are the technology giants such as Alphabet GOOGL, Apple AAPL, and Meta Platforms META. Their valuations have exploded h\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EWJ. Express as a decimal (e.g., -0.02).", "answer": "-0.0125", "answer_numeric": -0.012484, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0125 (i.e., on a bad day with 5% probability, the loss exceeds 1.25%). CVaR(95%) = -0.0169.", "metadata": {"var": -0.012484, "cvar": -0.016857, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230831_0763", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-08-31", "context_summary": "VEA: 60-day return history, mean=0.0002, std=0.0085.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0002, std=0.0085, min=-0.0195, max=0.0190\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-30] [\"Should Schwab 1000 Index ETF (SCHK) Be on Your Investing Radar? Looking for broad exposure to the Large Cap Blend segment of the US equity market? You should consider the Schwab 1000 Index ETF (SCHK), a passively managed exchange traded fund launched on 10/11/2017. The fund is sponsored by Charles Schwab. It has amassed assets over $2.93 billion, making it one of the larger ETFs attempting to match the Large Cap Blend segment of the US equity market. Why Large Cap Blend Large cap companies usually have a market capitalization above $10 billion. They tend to be stable companies with predictable cash flows and are usually less volatile than mid and small cap companies. Blend ETFs usually hold a mix of growth and value stocks as well as stocks that exhibit both value and growth characteristics. Costs Cost is an important factor in selecting the right ETF, and cheaper funds can significantly outperform their more expensive counterparts if all other fundamentals are the same. Annual operating expenses for this ETF are 0.05%, making it one of the least expensive products in the space. It has a 12-month trailing dividend yield of 1.41%. Sector Exposure and Top Holdings It is important to delve into an ETF's holdings before investing despite the many upsides to these kinds of funds like diversified exposure, which minimizes single stock risk. And, most ETFs are very transparent products that disclose their holdings on a daily basis. This ETF has heaviest allocation to the Information Technology sector--about 27.40% of the portfolio. Healthcare and Financials round out the top three. Looking at individual holdings, Apple Inc (AAPL) accounts for about 6.76% of total assets, followed by Microsoft Corp (MSFT) and Amazon Com Inc (AMZN). The top 10 holdings account for about 27.26% of total assets under management. Performance and Risk SCHK seeks to match the performance of the Schwab 1000 Index before fees and expenses. The Schwab 1000 Index is a float-adjusted market capitalization weighted index that includes the 1,000 largest stocks of publicly traded companies in the United States, with size being determined by market capitalization. The index is designed to be a measure of the performance of large- and mid-cap U.S. stocks. The ETF has gained about 18.11% so far this year and is up roughly 12.56% in the last one year (as of 08/30/2023). In the past 52-week period, it has traded between $34.56 and $44.27. The ETF has a beta of 1.02 and standard deviation of 18.60% for the trailing three-year period. With about 988 holdings, it effectively diversifies company-specific risk. Alternatives Schwab 1000 Index ETF carries a Zacks ETF Rank of 3 (Hold), which is based on expected asset class return, expense ratio, and momentum, among other factors. Thus, SCHK is a good option for those seeking exposure to the Style Box - Large Cap Blend area of the market. Investors might also want to consider some other ETF options in the space. The iShares Core S&P 500 ETF (IVV\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VEA. Express as a decimal (e.g., -0.02).", "answer": "-0.0141", "answer_numeric": -0.014143, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0141 (i.e., on a bad day with 5% probability, the loss exceeds 1.41%). CVaR(95%) = -0.0179.", "metadata": {"var": -0.014143, "cvar": -0.017872, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231212_0764", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-12-12", "context_summary": "EEM: 60-day return history, mean=0.0000, std=0.0092.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0000, std=0.0092, min=-0.0175, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-11] [\"Here\\u2019s What to Expect From Apple Stock in 2024 InvestorPlace - Stock Market News, Stock Advice & Trading Tips As a member of the \\u201cMagnificent Seven,\\u201d Apple (NASDAQ:AAPL) earned the market\\u2019s favor throughout 2023. However, this doesn\\u2019t guarantee similar results for Apple\\u2019s investors in 2024. Overall, the outlook for AAPL stock is good and we\\u2019re assigning it a \\u201cB\\u201d grade, but there\\u2019s no urgency to buy it now if you don\\u2019t want to. It\\u2019s amazing to consider how quickly Apple\\u2019s market capitalization swelled from $2 trillion to $3 trillion. Getting Apple\\u2019s market cap to $4 trillion might not be so quick or easy. Ultimately, Apple\\u2019s shareholders should expect decent returns over the long run, but also need to acknowledge Apple\\u2019s challenges in the coming year. Apple\\u2019s Shift Away From China Relations between the U.S. and China were strained in 2023, and the situation might not get any better next year. This is relevant, as China has banned government officials from using Apple\\u2019s iPhones at work. Plus, the U.S. government has limited the exports of certain technology components to China. Amid this tense backdrop, Apple is taking actions to shift its operations away from China. In particular, the company has its eye on India as a major source of components. According to The Wall Street Journal, Apple \\u201cand its suppliers aim to build over 50 million iPhones in India annually within the next two to three years,\\u201d followed by an \\u201cadditional tens of millions of units after that.\\u201d Furthermore, Apple is in the process of moving its iPad product-development operations from China to Vietnam. This may be a savvy move for Apple, especially if Sino-U.S. relations deteriorate during the coming quarters. Going forward, investors should keep tabs on Apple\\u2019s production costs to see if the company\\u2019s operational shifts have a positive long-term impact on Apple\\u2019s financials. Serious Concerns for AAPL Stock Investors There\\u2019s no denying that AAPL stock ran fast in 2023. Do Apple\\u2019s fundamentals justify the share-price move, though? It\\u2019s a question that one particular analysts wants investors to consider. Barclays Senior Analyst Tim Long said that he struggles with Apple\\u2019s \\u201cmultiple and valuation.\\u201d Not long ago, Apple\\u2019s trailing 12-month price-to-earnings ratio was above 31x, versus Apple\\u2019s five-year average P/E ratio of 26.42x. Long observed that Apple\\u2019s near-term forecasts aren\\u2019t highly optimistic. \\u201cThey\\u2019ve basically lowered guidance maybe four quarters in a row. They don\\u2019t give official guidance, but numbers have come down for four quarters in a row,\\u201d Long stated. Along with that, Long sees soft demand for Apple\\u2019s products, and especially the iPhone, in China. Notably, Apple\\u2019s revenue from China fell 2.5% year over year in the company\\u2019s most recently reported quarter. Be \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0134", "answer_numeric": -0.013374, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0134 (i.e., on a bad day with 5% probability, the loss exceeds 1.34%). CVaR(95%) = -0.0157.", "metadata": {"var": -0.013374, "cvar": -0.015678, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230222_0766", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-02-22", "context_summary": "QUAL: 60-day return history, mean=0.0001, std=0.0122.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0001, std=0.0122, min=-0.0262, max=0.0266\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K KO 2023-02-21] ko-20221231 0000021344 2022 FY False http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#OtherNonoperatingIncomeExpense http://fasb.org/us-gaap/2022#OtherNonoperatingIncomeExpense http://fasb.org/us-gaap/2022#CostOfGoodsAndServicesSold http://fasb.org/us-gaap/2022#CostOfGoodsAndServicesSold http://fasb.org/us-gaap/2022#CostOfGoodsAndServicesSold http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#InterestExpense http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#AccountsPayableAndAccruedLiabilitiesCurrent http://fasb.org/us-gaap/2022#AccountsPayableAndAccruedLiabilitiesCurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2022#OtherAssetsNoncurrent http://fasb.org/us-gaap/2022#OtherLiabilitiesNoncurrent 0000021344 2022-01-01 2022-12-31 0000021344 ko:CommonStock0.25ParValueMember 2022-01-01 2022-12-31 0000021344 ko:A0.500NotesDue2024Member 2022-01-01 2022-12-31 0000021344 ko:A1.875NotesDue2026Member 2022-01-01 2022-12-31 0000021344 ko:A0.750NotesDue2026Member 2022-01-01 2022-12-31 0000021344 ko:A1.125NotesDue2027Member 2022-01-01 2022-12-31 0000021344 ko:A0125NotesDue2029KO29AMember 2022-01-01 2022-12-31 0000021344 ko:A0125NotesDue2029KO29BMember 2022-01-01 2022-12-31 0000021344 ko:A0400NotesDue2030Member 2022-01-01 2022-12-31 0000021344 ko:A1.250NotesDue2031Member 2022-01-01 2022-12-31 0000021344 ko:A0375NotesDue2033Member 2022-01-01 2022-12-31 0000021344 ko:A0500NotesDue2033Member 2022-01-01 2022-12-31 0000021344 ko:A1.625NotesDue2035Member 2022-01-01 2022-12-31 0000021344 ko:A1.100NotesDue2036Member 2022-01-01 2022-12-31 0000021344 ko:A0950NotesDue2036Member 2022-01-01 2022-12-31 0000021344 ko:A0800NotesDue2040Member 2022-01-01 2022-12-31 0000021344 ko:A1000NotesDue2041Member 2022-01-01 2022-12-31 0000021344 2022-07-01 iso4217:USD 0000021344 2023-02-17 xbrli:shares 0000021344 ko:TaxYears20072009Member 2015-12-31 0000021344 ko:TaxYears20072009Member 2018-01-01 2018-03-30 0000021344 2020-12-31 0000021344 2022-12-31 xbrli:pure 0000021344 2021-01-01 2021-12-31 0000021344 2020-01-01 2020-12-31 iso4217:USD xbrli:shares 0000021344 2021-12-31 0000021344 2019-12-31 0000021344 us-gaap:CommonStockMember 2021-12-31 0000021344 us-gaap:CommonStockMember 2020-12-31 0000021344 us-gaap:CommonStockMember 2019-12-31 0000021344 us-gaap:CommonStockMember 2022-01-01 2022-12-31 0000021344 us-gaap:CommonStockMember 2021-01-01 2021-12-31 0000021344 us-gaap:CommonStockMember 2020-01-01 2020-12-31 0000021344 us-gaap:CommonStockMember 2022-12-31 0000021344 us-gaap:AdditionalPaidInCapitalMember 2021-12-31 0000021344 us-gaap:AdditionalPaidInCapitalMember 2020-12-31 0000021344 us-gaap:AdditionalPaidInCapitalMember 2019-12-31 0000021344 us-gaap:AdditionalPaidInCapitalMember 2022-01-01 2022-12-31 0000021344 us-gaap:AdditionalPaidInCapitalMember 2021-01-01 2021-12-31 0000021344 us-gaap:AdditionalPaidInCapitalMember 2020-01-01 2020-12-31 0000021344 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000021344 us-gaap:RetainedEarningsMember 2021-12-31 0000021344 us-gaap:RetainedEarningsMember 2020-12-31 0000021344 us-gaap:RetainedEarningsMember 2019-12-31 0000021344 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2022-12-31 0000021344 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2021-12-31 0000021344 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2020-12-31 0000021344 us-gaap:RetainedEarningsMember 2022-01-01 2022-12-31 0000021344 us-gaap:RetainedEarningsMember 2021-01-01 2021-12-31 0000021344 us-gaap:RetainedEarningsMember 2020-01-01 2020-12-31 0000021344 us-gaap:RetainedEarningsMember 2022-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-01-01 2022-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-01-01 2021-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-01-01 2020-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-12-31 0000021344 us-gaap:TreasuryStockMember 2021-12-31 0000021344 us-gaap:TreasuryStockMember 2020-12-31 0000021344 us-gaap:TreasuryStockMember 2019-12-31 0000021344 us-gaap:TreasuryStockMember 2022-01-01 2022-12-31 0000021344 us-gaap:TreasuryStockMember 2021-01-01 2021-12-31 0000021344 us-gaap:TreasuryStockMember 2020-01-01 2020-12-31 0000021344 us-gaap:TreasuryStockMember 2022-12-31 0000021344 us-gaap:ParentMember 2022-12-31 0000021344 us-gaap:ParentMember 2021-12-31 0000021344 us-gaap:ParentMember 2020-12-31 0000021344 us-gaap:NoncontrollingInterestMember 2021-12-31 0000021344 us-gaap:NoncontrollingInterestMember 2020-12-31 0000021344 us-gaap:NoncontrollingInterestMember 2019-12-31 0000021344 us-gaap:NoncontrollingInterestMember 2022-01-01 2022-12-31 0000021344 us-gaap:NoncontrollingInterestMember 2021-01-01 2021-12-31 0000021344 us-gaap:NoncontrollingInterestMember 2020-01-01 2020-12-31 0000021344 us-gaap:NoncontrollingInterestMember 2022-12-31 0000021344 us-gaap:VariableInterestEntityNotPrimaryBeneficiaryMember 2022-12-31 0000021344 us-gaap:VariableInterestEntityN [...TRUNCATED...] er of The Coca-Cola Company, and by John Murphy, Pr esident and Chief Financial Officer of The Coca-Cola Company. 101 The following financial information from The Coca-Cola Company’s Annual Report on Form 10-K for the year ended December 31, 2022, formatted in iXBRL (Inline Extensible Business Reporting Language): (i) Consolidated Statements of Income for the years ended December 31, 2022, 2021 and 2020; (ii) Consolidated Statements of Comprehensive Income for the years ended December 31, 2022, 2021 and 2020; (iii) Consolidated Balance Sheets as of December 31, 2022 and 2021; (iv) Consolidated Statements of Cash Flows for the years ended December 31, 2022, 2021 and 2020; (v) Consolidated Statements of Shareowners’ Equity for the years ended December 31, 2022, 2021 and 2020; and (vi) Notes to Consolidated Financial Statements. 104 Cover Page Interactive Data File (the cover page XBRL tags are embedded within the iXBRL document). *Management contracts and compensatory plans and arrangements required to be filed as exhibits pursuant to Item 15(b) of Form 10-K. ITEM 16.  FORM 10-K SUMMARY None. 139 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   THE COCA-COLA COMPANY   (Registrant) By: /s/ JAMES QUINCEY   James R. Quincey Chairman of the Board of Directors and Chief Executive Officer     Date: February 21, 2023 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated. /s/ JAMES QUINCEY   /s/ JOHN MURPHY James R. Quincey Chairman of the Board of Directors and Chief Executive Officer (Principal Executive Officer)   John Murphy President and Chief Financial Officer (Principal Financial Officer) February 21, 2023   February 21, 2023 /s/ KATHY LOVELESS   /s/ MARK RANDAZZA Kathy Loveless Vice President and Controller (On behalf of the Registrant) Mark Randazza Vice President, Assistant Controller and Chief Accounting Officer (Principal Accounting Officer) February 21, 2023 February 21, 2023 * * Herb Allen Director   Christopher C. Davis Director February 21, 2023   February 21, 2023 *   * Marc Bolland Director   Barry Diller Director February 21, 2023   February 21, 2023 *   * Ana Botín Director   Carolyn Everson Director February 21, 2023   February 21, 2023 140 * * Helene D. Gayle Director Caroline J. Tsay Director February 21, 2023 February 21, 2023 * Alexis M. Herman Director David B. Weinberg Director February 21, 2023 February 21, 2023 *   Maria Elena Lagomasino Director February 21, 2023 *By: /s/ JENNIFER MANNING Jennifer Manning Attorney-in-fact   February 21, 2023 141\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0164", "answer_numeric": -0.016419, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0164 (i.e., on a bad day with 5% probability, the loss exceeds 1.64%). CVaR(95%) = -0.0215.", "metadata": {"var": -0.016419, "cvar": -0.021507, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20241107_0768", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PPLT"], "decision_date": "2024-11-07", "context_summary": "PPLT: 60-day return history, mean=0.0002, std=0.0155.", "question": "Asset: PPLT\nDaily returns (past 60 days): mean=0.0002, std=0.0155, min=-0.0337, max=0.0322\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for PPLT. Express as a decimal (e.g., -0.02).", "answer": "-0.0222", "answer_numeric": -0.022237, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0222 (i.e., on a bad day with 5% probability, the loss exceeds 2.22%). CVaR(95%) = -0.0276.", "metadata": {"var": -0.022237, "cvar": -0.027593, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231211_0770", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-12-11", "context_summary": "XLB: 60-day return history, mean=-0.0001, std=0.0105.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0001, std=0.0105, min=-0.0262, max=0.0291\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-08] [\"American Micro Devices Stock Spikes Thanks to Artificial Intelligence (AI), Yet There's More to the Story In today's video, I discuss recent AI updates affecting Advanced Micro Devices (NASDAQ: AMD). Check out the short video to learn more, consider subscribing, and click the special offer link below. *Stock prices used were the market prices of Dec. 7, 2023. The video was published on Dec. 7, 2023. Should you invest $1,000 in Advanced Micro Devices right now? Before you buy stock in Advanced Micro Devices, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now... and Advanced Micro Devices wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Stock Advisor provides investors with an easy-to-follow blueprint for success, including guidance on building a portfolio, regular updates from analysts, and two new stock picks each month. The Stock Advisor service has nearly quadrupled the return of S&P 500 since 2002*. See the 10 stocks *Stock Advisor returns as of December 7, 2023 Jose Najarro has positions in Advanced Micro Devices, Nvidia, and Qualcomm. The Motley Fool has positions in and recommends Advanced Micro Devices, Apple, Nvidia, and Qualcomm. The Motley Fool recommends Intel and recommends the following options: long January 2023 $57.50 calls on Intel, long January 2025 $45 calls on Intel, and short February 2024 $47 calls on Intel. The Motley Fool has a disclosure policy. Jose Najarro is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple (AAPL) Rises Higher Than Market: Key Facts Apple (AAPL) closed the latest trading day at $195.71, indicating a +0.74% change from the previous session's end. The stock exceeded the S&P 500, which registered a gain of 0.41% for the day. Meanwhile, the Dow experienced a rise of 0.36%, and the technology-dominated Nasdaq saw an increase of 0.45%. Shares of the maker of iPhones, iPads and other products have appreciated by 6.5% over the course of the past month, outperforming the Computer and Technology sector's gain of 5.9% and the S&P 500's gain of 4.91%. Market participants will be closely following the financial results of Apple in its upcoming release. It is anticipated that the company will report an EPS of $2.08, marking a 10.64% rise compared to the same quarter of the previous year. Meanwhile, the latest consensus estimate predicts the revenue to be $117.31 billion, indicating a 0.13% increase compared to the same quarter of the previous year. For the full year, the Zacks Consensus Estimates are projecting earnings of $6.5\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLB. Express as a decimal (e.g., -0.02).", "answer": "-0.0153", "answer_numeric": -0.015256, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0153 (i.e., on a bad day with 5% probability, the loss exceeds 1.53%). CVaR(95%) = -0.0220.", "metadata": {"var": -0.015256, "cvar": -0.022043, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20241213_0772", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-12-13", "context_summary": "AVAX-USD: 60-day return history, mean=0.0116, std=0.0576.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0116, std=0.0576, min=-0.1614, max=0.2028\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0485", "answer_numeric": -0.048471, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0485 (i.e., on a bad day with 5% probability, the loss exceeds 4.85%). CVaR(95%) = -0.0977.", "metadata": {"var": -0.048471, "cvar": -0.097741, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230307_0774", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-03-07", "context_summary": "CSHI: 60-day return history, mean=0.0003, std=0.0007.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0003, std=0.0007, min=-0.0010, max=0.0026\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0007", "answer_numeric": -0.000664, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0007 (i.e., on a bad day with 5% probability, the loss exceeds 0.07%). CVaR(95%) = -0.0009.", "metadata": {"var": -0.000664, "cvar": -0.000864, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230201_0776", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-02-01", "context_summary": "MATIC-USD: 60-day return history, mean=0.0033, std=0.0358.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0033, std=0.0358, min=-0.0936, max=0.1295\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-31] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0508", "answer_numeric": -0.050763, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0508 (i.e., on a bad day with 5% probability, the loss exceeds 5.08%). CVaR(95%) = -0.0756.", "metadata": {"var": -0.050763, "cvar": -0.07556, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230620_0778", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-06-20", "context_summary": "XRP-USD: 60-day return history, mean=0.0010, std=0.0258.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0258, min=-0.0767, max=0.0562\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0479", "answer_numeric": -0.047926, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0479 (i.e., on a bad day with 5% probability, the loss exceeds 4.79%). CVaR(95%) = -0.0618.", "metadata": {"var": -0.047926, "cvar": -0.06184, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240319_0780", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-03-19", "context_summary": "ADA-USD: 60-day return history, mean=0.0053, std=0.0375.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0375, min=-0.1009, max=0.0968\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0386", "answer_numeric": -0.038644, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0386 (i.e., on a bad day with 5% probability, the loss exceeds 3.86%). CVaR(95%) = -0.0806.", "metadata": {"var": -0.038644, "cvar": -0.080626, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230623_0782", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-06-23", "context_summary": "XLU: 60-day return history, mean=0.0002, std=0.0087.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0002, std=0.0087, min=-0.0237, max=0.0256\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-22] [\"After Hours Most Active for Jun 22, 2023 : BTE, PLTR, ABR, AAPL, STKL, AMZN, KDP, IGIB, IQ, KO, SU, T The NASDAQ 100 After Hours Indicator is up 11.63 to 15,053.95. The total After hours volume is currently 81,431,725 shares traded. The following are the most active stocks for the after hours session: Baytex Energy Corp (BTE) is unchanged at $3.02, with 19,760,377 shares traded., following a 52-week high recorded in today's regular session. Palantir Technologies Inc. (PLTR) is -0.09 at $13.96, with 16,613,117 shares traded. PLTR's current last sale is 174.5% of the target price of $8. Arbor Realty Trust (ABR) is -0.02 at $14.06, with 8,556,060 shares traded. As reported by Zacks, the current mean recommendation for ABR is in the \\\"buy range\\\". Apple Inc. (AAPL) is +0.11 at $187.11, with 3,168,168 shares traded., following a 52-week high recorded in today's regular session. SunOpta, Inc. (STKL) is +0.1 at $6.95, with 2,583,726 shares traded. As reported in the last short interest update the days to cover for STKL is 7.427717; this calculation is based on the average trading volume of the stock. Amazon.com, Inc. (AMZN) is +0.24 at $130.39, with 2,345,481 shares traded. As reported by Zacks, the current mean recommendation for AMZN is in the \\\"buy range\\\". Keurig Dr Pepper Inc. (KDP) is unchanged at $31.92, with 2,158,387 shares traded. KDP's current last sale is 81.85% of the target price of $39. iShares 5-10 Year Investment Grade Corporate Bond ETF (IGIB) is +0.0074 at $50.39, with 1,646,206 shares traded. This represents a 7.64% increase from its 52 Week Low. iQIYI, Inc. (IQ) is +0.04 at $5.17, with 1,552,708 shares traded. As reported by Zacks, the current mean recommendation for IQ is in the \\\"buy range\\\". Coca-Cola Company (The) (KO) is -0.05 at $61.80, with 1,549,093 shares traded. As reported by Zacks, the current mean recommendation for KO is in the \\\"buy range\\\". Suncor Energy Inc. (SU) is unchanged at $28.81, with 1,319,952 shares traded. SU's current last sale is 73.87% of the target price of $39. AT&T Inc. (T) is unchanged at $15.58, with 1,268,446 shares traded. As reported by Zacks, the current mean recommendation for T is in the \\\"buy range\\\". The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-Wall Street ends higher as Powell wraps up testimony By Stephen Culp June 22 (Reuters) - The S&P 500 and the Nasdaq closed higher on Thursday as U.S. Federal Reserve Chairman Jerome Powell continued to beat a hawkish drum and suggested the central bank has not reached the end of its tightening cycle, but provided reassurance that the Fed would proceed with caution. The tech-heavy Nasdaq's robust gain got a boost from momentum stocks led by Amazon.com AMZN.O Apple Inc AAPL.O, and Microsoft Corp MSFT.O, while the S&P 500's advance was more modest. Industrials .SPLRCI and financials .SPSY held the blue-chip Dow essentially flat. \\\"Investors are playin\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0127", "answer_numeric": -0.012726, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0127 (i.e., on a bad day with 5% probability, the loss exceeds 1.27%). CVaR(95%) = -0.0199.", "metadata": {"var": -0.012726, "cvar": -0.019892, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230419_0783", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2023-04-19", "context_summary": "ACWI: 60-day return history, mean=0.0005, std=0.0087.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0005, std=0.0087, min=-0.0172, max=0.0161\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-18] [\"Apple CEO Tim Cook Opens First Store In India (RTTNews) - Apple Inc. Chief Executive Officer Tim Cook has inaugurated the tech major's first retail store in India, which is being considered as its new manufacturing base as well as new growth market. The first store, called Apple BKC, is located in the country's financial capital Mumbai. On Thursday, the company will open its second store in India, Apple Saket, in the capital of Delhi. The launch comes as Apple is aiming to boost sales, manufacturing and exports of Apple products including iPhones in India. Apple BKC is located inside the Jio World Drive mall at Bandra Kurla Complex or BKC in Mumbai. According to the company, Apple BKC is one of the most energy-efficient Apple Store locations in the world, operationally carbon neutral, running on 100 percent renewable energy. Prior to the inauguration, Cook tweeted a photo of himself and Apple BKC staff. Apple BKC will offer a special Today at Apple series, \\\"Mumbai Rising,\\\" running from the store's opening day through the summer. These free sessions featuring Apple products and services are expected to bring visitors, local artists, and creatives together. The iPhone maker, which views India as a key market, has been present in the country for more than 25 years. Cook in an earlier statement said, \\\"India has such a beautiful culture and an incredible energy, and we're excited to build on our long-standing history.\\\" Apple, which assembles most of its iPhones in China, last year announced plans to shift some production of its flagship smartphone iPhone 14 from China to India amid continuing tensions between the US and China, along with the then prevailed COVID-19 issues. Foxconn, Apple's key iPhone assembler, already manufactures iPhones at its Sriperumbudur factory on the outskirts of Chennai, India. In March, Bloomberg reported that Foxconn plans to invest $700 million to set up a new iPhone plant in India's Karnataka state, which would create 100,000 jobs. Foxconn will build a new 300-acre facility in Bengaluru as part of its ongoing effort to pivot away from China. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"3 Things About Shopify That Smart Investors Know Shopify (NYSE: SHOP) has taken investors on a wild ride since its initial public offering (IPO). The e-commerce services provider went public at a split-adjusted price of $1.70 per share on May 21, 2015; skyrocketed to an all-time high of $169.06 on Nov. 19, 2021, at the peak of the buying frenzy in growth stocks, but now trades at about $46. A $1,000 investment in its IPO would have grown to nearly $100,000 before shrinking back to about $27,000 today. Nevertheless, a 27-bagger gain in just under eight years still easily beats the S&P 500's gain of 94% during the same period. Image source: Getty Images. Shopify's stock initially caught fire because investors were impressed by its ability to disr\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ACWI. Express as a decimal (e.g., -0.02).", "answer": "-0.0140", "answer_numeric": -0.014048, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0140 (i.e., on a bad day with 5% probability, the loss exceeds 1.40%). CVaR(95%) = -0.0164.", "metadata": {"var": -0.014048, "cvar": -0.016439, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240924_0785", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-09-24", "context_summary": "ETH-USD: 60-day return history, mean=-0.0023, std=0.0385.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0023, std=0.0385, min=-0.1002, max=0.1484\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0677", "answer_numeric": -0.067697, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0677 (i.e., on a bad day with 5% probability, the loss exceeds 6.77%). CVaR(95%) = -0.0860.", "metadata": {"var": -0.067697, "cvar": -0.085988, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240123_0787", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-01-23", "context_summary": "ADA-USD: 60-day return history, mean=0.0048, std=0.0521.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0048, std=0.0521, min=-0.0799, max=0.1961\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0601", "answer_numeric": -0.060131, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0601 (i.e., on a bad day with 5% probability, the loss exceeds 6.01%). CVaR(95%) = -0.0726.", "metadata": {"var": -0.060131, "cvar": -0.072619, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230406_0789", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-04-06", "context_summary": "ETH-USD: 60-day return history, mean=0.0027, std=0.0301.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0027, std=0.0301, min=-0.0632, max=0.0751\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-05] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0387", "answer_numeric": -0.038675, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0387 (i.e., on a bad day with 5% probability, the loss exceeds 3.87%). CVaR(95%) = -0.0576.", "metadata": {"var": -0.038675, "cvar": -0.057606, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240621_0791", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-06-21", "context_summary": "BTC-USD: 60-day return history, mean=0.0003, std=0.0239.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0003, std=0.0239, min=-0.0502, max=0.0780\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0323", "answer_numeric": -0.032266, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0323 (i.e., on a bad day with 5% probability, the loss exceeds 3.23%). CVaR(95%) = -0.0418.", "metadata": {"var": -0.032266, "cvar": -0.041763, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240530_0792", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2024-05-30", "context_summary": "VTI: 60-day return history, mean=0.0004, std=0.0073.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0004, std=0.0073, min=-0.0166, max=0.0122\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VTI. Express as a decimal (e.g., -0.02).", "answer": "-0.0121", "answer_numeric": -0.012078, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0121 (i.e., on a bad day with 5% probability, the loss exceeds 1.21%). CVaR(95%) = -0.0145.", "metadata": {"var": -0.012078, "cvar": -0.014494, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230814_0793", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-08-14", "context_summary": "ETH-USD: 60-day return history, mean=0.0020, std=0.0181.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0020, std=0.0181, min=-0.0335, max=0.0718\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-13] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0222", "answer_numeric": -0.022152, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0222 (i.e., on a bad day with 5% probability, the loss exceeds 2.22%). CVaR(95%) = -0.0329.", "metadata": {"var": -0.022152, "cvar": -0.032855, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230824_0795", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-08-24", "context_summary": "XLE: 60-day return history, mean=0.0019, std=0.0122.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0019, std=0.0122, min=-0.0268, max=0.0300\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-23] [\"Netflix (NFLX) Expands Footprint in India With New Partnership Netflix NFLX is expanding its footprint in India through a recently inked creative partnership with acclaimed director Neeraj Pandey\\u2019s Friday Storytellers LLP, the digital content production arm of Friday Filmworks. Netflix and Neeraj Pandey have already collaborated for Khakee: The Bihar Chapter, a cop-thriller that was one of India\\u2019s Top ten TV shows for more than five months and became one of the longest trending shows on Netflix in India. Khakee\\u2019s second season will be the first series to be released through the latest collaboration. Netflix\\u2019s focus on developing regional content has been a key catalyst in attracting new subscribers. In terms of Indian audience, apart from Khakee: The Bihar Chapter, it has released a plethora of new shows including Guns & Gulaabs, The Hunt for Veerappan, Choona, Kohrra, Lust Stories 2, Scoop, Rana Naidu, Class, Mission Majnu and more. Moreover, Friday Night Plan, starring Babil Khan and Amrith Jayan, is set to release on Sep 1. It also announced the release of the mystery thriller, Do Patti, starring Kajol and Kriti Sanon in lead roles. Globally, Netflix has been focused on expanding its original content portfolio, with a range of foreign-language content like Cigarette Girl (Indonesian), Baby Fever (Danish), King the Land (Korean), Sleeping Dog (German) and The Surrogacy (Mexican). Netflix recently announced its first Korean-language animated film Lost in Starlight, in which popular K-drama stars Kim Tae-ri and Hong Kyung will lend their voices to the roles of astronaut Nan-young and musician Jay. Netflix, Inc. Price and Consensus Netflix, Inc. price-consensus-chart | Netflix, Inc. Quote The company is benefiting from strong viewership of foreign language-based films and shows amid stiff competition from its peers like Apple AAPL, Disney DIS and Amazon AMZN. In the second quarter of 2023, Netflix gained 5.89 million paid subscribers globally, thanks to a crackdown on password-sharing and the introduction of paid sharing in more than 100 countries in May. Netflix\\u2019s 2023 Prospects Remain Bright Netflix\\u2019s shares have risen 40.1% year to date, outperforming the Zacks Consumer Discretionary sector\\u2019s return of 9.3%. It also outperformed Apple and Disney but underperformed Amazon. Shares of Apple and Amazon have returned 36.4% and 59.8%, respectively, on a year-to-date basis. Disney shares have declined 1.3%. Netflix, which currently has a Zacks Rank #3 (Hold), is expected to benefit from its diversified content portfolio, which is attributable to heavy investments in the production and distribution of localized, foreign-language content. You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. Netflix now expects revenue growth to accelerate in the second half of 2023, driven by the launch of paid sharing. However, it anticipates foreign-exchange neutral average revenues per membership t\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLE. Express as a decimal (e.g., -0.02).", "answer": "-0.0211", "answer_numeric": -0.021078, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0211 (i.e., on a bad day with 5% probability, the loss exceeds 2.11%). CVaR(95%) = -0.0241.", "metadata": {"var": -0.021078, "cvar": -0.024053, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230324_0797", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-03-24", "context_summary": "BNB-USD: 60-day return history, mean=0.0018, std=0.0266.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0018, std=0.0266, min=-0.0674, max=0.0740\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-23] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0392", "answer_numeric": -0.039159, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0392 (i.e., on a bad day with 5% probability, the loss exceeds 3.92%). CVaR(95%) = -0.0555.", "metadata": {"var": -0.039159, "cvar": -0.055482, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240318_0799", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-03-18", "context_summary": "SGOV: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=0.0000, max=0.0006\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = 0.0000.", "metadata": {"var": 0.0, "cvar": 0.0, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240520_0801", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["FXI"], "decision_date": "2024-05-20", "context_summary": "FXI: 60-day return history, mean=0.0032, std=0.0153.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0032, std=0.0153, min=-0.0360, max=0.0476\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for FXI. Express as a decimal (e.g., -0.02).", "answer": "-0.0225", "answer_numeric": -0.022488, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0225 (i.e., on a bad day with 5% probability, the loss exceeds 2.25%). CVaR(95%) = -0.0318.", "metadata": {"var": -0.022488, "cvar": -0.031824, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230111_0803", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-01-11", "context_summary": "LINK-USD: 60-day return history, mean=-0.0016, std=0.0333.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0016, std=0.0333, min=-0.1071, max=0.0901\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-10] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0495", "answer_numeric": -0.049457, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0495 (i.e., on a bad day with 5% probability, the loss exceeds 4.95%). CVaR(95%) = -0.0847.", "metadata": {"var": -0.049457, "cvar": -0.084683, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241113_0805", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-11-13", "context_summary": "ADA-USD: 60-day return history, mean=0.0088, std=0.0464.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0088, std=0.0464, min=-0.0650, max=0.1957\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0559", "answer_numeric": -0.055943, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0559 (i.e., on a bad day with 5% probability, the loss exceeds 5.59%). CVaR(95%) = -0.0632.", "metadata": {"var": -0.055943, "cvar": -0.063182, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240716_0807", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["PALL"], "decision_date": "2024-07-16", "context_summary": "PALL: 60-day return history, mean=-0.0015, std=0.0207.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=-0.0015, std=0.0207, min=-0.0384, max=0.0413\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for PALL. Express as a decimal (e.g., -0.02).", "answer": "-0.0321", "answer_numeric": -0.032141, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0321 (i.e., on a bad day with 5% probability, the loss exceeds 3.21%). CVaR(95%) = -0.0368.", "metadata": {"var": -0.032141, "cvar": -0.036782, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241104_0809", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-11-04", "context_summary": "BNB-USD: 60-day return history, mean=0.0018, std=0.0199.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0018, std=0.0199, min=-0.0489, max=0.0360\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0335", "answer_numeric": -0.033518, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0335 (i.e., on a bad day with 5% probability, the loss exceeds 3.35%). CVaR(95%) = -0.0397.", "metadata": {"var": -0.033518, "cvar": -0.039744, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230524_0811", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-05-24", "context_summary": "CSHI: 60-day return history, mean=0.0003, std=0.0008.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0003, std=0.0008, min=-0.0018, max=0.0025\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0010", "answer_numeric": -0.000998, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0010 (i.e., on a bad day with 5% probability, the loss exceeds 0.10%). 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in July 2010, which initially authorized the repurchase of 5.1 million shares with no stated expiration. In January 2023, the Company announced that the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 70   Item 5. Other Information O n May 13, 2024 , Mark Wiedman , Senior Managing Director , adopted a Rule 10b5-1 trading plan, intended to satisfy the affirmative defense of Rule 10b5-1(c), for the sale of up to 36,000 shares of BlackRock common stock. The plan's expiration date is April 30, 2025 . 71   Item 6. Exh ibits Exhibit No.   Description       10.1(1)       Amendment No. 15, dated as of May 31, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein       10.2(2)   BlackRock, Inc. Third Amended and Restated 1999 Stock Award and Incentive Plan+       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on May 31, 2024. (2) Incorporated by reference to BlackRock’s Definitive Proxy Statement on Form DEF 14A filed on April 4, 2024. + Denotes compensatory plans or arrangements. 72   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.     BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: August 6, 2024     Martin S. Small       Senior Managing Director & Chief Financial Officer (Principal Financial Officer)   73\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0159", "answer_numeric": -0.015852, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0159 (i.e., on a bad day with 5% probability, the loss exceeds 1.59%). CVaR(95%) = -0.0216.", "metadata": {"var": -0.015852, "cvar": -0.021616, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241018_0814", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-10-18", "context_summary": "XLB: 60-day return history, mean=0.0014, std=0.0093.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0014, std=0.0093, min=-0.0230, max=0.0205\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLB. Express as a decimal (e.g., -0.02).", "answer": "-0.0139", "answer_numeric": -0.013924, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0139 (i.e., on a bad day with 5% probability, the loss exceeds 1.39%). CVaR(95%) = -0.0215.", "metadata": {"var": -0.013924, "cvar": -0.021523, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240209_0816", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-02-09", "context_summary": "XLK: 60-day return history, mean=0.0023, std=0.0096.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0023, std=0.0096, min=-0.0265, max=0.0248\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization 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Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0124", "answer_numeric": -0.012401, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0124 (i.e., on a bad day with 5% probability, the loss exceeds 1.24%). CVaR(95%) = -0.0210.", "metadata": {"var": -0.012401, "cvar": -0.020994, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20240705_0818", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-07-05", "context_summary": "XRP-USD: 60-day return history, mean=-0.0031, std=0.0208.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0031, std=0.0208, min=-0.0711, max=0.0543\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0359", "answer_numeric": -0.035912, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0359 (i.e., on a bad day with 5% probability, the loss exceeds 3.59%). CVaR(95%) = -0.0504.", "metadata": {"var": -0.035912, "cvar": -0.050378, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240405_0820", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-04-05", "context_summary": "BTC-USD: 60-day return history, mean=0.0085, std=0.0345.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0085, std=0.0345, min=-0.0834, max=0.0969\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0590", "answer_numeric": -0.059018, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0590 (i.e., on a bad day with 5% probability, the loss exceeds 5.90%). CVaR(95%) = -0.0703.", "metadata": {"var": -0.059018, "cvar": -0.070255, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240719_0822", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2024-07-19", "context_summary": "SOYB: 60-day return history, mean=-0.0014, std=0.0096.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=-0.0014, std=0.0096, min=-0.0263, max=0.0206\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOYB. Express as a decimal (e.g., -0.02).", "answer": "-0.0165", "answer_numeric": -0.01651, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0165 (i.e., on a bad day with 5% probability, the loss exceeds 1.65%). CVaR(95%) = -0.0218.", "metadata": {"var": -0.01651, "cvar": -0.021846, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230105_0824", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-01-05", "context_summary": "DOT-USD: 60-day return history, mean=-0.0062, std=0.0372.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0062, std=0.0372, min=-0.1400, max=0.1009\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-04] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0583", "answer_numeric": -0.058316, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0583 (i.e., on a bad day with 5% probability, the loss exceeds 5.83%). CVaR(95%) = -0.1218.", "metadata": {"var": -0.058316, "cvar": -0.121781, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230628_0825", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CORN"], "decision_date": "2023-06-28", "context_summary": "CORN: 60-day return history, mean=0.0009, std=0.0166.", "question": "Asset: CORN\nDaily returns (past 60 days): mean=0.0009, std=0.0166, min=-0.0326, max=0.0336\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CORN. Express as a decimal (e.g., -0.02).", "answer": "-0.0203", "answer_numeric": -0.020271, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0203 (i.e., on a bad day with 5% probability, the loss exceeds 2.03%). CVaR(95%) = -0.0306.", "metadata": {"var": -0.020271, "cvar": -0.030589, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230421_0827", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2023-04-21", "context_summary": "DBB: 60-day return history, mean=-0.0018, std=0.0121.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=-0.0018, std=0.0121, min=-0.0266, max=0.0276\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DBB. Express as a decimal (e.g., -0.02).", "answer": "-0.0223", "answer_numeric": -0.022274, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0223 (i.e., on a bad day with 5% probability, the loss exceeds 2.23%). CVaR(95%) = -0.0248.", "metadata": {"var": -0.022274, "cvar": -0.02477, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231009_0829", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-10-09", "context_summary": "BTC-USD: 60-day return history, mean=-0.0008, std=0.0181.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0008, std=0.0181, min=-0.0710, max=0.0621\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-08] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0232", "answer_numeric": -0.023207, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0232 (i.e., on a bad day with 5% probability, the loss exceeds 2.32%). CVaR(95%) = -0.0490.", "metadata": {"var": -0.023207, "cvar": -0.048978, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231117_0830", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-11-17", "context_summary": "ADA-USD: 60-day return history, mean=0.0071, std=0.0248.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0071, std=0.0248, min=-0.0651, max=0.0621\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-16] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0249", "answer_numeric": -0.024903, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0249 (i.e., on a bad day with 5% probability, the loss exceeds 2.49%). CVaR(95%) = -0.0432.", "metadata": {"var": -0.024903, "cvar": -0.043166, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230404_0832", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-04-04", "context_summary": "LINK-USD: 60-day return history, mean=0.0010, std=0.0378.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0378, min=-0.0647, max=0.0909\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-03] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0547", "answer_numeric": -0.054687, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0547 (i.e., on a bad day with 5% probability, the loss exceeds 5.47%). CVaR(95%) = -0.0621.", "metadata": {"var": -0.054687, "cvar": -0.062052, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230607_0834", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-06-07", "context_summary": "DOT-USD: 60-day return history, mean=-0.0026, std=0.0237.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0026, std=0.0237, min=-0.0870, max=0.0354\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-06] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0427", "answer_numeric": -0.042691, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0427 (i.e., on a bad day with 5% probability, the loss exceeds 4.27%). CVaR(95%) = -0.0601.", "metadata": {"var": -0.042691, "cvar": -0.060106, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230707_0836", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-07-07", "context_summary": "XLB: 60-day return history, mean=0.0002, std=0.0107.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0002, std=0.0107, min=-0.0250, max=0.0327\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-06] [\"Wall St logs sharp losses as labor market strength stokes rate-hike fears By Lewis Krauskopf, Bansari Mayur Kamdar and Johann M Cherian July 6 (Reuters) - Wall Street's main indexes ended sharply lower on Thursday in a broad sell-off after data showing a strong labor market boosted bond yields and fanned fears the Federal Reserve will be aggressive in raising U.S. interest rates. The S&P 500 posted its biggest daily percentage drop since May 23. The Dow logged its biggest single-day fall since May 2. Private payrolls surged far more than expected in June, data showed, suggesting the labor market remained solid despite growing risks of a recession. A separate report showed U.S. job openings dropped in May, but remained at elevated levels. A day before the monthly U.S employment report, evidence of a solid labor market spurred expectations the Fed will keep interest rates higher for longer to tame stubborn inflation. \\u201cWe don\\u2019t see any softening in the labor market,\\u201d said Brad McMillan, chief investment officer for Commonwealth Financial Network. \\u201cThe Fed doesn\\u2019t have to worry about the jobs market. When you look at their mandate, they have no reason not to keep hiking and to keep hiking for a while.\\u201d The Dow Jones Industrial Average .DJI fell 366.38 points, or 1.07%, to 33,922.26, the S&P 500 .SPX lost 35.23 points, or 0.79%, to 4,411.59 and the Nasdaq Composite .IXIC dropped 112.61 points, or 0.82%, to 13,679.04. All 11 S&P 500 sectors ended down. Energy .SPNY led declines among the sectors, dropping about 2.5%, while consumer discretionary .SPLRCD slumped nearly 1.7%. Gains in megacap stocks mitigated declines for the major indexes, which ended above their session lows. Microsoft MSFT.O rose 0.9% while Apple AAPL.O was up 0.3%. Treasury yields jumped following the labor market data. The benchmark 10-year yield US10YT=RR burst above 4% while the two-year US2YT=RR Treasury yield, which typically moves in step with interest rate expectations, hit a 16-year high. U.S. interest rate futures saw an increased probability of another rate hike by the Federal Reserve in November, according to CME's FedWatch. The Fed did not hike rates in June but is widely expected to resume increases at its July meeting. Dallas Fed President Lorie Logan said there was a case for a rate rise at the June policy meeting. In company news, Exxon Mobil Corp XOM.N shares fell 3.7% after the oil major signaled a sharp fall in second-quarter operating profits on lower natural gas prices and weaker oil refining margins. Second-quarter corporate reports will arrive in coming weeks with S&P 500 earnings expected to fall 5.7% from a year-ago, according to Refinitiv data. \\u201cYou have a situation where rates are going higher, profits are not really moving,\\\" said King Lip, chief strategist at Baker Avenue Wealth Management. \\\"That\\u2019s usually not a good combination for stocks.\\u201d JetBlue AirwaysJBLU.O shares dropped 7.2% a day after the company s\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLB. Express as a decimal (e.g., -0.02).", "answer": "-0.0156", "answer_numeric": -0.015643, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0156 (i.e., on a bad day with 5% probability, the loss exceeds 1.56%). CVaR(95%) = -0.0212.", "metadata": {"var": -0.015643, "cvar": -0.021166, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240507_0838", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-05-07", "context_summary": "SGOV: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=0.0000, max=0.0005\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "0.0001", "answer_numeric": 9.9e-05, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0001 (i.e., on a bad day with 5% probability, the loss exceeds 0.01%). CVaR(95%) = 0.0000.", "metadata": {"var": 9.9e-05, "cvar": 3.3e-05, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241030_0840", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-30", "context_summary": "SPY: 60-day return history, mean=0.0020, std=0.0076.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0020, std=0.0076, min=-0.0208, max=0.0208\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q KO 2024-10-24] ko-20240927 false 12/31 Q3 2024 0000021344 http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent 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ko:FinishedProductOperationsMember 2024-06-29 2024-09-27 0000021344 ko:FinishedProductOperationsMember 2024-06-29 2024-09-27 0000021344 country:US 2024-06-29 2024-09-27 0000021344 ko:InternationalMember 2024-06-29 2024-09-27 0000021344 country:US ko:ConcentrateOperationsMember 2023-07-01 2023-09-29 0000021344 ko:InternationalMember ko:ConcentrateOperationsMember 2023-07-01 2023-09-29 0000021344 ko:ConcentrateOperationsMember 2023-07-01 2023-09-29 0000021344 country:US ko:FinishedProductOperationsMember 2023-07-01 2023-09-29 0000021344 ko:InternationalMember ko:FinishedProductOperationsMember 2023-07-01 2023-09-29 0000021344 ko:FinishedProductOperationsMember 2 [...TRUNCATED...] among Coca-Cola Refreshments USA, Inc., the Company and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on June 2 3, 2017. 4.51 Third Supplemental Indenture, dated as of July 5, 2017, to the Indenture, dated as of July 30, 1991, as amended, among Coca-Cola Refreshments USA, Inc., the Company and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on July 6, 2017. 10.1 Supplemental Award Notification — 2022 and 2023 Performance Share Units under The Coca-Cola 2014 Equity Plan — incorporated herein by reference to Exhibit 10.1 to the Company’s Form 8-K filed on August 21, 2024. 10.2 Supplemental Award Notification — 2022 and 2023 Restricted Stock Units under The Coca-Cola 2014 Equity Plan — incorporated herein by reference to Exhibit 10.2 to the Company’s Form 8-K filed on August 21, 2024. 31.1 Rule 13a-14(a)/15d-14(a) Certification, executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company. 31.2 Rule 13a-14(a)/15d-14(a) Certification, executed by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 32.1 Certifications required by Rule 13a-14(b) or Rule 15d-14(b) and Section 1350 of Chapter 63 of Title 18 of the United States Code (18 U.S.C. Section 1350), executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company, and by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 101 The following financial information from The Coca-Cola Company’s Quarterly Report on Form 10-Q for the quarter ended September 27, 2024, formatted in iXBRL (Inline Extensible Business Reporting Language): (i) Consolidated Statements of Income for the three and nine months ended September 27, 2024 and September 29, 2023; (ii) Consolidated Statements of Comprehensive Income for the three and nine months ended September 27, 2024 and September 29, 2023; (iii) Consolidated Balance Sheets as of September 27, 2024 and December 31, 2023; (iv) Consolidated Statements of Cash Flows for the nine months ended September 27, 2024 and September 29, 2023; and (v) Notes to Consolidated Financial Statements. 104 Cover Page Interactive Data File (the cover page XBRL tags are embedded within the iXBRL document and included in Exhibit 101). 57 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     THE COCA-COLA COMPANY (Registrant) /s/ ERIN MAY Date: October 24, 2024 Erin May Senior Vice President, Controller and Chief Accounting Officer (Principal Accounting Officer) 58\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SPY. Express as a decimal (e.g., -0.02).", "answer": "-0.0091", "answer_numeric": -0.009086, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0091 (i.e., on a bad day with 5% probability, the loss exceeds 0.91%). CVaR(95%) = -0.0156.", "metadata": {"var": -0.009086, "cvar": -0.015649, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20230322_0842", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-03-22", "context_summary": "SOL-USD: 60-day return history, mean=-0.0009, std=0.0478.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0478, min=-0.1182, max=0.1144\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-21] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0785", "answer_numeric": -0.078494, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0785 (i.e., on a bad day with 5% probability, the loss exceeds 7.85%). CVaR(95%) = -0.0973.", "metadata": {"var": -0.078494, "cvar": -0.097297, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231228_0844", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2023-12-28", "context_summary": "VCIT: 60-day return history, mean=0.0015, std=0.0048.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=0.0015, std=0.0048, min=-0.0086, max=0.0100\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VCIT. Express as a decimal (e.g., -0.02).", "answer": "-0.0067", "answer_numeric": -0.00669, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0067 (i.e., on a bad day with 5% probability, the loss exceeds 0.67%). CVaR(95%) = -0.0074.", "metadata": {"var": -0.00669, "cvar": -0.007437, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231227_0846", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-12-27", "context_summary": "XLU: 60-day return history, mean=0.0011, std=0.0117.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0011, std=0.0117, min=-0.0339, max=0.0271\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-26] [\"Apple Watch ban goes into effect, Bristol Myers buying RayzeBio: Yahoo Finance Live Apple (AAPL) is appealing a ban on US sales of its Apple Watch Series 9 and Ultra 2. The ban stems from a patent dispute over pulse oximetry technology that is used in the watches. There is also deal news, with shares of RayzeBio (RYZB) doubling after it was announced Bristol Myers Squibb (BMY) was buying the company in a $4.1 billion agreement. Also on Yahoo Finance at 4 p.m. ET, Ark Invest\\u2019s Cathie Wood talks Tesla (TSLA) and the potential for a spot bitcoin ETF to be approved. Trending tickers on Yahoo Finance include Intel (INTC), Nio (NIO), and Nvidia (NVDA).Top guests on Yahoo Finance Live today include:3:05 p.m. ET - Tom Hainlin, U.S. Bank Wealth Management Senior Investment Strategist3:25 p.m. ET - Greg Martin, Managing Director of Rainmaker Securities3:50 p.m. ET - Shehzad Qazi, China Beige Book International Managing Director4:05 p.m. ET - Nick Powills, Mainland CEO, 1851 Franchise Publisher, and The Melting Pot Board Member\", \"Apple seeks a path to getting 2 of its best watches back on shelves during a bitter patent dispute Apple filed an emergency motion seeking court permission to begin selling two of its most popular watches again until a final decision on its broader appeal in a bitter patent dispute is decided. The company cut off sales right before the Christmas holiday and in a motion filed Tuesday, Apple said it would suffer \\u201cirreparable harm\\u201d if previous court orders remain for the two weeks that it said the U.S. International Trade Commission will take to respond to its appeal. The disruption will likely cost Apple about $300-400 million in holiday-season sales, estimated Wedbush Securities analyst Dan Ives.\", \"Bitcoin Dips Below $42,000 While Memecoin Rally Shows Signs of Stalling (Bloomberg) -- Bitcoin dropped below $42,000 for the first time in a week and the recent rally in memecoins has started to show signs of stalling. Most Read from BloombergGoldman\\u2019s Painful 2023 Lesson on China Forces Rethink of Emerging MarketsS&P 500 Trades Within a Whisker of All-Time High: Markets WrapApple to Fight Watch Ban in Court After White House Declines to ActHow Were So Many Economists So Wrong About the Recession?Ethiopia Fails to Pay Coupon, Becoming Latest African DefaulterThe lar\", \"25 Technologies That Have Changed the World In this article, we will be analyzing the evolution of technology while covering the 25 technologies that have changed the world. If you wish to skip our detailed analysis, you can move directly to the 5 Technologies That Have Changed the World. Technology Over the Years Following the dot com bubble burst, technology successfully rebounded. [\\u2026]\", \"South Korea\\u2019s Consumers Turn Less Pessimistic as Inflation Eases (Bloomberg) -- South Korean consumers turned less pessimistic this month as inflation eased and exports improved.Most Read from BloombergS&P 500 Trades Within a Whisker of All-Time High: Ma\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0176", "answer_numeric": -0.017588, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0176 (i.e., on a bad day with 5% probability, the loss exceeds 1.76%). CVaR(95%) = -0.0245.", "metadata": {"var": -0.017588, "cvar": -0.024477, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240102_0848", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-01-02", "context_summary": "ACWI: 60-day return history, mean=0.0020, std=0.0075.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0020, std=0.0075, min=-0.0144, max=0.0216\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-29] [\"2 Overheated Stocks That Could Tumble in 2024 No one can predict what the stock market, or any individual stock, will do in 2024. The stock market surged in 2023, which was probably not on many investors' bingo cards in January. But one thing investors can do is avoid investments where the odds are stacked against them. Paying too high a price for even the best company can lead to subpar results. Two stocks that look far too expensive going into 2024 are Nvidia (NASDAQ: NVDA) and Apple (NASDAQ: AAPL). Nvidia Nvidia is the leader of artificial intelligence. The company's data center GPUs are selling faster than they can be made. Training advanced large language models, like those that power ChatGPT, requires incredible computational horsepower. Nvidia's proprietary CUDA compute platform has been around since 2007, pairing with its world-class hardware to create a competitive advantage that has been difficult for anyone to overcome so far. While Nvidia may appear untouchable, its days of absolute dominance won't last. If estimates for how big the AI accelerator market will become are close to accurate, there will be mammoth incentives for the tech industry to ensure that there are options beyond Nvidia. AMD expects the market for AI chips to grow nearly tenfold by 2027 to $400 billion. Nvidia's market share is almost certain to shrink as alternatives balloon, and as buyers of AI accelerators optimize for total cost of ownership. Nvidia's growth has been incredible in 2023, and its profits have soared even faster than revenue. The company's profit margins are the highest they've ever been. But the shortage of AI chips won't last forever as competitors race to bring alternatives to market, and neither will the gold rush mentality surrounding AI. Nvidia's software advantage will be chipped away, although that process may take a while. Nvidia is valued at around $1.22 trillion. That's about 40 times the average analyst estimate for earnings. That valuation doesn't seem unreasonable at first glance, but you must be willing to assume that Nvidia's incredible profit margins and growth rate will persist. What if they don't? What if the companies spending big to train large language models find that turning those models into sustainable businesses is tougher than expected? What if competing chips from AMD, Intel, and others provide viable alternatives to Nvidia's pricey products? Taking current growth rates and extrapolating out years is a dangerous thing to do, especially in a very new market. ChatGPT, which kicked off the AI frenzy, has only existed for about a year. If there's any sign that Nvidia is running into trouble in 2024, the stock has a long way to fall. Apple What's Apple's growth story? After a big surge during the pandemic's height, revenue has essentially stagnated in the post-pandemic period. Revenue slipped 1% year over year in the fiscal fourth quarter, which ended on Sept. 30, and an import ban on the Apple Watch isn't going to help ma\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ACWI. Express as a decimal (e.g., -0.02).", "answer": "-0.0120", "answer_numeric": -0.012028, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0120 (i.e., on a bad day with 5% probability, the loss exceeds 1.20%). CVaR(95%) = -0.0138.", "metadata": {"var": -0.012028, "cvar": -0.013751, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240314_0850", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-03-14", "context_summary": "ETH-USD: 60-day return history, mean=0.0077, std=0.0246.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0077, std=0.0246, min=-0.0583, max=0.0743\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0266", "answer_numeric": -0.02662, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0266 (i.e., on a bad day with 5% probability, the loss exceeds 2.66%). CVaR(95%) = -0.0431.", "metadata": {"var": -0.02662, "cvar": -0.043055, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240126_0851", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-01-26", "context_summary": "XLU: 60-day return history, mean=0.0004, std=0.0102.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0004, std=0.0102, min=-0.0235, max=0.0271\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0148", "answer_numeric": -0.01478, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0148 (i.e., on a bad day with 5% probability, the loss exceeds 1.48%). CVaR(95%) = -0.0205.", "metadata": {"var": -0.01478, "cvar": -0.020517, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230118_0852", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2023-01-18", "context_summary": "MORT: 60-day return history, mean=0.0028, std=0.0169.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0028, std=0.0169, min=-0.0384, max=0.0390\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MORT. Express as a decimal (e.g., -0.02).", "answer": "-0.0241", "answer_numeric": -0.024096, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0241 (i.e., on a bad day with 5% probability, the loss exceeds 2.41%). CVaR(95%) = -0.0293.", "metadata": {"var": -0.024096, "cvar": -0.029286, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230119_0854", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-01-19", "context_summary": "EFA: 60-day return history, mean=0.0029, std=0.0112.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0029, std=0.0112, min=-0.0259, max=0.0259\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-18] [\"AAPL September 2024 Options Begin Trading Investors in Apple Inc (Symbol: AAPL) saw new options become available today, for the September 2024 expiration. One of the key inputs that goes into the price an option buyer is willing to pay, is the time value, so with 611 days until expiration the newly available contracts represent a potential opportunity for sellers of puts or calls to achieve a higher premium than would be available for the contracts with a closer expiration. At Stock Options Channel, our YieldBoost formula has looked up and down the AAPL options chain for the new September 2024 contracts and identified one put and one call contract of particular interest. The put contract at the $135.00 strike price has a current bid of $15.20. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $135.00, but will also collect the premium, putting the cost basis of the shares at $119.80 (before broker commissions). To an investor already interested in purchasing shares of AAPL, that could represent an attractive alternative to paying $136.98/share today. Because the $135.00 strike represents an approximate 1% discount to the current trading price of the stock (in other words it is out-of-the-money by that percentage), there is also the possibility that the put contract would expire worthless. The current analytical data (including greeks and implied greeks) suggest the current odds of that happening are 99%. Stock Options Channel will track those odds over time to see how they change, publishing a chart of those numbers on our website under the contract detail page for this contract. Should the contract expire worthless, the premium would represent a 11.26% return on the cash commitment, or 6.73% annualized \\u2014 at Stock Options Channel we call this the YieldBoost. Below is a chart showing the trailing twelve month trading history for Apple Inc, and highlighting in green where the $135.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $140.00 strike price has a current bid of $22.40. If an investor was to purchase shares of AAPL stock at the current price level of $136.98/share, and then sell-to-open that call contract as a \\\"covered call,\\\" they are committing to sell the stock at $140.00. Considering the call seller will also collect the premium, that would drive a total return (excluding dividends, if any) of 18.56% if the stock gets called away at the September 2024 expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if AAPL shares really soar, which is why looking at the trailing twelve month trading history for Apple Inc, as well as studying the business fundamentals becomes important. Below is a chart showing AAPL's trailing twelve month trading history, with the $140.00 strike highlighted in red: Considering the fact that the $140.00 strike represents an approximate 2% \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0133", "answer_numeric": -0.013271, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0133 (i.e., on a bad day with 5% probability, the loss exceeds 1.33%). CVaR(95%) = -0.0182.", "metadata": {"var": -0.013271, "cvar": -0.018196, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20241121_0855", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-11-21", "context_summary": "LINK-USD: 60-day return history, mean=0.0045, std=0.0437.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0045, std=0.0437, min=-0.0785, max=0.1223\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0598", "answer_numeric": -0.059842, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0598 (i.e., on a bad day with 5% probability, the loss exceeds 5.98%). CVaR(95%) = -0.0694.", "metadata": {"var": -0.059842, "cvar": -0.0694, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240429_0857", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-04-29", "context_summary": "ADA-USD: 60-day return history, mean=-0.0041, std=0.0480.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0041, std=0.0480, min=-0.1409, max=0.0968\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1014", "answer_numeric": -0.101358, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1014 (i.e., on a bad day with 5% probability, the loss exceeds 10.14%). CVaR(95%) = -0.1213.", "metadata": {"var": -0.101358, "cvar": -0.121303, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231226_0858", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-12-26", "context_summary": "XLY: 60-day return history, mean=0.0019, std=0.0121.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0019, std=0.0121, min=-0.0259, max=0.0331\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-22] [\"7 Risks Intel Stock Investors Should Know for 2024 In today's video, I discuss recent updates impacting Intel (NASDAQ: INTC). Check out the short video to learn more, consider subscribing, and click the special offer link below. *Stock prices used were the market prices of Dec. 21, 2023. The video was published on Dec. 21, 2023. Should you invest $1,000 in Intel right now? Before you buy stock in Intel, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now... and Intel wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Stock Advisor provides investors with an easy-to-follow blueprint for success, including guidance on building a portfolio, regular updates from analysts, and two new stock picks each month. The Stock Advisor service has more than tripled the return of S&P 500 since 2002*. See the 10 stocks *Stock Advisor returns as of December 18, 2023 Jose Najarro has positions in Advanced Micro Devices, Nvidia, Qualcomm, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Advanced Micro Devices, Apple, Nvidia, Qualcomm, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Intel and recommends the following options: long January 2023 $57.50 calls on Intel, long January 2025 $45 calls on Intel, and short February 2024 $47 calls on Intel. The Motley Fool has a disclosure policy. Jose Najarro is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"2 Artificial Intelligence (AI) Stocks That Could Go Parabolic Artificial intelligence (AI) stocks have been in the limelight over the past year, thanks to the massive impact this technology is likely to have across multiple industries, with McKinsey estimating that AI adoption could add a whopping $13 trillion to the global economy by 2030. There are many ways investors can capitalize on this huge opportunity. Two companies that stand to win big from AI adoption in two distinct industries are Advanced Micro Devices (NASDAQ: AMD) and SentinelOne (NYSE: S). Both stocks have been on fire in 2023. While shares of AMD have jumped 113%, SentinelOne has shot up 83%, with a big chunk of that jump coming since the beginning of November. The recent stock price action of both companies suggests they may already have gone parabolic -- which refers to a rapid jump in the share price of a company in a short time, similar to the right side of a parabolic curve. However, there is a solid chance that these two AI stocks could go on another parabolic run in 2024. 1. Advanced Micro Devices Nvidia (NAS\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLY. Express as a decimal (e.g., -0.02).", "answer": "-0.0206", "answer_numeric": -0.020571, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0206 (i.e., on a bad day with 5% probability, the loss exceeds 2.06%). CVaR(95%) = -0.0248.", "metadata": {"var": -0.020571, "cvar": -0.024754, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240927_0860", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-09-27", "context_summary": "EFA: 60-day return history, mean=0.0012, std=0.0104.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0012, std=0.0104, min=-0.0269, max=0.0218\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0161", "answer_numeric": -0.016067, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0161 (i.e., on a bad day with 5% probability, the loss exceeds 1.61%). CVaR(95%) = -0.0226.", "metadata": {"var": -0.016067, "cvar": -0.022638, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241003_0862", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2024-10-03", "context_summary": "STIP: 60-day return history, mean=0.0004, std=0.0010.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0004, std=0.0010, min=-0.0018, max=0.0030\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for STIP. Express as a decimal (e.g., -0.02).", "answer": "-0.0012", "answer_numeric": -0.001199, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0012 (i.e., on a bad day with 5% probability, the loss exceeds 0.12%). CVaR(95%) = -0.0015.", "metadata": {"var": -0.001199, "cvar": -0.001459, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230612_0864", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-06-12", "context_summary": "XLU: 60-day return history, mean=-0.0001, std=0.0100.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0001, std=0.0100, min=-0.0237, max=0.0271\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-09] [\"US STOCKS-S&P, Nasdaq hit fresh 2023 highs as Tesla rallies By Sruthi Shankar and Shristi Achar A June 9 (Reuters) - The S&P 500 and Nasdaq hit fresh 2023 highs on Friday as Tesla shares jumped following a tie-up with General Motors, while investors awaited inflation data and U.S. monetary policy decision due next week. Tesla Inc TSLA.O shares climbed 5.7% after General Motors GM.Nagreed to use the company's Supercharger network. GM shares GM.N rose 3.8%. The benchmark S&P 500 on Thursday ended 20% above its Oct. 12 closing low, heralding the start of a new bull market as defined by some market participants. A rally in megacap stocks, a better-than-expected earnings season and expectations that the Fed was nearing the end of its rate-hiking cycle have supported Wall Street this year despite concerns about a looming recession and sticky inflation. \\\"The overall tone of the market is based on the idea that the Fed will pause its increases,\\\" said Rick Meckler, partner at Cherry Lane Investments. \\\"As it pauses, the broader market will start to rally and maybe catch up with the large-cap tech stocks that have led the way up until now.\\\" Major growth stocks including Apple Inc AAPL.O, Microsoft Corp MSFT.O and Nvidia Corp NVDA.O rose between 0.5% and 2.6%. Traders see a 72% chance that the U.S. central bank will hold interest rates at the current 5%-5.25% range in its June 13-14 policy meeting, according to CMEGroup's Fedwatch tool. Consumer prices data on Tuesday will help shape expectations around further moves by the Fed, with traders already pricing in a 50% chance of another 25-basis-point rate hike in July. \\\"We expect the Fed to hike one last time in this cycle in July. By September, we think weakening activity and employment data will lead toward a more enduring pause, with the Fed holding at 5.5% until its first rate cut in March 2024,\\\" economists at BNP Paribas noted. Signs of a resilient U.S. economy and hopes of the Fed pausing its aggressive monetary tightening have pushed volatility gauges tumbling. The CBOE Volatility index .VIX, commonly known as Wall Street's fear gauge, sank to a fresh pre-pandemic level of 13.53 points on Thursday. At 10:00 a.m. ET, the Dow Jones Industrial Average .DJI was up 56.85 points, or 0.17%, at 33,890.46, the S&P 500 .SPX was up 19.56 points, or 0.46%, at 4,313.49, and the Nasdaq Composite .IXIC was up 122.32 points, or 0.92%, at 13,360.85. Target Corp TGT.N slipped 1.3% after Citi downgraded the big-box retailer to \\\"neutral\\\", saying sales could fall further this year amid a challenging macro backdrop. Adobe Inc ADBE.O added 5.4% after Wells Fargo upgraded it to \\\"overweight\\\", saying the Photoshop software maker was poised to benefit from the generative AI boom. Netflix Inc NFLX.O gained 1.7% following a report that its subscriptions jumped after the streaming giant's crackdown on password sharing. Declining issues outnumbered advancers by a 1.36-to-1 ratio on the NYSE, while advancing issues outnumb\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0199", "answer_numeric": -0.019871, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0199 (i.e., on a bad day with 5% probability, the loss exceeds 1.99%). CVaR(95%) = -0.0222.", "metadata": {"var": -0.019871, "cvar": -0.022167, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231006_0866", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-10-06", "context_summary": "QUAL: 60-day return history, mean=-0.0005, std=0.0073.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=-0.0005, std=0.0073, min=-0.0191, max=0.0149\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-05] [\"Apple Reportedly Considered Replacing Google With DuckDuckGo For Safari (RTTNews) - Apple Inc., which has been using Alphabet Inc.'s Google as the default search engine for its devices, had talks to use the search engine DuckDuckGo for the private mode on Apple's Safari browser, Bloomberg reported citing some court documents. However, the tech major ultimately rejected the idea, the report said. The details of those talks now emerged amid an ongoing legal fight between the US Department of Justice and tech major Google over allegations of abusing its search dominance and violating antitrust laws. Earlier, it was reported that Microsoft Corp. was in talks with Apple in 2020 for a possible sale of its Bing search engine, but the talks never reached an advanced stage. Bloomberg reported that the talks among Apple, DuckDuckGo, and Microsoft were revealed in transcripts unsealed by US District Judge Amit Mehta, who oversees the Google antitrust trial. Mehta unsealed the testimony of DuckDuckGo Chief Executive Officer Gabriel Weinberg and Apple executive John Giannandrea, who testified in closed sessions in the trial. According to Weinberg, DuckDuckGo in 2018 and 2019 had about 20 meetings and phone calls with Apple executives, including the Safari head, regarding becoming the default search engine for private browsing mode on the Safari browser. Weinberg noted that Apple had integrated several of DuckDuckGo's other privacy technologies into Safari. Meanwhile, Giannandrea said that Apple hadn't considered switching to DuckDuckGo, to his knowledge. Google is Apple devices' default search engine. It was in 2002 that both companies signed their partnership, which was extended in 2021. Cue is said to be behind the current search engine partnership. Google reportedly pays more than $10 billion every year to secure its default search engine status on millions of browsers and mobile devices. The antitrust trial features testimony from top executives from Google, Apple, Microsoft, and Samsung. In its testimony against Google, Apple reportedly made it clear that it has never thought to replace Google as the default on iPhones as there wasn't a valid alternative at that time. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Is It Too Late to Buy This Top-Performing Nasdaq-100 Dividend Stock? The first half of 2023 turned into an incredible comeback story for the U.S. tech sector, thanks primarily to artificial intelligence (AI) gaining rapid mainstream adoption among the masses. This resulted in stocks of AI industry leaders like Nvidia (NVDA) (up 203% YTD), Google (GOOGL) (up 52.6% YTD), and Microsoft (MSFT) (up 32.8% YTD) all reaching new highs this year. A critical aspect of the AI revolution is the role played by semiconductor companies. In fact, according to a report by the Semiconductor Industry Association, total sales from the semiconductor industry could reach $1 t\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0137", "answer_numeric": -0.013682, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0137 (i.e., on a bad day with 5% probability, the loss exceeds 1.37%). CVaR(95%) = -0.0167.", "metadata": {"var": -0.013682, "cvar": -0.016721, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231003_0868", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-10-03", "context_summary": "ETH-USD: 60-day return history, mean=-0.0015, std=0.0178.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0015, std=0.0178, min=-0.0669, max=0.0468\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-02] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0352", "answer_numeric": -0.035151, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0352 (i.e., on a bad day with 5% probability, the loss exceeds 3.52%). CVaR(95%) = -0.0492.", "metadata": {"var": -0.035151, "cvar": -0.04922, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230605_0869", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2023-06-05", "context_summary": "SGOV: 60-day return history, mean=0.0002, std=0.0002.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, min=-0.0001, max=0.0007\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0000.", "metadata": {"var": 0.0, "cvar": -7e-06, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240515_0870", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-05-15", "context_summary": "EEM: 60-day return history, mean=0.0012, std=0.0080.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0012, std=0.0080, min=-0.0232, max=0.0255\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments 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blk:DeferredCashCompensationPlanEquityMethodInvestmentsMember us-gaap:EquityMethodInvestmentsMember 2023-01-01 2023-12-31 0001364742 us-gaap:InvestmentAdviceMember blk:FixedIncomeMember 2024-01-01 2024-03-31 0001364742 us-gaap:InvestmentAdviceMember blk:EquityNonETFIndexMember 2023-01-01 2023-03-31 0001364742 blk:PerformanceBasedRestrictedStockUnitsMember 2023-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:InvestmentsMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 blk:InstitutionalMember blk:RevenueByClientTypeMember 2024-01-01 2024-03-31 0001364742 us-gaap:FixedIncomeFundsMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 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0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0133", "answer_numeric": -0.013273, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0133 (i.e., on a bad day with 5% probability, the loss exceeds 1.33%). CVaR(95%) = -0.0170.", "metadata": {"var": -0.013273, "cvar": -0.016983, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20230905_0872", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-09-05", "context_summary": "DOT-USD: 60-day return history, mean=-0.0026, std=0.0210.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0026, std=0.0210, min=-0.0588, max=0.0772\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-04] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0338", "answer_numeric": -0.033817, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0338 (i.e., on a bad day with 5% probability, the loss exceeds 3.38%). CVaR(95%) = -0.0477.", "metadata": {"var": -0.033817, "cvar": -0.04765, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230608_0874", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-06-08", "context_summary": "MTUM: 60-day return history, mean=0.0003, std=0.0089.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0003, std=0.0089, min=-0.0172, max=0.0199\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-07] [\"Is Apple Stock as Overpriced as Its Vision Pro Headset? There were audible groans and boos when Apple (NASDAQ: AAPL) revealed the price of its Vision Pro mixed-reality headset will be $3,499. But few investors are balking at the price of Apple stock, which is once again flirting with a $3 trillion market cap. Shares of Apple hit an all-time high price ahead of Apple's big announcement earlier this week at its World Wide Developers Conference (WWDC) in California. The shares have outperformed both the S&P 500 and Nasdaq Composite indexes by a wide margin year to date. Meanwhile, its valuation is touching levels not seen since the end of 2021, when it last sat near $3 trillion, despite an outlook for a revenue and earnings decline in 2023. Is Apple getting too expensive for both investors and consumers? A hefty price tag Apple shares peaked above a forward P/E ratio of 30 to start the month of June. That's a higher forward P/E than the last time Apple shares traded around the $3 trillion market cap mark. The culprit is expectations that Apple's revenue and earnings per share will decline over the next year. Analysts currently expect a 2.3% decline in EPS and a 2.5% decline in sales for Apple. The Vision Pro won't sway those numbers: The device won't come out until 2024 and probably won't have meaningful sales until fiscal 2025. Over the last 15 years, Apple shares have traded at a trailing P/E above 30 for nine months during the height of the COVID-19 pandemic and then briefly again near the end of 2021. With its current P/E of 30.4, it's starting to look quite pricey again. AAPL P/E Ratio data by YCharts. Is Apple worth it? Despite its high price tags, Apple's products (and its stock) are typically worth the price. While the Vision Pro's value may still be up for debate, the stock still looks like a good deal despite the P/E ratio climbing above 30. Apple's stock price is supported by the pile of cash sitting on its balance sheet. As of the end of the second quarter, Apple had $166 billion in cash and securities on its balance sheet. While it used debt to access that cash, it still had just $107 billion in debt on the balance sheet, leaving it with $59 billion in net cash. Meanwhile, it's generated nearly $100 billion in free cash flow over the past year, and the outlook remains strong for it to keep the cash machine running. That consistent cash flow and massive stockpile on its balance sheet gives Apple a lot of room to keep buying back shares of the stock and support its stock price. It bought back $39 billion worth of stock in the first half of 2023, and the board authorized a new $90 billion share repurchase program in May. The consistent sales of iPhones and the growth of Apple's high-margin services business are the reasons to buy Apple. It's a cash cow that allows it to return massive amounts of money to shareholders while still investing in products for the future, like Vision Pro. So, even if Vision Pro is an absolute overpriced flop (\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MTUM. Express as a decimal (e.g., -0.02).", "answer": "-0.0165", "answer_numeric": -0.016454, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0165 (i.e., on a bad day with 5% probability, the loss exceeds 1.65%). CVaR(95%) = -0.0169.", "metadata": {"var": -0.016454, "cvar": -0.016931, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230803_0876", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-08-03", "context_summary": "IWM: 60-day return history, mean=0.0019, std=0.0112.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0019, std=0.0112, min=-0.0163, max=0.0349\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-02] [\"Mediocre Earnings After the Bell; Selloff Continues Markets had a hard time today reconciling the first U.S. credit rating downgrade in 12 years, when Fitch Ratings \\u2014 one of the \\u201cbig three\\u201d credit rating agencies \\u2014 lowered its rating from the usual AAA to AA+. The reason for the move is the same as it was a dozen years ago: Congress is kicking the can on increasing its debt ceiling, which, if not raised, would cause the U.S. to default on its debts. Last time, it was also a Democratic White House and a Republican-led House of Representatives that saw this issue emerge. In any case, market indices were down across the board today. All the majors opened normal trading in the red and stayed there, closing off session lows, but not by much. The Dow shed -331 points, -0.93%, while the Nasdaq dropped -309 points, -2.17%. The S&P 500 and small-cap Russell 2000 were down -1.39% and -1.37%, respectively. So far, August looks to be giving back a significant amount of July gains, just in the first two days of the new month\\u2019s trading. Qualcomm QCOM is the latest major company to post mixed results in its quarterly report this afternoon: while fiscal Q3 earnings of $1.87 per share bettered the $1.81 in the Zacks consensus, revenues of $8.45 billion came up short of the $8.51 billion. Revenue guidance for fiscal Q4 are for a range of $8.1-8.9 billion, with a midpoint lower than the consensus $8.69 billion. A -25% drop in handset chip sales year over year and a slower recovery in China contributed to the performance. Shares are down -4.5% on the release. MGM Resorts MGM, however, outperformed estimates on both top and bottom lines, with earnings of 59 cents per share beating the 53 cents expected, and sales of $3.94 billion in the quarter easily surpassing the $3.76 billion consensus. Its MGM China business in Macau has surprised to the upside, notching +5% growth over 2019 (pre-Covid) levels, +21% on the key EBITDAR metric. However, after cranking +48% higher year to date, investors are selling this news; MGM is -7% in today\\u2019s after-market. PayPal PYPL reported in-line earnings at $1.16 per share on $7.29 billion in quarterly revenues, up nearly +7% year over year. Guidance for Q3 looks to be slightly above previous estimates, as Payment Volume grew +11% year over year. That said, Operating Margin of +21.4% in the quarter missed consensus expectations of +22%, and this may be adding fuel to the -7.5% selloff in today\\u2019s late trading. PayPal has also been an underperformer year to date. Etsy ETSY posted beats on both top and bottom lines this afternoon, with earnings of 45 cents per share improving by 4 cents over the Zacks consensus, on revenues of $629 million in the quarter. Gross merchandising came in at $3.01 billion, -20% year to date, even as the company noted Etsy Active Buyers reached an all-time high in the quarter. Shares are selling off -5% after normal hours. Closing on a positive note, DoorDash DASH shares are u\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0137", "answer_numeric": -0.013743, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0137 (i.e., on a bad day with 5% probability, the loss exceeds 1.37%). CVaR(95%) = -0.0154.", "metadata": {"var": -0.013743, "cvar": -0.015381, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230616_0877", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-06-16", "context_summary": "SOL-USD: 60-day return history, mean=-0.0084, std=0.0347.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0084, std=0.0347, min=-0.0992, max=0.0546\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-15] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0812", "answer_numeric": -0.08116, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0812 (i.e., on a bad day with 5% probability, the loss exceeds 8.12%). CVaR(95%) = -0.0906.", "metadata": {"var": -0.08116, "cvar": -0.090587, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240424_0879", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2024-04-24", "context_summary": "JNK: 60-day return history, mean=-0.0000, std=0.0032.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=-0.0000, std=0.0032, min=-0.0093, max=0.0054\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for JNK. Express as a decimal (e.g., -0.02).", "answer": "-0.0050", "answer_numeric": -0.005025, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0050 (i.e., on a bad day with 5% probability, the loss exceeds 0.50%). CVaR(95%) = -0.0078.", "metadata": {"var": -0.005025, "cvar": -0.007784, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240521_0881", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-05-21", "context_summary": "SOL-USD: 60-day return history, mean=0.0017, std=0.0468.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0017, std=0.0468, min=-0.1098, max=0.1138\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0788", "answer_numeric": -0.078787, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0788 (i.e., on a bad day with 5% probability, the loss exceeds 7.88%). CVaR(95%) = -0.0957.", "metadata": {"var": -0.078787, "cvar": -0.095748, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230516_0883", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-05-16", "context_summary": "QUAL: 60-day return history, mean=0.0004, std=0.0097.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0004, std=0.0097, min=-0.0217, max=0.0233\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-15] [\"Capitalize on the Emerging Age of AI for Hefty Profits InvestorPlace - Stock Market News, Stock Advice & Trading Tips Editor\\u2019s note: \\u201cCapitalize on the Emerging Age of AI for Hefty Profits\\u201d was previously published in March 2023. It has since been updated to include the most relevant information available. Crisis creates opportunity. And big crises create big opportunities. For example, did you know that the Internet Economy \\u2013 which created the world\\u2019s first trillion-dollar companies, churning out multiple 1,000% stock market winners \\u2013 was born amid the 2008 financial crisis? Technically, the internet was born in the 1990s \\u2013 the World Wide Web launched on Aug. 6, 1991. But it wasn\\u2019t until Apple (AAPL) released the first iPhone in 2007 \\u2013 and put the power of the internet literally in the palms of everyone\\u2019s hands \\u2013 that the Internet Economy really started to blossom. Just look at how the revenue growth trajectories for internet titans like Amazon (AMZN), Alphabet (GOOGL), and Netflix (NFLX) dramatically changed after the iPhone\\u2019s launch. Before the iPhone, internet companies were growing. After, they started to spread like wildfire and take over the world. It was a critical inflection point \\u2013 the \\u201ctipping point\\u201d for the internet revolution\\u2026 The moment when everything changed. Of course, at the time, it didn\\u2019t feel like that. The financial economy was collapsing because of the subprime loan meltdown. Unemployment rates were soaring. Stocks were crashing. Companies were going bankrupt. Home foreclosures were happening left and right. It felt like the end times, even for internet stocks like Amazon, Netflix, Alphabet, and the iPhone\\u2019s maker, Apple. All those stocks dropped between 50% and 60% in 2008 \\u2013 the year after the iPhone launched. What a crisis\\u2026 And what an opportunity. Crisis Begets Opportunity For investors who were able to zoom out and look at the big picture, the financial crisis created the opportunity of a lifetime. It left internet stocks trading at dirt-cheap valuations just months after the emergence of the Internet Economy\\u2019s biggest catalyst of all time \\u2013 the iPhone. Those \\u201cbig-picture\\u201d investors were able to recognize that the economy wasn\\u2019t going to collapse and that the 2008 crisis \\u2013 like all financial crises before it \\u2013 would pass. They were able to identify the iPhone\\u2019s significance as a critical inflection point for the Internet Economy that would spark 10-plus years of super-charged growth. They were able to see the deep value in internet stocks. And they were smart enough to buy the dip in names like Amazon, Netflix, Apple, and Alphabet. As a result, those \\u201cbig-picture\\u201d investors have since made fortunes. Every $10,000 invested in Alphabet stock in late 2008 would be worth nearly $140,000 today. A $10,000 investment in Amazon or Apple stock in late 2008 would be worth nearly $\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0166", "answer_numeric": -0.016631, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0166 (i.e., on a bad day with 5% probability, the loss exceeds 1.66%). CVaR(95%) = -0.0186.", "metadata": {"var": -0.016631, "cvar": -0.018568, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230509_0885", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-05-09", "context_summary": "XLV: 60-day return history, mean=0.0003, std=0.0083.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0003, std=0.0083, min=-0.0162, max=0.0171\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-08] [\"Is Apple Stock a Buy Right Now? Apple (NASDAQ: AAPL) has demonstrated an ability to create innovative products consumers are willing to pay premium prices for. Fool.com contributor and finance professor Parkev Tatevosian considers whether Apple's stock is a buy right now. *Stock prices used were the afternoon prices of May 4, 2023. The video was published on May 6, 2023. 10 stocks we like better than Apple When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now... and Apple wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of May 1, 2023 Parkev Tatevosian, CFA has positions in Apple. The Motley Fool has positions in and recommends Apple. The Motley Fool has a disclosure policy. Parkev Tatevosian is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through his link, he will earn some extra money that supports his channel. His opinions remain his own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Invest Like Warren Buffett With These 3 Stocks Warren Buffett, also commonly called the Oracle of Omaha, is a name that jumps to the forefront of many minds when thinking of the financial world. As we\\u2019re all aware, many mimic his portfolio moves. And just over the weekend, Berkshire Hathaway hosted its annual shareholder meeting, putting the Oracle of Omaha and his go-to man, Charlie Munger, in full focus. With the legendary investing icon making headlines following the meeting, let\\u2019s take a look at three companies that Buffett has placed big bets on. Apple (AAPL) Apple is a long-time favorite of Buffett, reflecting the largest holding of Berkshire. Over the weekend, the icon spoke positively about the iPhone\\u2019s rock-solid status among consumers, a big reason why he believes in the company. Apple\\u2019s quarterly results took the spotlight last week, with the tech titan delivering a positive 5.6% EPS surprise and reporting revenue nearly 2% above expectations. The company also announced a 4% increase to its quarterly cash dividend, payable on May 18th. Image Source: Zacks Investment Research In addition, the company posted solid iPhone results; iPhone revenue throughout the reported quarter totaled $51.3 billion, 4% above the Zacks Consensus Estimate and improving 1.5% from the year-ago period. As we can see from the chart below, the better-than-expected iPhone results snapped a streak of back-to-back negative surprises. Suprise (%) - iPhone Revenue Image Source: Zacks Investment Research Bank of America (BAC) Despite the recent turmoil within banking, Buffett still remains\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLV. Express as a decimal (e.g., -0.02).", "answer": "-0.0131", "answer_numeric": -0.013104, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0131 (i.e., on a bad day with 5% probability, the loss exceeds 1.31%). CVaR(95%) = -0.0153.", "metadata": {"var": -0.013104, "cvar": -0.015263, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240829_0888", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-08-29", "context_summary": "ETH-USD: 60-day return history, mean=-0.0040, std=0.0393.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0040, std=0.0393, min=-0.1002, max=0.1484\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0725", "answer_numeric": -0.072513, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0725 (i.e., on a bad day with 5% probability, the loss exceeds 7.25%). CVaR(95%) = -0.0860.", "metadata": {"var": -0.072513, "cvar": -0.085988, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230207_0890", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-02-07", "context_summary": "XLK: 60-day return history, mean=0.0012, std=0.0167.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0012, std=0.0167, min=-0.0381, max=0.0373\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-06] [\"A Rare Earnings Miss Couldn\\u2019t Stop Apple Stock (NASDAQ:AAPL) Shares of Apple (NASDAQ:AAPL) are fresh off a quarterly earnings miss, with sales slipping 5% year-over-year, marking the worst quarterly top-line decline in years. Still, Apple stock was resilient following the disappointing number, closing off Friday's session up 2.4% in a bloody day for tech stocks. I remain bullish as Apple stock shrugs off its forgettable quarter and moves on from headwinds that are bound to fade in time. The recent round of quarterly results themselves was nothing to write home about (weakness was broadly spread across categories). It was likely the words of management that helped soothed investor nerves, helping Apple stock outperform some FAANG rivals that also reported the previous day. The company didn't give formal guidance for Fiscal 2023 due to macro uncertainty. It's noteworthy that the words \\\"macro headwinds\\\" were used quite a bit throughout the conference call. In any case, I think it's only prudent not to attempt to provide any sort of concrete guidance with recession headwinds up ahead. Despite the lack of guidance, management didn't leave investors in the dark. CEO Tim Cook called for year-over-year sales growth to be \\\"similar to the December quarter.\\\" Such words, I believe, set the bar quite low for the coming quarter and could set the stage to impress. He also stated that \\\"from a supply chain point of view, we're now at a point where production is what we need it to be.\\\" That alone was likely enough to help Apple investors breathe a sigh of relief. Apple: The Worst of the Production Issues May Have Passed My takeaway from Cook's comments was that the worst of production headwinds may already be in the rearview mirror. Indeed, the next quarter could see iPhone revenue growth in the red. However, the second half could see Apple make up for lost time as production gets up to full speed while Apple users finally look to upgrade. Indeed, Apple can afford to have some sizeable supply-side hiccups without losing too much business. At the end of the day, customer loyalty is unparalleled, with many Apple users that will opt not to switch to a competing product, even if it means having to endure longer wait times. Lockdowns in China have weighed heavily on operations. Still, I am confident that Cook can promptly bring production back in order. The man is an operational genius who's effectively ironed out supply-chain wrinkles in the past. Once Apple moves past the current barrage of headwinds, it'll likely be right back to gaining meaningful market share in the smartphone market again. Further, amping up efforts to expand into India, a market where Apple is reportedly enjoying double-digit growth, could help fuel such market gains. Apple's Rough Quarter is Easy to Forgive There's no question that Apple was up against it going into what many expected would be a rough quarter. Going into the quarter, estimates were muted, thanks in part to manufact\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0218", "answer_numeric": -0.021838, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0218 (i.e., on a bad day with 5% probability, the loss exceeds 2.18%). CVaR(95%) = -0.0300.", "metadata": {"var": -0.021838, "cvar": -0.030005, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230906_0891", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-09-06", "context_summary": "XRP-USD: 60-day return history, mean=-0.0019, std=0.0538.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0019, std=0.0538, min=-0.1380, max=0.3257\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-05] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0487", "answer_numeric": -0.048731, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0487 (i.e., on a bad day with 5% probability, the loss exceeds 4.87%). CVaR(95%) = -0.1023.", "metadata": {"var": -0.048731, "cvar": -0.102251, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231012_0893", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-10-12", "context_summary": "XLP: 60-day return history, mean=-0.0016, std=0.0067.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0016, std=0.0067, min=-0.0199, max=0.0103\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-11] [\"Meta Platforms sued by virtual reality fitness app developer after deal craters By Mike Scarcella Oct 11 (Reuters) - An interactive app and game-design collective has sued Meta Platforms META.O in U.S. court, accusing Facebook's owner of unlawfully breaking a contract for a fitness program in an anticompetitive \\\"campaign to conquer\\\" virtual reality markets. California-based Andre Elijah Immersive Inc filed its complaint in San Jose federal court against Meta and other defendants, including Alo Yoga, the clothing and fitness company. The collective said it had developed a fitness app with Meta and Alo featuring the \\\"best and most widely-recognized yoga instructors in the world.\\\" The lawsuit claimed Meta was prepared to launch the app at the company's virtual reality conference Meta Connect 2023. But Meta, according to the complaint, terminated its contract with the collective after learning it was also working with rival platforms Apple AAPL.O and Pico to distribute its app. A representative from Meta had no immediate comment on Wednesday. Los Angeles-founded Alo did not immediately respond to a request for comment. Attorneys for the defendants have not yet made appearances in the case. Apple and Pico, a virtual reality headset manufacturer owned by TikTok's Chinese developer ByteDance, did not immediately respond to requests for comment. Apple, Pico and ByteDance are not defendants in the case. The collective's attorney, Joseph Prencipe, told Reuters that \\\"resolution of the lawsuit will determine what happens to the app.\\\" The lawsuit accused Meta and the co-defendants of \\\"abusive and anticompetitive behavior\\\" in violation of U.S. antitrust law. The complaint demands more than $100 million in antitrust damages, before automatic trebling, as well as several million dollars for the defendants' alleged breach of the app contract. The collective described itself in the lawsuit as a \\\"new entrant\\\" in the virtual reality fitness market, which was the centerpiece of a U.S. Federal Trade Commission lawsuit against Meta last year in California federal court. The FTC unsuccessfully sued to stop Meta's purchase of Within Unlimited, maker of the Supernatural fitness workouts. Meta denied the agency's claim that the acquisition would \\\"dampen innovation\\\" in markets for VR fitness apps. The deal closed in February after a U.S. judge declined to order a preliminary injunction. The collective's lawsuit, featuring contract documents between it and Meta, said Meta had become a \\\"key player\\\" at various levels in the virtual reality marketplace, including hardware and app distribution. The exclusion of the collective's fitness app \\\"eliminates both present and future competition,\\\" the complaint alleged. The case is Andre Elijah Immersive Inc v. Meta Platforms Technologies LLC et al, U.S. District Court, Northern District of California, No. 5:23-cv-05159-NC. Read more: Meta unveils Quest 3 mixed reality headset ahead of Apple's VR debut U.S. judge denies\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLP. Express as a decimal (e.g., -0.02).", "answer": "-0.0100", "answer_numeric": -0.010037, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0100 (i.e., on a bad day with 5% probability, the loss exceeds 1.00%). CVaR(95%) = -0.0146.", "metadata": {"var": -0.010037, "cvar": -0.014568, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230823_0895", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IEF"], "decision_date": "2023-08-23", "context_summary": "IEF: 60-day return history, mean=-0.0008, std=0.0050.", "question": "Asset: IEF\nDaily returns (past 60 days): mean=-0.0008, std=0.0050, min=-0.0103, max=0.0106\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IEF. Express as a decimal (e.g., -0.02).", "answer": "-0.0080", "answer_numeric": -0.007962, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0080 (i.e., on a bad day with 5% probability, the loss exceeds 0.80%). CVaR(95%) = -0.0096.", "metadata": {"var": -0.007962, "cvar": -0.009589, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231020_0896", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-10-20", "context_summary": "XLB: 60-day return history, mean=-0.0018, std=0.0090.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0018, std=0.0090, min=-0.0262, max=0.0165\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-19] [\"Google to manufacture smartphones in India starting with Pixel 8 Adds quote in paragraph 3, context from paragraph 4 NEW DELHI, Oct 19 (Reuters) - Alphabet Inc GOOGL.O will start manufacturing in India and will partner with international and domestic manufacturers to produce its Pixel smartphones locally, starting with Pixel 8, an executive said on Thursday. The devices are expected to be rolled out in 2024, Rick Osterloh, senior vice president of devices and services, said at a Google event. \\\"India is a priority market for Pixel smartphones, and we\\u2019re committed to bringing the best of our hardware and underlying built-in software capabilities to people across the country,\\\" Osterloh said. India is aiming to become a manufacturing powerhouse, amid a greater push for Prime Minister Narendra Modi's \\\"Make in India\\\" initiative. Apple AAPL.O, which has been touting India as its next big growth driver, is projected to account for 7% of all smartphone sales in the country from July to December, up from 5% in the first half of 2023, according to data from market researcher Counterpoint. U.S. memory chip firm Micron Technology MU.O recently announced plans to set up its first semiconductor plant in the country. (Reporting by Tanvi Mehta and Blassy Boben; Editing by Muralikumar Anantharaman) ((blassy.boben@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"TSMC Q3 profit falls 24.9%, beats market forecasts Q3 profit T$211 bln vs T$195.5 bln analyst view Q3 revenue down 14.6% on year at $17.3 bln Q3 capex $7.1 bln vs Q2 $8.17 bln Adds details and share prices in paragraphs 4-7 TAIPEI, Oct 19 (Reuters) - Taiwanese chipmaker TSMC 2330.TW posted a 24.9% fall in third-quarter net profit on Thursday as global economic woes hit demand for chips used in applications from cars to cellphones and servers and coming off a high base last year. Taiwan Semiconductor Manufacturing Co Ltd (TSMC) TSM.N, the world's largest contract chipmaker and a major Apple Inc AAPL.O supplier, saw July-September net profit fall to T$211 billion from T$280.9 billion a year earlier. The profit beat a T$195.5 billion LSEG SmartEstimate, which is weighted toward forecasts from analysts who are more consistently accurate. TSMC, Asia's most valuable listed company, said third-quarter revenue dropped 14.6% to $17.3 billion, in line with the company's previous forecast of $16.7 billion to $17.5 billion. Capital expenditure in the third quarter was $7.1 billion, TSMC said, compared with $8.17 billion in the previous quarter. As the biggest maker of advanced chips, TSMC must navigate an uncertain industry outlook and a U.S.-China chip spat that could make it vulnerable. TSMC's Taipei-listed shares fell 27.1% in 2022, but are up around 22% so far this year, giving the chipmaker a market value of $432.3 billion. The stock rose 1.1% on Thursday versus a flat benchmark index .TWII. (Re\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLB. Express as a decimal (e.g., -0.02).", "answer": "-0.0165", "answer_numeric": -0.016531, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0165 (i.e., on a bad day with 5% probability, the loss exceeds 1.65%). CVaR(95%) = -0.0217.", "metadata": {"var": -0.016531, "cvar": -0.021738, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240909_0897", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-09-09", "context_summary": "XLF: 60-day return history, mean=0.0014, std=0.0094.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0014, std=0.0094, min=-0.0294, max=0.0160\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0143", "answer_numeric": -0.014302, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0143 (i.e., on a bad day with 5% probability, the loss exceeds 1.43%). CVaR(95%) = -0.0230.", "metadata": {"var": -0.014302, "cvar": -0.023039, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240301_0899", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2024-03-01", "context_summary": "XHB: 60-day return history, mean=0.0031, std=0.0137.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0031, std=0.0137, min=-0.0318, max=0.0435\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XHB. Express as a decimal (e.g., -0.02).", "answer": "-0.0192", "answer_numeric": -0.019155, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0192 (i.e., on a bad day with 5% probability, the loss exceeds 1.92%). CVaR(95%) = -0.0300.", "metadata": {"var": -0.019155, "cvar": -0.030015, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230706_0901", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-07-06", "context_summary": "ICSH: 60-day return history, mean=0.0000, std=0.0004.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0000, std=0.0004, min=-0.0010, max=0.0014\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ICSH. Express as a decimal (e.g., -0.02).", "answer": "-0.0004", "answer_numeric": -0.000429, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0004 (i.e., on a bad day with 5% probability, the loss exceeds 0.04%). CVaR(95%) = -0.0010.", "metadata": {"var": -0.000429, "cvar": -0.000997, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231017_0903", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2023-10-17", "context_summary": "VLUE: 60-day return history, mean=-0.0009, std=0.0068.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0009, std=0.0068, min=-0.0152, max=0.0123\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-16] [\"US STOCKS-Wall St jumps 1% to kick-start earnings and data-heavy week, megacaps rise By Ankika Biswas and Shashwat Chauhan Oct 16 (Reuters) - Wall Street's main indexes jumped more than 1% on Monday as megacaps rose to kick-start a week packed with corporate earnings and economic data, while investors also monitored the Israel-Hamas conflict. The Dow touched a near four-week high and was on course for its best day in more than two months, while the S&P 500 and the Nasdaq were headed for their best days in nearly two weeks. Megacaps Microsoft MSFT.O, Meta Platforms META.O, Alphabet GOOGL.O and Amazon.com AMZN.O rose between 1% and 2%. Consumer discretionary .SPLRCD and materials .SPLRCM led the gains across major S&P 500 sectors, while utilities .SPLRCU and energy stocks .SPNY lagged behind. \\\"There's a little bit of risk-on sentiment coming from a pretty solid start to their earnings season,\\\" said Ross Mayfield, investment strategy analyst at Baird. \\\"It says that what the economic data is also saying, which is that the economy is stronger than we were giving it credit for at the year's start, certainly not recessionary.\\\" Results from large banks Goldman Sachs GS.N, Bank of America BAC.N, Morgan Stanley MS.N, pharmaceutical giant Johnson & Johnson JNJ.N, EV maker Tesla TSLA.O and video-streaming pioneer Netflix NFLX.O are due this week. Third-quarter earnings for S&P 500 companies are estimated to grow 2.2% year-on-year, LSEG data showed on Friday. Long-dated Treasury yields rose amid increased U.S. government debt issuance while a possible Israeli ground offensive in Gaza has led to uncertainty in the bond market. Investors also await economic data including retail sales for September and the Philly Fed Business Index for October later this week. Latest data showed the NY Fed's \\\"Empire State\\\" index, a gauge of manufacturing activity in New York State, fell to -4.60 in October, against expectations of a drop to -7. The Dow Jones Transport Average index .DJT, seen as an indicator of economic prosperity, was on track for its best day in nearly three months. Investors are focused on Federal Reserve Chair Jerome Powell's comments on Thursday, before Fed officials enter a blackout period starting Oct. 21 ahead of their policy meeting. Philadelphia Fed President Patrick Harker reiterated his view from Friday that the U.S. central bank was likely done with its rate-hike cycle. Among stocks, Apple AAPL.O bucked the trend among its growth peers, dipping 0.1% on a report the company's iPhones were off to a disappointing start in China. Lululemon AthleticaLULU.O added 9.6% as the sportswear apparel maker is set to join the S&P 500 index this week, replacing Activision Blizzard ATVI.O. ModernaMRNA.O reaffirmed its forecast of $6 billion to $8 billion in COVID vaccine sales for the year. The company's shares fell 5.0%. Charles SchwabSCHW.N jumped 4.8% as the brokerage posted a smaller-than-expected drop in quarterly profit. Advancing issues outnumbered \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0120", "answer_numeric": -0.011992, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0120 (i.e., on a bad day with 5% probability, the loss exceeds 1.20%). CVaR(95%) = -0.0141.", "metadata": {"var": -0.011992, "cvar": -0.014059, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20241106_0905", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-11-06", "context_summary": "XLF: 60-day return history, mean=0.0018, std=0.0079.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0018, std=0.0079, min=-0.0148, max=0.0191\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PFE 2024-11-04] pfe-20240929 0000078003 12/31 2024 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares pfe:operatingSegment xbrli:pure pfe:facility pfe:patent pfe:treatmentCourse 0000078003 2024-01-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-01-01 2024-09-29 0000078003 pfe:NotesDue20271.000Member 2024-01-01 2024-09-29 0000078003 2024-10-30 0000078003 us-gaap:ProductMember 2024-07-01 2024-09-29 0000078003 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0000078003 us-gaap:ParentMember 2024-07-01 2024-09-29 0000078003 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-09-29 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-07-01 2024-09-29 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-07-01 2024-09-29 0000078003 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-09-29 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-09-29 0000078003 us-gaap:TreasuryStockCommonMember 2024-09-29 0000078003 us-gaap:RetainedEarningsMember 2024-09-29 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-09-29 0000078003 us-gaap:ParentMember 2024-09-29 0000078003 us-gaap:NoncontrollingInterestMember 2024-09-29 0000078003 us-gaap:CommonStockMember 2023-07-02 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-07-02 0000078003 us-gaap:TreasuryStockCommonMember 2023-07-02 0000078003 us-gaap:RetainedEarningsMember 2023-07-02 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-02 0000078003 us-gaap:ParentMember 2023-07-02 0000078003 us-gaap:NoncontrollingInterestMember 2023-07-02 0000078003 2023-07-02 0000078003 us-gaap:RetainedEarningsMember 2023-07-03 2023-10-01 0000078003 us-gaap:ParentMember 2023-07-03 2023-10-01 0000078003 us-gaap:NoncontrollingInterestMember 2023-07-03 2023-10-01 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-03 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-07-03 2023-10-01 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-07-03 2023-10-01 0000078003 us-gaap:TreasuryStockCommonMember 2023-07-03 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-10-01 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-10-01 0000078003 us-gaap:TreasuryStockCommonMember 2023-10-01 0000078003 us-gaap:RetainedEarningsMember 2023-10-01 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-10-01 0000078003 us-gaap:ParentMember 2023-10-01 0000078003 us-gaap:NoncontrollingInterestMember 2023-10-01 0000078003 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-12-31 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000078003 us-gaap:TreasuryStockCommonMember 2023-12-31 0000078003 us-gaap:RetainedEarningsMember 2023-12-31 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000078003 us-gaap:ParentMember 2023-12-31 0000078003 us-gaap:NoncontrollingInterestMember 2023-12-31 0000078003 us-gaap:RetainedEarningsMember 2024-01-01 2024-09-29 0000078003 us-gaap:ParentMember 2024-01-01 2024-09-29 0000078003 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-09-29 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-01-01 2024-09-29 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-09-29 0000078003 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2022-12-31 0000078003 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000078003 us-gaap:TreasuryStockCommonMember 2022-12-31 0000078003 us-gaap:RetainedEarningsMember 2022-12-31 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-12-31 0000078003 us-gaap:ParentMember 2022-12-31 0000078003 us-gaap:NoncontrollingInterestMember 2022-12-31 0000078003 2022-12-31 0000078003 us-gaap:RetainedEarningsMember 2023-01-01 2023-10-01 0000078003 us-gaap:ParentMember 2023-01-01 2023-10-01 0000078003 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-10-01 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-01 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-01-01 2023-10-01 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-10-01 0000078003 us-gaap:TreasuryStockCommonMember 2023-01-01 2023-10-01 0000078003 us-gaap:AccountsReceivableMember 2024-09-29 0000078003 us-gaap:AccountsReceivableMember 2023-12-31 0000078003 us-gaap:OtherCurrentLiabilitiesMember 2024-09-29 0000078003 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0000078003 us-gaap:OtherNoncurrentLiabilitiesMember 2024-09-29 0000078003 us-gaap:OtherNoncurrentLiabilitiesMember 2023-12-31 0000078003 pfe:SeagenMember 2023-12-14 0000078003 pfe:SeagenMember 2023-12-14 2023-12-14 0000078003 pfe:SeagenMember 2024-01-01 2024-09-29 0000078003 pfe:SeagenMember 2024-09-29 0000078003 pfe:SeagenMember pfe:DevelopedTechnologyRightsAndOtherIntangibleAssetsMember 2023-12-14 0000078003 pfe:SeagenMember pfe:DevelopedTechnologyRightsAndOtherIntangibleAssetsMember 2024-01-01 2024-09-29 0000078003 pfe:SeagenMe [...TRUNCATED...] 2024 14,581  $ 27.73  —  $ 3,292,882,444  July 29 through August 25, 2024 22,257  $ 30.44  —  $ 3,292,882,444  August 26 through September 29, 2024 57,730  $ 29.02  —  $ 3,292,882,444  Total 94,568  $ 29.16  —  (a) Represents (i) 91,700 shares of common stock surrendered to the Company to satisfy tax withholding obligations in connection with the vesting of awards under our long-term incentive programs and (ii) the open market purchase by the trustee of 2,868 shares of common stock in connection with the reinvestment of dividends paid on common stock held in trust for employees who deferred receipt of performance share awards. (b) See the Analysis of Financial Condition, Liquidity, Capital Resources and Market Risk—Capital Allocation Framework section within MD&A of this Form 10-Q and Note 12 in our 2023 Form 10-K. ITEM 5. OTHER INFORMATION During the three months ended September 29, 2024, none of our directors or officers adopted or terminated a “Rule 10b5-1 trading arrangement” or “non-Rule 10b5-1 trading arrangement,” as each term is defined in Item 408 of Regulation S-K. 60 ITEM 6. EXHIBITS   Exhibit 31.1 Certification by the Chief Executive Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 31.2 Certification by the Chief Financial Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.1 Certification by the Chief Executive Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.2 Certification by the Chief Financial Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 101:     EX-101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document.   EX-101.SCH EX-101.CAL EX-101.LAB EX-101.PRE EX-101.DEF   Inline XBRL Taxonomy Extension Schema Inline XBRL Taxonomy Extension Calculation Linkbase Inline XBRL Taxonomy Extension Label Linkbase Inline XBRL Taxonomy Extension Presentation Linkbase Inline XBRL Taxonomy Extension Definition Document Exhibit 104 Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   Pfizer Inc.   (Registrant)         Dated: November 4, 2024 /s/ Jennifer B. Damico   Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) 61\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0112", "answer_numeric": -0.011153, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0112 (i.e., on a bad day with 5% probability, the loss exceeds 1.12%). CVaR(95%) = -0.0137.", "metadata": {"var": -0.011153, "cvar": -0.013674, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240506_0907", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2024-05-06", "context_summary": "SCHP: 60-day return history, mean=0.0001, std=0.0030.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0001, std=0.0030, min=-0.0090, max=0.0045\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SCHP. Express as a decimal (e.g., -0.02).", "answer": "-0.0058", "answer_numeric": -0.005795, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0058 (i.e., on a bad day with 5% probability, the loss exceeds 0.58%). CVaR(95%) = -0.0072.", "metadata": {"var": -0.005795, "cvar": -0.007209, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230519_0909", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-05-19", "context_summary": "XLK: 60-day return history, mean=0.0025, std=0.0117.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0025, std=0.0117, min=-0.0216, max=0.0277\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-18] [\"EXPLAINER-How Montana could enforce a TikTok ban May 18 (Reuters) - Montana took the unusual step on Wednesday of banning Chinese-owned short video app TikTok, with lawmakers of the sparsely populated western U.S. state saying they aimed to protect residents from alleged intelligence gathering by China. TikTok, which is wildly popular with American teens and owned by Chinese tech company ByteDance, is already banned on government-issued devices in around 30 U.S. states and for employees of the country's federal agencies. While blocking apps by geography is not unheard of, the Montana law is notable for doing so at the state level, upending a single-market approach Apple AAPL.O and Alphabet's Google GOOGL.O have long been able to use for their U.S. app stores. Montana's ban is set to take effect on Jan. 1 2024. HAS THIS EVER BEEN DONE BEFORE? Sort of. Tech companies are now well-practiced in blocking apps at the country level, mostly to comply with U.S. sanctions or for business purposes, like Apple's blocking of messaging and privacy apps in China upon government request. Enterprising young people in affected countries have an equally long track record of skirting the bans by downloading the apps while traveling internationally or using tools like virtual private networks (VPNs), which obscure their location. Within the United States, Pornhub recently disabled its services for IP addresses in Utah ahead of a state law that came into effect requiring adult content platforms to verify users' ages. However, that involved a website only, not an app. Specifically for apps, Google and Apple appear to have navigated a tangle of different U.S. state rules around online gambling by leaving compliance to individual app developers, according to their app storeguidance. Google only started allowing gambling apps in its U.S. app store as of 2021, prior to which it restricted the apps in all but four countries: Brazil, France, Ireland and the United Kingdom. Apple and Google declined to comment on how they approach state rules on gambling. IS A STATE-LEVEL BAN EVEN TECHNICALLY FEASIBLE? While TikTok can theoretically block IP addresses registered in Montana, app stores will have a more difficult time. Apple and Google declined comment on the technical aspects of implementing a ban, but TechNet, a trade group funded by both companies, told Montana lawmakers in March that app stores \\\"do not have the ability to geofence on a state-by-state basis.\\\" \\\"It would thus be impossible for our members to prevent the app from being downloaded specifically in the state of Montana,\\\" the TechNet representative testified. According to cybersecurity researchers, that is likely because companies organize their app stores at the country level, meaning they have systems for shutting off downloads of a given app in some countries while keeping it accessible elsewhere. The companies do not appear to have built such controls at a more granular level, the researchers said. \\\"I th\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0146", "answer_numeric": -0.014604, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0146 (i.e., on a bad day with 5% probability, the loss exceeds 1.46%). CVaR(95%) = -0.0191.", "metadata": {"var": -0.014604, "cvar": -0.019101, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231018_0911", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-10-18", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0025, std=0.0247.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0025, std=0.0247, min=-0.0553, max=0.0733\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-17] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0408", "answer_numeric": -0.040846, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0408 (i.e., on a bad day with 5% probability, the loss exceeds 4.08%). CVaR(95%) = -0.0482.", "metadata": {"var": -0.040846, "cvar": -0.048247, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241001_0913", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2024-10-01", "context_summary": "USO: 60-day return history, mean=-0.0031, std=0.0200.", "question": "Asset: USO\nDaily returns (past 60 days): mean=-0.0031, std=0.0200, min=-0.0437, max=0.0441\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USO. Express as a decimal (e.g., -0.02).", "answer": "-0.0334", "answer_numeric": -0.033408, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0334 (i.e., on a bad day with 5% probability, the loss exceeds 3.34%). CVaR(95%) = -0.0388.", "metadata": {"var": -0.033408, "cvar": -0.038762, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230529_0915", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-05-29", "context_summary": "LINK-USD: 60-day return history, mean=-0.0014, std=0.0268.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0014, std=0.0268, min=-0.0940, max=0.0505\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-28] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0407", "answer_numeric": -0.040689, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0407 (i.e., on a bad day with 5% probability, the loss exceeds 4.07%). CVaR(95%) = -0.0644.", "metadata": {"var": -0.040689, "cvar": -0.064443, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240627_0917", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-06-27", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0040, std=0.0393.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0040, std=0.0393, min=-0.0752, max=0.1268\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0668", "answer_numeric": -0.066788, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0668 (i.e., on a bad day with 5% probability, the loss exceeds 6.68%). CVaR(95%) = -0.0703.", "metadata": {"var": -0.066788, "cvar": -0.070309, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230308_0919", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-03-08", "context_summary": "EEM: 60-day return history, mean=0.0002, std=0.0110.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0002, std=0.0110, min=-0.0233, max=0.0296\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-07] [\"Better Ad Tech Stock: The Trade Desk vs. Magnite The Trade Desk (NASDAQ: TTD) and Magnite (NASDAQ: MGNI) are both independent ad tech companies that operate in the shadows of diversified advertising giants like Alphabet's (NASDAQ: GOOG) (NASDAQ: GOOGL) Google and Meta Platforms (NASDAQ: META). Unlike those larger advertising companies, The Trade Desk and Magnite don't lock publishers and advertisers into their walled gardens. Instead, both companies make it easier to purchase ads on desktop, mobile, and connected TV (CTV) platforms across the \\\"open\\\" internet, which doesn't operate under those big tech umbrellas. But over the past 12 months, The Trade Desk's stock declined 28% as Magnite's stock dropped 17%. Image source: Getty Images. Both stocks lost their luster as rising rates and other macro headwinds caused companies to curb their spending on ads. Cautious investors also abandoned higher-growth tech stocks in favor of cheaper value plays. But could either of these fallen ad tech stocks bounce back this year? The differences between The Trade Desk and Magnite The Trade Desk and Magnite are both independent platforms, but they sit at opposite ends of the advertising supply chain. The Trade Desk is a demand-side platform (DSP), which allows advertisers to bid on ad space across a wide range of platforms, while Magnite operates a sell-side platform (SSP), which helps publishers sell their own ad inventories. These two companies are the largest independent players in their respective markets. DSPs typically work in tandem with SSPs to sell digital ads. Google and Meta bundle together DSPs, SSPs, and other advertising services, but they're not independent platforms. However, The Trade Desk recently launched OpenPath, a new feature that bypasses SSPs like Magnite to connect publishers to advertisers. That feature could make it a more diversified advertising company like Google or Meta, but it could also hurt Magnite and other SSPs. The Trade Desk hasn't made any acquisitions since it bought the assets of the ad tech company AdBrain in 2017. Meanwhile, Magnite was created by the merger of two smaller companies, The Rubicon Project and Telaria, in 2020. It then bought the video advertising companies SpotX and SpringServe, as well as the publisher monetization firm Carbon. Therefore, it's fairly easy for investors to track The Trade Desk's growth. Magnite's growth rates need to be reviewed more carefully due to its inorganic growth rates and ex-TAC (excluding traffic acquisition costs) revenues -- which it started using as its core growth metric after its purchase of SpotX in 2021. Which company is growing faster? The Trade Desk's revenue rose 26% in 2020, even as the pandemic throttled the market's demand for digital ads. But in 2021, its revenue increased 43% as the advertising market recovered. In 2022, its revenue rose 32% to $1.58 billion, even as inflation rattled the markets and Apple's (NASDAQ: AAPL) iOS update prevented many advertisers -\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0181", "answer_numeric": -0.018058, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0181 (i.e., on a bad day with 5% probability, the loss exceeds 1.81%). CVaR(95%) = -0.0221.", "metadata": {"var": -0.018058, "cvar": -0.022112, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230125_0921", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-01-25", "context_summary": "BNB-USD: 60-day return history, mean=0.0004, std=0.0267.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0004, std=0.0267, min=-0.1047, max=0.0528\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-24] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0419", "answer_numeric": -0.041851, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0419 (i.e., on a bad day with 5% probability, the loss exceeds 4.19%). CVaR(95%) = -0.0642.", "metadata": {"var": -0.041851, "cvar": -0.064241, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240524_0923", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-05-24", "context_summary": "BNB-USD: 60-day return history, mean=0.0012, std=0.0257.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0012, std=0.0257, min=-0.0706, max=0.0504\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0422", "answer_numeric": -0.042215, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0422 (i.e., on a bad day with 5% probability, the loss exceeds 4.22%). CVaR(95%) = -0.0551.", "metadata": {"var": -0.042215, "cvar": -0.055149, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240729_0925", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-07-29", "context_summary": "LINK-USD: 60-day return history, mean=-0.0048, std=0.0367.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0048, std=0.0367, min=-0.0783, max=0.0741\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0567", "answer_numeric": -0.056663, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0567 (i.e., on a bad day with 5% probability, the loss exceeds 5.67%). CVaR(95%) = -0.0673.", "metadata": {"var": -0.056663, "cvar": -0.06733, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231004_0927", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-10-04", "context_summary": "BNB-USD: 60-day return history, mean=-0.0020, std=0.0145.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0145, min=-0.0575, max=0.0372\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-03] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0278", "answer_numeric": -0.027777, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0278 (i.e., on a bad day with 5% probability, the loss exceeds 2.78%). CVaR(95%) = -0.0398.", "metadata": {"var": -0.027777, "cvar": -0.039759, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230901_0928", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2023-09-01", "context_summary": "TLH: 60-day return history, mean=-0.0008, std=0.0079.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=-0.0008, std=0.0079, min=-0.0177, max=0.0176\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for TLH. Express as a decimal (e.g., -0.02).", "answer": "-0.0135", "answer_numeric": -0.013475, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0135 (i.e., on a bad day with 5% probability, the loss exceeds 1.35%). CVaR(95%) = -0.0164.", "metadata": {"var": -0.013475, "cvar": -0.016384, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231123_0930", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-11-23", "context_summary": "XLE: 60-day return history, mean=-0.0006, std=0.0137.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0006, std=0.0137, min=-0.0319, max=0.0328\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-22] [\"AAPL Factor-Based Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Actor Jamie Foxx accused of sexual abuse in New York lawsuit By Dawn Chmielewski and Steve Gorman Nov 22 (Reuters) - Oscar-winning actor Jamie Foxx was accused of sexual assault in a lawsuit filed in New York City on Wednesday that alleges he groped a woman at a rooftop bar and restaurant in Manhattan in August 2015. The plaintiff, identified in the complaint only as Jan\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLE. Express as a decimal (e.g., -0.02).", "answer": "-0.0205", "answer_numeric": -0.020471, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0205 (i.e., on a bad day with 5% probability, the loss exceeds 2.05%). CVaR(95%) = -0.0262.", "metadata": {"var": -0.020471, "cvar": -0.026202, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240517_0932", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-05-17", "context_summary": "DOT-USD: 60-day return history, mean=-0.0051, std=0.0430.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0051, std=0.0430, min=-0.1359, max=0.0830\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0661", "answer_numeric": -0.066083, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0661 (i.e., on a bad day with 5% probability, the loss exceeds 6.61%). CVaR(95%) = -0.1216.", "metadata": {"var": -0.066083, "cvar": -0.121632, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230705_0934", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-07-05", "context_summary": "DOT-USD: 60-day return history, mean=-0.0012, std=0.0261.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0012, std=0.0261, min=-0.0915, max=0.0558\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-04] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0424", "answer_numeric": -0.042367, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0424 (i.e., on a bad day with 5% probability, the loss exceeds 4.24%). CVaR(95%) = -0.0616.", "metadata": {"var": -0.042367, "cvar": -0.061608, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231225_0936", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-12-25", "context_summary": "VTI: 60-day return history, mean=0.0018, std=0.0083.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0018, std=0.0083, min=-0.0150, max=0.0219\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-22] [\"7 Risks Intel Stock Investors Should Know for 2024 In today's video, I discuss recent updates impacting Intel (NASDAQ: INTC). Check out the short video to learn more, consider subscribing, and click the special offer link below. *Stock prices used were the market prices of Dec. 21, 2023. The video was published on Dec. 21, 2023. Should you invest $1,000 in Intel right now? Before you buy stock in Intel, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now... and Intel wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Stock Advisor provides investors with an easy-to-follow blueprint for success, including guidance on building a portfolio, regular updates from analysts, and two new stock picks each month. The Stock Advisor service has more than tripled the return of S&P 500 since 2002*. See the 10 stocks *Stock Advisor returns as of December 18, 2023 Jose Najarro has positions in Advanced Micro Devices, Nvidia, Qualcomm, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Advanced Micro Devices, Apple, Nvidia, Qualcomm, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Intel and recommends the following options: long January 2023 $57.50 calls on Intel, long January 2025 $45 calls on Intel, and short February 2024 $47 calls on Intel. The Motley Fool has a disclosure policy. Jose Najarro is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"2 Artificial Intelligence (AI) Stocks That Could Go Parabolic Artificial intelligence (AI) stocks have been in the limelight over the past year, thanks to the massive impact this technology is likely to have across multiple industries, with McKinsey estimating that AI adoption could add a whopping $13 trillion to the global economy by 2030. There are many ways investors can capitalize on this huge opportunity. Two companies that stand to win big from AI adoption in two distinct industries are Advanced Micro Devices (NASDAQ: AMD) and SentinelOne (NYSE: S). Both stocks have been on fire in 2023. While shares of AMD have jumped 113%, SentinelOne has shot up 83%, with a big chunk of that jump coming since the beginning of November. The recent stock price action of both companies suggests they may already have gone parabolic -- which refers to a rapid jump in the share price of a company in a short time, similar to the right side of a parabolic curve. However, there is a solid chance that these two AI stocks could go on another parabolic run in 2024. 1. Advanced Micro Devices Nvidia (NAS\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VTI. Express as a decimal (e.g., -0.02).", "answer": "-0.0146", "answer_numeric": -0.01464, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0146 (i.e., on a bad day with 5% probability, the loss exceeds 1.46%). CVaR(95%) = -0.0150.", "metadata": {"var": -0.01464, "cvar": -0.014963, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240117_0938", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2024-01-17", "context_summary": "IYR: 60-day return history, mean=0.0022, std=0.0127.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0022, std=0.0127, min=-0.0239, max=0.0302\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IYR. Express as a decimal (e.g., -0.02).", "answer": "-0.0161", "answer_numeric": -0.016071, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0161 (i.e., on a bad day with 5% probability, the loss exceeds 1.61%). CVaR(95%) = -0.0232.", "metadata": {"var": -0.016071, "cvar": -0.023206, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240529_0939", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-05-29", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0048, std=0.0513.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0048, std=0.0513, min=-0.1442, max=0.1268\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0759", "answer_numeric": -0.075898, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0759 (i.e., on a bad day with 5% probability, the loss exceeds 7.59%). CVaR(95%) = -0.1232.", "metadata": {"var": -0.075898, "cvar": -0.123204, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230327_0941", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-03-27", "context_summary": "SOL-USD: 60-day return history, mean=-0.0015, std=0.0473.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0015, std=0.0473, min=-0.1182, max=0.1144\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-26] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0785", "answer_numeric": -0.078494, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0785 (i.e., on a bad day with 5% probability, the loss exceeds 7.85%). CVaR(95%) = -0.0973.", "metadata": {"var": -0.078494, "cvar": -0.097297, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230830_0943", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-08-30", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0012, std=0.0352.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0012, std=0.0352, min=-0.0789, max=0.1733\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-29] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0475", "answer_numeric": -0.047471, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0475 (i.e., on a bad day with 5% probability, the loss exceeds 4.75%). CVaR(95%) = -0.0636.", "metadata": {"var": -0.047471, "cvar": -0.06363, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230112_0945", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-01-12", "context_summary": "XLV: 60-day return history, mean=0.0015, std=0.0102.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0015, std=0.0102, min=-0.0185, max=0.0244\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-11] [\"Is Apple a Screaming Buy Right Now? For much of 2022, Apple (NASDAQ: AAPL) resisted the market sell-off, but eventually, it succumbed. The tech giant finished the year down 27%, ahead of the Nasdaq but behind the S&P 500. Despite its retreat, the iPhone maker delivered a better performance than most of its big tech peers, reporting revenue growth of 8% for the quarter and the year, even as it faced stiff headwinds from a stronger dollar. Earnings per share growth was slower, up in the fiscal fourth quarter from $1.24 to $1.29, as the company faced inflationary pressure in areas like wages and logistics. However, after the sell-off, Apple stock looks surprisingly well priced. It currently trades at a price-to-earnings ratio of 21, the cheapest it has been since the pandemic started, only slightly more expensive than that of the S&P 500 at 20.2. Is Apple a screaming buy? Let's take a look at the debate. Image source: Getty Images. Why Apple stock has fallen There isn't anything particularly alarming in Apple's recent results, but there are a number of reasons why the stock has tumbled over the last few months. First, the market is increasingly betting on a recession this year as the Federal Reserve continues to raise interest rates. As a seller of higher-end discretionary tech hardware, Apple is at risk of a recession, which would lead consumers to spend less on discretionary products. Even if they needed a new smartphone or computer, they could trade down to a cheaper Apple model or buy one from another company altogether. Second, Apple has faced a number of challenges in its manufacturing in China. The company said in November that its iPhone factory in Zhengzhou was operating at significantly limited capacity, meaning it expected shipments of its iPhone 14 Pro and Pro Max to be lower in the fiscal first quarter than originally anticipated. The company did say that demand for those phones remains strong. The COVID-19 lockdowns that caused those delays have since ended, so the problem should be temporary. However, Apple also announced plans to move more production out of China. Finally, the company's revenue approached $400 billion in fiscal 2022, and its growth is expected to be moderate. On such a large base of revenue, it will be difficult to put up 20% revenue growth. However, the valuation seems to reflect the dialed-down growth expectations. The good news With an earnings valuation on par with the S&P 500, Apple doesn't need to put up high growth numbers in order to justify its valuation. In fact, the company could easily grow earnings per share by double digits with just modest revenue and share buybacks. Apple has been committed to share buybacks, having reduced shares outstanding by more than 20% over the last five years. With the stock price down, it could get more aggressive with repurchases. The company's economic moat has also never looked as strong. Apple has gained market share on Android and now claims a majority of market share \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLV. Express as a decimal (e.g., -0.02).", "answer": "-0.0148", "answer_numeric": -0.01476, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0148 (i.e., on a bad day with 5% probability, the loss exceeds 1.48%). CVaR(95%) = -0.0175.", "metadata": {"var": -0.01476, "cvar": -0.017516, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240611_0947", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-06-11", "context_summary": "EFA: 60-day return history, mean=0.0005, std=0.0069.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0005, std=0.0069, min=-0.0163, max=0.0134\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 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blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0128", "answer_numeric": -0.01276, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0128 (i.e., on a bad day with 5% probability, the loss exceeds 1.28%). CVaR(95%) = -0.0152.", "metadata": {"var": -0.01276, "cvar": -0.015185, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240912_0949", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2024-09-12", "context_summary": "EWJ: 60-day return history, mean=0.0010, std=0.0135.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0010, std=0.0135, min=-0.0325, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 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us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EWJ. Express as a decimal (e.g., -0.02).", "answer": "-0.0205", "answer_numeric": -0.020476, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0205 (i.e., on a bad day with 5% probability, the loss exceeds 2.05%). CVaR(95%) = -0.0325.", "metadata": {"var": -0.020476, "cvar": -0.032508, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20241126_0951", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2024-11-26", "context_summary": "XLE: 60-day return history, mean=0.0009, std=0.0127.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0009, std=0.0127, min=-0.0328, max=0.0369\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2024-11-20] nvda-20241027 0001045810 1/26 2025 Q3 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 0 550 456 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2024-01-29 2024-10-27 0001045810 2024-11-15 0001045810 2024-07-29 2024-10-27 0001045810 2023-07-31 2023-10-29 0001045810 2023-01-30 2023-10-29 0001045810 2024-10-27 0001045810 2024-01-28 0001045810 us-gaap:CommonStockMember 2024-07-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-28 0001045810 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-29 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-07-29 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-27 0001045810 us-gaap:RetainedEarningsMember 2024-10-27 0001045810 us-gaap:CommonStockMember 2023-07-30 0001045810 us-gaap:AdditionalPaidInCapitalMember 2023-07-30 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-30 0001045810 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us-gaap:EmployeeStockMember 2024-01-29 2024-10-27 0001045810 us-gaap:USTreasurySecuritiesMember 2024-10-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2024-10-27 0001045810 us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-10-27 0001045810 us-gaap:CertificatesOfDepositMember 2024-10-27 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-10-27 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-29 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-07-29 2024-10-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2024-01-28 0001045810 us-gaap:USTreasurySecuritiesMember 2024-01-28 0001045810 us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-01-28 0001045810 us-gaap:CertificatesOfDepositMember 2024-01-28 0001045810 us-gaap:ForeignGovernmentDebtMember 2024-01-28 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-10-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLE. Express as a decimal (e.g., -0.02).", "answer": "-0.0202", "answer_numeric": -0.020199, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0202 (i.e., on a bad day with 5% probability, the loss exceeds 2.02%). CVaR(95%) = -0.0281.", "metadata": {"var": -0.020199, "cvar": -0.028128, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20241128_0952", "template": "T2", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["PALL"], "decision_date": "2024-11-28", "context_summary": "PALL: 60-day return history, mean=0.0005, std=0.0267.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=0.0005, std=0.0267, min=-0.0558, max=0.0592\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for PALL. Express as a decimal (e.g., -0.02).", "answer": "-0.0350", "answer_numeric": -0.03499, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0350 (i.e., on a bad day with 5% probability, the loss exceeds 3.50%). CVaR(95%) = -0.0478.", "metadata": {"var": -0.03499, "cvar": -0.047835, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230103_0954", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-01-03", "context_summary": "XLB: 60-day return history, mean=0.0010, std=0.0156.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0010, std=0.0156, min=-0.0337, max=0.0327\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-30] [\"Have $500? These 2 Stocks Could Be Bargain Buys for 2023 and Beyond Regularly adding money to stocks can be one of the smartest financial moves you make. The popular market barometer, the S&P 500 index, has returned 11% per year since 1950, which includes several market crashes along the way. The key is consistency. Adding $500 per month to growing companies will put you well on the way to retiring a millionaire. Here are two bargain growth stocks that are begging to be bought right now. 1. MercadoLibre The growth of global e-commerce is expected to hit $58 trillion worldwide by 2028, and one of the fastest-growing e-commerce regions in the world is Latin America. Argentina, Brazil, and Mexico are seeing explosive growth in online sales, serving as a strong tailwind for MercadoLibre (NASDAQ: MELI) -- the leading online-commerce ecosystem in Latin America. MercadoLibre connects buyers and sellers through its online marketplace. It offers mobile payments both online and at the point of sale, consumer credit, and shipping and advertising services to small businesses. A vast number of transactions in Latin America are still completed with cash, which lends to a long runway of growth, and this is clearly reflected in the company's recent performance. In the third quarter, revenue and total payment volume were up 61% and 76%, respectively, in local currency. MercadoLibre's fintech business reached 40 million active users, representing the most quarterly additions to its ecosystem in the last two years. What's more, MercadoLibre is reinvesting in marketing and technology for more growth while reporting an improving operating profit margin. Its recent growth is testament to the company's competitive advantages in selection, price competitiveness, and the overall effectiveness of its merchant services. The market is severely undervaluing the company's improving profitability. Despite continuing to post robust growth, the stock sells at a low valuation of 27 times trailing free cash flow. This stock is a good bet at these levels. 2. Roku The growing adoption of smart TVs and streaming is still a huge opportunity for leading developers of TV operating systems. The market for connected TVs is expected to grow about 15% per year through 2026, according to Mordor Intelligence. This opportunity is attracting many competitors, including Apple, Samsung, Alphabet's Android, and Amazon, that offer their own devices and software. But Roku (NASDAQ: ROKU) has the leading market share in the U.S. The stock fell hard over the past year, as sales of TVs dropped amid supply chain issues and inflation pressuring consumer spending. But these headwinds will eventually clear and send Roku off to the races. Investors only need to look at the company's recent numbers to see the value here. Even with lower sales of streaming devices dragging down Roku's growth, the company's platform segment, which includes advertising revenue, increased by 15% year over year in the third quar\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLB. Express as a decimal (e.g., -0.02).", "answer": "-0.0251", "answer_numeric": -0.025088, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0251 (i.e., on a bad day with 5% probability, the loss exceeds 2.51%). CVaR(95%) = -0.0303.", "metadata": {"var": -0.025088, "cvar": -0.030346, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230417_0956", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-04-17", "context_summary": "BNB-USD: 60-day return history, mean=0.0018, std=0.0226.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0018, std=0.0226, min=-0.0545, max=0.0740\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-16] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0337", "answer_numeric": -0.033651, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0337 (i.e., on a bad day with 5% probability, the loss exceeds 3.37%). CVaR(95%) = -0.0446.", "metadata": {"var": -0.033651, "cvar": -0.044562, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20241219_0958", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-19", "context_summary": "SPY: 60-day return history, mean=0.0004, std=0.0073.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0004, std=0.0073, min=-0.0274, max=0.0208\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 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The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SPY. Express as a decimal (e.g., -0.02).", "answer": "-0.0094", "answer_numeric": -0.009365, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0094 (i.e., on a bad day with 5% probability, the loss exceeds 0.94%). CVaR(95%) = -0.0200.", "metadata": {"var": -0.009365, "cvar": -0.02003, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240226_0960", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-02-26", "context_summary": "LINK-USD: 60-day return history, mean=0.0027, std=0.0396.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0027, std=0.0396, min=-0.0687, max=0.1160\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0552", "answer_numeric": -0.055211, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0552 (i.e., on a bad day with 5% probability, the loss exceeds 5.52%). CVaR(95%) = -0.0651.", "metadata": {"var": -0.055211, "cvar": -0.065117, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20231114_0962", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2023-11-14", "context_summary": "TIP: 60-day return history, mean=0.0001, std=0.0015.", "question": "Asset: TIP\nDaily returns (past 60 days): mean=0.0001, std=0.0015, min=-0.0028, max=0.0045\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for TIP. Express as a decimal (e.g., -0.02).", "answer": "-0.0020", "answer_numeric": -0.002019, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0020 (i.e., on a bad day with 5% probability, the loss exceeds 0.20%). CVaR(95%) = -0.0026.", "metadata": {"var": -0.002019, "cvar": -0.002612, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20231101_0964", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-11-01", "context_summary": "DOT-USD: 60-day return history, mean=0.0012, std=0.0229.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0012, std=0.0229, min=-0.0397, max=0.0967\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-31] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0323", "answer_numeric": -0.032307, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0323 (i.e., on a bad day with 5% probability, the loss exceeds 3.23%). CVaR(95%) = -0.0370.", "metadata": {"var": -0.032307, "cvar": -0.037007, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240119_0966", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-01-19", "context_summary": "ICSH: 60-day return history, mean=0.0003, std=0.0003.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0003, std=0.0003, min=-0.0002, max=0.0010\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ICSH. Express as a decimal (e.g., -0.02).", "answer": "-0.0002", "answer_numeric": -0.000199, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0002 (i.e., on a bad day with 5% probability, the loss exceeds 0.02%). CVaR(95%) = -0.0002.", "metadata": {"var": -0.000199, "cvar": -0.000199, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240509_0968", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2024-05-09", "context_summary": "EMB: 60-day return history, mean=0.0003, std=0.0049.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0003, std=0.0049, min=-0.0155, max=0.0082\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EMB. Express as a decimal (e.g., -0.02).", "answer": "-0.0073", "answer_numeric": -0.007298, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0073 (i.e., on a bad day with 5% probability, the loss exceeds 0.73%). CVaR(95%) = -0.0124.", "metadata": {"var": -0.007298, "cvar": -0.012403, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230320_0970", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2023-03-20", "context_summary": "MORT: 60-day return history, mean=-0.0019, std=0.0174.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=-0.0019, std=0.0174, min=-0.0405, max=0.0249\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MORT. Express as a decimal (e.g., -0.02).", "answer": "-0.0354", "answer_numeric": -0.035358, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0354 (i.e., on a bad day with 5% probability, the loss exceeds 3.54%). CVaR(95%) = -0.0398.", "metadata": {"var": -0.035358, "cvar": -0.039831, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20230809_0972", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2023-08-09", "context_summary": "VNQ: 60-day return history, mean=0.0005, std=0.0101.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0005, std=0.0101, min=-0.0250, max=0.0244\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VNQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0147", "answer_numeric": -0.014673, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0147 (i.e., on a bad day with 5% probability, the loss exceeds 1.47%). CVaR(95%) = -0.0227.", "metadata": {"var": -0.014673, "cvar": -0.022731, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240215_0974", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-02-15", "context_summary": "VEA: 60-day return history, mean=0.0011, std=0.0074.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0011, std=0.0074, min=-0.0180, max=0.0168\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2024-02-02] amzn-20231231 false 2023 FY 0001018724 http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent http://fasb.org/us-gaap/2023#OtherAssetsNoncurrent P3Y P1Y P1Y http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2023#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization 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Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VEA. Express as a decimal (e.g., -0.02).", "answer": "-0.0110", "answer_numeric": -0.010984, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0110 (i.e., on a bad day with 5% probability, the loss exceeds 1.10%). CVaR(95%) = -0.0157.", "metadata": {"var": -0.010984, "cvar": -0.015705, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20241122_0976", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-11-22", "context_summary": "ETH-USD: 60-day return history, mean=0.0050, std=0.0339.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0050, std=0.0339, min=-0.0592, max=0.1245\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0419", "answer_numeric": -0.041889, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0419 (i.e., on a bad day with 5% probability, the loss exceeds 4.19%). CVaR(95%) = -0.0516.", "metadata": {"var": -0.041889, "cvar": -0.051631, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240607_0978", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-06-07", "context_summary": "QUAL: 60-day return history, mean=0.0005, std=0.0073.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0005, std=0.0073, min=-0.0148, max=0.0161\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 us-gaap:BorrowingsMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:RealEstateFundsMember 2024-03-31 0001364742 blk:IcapitalMember 2024-03-31 0001364742 blk:EquityMutualFundInvestmentsMember us-gaap:FairValueInputsLevel3Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 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0001364742 us-gaap:HedgeFundsEquityMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2023-12-31 0001364742 blk:FourPointSevenZeroPercentNotesDueTwoThousandTwentyNineMember 2024-01-01 2024-03-31 0001364742 blk:CarriedInterestMember us-gaap:ConsolidatedEntitiesMember 2023-12-31 0001364742 us-gaap:RetainedEarningsUnappropriatedMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember us-gaap:DebtSecuritiesMember 2024-03-31 0001364742 us-gaap:ParentMember 2022-12-31 0001364742 us-gaap:OtherLiabilitiesMember 2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QUAL. Express as a decimal (e.g., -0.02).", "answer": "-0.0128", "answer_numeric": -0.012758, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0128 (i.e., on a bad day with 5% probability, the loss exceeds 1.28%). CVaR(95%) = -0.0142.", "metadata": {"var": -0.012758, "cvar": -0.014151, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20240918_0980", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-09-18", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0018, std=0.0472.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0018, std=0.0472, min=-0.0828, max=0.1466\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0645", "answer_numeric": -0.064546, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0645 (i.e., on a bad day with 5% probability, the loss exceeds 6.45%). CVaR(95%) = -0.0778.", "metadata": {"var": -0.064546, "cvar": -0.077755, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230303_0982", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-03-03", "context_summary": "SOL-USD: 60-day return history, mean=0.0150, std=0.0708.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0150, std=0.0708, min=-0.1182, max=0.2870\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-02] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0677", "answer_numeric": -0.067742, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0677 (i.e., on a bad day with 5% probability, the loss exceeds 6.77%). CVaR(95%) = -0.0969.", "metadata": {"var": -0.067742, "cvar": -0.096892, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20240408_0984", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2024-04-08", "context_summary": "IYR: 60-day return history, mean=-0.0005, std=0.0103.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=-0.0005, std=0.0103, min=-0.0203, max=0.0252\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IYR. Express as a decimal (e.g., -0.02).", "answer": "-0.0165", "answer_numeric": -0.016533, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0165 (i.e., on a bad day with 5% probability, the loss exceeds 1.65%). CVaR(95%) = -0.0195.", "metadata": {"var": -0.016533, "cvar": -0.019504, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20241114_0986", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-11-14", "context_summary": "DOT-USD: 60-day return history, mean=0.0029, std=0.0373.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0029, std=0.0373, min=-0.0695, max=0.1337\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0564", "answer_numeric": -0.05643, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0564 (i.e., on a bad day with 5% probability, the loss exceeds 5.64%). CVaR(95%) = -0.0660.", "metadata": {"var": -0.05643, "cvar": -0.066024, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230914_0988", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-09-14", "context_summary": "IVV: 60-day return history, mean=0.0003, std=0.0064.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0003, std=0.0064, min=-0.0141, max=0.0143\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-13] [\"US presses on with fight against Google's search and advertising clout By Diane Bartz WASHINGTON, Sept 13 (Reuters) - The Justice Department questioned a former Google executive about billion-dollar deals with mobile carriers and others that helped make Google the default search engine, in the second day of a once-in-a-generation antitrust trial on Wednesday. Chris Barton, who was at Google from 2004 to 2011, said the company was quick to see the advantage of people using Google search on handheld devices and early versions of smartphones, spurring dramatic growth in the number of Google executives working on deals to win default status with mobile carriers. Google's clout in search, the government argues, has helped Google, a $1 trillion company, build monopolies in some aspects of online search advertising. Since search is free, Google makes its money through advertising. The government says the Alphabet IncGOOGL.Ounit paid $10 billion annually to wireless companies like AT&T T.N, device makers like Apple AAPL.O and browser makers like Mozilla to fend off rivals and keep its search engine's market share at around 90%. Barton testified that in negotiating revenue-sharing deals with mobile carriers and Android smartphone makers, Google pressed for its search to be the default and to be exclusive. If Microsoft's search engine Bing was the default on an Android phone, Barton said, then users would have a \\\"difficult time finding or changing to Google.\\\" Barton said on his LinkedIn profile that he was responsible for leading Google's partnerships with mobile carriers like Verizon and AT&T, estimating that the deals \\\"drive hundreds of millions in revenue.\\\" Google attorney John Schmidtlein said in opening arguments on Tuesday that the government was wrong to say that Google broke the law to hold onto its massive market share, noting its search engine was wildly popular because of its quality and that the payments were fair compensation for partners. The fight has major implications for Big Tech, which has been accused of buying or strangling small rivals but has defended itself by pointing out that its services are free, as in the case of Google, or inexpensive, as in the case of Amazon.com AMZN.O. Previous major antitrust trials include Microsoft, filed in 1998, and AT&T, filed in 1974. The AT&T breakup in 1982 is credited with paving the way for the modern cell phone industry, while the fight with Microsoft is credited with opening space for Google and others on the internet. The government's first witness Tuesday was Google economist Hal Varian, who was asked about discussions inside the company about the importance of scale and of Google becoming the default on home pages. If Google is found to have broken the law, Judge Amit Mehta, who is deciding the case, will then decide how best to resolve it. He may decide simply to order Google to stop practices he has found to be illegal or he may order Google to sell assets. EXPLAINER-Why is the US su\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IVV. Express as a decimal (e.g., -0.02).", "answer": "-0.0084", "answer_numeric": -0.008383, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0084 (i.e., on a bad day with 5% probability, the loss exceeds 0.84%). CVaR(95%) = -0.0130.", "metadata": {"var": -0.008383, "cvar": -0.012992, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20230301_0989", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2023-03-01", "context_summary": "VLUE: 60-day return history, mean=-0.0006, std=0.0105.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0006, std=0.0105, min=-0.0242, max=0.0251\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-28] [\"The Zacks Analyst Blog Highlights Apple, Linde, Marsh & McLennan Companies, GSK and Expedia For Immediate Release Chicago, IL \\u2013 February 28, 2023 \\u2013 Zacks.com announces the list of stocks featured in the Analyst Blog. Every day the Zacks Equity Research analysts discuss the latest news and events impacting stocks and the financial markets. Stocks recently featured in the blog include: Apple Inc. AAPL, Linde plc LIN, Marsh & McLennan Companies, Inc. MMC, GSK plc GSK and Expedia Group, Inc. EXPE. Here are highlights from Monday\\u2019s Analyst Blog: Top Analyst Reports from Apple, Linde and Marsh & McLennan The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc., Linde plc and Marsh & McLennan Companies, Inc. These research reports have been hand-picked from the roughly 70 reports published by our analyst team today. You can see all of today\\u2019s research reports here >>> Shares of Apple have roughly matched the broader market over the past year (-10.4% for Apple vs. -10.9% for the S&P 500 index), but handily outperformed the Zacks Tech sector (down - 19.8%). The Zacks analyst covering Apple expects year-over-year revenue growth to decelerate in the fiscal first quarter compared with the fiscal fourth quarter due to unfavorable forex. Mac revenues are expected to be negatively impacted by forex. Apple expects Mac revenues to decline substantially year over year during the December quarter. Services revenue growth is expected to be negatively impacted by challenging macroeconomic conditions, unfavorable forex, as well as weakness in digital advertising and gaming. Nevertheless, a growing subscriber base in the Services business and a strong liquidity position are key catalysts. (You can read the full research report on Apple here >>>) Linde shares have outperformed the Zacks Chemical - Diversified industry over the past year (+18.6% vs. +10.3%). The company\\u2019s wide range of applications for its industrial gases, Linde is making the world more productive by the day. The company\\u2019s primary products in industrial gases include oxygen, which is used as life support in hospitals. Its process gas, like hydrogen, is being utilized for clean fuels, while its high-purity and specialty gases are employed to manufacture electronics. Linde has long-term contracts with on-site customers backed by minimum purchase requirements, thereby securing stable cashflows. In the profitable industrial gas market, the merger of Praxair and Linde has created an efficient player with considerable size advantages. However, the cost of sales continues to increase, hurting the firm\\u2019s bottom line. The firm has mostly been paying a lower dividend yield than the industry\\u2019s composite stocks over the past two years. (You can read the full research report on Linde here >>>) Marsh & McLennan shares have outperformed the Zacks Insurance - Bro\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0172", "answer_numeric": -0.017164, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0172 (i.e., on a bad day with 5% probability, the loss exceeds 1.72%). CVaR(95%) = -0.0220.", "metadata": {"var": -0.017164, "cvar": -0.022014, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20240709_0991", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2024-07-09", "context_summary": "STIP: 60-day return history, mean=0.0004, std=0.0010.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0004, std=0.0010, min=-0.0029, max=0.0024\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for STIP. Express as a decimal (e.g., -0.02).", "answer": "-0.0011", "answer_numeric": -0.001122, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0011 (i.e., on a bad day with 5% probability, the loss exceeds 0.11%). CVaR(95%) = -0.0021.", "metadata": {"var": -0.001122, "cvar": -0.002116, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20240307_0993", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-03-07", "context_summary": "EEM: 60-day return history, mean=0.0009, std=0.0093.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0009, std=0.0093, min=-0.0245, max=0.0225\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K UNH 2024-02-28] unh-20231231 false 2023 FY 0000731766 12/31 10 50 http://fasb.org/us-gaap/2023#OtherLiabilities P4Y P4Y P5Y P3Y 1/1/2026 1/1/2042 1/1/2024 1/1/2043 0.038 0.046 0.019 0.043 0.007 0.012 0.297 0.306 0.306 0.308 0.292 0.298 0.013 0.015 0.012 0.012 0.013 0.015 4.605251141552511 4.702283105022831 4.802054794520548 5.502739726027397 4.202283105022831 5.502739726027397 1.2993150684931507 0000731766 2023-01-01 2023-12-31 0000731766 2023-06-30 iso4217:USD 0000731766 2024-01-31 xbrli:shares 0000731766 2023-12-31 0000731766 2022-12-31 iso4217:USD xbrli:shares 0000731766 2022-01-01 2022-12-31 0000731766 2021-01-01 2021-12-31 0000731766 us-gaap:ProductMember 2023-01-01 2023-12-31 0000731766 us-gaap:ProductMember 2022-01-01 2022-12-31 0000731766 us-gaap:ProductMember 2021-01-01 2021-12-31 0000731766 us-gaap:ServiceMember 2023-01-01 2023-12-31 0000731766 us-gaap:ServiceMember 2022-01-01 2022-12-31 0000731766 us-gaap:ServiceMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2020-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2020-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2020-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2020-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2020-12-31 0000731766 2020-12-31 0000731766 us-gaap:RetainedEarningsMember 2021-01-01 2021-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2021-01-01 2021-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2021-01-01 2021-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2021-01-01 2021-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2021-01-01 2021-12-31 0000731766 us-gaap:CommonStockMember 2021-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2021-12-31 0000731766 us-gaap:RetainedEarningsMember 2021-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2021-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2021-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2021-12-31 0000731766 2021-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-01-01 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-01-01 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-01-01 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-01-01 2022-12-31 0000731766 us-gaap:CommonStockMember 2022-01-01 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-01-01 2022-12-31 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-12-31 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-12-31 0000731766 us-gaap:CommonStockMember 2023-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2023-12-31 0000731766 unh:EmployeeStockPurchasePlanESPPMember 2023-01-01 2023-12-31 xbrli:pure 0000731766 2024-01-01 2023-12-31 0000731766 unh:ProductsandservicesMember 2023-12-31 0000731766 unh:ProductsandservicesMember 2022-12-31 0000731766 us-gaap:HealthInsuranceProductLineMember 2023-12-31 0000731766 unh:PharmaceuticalManufacturerRebatesReceivableMember 2023-12-31 0000731766 unh:PharmaceuticalManufacturerRebatesReceivableMember 2022-12-31 0000731766 unh:UsefulLifeMember 2023-01-01 2023-12-31 0000731766 us-gaap:FurnitureAndFixturesMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:FurnitureAndFixturesMember 2023-12-31 0000731766 us-gaap:BuildingMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember us-gaap:BuildingMember 2023-12-31 0000731766 unh:CapitalizedsoftwareMember srt:MinimumMember 2023-12-31 0000731766 srt:MaximumMember unh:CapitalizedsoftwareMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0000731766 us-gaap:OtherCurrentLiabilitiesMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2021-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-01-01 2023-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2022-01-01 2022-12-31 0000731766 unh:RedeemableNoncontrollingInterestsMember 2023-12-31 0000731766 us-gaap:RestrictedStockMember 2023-01-01 2023-12-31 0000731766 unh:StockOptionsandSARsMember 2023-01-01 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:USTreasuryAndGovernmentMember 2022-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2022-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0152", "answer_numeric": -0.015172, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0152 (i.e., on a bad day with 5% probability, the loss exceeds 1.52%). CVaR(95%) = -0.0206.", "metadata": {"var": -0.015172, "cvar": -0.02056, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20231025_0995", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-10-25", "context_summary": "EEM: 60-day return history, mean=-0.0020, std=0.0089.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0020, std=0.0089, min=-0.0242, max=0.0158\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-24] [\"US STOCKS-Wall Street eyes higher open as Treasury yields retreat; earnings in focus For a Reuters live blog on U.S., UK and European stock markets, click LIVE/ or type LIVE/ in a news window. Coca-Cola raises annual sales forecast 3M raises FY adjusted profit forecast GM withdraws 2023 guidance, beats Q3 profit estimates General Electric raises FY profit forecast Futures up: Dow 0.50%, S&P 0.58%, Nasdaq 0.59% Updated at 8:37 a.m. ET/ 1237 GMT By Shubham Batra and Shashwat Chauhan Oct 24 (Reuters) - Wall Street's main indexes were set to open higher as a selloff in U.S. Treasuries eased on Tuesday, while shares of General Electric and Coca-Cola surged on upbeat forecasts. General ElectricGE.N jumped 5.9% in premarket trading after the aircraft engine manufacturer lifted its full-year profit forecast, while Coca-ColaKO.N advanced 2.8% on raising its annual sales outlook. General MotorsGM.N added 1.3% after beating third-quarter profit estimates, while 3MMMM.N gained 4.5% after raising its full-year adjusted profit forecast. The yield on the 10-year Treasury note US10YT=RR was last at 4.8504%, after breaching the 5% mark in the previous session. \\\"Yesterday, Bill Ackman, head at Pershing Square, (who's) been very bearish on U.S. bonds for a number of months closed that bearish position ... he's got a very good track record from a macro perspective of calling things well in the past,\\\" said Dan Boardman-Weston, chief executive officer at BRI Wealth Management. \\\"The impact that interest rates have on an economy are lagged, so we're only now just really starting to see those rate increases bite and start to impact the underlying economy.\\\" Megacaps including Apple AAPL.O, Tesla TSLA.O, Meta Platforms META.O and Amazon.com AMZN.O rose between 0.2% and 2.4%. U.S. technology giants are expected to post their strongest quarterly revenue growth in at least a year as their legacy businesses have stabilized, with Microsoft MSFT.O and Alphabet GOOGL.O scheduled to report results after markets close on Tuesday. Of the 86 companies in the S&P 500 .SPX that have reported earnings so far, 78% have topped analysts' expectations, LSEG data showed. Overall, third-quarter earnings are expected to rise 1.2% year-on-year. The benchmark index has fallen sharply from its July highs on worries the Federal Reserve could keep its monetary policy restrictive for longer than expected against the backdrop of a still-strong economy, though the index is up nearly 10% this year as of last close. On the data front, investors will closely monitor the S&P Global Purchasing Managers' Index for manufacturing and services to assess the strength of the American economy. The Commerce Department will announce third-quarter GDP on Thursday, which is seen accelerating to 4.3%. Its wide-ranging Personal Consumption Expenditures (PCE) report is due on Friday. The turmoil in the Middle East is also in focus as Israel intensifies its assault on Hamas in Gaza. At 8:37 a.m. ET, Dow e-minis 1YM\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EEM. Express as a decimal (e.g., -0.02).", "answer": "-0.0148", "answer_numeric": -0.014832, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0148 (i.e., on a bad day with 5% probability, the loss exceeds 1.48%). CVaR(95%) = -0.0190.", "metadata": {"var": -0.014832, "cvar": -0.019008, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20231206_0997", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-12-06", "context_summary": "AVAX-USD: 60-day return history, mean=0.0154, std=0.0552.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0154, std=0.0552, min=-0.1393, max=0.2132\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-05] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0569", "answer_numeric": -0.056881, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0569 (i.e., on a bad day with 5% probability, the loss exceeds 5.69%). CVaR(95%) = -0.1046.", "metadata": {"var": -0.056881, "cvar": -0.104612, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20230131_0998", "template": "T2", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2023-01-31", "context_summary": "XHB: 60-day return history, mean=0.0015, std=0.0164.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0015, std=0.0164, min=-0.0384, max=0.0435\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XHB. Express as a decimal (e.g., -0.02).", "answer": "-0.0233", "answer_numeric": -0.023283, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0233 (i.e., on a bad day with 5% probability, the loss exceeds 2.33%). CVaR(95%) = -0.0325.", "metadata": {"var": -0.023283, "cvar": -0.032491, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230601_0001", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-06-01", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0875, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0033, std=0.0286, worst_day=-0.1052\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-31] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0875 (i.e., a 8.75% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0875 = 1.1427, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.08751, "expected_loss": 0.08751, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231219_0004", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-12-19", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0912, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0081, std=0.0411, worst_day=-0.0973\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-18] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0912 (i.e., a 9.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0912 = 1.0969, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.091162, "expected_loss": 0.091162, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230407_0007", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2023-04-07", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0226, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0004, std=0.0110, worst_day=-0.0240\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-06] [\"Guru Fundamental Report for AAPL - Warren Buffett Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Patient Investor model based on the published strategy of Warren Buffett. This strategy seeks out firms with long-term, predictable profitability and low debt that trade at reasonable valuations. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 100% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. EARNINGS PREDICTABILITY: PASS DEBT SERVICE: PASS RETURN ON EQUITY: PASS RETURN ON TOTAL CAPITAL: PASS FREE CASH FLOW: PASS USE OF RETAINED EARNINGS: PASS SHARE REPURCHASE: PASS INITIAL RATE OF RETURN: PASS EXPECTED RETURN: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Warren Buffett Warren Buffett Portfolio Top Warren Buffett Stocks About Warren Buffett: Warren Buffett is considered by many to be the greatest investor of all time. As the chairman of Berkshire Hathaway, Buffett has consistently outperformed the S&P 500 for decades, and in the process has become one of the world's richest men. (Forbes puts his net worth at $37 billion.) Despite his fortune, Buffett is known for living a modest lifestyle, by billionaire standards. His primary residence remains the gray stucco Nebraska home he purchased for $31,500 nearly 50 years ago, according to Forbes, and his folksy Midwestern manner and penchant for simple pleasures -- a cherry Coke, a good burger, and a good book are all near the top of the list -- have been well-documented. Additional Research Links Factor-Based Stock Portfolios Factor-Based ETF Portfolios Harry Browne Permanent Portfolio Ray Dalio All Weather Portfolio About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"3 Cryptos That Day Traders Love Right Now InvestorPlace - Stock Market News, Stock Advice & Trading Tips Cryptocurrencies delivered huge gains for investors during the previous bull market. Yet, more than a few got wiped o\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VLUE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0226 (i.e., a 2.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0226 = 4.4321, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022563, "expected_loss": 0.022563, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230517_0009", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-05-17", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0610, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0006, std=0.0254, worst_day=-0.0799\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-16] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0610 (i.e., a 6.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0610 = 1.6387, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.061023, "expected_loss": 0.061023, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230919_0012", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-09-19", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0530, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0042, std=0.0183, worst_day=-0.0588\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-18] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0530 (i.e., a 5.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0530 = 1.8884, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.052956, "expected_loss": 0.052956, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240626_0015", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-06-26", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1051, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0002, std=0.0548, worst_day=-0.1133\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9516", "answer_numeric": 0.9516, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1051 (i.e., a 10.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1051 = 0.9516, capped at 1.0.\nMaximum position size = 0.9516 (95.2% of portfolio).", "metadata": {"var_99": -0.105088, "expected_loss": 0.105088, "max_drawdown_threshold": 0.1, "position_size": 0.9516, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20231122_0018", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-11-22", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.0976, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0020, std=0.0589, worst_day=-0.1157\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-21] [\"AAPL Quantitative Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"EXPLAINER-What is Black Friday? And will shoppers find bargains this year? By Juveria Tabassum, Savyata Mishra Nov 16 (Reuters) - Retailers are preparing for what they hope will be yet another record-setting global shopping spree on Black Friday, the fourth Friday of November, which this year is Nov. 24. Known for crowds lining up at big-box stores to pounce on doorbuste\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. 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Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0001 (i.e., a 0.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0001 = 711.3036, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000141, "expected_loss": 0.000141, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240423_0024", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-04-23", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0102, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0003, std=0.0049, worst_day=-0.0109\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0102 (i.e., a 1.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0102 = 9.7825, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010222, "expected_loss": 0.010222, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230124_0026", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2023-01-24", "context_summary": "TLH: 60-day history, VaR(99%)=-0.0162, max drawdown threshold=10%.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=0.0011, std=0.0098, worst_day=-0.0175\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to TLH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0162 (i.e., a 1.62% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0162 = 6.1681, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016212, "expected_loss": 0.016212, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230728_0029", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-07-28", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1092, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0035, std=0.0451, worst_day=-0.1591\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-27] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9161", "answer_numeric": 0.9161, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1092 (i.e., a 10.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1092 = 0.9161, capped at 1.0.\nMaximum position size = 0.9161 (91.6% of portfolio).", "metadata": {"var_99": -0.109161, "expected_loss": 0.109161, "max_drawdown_threshold": 0.1, "position_size": 0.9161, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240202_0032", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2024-02-02", "context_summary": "HYG: 60-day history, VaR(99%)=-0.0062, max drawdown threshold=10%.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0010, std=0.0038, worst_day=-0.0063\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to HYG, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0062 (i.e., a 0.62% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0062 = 16.0121, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.006245, "expected_loss": 0.006245, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231013_0035", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2023-10-13", "context_summary": "EMB: 60-day history, VaR(99%)=-0.0110, max drawdown threshold=10%.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=-0.0010, std=0.0059, worst_day=-0.0112\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EMB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0110 (i.e., a 1.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0110 = 9.0648, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011032, "expected_loss": 0.011032, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231024_0038", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2023-10-24", "context_summary": "BIL: 60-day history, VaR(99%)=-0.0000, max drawdown threshold=10%.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0002, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BIL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0000 (i.e., a 0.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0000 = 2242.4251, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -4.5e-05, "expected_loss": 4.5e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240815_0040", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-08-15", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0852, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0042, std=0.0371, worst_day=-0.1002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0852 (i.e., a 8.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0852 = 1.1740, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.085178, "expected_loss": 0.085178, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230626_0043", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-06-26", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0653, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0017, std=0.0252, worst_day=-0.0915\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-25] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0653 (i.e., a 6.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0653 = 1.5322, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.065266, "expected_loss": 0.065266, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230531_0048", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2023-05-31", "context_summary": "DBC: 60-day history, VaR(99%)=-0.0232, max drawdown threshold=10%.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=-0.0006, std=0.0105, worst_day=-0.0233\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DBC, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0232 (i.e., a 2.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0232 = 4.3045, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023232, "expected_loss": 0.023232, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241212_0051", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-12-12", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0250, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0004, std=0.0117, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0250 (i.e., a 2.50% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0250 = 3.9997, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025002, "expected_loss": 0.025002, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230117_0054", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-01-17", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0434, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0048, std=0.0260, worst_day=-0.0438\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-13] [\"Tim Cook\\u2019s pay re-enters earth\\u2019s atmosphere Reuters Reuters NEW YORK (Reuters Breakingviews) - How to compensate Apple Chief Executive Tim Cook is one of the more puzzling questions for corporate governance experts. His pay has been out of this world, but then so has the iPhone maker\\u2019s share price performance. Nonetheless Apple, its investors and its board have agreed Cook\\u2019s pay should orbit closer to Earth in 2023. The $2.1 trillion company has comfortably outperformed rivals over the past three years, with shareholder returns including reinvested dividends in the top percentile among its peers, according to Institutional Shareholder Services. Likewise, his annual compensation of $99 million in 2022 was over 4 times the median of peers, who include Amazon.com\\u2019s Andrew Jassy and AT&T\\u2019s John Stankey. On Friday, Apple said Cook\\u2019s targeted pay will fall to $49 million. That\\u2019s an improvement, but still generous. Apple says it will target his pay between 80th and 90th percentile among peers in future years. A bigger improvement is making Cook\\u2019s pay less of a giveaway. In 2022, half of his award of Apple stock paid out automatically over time \\u2013 so all he had to do is wait. Now it\\u2019s 75% performance-based, and his unvested time-based awards lapse if he retires. This is hardly space-age stuff, but at least Apple\\u2019s pay is no longer stuck in the past. (By Robert Cyran) Follow @Breakingviews on Twitter Capital Calls - More concise insights on global finance: BlackRock edges closer to its Blackstone roots The fog lifts for Didi's path to normalcy Inflation drop gives Fed leeway to save jobs Gaming\\u2019s winter of discontent bolsters M&A logic TSMC foots the bill for global chip supremacy (Editing by John Foley and Amanda Gomez) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Don't Ignore These Companies' Cash-Generating Abilities It goes without saying that searching for stocks can be challenging, especially with an extensive list of options available. However, one way to cut out the bad apples is by focusing on stocks with strong free cash flow. But what is free cash flow, and why does it matter? In its simplest form, free cash flow is the amount of cash a company keeps after paying for operating costs and capital expenditures. A high free cash flow allows for more growth opportunities, a greater potential for share buybacks, consistent dividend payouts, and the ability to pay off debt easily. Three companies \\u2013 Apple AAPL, Alphabet GOOGL, and Verizon Communications VZ \\u2013 all generate substantial cash. Below is a chart illustrating the performance of all three stocks over the last year, with the S&P 500 blended in as a benchmark. Image Source: Zacks Investment Research Let\\u2019s take a closer look at each one. Apple We\\u2019re all familiar with the legendary Apple, the company that\\u2019s entirely ch\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to FXI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0434 (i.e., a 4.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0434 = 2.3066, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.043354, "expected_loss": 0.043354, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240610_0057", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2024-06-10", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0144, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0002, std=0.0077, worst_day=-0.0150\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0144 (i.e., a 1.44% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0144 = 6.9511, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014386, "expected_loss": 0.014386, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240201_0060", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2024-02-01", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0206, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0015, std=0.0117, worst_day=-0.0239\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VNQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0206 (i.e., a 2.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0206 = 4.8580, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020585, "expected_loss": 0.020585, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241225_0063", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PPLT"], "decision_date": "2024-12-25", "context_summary": "PPLT: 60-day history, VaR(99%)=-0.0301, max drawdown threshold=10%.", "question": "Asset: PPLT\nDaily returns (past 60 days): mean=-0.0006, std=0.0136, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PPLT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0301 (i.e., a 3.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0301 = 3.3236, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030088, "expected_loss": 0.030088, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230920_0066", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2023-09-20", "context_summary": "PALL: 60-day history, VaR(99%)=-0.0340, max drawdown threshold=10%.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=-0.0000, std=0.0161, worst_day=-0.0346\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PALL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0340 (i.e., a 3.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0340 = 2.9382, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034034, "expected_loss": 0.034034, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230512_0069", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-05-12", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0295, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0017, std=0.0133, worst_day=-0.0300\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-11] [\"TMF, SPXN: Big ETF Inflows Comparing units outstanding versus one week ago at the coverage universe of ETFs at ETF Channel, the biggest inflow was seen in the DIREXION DAILY 20-YR TREASURY BULL 3X Shares, which added 12,750,000 units, or a 7.0% increase week over week. And on a percentage change basis, the ETF with the biggest increase in inflows was the ProShares S&P 500 Ex-Financials ETF, which added 80,000 units, for a 37.2% increase in outstanding units. Among the largest underlying components of SPXN, in morning trading today Apple is down about 0.5%, and Microsoft is lower by about 1%. VIDEO: TMF, SPXN: Big ETF Inflows The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple supplier Foxconn's Q1 profit slumps 56% y/y, lags forecasts Adds details TAIPEI, May 11 (Reuters) - Apple Inc AAPL.O supplier Foxconn 2317.TW reported on Thursday a 56% fall in first-quarter net profit, lagging forecasts in its biggest quarterly fall in three years, as global economic woes hurt demand for smart consumer electronics. The Taiwanese company, which is the world's largest contract electronics maker, said net profit for the January-March quarter fell to T$12.8 billion ($417.17 million) from T$29.45 billion in the same period the previous year. It was much worse than an average forecast of T$29.18 billion profit from 13 analysts, according to Refinitiv. Foxconn said it expected revenue for its key consumer electronics products to decline year on year in the second quarter. That group includes smartphones and makes up more than half of Foxconn's total revenue. It expects revenues for cloud and networking products in 2023 to be flat, compared to a previous forecast of significant growth for those sectors. Overall, revenues for the second quarter would fall, while full-year revenues would be flat, the Taiwanese company said. Foxconn earlier this year forecast revenue to be flat for 2023. ($1 = 30.6830 Taiwan dollars) (Reporting by Yimou Lee; Editing by Jacqueline Wong and Sonali Paul) ((ben.blanchard@thomsonreuters.com)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Get Exposure to NVIDIA Stock Price, Options Income in New YieldMax ETF YieldMax announced the launch of the YieldMax NVDA Option Income Strategy ETF (NYSE Arca: NVDY). The actively managed fund seeks to generate monthly income via a synthetic covered call strategy on NVIDIA (NVDA) stock. The fund, which ZEGA Financial actively manages, does not invest directly in NVDA. As part of its strategy, NVDY will write (sell) call option contracts on NVDA to generate income. Since the fund does not directly own NVDA, these written call options will be sold short. The call options that NVDY writes will generally have an expiration of one month or less. They\\u2019ll have a strike price that is around 5% to 15% above the then-current NVDA\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0295 (i.e., a 2.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0295 = 3.3850, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029542, "expected_loss": 0.029542, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230504_0072", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-05-04", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0863, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0464, worst_day=-0.1006\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-03] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0863 (i.e., a 8.63% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0863 = 1.1587, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.086302, "expected_loss": 0.086302, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240620_0074", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-06-20", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0184, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0009, std=0.0084, worst_day=-0.0232\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0184 (i.e., a 1.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0184 = 5.4481, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018355, "expected_loss": 0.018355, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240503_0077", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-03", "context_summary": "SPY: 60-day history, VaR(99%)=-0.0147, max drawdown threshold=10%.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0004, std=0.0075, worst_day=-0.0160\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SPY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0147 (i.e., a 1.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0147 = 6.7808, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014747, "expected_loss": 0.014747, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230410_0080", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2023-04-10", "context_summary": "PDBC: 60-day history, VaR(99%)=-0.0232, max drawdown threshold=10%.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=-0.0003, std=0.0107, worst_day=-0.0234\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PDBC, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0232 (i.e., a 2.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0232 = 4.3110, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023197, "expected_loss": 0.023197, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230911_0083", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-09-11", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0677, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0049, std=0.0334, worst_day=-0.0789\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-10] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0677 (i.e., a 6.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0677 = 1.4770, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.067706, "expected_loss": 0.067706, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240411_0086", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2024-04-11", "context_summary": "CSHI: 60-day history, VaR(99%)=-0.0005, max drawdown threshold=10%.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0004, worst_day=-0.0006\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CSHI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0005 (i.e., a 0.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0005 = 206.6521, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000484, "expected_loss": 0.000484, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230929_0088", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-09-29", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0221, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0008, std=0.0100, worst_day=-0.0242\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-28] [\"US STOCKS-Wall St set for lower open on rate jitters; Powell on deck By Ankika Biswas and Shashwat Chauhan Sept 28 (Reuters) - Wall Street's main indexes eyed a lower open on Thursday aselevated oil prices muddled the inflation outlook amid worries over prolonged restrictive monetary policy, while investors assessed data and awaited Federal Reserve chief Jerome Powell's remarks. The scope for interest rates staying higher for longer than anticipated has solidified with soaring energy prices keeping headline inflation elevated. Deepening the concerns, U.S. oil futures jumped to a more than one-year high on Thursday. Riding on the back of higher crude prices, energy .SPNY is set to emerge as the only major S&P 500 sector to notch monthly gains. Meanwhile, rate-sensitive information technology .SPLRCT and real estate .SPLRCT were on track to be the worst hit. Further, data showed the U.S. economy maintained a fairly strong pace of growth in the second quarter, the government confirmed on Thursday, and appears to have gathered momentum this quarter amid a resilient labor market. \\\"A sharp rise in unemployment and claims isn't a prerequisite for the Fed to stop raising rates,\\\" said Nancy Vanden Houten, lead U.S. economist at Oxford Economics. \\\"Fed Chair Powell made clear last week, however, that the Fed needs to see other signs that the labor market is continuing to come into better balance if it is to refrain from further rate hikes.\\\" As U.S. Treasury yields resumed their uptrend after briefly slipping following the data, megacap growth stocks including Apple AAPL.O, Microsoft MSFT.O, Amazon.com AMZN.O and Tesla TSLA.O shed between 0.1% and 1.2% in premarket trading. At 8:52 a.m. ET, Dow e-minis 1YMcv1 were down 32 points, or 0.09%, S&P 500 e-minis EScv1 were down 6.75 points, or 0.16%, and Nasdaq 100 e-minis NQcv1 were down 45 points, or 0.31%. All the three indexes are set for their first quarterly decline in 2023. Also on radar will be comments by Powell at 4 p.m. ET, as well as remarks by voting member Lisa Cook during the day. With a partial government shutdown just three days away, a procedural vote on a bipartisan short-term spending measure by the Senate on Thursday will also be closely watched. Among individual movers, Micron TechnologyMU.O dropped 2.8% after forecasting a bigger-than-expected first-quarter loss. WorkdayWDAY.O dipped 9.8% after the human resources software company lowered its subscription revenue growth outlook for the next three years. Meme darling GameStopGME.N jumped 7.3% after the company named billionaire activist investor Ryan Cohen as its CEO and chairman. (Reporting by Ankika Biswas and Shashwat Chauhan; Editing by Sriraj Kalluvila and Maju Samuel) ((Ankika.Biswas@thomsonreuters.com; Shashwat.Chauhan@thomsonreuters.com)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"SCHX ETF: A Large-Cap ETF for Large Gains The Schwab U.S.\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0221 (i.e., a 2.21% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0221 = 4.5326, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022062, "expected_loss": 0.022062, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231106_0091", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-11-06", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0155, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=-0.0004, std=0.0084, worst_day=-0.0165\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:FairValueInputsLevel2Member 2023-09-30 0000320193 us-gaap:CashMember 2022-09-24 0000320193 us [...TRUNCATED...] Document Set for the consolidated financial statements and accompanying notes in Part II, Item 8, “Financial Statements and Supplementary Data” of this Annual Report on Form 10-K. Apple Inc. | 2023 Form 10-K | 56 Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 104** Inline XBRL for the cover page of this Annual Report on Form 10-K, included in the Exhibit 101 Inline XBRL Document Set. * Indicates management contract or compensatory plan or arrangement. ** Filed herewith. *** Furnished herewith. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Registrant hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. Item 16.    Form 10-K Summary None. Apple Inc. | 2023 Form 10-K | 57 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: November 2, 2023 Apple Inc. By: /s/ Luca Maestri Luca Maestri Senior Vice President, Chief Financial Officer Power of Attorney KNOW ALL PERSONS BY THESE PRESENTS, that each person whose signature appears below constitutes and appoints Timothy D. Cook and Luca Maestri, jointly and severally, his or her attorneys-in-fact, each with the power of substitution, for him or her in any and all capacities, to sign any amendments to this Annual Report on Form 10-K, and to file the same, with exhibits thereto and other documents in connection therewith, with the Securities and Exchange Commission, hereby ratifying and confirming all that each of said attorneys-in-fact, or his substitute or substitutes, may do or cause to be done by virtue hereof. Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated: Name Title Date /s/ Timothy D. Cook Chief Executive Officer and Director (Principal Executive Officer) November 2, 2023 TIMOTHY D. COOK /s/ Luca Maestri Senior Vice President, Chief Financial Officer (Principal Financial Officer) November 2, 2023 LUCA MAESTRI /s/ Chris Kondo Senior Director of Corporate Accounting (Principal Accounting Officer) November 2, 2023 CHRIS KONDO /s/ James A. Bell Director November 2, 2023 JAMES A. BELL /s/ Al Gore Director November 2, 2023 AL GORE /s/ Alex Gorsky Director November 2, 2023 ALEX GORSKY /s/ Andrea Jung Director November 2, 2023 ANDREA JUNG /s/ Arthur D. Levinson Director and Chair of the Board November 2, 2023 ARTHUR D. LEVINSON /s/ Monica Lozano Director November 2, 2023 MONICA LOZANO /s/ Ronald D. Sugar Director November 2, 2023 RONALD D. SUGAR /s/ Susan L. Wagner Director November 2, 2023 SUSAN L. WAGNER Apple Inc. | 2023 Form 10-K | 58\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0155 (i.e., a 1.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0155 = 6.4642, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01547, "expected_loss": 0.01547, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240619_0094", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-06-19", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0612, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0019, std=0.0342, worst_day=-0.0678\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0612 (i.e., a 6.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0612 = 1.6340, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.061199, "expected_loss": 0.061199, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231102_0096", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-11-02", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0477, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0039, std=0.0286, worst_day=-0.0553\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-01] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0477 (i.e., a 4.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0477 = 2.0975, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.047676, "expected_loss": 0.047676, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230126_0098", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-01-26", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0577, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0052, std=0.0268, worst_day=-0.0775\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-25] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0577 (i.e., a 5.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0577 = 1.7325, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.057721, "expected_loss": 0.057721, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230503_0100", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2023-05-03", "context_summary": "JNK: 60-day history, VaR(99%)=-0.0108, max drawdown threshold=10%.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=0.0002, std=0.0056, worst_day=-0.0142\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to JNK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0108 (i.e., a 1.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0108 = 9.2223, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010843, "expected_loss": 0.010843, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230130_0102", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-01-30", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0303, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0002, std=0.0141, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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srt:MaximumMember us-gaap:LandAndLandImprovementsMember 2022-01-01 2022-12-31 0000012927 us-gaap:MachineryAndEquipmentMember srt: [...TRUNCATED...] rm 130 Table of Contents 31.1 Certification of Chief Executive Officer pursuant to Section 302 of Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 99.1 Commercial Program Method of Accounting (Exhibit (99)(i) to the Company’s Form 10-K for the year ended December 31, 1997) 101.SCH XBRL Taxonomy Extension Schema Document 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF XBRL Taxonomy Extension Definition Linkbase Document 101.LAB XBRL Taxonomy Extension Label Linkbase Document 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page XBRL tags are embedded within the Inline XBRL document contained in Exhibit 101 * Management contract or compensatory plan In accordance with Item 601(b)(4)(iii)(A) of Regulation S-K, copies of certain instruments defining the rights of holders of long-term debt of the Company are not filed herewith. Pursuant to this regulation, we hereby agree to furnish a copy of any such instrument to the SEC upon request. Item 16. Form 10-K Summary None. 131 Table of Contents Signatures Pursuant to the requirements of Section 13 of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on January 27, 2023. THE BOEING COMPANY (Registrant) By:   /s/ Carol J. Hibbard   Carol J. Hibbard – Senior Vice President and Controller 132 Table of Contents Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated on January 27, 2023. /s/ David L. Calhoun /s/ Stayce D. Harris David L. Calhoun – President and Chief Executive Officer and Director Stayce D. Harris – Director (Principal Executive Officer) /s/ Brian J. West /s/ Akhil Johri Brian J. West – Executive Vice President and Chief Financial Officer Akhil Johri – Director (Principal Financial Officer) /s/ Carol J. Hibbard /s/ David L. Joyce Carol J. Hibbard – Senior Vice President and Controller David L. Joyce – Director (Principal Accounting Officer) /s/ Robert A. Bradway /s/ Lawrence W. Kellner Robert A. Bradway – Director Lawrence W. Kellner – Chair of the Board /s/ Lynne M. Doughtie /s/ Steven M. Mollenkopf Lynne M. Doughtie – Director Steven M. Mollenkopf – Director /s/ David L. Gitlin /s/ John M. Richardson David L. Gitlin – Director John M. Richardson – Director /s/ Lynn J. Good /s/ Ronald A. Williams Lynn J. Good – Director Ronald A. Williams – Director 133\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0303 (i.e., a 3.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0303 = 3.2990, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030312, "expected_loss": 0.030312, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20230810_0105", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-08-10", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1101, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0011, std=0.0518, worst_day=-0.1366\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-09] [\"US STOCKS-Wall Street falls ahead of CPI inflation data By Bansari Mayur Kamdar and Johann M Cherian Aug 9 (Reuters) - Wall Street's main indexes fell on Wednesday ahead of a key inflation report this week, with investors also assessing remarks from U.S. Federal Reserve officials. Rate-sensitive megacap growth and technology stocks, that have led the Wall Street rally this year, such as Nvidia NVDA.O, Apple AAPL.O and Tesla TSLA.O were down between 1.3% and 4.6%. \\\"We think that at this point there is some profit taking and retrenchment in the short term on the card,\\\" said Aadil Zaman, partner at Wall Street Alliance Group. Philadelphia Fed President Patrick Harker said on Tuesday the U.S. central bank may be at the stage where it can leave interest rates unchanged, barring any abrupt change in the direction of recent economic data. However, Fed Governor Michelle Bowman on Monday said the combination of still-elevated inflation and continued economic growth meant further rate increases are likely. Traders expect an 86.5% chance of no rate hike at the Fed's next policy meeting in September, according to CME FedWatch Tool. The Consumer Price Index (CPI) for July, due on Thursday, is expected to show a slight year-over-year acceleration. On a month-to-month basis, consumer prices are seen increasing 0.2%, the same rate as in June. \\\"CPI won't be major surprise. It's going to be either matching expectations most likely or slightly better than expectation, showing that inflation is cooling off,\\\" Zaman added. Wall Street's main indexes ended the previous session lower in a broad selloff after the downgrading of several small and mid-sized banks by credit rating agency Moody's. Big banks extended losses on Wednesday, with Bank of America BAC.N and Wells Fargo WFC.N down 1.0% and 1.5%, respectively. Adding to concerns about the global economy, China's consumer sector fell into deflation and factory-gate prices extended declines in July, as the world's second-largest economy struggled to revive demand. At 11:33 a.m. ET, the Dow Jones Industrial Average .DJI was down 154.86 points, or 0.44%, at 35,159.63, the S&P 500 .SPX was down 27.85 points, or 0.62%, at 4,471.53, and the Nasdaq Composite .IXIC was down 164.88 points, or 1.19%, at 13,719.44. Seven of the top 11 S&P 500 sectors rose, led by gains in energy stocks .SPNY, that increased 1.6%, touching a near six-month high, tracking a jump in crude oil prices. O/R Casino owner Penn Entertainment's PENN.O shares jumped 7.6% on a $2 billion deal with Walt Disney's ESPN DIS.N to launch a sports betting business. Walt Disney's shares rose 0.8% ahead of its quarterly results due after the bell. LyftLYFT.O signaled it would double down on competitive pricing to catch up with rival Uber UBER.N, taking the shine off its strong earnings forecast and sending the company's shares down 5.4%. Of the 443 S&P 500 companies that have reported results as of Tuesday, 78.6% beat analyst expectations, according to Refinit\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9084", "answer_numeric": 0.9084, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1101 (i.e., a 11.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1101 = 0.9084, capped at 1.0.\nMaximum position size = 0.9084 (90.8% of portfolio).", "metadata": {"var_99": -0.11008, "expected_loss": 0.11008, "max_drawdown_threshold": 0.1, "position_size": 0.9084, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231030_0107", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2023-10-30", "context_summary": "UNG: 60-day history, VaR(99%)=-0.0587, max drawdown threshold=10%.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=-0.0003, std=0.0267, worst_day=-0.0615\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to UNG, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0587 (i.e., a 5.87% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0587 = 1.7041, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.058682, "expected_loss": 0.058682, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241129_0109", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2024-11-29", "context_summary": "CSHI: 60-day history, VaR(99%)=-0.0005, max drawdown threshold=10%.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0003, worst_day=-0.0008\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CSHI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0005 (i.e., a 0.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0005 = 197.3517, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000507, "expected_loss": 0.000507, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230411_0112", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-04-11", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0672, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0060, std=0.0447, worst_day=-0.1006\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-10] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0672 (i.e., a 6.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0672 = 1.4870, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.067249, "expected_loss": 0.067249, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231107_0115", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-11-07", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0266, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0009, std=0.0132, worst_day=-0.0277\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-06] [\"Is Fidelity Quality Factor ETF (FQAL) a Strong ETF Right Now? Making its debut on 09/12/2016, smart beta exchange traded fund Fidelity Quality Factor ETF (FQAL) provides investors broad exposure to the Style Box - Large Cap Blend category of the market. What Are Smart Beta ETFs? For a long time now, the ETF industry has been flooded with products based on market capitalization weighted indexes, which are designed to represent the broader market or a particular market segment. Investors who believe in market efficiency should consider market cap indexes, as they replicate market returns in a low-cost, convenient, and transparent way. If you're the kind of investor who would rather try and beat the market through good stock selection, then smart beta funds are your best choice; this fund class is known for tracking non-cap weighted strategies. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index Because the fund has amassed over $314.58 million, this makes it one of the average sized ETFs in the Style Box - Large Cap Blend. FQAL is managed by Fidelity. Before fees and expenses, this particular fund seeks to match the performance of the Fidelity U.S. Quality Factor Index. The Fidelity U.S. Quality Factor Index reflects the performance of stocks of large and mid-capitalization U.S. companies with a higher quality profile than the broader market. Cost & Other Expenses Expense ratios are an important factor in the return of an ETF and in the long-term, cheaper funds can significantly outperform their more expensive cousins, other things remaining the same. Operating expenses on an annual basis are 0.29% for this ETF, which makes it on par with most peer products in the space. It has a 12-month trailing dividend yield of 1.38%. Sector Exposure and Top Holdings It is important to delve into an ETF's holdings before investing despite the many upsides to these kinds of funds like diversified exposure, which minimizes single stock risk. And, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 27.20% of the portfolio, the fund has heaviest allocation to the Information Technology sector; Financials and Healthcare round out the top three. Taking into account individual holdings, Apple Inc (AAPL) accounts for about 7.69% of the fund's total assets, followed by Microsoft Corp (MSFT) and Alphabet Inc Cl A (GOOGL). The top 10 holdings account for about 31.41% of total assets under management. Performance and Risk So far this year, FQAL has added about 13.80%, and it's up approximately 17.68% in the last on\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0266 (i.e., a 2.66% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0266 = 3.7573, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026615, "expected_loss": 0.026615, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240617_0118", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-06-17", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0693, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0007, std=0.0338, worst_day=-0.0806\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0693 (i.e., a 6.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0693 = 1.4431, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069295, "expected_loss": 0.069295, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231201_0120", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-12-01", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0186, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0000, std=0.0070, worst_day=-0.0209\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-30] [\"UK antitrust regulator wins appeal over Apple probe Adds details from ruling and CMA comment in paragraphs 4-6 LONDON, Nov 30 (Reuters) - Britain's antitrust regulator won an appeal on Thursday against a ruling blocking its investigation into Apple Inc's AAPL.O mobile browser and cloud gaming services. The Competition and Markets Authority (CMA) opened a full investigation last year into the dominance of Apple and Alphabet Inc's Google GOOGL.O in mobile browsers, and the possibility of the iPhone maker restricting the cloud gaming market through its app store. Apple argued that the CMA had \\\"no power\\\" to launch such an inquiry because it did so too late and the Competition Appeal Tribunal (CAT) ruled in Apple's favour in March, but the Court of Appeal in London overturned that decision on Thursday. Judge Nicholas Green said in a written ruling that the CAT had \\\"lost sight\\\" of the CMA's role to \\\"promote competition and protect consumers\\\". Sarah Cardell, chief executive of the CMA, welcomed the decision which she said \\\"gives the CMA the backing it needs to protect consumers and promote competition in UK\\\". She added that the CMA is ready to reopen the investigation \\\"when the legal process is complete\\\". (Reporting by Sam Tobin; editing by Michael Holden) ((Sam.Tobin@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Japan aircon king Daikin looks to custom chips for energy savings By Sam Nussey and Miho Uranaka TOKYO, Dec 1 (Reuters) - Japanese air conditioner maker Daikin Industries 6367.T is turning to custom-made semiconductors to eke out energy savings, as companies increasingly look to bespoke chip designs to enhance performance. As tech heavyweights such as Apple AAPL.O and Amazon AMZN.O spend heavily on custom cutting-edge chips, companies using legacy chips are also looking to introduce custom silicon. Osaka-headquartered Daikin, which expects to make 10 million home air conditioners in the current financial year, said it is partnering with a Japanese design company to customise logic chips for inverters used in its air conditioners. Inverters adjust the speed of an air conditioner's motor to save energy. They are standard in Japan and the European Union but less common in the United States. The custom chips, to be made by Taiwan's TSMC 2330.TW, cost more than off-the-shelf alternatives but offer better energy efficiency and allow a reduction in the use of other components, according to a Daikin executive. \\\"To bring out the full performance of an air conditioner's compressor and motor, we need to improve chip performance or we will hit a limit,\\\" Yuji Yoneda, general manger of Daikin's technology and innovation centre, said in an interview. Daikin plans to start introducing the chips in high-end air conditioners from 2025 and is looking at using them in about a fifth of units by the end of the decade. The company, which deve\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0186 (i.e., a 1.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0186 = 5.3657, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018637, "expected_loss": 0.018637, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231113_0123", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-11-13", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0186, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0009, std=0.0071, worst_day=-0.0209\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-10] [\"RPT-EXPLAINER-What is China\\u2019s Singles Day, and how is it celebrated? By Granth Vanaik Nov 9 (Reuters) - Black Friday? No. Cyber Monday? Nope. Prime Day? Absolutely not. The world's biggest shopping event happens in China each year - and it's called Singles Day. Originally a holiday to celebrate being single, as a counter to Valentine's Day, the event has grown into a weeks-long online shopping festival that peaks on Nov. 11. WHEN DID THE IDEA OF SINGLES DAY ORIGINATE? The idea for Singles Day had originated at China's Nanjing University back in 1993 and was originally called \\\"Bachelor's Day.\\\" On the day, single people treat themselves with gifts and presents, while also organizing social gatherings and parties. HOW MUCH DO CONSUMERS SPEND? Last year, the total value of goods sold during the shopping bonanza - also known as \\\"Double 11\\\" - totaled 1.15 trillion yuan ($157.97 billion), according to data from consultancy firm Bain. That is more than four times the $35.3 billion U.S. shoppers spent last year during Cyber Week, the period from Black Friday to Cyber Monday, per data from Adobe Analytics. Cyber Monday immediately follows Black Friday, which falls on the day after the U.S. Thanksgiving Day holiday, the busiest shopping day of the year in the United States. But growth has been slowing even as overall sales for Singles Day hit record highs, with last year's 3% rise marking the slowest increase ever. The event has in recent years lost some of its novelty with the rise of other shopping festivals in China,including the midyear \\\"618\\\" sales that are the country's second largest. Strict COVID-19 curbs in China impacted sales last year, but several industry experts are expecting a rebound, as the economy improves and livestream sales remain robust. \\\"We're optimistic about growth this year because the recovery seems to be stabilizing and consumption is on a more clear upward trend,\\\" said Jacob Cooke, co-founder and CEO of Beijing-based WPIC Marketing + Technologies. His e-commerce consultancy firm expects sales for the Chinese shopping event to rise in the range between 14% and 18% from last year, which is higher than Adobe's projection for a 5.4% rise in Cyber Week sales. WHAT MAJOR BRANDS AND PRODUCTS ARE SHOPPERS BUYING? JD.com 9618.HK joined in 2012 and PDD Holdings-owned PDD.O Pinduoduo has also become a significant player, offering low cost products in competition with Alibaba-owned Tmall and Taobao platforms. Last year, Chinese shoppers spent more on essentials, supplements, vitamins and pet-care products. Those products are expected to stay in demand this year, along with more lifestyle-focused products such as athletic wear and sports equipment. \\\"There is enormous demand among Chinese consumers for products and services that improve their lifestyles and facilitate self-expression,\\\" Cooke said. HOW DOES SINGLES DAY COMPARE TO BLACK FRIDAY? In comparison, U.S. shoppers last year had bought more Pokemon toys, Hot Wheels, TVs,\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0186 (i.e., a 1.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0186 = 5.3657, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018637, "expected_loss": 0.018637, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241111_0126", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2024-11-11", "context_summary": "REZ: 60-day history, VaR(99%)=-0.0212, max drawdown threshold=10%.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0012, std=0.0096, worst_day=-0.0219\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to REZ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0212 (i.e., a 2.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0212 = 4.7249, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021165, "expected_loss": 0.021165, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240305_0128", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2024-03-05", "context_summary": "CSHI: 60-day history, VaR(99%)=-0.0006, max drawdown threshold=10%.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0004, worst_day=-0.0009\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CSHI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0006 (i.e., a 0.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0006 = 165.3861, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000605, "expected_loss": 0.000605, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230302_0130", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-03-02", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0542, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0059, std=0.0272, worst_day=-0.0632\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-01] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0542 (i.e., a 5.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0542 = 1.8466, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.054154, "expected_loss": 0.054154, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241015_0133", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2024-10-15", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0204, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0014, std=0.0085, worst_day=-0.0286\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VNQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0204 (i.e., a 2.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0204 = 4.8989, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020413, "expected_loss": 0.020413, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240701_0136", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-07-01", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0238, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0015, std=0.0121, worst_day=-0.0248\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0238 (i.e., a 2.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0238 = 4.2023, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023796, "expected_loss": 0.023796, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240313_0139", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-03-13", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0694, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0070, std=0.0373, worst_day=-0.0703\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0694 (i.e., a 6.94% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0694 = 1.4418, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069357, "expected_loss": 0.069357, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230526_0142", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-05-26", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0674, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0318, worst_day=-0.0861\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-25] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0674 (i.e., a 6.74% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0674 = 1.4847, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.067355, "expected_loss": 0.067355, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230727_0144", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-07-27", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0113, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0017, std=0.0069, worst_day=-0.0123\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-26] [\"Machine Learning Megatrends: 3 AI Stocks Set to Dominate InvestorPlace - Stock Market News, Stock Advice & Trading Tips There\\u2019s no denying the strength and momentum we\\u2019ve seen in AI stocks this year. In fact, the top AI stocks have played an enormous role in the stock market\\u2019s robust returns so far this year. While the S&P 500 was searching for direction in the first quarter, Microsoft (NASDAQ:MSFT) and Nvidia (NASDAQ:NVDA) were bombarding higher as catalyst after catalyst continued to pave the way for its AI advances. Together, the duo now accounts for more than $3.6 trillion in combined market capitalizations. However, they have ignited plenty of other stocks higher along the way, too. Some of these firms are well-known tech companies. Others are smaller, lesser-known entities in the high-growth space. Either way, the trend remains robust. Earlier this year, Billionaire investor Stanley Druckenmiller said AI could be as \\u201ctransformative as the internet.\\u201d If that\\u2019s the case, let\\u2019s look at a few of the top AI stocks to buy now. AI Stocks to Dominate: Nvidia (NVDA) Source: sdx15 / Shutterstock.com There\\u2019s no denying that Nvidia is the most dominant name in AI right now. In some measures, it has no competition, so while its stock gains are astronomical (and even somewhat comical), what\\u2019s going to stop Nvidia from printing money at this moment? Nothing! Shares are currently up more than 215% so far this year and up more than 300% from the 2022 lows. Going into earnings in late May, the stock was up almost 110%, and the bullish bets had been piling up. I distinctly remember most investors assuming it couldn\\u2019t go much higher, as it had made up almost all of its bear market losses and run a great deal going into the event. Then the company blew out expectations, while management guided for current-quarter revenue of roughly $11 billion vs. expectations of just $7 billion, and the stock erupted. Shares closed higher by almost 25% the next day and have now climbed 50% since that report. My point is, what if Nvidia has another massive revenue guidance this quarter? What company is stepping in to soak up the excess demand for its AI chips? For now, Nvidia remains at the forefront of AI domination. Best Machine Learning Stocks: Alphabet (GOOGL, GOOG) Source: IgorGolovniov / Shutterstock.com ChatGPT is owned by OpenAI, a firm that Microsoft had invested in previously but made another big investment in earlier this year. That\\u2019s as the company\\u2019s ChatGPT platform exploded in popularity, garnering more than 100 million active users in record time. In the minds of investors, that made Microsoft a top AI play seemingly overnight. To pour salt on the wound for Alphabet (NASDAQ:GOOGL, NASDAQ:GOOG), the company had a somewhat embarrassing gaff with its own AI chat platform, Bard. Now, there are a few things to take note of here. First, Alphabet hasn\\u2019t been the best at building out platforms outside of \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VTI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0113 (i.e., a 1.13% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0113 = 8.8388, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011314, "expected_loss": 0.011314, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230627_0147", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-06-27", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0196, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0005, std=0.0094, worst_day=-0.0229\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-26] [\"Is Trending Stock Apple Inc. (AAPL) a Buy Now? Apple (AAPL) has been one of the most searched-for stocks on Zacks.com lately. So, you might want to look at some of the facts that could shape the stock's performance in the near term. Shares of this maker of iPhones, iPads and other products have returned +6.4% over the past month versus the Zacks S&P 500 composite's +5% change. The Zacks Computer - Mini computers industry, to which Apple belongs, has gained 8.7% over this period. Now the key question is: Where could the stock be headed in the near term? Although media reports or rumors about a significant change in a company's business prospects usually cause its stock to trend and lead to an immediate price change, there are always certain fundamental factors that ultimately drive the buy-and-hold decision. Earnings Estimate Revisions Here at Zacks, we prioritize appraising the change in the projection of a company's future earnings over anything else. That's because we believe the present value of its future stream of earnings is what determines the fair value for its stock. We essentially look at how sell-side analysts covering the stock are revising their earnings estimates to reflect the impact of the latest business trends. And if earnings estimates go up for a company, the fair value for its stock goes up. A higher fair value than the current market price drives investors' interest in buying the stock, leading to its price moving higher. This is why empirical research shows a strong correlation between trends in earnings estimate revisions and near-term stock price movements. Apple is expected to post earnings of $1.18 per share for the current quarter, representing a year-over-year change of -1.7%. Over the last 30 days, the Zacks Consensus Estimate has changed +0.1%. For the current fiscal year, the consensus earnings estimate of $5.99 points to a change of -2% from the prior year. Over the last 30 days, this estimate has remained unchanged. For the next fiscal year, the consensus earnings estimate of $6.64 indicates a change of +10.8% from what Apple is expected to report a year ago. Over the past month, the estimate has changed -0.1%. Having a strong externally audited track record, our proprietary stock rating tool, the Zacks Rank, offers a more conclusive picture of a stock's price direction in the near term, since it effectively harnesses the power of earnings estimate revisions. Due to the size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, Apple is rated Zacks Rank #3 (Hold). The chart below shows the evolution of the company's forward 12-month consensus EPS estimate: 12 Month EPS Projected Revenue Growth While earnings growth is arguably the most superior indicator of a company's financial health, nothing happens as such if a business isn't able to grow its revenues. After all, it's nearly impossible for a company to increase its earnings for an extended period witho\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0196 (i.e., a 1.96% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0196 = 5.0920, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019639, "expected_loss": 0.019639, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240819_0150", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DBB"], "decision_date": "2024-08-19", "context_summary": "DBB: 60-day history, VaR(99%)=-0.0258, max drawdown threshold=10%.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=-0.0014, std=0.0113, worst_day=-0.0296\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DBB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0258 (i.e., a 2.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0258 = 3.8786, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025783, "expected_loss": 0.025783, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230102_0151", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-01-02", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0383, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0028, std=0.0171, worst_day=-0.0385\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-30] [\"Have $500? These 2 Stocks Could Be Bargain Buys for 2023 and Beyond Regularly adding money to stocks can be one of the smartest financial moves you make. The popular market barometer, the S&P 500 index, has returned 11% per year since 1950, which includes several market crashes along the way. The key is consistency. Adding $500 per month to growing companies will put you well on the way to retiring a millionaire. Here are two bargain growth stocks that are begging to be bought right now. 1. MercadoLibre The growth of global e-commerce is expected to hit $58 trillion worldwide by 2028, and one of the fastest-growing e-commerce regions in the world is Latin America. Argentina, Brazil, and Mexico are seeing explosive growth in online sales, serving as a strong tailwind for MercadoLibre (NASDAQ: MELI) -- the leading online-commerce ecosystem in Latin America. MercadoLibre connects buyers and sellers through its online marketplace. It offers mobile payments both online and at the point of sale, consumer credit, and shipping and advertising services to small businesses. A vast number of transactions in Latin America are still completed with cash, which lends to a long runway of growth, and this is clearly reflected in the company's recent performance. In the third quarter, revenue and total payment volume were up 61% and 76%, respectively, in local currency. MercadoLibre's fintech business reached 40 million active users, representing the most quarterly additions to its ecosystem in the last two years. What's more, MercadoLibre is reinvesting in marketing and technology for more growth while reporting an improving operating profit margin. Its recent growth is testament to the company's competitive advantages in selection, price competitiveness, and the overall effectiveness of its merchant services. The market is severely undervaluing the company's improving profitability. Despite continuing to post robust growth, the stock sells at a low valuation of 27 times trailing free cash flow. This stock is a good bet at these levels. 2. Roku The growing adoption of smart TVs and streaming is still a huge opportunity for leading developers of TV operating systems. The market for connected TVs is expected to grow about 15% per year through 2026, according to Mordor Intelligence. This opportunity is attracting many competitors, including Apple, Samsung, Alphabet's Android, and Amazon, that offer their own devices and software. But Roku (NASDAQ: ROKU) has the leading market share in the U.S. The stock fell hard over the past year, as sales of TVs dropped amid supply chain issues and inflation pressuring consumer spending. But these headwinds will eventually clear and send Roku off to the races. Investors only need to look at the company's recent numbers to see the value here. Even with lower sales of streaming devices dragging down Roku's growth, the company's platform segment, which includes advertising revenue, increased by 15% year over year in the third quar\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0383 (i.e., a 3.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0383 = 2.6132, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.038267, "expected_loss": 0.038267, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240702_0154", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-07-02", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0111, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0004, std=0.0050, worst_day=-0.0115\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0111 (i.e., a 1.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0111 = 8.9769, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01114, "expected_loss": 0.01114, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240814_0157", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2024-08-14", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0267, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0007, std=0.0120, worst_day=-0.0269\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-01-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-04-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-04-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-01-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2024-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-03-31 0000731766 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us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0267 (i.e., a 2.67% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0267 = 3.7505, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026663, "expected_loss": 0.026663, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20231121_0158", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-11-21", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0215, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0012, std=0.0110, worst_day=-0.0248\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-20] [\"EXCLUSIVE-OpenAI investors considering suing the board after CEO's abrupt firing -sources By Anna Tong, Krystal Hu and Jody Godoy Nov 20 (Reuters) - Some investors in OpenAI, makers of ChatGPT, are exploring legal recourse against the company's board, sources familiar with the matter told Reuters on Monday, after the directors ousted CEO Sam Altman and sparked a potential mass exodus of employees. Sources said investors are working with legal advisers to study their options. It was not immediately clear if these investors will sue OpenAI. Investors worry that they could lose hundreds of millions of dollars they invested in OpenAI, a crown jewel in some of their portfolios, with the potential collapse of the hottest startup in the rapidly growing generative AI sector. OpenAI did not respond to a request for comment. Microsoft MSFT.O owns 49% of the for-profit operating company, according to sources familiar with the matter. Other investors and employees control 49%, with 2% owned by OpenAI's nonprofit parent, according to Semafor. OpenAI's board fired Altman on Friday after a \\\"breakdown of communications,\\\" according to an internal memo seen by Reuters. By Monday, most of OpenAI's more than 700 employees threatened to resign unless the company replaced the board. Venture capital investors usually hold board seats or voting power in their portfolio companies but OpenAI is controlled by its nonprofit parent company OpenAI Nonprofit, which according to OpenAI's website was created to benefit \\\"humanity, not OpenAI investors.\\\" As a result, employees have more leverage in pressuring the board than the venture capitalists who helped fund the company, said Minor Myers, a law professor at the University of Connecticut. \\\"There is nobody exactly who is in the seat of an injured investor,\\\" he said. That is a feature, not a bug of OpenAI's structure, which started out as a nonprofit but added a for-profit subsidiary in 2019 to raise capital. Keeping control of operations let the nonprofit preserve its \\\"core mission, governance, and oversight,\\\" according to the company's website. Nonprofit boards have legal obligations to the organizations they oversee. But those obligations, such as the duty to exercise care and avoid self-dealing, leave a lot of leeway for leadership decisions, experts said. Those obligations can be further narrowed in a corporate structure such as OpenAI, which used a limited liability company as its operating arm, potentially further insulating the nonprofit's directors from investors, said Paul Weitzel, a law professor at the University of Nebraska. Even if investors found a way to sue, Weitzel said they would have a \\\"weak case.\\\" Companies have broad latitude under the law to make business decisions, even ones that backfire. \\\"You can fire visionary founders,\\\" Weitzel said. Apple AAPL.O famously fired Steve Jobs in the 1980s, before bringing him back around a decade later. OpenAI appoints new boss as Sam Altman joins Microsoft \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QQQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0215 (i.e., a 2.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0215 = 4.6472, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021518, "expected_loss": 0.021518, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230110_0160", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-01-10", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1032, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0071, std=0.0457, worst_day=-0.1033\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-09] [\"Technology Sector Update for 01/09/2023: AAPL,PL,META Technology stocks were posting large gains on Monday, with the Technology Select Sector SPDR Fund (XLK) rising 2.8% and the Philadelphia Semiconductor Index advancing 3.7% this afternoon. In company news, Apple (AAPL) gained 2.1% amid reports the tech giant exported $2.5 billion of iPhones from India from April 1 through the end of 2022, almost double its total for the previous fiscal year. Contract manufacturers Foxconn and Wistron each shipped over $1 billion of the phones over the final nine months of 2022, while Pegatron is expected to ship about $500 million worth of the devices by end-January. Planet Labs PBC (PL) added 1.8% after the global data company Monday said it has completed its acquisition of privately held climate technology firm Salo Sciences. Meta Platform (META) rose 1.1% after the oversight board for the company's Facebook unit Monday reversed the decision to remove a post written in Farsi in July against Iran's supreme leader, concluding the slogan \\\"marg bar Khamenei\\\" should be understood as \\\"Down with Khamenei\\\" rather than a credible threat. Meta originally removed the post saying violated its Violence and Incitement community standard. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Why Microsoft Stock Topped the Market Today What happened Like many big companies, Microsoft (NASDAQ: MSFT) likes to grow even larger by acquisitions. The pace of the software giant's asset buys has slowed of late, but it's still got its eyes on attractively valued prizes. On Monday the company announced its latest acquisition, and investors greeted the news by trading Microsoft stock up by 1% to top the essentially flat S&P 500 index. So what Confirming rumors that had been floating around the tech space for several weeks, Microsoft announced on its official blog that it acquired Fungible. The formerly privately held company specializes in data processing units (DPUs), a type of hardware frequently deployed for use in data centers. The company was founded by onetime Apple software engineer Bertrand Serlet in 2016. Fungible's core product, the Fungible DPU, was also invented that year. In its post, Microsoft did not specify how much it paid for Fungible. Media reports in December speculated that the tech giant parted with around $190 million to buy the company. Now what The post did state that the deal further signals Microsoft's commitment to long-term differentiated investments in our data center infrastructure, which enhances our broad range of technologies and offerings including offloading, improving latency, increasing data center server density, optimizing energy efficiency and reducing costs. Data centers, which as their name implies are facilities that store large amounts of data, are crucial to the modern IT operations of corporations. Although the Fungible acquisition is rather small comp\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9690", "answer_numeric": 0.969, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1032 (i.e., a 10.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1032 = 0.9690, capped at 1.0.\nMaximum position size = 0.9690 (96.9% of portfolio).", "metadata": {"var_99": -0.103196, "expected_loss": 0.103196, "max_drawdown_threshold": 0.1, "position_size": 0.969, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240510_0162", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-05-10", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0062, std=0.0405, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230227_0165", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-02-27", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0307, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0005, std=0.0162, worst_day=-0.0381\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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2021-01-31 0001045810 us-gaap:EmployeeStockMember 2022-01-31 2023-01-29 0001045810 us-gaap:EmployeeStockMember 2021-0 [...TRUNCATED...] request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051 ITEM 16. FORM 10-K SUMMARY Not Applicable. 90 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on February 24, 2023. NVIDIA Corporation By: /s/ Jen-Hsun Huang    Jen-Hsun Huang   President and Chief Executive Officer POWER OF ATTORNEY KNOW ALL PERSONS BY THESE PRESENTS, that each person whose signature appears below constitutes and appoints Jen-Hsun Huang and Colette M. Kress, and each or any one of them, his true and lawful attorney-in-fact and agent, with full power of substitution and resubstitution, for him and in his name, place and stead, in any and all capacities, to sign any and all amendments to this report, and to file the same, with all exhibits thereto, and other documents in connection therewith, with the Securities and Exchange Commission, granting unto said attorneys-in-facts and agents, and each of them, full power and authority to do and perform each and every act and thing requisite and necessary to be done in connection therewith, as fully to all intents and purposes as he might or could do in person, hereby ratifying and confirming all that said attorneys-in-fact and agents, or any of them, or their or his substitutes or substitutes, may lawfully do or cause to be done by virtue hereof. 91 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated. Signature Title Date /s/ JEN-HSUN HUANG  President, Chief Executive Officer and Director (Principal Executive Officer) February 24, 2023 Jen-Hsun Huang   /s/ COLETTE M. KRESS  Executive Vice President and Chief Financial Officer (Principal Financial Officer) February 24, 2023 Colette M. Kress   /s/ DONALD ROBERTSON Vice President and Chief Accounting Officer (Principal Accounting Officer) February 24, 2023 Donald Robertson /s/ ROBERT BURGESS Director February 24, 2023 Robert Burgess /s/ TENCH COXE   Director February 24, 2023 Tench Coxe    /s/ JOHN O. DABIRI Director February 24, 2023 John O. Dabiri   /s/ PERSIS DRELL Director February 24, 2023 Persis Drell /s/ DAWN HUDSON Director February 24, 2023 Dawn Hudson /s/ HARVEY C. JONES  Director February 24, 2023 Harvey C. Jones   /s/ MICHAEL MCCAFFERY Director February 24, 2023 Michael McCaffery /s/ STEPHEN C. NEAL Director February 24, 2023 Stephen C. Neal /s/ MARK L. PERRY  Director February 24, 2023 Mark L. Perry    /s/ A. BROOKE SEAWELL Director February 24, 2023 A. Brooke Seawell  /s/ AARTI SHAH Director February 24, 2023 Aarti Shah /s/ MARK STEVENS Director February 24, 2023 Mark Stevens    92\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0307 (i.e., a 3.07% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0307 = 3.2574, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030699, "expected_loss": 0.030699, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240104_0167", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-01-04", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0649, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0295, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0649 (i.e., a 6.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0649 = 1.5399, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064941, "expected_loss": 0.064941, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230807_0170", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-08-07", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0490, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0203, worst_day=-0.0509\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-06] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0490 (i.e., a 4.90% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0490 = 2.0395, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.049032, "expected_loss": 0.049032, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240325_0173", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2024-03-25", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0186, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0029, std=0.0118, worst_day=-0.0189\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MTUM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0186 (i.e., a 1.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0186 = 5.3658, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018637, "expected_loss": 0.018637, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240101_0175", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-01-01", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0186, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0011, std=0.0075, worst_day=-0.0209\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-29] [\"2 Overheated Stocks That Could Tumble in 2024 No one can predict what the stock market, or any individual stock, will do in 2024. The stock market surged in 2023, which was probably not on many investors' bingo cards in January. But one thing investors can do is avoid investments where the odds are stacked against them. Paying too high a price for even the best company can lead to subpar results. Two stocks that look far too expensive going into 2024 are Nvidia (NASDAQ: NVDA) and Apple (NASDAQ: AAPL). Nvidia Nvidia is the leader of artificial intelligence. The company's data center GPUs are selling faster than they can be made. Training advanced large language models, like those that power ChatGPT, requires incredible computational horsepower. Nvidia's proprietary CUDA compute platform has been around since 2007, pairing with its world-class hardware to create a competitive advantage that has been difficult for anyone to overcome so far. While Nvidia may appear untouchable, its days of absolute dominance won't last. If estimates for how big the AI accelerator market will become are close to accurate, there will be mammoth incentives for the tech industry to ensure that there are options beyond Nvidia. AMD expects the market for AI chips to grow nearly tenfold by 2027 to $400 billion. Nvidia's market share is almost certain to shrink as alternatives balloon, and as buyers of AI accelerators optimize for total cost of ownership. Nvidia's growth has been incredible in 2023, and its profits have soared even faster than revenue. The company's profit margins are the highest they've ever been. But the shortage of AI chips won't last forever as competitors race to bring alternatives to market, and neither will the gold rush mentality surrounding AI. Nvidia's software advantage will be chipped away, although that process may take a while. Nvidia is valued at around $1.22 trillion. That's about 40 times the average analyst estimate for earnings. That valuation doesn't seem unreasonable at first glance, but you must be willing to assume that Nvidia's incredible profit margins and growth rate will persist. What if they don't? What if the companies spending big to train large language models find that turning those models into sustainable businesses is tougher than expected? What if competing chips from AMD, Intel, and others provide viable alternatives to Nvidia's pricey products? Taking current growth rates and extrapolating out years is a dangerous thing to do, especially in a very new market. ChatGPT, which kicked off the AI frenzy, has only existed for about a year. If there's any sign that Nvidia is running into trouble in 2024, the stock has a long way to fall. Apple What's Apple's growth story? After a big surge during the pandemic's height, revenue has essentially stagnated in the post-pandemic period. Revenue slipped 1% year over year in the fiscal fourth quarter, which ended on Sept. 30, and an import ban on the Apple Watch isn't going to help ma\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0186 (i.e., a 1.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0186 = 5.3657, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018637, "expected_loss": 0.018637, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230811_0178", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2023-08-11", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0142, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0012, std=0.0081, worst_day=-0.0156\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-10] [\"Invest Like Warren Buffett with These Stocks & ETFs (1:30) - How Did Warren Buffett Get Started In Investing? (7:10) - How Has Berkshire Hathaway\\u2019s Investing Changed Over The Years? (12:20) - Breaking Down Warren Buffett\\u2019s Current Portfolio Holdings (19:30) - Creating Your Own Mini Berkshire Hathaway Portfolio: What Stocks Should You Consider? (23:40) - First Trust RBA American Industrial Renaissance ETF: AIRR (28:50) - Episode Roundup: FAST,MTZ, URI, MOAT, VOO, IVV, SPLG, QUS Podcast@Zacks.com In this episode of ETF Spotlight, I speak with Tracey Ryniec, Zacks Senior Equity Strategist, about investing like Warren Buffett, one of the greatest and most respected investors of all time. Berkshire Hathaway (BRK.A) reported excellent earnings last week, sending its class A shares to an all-time high. The stock is up more than 25,000 times since Buffett took control of the company in 1965, according to Barron's. Most investors would like to emulate Buffett's investing style in their portfolios, which is not easy, but we can certainly learn from his strategies. In the past, Buffett invested in undervalued companies with great potential, which he called \\\"cigar butts.\\\" However, his thinking later evolved to \\\"it's far better to buy a wonderful company at a fair price than a fair company at a wonderful price.\\\" The Oracle of Omaha avoided investing in tech companies earlier in his career but changed his stance later. Apple AAPL, which is now Berkshire's largest stock investment, was praised by Buffett as \\\"a better business than any we own.\\\" The SPDR MSCI USA StrategicFactors ETF QUS seeks to invest in high-quality firms with durable balance sheets and stable cash flows, trading at reasonable valuations. The legendary investor likes companies with \\\"economic moats,\\\" that allow a company to outperform others in the same industry over time. The VanEck Morningstar Wide Moat ETF MOAT invests in attractively priced companies with sustainable competitive advantages. Buffett has long recommended that most investors should stick with low-cost index funds. The iShares Core S&P 500 ETF IVV and Vanguard S&P 500 ETF VOO charge just 0.03% each, but SPDR Portfolio S&P 500 ETF SPLG's new fee of 0.02% makes it the cheapest in the space. Fastenal FAST, MasTec MTZ and United Rentals URI are among Berkshire-like companies that investors may want to consider. Tune in to the podcast to learn more. Make sure to be on the lookout for the next edition of the ETF Spotlight and remember to subscribe! If you have any comments or questions, please email podcast@zacks.com. Want key ETF info delivered straight to your inbox? Zacks\\u2019 free Fund Newsletter will brief you on top news and analysis, as well as top-performing ETFs, each week. Get it free >> Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Apple Inc. (AAPL) : Free Stock Analysis Report Fastenal Company (\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VLUE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0142 (i.e., a 1.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0142 = 7.0556, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014173, "expected_loss": 0.014173, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241211_0180", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-12-11", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0247, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0016, std=0.0095, worst_day=-0.0256\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QQQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0247 (i.e., a 2.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0247 = 4.0470, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02471, "expected_loss": 0.02471, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240222_0183", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-02-22", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0153, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0015, std=0.0064, worst_day=-0.0166\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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2024-01-28 nvda:period 0001045810 nvda:ComputeAndNetworkingMember 2024-01-28 0001045810 nvda:GraphicsMember 2024-01-28 0 [...TRUNCATED...] mas Expressway, Santa Clara, CA 95051 Item 16. Form 10-K Summary Not Applicable. 83 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on February 21, 2024. NVIDIA Corporation By: /s/ Jen-Hsun Huang    Jen-Hsun Huang   President and Chief Executive Officer Power of Attorney KNOW ALL PERSONS BY THESE PRESENTS, that each person whose signature appears below constitutes and appoints Jen-Hsun Huang and Colette M. Kress, and each or any one of them, his true and lawful attorney-in-fact and agent, with full power of substitution and resubstitution, for him and in his name, place and stead, in any and all capacities, to sign any and all amendments to this report, and to file the same, with all exhibits thereto, and other documents in connection therewith, with the Securities and Exchange Commission, granting unto said attorneys-in-facts and agents, and each of them, full power and authority to do and perform each and every act and thing requisite and necessary to be done in connection therewith, as fully to all intents and purposes as he might or could do in person, hereby ratifying and confirming all that said attorneys-in-fact and agents, or any of them, or their or his substitutes or substitutes, may lawfully do or cause to be done by virtue hereof. 84 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated. Signature Title Date /s/ JEN-HSUN HUANG  President, Chief Executive Officer and Director (Principal Executive Officer) February 21, 2024 Jen-Hsun Huang   /s/ COLETTE M. KRESS  Executive Vice President and Chief Financial Officer (Principal Financial Officer) February 21, 2024 Colette M. Kress   /s/ DONALD ROBERTSON Vice President and Chief Accounting Officer (Principal Accounting Officer) February 21, 2024 Donald Robertson /s/ ROBERT BURGESS Director February 21, 2024 Robert Burgess /s/ TENCH COXE   Director February 21, 2024 Tench Coxe    /s/ JOHN O. DABIRI Director February 21, 2024 John O. Dabiri   /s/ PERSIS DRELL Director February 21, 2024 Persis Drell /s/ DAWN HUDSON Director February 21, 2024 Dawn Hudson /s/ HARVEY C. JONES  Director February 21, 2024 Harvey C. Jones   /s/ MELISSA B. LORA Director February 21, 2024 Melissa B. Lora /s/ MICHAEL MCCAFFERY Director February 21, 2024 Michael McCaffery /s/ STEPHEN C. NEAL Director February 21, 2024 Stephen C. Neal /s/ MARK L. PERRY  Director February 21, 2024 Mark L. Perry    /s/ A. BROOKE SEAWELL Director February 21, 2024 A. Brooke Seawell  /s/ AARTI SHAH Director February 21, 2024 Aarti Shah /s/ MARK STEVENS Director February 21, 2024 Mark Stevens    85\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0153 (i.e., a 1.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0153 = 6.5343, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015304, "expected_loss": 0.015304, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240425_0186", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-04-25", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0031, std=0.0438, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240430_0189", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-04-30", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0043, std=0.0438, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230915_0191", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-09-15", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0172, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0000, std=0.0087, worst_day=-0.0213\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-14] [\"What TSMC, ARM, AMD, Apple, and Nvidia Stock Investors Should Know About Recent Chip Updates In today's video, I discuss various semiconductor stocks and recent updates. Check out the short video to learn more, consider subscribing, and click the special offer link below. *Stock prices used were the market prices of Sept. 14, 2023. The video was published on Sept. 14, 2023. 10 stocks we like better than Taiwan Semiconductor Manufacturing When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now... and Taiwan Semiconductor Manufacturing wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of September 11, 2023 Jose Najarro has positions in Advanced Micro Devices, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Advanced Micro Devices, Apple, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy. Jose Najarro is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"SoftBank's Arm set to debut on Nasdaq after biggest IPO since 2021 Adds analyst comment on IPO enthusiasm in paragraph 7, chip stock movement in paragraph 8, background throughout Sept 14 (Reuters) - SoftBank's chip designer Arm Holdings ARM.O is set to debut on the Nasdaq on Thursday, in what is expected to be the biggest test for the U.S. IPO market after a listing drought that lasted for nearly 16 months. The company on Wednesday priced its offering of 95.5 million American Depositary shares at $51 apiece, fetching $4.87 billion for SoftBank at a valuation of $54.5 billion, with participation from cornerstone investors including Apple AAPL.O, Intel INTC.O and Alphabet GOOGL.O. Arm will be back as a publicly traded firm after seven years. Its shares used to trade on the London Stock Exchange and the Nasdaq from 1998 until 2016 when it was taken private by SoftBank in a $32 billion deal. Hopes of a revival in the IPO market largely depend on the success of the high-profile listings of Arm and other marquee startups, including grocery delivery firm Instacart and marketing firm Klaviyo. Investors have over the last year begun to pay more attention to profitability, shunning cash-burning startups that had in 2021 fetched lofty valuations on the back of a record year for deals. Arm has positioned itself as indispensable in the tech hardware ecosystem as its chip designs power nearly every smartp\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLRE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0172 (i.e., a 1.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0172 = 5.8287, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017157, "expected_loss": 0.017157, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230912_0194", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-09-12", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0137, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0005, std=0.0066, worst_day=-0.0141\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-11] [\"Notable Monday Option Activity: AAPL, GS, SJM Among the underlying components of the S&P 500 index, we saw noteworthy options trading volume today in Apple Inc (Symbol: AAPL), where a total of 604,734 contracts have traded so far, representing approximately 60.5 million underlying shares. That amounts to about 107% of AAPL's average daily trading volume over the past month of 56.5 million shares. Particularly high volume was seen for the $180 strike call option expiring September 15, 2023, with 83,977 contracts trading so far today, representing approximately 8.4 million underlying shares of AAPL. Below is a chart showing AAPL's trailing twelve month trading history, with the $180 strike highlighted in orange: Goldman Sachs Group Inc (Symbol: GS) options are showing a volume of 15,558 contracts thus far today. That number of contracts represents approximately 1.6 million underlying shares, working out to a sizeable 90.5% of GS's average daily trading volume over the past month, of 1.7 million shares. Particularly high volume was seen for the $400 strike put option expiring January 19, 2024, with 1,280 contracts trading so far today, representing approximately 128,000 underlying shares of GS. Below is a chart showing GS's trailing twelve month trading history, with the $400 strike highlighted in orange: And J.M. Smucker Co. (Symbol: SJM) options are showing a volume of 7,373 contracts thus far today. That number of contracts represents approximately 737,300 underlying shares, working out to a sizeable 73% of SJM's average daily trading volume over the past month, of 1.0 million shares. Particularly high volume was seen for the $140 strike call option expiring October 20, 2023, with 1,210 contracts trading so far today, representing approximately 121,000 underlying shares of SJM. Below is a chart showing SJM's trailing twelve month trading history, with the $140 strike highlighted in orange: For the various different available expirations for AAPL options, GS options, or SJM options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb Also see: \\u0095 Dow Average Annual Return \\u0095 ZLS shares outstanding history \\u0095 Funds Holding USMR The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The 3 Most Undervalued AI Chip Stocks to Buy in September 2023 InvestorPlace - Stock Market News, Stock Advice & Trading Tips Artificial intelligence has been around for a while, but tools like ChatGPT have brought this innovative technology into the spotlight. A growing number of companies want to create their own AI-powered tools. When many companies and consumers rush toward a technological innovation, it presents an opportunity for investors. Some publicly-traded companies stand to immensely benefit from the surge of artificial intelligence tools. Other have plenty of runway to generate robust gains for investors. With that said, art\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0137 (i.e., a 1.37% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0137 = 7.2752, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013745, "expected_loss": 0.013745, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240827_0197", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-08-27", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0247, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0016, std=0.0075, worst_day=-0.0271\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-01-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-04-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-04-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-01-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2024-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-03-31 0000731766 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2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-06-30 0000731766 unh:ProductsAndServicesMember 2024-06-30 0000731766 unh:ProductsAndServicesMember 2023-12-31 0000731766 2024-07-01 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2024-06-30 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2024-06-30 0000731766 us-gaap:CorporateDebtSecuritiesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2024-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2024-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2023-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2023-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2023-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2023-12-31 0000731766 us-gaap:DebtSecuritiesMember 2024-06-30 0000731766 us-gaap:DebtSecuritiesMember 2023-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0247 (i.e., a 2.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0247 = 4.0552, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02466, "expected_loss": 0.02466, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241010_0199", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-10-10", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0226, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0004, std=0.0099, worst_day=-0.0266\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ACWI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0226 (i.e., a 2.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0226 = 4.4178, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022636, "expected_loss": 0.022636, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241209_0202", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["PALL"], "decision_date": "2024-12-09", "context_summary": "PALL: 60-day history, VaR(99%)=-0.0517, max drawdown threshold=10%.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=-0.0020, std=0.0248, worst_day=-0.0558\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PALL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0517 (i.e., a 5.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0517 = 1.9343, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.051698, "expected_loss": 0.051698, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240920_0205", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-09-20", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0202, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0028, std=0.0088, worst_day=-0.0293\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 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0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLRE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0202 (i.e., a 2.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0202 = 4.9573, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020172, "expected_loss": 0.020172, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230120_0207", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-01-20", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0352, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0045, std=0.0188, worst_day=-0.0413\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0352 (i.e., a 3.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0352 = 2.8401, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03521, "expected_loss": 0.03521, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231019_0210", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-10-19", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1020, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0054, std=0.0619, worst_day=-0.1157\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-18] [\"Beyond Nvidia: Avoid These At-Risk Chip Stocks as U.S.-China Tensions Rise The U.S. Commerce Department this week has expanded its restrictions on chip exports to China. Unsurprisingly, many large-cap semiconductor stocks fell yesterday, considering their high revenue exposure to the world\\u2019s second-largest economy. While Nvidia (NVDA) is getting outsized attention on this news \\u2013 which is justified, given its trillion-dollar market cap and status as the bellwether of artificial intelligence (AI) chip demand \\u2013 there are other chip stocks investors should also look to avoid if you expect the ongoing tensions between the world\\u2019s two largest economies to result in deeper and broader export curbs going forward. www.barchart.com U.S.-China Tensions Are On the Rise U.S.-China relations have been on the decline for years now. In 2018, former President Donald Trump took on China over the burgeoning trade deficit, and imposed tariffs on billions of dollars of imports from China. While the actual positive impact of these tariffs on the U.S. economy and job markets is debatable (and polarizing) \\u2013 it nonetheless raised important questions about the lopsided trade relations between the two countries. Unlike the Trump administration - which more or less went for the carpet-bombing approach in trying to address the U.S. trade imbalance, and imposed tariffs on not only China, but many strategic allies as well - the Biden administration has taken a more focused approach, and has been trying to support on-shoring through legislation like the Inflation Reduction Act and the CHIPS and Science Act, with the latter intended to boost U.S. chip manufacturing capacity and reduce reliance on imports. U.S. Restricts Sales of AI Chips to China Another pillar of the current administration\\u2019s strategy has been to limit exports of high-end chips and other cutting-edge technology to China. Last year, the Commerce Department imposed restrictions on exports of some high-end chips, like Nvidia\\u2019s A100 and H100 processors \\u2013 to which Nvidia responded by coming up with A800 and H800 chips, which were designed specifically for China. The current regulations impose a ban on these two chips, and are also expected to impact sales of AI chips from chipmakers like Intel (INTC) and Advanced Micro Devices (AMD). Also, any new set of chips with processing power just below what\\u2019s currently restricted would need prior approval for exports to China \\u2013 effectively closing a loophole that had previously provided a workaround to chipmakers. Generally speaking, it would be reasonable to expect further escalation in U.S.-China tensions - no matter whether you term it as the \\u201cnew Cold War,\\u201d \\u201ctrade war,\\u201d \\u201ctech war,\\u201d or \\u201cAI war.\\u201d Which Chip Stocks Have the Highest Exposure to China? Data compiled by Kearney shows that while names like Nvidia, AMD, and Intel get roughly a quarter of their revenues from China, the numbe\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9803", "answer_numeric": 0.9803, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1020 (i.e., a 10.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1020 = 0.9803, capped at 1.0.\nMaximum position size = 0.9803 (98.0% of portfolio).", "metadata": {"var_99": -0.102005, "expected_loss": 0.102005, "max_drawdown_threshold": 0.1, "position_size": 0.9803, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230414_0213", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-04-14", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0324, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0009, std=0.0154, worst_day=-0.0340\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-13] [\"Canaccord Genuity Maintains Apple (AAPL) Buy Recommendation Fintel reports that on April 13, 2023, Canaccord Genuity maintained coverage of Apple (NASDAQ:AAPL) with a Buy recommendation. Analyst Price Forecast Suggests 8.49% Upside As of April 6, 2023, the average one-year price target for Apple is $173.69. The forecasts range from a low of $119.18 to a high of $215.25. The average price target represents an increase of 8.49% from its latest reported closing price of $160.10. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is $413,641MM, an increase of 6.74%. The projected annual non-GAAP EPS is $6.36. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. What are Other Shareholders Doing? Iyo Bank holds 67K shares representing 0.00% ownership of the company. No change in the last quarter. Keb Asset Management holds 9K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 10K shares, representing a decrease of 5.83%. The firm decreased its portfolio allocation in AAPL by 99.93% over the last quarter. NSFBX - Natixis Sustainable Future 2015 Fund Class N holds 0K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 0K shares, representing an increase of 11.96%. The firm decreased its portfolio allocation in AAPL by 13.12% over the last quarter. Saxon Interests holds 35K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 36K shares, representing a decrease of 1.41%. The firm increased its portfolio allocation in AAPL by 23.77% over the last quarter. Bank Julius Baer & Co. Ltd, Zurich holds 3,989K shares representing 0.03% ownership of the company. In it's prior filing, the firm reported owning 3,932K shares, representing an increase of 1.43%. The firm decreased its portfolio allocation in AAPL by 99.91% over the last quarter. What is the Fund Sentiment? There are 6408 funds or institutions reporting positions in Apple. This is an increase of 203 owner(s) or 3.27% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 2.31%, a decrease of 40.18%. Total shares owned by institutions increased in the last three months by 0.35% to 10,154,214K shares. The put/call ratio of AAPL is 1.01, indicating a bearish outlook. Apple Background Information (This description is provided by the company.) Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services. It is considered one of the Big Five companies in the U.S. information technology industry, along with Amazon, Google, Microsoft, and Facebook. Its hardware products include the iPhone smartphone, the iPad tablet computer, the Mac personal computer, the iPod portable media player, the Apple Watch smartwatc\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0324 (i.e., a 3.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0324 = 3.0874, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03239, "expected_loss": 0.03239, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230106_0215", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2023-01-06", "context_summary": "INDS: 60-day history, VaR(99%)=-0.0347, max drawdown threshold=10%.", "question": "Asset: INDS\nDaily returns (past 60 days): mean=0.0007, std=0.0163, worst_day=-0.0350\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to INDS, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0347 (i.e., a 3.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0347 = 2.8809, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034712, "expected_loss": 0.034712, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241224_0218", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2024-12-24", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0264, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=-0.0011, std=0.0101, worst_day=-0.0339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VNQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0264 (i.e., a 2.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0264 = 3.7818, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026442, "expected_loss": 0.026442, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240614_0220", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2024-06-14", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0154, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0007, std=0.0071, worst_day=-0.0166\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VTI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0154 (i.e., a 1.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0154 = 6.5063, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01537, "expected_loss": 0.01537, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240725_0222", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-07-25", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0833, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0016, std=0.0318, worst_day=-0.1079\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0833 (i.e., a 8.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0833 = 1.2000, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.083334, "expected_loss": 0.083334, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240212_0225", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-02-12", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0805, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0083, std=0.0514, worst_day=-0.0820\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0805 (i.e., a 8.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0805 = 1.2418, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080529, "expected_loss": 0.080529, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241021_0228", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-10-21", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0453, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0023, std=0.0224, worst_day=-0.0537\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0453 (i.e., a 4.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0453 = 2.2099, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.045252, "expected_loss": 0.045252, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230425_0231", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-04-25", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0863, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0038, std=0.0464, worst_day=-0.1006\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-24] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0863 (i.e., a 8.63% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0863 = 1.1587, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.086302, "expected_loss": 0.086302, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240111_0234", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2024-01-11", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0244, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0021, std=0.0131, worst_day=-0.0249\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLRE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0244 (i.e., a 2.44% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0244 = 4.1005, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024388, "expected_loss": 0.024388, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230711_0236", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-07-11", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0640, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0024, std=0.0238, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-10] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0640 (i.e., a 6.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0640 = 1.5619, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064023, "expected_loss": 0.064023, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231205_0239", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-12-05", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0695, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0020, std=0.0231, worst_day=-0.1070\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-04] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0695 (i.e., a 6.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0695 = 1.4398, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069453, "expected_loss": 0.069453, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241210_0240", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLP"], "decision_date": "2024-12-10", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0127, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0002, std=0.0059, worst_day=-0.0165\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0127 (i.e., a 1.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0127 = 7.8897, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012675, "expected_loss": 0.012675, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230908_0243", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-09-08", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0240, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0003, std=0.0109, worst_day=-0.0251\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-07] [\"Stock Market News for Sep 7, 2023 U.S. stock markets closed lower on Wednesday as market participants remain highly concerned regarding the Fed\\u2019s next move with respect to interest rate. A resilient U.S. economy and an elevated inflation rate may compel the central bank to pursue high interest rate regime. Higher yield on U.S. sovereign bonds higher U.S. dollar index also dented investors\\u2019 confidence on risky assets. like equities. All the three major stock indexes ended in negative territory. How Did The Benchmarks Perform? The Dow Jones Industrial Average (DJI) fell 0.6% or 198.78 points to close at 34,443.19 after a choppy session. Notably, 22 components of the 30-stock index ended in negative territory, while 8 in green. The tech-heavy Nasdaq Composite finished at 13,872.47, sliding 1.1% due to weak performance of large-cap technology stocks. The S&P 500 dropped 0.7% to end at 4,465.48. Nine out of 11 broad sectors of the benchmark ended in negative territory, while two finished in green. The Technology Select Sector SPDR (XLK), the Consumer Discretionary Select Sector SPDR (XLY), the Industrials Select Sector SPDR (XLF), the Health Care Select Sector SPDR (XLV) and the Materials Select Sector SPDR (XLB) fell 1.1%, 0.9%, 0.4%, 0.5% and 0.2%, respectively. The fear-gauge CBOE Volatility Index (VIX) was up 3.1% to 14.45. A total of 9.39 billion shares were traded on Wednesday, lower than the last 20-session average of 10.17 billion. Decliners outnumbered decliners on the NYSE by a 2.05-to-1 ratio. On Nasdaq, a 1.97-to-1 ratio favored declining issues. Near-Term Concerns Crude oil prices spiked on Sep 5, following the decision of Saudi Arabia to extend its daily production cut decision until the end of 2023. Investors are concerned that higher crude oil prices will result in higher inflation. Higher oil prices will directly affect transportation sector, which in turn will raise the general price level. This will make the task of the Fed more difficult for a soft landing of the U.S. economy. Moreover, the yield on the benchmark 10-Year U.S. Treasury Note rose 2 basis points to 4.292%. The yield on the short-term 2-Year U.S. Treasury Note jumped 10 basis points to 5.02%. This yield is loosely linked to interest rate movement. The yield on the long-term 30-Year U.S. Treasury Note climbed 14 basis points to 4.373%. The ICE U.S. dollar Index rose to a six-month high at 104.90. Higher risk-free market interest rate is detrimental to growth stocks like technology. These companies depend on easy access to cheap credits. Consequently, shares of tech behemoths like NVIDIA Cor. NVDA, Apple Inc. AAPL and Alphabet Inc. GOOGL declined 3.1%, 3.6% and 1%, respectively. NVIDIA currently sports a Zacks Rank #1 (Strong Buy). You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. Strong Economic Data The Institute of Supply Management reported that services purchasing managers\\u2019 index (PMI) for August came in at 54.5%,\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0240 (i.e., a 2.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0240 = 4.1617, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024029, "expected_loss": 0.024029, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241118_0245", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2024-11-18", "context_summary": "SHV: 60-day history, VaR(99%)=-0.0001, max drawdown threshold=10%.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SHV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0001 (i.e., a 0.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0001 = 1101.5422, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -9.1e-05, "expected_loss": 9.1e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240802_0248", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-08-02", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0177, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0009, std=0.0068, worst_day=-0.0228\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:CostOfSalesMember us-gaap:EmployeeSeveranceMember 2023-04-01 2023-06-30 0001326801 meta:A20 [...TRUNCATED...] tered into a new trading plan that provides for the sale of an aggregate of 14,376 shares of our Class A common stock and all of the net shares received during the duration of the plan pursuant to Ms. Li and her spouse’s outstanding equity awards and any future equity award grants. The plan will terminate on November 25, 2024 , subject to early termination for certain specified events set forth in the plan. 90 Table of Contents Item 6. Exhibits Exhibit Number Incorporated by Reference Filed Herewith Exhibit Description Form File No. Exhibit Filing Date 3.1 Amended and Restated Certificate of Incorporation (including all amendments thereto) . X 10.1+ Fourth Amendment to the 2012 Equity Incentive Plan. X 31.1 Certification of Mark Zuckerberg, Chief Executive Officer, pursuant to Rule 13a-14(a)/15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 . X 31.2 Certification of Susan Li, Chief Financial Officer, pursuant to Rule 13a-14(a)/15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002. X 32.1# Certification of Mark Zuckerberg, Chief Executive Officer, pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 . X 32.2# Certification of Susan Li, Chief Financial Officer, pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002. X 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document). X 101.SCH Inline XBRL Taxonomy Extension Schema Document. X 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. X 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. X 101.LAB Inline XBRL Taxonomy Extension Labels Linkbase Document. X 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. X 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101). X + Indicates a management contract or compensatory plan. # This certification is deemed not filed for purposes of Section 18 of the Securities Exchange Act of 1934, as amended (Exchange Act), or otherwise subject to the liability of that section, nor shall it be deemed incorporated by reference into any filing under the Securities Act of 1933, as amended, or the Exchange Act. 91 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Quarterly Report on Form 10-Q to be signed on its behalf by the undersigned, thereunto duly authorized, in the City of Menlo Park, State of California, on this 31st day of July 2024.     META PLATFORMS, INC. Date: July 31, 2024 /s/ SUSAN LI Susan Li Chief Financial Officer (Principal Financial Officer) Date: July 31, 2024 /s/ AARON ANDERSON Aaron Anderson Chief Accounting Officer (Principal Accounting Officer) 92\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0177 (i.e., a 1.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0177 = 5.6632, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017658, "expected_loss": 0.017658, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20230613_0251", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-06-13", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0871, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0068, std=0.0289, worst_day=-0.0889\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-12] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0871 (i.e., a 8.71% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0871 = 1.1479, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.087115, "expected_loss": 0.087115, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231213_0254", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-12-13", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0953, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0211, std=0.0628, worst_day=-0.1169\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-12] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0953 (i.e., a 9.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0953 = 1.0498, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.095253, "expected_loss": 0.095253, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241203_0257", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-12-03", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0772, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0105, std=0.0531, worst_day=-0.0971\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0772 (i.e., a 7.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0772 = 1.2954, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.077198, "expected_loss": 0.077198, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230718_0260", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2023-07-18", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0201, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0008, std=0.0100, worst_day=-0.0206\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-17] [\"Mirror, Mirror, on the Wall, Which Is the Cheapest FAANG Stock of Them All? Regardless of how well or poorly the broad-market indexes have performed, new and tenured investors have gravitated to the FAANG stocks for more than a decade. When I say \\\"FAANG\\\" stocks, I'm referring to: Facebook, which is now part of Meta Platforms (NASDAQ: META) Apple (NASDAQ: AAPL) Amazon (NASDAQ: AMZN) Netflix (NASDAQ: NFLX) Google, which is now part of Alphabet (NASDAQ: GOOGL)(NASDAQ: GOOG) The reason these companies are so widely owned has to do with their long-term outperformance and industry-based competitive advantages. Image source: Getty Images. With regard to the latter, all five of these companies have well-defined moats or edges that have, thus far, proved insurmountable. Meta Platforms had more than half of the world's adult population visit at least one of its social media sites (Facebook, WhatsApp, Instagram, or Facebook Messenger) during the first quarter. Apple's iPhone has consistently accounted for around half, if not more, of U.S. smartphone market share since introducing a 5G-capable iPhone. Amazon is responsible for bringing in about 40% of U.S. online retail sales. Netflix is the global and international leader of streaming service market share. Alphabet's internet search engine Google has accounted for no less than 90% of worldwide search share dating back to March 2015. They're also crushing the major U.S. stock indexes in the return column. Over the trailing-10-year period, through July 13, Apple, Netflix, Meta, Amazon, and Alphabet (Class A shares, GOOGL), in that order, have produced returns of around 1,150%, 1,120%, 1,110%, 773%, and 440%. By comparison, the benchmark S&P 500 has gained 168% over the same timeline. These are five highly trusted businesses -- but they're not identical on a valuation basis. Based on forward P/E, there's one FAANG that's clearly cheaper than the others Although there are a number of ways to evaluate stocks from a fundamental perspective, the forward price-to-earnings (P/E) ratio is one of the most common metrics used. The forward P/E is derived by dividing a company's share price into Wall Street's consensus earnings per share (EPS) for the upcoming year. Based on Wall Street's consensus EPS for these companies in 2024, here's what the forward P/Es currently look like for the FAANG stocks: Alphabet (Class A shares, GOOGL): forward P/E of 19.9 Meta Platforms: forward P/E of 21.3 Apple: forward P/E of 29 Netflix: forward P/E of 31.1 Amazon: forward P/E of 52.1 This traditional fundamental metric suggests Alphabet, the parent of Google, streaming platform YouTube, and autonomous vehicle company Waymo, is the cheapest of the FAANG stocks at just shy of 20 times forward-year earnings. What's noteworthy about Alphabet is that it'll continue to benefit from its foundational search engine, which is generating copious amount of cash flow, while enjoying potentially faster growth rates from its ancillary segments. T\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0201 (i.e., a 2.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0201 = 4.9753, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020099, "expected_loss": 0.020099, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230721_0262", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-07-21", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0117, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0004, std=0.0059, worst_day=-0.0125\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-20] [\"2 Best Value Stocks to Buy Right Now Value stocks have historically outperformed most other asset classes. During the latest bear market, for instance, investors leaned heavily into value stocks as a hedge against inflation and a weakening global economy. With the tide seemingly turning in the market, however, growth stocks will probably start to outperform value-oriented assets over the next few years. Nonetheless, some value stocks are still worth buying as this shift in sentiment unfolds. Here is a brief overview of two top-shelf value stocks that stand out as superb buys in this dynamic market. Image source: Getty Images. Berkshire Hathaway: A diversified powerhouse Berkshire Hathaway (NYSE: BRK.A) (NYSE: BRK.B) is a diversified holding company that operates a wide range of businesses in different industries. The company is led by Warren Buffett, one of the most successful and respected investors in history. The company owns and controls many well-known companies, such as Geico, BNSF Railway, Berkshire Hathaway Energy, Dairy Queen, and Duracell. These businesses provide stable and consistent earnings for the holding company. Berkshire Hathaway also invests in a large number of publicly traded companies, such as Apple, Bank of America, Coca-Cola, American Express, and T-Mobile. These investments give the holding company exposure to some of the most profitable and dominant companies in the world. Berkshire Hathaway has a long history of delivering market-beating returns to its shareholders. Since 1965, its stock has generated compound annual returns of 19.8% per year, compared to 9.9% for the S&P 500. Now, the holding company's stock performance did lag behind the market during the previous bull market, but it has regained its edge over the past year. BRK.A data by YCharts With the challenges posed by rising interest rates and a possible economic slowdown, Berkshire's resilient portfolio of stocks and businesses should continue to drive market-beating returns -- especially with its shares trading at a mere 2.6 times trailing sales. British American Tobacco: A resilient tobacco giant British American Tobacco is one of the largest tobacco companies in the world, with a presence in more than 180 countries and a portfolio of popular brands such as Dunhill, Lucky Strike, Pall Mall, Kent, Rothmans, and Camel. The company also has a growing presence in the reduced-risk products segment, which includes e-cigarettes, heated tobacco products, and oral nicotine products. British American Tobacco has been able to maintain its profitability and cash flow despite the challenges facing the tobacco industry, such as declining smoking rates, regulatory pressures, and increased competition. Wall Street analysts, in fact, expect the tobacco giant to grow its earnings per share by double digits over the next few years, thanks heavily to its opportunity in the rapidly growing noncombustible product category. Perhaps most importantly, though, British American Toba\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0117 (i.e., a 1.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0117 = 8.5733, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011664, "expected_loss": 0.011664, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230822_0264", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-08-22", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0660, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0030, std=0.0277, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-21] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0660 (i.e., a 6.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0660 = 1.5151, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.066003, "expected_loss": 0.066003, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231023_0266", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-10-23", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0315, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0023, std=0.0169, worst_day=-0.0321\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-20] [\"Earnings Preview of \\\"Magnificent Seven\\\": ETFs in Focus The \\\"Magnificent Seven\\\" typically refers to the 1960 Western film, but today\\u2019s stock market investors recognize the term as the set of seven big tech stocks, namely Apple AAPL, Microsoft MSFT, Alphabet GOOGL, Amazon AMZN, Nvidia NVDA, Meta Platforms META and Tesla TSLA. With the third-quarter earnings season underway, investors\\u2019 eyes will be glued to the \\\"Magnificent Seven\\\" earnings. While Tesla has already posted a weak Q3 earnings (missing estimates on both fronts), others are yet to report (read: Tesla Posts Weak Q3 Earnings: ETFs in Focus). Investors should note that according to our methodology, the combination of a positive Earnings ESP and a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 increases the chances of an earnings beat. You can uncover the best stocks to buy or sell before they\\u2019re reported with our Earnings ESP Filter. Earnings Whispers Microsoft is expected to report on Oct 24. The stock has an Earnings ESP of 0.00% and a Zacks Rank #3 (Hold). In the past 90 days, Microsoft\\u2019s earnings for the September quarter rose by 8 cents to $2.65 per share. Alphabet is expected to report on Oct 24. The stock has an Earnings ESP of +0.89% and a Zacks Rank #3. In the past 90 days, Alphabet\\u2019s earnings for the September quarter rose by 11 cents to $1.45 per share. Meta is expected to report on Oct 25. The stock has an Earnings ESP of +3.98% and a Zacks Rank #3. In the past 90 days, Meta\\u2019s earnings for the September quarter surged from $2.99 to $3.57 per share. Amazon is expected to report on Oct 26. The stock has an Earnings ESP of 0.00% and a Zacks Rank #2 (Buy). In the past 90 days, Amazon\\u2019s earnings for the September quarter surged from 39 cents to 58 cents per share. Apple is expected to report on Nov 2. The stock has an Earnings ESP of 0.00% and a Zacks Rank #3. In the past 90 days, Apple\\u2019s earnings for the September quarter inched up by 2 cents $1.39 per share. Nvidia is expected to report on Nov 15. The stock has an Earnings ESP of +6.93% and a Zacks Rank #1 (Strong Buy). In the past 90 days, Nvidia\\u2019s earnings for the October quarter jumped from $2.22 to $3.34 per share. Inside the Valuation of Magnificent Seven While the 'Magnificent Seven' hold industry-leading positions in areas such as Artificial Intelligence, cloud services, social networking, search engines, the metaverse, premium smartphones, and electric vehicles (which have enabled them to capture a hugeglobal marketshare), valuation remains equally important in influencing their stock performance in the near future. In this respect, Meta, Alphabet and Microsoft have a lower P/E than the concerned industry Computer Software-Services Market\\u2019s P/E, Apple\\u2019s P/E is almost in-line with the concerned industry Computer-Office Equipment Market\\u2019s P/E. However, Amazon, Tesla and Nvidia are pricey. ETFs in Focus Since some of the stocks appear overvalued and some stocks have\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to FXI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0315 (i.e., a 3.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0315 = 3.1723, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031523, "expected_loss": 0.031523, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240531_0269", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-05-31", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1347, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0052, std=0.0423, worst_day=-0.1455\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7425", "answer_numeric": 0.7425, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1347 (i.e., a 13.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1347 = 0.7425, capped at 1.0.\nMaximum position size = 0.7425 (74.2% of portfolio).", "metadata": {"var_99": -0.134679, "expected_loss": 0.134679, "max_drawdown_threshold": 0.1, "position_size": 0.7425, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240910_0272", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-09-10", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0246, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0002, std=0.0099, worst_day=-0.0259\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 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us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0246 (i.e., a 2.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0246 = 4.0701, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024569, "expected_loss": 0.024569, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230724_0275", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2023-07-24", "context_summary": "VNQI: 60-day history, VaR(99%)=-0.0191, max drawdown threshold=10%.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=0.0003, std=0.0100, worst_day=-0.0197\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VNQI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0191 (i.e., a 1.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0191 = 5.2368, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019096, "expected_loss": 0.019096, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230424_0278", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-04-24", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0784, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0049, std=0.0354, worst_day=-0.0851\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-23] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0784 (i.e., a 7.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0784 = 1.2763, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.078351, "expected_loss": 0.078351, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240219_0280", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-02-19", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0592, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0014, std=0.0242, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0592 (i.e., a 5.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0592 = 1.6890, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.059207, "expected_loss": 0.059207, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230703_0282", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-07-03", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0917, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0015, std=0.0388, worst_day=-0.0992\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-02] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0917 (i.e., a 9.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0917 = 1.0907, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.091688, "expected_loss": 0.091688, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230202_0285", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-02-02", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1074, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0058, std=0.0506, worst_day=-0.1133\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-01] [\"GLOBAL MARKETS-Stocks rise, dollar falls after Fed hikes as expected By Chuck Mikolajczak NEW YORK, Feb 1 (Reuters) - A gauge of global stocks rose and the U.S. dollar and Treasury yields were lower on Wednesday after the Federal Reserve raised its target interest rate by the expected 25 basis points but communicated more increases were on the horizon. The Fed said the U.S. economy was enjoying \\\"modest growth\\\" and \\\"robust\\\" job gains, with policymakers still \\\"highly attentive to inflation risks\\\" as it seeks to tighten financial conditions and reign in high prices. Markets have been pricing in the possibility of a rate cut by the Fed in the back half of the year. On Wall Street, U.S. stocks were choppy after the Fed announcement but rebounded to turn positive as Chair Jerome Powell began to speak. \\\"The key thing the Fed is focused on is wages and we are seeing wage inflation continue to ameliorate if you look at both average hourly earnings and the employment cost index which just came out, wages are beginning to soften, but they are not softening enough to get inflation down to that 2% target,\\\" said Ellen Hazen, chief market strategist at F.L.Putnam Investment Management in Wellesley, Massachusetts. \\\"They had a very slightly dovish change in the language where they previously had talked about determining the pace of future increases and now they are talking about determining the extent of future increases.\\\" Investors will now closely eye comments from Fed Chair Powell for further signals on the path of the central bank's policy. The Dow Jones Industrial Average .DJI fell 5.45 points, or 0.02%, to 34,080.59, the S&P 500 .SPX gained 30.83 points, or 0.76%, to 4,107.43 and the Nasdaq Composite .IXIC added 173.22 points, or 1.5%, to 11,757.77. Before the policy announcement, economic data painted a mixed picture, with a labor market that remains strong while manufacturing activity continues to weaken, showing contraction for a third straight month. Investors have viewed a weaker labor market as a key component to bring down stubbornly high inflation. Earnings season also continues to roll on, with Facebook owner Meta META.O reporting earnings after the closing bell on Wednesday. Later in the week will bring earnings from names such as Apple AAPL.O and Amazon .AMZN.O. Early gains for European shares faded to close virtually unchanged ahead of the Fed statement, although industrial stocks SXNP, up 0.85%, were a bright spot. On the heels of the Fed, the European Central Bank (ECB) and Bank of England will make their policy statements on Thursday, in which each is largely expected to hike by 50 basis points. The pan-European STOXX 600 index .STOXX closed down 0.03% and MSCI's gauge of stocks across the globe .MIWD00000PUS gained 0.81%. Data on Wednesday showed headline inflation in the euro zone moderated to 8.5% in January, from 9% in December, while core prices picked up to 7% from 6.9%, likely keeping pressure on the ECB to raise interest r\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9311", "answer_numeric": 0.9311, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1074 (i.e., a 10.74% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1074 = 0.9311, capped at 1.0.\nMaximum position size = 0.9311 (93.1% of portfolio).", "metadata": {"var_99": -0.107405, "expected_loss": 0.107405, "max_drawdown_threshold": 0.1, "position_size": 0.9311, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240315_0288", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["GLD"], "decision_date": "2024-03-15", "context_summary": "GLD: 60-day history, VaR(99%)=-0.0122, max drawdown threshold=10%.", "question": "Asset: GLD\nDaily returns (past 60 days): mean=0.0013, std=0.0066, worst_day=-0.0138\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to GLD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0122 (i.e., a 1.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0122 = 8.2286, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012153, "expected_loss": 0.012153, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230313_0290", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-03-13", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1016, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0051, std=0.0661, worst_day=-0.1182\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-12] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9843", "answer_numeric": 0.9843, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1016 (i.e., a 10.16% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1016 = 0.9843, capped at 1.0.\nMaximum position size = 0.9843 (98.4% of portfolio).", "metadata": {"var_99": -0.101591, "expected_loss": 0.101591, "max_drawdown_threshold": 0.1, "position_size": 0.9843, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240916_0292", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-09-16", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0647, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0010, std=0.0302, worst_day=-0.0710\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0647 (i.e., a 6.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0647 = 1.5457, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064694, "expected_loss": 0.064694, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231031_0295", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-10-31", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0229, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0010, std=0.0109, worst_day=-0.0248\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-30] [\"Google CEO Sundar Pichai testifies in US antitrust trial Updates with hearing beginning WASHINGTON, Oct 30 (Reuters) - Sundar Pichai, CEO of Alphabet Inc GOOGL.O and its subsidiary Google, testified Monday in a once-in-a generation antitrust fight with the U.S. government that the company sought to make browser use and internet search easy and secure. Pichai testified under oath in a trial to determine whether Google acted illegally to maintain its dominance of search and parts of search advertising. If the government wins, the company may be forced to scrap some business practices that have helped it stay on top. In testimony Monday morning, Pichai took a couple of swipes at Microsoft's MSFT.O browser, Internet Explorer. Before Google launched its Chrome browser, which competes with the Microsoft product, Pichai said, \\\"The browser market at the time had kind of stagnated. \\\"They (Microsoft) were not that incented to improve the browser,\\\" he added, calling Chrome a \\\"pretty dramatic improvement\\\" when it was launched in 2008. He also said that Google made it easy to change the Chrome browser if a user wanted to use a search engine that was not Google. Pichai, who was called as a witness for Google, will likely be asked about the company's investments aimed at keeping its online search engine dominant, especially as smartphones took over, and innovation in search advertising. The government, in cross-examination, will likely also ask about the billions of dollars paid annually to smartphone makers like Apple AAPL.O and wireless carriers like AT&T T.N to be the default in search on their devices in order to stay on top. The clout in search makes Google a heavy hitter in the lucrative advertising market, its biggest revenue source. Google has argued the revenue share agreements are legal and that it has invested heavily to keep its search and advertising businesses competitive. It has also argued that if people are dissatisfied with default search engines, they can, and do, switch to another search provider. Why is the US suing Google for antitrust violations? https://www.reuters.com/legal/why-is-us-suing-google-antitrust-violations-2023-09-11/ (Reporting by Diane Bartz and Chris Sanders; Editing by Marguerita Choy and Jonathan Oatis) ((Chris.Sanders@thomsonreuters.com; +1 202-558-8254; Reuters Messaging: chris.sanders.reuters.com@reuters.net)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Keybanc Reiterates Apple (AAPL) Sector Weight Recommendation Fintel reports that on October 30, 2023, Keybanc reiterated coverage of Apple (NASDAQ:AAPL) with a Sector Weight recommendation. Analyst Price Forecast Suggests 21.01% Upside As of October 5, 2023, the average one-year price target for Apple is 203.55. The forecasts range from a low of 150.49 to a high of $252.00. The average price target represents an increase of 21.01% from its latest reported closing price o\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QQQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0229 (i.e., a 2.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0229 = 4.3652, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022909, "expected_loss": 0.022909, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230922_0298", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2023-09-22", "context_summary": "CSHI: 60-day history, VaR(99%)=-0.0011, max drawdown threshold=10%.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0003, std=0.0006, worst_day=-0.0012\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CSHI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0011 (i.e., a 0.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0011 = 92.5522, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.00108, "expected_loss": 0.00108, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240416_0301", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-04-16", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0055, std=0.0422, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240415_0304", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-04-15", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0861, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0029, std=0.0383, worst_day=-0.1024\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0861 (i.e., a 8.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0861 = 1.1610, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.086134, "expected_loss": 0.086134, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241009_0307", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-10-09", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0425, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=-0.0004, std=0.0193, worst_day=-0.0427\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0425 (i.e., a 4.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0425 = 2.3557, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042451, "expected_loss": 0.042451, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230525_0310", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2023-05-25", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0188, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0005, std=0.0095, worst_day=-0.0199\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-24] [\"7 Stocks That Could Be the First $10 Trillion-Dollar Company InvestorPlace - Stock Market News, Stock Advice & Trading Tips Let\\u2019s begin by understanding that most of the future $10 trillion companies are those that already have the highest valuations. Even the youngest among these companies have existed for 20 years. The point is that companies valued in the hundreds of billions and trillions take a long time to build: They, therefore, have the best chance of reaching the unthinkable $10 trillion mark first. To provide further context, no firm is currently valued at $5 trillion. Expectations are that the threshold will be reached in 2028. It seems that it could take decades for a company to reach a valuation twice that level. In truth, it could be a company that bursts onto the scene from relative obscurity. Some now-unknown AI companies could certainly fit the mold. But no one knows. MSFT Microsoft $313.85 GOOG GOOGL Alphabet $121.64 AAPL Apple $171.84 META Meta Platforms $249.21 NVDA Nvidia $305.38 AMZN Amazon $116.75 TSLA Tesla $182.90 Microsoft (MSFT) Source: Asif Islam / Shutterstock.com Microsoft (NASDAQ:MSFT) stock is the second highest-valued equity globally, at $2.35 trillion. It was actually worth $230 billion more at the height of the pandemic tech bubble before losing ground as rate hikes did their work. It\\u2019s another one of the future $10 trillion companies. One thing that is noteworthy about Microsoft\\u2019s market cap is just how rapidly it has grown of late. Just before the onset of the pandemic, the total value of all outstanding MSFT stock was approximately $1.3 trillion. So it has gained about $1 trillion in value since. That is primarily attributable to the fact that the pandemic put tech on steroids. Money was flowing into these companies at an extraordinary pace that no one could have anticipated. While the pandemic was a massive disaster, it was a boon for tech as everyone was forced inside. Companies like Microsoft were gifted accelerated sales and quantities of data that they couldn\\u2019t have otherwise. That acceleration of everything explains how Microsoft has grown so quickly. And now it has AI setting it up for its next growth phase. Alphabet (GOOG,GOOGL) Source: IgorGolovniov / Shutterstock.com The story of Alphabet\\u2019s (NASDAQ:GOOG,GOOGL) stock and its valuation follows a very similar arc to Microsoft\\u2019s. The same overarching catalysts apply to Alphabet and the benefits are similar too. Both companies have become much stronger as a result of the pandemic. It\\u2019s another one of the future $10 trillion companies. The difference is basically scale. Alphabet gained roughly $500 billion in value and is now valued near $1.6 trillion. The company has suffered in different ways over the past year. Mainly, Google has seen a massive slide as search revenues have declined on persistent economic fears. Companies are spending less on advertising. Yet it\\u2019s very much worth noting that Google must have co\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VTI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0188 (i.e., a 1.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0188 = 5.3134, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01882, "expected_loss": 0.01882, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240306_0313", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-03-06", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0115, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0016, std=0.0065, worst_day=-0.0146\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0115 (i.e., a 1.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0115 = 8.7049, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011488, "expected_loss": 0.011488, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20231208_0315", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2023-12-08", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0215, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0007, std=0.0106, worst_day=-0.0248\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-07] [\"US STOCKS-Nasdaq ends sharply higher as Alphabet and AMD fuel AI surge (Updated at 4:10 p.m. ET/ 2110 GMT) * Investors cheer Alphabet's new AI model * Advanced Micro Devices climbs after AI-chip market forecast * Weekly jobless claims lower than expected * Indexes: S&P 500 +0.80%, Nasdaq +1.37%, Dow +0.18% * By Noel Randewich and Shristi Achar A Dec 7 (Reuters) - The Nasdaq ended sharply higher on Thursday after Alphabet and Advanced Micro Devices sparked a megacap rally on fresh optimism about artificial intelligence. Shares of Alphabet jumped 5.3% as analysts cheered the launch of the Google-parent's newest AI model, while AMD soared nearly 10% after the company estimated the potential market for its data center AI chips could reach $45 billion this year. Other heavyweight tech-related stocks also gained, with Nvidia and Meta Platforms rising over 2%, Amazon up 1.6% and Apple 1% higher. The Philadelphia semiconductor index jumped 2.8%, increasing its 2023 gain to 48%, much of that fueled by bets about the future of AI. \\\"Today it's an AMD-Google rally. There's a contagion effect across the market. Everyone wants to get on the bandwagon,\\\" said Jay Hatfield, CEO of Infrastructure Capital Management in New York. \\\"We're kind of in this weird market, a tag-team market, where one day tech leads, and then the next day value and the broad market lead.\\\" The S&P 500 has steadily climbed since the end of October on expectations the Federal Reserve has finished its campaign of interest rate hikes and that it could begin cutting rates in March. The S&P 500 climbed 0.80% to end the session at 4,585.59 points, with 1.8 stocks in the index gaining for each one that fell. The most traded stock in the S&P 500 was Tesla , with $25.7 billion worth of shares changing hands during the session. The shares rose 1.37%. The Nasdaq Composite jumped 1.37% to 14,339.99 points, while Dow Jones Industrial Average rose 0.18% to 36,117.57 points. Volume on U.S. exchanges was relatively heavy, with 11.2 billion shares traded, compared to an average of 10.8 billion shares over the previous 20 sessions. Traders have almost fully priced in the likelihood of the Fed keeping rates unchanged at its meeting next week. Data on Thursday showed the number of Americans filing new claims for unemployment benefits increased less than expected last week to a seasonally adjusted 220,000 for the week. A Labor Department jobs report due on Friday could hint at how quickly the U.S. economy is softening and may sway expectations about when the Fed is likely to begin cutting rates. Non-farm payrolls are expected to have increased by 180,000 jobs last month after rising by 150,000 in October. Interest rate futures imply a nearly 64% chance of a rate cut as soon as March, according to the CME Group's FedWatch tool. Limiting gains in the Dow, shares of Merck fell 1.7% after the drugmaker's immunotherapy combination failed in a lung cancer study. (Reporting by Amruta Khandekar and Shristi Achar A\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QQQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0215 (i.e., a 2.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0215 = 4.6472, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021518, "expected_loss": 0.021518, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240704_0318", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2024-07-04", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0114, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0006, std=0.0062, worst_day=-0.0119\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0114 (i.e., a 1.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0114 = 8.7892, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011378, "expected_loss": 0.011378, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240502_0320", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-05-02", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1241, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0072, std=0.0458, worst_day=-0.1409\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8057", "answer_numeric": 0.8057, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1241 (i.e., a 12.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1241 = 0.8057, capped at 1.0.\nMaximum position size = 0.8057 (80.6% of portfolio).", "metadata": {"var_99": -0.124117, "expected_loss": 0.124117, "max_drawdown_threshold": 0.1, "position_size": 0.8057, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230925_0323", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2023-09-25", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0372, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=-0.0005, std=0.0130, worst_day=-0.0388\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XHB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0372 (i.e., a 3.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0372 = 2.6889, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03719, "expected_loss": 0.03719, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230113_0326", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-01-13", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0193, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0027, std=0.0114, worst_day=-0.0259\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-12] [\"My Top Tech IPO to Buy in January Last year was not kind to the initial public offering market, with global IPO activity volume tumbling 45%, leading to a 61% decline in proceeds. In fact, only a little over 1,300 IPOs raised just $179.5 billion, according to Ernst & Young, though technology issues led the way, accounting for nearly a quarter of the total number. In the U.S., there were just 214 IPOs that raised $21.8 billion in 2022, a far cry from the 1,091 offerings that raised $335 billion in 2021. One of the biggest was Mobileye (NASDAQ: MBLY), the autonomous vehicle technology spinoff from Intel (NASDAQ: INTC) that went public on Oct. 26, issuing 51.9 million shares at a price of $21 per share. It generated a little over $1 billion in net proceeds for the tech stock. In a little over two months of trading, the stock gained 59%, and though there are substantial risks for this business, this may be a tech IPO you'll want to buy this month. Image source: Getty Images. Driving to new heights The autonomous vehicle market is exploding. Already a $25 billion opportunity that's growing at a near-26% compounded annual rate, it's expected the market could reach as high as $197 billion by 2030, depending upon who's counting. While analysts tend to extrapolate an industry's growth at a sharply rising angle, it's clear the self-driving vehicle market is one that could actually achieve the growth projected. Mobileye is a leading player in the space and was always one of Intel's successful divisions from the time Intel acquired it in 2017, counting Ford, BMW, General Motors, Volkswagen, and Toyota among its customers. The company makes chips that power not only the cameras and other driver assistance systems for self-driving vehicles, but according to Intel, Mobileye also offers a complete software platform that can enable the \\\"entire stack\\\" of assisted and autonomous driving technologies. Mobileye generated almost $1.4 billion in revenue in 2021, but has already generated $1.3 billion through the first nine months of 2022, up 27% year over year. CEO Amnon Shashua told the Consumer Electronics Show 2023 he expected Mobileye would see as much as $17 billion in assisted-driving product revenue by 2030, with 20% of that, or $3.5 billion, coming from its SuperVision product that was only launched in the fourth quarter of 2021. SuperVision was developed by China's Geely Group and is an outgrowth of Mobileye's camera-only subsystems, offering premium, full-surround computer vision and operational point-to-point assisted driving navigation. It carries a higher price tag, which helped boost quarterly revenue and average system pricing to $53 million from $45.7 million last year, but it also sports lower margins due to the additional hardware it contains. Image source: Getty Images. Near-term headwinds Despite all this upward momentum behind Mobileye, Wall Street is only looking for single-digit earnings growth in 2023, as it feels this will be something of a\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EFA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0193 (i.e., a 1.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0193 = 5.1926, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019258, "expected_loss": 0.019258, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240328_0329", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-03-28", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0083, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0012, std=0.0045, worst_day=-0.0095\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0083 (i.e., a 0.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0083 = 12.0253, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008316, "expected_loss": 0.008316, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230223_0332", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-02-23", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0288, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0003, std=0.0135, worst_day=-0.0300\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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xbrli:pure 0000034088 xom:UpstreamMember 2022-01-01 2022-12-31 0000034088 xom:UpstreamMember 2021-01-01 2021-12-31 0000034088 xom:UpstreamMember 2020-01-01 2020-12-31 0000034088 [...TRUNCATED...] L and contained in Exhibit 101). _____________________   * Compensatory plan or arrangement required to be identified pursuant to Item 15(a)(3) of this Annual Report on Form 10-K. The registrant has not filed with this report copies of the instruments defining the rights of holders of long-term debt of the registrant and its subsidiaries for which consolidated or unconsolidated financial statements are required to be filed. The registrant agrees to furnish a copy of any such instrument to the Securities and Exchange Commission upon request. 133 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.         EXXON MOBIL CORPORATION         By: /s/ DARREN W. WOODS Dated February 22, 2023   Darren W. Woods, Chairman of the Board POWER OF ATTORNEY Each person whose signature appears below constitutes and appoints John D. Buchanan, Brian J. Conjelko, and Antony E. Peters and each of them, his or her true and lawful attorneys-in-fact and agents, with full power of substitution and resubstitution, for him or her and in his or her name, place and stead, in any and all capacities, to sign any and all amendments to this Annual Report on Form 10-K, and to file the same, with all exhibits thereto, and other documents in connection therewith, with the Securities and Exchange Commission, granting unto said attorneys-in-fact and agents, and each of them, full power and authority to do and perform each and every act and thing requisite and necessary to be done, as fully to all intents and purposes as he or she might or could do in person, hereby ratifying and confirming all that said attorneys-in-fact and agents or any of them, or their or his or her substitute or substitutes, may lawfully do or cause to be done by virtue hereof.       Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated and on February 22, 2023. Principal Executive Officer Directors /s/ DARREN W. WOODS /s/ MICHAEL J. ANGELAKIS /s/ KAISA H. HIETALA Darren W. Woods, Chairman of the Board Michael J. Angelakis Kaisa H. Hietala /s/ SUSAN K. AVERY /s/ JOSEPH L. HOOLEY Principal Financial Officer Susan K. Avery Joseph L. Hooley   /s/ KATHRYN A. MIKELLS /s/ ANGELA F. BRALY /s/ STEVEN A. KANDARIAN Kathryn A. Mikells, Senior Vice President and Chief Financial Officer Angela F. Braly Steven A. Kandarian   /s/ URSULA M. BURNS /s/ ALEXANDER A. KARSNER Principal Accounting Officer Ursula M. Burns Alexander A. Karsner /s/ LEN M. FOX /s/ GREGORY J. GOFF /s/ LAWRENCE W. KELLNER Len M. Fox, Vice President and Controller Gregory J. Goff Lawrence W. Kellner /s/ JOHN D. HARRIS II /s/ JEFFREY W. UBBEN John D. Harris II Jeffrey W. Ubben 134\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0288 (i.e., a 2.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0288 = 3.4767, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028763, "expected_loss": 0.028763, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240808_0335", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-08-08", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0852, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0071, std=0.0304, worst_day=-0.1002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0852 (i.e., a 8.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0852 = 1.1740, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.085178, "expected_loss": 0.085178, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230209_0338", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-02-09", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0324, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0004, std=0.0171, worst_day=-0.0357\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-08] [\"3 Blue Chip Stocks To Watch In February 2023 Blue chip stocks are highly respected and established companies that have a strong reputation for stability and steady growth. Blue chip companies are typically leaders in their respective industries and have a long history of profitability, making them potentially attractive to both individual and institutional investors. Examples of blue chip stocks include large multinational corporations such as Apple (NASDAQ: AAPL), Johnson & Johnson (NYSE: JNJ), and Microsoft (NASDAQ: MSFT). These companies have proven track records of success, with a long history of consistently high earnings and steady growth. Their financial stability and reputation for reliability make them a popular choice among investors looking to build a balanced and diversified portfolio. In addition, blue chip stocks often pay dividends to shareholders, providing a steady source of income in addition to any potential capital gains. Investing in blue chip stocks can provide a solid foundation for your investment portfolio and offer peace of mind in knowing that you are investing in well-established companies with a long history of success. It\\u2019s important to note that, while these stocks are generally considered to be low-risk, no investment is completely risk-free, so it\\u2019s important to conduct your own research and due diligence. Accordingly, let\\u2019s look at three blue-chip stocks for you to watch in the stock market today. Blue Chip Stocks To Buy [Or Avoid] Today JP Morgan Chase & Co. (NYSE: JPM) The Procter & Gamble Company (NYSE: PG) The Coca-Cola Company (NYSE: KO) JP Morgan Chase & Co. (JPM Stock) To kick off this list let\\u2019s turn our attention to JP Morgan Chase & Co. (JPM). In brief, the company is one of the largest financial institutions in the United States. What\\u2019s more, JPM is organized into four major segments. These are consumer and community banking, corporate and investment banking, commercial banking, and asset and wealth management. Moving along, just last month, JPM reported its Q4 2022 financial and operating results. In the report, the company reported earnings per share of $3.57, along with $47.4 billion. For context, these numbers came in better than what analysts estimated, which was earnings of $3.11 per share and $34.2 billion in revenue. Moreover, JP Morgan Chase & Co also reported a 54.6% increase in revenue on a year-over-year basis. Looking since the beginning of 2023, shares of JPM stock have increased by 6.05%. Meanwhile, on Wednesday morning, JPM stock opened down by 0.26% and is currently trading at $143.29 a share. Source: TD Ameritrade TOS [Read More] 3 Natural Gas Stocks To Watch Today Procter & Gamble (PG Stock) Next, let\\u2019s look at consumer giant The Procter & Gamble Company (PG). This consumer goods behemoth owns popular brands like Tide, Crest, and Pampers. Additionally, PG currently operates in multiple business segments. These include Beauty, Grooming, Health Care, Fab\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0324 (i.e., a 3.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0324 = 3.0843, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032422, "expected_loss": 0.032422, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231002_0340", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-10-02", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0629, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0286, worst_day=-0.0806\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-01] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0629 (i.e., a 6.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0629 = 1.5892, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.062923, "expected_loss": 0.062923, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240105_0343", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2024-01-05", "context_summary": "HAUZ: 60-day history, VaR(99%)=-0.0180, max drawdown threshold=10%.", "question": "Asset: HAUZ\nDaily returns (past 60 days): mean=0.0015, std=0.0110, worst_day=-0.0191\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to HAUZ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0180 (i.e., a 1.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0180 = 5.5510, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018015, "expected_loss": 0.018015, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231109_0345", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-11-09", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0171, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=-0.0005, std=0.0084, worst_day=-0.0176\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-08] [\"AAPL Factor-Based Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple's Annual Buybacks Hit a 3-Year Low. Should Investors Be Concerned? On Nov. 2, Apple (NASDAQ: AAPL) reported its fourth-quarter and full-year fiscal 2023 results. Despite beating top- and bottom-line expectations, the company saw its stock fall as much as 2.4% on Friday, although it finished the day down just 0.5%. A lot of attention is focused on Apple's slowing re\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EFA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0171 (i.e., a 1.71% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0171 = 5.8543, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017082, "expected_loss": 0.017082, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230329_0348", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-03-29", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0162, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0003, std=0.0081, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-28] [\"Wall Street falls with tech shares as yields up By Caroline Valetkevitch March 28 (Reuters) - U.S. stocks were lower in afternoon trading on Tuesday, led by a nearly 1% decline in the Nasdaq as higher Treasury yields hit technology-related shares. Shares of Apple AAPL.O and Microsoft MSFT.O along with other technology-related shares, which tend to be the most negatively affected by rising yields, weighed the most on the S&P 500. Yields have climbed from six-months lows hit Friday as investors have been cautiously optimistic that stress in the banking sector following some recent regional bank failures may be subsiding. Shares of First Citizens BancShares Inc FCNCA.O were up about 2.2% on Tuesday, a day after the stock rose more than 50% after it said it would acquire the deposits and loans of Silicon Valley Bank. U.S. consumer confidence unexpectedly increased in March, according to a survey, which also showed Americans are becoming a bit anxious about the labor market. The rise in yields \\\"is causing a little bit of cautiousness in the market,\\\" said Peter Cardillo, chief market economist at Spartan Capital Securities in New York, while data suggested \\\"consumers are not too cheerful about rates going up and the prospects of a recession.\\\" Investors also paid close attention to comments in the first congressional hearing into the collapse of the two U.S. regional lenders. Both Democratic and Republican lawmakers pressed the Federal Reserve's top banking regulator on whether the central bank should have been more aggressive in its oversight of Silicon Valley Bank. \\\"If the market thinks there's not a banking crisis and that's in the rear view mirror, that would mean the Fed is able to hold rates higher for longer,\\\" said Irene Tunkel, chief U.S. equity strategist at BCA Research. The Dow Jones Industrial Average .DJI fell 108.04 points, or 0.33%, to 32,324.04, the S&P 500 .SPX lost 19.76 points, or 0.50%, to 3,957.77 and the Nasdaq Composite .IXIC dropped 105.51 points, or 0.9%, to 11,663.33. The KBW regional banking index .KRX was down on the day. Strategists said that as lenders report quarterly results from next month, the market will learn more details about the health of banks following the collapse of some big regional lenders that fanned fears of a sector-wide contagion. Alibaba Group Holding BABA.K jumped 14.1% after the company said it plans to split its business into six main units covering e-commerce, media and the cloud. Advancing issues outnumbered declining ones on the NYSE by a 1.04-to-1 ratio; on Nasdaq, a 1.53-to-1 ratio favored decliners. The S&P 500 posted 6 new 52-week highs and no new lows; the Nasdaq Composite recorded 30 new highs and 124 new lows. (Reporting by Caroline Valetkevitch; additional reporting by Shubham Batra, Amruta Khandekar, Sruthi Shankar and Shashwat Chauhan in Bengaluru; Editing by Savio D'Souza, Vinay Dwivedi and Aurora Ellis) ((caroline.valetkevitch@thomsonreuters.com)) The views and opinions expresse\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0162 (i.e., a 1.62% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0162 = 6.1633, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016225, "expected_loss": 0.016225, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231026_0351", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2023-10-26", "context_summary": "SCHP: 60-day history, VaR(99%)=-0.0072, max drawdown threshold=10%.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=-0.0005, std=0.0039, worst_day=-0.0075\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SCHP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0072 (i.e., a 0.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0072 = 13.9812, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.007152, "expected_loss": 0.007152, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230314_0354", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-03-14", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0189, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0001, std=0.0099, worst_day=-0.0246\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-13] [\"Apple's (AAPL) Animation Film Emerges Winner at 2023 Oscars Apple AAPL continues its winning stride at the Academy Awards with its animation movie The Boy, the Mole, the Fox and the Horse winning an Oscar for Best Animated Short Film. Last year, Apple won three Academy Awards for CODA. Based on the book by Charlie Mackesy, The Boy, the Mole, the Fox and the Horse has already won a BAFTA award, four Annie Awards including Best Special Production, and an NAACP Image Awards nomination for Outstanding Short Form (Animated) film. Apple\\u2019s impressive run at the Oscars has been instrumental in driving recognition of Apple TV+ in the saturated streaming market currently dominated by the likes of Amazon AMZN Prime Video, Netflix NFLX and Disney\\u2019s DIS Disney+. Nevertheless, the growing popularity of Apple TV+ and services like Fitness+ have been beneficial for Apple\\u2019s Services business, which has become a major revenue-generating source in recent times. The Services portfolio currently has more than 935 million paid subscribers and accounted for 17.7% of sales in the fiscal first quarter. Services revenues increased 6.4% from the year-ago quarter to $20.77 billion. Apple Inc. Price, Consensus and EPS Surprise Apple Inc. price-consensus-eps-surprise-chart | Apple Inc. Quote For the fiscal second quarter, Services revenues are expected to grow year over year despite challenging macroeconomic conditions, as well as weakness in digital advertising and gaming. Apple shares have outperformed the Zacks Computer and Technology sector in the past year. While AAPL shares have declined 1.4%, Netflix, Disney and Amazon shares have declined 11.5%, 27.4% and 36%, respectively. Estimates on the Rise The Zacks Consensus Estimate for Apple\\u2019s fiscal second-quarter earnings has increased by a penny to $1.44 over the past 30 days. Apple expects the fiscal second quarter\\u2019s year-over-year revenue growth to be similar to that of the December (fiscal first) quarter due to unfavorable forex. In the previous quarter, net sales decreased 5.5% year over year to $117.15 billion. Unfavorable forex hurt revenues by more than 800 basis points. For iPhone, Apple expects the March quarter\\u2019s year-over-year revenue growth to accelerate relative to the December quarter\\u2019s year-over-year revenue growth. For Mac and iPad, this Zacks Rank #3 (Hold) company expects revenues to decline double digits on a year-over-year basis due to challenging comparison and macroeconomic headwinds. You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. Free Report Reveals How You Could Profit from the Growing Electric Vehicle Industry Globally, electric car sales continue their remarkable growth even after breaking records in 2021. High gas prices have fueled his demand, but so has evolving EV comfort, features and technology. So, the fervor for EVs will be around long after gas prices normalize. Not only are manufacturers seeing record-high profit\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0189 (i.e., a 1.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0189 = 5.2777, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018948, "expected_loss": 0.018948, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240311_0357", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-03-11", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0311, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0018, std=0.0140, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0311 (i.e., a 3.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0311 = 3.2110, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031143, "expected_loss": 0.031143, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230321_0360", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-03-21", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0176, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0003, std=0.0080, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-20] [\"Kremlin tells officials to stop using iPhones - Kommersant newspaper Adds Kremlin quote, recasts lead MOSCOW, March 20 (Reuters) - The Kremlin told officials involved in preparations for Russia's 2024 presidential election to stop using Apple AAPL.O iPhones because of concerns that the devices are vulnerable to Western intelligence agencies, the Kommersant newspaper reported. At a Kremlin-organised seminar for officials involved in domestic politics, Sergei Kiriyenko, first deputy head of the presidential administration, told officials to change their phones by April 1, Kommersant said, citing unidentified sources. \\\"It's all over for the iPhone: either throw it away or give it to the children,\\\" Kommersant quoted one of the participants of the meeting as saying. \\\"Everyone will have to do it in March.\\\" When asked about the issue on Monday, Kremlin spokesman Dmitry Peskov said he could not confirm the report. \\\"Smartphones should not be used for official business,\\\" Peskov told reporters. \\\"Any smartphone has a fairly transparent mechanism, no matter what operating system it has \\u2013 Android or iOS. Naturally, they are not used for official purposes.\\\" Apple did not immediately respond to a request for comment. The Kremlin may provide other devices with different operating systems to replace the iPhones, Kommersant said, adding that the order to cease using iPhones had been directed at those involved in domestic politics - for which Kiriyenko is responsible. President Vladimir Putin has always said he has no smartphone, though Peskov has said Putin does use the Internet from time to time. Shortly after Russia sent its troops into Ukraine last year, U.S. and British spies claimed a scoop by uncovering - and going public with - intelligence that Putin was planning to invade. It is unclear how the spies obtained such intelligence. (Reporting by Guy Faulconbridge; Editing by Mark Trevelyan and Gareth Jones) ((guy.faulconbridge@thomsonreuters.com; 07825218698;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple (AAPL) Outpaces Stock Market Gains: What You Should Know Apple (AAPL) closed at $157.40 in the latest trading session, marking a +1.55% move from the prior day. This move outpaced the S&P 500's daily gain of 0.89%. At the same time, the Dow added 1.2%, and the tech-heavy Nasdaq lost 0.68%. Coming into today, shares of the maker of iPhones, iPads and other products had gained 1.61% in the past month. In that same time, the Computer and Technology sector gained 2.42%, while the S&P 500 lost 3.9%. Investors will be hoping for strength from Apple as it approaches its next earnings release. On that day, Apple is projected to report earnings of $1.44 per share, which would represent a year-over-year decline of 5.26%. Our most recent consensus estimate is calling for quarterly revenue of $93.39 billion, down 4% from the year-ago period. Looking at the ful\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0176 (i.e., a 1.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0176 = 5.6663, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017648, "expected_loss": 0.017648, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230804_0362", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-08-04", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0871, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0036, std=0.0432, worst_day=-0.0889\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-03] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0871 (i.e., a 8.71% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0871 = 1.1479, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.087115, "expected_loss": 0.087115, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230828_0365", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-08-28", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0434, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0007, std=0.0185, worst_day=-0.0575\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-27] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0434 (i.e., a 4.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0434 = 2.3034, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.043414, "expected_loss": 0.043414, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230123_0368", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-01-23", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0002, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0003, worst_day=-0.0002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ICSH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0002 (i.e., a 0.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0002 = 500.5482, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.0002, "expected_loss": 0.0002, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231120_0370", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-11-20", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0459, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0074, std=0.0249, worst_day=-0.0651\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0459 (i.e., a 4.59% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0459 = 2.1777, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.045919, "expected_loss": 0.045919, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240205_0373", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-02-05", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0397, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0051, std=0.0277, worst_day=-0.0405\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0397 (i.e., a 3.97% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0397 = 2.5213, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.039662, "expected_loss": 0.039662, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240513_0376", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-05-13", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0105, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0006, std=0.0048, worst_day=-0.0109\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0105 (i.e., a 1.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0105 = 9.5095, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010516, "expected_loss": 0.010516, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20231129_0379", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-11-29", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0163, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0003, std=0.0073, worst_day=-0.0199\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-28] [\"AAPL Quantitative Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple to end credit-card partnership with Goldman Sachs - WSJ Adds details on the contract in paragraph 2 Nov 28 (Reuters) - Apple AAPL.O is pulling the plug on its credit-card partnership with Goldman Sachs Group GS.N, the Wall Street Journal reported on Tuesday. The tech giant recently sent a proposal to the Wall Street bank to exit the contract in the next roughly 12 \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0163 (i.e., a 1.63% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0163 = 6.1459, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016271, "expected_loss": 0.016271, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240527_0381", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-05-27", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0181, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0008, std=0.0074, worst_day=-0.0183\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q BLK 2024-05-07] 10-Q --12-31 Q1 0001364742 false http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#OtherAssets http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense http://fasb.org/us-gaap/2023#NonoperatingIncomeExpense 2024-06 2024-03 2024-06 2024-03 http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GainLossOnInvestments http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense http://fasb.org/us-gaap/2023#GeneralAndAdministrativeExpense 2028-03-31 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 9 1 1 1 1 1 P2Y 0 years 0 years 2027-05-30 2028-05-30 2029-05-30 2027-05-30 2028-05-30 2029-05-30 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:PrivateEquityFundsMember us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:InvestmentInNAVMember 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2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0181 (i.e., a 1.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0181 = 5.5396, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018052, "expected_loss": 0.018052, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230808_0384", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-08-08", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0936, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0004, std=0.0515, worst_day=-0.1180\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-07] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0936 (i.e., a 9.36% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0936 = 1.0683, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.093603, "expected_loss": 0.093603, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240206_0387", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-02-06", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0397, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0277, worst_day=-0.0405\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0397 (i.e., a 3.97% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0397 = 2.5213, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.039662, "expected_loss": 0.039662, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240124_0389", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-01-24", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0002, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0003, std=0.0003, worst_day=-0.0002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ICSH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0002 (i.e., a 0.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0002 = 502.7867, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000199, "expected_loss": 0.000199, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240418_0392", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2024-04-18", "context_summary": "JNK: 60-day history, VaR(99%)=-0.0086, max drawdown threshold=10%.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=-0.0001, std=0.0032, worst_day=-0.0093\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to JNK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0086 (i.e., a 0.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0086 = 11.6758, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008565, "expected_loss": 0.008565, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230719_0395", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-07-19", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0162, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0006, std=0.0077, worst_day=-0.0171\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-18] [\"Spain antitrust watchdog fines Amazon, Apple $218 million Adds CNMC quotes, detail throughout MADRID, July 18 (Reuters) - Spain's antitrust watchdog on Tuesday said it had imposed fines worth a total 194.1 million euros ($218.03 million) on Amazon AMZN.O and Apple AAPL.O for colluding to limit the online sale of devices from Apple and competitors in Spain. The two contracts the companies signed on Oct. 31, 2018 granting Amazon the status of authorized Apple dealer included anti-competitive clauses that affected the online market for electronic devices in Spain, CNMC, as the watchdog is known, said in a statement. \\\"The two companies restricted without justification the number of sellers of Apple products on the Amazon website in Spain,\\\" it said. More than 90% of the existing retailers who were using Amazon's market place to sell Apple devices were blocked as a result, CNMC added. Amazon also reduced the capacity of retailers in the European Union based outside Spain to access Spanish customers, the regulator said. It also restricted the advertising Apple's competitors were allowed to place on its website when users searched for Apple products, CNMC said. Following the deal between the two tech giants, the prices of Apple devices sold online rose in Spain, it added. Apple was fined 143.6 million euros and Amazon 50.5 million euros. The two companies have two months to appeal the decision. Representatives for Apple and Amazon did not immediately respond to requests for comment. ($1 = 0.8902 euros) (Reporting by Inti Landauro; Editing by David Latona and Jan Harvey) ((Inti.Landauro@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"AAPL Quantitative Stock Analysis - Warren Buffett Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Patient Investor model based on the published strategy of Warren Buffett. This strategy seeks out firms with long-term, predictable profitability and low debt that trade at reasonable valuations. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 100% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. EARNINGS PREDICTABILITY: PASS DEBT SERVICE: PASS RETURN ON EQUITY: PASS RETURN ON TOTAL CAPITAL: PASS FREE CASH FLOW: PASS USE OF RETAINED EARNINGS: PASS SHARE REPURCHASE: PASS INITIAL RATE OF RETURN: \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MTUM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0162 (i.e., a 1.62% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0162 = 6.1834, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016172, "expected_loss": 0.016172, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230816_0398", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-08-16", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0338, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0000, std=0.0180, worst_day=-0.0341\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-15] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0338 (i.e., a 3.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0338 = 2.9579, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033808, "expected_loss": 0.033808, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230116_0401", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-01-16", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0713, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0018, std=0.0303, worst_day=-0.0854\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-15] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0713 (i.e., a 7.13% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0713 = 1.4019, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.071333, "expected_loss": 0.071333, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241023_0404", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2024-10-23", "context_summary": "CSHI: 60-day history, VaR(99%)=-0.0013, max drawdown threshold=10%.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0006, worst_day=-0.0014\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CSHI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0013 (i.e., a 0.13% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0013 = 75.6589, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.001322, "expected_loss": 0.001322, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230405_0406", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-04-05", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0161, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0001, std=0.0076, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-04] [\"Wall Street Analysts Think Apple (AAPL) Is a Good Investment: Is It? The recommendations of Wall Street analysts are often relied on by investors when deciding whether to buy, sell, or hold a stock. Media reports about these brokerage-firm-employed (or sell-side) analysts changing their ratings often affect a stock's price. Do they really matter, though? Before we discuss the reliability of brokerage recommendations and how to use them to your advantage, let's see what these Wall Street heavyweights think about Apple (AAPL). Apple currently has an average brokerage recommendation (ABR) of 1.35, on a scale of 1 to 5 (Strong Buy to Strong Sell), calculated based on the actual recommendations (Buy, Hold, Sell, etc.) made by 24 brokerage firms. An ABR of 1.35 approximates between Strong Buy and Buy. Of the 24 recommendations that derive the current ABR, 18 are Strong Buy and three are Buy. Strong Buy and Buy respectively account for 75% and 12.5% of all recommendations. Brokerage Recommendation Trends for AAPL Check price target & stock forecast for Apple here>>> The ABR suggests buying Apple, but making an investment decision solely on the basis of this information might not be a good idea. According to several studies, brokerage recommendations have little to no success guiding investors to choose stocks with the most potential for price appreciation. Do you wonder why? As a result of the vested interest of brokerage firms in a stock they cover, their analysts tend to rate it with a strong positive bias. According to our research, brokerage firms assign five \\\"Strong Buy\\\" recommendations for every \\\"Strong Sell\\\" recommendation. This means that the interests of these institutions are not always aligned with those of retail investors, giving little insight into the direction of a stock's future price movement. It would therefore be best to use this information to validate your own analysis or a tool that has proven to be highly effective at predicting stock price movements. Zacks Rank, our proprietary stock rating tool with an impressive externally audited track record, categorizes stocks into five groups, ranging from Zacks Rank #1 (Strong Buy) to Zacks Rank #5 (Strong Sell), and is an effective indicator of a stock's price performance in the near future. Therefore, using the ABR to validate the Zacks Rank could be an efficient way of making a profitable investment decision. Zacks Rank Should Not Be Confused With ABR Although both Zacks Rank and ABR are displayed in a range of 1-5, they are different measures altogether. The ABR is calculated solely based on brokerage recommendations and is typically displayed with decimals (example: 1.28). In contrast, the Zacks Rank is a quantitative model allowing investors to harness the power of earnings estimate revisions. It is displayed in whole numbers -- 1 to 5. It has been and continues to be the case that analysts employed by brokerage firms are overly optimistic with their recommendations. Because o\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0161 (i.e., a 1.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0161 = 6.1996, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01613, "expected_loss": 0.01613, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241127_0409", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-11-27", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0712, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0071, std=0.0385, worst_day=-0.0730\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0712 (i.e., a 7.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0712 = 1.4037, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.071243, "expected_loss": 0.071243, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240805_0412", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-08-05", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0170, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0001, std=0.0083, worst_day=-0.0190\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:CommercialPaperMember 2024-06-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2024-06-29 0000 [...TRUNCATED...] purchases 45,690  $ 169.74  45,690  May 5, 2024 to June 1, 2024: Open market and privately negotiated purchases 51,729  $ 188.38  51,729  June 2, 2024 to June 29, 2024: Open market and privately negotiated purchases 41,354  $ 205.54  41,354  Total 138,773  $ 114,074  (1) On May 4, 2023, the Board of Directors authorized the purchase of up to $90 billion of the Company’s common stock under a share repurchase program. As of June 29, 2024, remaining availability under the May 2023 program was $4.1 billion. On May 2, 2024, the Board of Directors authorized an additional program to repurchase up to $110 billion of the Company’s common stock. The programs do not obligate the Company to acquire a minimum amount of shares. Under the programs, shares may be repurchased in privately negotiated or open market transactions, including under plans complying with Rule 10b5-1 under the Exchange Act. Item 3.    Defaults Upon Senior Securities None. Item 4.    Mine Safety Disclosures Not applicable. Item 5.    Other Information Insider Trading Arrangements On May 24, 2024 , Tim Cook , the Company’s Chief Executive Officer , entered into a trading plan intended to satisfy the affirmative defense conditions of Rule 10b5-1(c) under the Exchange Act. The plan provides for the sale, subject to certain price limits, of shares vesting during the duration of the plan pursuant to certain equity awards granted to Mr. Cook, excluding shares withheld by the Company to satisfy income tax withholding and remittance obligations. Mr. Cook’s plan will expire on May 24, 2026, subject to early termination in accordance with the terms of the plan. Apple Inc. | Q3 2024 Form 10-Q | 20 Item 6.    Exhibits Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 31.1* Rule 13a-14(a) / 15d-14(a) Certification of Chief Executive Officer. 31.2* Rule 13a-14(a) / 15d-14(a) Certification of Chief Financial Officer. 32.1** Section 1350 Certifications of Chief Executive Officer and Chief Financial Officer. 101* Inline XBRL Document Set for the condensed consolidated financial statements and accompanying notes in Part I, Item 1, “Financial Statements” of this Quarterly Report on Form 10-Q. 104* Inline XBRL for the cover page of this Quarterly Report on Form 10-Q, included in the Exhibit 101 Inline XBRL Document Set. *    Filed herewith. **    Furnished herewith. Apple Inc. | Q3 2024 Form 10-Q | 21 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: August 1, 2024 Apple Inc. By: /s/ Luca Maestri Luca Maestri Senior Vice President, Chief Financial Officer Apple Inc. | Q3 2024 Form 10-Q | 22\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0170 (i.e., a 1.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0170 = 5.8963, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01696, "expected_loss": 0.01696, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240904_0415", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-09-04", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0901, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0027, std=0.0389, worst_day=-0.1002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0901 (i.e., a 9.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0901 = 1.1103, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.090068, "expected_loss": 0.090068, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241004_0418", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-10-04", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0556, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0275, worst_day=-0.0652\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0556 (i.e., a 5.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0556 = 1.7994, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.055574, "expected_loss": 0.055574, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241230_0421", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-12-30", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1303, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0105, std=0.0694, worst_day=-0.1824\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7673", "answer_numeric": 0.7673, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1303 (i.e., a 13.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1303 = 0.7673, capped at 1.0.\nMaximum position size = 0.7673 (76.7% of portfolio).", "metadata": {"var_99": -0.130335, "expected_loss": 0.130335, "max_drawdown_threshold": 0.1, "position_size": 0.7673, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230621_0424", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-06-21", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0361, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0007, std=0.0183, worst_day=-0.0438\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-20] [\"Got $10,000? Here Are 3 Stocks to Buy There is no better time to invest than now, as the saying goes. Starting as soon as you can ensures that you not only compound your wealth over time, but also start accumulating a dividend stream that will provide you with useful passive income. Rather than segregate investors into either growth or income, I believe you can enjoy the best of both worlds by setting up your investment portfolio with a healthy mix of each type of stock. You should adhere to a set of criteria when choosing suitable stocks for your portfolio. Companies should have a strong brand or competitive moat ensuring they can continue to draw customers. They should also possess a long growth runway and be innovative in launching new products and services that generate customer loyalty. It also does not hurt if a company has a strong track record of growing its dividends as this means it can likely continue doing so. So if you have $10,000 to spare, here are three stocks you might want to consider accumulating. Image source: Getty images. Apple Apple (NASDAQ: AAPL) needs no introduction -- it's a pioneer in the smartphone industry armed with a plethora of useful gadgets and devices that many cannot do without. Its iconic iPhone, iPad, and Apple Watch have set the standard for many competitors, and the company has a large and loyal following of customers that eagerly await each new product launch. Despite being a trillion-dollar company, Apple posted revenue growth of 7.8% year over year for its fiscal 2022, along with a 5.4% year-over-year increase in net income. For the first six months of fiscal 2023, Apple posted a rare 4.2% year-over-year revenue decline, with net income slipping by 9.2% year over year to $54.2 billion. The drop was because of supply chain woes amid the U.S.-China spat, but many investors believe that this is merely a blip for the company. Despite the weaker numbers, there is now palpable excitement over Apple as the company launches its first major piece of hardware in nearly a decade, the Vision Pro. The new headset promises to blend the real and virtual worlds using a mix of virtual and augmented reality, and promises a new level of immersion and clarity, all with a price tag of $3,500. Apple is also thinking of shifting around 18% of its global iPhone production to India by 2025, reducing its reliance on China and possibly enjoying better margins as costs are lower in India compared with China. Meanwhile, investors can also enjoy quarterly dividends fof $0.24 per share, a slight year-over-year increase from the $0.23 paid out a year earlier. Polaris Polaris (NYSE: PII) is a manufacturer of power sports vehicles, such as off-road vehicles, snowmobiles, and motorcycles. The company has remained resilient through the pandemic as its vehicles continue to find a ready market. Sales rose from $7 billion in 2020 to $8.6 billion in 2020, with net income (excluding exceptional and one-off items) climbing from $504 million t\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to FXI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0361 (i.e., a 3.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0361 = 2.7664, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.036149, "expected_loss": 0.036149, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240116_0426", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2024-01-16", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0151, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0016, std=0.0094, worst_day=-0.0175\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VLUE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0151 (i.e., a 1.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0151 = 6.6298, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015083, "expected_loss": 0.015083, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240723_0428", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-07-23", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0568, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0013, std=0.0230, worst_day=-0.0724\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0568 (i.e., a 5.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0568 = 1.7613, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056777, "expected_loss": 0.056777, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231130_0433", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-11-30", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0177, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0003, std=0.0085, worst_day=-0.0191\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-29] [\"3 Unstoppable Growth Stocks to Buy if There's a Stock Market Sell-Off The stock market has been on a nice run of late. At the time of this writing, the S&P 500 has gained 7% over the past month while the Nasdaq Composite has risen by 8%. While it's always great to see green in your brokerage account, with higher prices come higher valuations. Paying too much for even a great growth stock can significantly cut into investor returns. However, it is inevitable that the market will eventually turn and stocks will fall. That can be difficult to endure, but it will also provide buying opportunities for the best businesses in the world. Let's take a look at three growth companies with stocks to buy if there's a sell-off in the market. Nvidia Semiconductor chip developer Nvidia (NASDAQ: NVDA) has been in the news lately for very good reasons. Driven by the rush into artificial intelligence (AI), Nvidia has seen mind-boggling results in the last two quarters. Consider the year-over-year revenue growth and net income over the latest two quarters of its fiscal 2024 (ended Oct. 29, 2023). METRIC Q2 2024 Q3 2024 Revenue growth (YOY) 101% 206% Net income (YOY) 843% 1,259% Data source: Nvidia. Management expects this trend to continue at least for another quarter. Fourth-quarter 2024 revenue is projected to be $20 billion. That would represent a 231% increase over Q4 2023. The majority of this growth has been in Nvidia's data center business and it's because of the interest in chips that can help with artificial intelligence. Even if the AI revolution is upon us, it's unlikely Nvidia will see this level of growth over the long term. As one might expect, the valuation of Nvidia shares is a reflection of the recent results. Nvidia currently trades for 115 times trailing earnings. Compare that to the S&P 500's price-to-earnings (P/E) ratio of 25 and it's clear that investors may be better off waiting for the stock to pull back before buying shares. Apple Apple (NASDAQ: AAPL) is a great company and still is likely to show periods of growth ahead, but the current valuation suggests it may be best to wait before buying shares. Apple is trading for a P/E multiple of 31, which is well above the market average. What makes that more concerning from the standpoint of potential returns is that the results over the last few quarters are showing signs of slowing momentum. In the most recently reported fiscal quarter, revenue growth declined by 1% year over year. This was the fourth consecutive quarter with a decline in year-over-year revenue growth. Both revenue and free cash flow have been trending down over the last year. AAPL Free Cash Flow (Quarterly) data by YCharts There's every chance that this is a temporary lull in Apple's growth story. However, the current valuation doesn't match the results. There's a chance that Apple's growth reaccelerates from here, rewarding shareholders who buy today. However, the more likely scenario is that results from today's valuation \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QUAL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0177 (i.e., a 1.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0177 = 5.6593, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01767, "expected_loss": 0.01767, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241014_0436", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2024-10-14", "context_summary": "TLH: 60-day history, VaR(99%)=-0.0141, max drawdown threshold=10%.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=0.0001, std=0.0065, worst_day=-0.0176\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to TLH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0141 (i.e., a 1.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0141 = 7.1170, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014051, "expected_loss": 0.014051, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230829_0439", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-08-29", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.0920, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0006, std=0.0503, worst_day=-0.0925\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-28] [\"What's Going On With Apple Stock? Fool.com contributor Parkev Tatevosian reviews the latest quarterly update from Apple (NASDAQ: AAPL) to offer insights to everyday investors. *Stock prices used were the afternoon prices of Aug. 25, 2023. The video was published on Aug. 27, 2023. 10 stocks we like better than Apple When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now... and Apple wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of August 21, 2023 Parkev Tatevosian, CFA has positions in Apple. The Motley Fool has positions in and recommends Apple. The Motley Fool has a disclosure policy. Parkev Tatevosian is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through his link, he will earn some extra money that supports his channel. His opinions remain his own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"New Zealand plans digital services tax for multinationals from 2025 Aug 29 (Reuters) - New Zealand said on Tuesday it would introduce legislation for a digital services tax on large multinational companies from 2025 after talks for a global rollout did not reach consensus at the Organization for Economic Cooperation and Development (OECD). More than 140 countries were supposed to start implementing next year a 2021 deal overhauling decades-old rules on how governments tax multinationals that are widely considered to be outdated as digital giants like Apple AAPL.O or Amazon AMZN.O can book profits in low-tax countries. But the proposal was pushed back last month after countries with digital services taxes, with the exception of Canada, agreed to hold off applying them for at least another year. \\\"While we will keep working to support a multilateral agreement, we are not prepared to simply wait around until then to find out,\\\" Finance Minister Grant Robertson said in a statement. \\\"We don't think it's fair that everyday Kiwis pay their fair share of taxes but there's no tax liability for large multinationals.\\\" The proposed digital services tax will target multinational businesses that earn income from New Zealand users of social media platforms, search engines, and online marketplaces. The tax would be payable by businesses that make over 750 million euros ($812 million) a year from global digital services and over NZ$3.5 million a year from digital services provided to New Zealand users. It is expected to generate NZ$222 million over four years. The tax would be applied at 3% on gross taxable New Zealand digital services revenue, a similar rate adopted by comparable countrie\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0920 (i.e., a 9.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0920 = 1.0867, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.092025, "expected_loss": 0.092025, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230413_0442", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-04-13", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1245, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0007, std=0.0588, worst_day=-0.1284\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-12] [\"Wall Street rises as inflation data soothes rate-hike jitters By Sruthi Shankar and Ankika Biswas April 12 (Reuters) - U.S. stock indexes were higher on Wednesday after data showed consumer prices cooled faster than expected in March, raising hopes that the Federal Reserve could hit pause on its interest rate hiking cycle soon. The Labor Department data showed headline and core CPI in March rose 0.1% and 0.4%, respectively, on a month-on-month basis. Economists were expecting a rise of 0.2% and 0.4%, respectively. On a year-over-year basis, the headline number rose 5% against economists' estimates of a 5.2% rise, while the core measure, which strips out volatile food and energy prices, climbed 5.6% in-line with consensus estimates. \\\"Today's CPI takes some heat off the Fed, for now. Moderating price pressures combined with signs of cooling in the labor market will offer a temporary reprieve to markets,\\\" said Ronald Temple, chief market strategist at Lazard. \\\"While this is good news, it does not mean tightening is over. Core inflation remains far above the Fed's target, and the path to 2% will be bumpy.\\\" Stubbornly high rents kept underlying inflation pressures simmering, likely ensuring that the U.S. central bank will raise interest rates again next month. Traders mostly stuck to bets that the Fed will hike rates by 25 basis points next month, with Fed fund futures pricing in a 70% chance of such a move. After the banking turmoil last month, investors were betting that the Fed will soon end its aggressive monetary tightening campaign and also start cutting rates in the back half of the year amid growing concerns of a recession. Major technology and other growth stocks such as Microsoft Corp MSFT.O, Tesla Inc TSLA.O and Apple Inc AAPL.O edged higher as Treasury yields slipped. US/ Minutes from the U.S. central bank's policy meeting in March will also be watched closely by investors later in the day for further clues on the trajectory of interest rates. The Fed raised rates by 25 bps last month and signaled it was on the verge of pausing further rate hikes. Investors are also awaiting the first-quarter earnings season, which begins in earnest on Friday with results from three major banks, Citigroup Inc C.N, JPMorgan Chase & Co JPM.N and Wells Fargo & Co WFC.N. At 9:58 a.m. ET, the Dow Jones Industrial Average .DJI was up 155.96 points, or 0.46%, at 33,840.75, the S&P 500 .SPX was up 13.20 points, or 0.32%, at 4,122.14, and the Nasdaq Composite .IXIC was up 9.36 points, or 0.08%, at 12,041.24. American Airlines Group Inc AAL.O dropped 7.1% as it forecast a lower-than-expected profit for the first quarter as the carrier battles high fuel costs. The wider airlines index .SPLRCALI fell nearly 4%. U.S.-listed shares of Chinese firms Alibaba Group Holding Ltd BABA.N and JD.com Inc JD.O fell almost 4% each as investors weighed rising geopolitical tensions. Taiwan said on Wednesday it had successfully urged China to drastically narrow its plan to clos\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8030", "answer_numeric": 0.803, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1245 (i.e., a 12.45% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1245 = 0.8030, capped at 1.0.\nMaximum position size = 0.8030 (80.3% of portfolio).", "metadata": {"var_99": -0.124526, "expected_loss": 0.124526, "max_drawdown_threshold": 0.1, "position_size": 0.803, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240816_0445", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2024-08-16", "context_summary": "EMB: 60-day history, VaR(99%)=-0.0089, max drawdown threshold=10%.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0008, std=0.0045, worst_day=-0.0102\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EMB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0089 (i.e., a 0.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0089 = 11.2871, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.00886, "expected_loss": 0.00886, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230622_0447", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-06-22", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0653, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0032, std=0.0237, worst_day=-0.0915\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-21] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0653 (i.e., a 6.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0653 = 1.5322, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.065266, "expected_loss": 0.065266, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240813_0450", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-08-13", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0979, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0050, std=0.0450, worst_day=-0.1260\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0979 (i.e., a 9.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0979 = 1.0216, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.09789, "expected_loss": 0.09789, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230104_0451", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-01-04", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0212, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0008, std=0.0113, worst_day=-0.0231\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-03] [\"US STOCKS-Wall St starts the year with a dip; Apple, Tesla shares drag By Sin\\u00e9ad Carew and Amruta Khandekar Jan 3 (Reuters) - Wall Street's main indexes closed lower on the first trading day of 2023 with the biggest drags from Tesla and Apple, while investors worried about the Federal Reserve's interest-rate hiking path as they awaited minutes from its December meeting. Shares in electric vehicle maker Tesla Inc TSLA.O closed down 12% after hitting their lowest level since August 2020 and put pressure on the consumer discretionary sector .SPLRCD following a miss on Wall Street estimates for fourth-quarter deliveries. Apple Inc AAPL.O shares sank 3.7%, with the iPhone maker hitting its lowest level since June 2021, after a report from Nikkei Asia pointed to weaker demand. In addition, an analyst downgraded their rating of the stock due to production cuts in COVID-19-hit China. The energy sector .SPNY, which logged stellar gains in 2022, closed down 3.6% in the year's first trading day as oil prices fell on bleak business activity data from China and concerns about the global economic outlook. O/R. The main U.S. stock indexes in 2022 showed their steepest annual losses since 2008 following the Fed's fastest pace of rate hikes since the 1980s to stamp out decades-high inflation. \\\"2022 was a terrible year for equity markets. Some of the reasons for that haven't dissipated because we turned the calendar,\\\" said Michael James, managing director of equity trading at Wedbush Securities in Los Angeles. \\\"There's still elevated anxiety, uncertainty about the Fed and inflation. Until there's clarity on that, it's going to be tough to make any upside headway in equity markets.\\\" Given Apple and Tesla's clout in the market, James also cited specific concerns about them for broader S&P weakness Tuesday. The Dow Jones Industrial Average .DJI fell 10.88 points, or 0.03%, to 33,136.37; the S&P 500 .SPX lost 15.36 points, or 0.40%, to 3,824.14; and the Nasdaq Composite .IXIC dropped 79.50 points, or 0.76%, to 10,386.99. The S&P 500 had shed 19.4% in 2022, marking a roughly $8 trillion decline in market capitalization, while the Nasdaq fell 33.1%, dragged down by growth stocks. Among the S&P 500's 11 major sectors, behind energy, technology was the second biggest decliner, losing 1%, with Apple hastening the decline as it ended the day with a market valuation below $2 trillion for the first time since March 2021. Tesla's biggest daily percentage drop since September 2020 helped make the consumer discretionary index .SPLRCD the S&P's third weakest sector on the day with a 0.6% drop. The benchmark's biggest gainer on the day was communications services .SPLRCL, with Facebook parent Meta Platforms Inc META.O leading the advancers there with a gain of 3.7%. Investors on Wednesday will closely monitor the minutes of the Fed's December policy meeting, when the central bank raised interest rates by 50 basis points after four straight 75 basis points hikes and sign\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MTUM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0212 (i.e., a 2.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0212 = 4.7147, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02121, "expected_loss": 0.02121, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241217_0454", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-12-17", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0427, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0079, std=0.0274, worst_day=-0.0501\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0427 (i.e., a 4.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0427 = 2.3413, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042711, "expected_loss": 0.042711, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230821_0457", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-08-21", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0660, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0025, std=0.0272, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-20] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0660 (i.e., a 6.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0660 = 1.5151, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.066003, "expected_loss": 0.066003, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230619_0462", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-06-19", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1065, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0080, std=0.0318, worst_day=-0.1516\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-18] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9387", "answer_numeric": 0.9387, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1065 (i.e., a 10.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1065 = 0.9387, capped at 1.0.\nMaximum position size = 0.9387 (93.9% of portfolio).", "metadata": {"var_99": -0.106532, "expected_loss": 0.106532, "max_drawdown_threshold": 0.1, "position_size": 0.9387, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230720_0465", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-07-20", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0132, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0017, std=0.0075, worst_day=-0.0160\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-19] [\"Technology Sector Update for 07/19/2023: AAPL, U, MSFT, ATVI Tech stocks were lower Wednesday afternoon with the Technology Select Sector SPDR Fund (XLK) decreasing 0.5% and the Philadelphia Semiconductor index falling 1.1%. In company news, Apple (AAPL) has been working on generative artificial intelligence tools to catch up with rivals, but it hasn't decided yet how to release the new technology to consumers, Bloomberg reported Wednesday. Apple shares were adding 0.5%. Unity Software (U) was up 1.7% after the company launched its beta program for visionOS, the operating system that powers Apple's Vision Pro. Microsoft (MSFT) and Activision Blizzard (ATVI) revised some terms of their planned deal and extended the time period by which the companies must close the deal as they seek to resolve the remaining regulatory hurdles. Microsoft shares fell1.9% and Activision dropped 0.5%. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple tests generative AI tools to rival OpenAI's ChatGPT - Bloomberg News Updates shares, adds details from the report and background July 19 (Reuters) - Apple AAPL.O is working on artificial intelligence(AI) offerings similar to OpenAI's ChatGPT and Google's Bard, Bloomberg News reported on Wednesday, sending its shares up as much as 2% to a record high. The iPhone maker has built its own framework, known as \\\"Ajax\\\", to create large language models (LLMs) and is also testing a chatbot that some engineers call \\\"Apple GPT\\\", the report said,citing people with knowledge of the matter. The company did not respond to a Reuters request for comment. Apple has so far held back from any big moves in AI and even avoided mentioning the buzzword at its developer conference in June - in stark contrast to other tech giants such as Alphabet GOOGL.O and Microsoft MSFT.Owhich have made bold moves to incorporate the breakthrough technology. Shares of Microsoft, Nvidia NVDA.O and Alphabet dropped more than 1% after the report. Apple has, however, subtly pushed advanced AI in some of its products such as Apple Photos, on device texting, and the recently launched mixed-reality headset Vision Pro. Still, analysts say the company is behind peers in incorporating the new technology. Apple's core AI product, voice assistant Siri, has also stagnated over the years. The Bloomberg report said several teams are involved in the latest AI effort, which is led by John Giannandrea, the company's head of machine learning and AI, andCraig Federighi, Apple's top software engineering executive. Apple's new virtual assistant summarizes text and answers questions based on data it has been trained with, and is being used internally for product prototyping, according to the report. Employees say the tool essentially replicates Bard, ChatGPT and Bing AI, and works as a web application. Apple does not yet have a concrete plan for the tools it is developing, but it is aiming\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0132 (i.e., a 1.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0132 = 7.5751, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013201, "expected_loss": 0.013201, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231222_0468", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-12-22", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0912, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0057, std=0.0405, worst_day=-0.0973\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0912 (i.e., a 9.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0912 = 1.0969, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.091162, "expected_loss": 0.091162, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230815_0471", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-08-15", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0379, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0024, std=0.0231, worst_day=-0.0418\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-14] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0379 (i.e., a 3.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0379 = 2.6413, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03786, "expected_loss": 0.03786, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240326_0474", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-03-26", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0868, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0126, std=0.0424, worst_day=-0.0885\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0868 (i.e., a 8.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0868 = 1.1519, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.086816, "expected_loss": 0.086816, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241227_0477", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-12-27", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1152, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0176, std=0.0666, worst_day=-0.1578\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8680", "answer_numeric": 0.868, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1152 (i.e., a 11.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1152 = 0.8680, capped at 1.0.\nMaximum position size = 0.8680 (86.8% of portfolio).", "metadata": {"var_99": -0.115204, "expected_loss": 0.115204, "max_drawdown_threshold": 0.1, "position_size": 0.868, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240118_0479", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-01-18", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0217, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0006, std=0.0107, worst_day=-0.0235\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLU, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0217 (i.e., a 2.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0217 = 4.5987, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021745, "expected_loss": 0.021745, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240726_0482", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-07-26", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0583, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0028, std=0.0242, worst_day=-0.0724\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0583 (i.e., a 5.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0583 = 1.7148, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.058315, "expected_loss": 0.058315, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230522_0485", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2023-05-22", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0007, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0001, std=0.0004, worst_day=-0.0008\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ICSH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0007 (i.e., a 0.07% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0007 = 147.2769, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000679, "expected_loss": 0.000679, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240624_0487", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-24", "context_summary": "SPY: 60-day history, VaR(99%)=-0.0147, max drawdown threshold=10%.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0009, std=0.0068, worst_day=-0.0160\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SPY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0147 (i.e., a 1.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0147 = 6.7808, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014747, "expected_loss": 0.014747, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20231220_0489", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-12-20", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0162, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0018, std=0.0080, worst_day=-0.0166\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] [\"Here's Why I Just Sold These 2 Blue-Chip Stocks, Even Though They're Great Businesses One of our contributors recently sold several positions, including two absolutely incredible businesses.\", \"JPMorgan Among Winners as Latin American Wealth Flocks to Miami (Bloomberg) -- Latin America\\u2019s wealthiest investors are taking their fortunes to Miami at one of the fastest clips in history, with some fleeing regional turmoil and others lured by yields higher than they can find at home.Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Houthi Ship AttacksUS Announces New Task Force to Counter Houthi Red Sea ThreatUS Frackers Return to\", \"Demise of Small Caps Haunts Wall Street in the Age of Big Tech (Bloomberg) -- Declaring the demise of an asset class is a mistake people have made since the dawn of markets. It\\u2019s a temptation many on Wall Street succumbed to recently when small-cap stocks notched two-decade lows versus the S&P 500 \\u2013 only to rally sharply after the Federal Reserve\\u2019s dovish policy surprise last week.Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Hou\", \"Brazil Central Bank Reinforces Cautious View on Fight to Bring Inflation Back to Target (Bloomberg) -- Brazil\\u2019s central bank reinforced there\\u2019s still a long way to go to bring inflation back to target, warning that the El Nino weather pattern may have a bigger impact on food prices than initially thought. Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Houthi Ship AttacksUS Announces New Task Force to Counter Houthi Red Sea ThreatUS Frackers Return to Haun\", \"Will Taiwan Semiconductor Be a Trillion-Dollar Stock by 2030? Taiwan Semiconductor has a vital product for many of the most important tech companies.\", \"UBS Investor Cevian to Be an \\u2018Engaged Owner\\u2019 Over Long Term (Bloomberg) -- Activist investor Cevian Capital AB, which picked up a $1.3 billion stake in UBS Group AG, said it\\u2019s planning to hold the shares for the long term, betting the Swiss bank\\u2019s current strategy would help create the world\\u2019s biggest global wealth manager. Most Read from BloombergApple Races to Tweak Software Ahead of Looming US Watch BanApple to Halt US Sales of Smartwatches After Patent LossGulf Splits Hinder US Efforts to End Houthi Ship AttacksWhat If Putin Wins? US Allies Fear Defe\", \"Canadian Dollar Surges to Highest Since August as Inflation Stays Elevated (Bloomberg) -- The rate of inflation in Canada unexpectedly remained stuck at 3.1% last month, giving the central bank another reason to keep its policy rate at the highest level in two decades.Most Read from BloombergApple Races t\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QUAL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0162 (i.e., a 1.62% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0162 = 6.1676, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016214, "expected_loss": 0.016214, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241226_0492", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2024-12-26", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0269, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0008, std=0.0098, worst_day=-0.0352\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MTUM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0269 (i.e., a 2.69% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0269 = 3.7125, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026936, "expected_loss": 0.026936, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20231127_0494", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2023-11-27", "context_summary": "ITB: 60-day history, VaR(99%)=-0.0459, max drawdown threshold=10%.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=0.0001, std=0.0176, worst_day=-0.0460\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ITB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0459 (i.e., a 4.59% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0459 = 2.1793, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.045886, "expected_loss": 0.045886, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230203_0497", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-02-03", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0223, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0013, std=0.0112, worst_day=-0.0245\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-02] [\"Apple (AAPL) Misses Q1 Earnings and Revenue Estimates Apple (AAPL) came out with quarterly earnings of $1.88 per share, missing the Zacks Consensus Estimate of $1.93 per share. This compares to earnings of $2.10 per share a year ago. These figures are adjusted for non-recurring items. This quarterly report represents an earnings surprise of -2.59%. A quarter ago, it was expected that this maker of iPhones, iPads and other products would post earnings of $1.26 per share when it actually produced earnings of $1.29, delivering a surprise of 2.38%. Over the last four quarters, the company has surpassed consensus EPS estimates three times. Apple, which belongs to the Zacks Computer - Mini computers industry, posted revenues of $117.15 billion for the quarter ended December 2022, missing the Zacks Consensus Estimate by 3.34%. This compares to year-ago revenues of $123.95 billion. The company has topped consensus revenue estimates three times over the last four quarters. The sustainability of the stock's immediate price movement based on the recently-released numbers and future earnings expectations will mostly depend on management's commentary on the earnings call. Apple shares have added about 11.9% since the beginning of the year versus the S&P 500's gain of 7.3%. What's Next for Apple? While Apple has outperformed the market so far this year, the question that comes to investors' minds is: what's next for the stock? There are no easy answers to this key question, but one reliable measure that can help investors address this is the company's earnings outlook. Not only does this include current consensus earnings expectations for the coming quarter(s), but also how these expectations have changed lately. Empirical research shows a strong correlation between near-term stock movements and trends in earnings estimate revisions. Investors can track such revisions by themselves or rely on a tried-and-tested rating tool like the Zacks Rank, which has an impressive track record of harnessing the power of earnings estimate revisions. Ahead of this earnings release, the estimate revisions trend for Apple: mixed. While the magnitude and direction of estimate revisions could change following the company's just-released earnings report, the current status translates into a Zacks Rank #3 (Hold) for the stock. So, the shares are expected to perform in line with the market in the near future. You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. It will be interesting to see how estimates for the coming quarters and current fiscal year change in the days ahead. The current consensus EPS estimate is $1.50 on $98 billion in revenues for the coming quarter and $6.15 on $402.73 billion in revenues for the current fiscal year. Investors should be mindful of the fact that the outlook for the industry can have a material impact on the performance of the stock as well. In terms of the Zacks Industry Rank, Computer - Mini computers is currently i\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0223 (i.e., a 2.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0223 = 4.4861, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022291, "expected_loss": 0.022291, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241206_0499", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-06", "context_summary": "SPY: 60-day history, VaR(99%)=-0.0157, max drawdown threshold=10%.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0015, std=0.0065, worst_day=-0.0198\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SPY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0157 (i.e., a 1.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0157 = 6.3601, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015723, "expected_loss": 0.015723, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20230629_0502", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-06-29", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0130, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0001, std=0.0058, worst_day=-0.0153\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-28] [\"ANALYSIS-India's aerospace suppliers see upside in parts-making from record jet orders By Allison Lampert and Aditi Shah PARIS/DELHI, June 28 (Reuters) - Indian aerospace suppliers see record jet orders by the country's top two carriers boosting domestic parts manufacturing and aircraft repairs, but argue the government must do more to support production. Rising traffic, a search for alternative sourcing to China and orders this month from Air India and IndiGo for nearly 1,000 jets combined have made India a key market for aerospace. Now, small and medium suppliers want to capitalize on that to drive more sales of locally sourced parts, they told Reuters on the sidelines of the Paris Airshow last week. \\\"Today we are going to be the largest purchaser of planes in the world,\\\" said Shekhar Sardessai, managing director at Kineco Group, a supplier in the western state of Goa, referring to India. \\\"We deserve a piece of that pie,\\\" added Sardessai, whose company makes engine and plane interior parts. While French engine maker Safran SAF.PA has plans for an engine repair and overhaul facility in India, about 90% of the country's aircraft maintenance and repair activity occurs outside its borders, according to consultancy Deloitte. The Indian repair and overhaul industry is expected to grow to $4 billion by 2031, up from $1.7 billion in 2021, Deloitte said. India's civil aviation ministry expects the orders to boost aerospace manufacturing in the country, but it cannot mandate local production since the orders do not have requirements for local production like defense deals, a senior government official told Reuters. Deloitte India partner Alaric Diniz expects parts of the commercial aviation supply chain to move to India as plane and engine makers look to avoid disruptions seen in recent years. While he could not estimate how much small suppliers will benefit, any subsidy or incentive could be helpful. AEROSPACE INCENTIVES Some suppliers like Sardessai and Aravind Melligeri, CEO of aerospace-parts producer Aequs, said India should create a production-linked incentive scheme for aerospace as it has done with other sectors. In 2020, Indian Prime Minister Narendra Modi's government launched a program to encourage companies in 14 sectors including autos to manufacture locally by earmarking 1.97 trillion rupees ($24 billion) in incentives. It has drawn investment from the likes of Foxconn 2317.TW, which supplies to iPhone maker Apple AAPL.O, and automakers including Japan's Suzuki Motor 7269.T and South Korea's Hyundai Motor 005380.KS have committed to put in money. Even without incentives, India's growing fleet of aircraft will require more maintenance services. \\\"If you will have that many planes in India who repairs them?\\\" said Sachin Agarwal, chairman of PTC Industries PCIN.NS, based in the state of Uttar Pradesh. \\\"Every supplier wants to be closer to the customer.\\\" PTC is already taking advantage of global supply-chain demand for alternate source\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0130 (i.e., a 1.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0130 = 7.6651, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013046, "expected_loss": 0.013046, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240919_0505", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-09-19", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0619, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0004, std=0.0375, worst_day=-0.0648\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0619 (i.e., a 6.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0619 = 1.6159, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.061885, "expected_loss": 0.061885, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240715_0508", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-07-15", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0568, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0301, worst_day=-0.0724\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0568 (i.e., a 5.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0568 = 1.7613, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056777, "expected_loss": 0.056777, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240514_0511", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-05-14", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0066, std=0.0408, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230217_0514", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-02-17", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0429, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0265, worst_day=-0.0463\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-16] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0429 (i.e., a 4.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0429 = 2.3294, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042929, "expected_loss": 0.042929, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230510_0517", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-05-10", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0173, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0005, std=0.0088, worst_day=-0.0205\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-09] [\"Finding the Next Double (5 Factors to Consider) Every investor who tries their hand at Wall Street is looking for the next stock that will double. However, so few investors are successful in finding a winning stock, let alone holding one. Though legendary investors such as Jesse Livermore, Paul Tudor Jones, and Warren Buffett have differing strategies, they share a common thought process about how to make big money in the stock market. Jesse Livermore once said, \\u201cThose who can both be right and sit tight are uncommon.\\u201d In an interview with Tony Robbins, Paul Tudor Jones said he shoots for a risk-to-reward ratio of 5:1. \\u201cFive to one means I\\u2019m risking one dollar to make 5.\\u201d Buffett proclaimed that \\u201cThe stock market is a device to transfer money from the impatient to the patient.\\u201d Though the advice of running winners may sound evident on the surface, in practice, it is a different story for most investors. How can investors find the next big winner, and more importantly, how can they fight the human emotions of hope, fear, and greed and ride these winners? Identify a stock in an uptrend: All else equal, it is easier to latch onto an already strong stock than it is to catch a bottom in a weak stock. Stocks like Apple (AAPL), Amazon (AMZN), or Monster (MNST) that doubled years ago went onto double several more times. In other words, strength begets strength. Image Source: Zacks Investment Research Pictured: MNST is up nearly 140,000% since inception! Use moving averages: Moving averages can help you in various ways. For example, a bullish \\u201cgolden cross\\u201d occurs when the \\u201cfaster\\u201d 50-day moving average crosses above the \\u201cslower\\u201d 200-day moving average from below \\u2013 signaling a bullish trend change. Nvidia (NVDA), the current market leader, triggered this signal earlier this year. Image Source: Zacks Investment Research Beyond getting you into the stock, the 50-day moving average can help you to stay in the stock for the bulk of a move. The 50-day moving average is an area where institutional investors like to \\u201creload on stock\\u201d. Thus, the strongest trends are contained within the 50-day moving average. If you can buy a stock above the 50-day moving average and hold until your average cost is below the moving average, you put yourself in a position for success. A good recent example is Elf Beauty (ELF). Image Source: Zacks Investment Research Pictured: ELF has hugged the 50-day moving average for months. Look for stocks with Zacks Rankings of 3 or better: The Zacks Rank grades stocks based on earnings estimates. Year-over-year, the stocks with rising earnings estimates have significantly outperformed the S&P 500 Index. By combining technicals and fundamentals, you begin to stack the odds in your favor. Hone your entry points: It is much easier to hang onto a stock if you purchased it correctly. When entering a stock, there is no need to complicate the process. Find an up-trend\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0173 (i.e., a 1.73% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0173 = 5.7818, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017296, "expected_loss": 0.017296, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241119_0520", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-11-19", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0674, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0067, std=0.0445, worst_day=-0.0695\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0674 (i.e., a 6.74% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0674 = 1.4842, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.067378, "expected_loss": 0.067378, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230926_0523", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2023-09-26", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0271, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0013, std=0.0090, worst_day=-0.0353\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-25] [\"OpenAI's ChatGPT will 'see, hear and speak' in major update Sept 25 (Reuters) - OpenAI's ChatGPT is getting a major update that will enable the viral chatbot to have voice conversations with users and interact using images, moving it closer to popular artificial intelligence (AI) assistants like Apple's AAPL.O Siri. The voice feature \\\"opens doors to many creative and accessibility-focused applications\\\", OpenAI said in a blog post on Monday. Similar AI services like Siri, Google GOOGL.O voice assistant and Amazon.com's AMZN.O Alexa are integrated with the devices they run on and are often used to set alarms and reminders, and deliver information off the internet. Since its debut last year, ChatGPT has been adopted by companies for a wide range of tasks from summarizing documents to writing computer code, setting off a race amongst Big Tech companies to launch their own offerings based on generative AI. ChatGPT's new voice feature can also narrate bedtime stories, settle debates at the dinner table, and speak out loud text input from users. The technology behind it is being used by Spotify SPOT.N for the platform's podcasters to translate their content in different languages, OpenAI said. With images support, users can take pictures of things around them and ask the chatbot to \\\"troubleshoot why your grill won't start, explore the contents of your fridge to plan a meal, or analyze a complex graph for work-related data\\\". Alphabet's Google Lens is currently the popular choice to gain information on images. The new ChatGPT features will be released for subscribers of its Plus and Enterprise plans over the next two weeks. (Reporting by Zaheer Kachwala and Yuvraj Malik in Bengaluru; Editing by Devika Syamnath) ((yuvraj.malik@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Netflix (NFLX) Expands Portfolio With New Italian Content Netflix NFLX is having a steady run in 2023, with shares rising 28.8% year to date compared with the Zacks Consumer Discretionary sector\\u2019s increase of 4.6%. The upside can be attributed to an expanding subscriber base and robust content offerings. Netflix continues to bolster its international content portfolio. Italy plays a prominent role in this endeavour through an extensive lineup that includes a wide range of series, films, docuseries and unscripted shows spanning diverse genres, formats and languages. Netflix recently announced four captivating new projects, including Il treno dei bambini, an in-depth exploration of postwar Italy and Fabbricante di lacrime, based on a popular book. Additionally, two fresh series, Storia della mia famiglia and Adorazione, provide deep explorations of intricate family dynamics and young adult experiences. Expanding Portfolio Aids Growth Netflix is anticipated to gain from its diversified content portfolio, driven by substantial investments in producing and distributing lo\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLRE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0271 (i.e., a 2.71% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0271 = 3.6954, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027061, "expected_loss": 0.027061, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230208_0525", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-02-08", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0204, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0003, std=0.0085, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-07] [\"Looking for Turnaround Plays? 5 EPS Reports to Watch this Week Though last week showcased earnings from mega tech giants such as Apple AAPL, Meta Platforms META, and Alphabet GOOGL, Wall Street is still in the heart of earnings season. Below we will discuss 5 key earnings reports to monitor this week: Tuesday, February 7th After the Market Close: Enphase Energy (ENPH) is a global solar technology company that delivers energy management technology to the solar industry. Over the past two quarters, Enphase has delivered robust triple-digit EPS growth of 108% and 102% on revenue growth of 81% and 68%. Despite the impressive fundamental backdrop, shares of ENPH have underperformed its solar peers such as First Solar FSLR. Image Source: Zacks Investment Research One potential reason that ENPH\\u2019s consensus analyst estimates for 2023 have dropped in recent weeks. Image Source: Zacks Investment Research The stock has also gone from having a best possible Zacks ranking of 1 to having a mediocre ranking of 3. ENPH also has a negative Expected Surprise Prediction (ESP) number suggesting that shares are likely to underperform on earnings. Investors should watch to see if the company can defy analyst expectations and continue to deliver strong results. Chipotle Mexican Grill CMG is an early entrant and leader in the \\u201cfast-casual\\u201d food space due to its popular Mexican food chain and burritos. The company gained popularity due to its low-cost yet healthy food offering. Chipotle only uses hormone-free pork and natural chicken ingredients, which are cooked through traditional methods. Though the stock has had a difficult couple of years, elevated inflation may be working in the company\\u2019s favor. While most prominent tech companies are laying off thousands of employees, CMG is bucking that trend. Recently, the burrito giant announced that it is looking to hire 15,000 new employees. Wednesday, February 8th Before the Market Open: Uber Technologies UBER is the largest ride-sharing company in the world. Despite its massive market cap and name recognition, Uber has yet to turn an annual profit as a public company. Uber and its most significant competitor Lyft LYFT have underperformed the S&P 500 since debuting but have tried to turn the corner in recent weeks. Each is up six straight weeks into their earnings reports this week (LYFT is expected to report Thursday after the close) Image Source: Zacks Investment Research Lyft is likely to move in sympathy with Uber\\u2019s Wednesday report. However, presently Lyft is a more robust stock from a fundamental lens. Lyft has a strong Zacks rank of 2, and a positive Earnings Expected Price Surprise (ESP). Image Source: Zacks Investment Research Wednesday, February 8th After the Market Close: Robinhood Markets HOOD is a registered broker-dealer and one of the most popular online brokers for online traders. Robinhood shares quickly doubled after debuting in September 202. However, they have careened lower sin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0204 (i.e., a 2.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0204 = 4.9096, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020368, "expected_loss": 0.020368, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240731_0528", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-07-31", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0149, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0006, std=0.0080, worst_day=-0.0155\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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FORM 10-K SUMMARY None. 110   SIGNAT URES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned; thereunto duly authorized, in the City of Redmond, State of Washington, on July 30, 2024.   M ICROSOFT  C ORPORATION   /s/ A LICE  L. J OLLA Alice L. Jolla Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer)   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of Registrant and in the capacities indicated on July 30, 2024.   Signature Title   /s/ S ATYA  N ADELLA Chairman and Chief Executive Officer (Principal Executive Officer) Satya Nadella     /s/ R EID  H OFFMAN   Director Reid Hoffman     /s/ H UGH  F. J OHNSTON Director Hugh F. Johnston     /s/ T ERI L. L IST Director Teri L. List     /s/ C ATHERINE  M AC G REGOR   Director Catherine MacGregor         /s/ M ARK  A. L. M ASON   Director Mark A. L. Mason         /s/ S ANDRA  E. P ETERSON Lead Independent Director Sandra E. Peterson       /s/ P ENNY S. P RITZKER   Director Penny S. Pritzker       /s/ C ARLOS A. R ODRIGUEZ   Director Carlos A. Rodriguez       /s/ C HARLES  W. S CHARF Director Charles W. Scharf     /s/ J OHN  W. S TANTON Director John W. Stanton       /s/ E MMA  N. W ALMSLEY   Director Emma N. Walmsley     /s/ A MY  E. H OOD Executive Vice President and Chief Financial Officer (Principal Financial Officer) Amy E. Hood     /s/ A LICE  L. J OLLA Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer) Alice L. Jolla     111\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0149 (i.e., a 1.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0149 = 6.7332, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014852, "expected_loss": 0.014852, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240612_0530", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-06-12", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0150, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0000, std=0.0076, worst_day=-0.0160\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0150 (i.e., a 1.50% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0150 = 6.6799, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01497, "expected_loss": 0.01497, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230710_0532", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-07-10", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0232, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0002, std=0.0107, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-07] [\"Here is What to Know Beyond Why Apple Inc. (AAPL) is a Trending Stock Apple (AAPL) has recently been on Zacks.com's list of the most searched stocks. Therefore, you might want to consider some of the key factors that could influence the stock's performance in the near future. Over the past month, shares of this maker of iPhones, iPads and other products have returned +6.2%, compared to the Zacks S&P 500 composite's +3.1% change. During this period, the Zacks Computer - Mini computers industry, which Apple falls in, has gained 7%. The key question now is: What could be the stock's future direction? While media releases or rumors about a substantial change in a company's business prospects usually make its stock 'trending' and lead to an immediate price change, there are always some fundamental facts that eventually dominate the buy-and-hold decision-making. Earnings Estimate Revisions Here at Zacks, we prioritize appraising the change in the projection of a company's future earnings over anything else. That's because we believe the present value of its future stream of earnings is what determines the fair value for its stock. We essentially look at how sell-side analysts covering the stock are revising their earnings estimates to reflect the impact of the latest business trends. And if earnings estimates go up for a company, the fair value for its stock goes up. A higher fair value than the current market price drives investors' interest in buying the stock, leading to its price moving higher. This is why empirical research shows a strong correlation between trends in earnings estimate revisions and near-term stock price movements. Apple is expected to post earnings of $1.20 per share for the current quarter, representing no change from the year-ago quarter. Over the last 30 days, the Zacks Consensus Estimate has changed -1.5%. The consensus earnings estimate of $6 for the current fiscal year indicates a year-over-year change of -1.8%. This estimate has changed +0.1% over the last 30 days. For the next fiscal year, the consensus earnings estimate of $6.62 indicates a change of +10.4% from what Apple is expected to report a year ago. Over the past month, the estimate has changed -0.2%. Having a strong externally audited track record, our proprietary stock rating tool, the Zacks Rank, offers a more conclusive picture of a stock's price direction in the near term, since it effectively harnesses the power of earnings estimate revisions. Due to the size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, Apple is rated Zacks Rank #3 (Hold). The chart below shows the evolution of the company's forward 12-month consensus EPS estimate: 12 Month EPS Projected Revenue Growth While earnings growth is arguably the most superior indicator of a company's financial health, nothing happens as such if a business isn't able to grow its revenues. After all, it's nearly impossible for a company to increase i\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0232 (i.e., a 2.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0232 = 4.3193, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023152, "expected_loss": 0.023152, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231204_0535", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2023-12-04", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0322, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0013, std=0.0152, worst_day=-0.0416\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-01] [\"Best Blue Chip Stocks To Invest In Right Now? 2 In Focus Blue-chip stocks are shares of well-established, financially sound companies with a history of stable earnings. These companies are often market leaders or among the top in their sectors. Characterized by their large market capitalization, blue-chip stocks are known for their reliability and strong track record. They are often included in major stock indices. Investing in blue-chip stocks offers several advantages. These stocks typically provide consistent dividends, contributing to steady income for investors. Their long-standing market presence suggests a lower risk of volatility. This makes them a popular choice for conservative investors. However, there are also disadvantages. Blue-chip stocks may have slower growth compared to emerging companies. Their size can limit their potential for rapid expansion. When considering blue-chip stocks, investors should weigh their investment goals. These stocks can be a cornerstone for a long-term, stable portfolio. Yet, their conservative nature might not suit those seeking high growth rates. As with any investment, diversification is key. Keeping this on top of mind, let\\u2019s look at two blue chip stocks to watch in the stock market today. Blue Chip Stocks To Buy [Or Avoid] Today McDonald\\u2019s Corporation (NYSE: MCD) Apple Inc. (NASDAQ: AAPL) McDonald\\u2019s Corporation (MCD Stock) Let\\u2019s start with McDonald\\u2019s Corporation (MCD). The company is a global fast-food chain, renowned for its hamburgers, fries, and quick-service meals. McDonald\\u2019s is one of the world\\u2019s largest restaurant chains, with outlets in over 100 countries. McDonald\\u2019s is known for its standardized menu items and for pioneering the franchise model in the fast-food industry. Last month, McDonald\\u2019s Corporation announced its decision to acquire Carlyle\\u2019s minority ownership stake in the strategic partnership managing McDonald\\u2019s business in mainland China, Hong Kong, and Macau. The announcement, made on November 20, 2023, detailed that while the CITIC Consortium, primarily through CITIC Capital, would maintain its controlling 52% stake, McDonald\\u2019s would increase its stake from 20% to 48%. This move marks a significant adjustment in McDonald\\u2019s involvement in its Chinese operations. In the last month of trading action, shares of MCD have advanced by 8.36%. Meanwhile, during Friday morning\\u2019s trading session, McDonald\\u2019s stock is trading slightly higher on the day so far by 0.72%, trading at $283.88 a share. [Read More] 2 Dow 30 Stocks For Your December 2023 Watchlist Apple (AAPL Stock) Next, Apple Inc. (AAPL) is a multinational technology company that specializes in consumer electronics, software, and online services. Apple\\u2019s key products include the iPhone, iPad, Mac computers, and services like the App Store, Apple Music, and iCloud. At the beginning of last month, Apple reported better-than-expected fourth-quarter 2023 f\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to FXI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0322 (i.e., a 3.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0322 = 3.1071, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032184, "expected_loss": 0.032184, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231218_0537", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2023-12-18", "context_summary": "BNO: 60-day history, VaR(99%)=-0.0480, max drawdown threshold=10%.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=-0.0028, std=0.0214, worst_day=-0.0545\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNO, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0480 (i.e., a 4.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0480 = 2.0816, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.04804, "expected_loss": 0.04804, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240404_0540", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2024-04-04", "context_summary": "VNQI: 60-day history, VaR(99%)=-0.0240, max drawdown threshold=10%.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=0.0000, std=0.0079, worst_day=-0.0251\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VNQI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0240 (i.e., a 2.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0240 = 4.1681, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023991, "expected_loss": 0.023991, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241002_0543", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-10-02", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0332, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0005, std=0.0151, worst_day=-0.0365\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QQQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0332 (i.e., a 3.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0332 = 3.0150, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033168, "expected_loss": 0.033168, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230913_0546", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-09-13", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0558, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0075, std=0.0209, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-12] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0558 (i.e., a 5.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0558 = 1.7912, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.055828, "expected_loss": 0.055828, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240801_0548", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2024-08-01", "context_summary": "PDBC: 60-day history, VaR(99%)=-0.0142, max drawdown threshold=10%.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=-0.0004, std=0.0082, worst_day=-0.0149\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PDBC, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0142 (i.e., a 1.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0142 = 7.0314, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014222, "expected_loss": 0.014222, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230630_0551", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-06-30", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0188, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0003, std=0.0103, worst_day=-0.0219\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-29] [\"Britain tightens planned tech law to stop children viewing porn LONDON, June 30 (Reuters) - Britain said on Friday it had tightened protections in its Online Safety Bill that will prevent children from viewing pornography in an update to long-delayed legislation that is being closely watched by the tech industry. Under the government's latest amendments after debates in parliament, Britain will set higher standards for age verification tools used by services that publish or allow porn on their platforms, to ensure they are effective in establishing whether a user is a child. Britain, like the European Union and other countries, has been grappling over how to protect social media users, and in particular children, from harmful content without damaging free speech. New measures will also seek to hold top executives personally responsible for keeping children safe on their platforms, the government said, after agreeing to toughen the bill in January with the prospect of jail time for tech bosses. \\\"This government will not allow the lives of our children to be put at stake whenever they go online; whether that is through facing abuse or viewing harmful content that could go on to have a devastating impact on their lives,\\\" Paul Scully, minister for tech and the digital economy, said. \\\"To prevent any further tragedy and build a better future for our children, we are acting robustly and with urgency to make the Online Safety Bill the global standard for protecting our children.\\\" Other changes to the bill will allow regulators to obtain information on a child's social media use if requested by a coroner, which will help bereaved families understand any possible influence of online activity in their death. The tech industry including firms like Apple AAPL.O have criticised sections of the Online Safety Bill, particularly provisions that could be used to make messaging services break end-to-end encryption in order scan for child abuse material. The bill, which is possibly months away from being passed, is currently at parliament's upper House of Lords where lawmakers can make amendments before deciding whether to pass or reject it. (Reporting by Sachin Ravikumar; Editing by Alison Williams;) ((saisachin.r@tr.com; Twitter: @sachinr27)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"GLOBAL MARKETS-Wall Street mixed, Treasury yields rise on solid U.S. economic data * Jobless claims unexpectedly fall, GDP revised higher * U.S. banks rise after Fed's banking stress test * Dollar strengthens, Treasury yields rise after data (Updates to U.S. markets open, changes dateline to NEW YORK from LONDON) By Stephen Culp NEW YORK, June 29 (Reuters) - U.S. stocks were mixed and benchmark Treasury yields jumped on Thursday as robust economic data helped stave off recession fears, but also raised the likelihood that the Fed will keep its restrictive policy in place for longer than\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0188 (i.e., a 1.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0188 = 5.3196, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018798, "expected_loss": 0.018798, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230731_0554", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-07-31", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0648, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0000, std=0.0277, worst_day=-0.0915\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-30] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0648 (i.e., a 6.48% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0648 = 1.5427, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064822, "expected_loss": 0.064822, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230818_0557", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-08-18", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1101, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0006, std=0.0531, worst_day=-0.1366\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-17] [\"Noteworthy ETF Inflows: IVV, AAPL, MSFT, AMZN Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel, one standout is the iShares Core S&P 500 ETF (Symbol: IVV) where we have detected an approximate $1.5 billion dollar inflow -- that's a 0.4% increase week over week in outstanding units (from 776,300,000 to 779,650,000). Among the largest underlying components of IVV, in trading today Apple Inc (Symbol: AAPL) is down about 1.1%, Microsoft Corporation (Symbol: MSFT) is off about 0.3%, and Amazon.com Inc (Symbol: AMZN) is lower by about 0.6%. For a complete list of holdings, visit the IVV Holdings page \\u00bb The chart below shows the one year price performance of IVV, versus its 200 day moving average: Looking at the chart above, IVV's low point in its 52 week range is $349.53 per share, with $461.88 as the 52 week high point \\u2014 that compares with a last trade of $442.45. Comparing the most recent share price to the 200 day moving average can also be a useful technical analysis technique -- learn more about the 200 day moving average \\u00bb. Exchange traded funds (ETFs) trade just like stocks, but instead of ''shares'' investors are actually buying and selling ''units''. These ''units'' can be traded back and forth just like stocks, but can also be created or destroyed to accommodate investor demand. Each week we monitor the week-over-week change in shares outstanding data, to keep a lookout for those ETFs experiencing notable inflows (many new units created) or outflows (many old units destroyed). Creation of new units will mean the underlying holdings of the ETF need to be purchased, while destruction of units involves selling underlying holdings, so large flows can also impact the individual components held within ETFs. Click here to find out which 9 other ETFs had notable inflows \\u00bb Also see: \\u0095 YY Videos \\u0095 Top Ten Hedge Funds Holding CSP \\u0095 ARRS market cap history The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The 3 Most Undervalued Small-Cap Stocks to Buy Now: August 2023 InvestorPlace - Stock Market News, Stock Advice & Trading Tips At the core of the discussion, investors seeking undervalued small-cap stocks do so for one main reason: to maximize their return potential. Of course, such a directive inherently carries risks. Basically, less-proven enterprises often run on little else than a compelling narrative feature with very low predictability. But in exchange for this dubious profile, moonshots may be on the horizon. Fundamentally, another reason to consider small-cap stocks centers on the targeting of hidden gems. For example, you can buy a sector leader like Apple (NASDAQ:AAPL) right now. However, if you had a time machine, you\\u2019d rather acquire AAPL when it was trading for pennies in the 1980s. Back then, few could have imagined the success the consumer technology g\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9084", "answer_numeric": 0.9084, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1101 (i.e., a 11.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1101 = 0.9084, capped at 1.0.\nMaximum position size = 0.9084 (90.8% of portfolio).", "metadata": {"var_99": -0.11008, "expected_loss": 0.11008, "max_drawdown_threshold": 0.1, "position_size": 0.9084, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240925_0560", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-09-25", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1678, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0007, std=0.0943, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.5960", "answer_numeric": 0.596, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1678 (i.e., a 16.78% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1678 = 0.5960, capped at 1.0.\nMaximum position size = 0.5960 (59.6% of portfolio).", "metadata": {"var_99": -0.167778, "expected_loss": 0.167778, "max_drawdown_threshold": 0.1, "position_size": 0.596, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241016_0563", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2024-10-16", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0141, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0010, std=0.0062, worst_day=-0.0199\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-08-30] wmt-20240731 0000104169 1/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:order wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-07-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-07-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-07-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-07-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-07-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-07-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-07-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-07-31 0000104169 2024-08-28 0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2024-02-23 2024-02-23 0000104169 2024-02-23 0000104169 srt:MinimumMember 2024-07-31 0000104169 srt:MaximumMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0141 (i.e., a 1.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0141 = 7.1031, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014078, "expected_loss": 0.014078, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240229_0566", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-02-29", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0311, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0021, std=0.0144, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2022-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnt [...TRUNCATED...] d long-term debt can be found in Note 8 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” Long-term debt obligations of the parent company do not include other financing obligations at subsidiaries which totaled $ 1.1 billion and $ 0.9 billion at December 31, 2023 and 2022. Maturities of short-term borrowings and long-term debt for the years ending December 31 are as follows: (in millions) 2024 $ 4,088   2025 3,050   2026 2,500   2027 2,925   2028 3,000   Thereafter 47,002   UnitedHealth Group’s parent company had notes payable to subsidiaries of $ 9.9 billion and $ 8.7 billion as of December 31, 2023 and 2022, respectively, which included on-demand features. 4. Commitments and Contingencies Certain regulated subsidiaries are guaranteed by UnitedHealth Group’s parent company in the event of insolvency. UnitedHealth Group’s parent company also provides guarantees related to its service level under certain contracts. None of the amounts accrued, paid or charged to income for service level guarantees were material as of December 31, 2023, 2022 or 2021. For a summary of commitments and contingencies, see Note 12 of the Notes to the Consolidated Financial Statements included in Part II, Item 8, “Financial Statements and Supplementary Data.” ITEM  16.    FORM 10-K SUMMARY None. 79 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Dated: February 28, 2024   UNITEDHEALTH GROUP INCORPORATED By /s/    A NDREW W ITTY   Andrew Witty Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated.   Signature Title Date /s/ A NDREW W ITTY Director and Chief Executive Officer (principal executive officer) February 28, 2024 Andrew Witty /s/ J OHN R EX Executive Vice President and Chief Financial Officer (principal financial officer) February 28, 2024 John Rex /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) February 28, 2024 Thomas Roos * Director February 28, 2024 Charles Baker * Director February 28, 2024 Timothy Flynn * Director February 28, 2024 Paul Garcia * Director February 28, 2024 Kristen Gil * Director February 28, 2024 Stephen Hemsley * Director February 28, 2024 Michele Hooper * Director February 28, 2024 F. William McNabb III * Director February 28, 2024 Valerie Montgomery Rice, M.D. * Director February 28, 2024 John Noseworthy, M.D.   *By /s/ R UPERT B ONDY   Rupert Bondy As Attorney-in-Fact 80\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0311 (i.e., a 3.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0311 = 3.2110, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031143, "expected_loss": 0.031143, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240417_0568", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-04-17", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0310, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0004, std=0.0131, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0310 (i.e., a 3.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0310 = 3.2271, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030987, "expected_loss": 0.030987, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241017_0571", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-10-17", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0580, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0012, std=0.0293, worst_day=-0.0613\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0580 (i.e., a 5.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0580 = 1.7246, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.057983, "expected_loss": 0.057983, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241204_0574", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-12-04", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0430, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0051, std=0.0277, worst_day=-0.0527\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0430 (i.e., a 4.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0430 = 2.3271, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042972, "expected_loss": 0.042972, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230216_0577", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-02-16", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0542, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0061, std=0.0263, worst_day=-0.0632\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-15] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0542 (i.e., a 5.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0542 = 1.8466, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.054154, "expected_loss": 0.054154, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240125_0580", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2024-01-25", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0242, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0008, std=0.0120, worst_day=-0.0243\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0242 (i.e., a 2.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0242 = 4.1351, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024183, "expected_loss": 0.024183, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240403_0583", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-04-03", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0968, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0030, std=0.0447, worst_day=-0.0987\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0968 (i.e., a 9.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0968 = 1.0333, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.096781, "expected_loss": 0.096781, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240112_0586", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-01-12", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0573, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0296, worst_day=-0.0616\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0573 (i.e., a 5.73% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0573 = 1.7445, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.057322, "expected_loss": 0.057322, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240208_0589", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2024-02-08", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0368, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0019, std=0.0193, worst_day=-0.0416\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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amzn:VendorAccountsReceivableMember 2023-12-31 0001018724 us-gaap:LoansReceivableMember 2022-12-31 0001018724 us-gaap:LoansReceivableMember 2023-12-31 00 [...TRUNCATED...] tents 32.2 Certification of Brian T. Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to FXI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0368 (i.e., a 3.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0368 = 2.7175, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.036799, "expected_loss": 0.036799, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240730_0592", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-07-30", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0156, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0006, std=0.0081, worst_day=-0.0164\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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ko:ConcentrateOperationsMember 2024-03-30 2024-06-28 0000021344 ko:FinishedProductOperationsMember country:US 2024-03-30 2024-06-28 0000021344 ko:FinishedProductOperationsMember ko:InternationalMember 2024-03-30 2024-06-28 0000021344 ko:FinishedProductOperationsMember 2024-03-30 2024-06-28 0000021344 country:US 2024-03-30 2024-06-28 0000021344 ko:InternationalMember 2024-03-30 2024-06-28 0000021344 ko:ConcentrateOperationsMember country:US 2023-04-01 2023-06-30 0000021344 ko:ConcentrateOperationsMember ko:InternationalMember 2023-04-01 2023-06-30 0000021344 ko:ConcentrateOperationsMember 2023-04-01 2023-06-30 0000021344 ko:FinishedProductOperationsMember country:US 2023-04-01 2023-06-30 0000021344 ko:FinishedProductOperationsMember ko:InternationalMember 2023-04-01 2023-06-30 0000021344 ko:FinishedProductOperationsMember 2023-04-01 2023-06-30 0000021344 country:US 2023-04-01 2023-06-30 0000021344 ko:InternationalMember 2023-04-01 2023-06-30 0000021344 ko:ConcentrateOperationsMember country:US 2024-01-01 2024-06-28 0000021344 ko:ConcentrateOperationsMember ko:InternationalMember 2024-01-01 2024-06-28 0000021344 ko:ConcentrateOperationsMember 2024-01-01 2024-06-28 0000021344 ko [...TRUNCATED...] rence to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on June 3, 2017. 4.47 Third Supplemental Indenture, dated as of July 5, 2017, to the Indenture, dated as of July 30, 1991, as amended, among Coca-Cola Refreshments USA, Inc., the Company and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on July 6, 2017. 10.1 Letter, dated May 1, 2024, from the Company to Erin “Ellie” May — incorporated herein by reference to Exhibit 10.1 to the Company’s Form 8-K filed on May 2, 2024. 10.2 The Coca-Cola Company 2024 Equity Plan — incorporated herein by reference to Exhibit 10.2 to the Company’s Form 8-K filed on May 2, 2024. 10.3 Form of Performance Share Agreement for grants under the 2024 Equity Plan, as adopted May 1, 2024. 10.4 Form of Restricted Stock Unit Agreement for grants under the 2024 Equity Plan, as adopted May 1 , 2024. 10.5 Form of Stock Option Agreement for grants under the 2024 Equity Plan, as adopted May 1, 2024. 31.1 Rule 13a-14(a)/15d-14(a) Certification, executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company. 31.2 Rule 13a-14(a)/15d-14(a) Certification, executed by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 32.1 Certifications required by Rule 13a-14(b) or Rule 15d-14(b) and Section 1350 of Chapter 63 of Title 18 of the United States Code (18 U.S.C. Section 1350), executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company, and by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 101 The following financial information from The Coca-Cola Company’s Quarterly Report on Form 10-Q for the quarter ended June 28, 2024, formatted in iXBRL (Inline Extensible Business Reporting Language): (i) Consolidated Statements of Income for the three and six months ended June 28, 2024 and June 30, 2023; (ii) Consolidated Statements of Comprehensive Income for the three and six months ended June 28, 2024 and June 30, 2023; (iii) Consolidated Balance Sheets as of June 28, 2024 and December 31, 2023; (iv) Consolidated Statements of Cash Flows for the six months ended June 28, 2024 and June 30, 2023; and (v) Notes to Consolidated Financial Statements. 104 Cover Page Interactive Data File (the cover page XBRL tags are embedded within the iXBRL document and included in Exhibit 101). 55 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     THE COCA-COLA COMPANY (Registrant) /s/ ERIN MAY Date: July 29, 2024 Erin May Senior Vice President, Controller and Chief Accounting Officer (On behalf of the Registrant) 56\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0311 (i.e., a 3.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0311 = 3.2110, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031143, "expected_loss": 0.031143, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230328_0603", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-03-28", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0649, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0000, std=0.0378, worst_day=-0.0652\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-27] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0649 (i.e., a 6.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0649 = 1.5417, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064865, "expected_loss": 0.064865, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230606_0606", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-06-06", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0742, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0025, std=0.0267, worst_day=-0.0940\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-05] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0742 (i.e., a 7.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0742 = 1.3481, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.074181, "expected_loss": 0.074181, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240227_0609", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2024-02-27", "context_summary": "DBC: 60-day history, VaR(99%)=-0.0190, max drawdown threshold=10%.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=-0.0005, std=0.0082, worst_day=-0.0243\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DBC, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0190 (i.e., a 1.90% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0190 = 5.2676, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018984, "expected_loss": 0.018984, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240312_0612", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-03-12", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0838, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0056, std=0.0379, worst_day=-0.0987\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0838 (i.e., a 8.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0838 = 1.1940, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.083755, "expected_loss": 0.083755, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241007_0614", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2024-10-07", "context_summary": "HAUZ: 60-day history, VaR(99%)=-0.0202, max drawdown threshold=10%.", "question": "Asset: HAUZ\nDaily returns (past 60 days): mean=0.0016, std=0.0093, worst_day=-0.0234\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to HAUZ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0202 (i.e., a 2.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0202 = 4.9615, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020155, "expected_loss": 0.020155, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240109_0617", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-01-09", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0886, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0077, std=0.0509, worst_day=-0.0916\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0886 (i.e., a 8.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0886 = 1.1288, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.088591, "expected_loss": 0.088591, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240628_0622", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-06-28", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0477, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0244, worst_day=-0.0502\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0477 (i.e., a 4.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0477 = 2.0968, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.047691, "expected_loss": 0.047691, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230316_0625", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2023-03-16", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0229, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0010, std=0.0114, worst_day=-0.0243\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-15] [\"A Bull Market Is Coming: 3 Big Reasons to Buy Apple Stock Right Now Every bear market in history has given way to a new bull market. This time should be no different. Inflation, recession fears, and now bank failures -- there's certainly no shortage of calamities currently weighing on the stock market. But inflation will eventually be tamed, the economy will recover, and the financial industry will stabilize. Strong businesses should help to lead the market higher. And the investors who buy their shares at today's discounted prices stand to profit handsomely. Apple (NASDAQ: AAPL) is one such company. Here are three reasons the tech titan is a particularly attractive buy today. 1. Apple's services are probably worth more than you think Investors love businesses with dependable, recurring revenue. Apple's services business might just be the best of the bunch. Apple earned a whopping $20.8 billion in services revenue in its fiscal 2023 first quarter ended Dec. 31. Services accounted for roughly 18% of the tech giant's total sales. But with the segment's sky-high gross margin of 70.8%, compared with 37% for Apple's products, services account for a far larger percentage of the company's profits. Apple's massive installed base of more than 2 billion active devices gives it an incredible opportunity to deepen its relationship with its customers -- and sell even more services. The company already has more than 935 million paid subscriptions. The continued growth of app purchases, cloud storage, digital payments, streaming TV, and advertising solutions should all help to fuel further increases in Apple's services revenue and profits. For his part, Goldman Sachs analyst Michael Ng expects Apple to generate 40% of its gross profit from services by 2027, up from 33% in 2022. \\\"Apple's success in premier hardware design and resulting brand loyalty has led to a growing installed base of users that provide visibility into revenue growth by reducing customer churn, lowering customer acquisition costs for new product and services launches, and encouraging repeat purchases,\\\" Ng said earlier this month. Wedbush analyst Dan Ives, meanwhile, sees Apple's services revenue growing at a double-digit percentage in the coming year. Ives, in turn, thinks the company's services business alone could be worth a staggering $1.3 trillion. 2. China is rebounding The Chinese government's strict COVID-related restrictions weighed heavily on Apple's results last year. Manufacturing facilities were forced to close, snarling Apple's otherwise highly efficient supply chain network. That dented the company's sales and drove up its costs. China recently lifted many of its health restrictions and reopened its economy, and that should allow Apple to work through its supply chain bottlenecks and increase production of its popular iPhones and other devices. Better still, China's economic recovery should also create higher demand for Apple's products in the populous country. The greater C\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLU, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0229 (i.e., a 2.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0229 = 4.3716, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022875, "expected_loss": 0.022875, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240523_0628", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SHV"], "decision_date": "2024-05-23", "context_summary": "SHV: 60-day history, VaR(99%)=-0.0000, max drawdown threshold=10%.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SHV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0000 (i.e., a 0.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0000 = 2686.2104, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -3.7e-05, "expected_loss": 3.7e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241008_0630", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2024-10-08", "context_summary": "EMB: 60-day history, VaR(99%)=-0.0091, max drawdown threshold=10%.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0006, std=0.0039, worst_day=-0.0102\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EMB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0091 (i.e., a 0.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0091 = 11.0071, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.009085, "expected_loss": 0.009085, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240401_0633", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-04-01", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0784, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0044, std=0.0393, worst_day=-0.0827\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0784 (i.e., a 7.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0784 = 1.2753, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.07841, "expected_loss": 0.07841, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230427_0636", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-04-27", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0156, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0001, std=0.0085, worst_day=-0.0162\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-26] [\"Unusual Call Option Trade in Apple (AAPL) Worth $3,040.50K On April 26, 2023 at 15:31:16 ET an unusually large $3,040.50K block of Call contracts in Apple (AAPL) was sold, with a strike price of $167.50 / share, expiring in 23 day(s) (on May 19, 2023). Fintel tracks all large options trades, and the premium spent on this trade was 3.98 sigmas above the mean, placing it in the 100.00th percentile of all recent large trades made in AAPL options. This trade was first picked up on Fintel's real time Options Flow tool, where unusual option trades are highlighted. What is the Fund Sentiment? There are 6408 funds or institutions reporting positions in Apple. This is an increase of 189 owner(s) or 3.04% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 2.79%, a decrease of 26.22%. Total shares owned by institutions increased in the last three months by 0.12% to 10,139,399K shares. The put/call ratio of AAPL is 1.00, indicating a bullish outlook. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. Analyst Price Forecast Suggests 6.19% Upside As of April 24, 2023, the average one-year price target for Apple is $173.91. The forecasts range from a low of $117.16 to a high of $215.25. The average price target represents an increase of 6.19% from its latest reported closing price of $163.77. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is $413,641MM, an increase of 6.74%. The projected annual non-GAAP EPS is $6.36. What are Other Shareholders Doing? MAINSTAY VP FUNDS TRUST - MainStay VP T. Rowe Price Equity Income Portfolio Initial Class holds 144K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 150K shares, representing a decrease of 4.30%. The firm decreased its portfolio allocation in AAPL by 14.11% over the last quarter. Benchmark Investment Advisors holds 51K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 52K shares, representing a decrease of 1.70%. The firm decreased its portfolio allocation in AAPL by 9.34% over the last quarter. Lowery Thomas holds 2K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 3K shares, representing a decrease of 17.45%. The firm decreased its portfolio allocation in AAPL by 17.98% over the last quarter. Rbo & Co holds 105K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 104K shares, representing an increase of 0.40%. The firm decreased its portfolio allocation in AAPL by 99.92% over the last quarter. Invst holds 58K shares representing 0.00% ownership of the company. In it's prior filing, the firm reported owning 60K shares, representing a decrease of 2.99%. The firm decreased its portfolio allocation in AAPL by 99.91% over the last quarter. Apple Background Information (This descr\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0156 (i.e., a 1.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0156 = 6.3931, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015642, "expected_loss": 0.015642, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240207_0639", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-02-07", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0138, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0021, std=0.0066, worst_day=-0.0147\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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amzn:VendorAccountsReceivableMember 2023-12-31 0001018724 us-gaap:LoansReceivableMember 2022-12-31 0001018724 us-gaap:LoansReceivableMember 2023-12-31 00 [...TRUNCATED...] tents 32.2 Certification of Brian T. Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QUAL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0138 (i.e., a 1.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0138 = 7.2658, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013763, "expected_loss": 0.013763, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20230907_0642", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-09-07", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0629, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0007, std=0.0402, worst_day=-0.0806\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-06] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0629 (i.e., a 6.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0629 = 1.5892, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.062923, "expected_loss": 0.062923, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241218_0645", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SLV"], "decision_date": "2024-12-18", "context_summary": "SLV: 60-day history, VaR(99%)=-0.0373, max drawdown threshold=10%.", "question": "Asset: SLV\nDaily returns (past 60 days): mean=-0.0007, std=0.0176, worst_day=-0.0444\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0373 (i.e., a 3.73% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0373 = 2.6780, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037341, "expected_loss": 0.037341, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240402_0648", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2024-04-02", "context_summary": "VCIT: 60-day history, VaR(99%)=-0.0081, max drawdown threshold=10%.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=-0.0000, std=0.0035, worst_day=-0.0089\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VCIT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0081 (i.e., a 0.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0081 = 12.3954, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008067, "expected_loss": 0.008067, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241223_0651", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2024-12-23", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0170, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0017, std=0.0074, worst_day=-0.0187\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0170 (i.e., a 1.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0170 = 5.8718, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01703, "expected_loss": 0.01703, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241105_0654", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2024-11-05", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0287, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0013, std=0.0114, worst_day=-0.0308\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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pfe:DevelopedTechnologyRightsAndOtherIntangibleAssetsMember 2024-01-01 2024-09-29 0000078003 pfe:SeagenMe [...TRUNCATED...] 2024 14,581  $ 27.73  —  $ 3,292,882,444  July 29 through August 25, 2024 22,257  $ 30.44  —  $ 3,292,882,444  August 26 through September 29, 2024 57,730  $ 29.02  —  $ 3,292,882,444  Total 94,568  $ 29.16  —  (a) Represents (i) 91,700 shares of common stock surrendered to the Company to satisfy tax withholding obligations in connection with the vesting of awards under our long-term incentive programs and (ii) the open market purchase by the trustee of 2,868 shares of common stock in connection with the reinvestment of dividends paid on common stock held in trust for employees who deferred receipt of performance share awards. (b) See the Analysis of Financial Condition, Liquidity, Capital Resources and Market Risk—Capital Allocation Framework section within MD&A of this Form 10-Q and Note 12 in our 2023 Form 10-K. ITEM 5. OTHER INFORMATION During the three months ended September 29, 2024, none of our directors or officers adopted or terminated a “Rule 10b5-1 trading arrangement” or “non-Rule 10b5-1 trading arrangement,” as each term is defined in Item 408 of Regulation S-K. 60 ITEM 6. EXHIBITS   Exhibit 31.1 Certification by the Chief Executive Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 31.2 Certification by the Chief Financial Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.1 Certification by the Chief Executive Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.2 Certification by the Chief Financial Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 101:     EX-101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document.   EX-101.SCH EX-101.CAL EX-101.LAB EX-101.PRE EX-101.DEF   Inline XBRL Taxonomy Extension Schema Inline XBRL Taxonomy Extension Calculation Linkbase Inline XBRL Taxonomy Extension Label Linkbase Inline XBRL Taxonomy Extension Presentation Linkbase Inline XBRL Taxonomy Extension Definition Document Exhibit 104 Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   Pfizer Inc.   (Registrant)         Dated: November 4, 2024 /s/ Jennifer B. Damico   Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) 61\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QQQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0287 (i.e., a 2.87% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0287 = 3.4891, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028661, "expected_loss": 0.028661, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240913_0657", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2024-09-13", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0002, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0003, std=0.0003, worst_day=-0.0002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ICSH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0002 (i.e., a 0.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0002 = 505.4744, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000198, "expected_loss": 0.000198, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240917_0659", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-09-17", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0801, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0036, std=0.0345, worst_day=-0.0895\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0801 (i.e., a 8.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0801 = 1.2486, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080091, "expected_loss": 0.080091, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241120_0662", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2024-11-20", "context_summary": "TIP: 60-day history, VaR(99%)=-0.0027, max drawdown threshold=10%.", "question": "Asset: TIP\nDaily returns (past 60 days): mean=0.0001, std=0.0011, worst_day=-0.0036\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to TIP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0027 (i.e., a 0.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0027 = 37.2560, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.002684, "expected_loss": 0.002684, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231016_0665", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-10-16", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0426, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0016, std=0.0149, worst_day=-0.0575\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-15] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0426 (i.e., a 4.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0426 = 2.3495, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042561, "expected_loss": 0.042561, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241202_0666", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-12-02", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0651, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0153, std=0.0577, worst_day=-0.0659\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0651 (i.e., a 6.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0651 = 1.5356, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.065122, "expected_loss": 0.065122, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230220_0669", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-02-20", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0198, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0015, std=0.0093, worst_day=-0.0264\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-17] [\"Zacks Value Trader Highlights: Taiwan Semiconductor, Chevron, US Bancorp, Apple and Amazon For Immediate Release Chicago, IL \\u2013 February 17, 2023 \\u2013 Zacks Value Trader is a podcast hosted weekly by Zacks Stock Strategist Tracey Ryniec. Every week, Tracey will be joined by guests to discuss the hottest investing topics in stocks, bonds and ETFs and how it impacts your life. To listen to the podcast, click here: https://www.zacks.com/stock/news/2055570/grading-berkshire-hathaways-q4-trades) Grading Berkshire Hathaway's Q4 Trades Welcome to Episode #317 of the Value Investor Podcast. (0:15) - What Can We Learn From Berkshire Hathaways 13F? (4:30) - Breaking Down Q4 Sells and Growing Positions: How Did They Perform? (15:50) - What Was Berkshire Hathaway Buying With Their Cash Reserves? (20:35) - Episode Roundup: TSM, USB, BK, BAC, CVX, AAPL, LPX, PARA Podcast@Zacks.com Every week, Tracey Ryniec, the editor of Zacks Value Investor portfolio, shares some of her top value investing tips and stock picks. The fourth quarter 2022 13-F filings are out and that means value investors get to see what stocks Warren Buffett, and Berkshire Hathaway, are buying, or selling. Many investors follow his trades to a \\\"t\\\" even going as far as replicating them. But should you? This filing had some surprising sales and few stock purchases, even though the stock market was still selling off, and many stocks were cheap on a valuation basis, and Berkshire was still sitting on a pile of cash. What is Buffett waiting for? Is his lack of purchases a sign that he thinks stocks have further to sell-off? Or did he \\\"miss\\\" the bottom again, like he did in 2020's pandemic sell-off when he also didn't jump in to buy? Let's look at 5 of the key buys and sales in Q4. Berkshire Hathaway's Big Buys, and Sales, in the Fourth Quarter of 2022 1. Taiwan Semiconductor TSM Berkshire Hathaway first bought a position in Taiwan Semiconductor in the third quarter of 2022 to much fanfare. It was a $4.2 billion position and the first semiconductor company to be in the portfolio for years. But in the fourth quarter, just a few months later, Berkshire sold 86% of its Taiwan Semiconductor shares. It went from 60 million shares to just 8.3 million. What happened to the infamous Buffett strategy of the best time to sell is never? Even worse, shares of Taiwan Semiconductor have rallied big in 2023, adding 24.5%. Does this sale of Taiwan Semiconductor make any sense? 2. Chevron CVX Berkshire Hathaway has gone all in on the energy companies over the last 2 years, buying billions of dollars of Chevron and Occidental Petroleum. But in the fourth quarter of 2022, it sold 1%, or 2.4 million shares, of its Chevron position. This was also a head scratcher to many. What's the point of selling such a small position? Is Buffett still a big believer in Chevron? 3. US Bancorp USB Berkshire continues to sell shares of its regional banks. It first bought US Bancorp in the first quarter of 2006. But in the fo\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0198 (i.e., a 1.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0198 = 5.0491, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019806, "expected_loss": 0.019806, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240329_0672", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-03-29", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0919, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0037, std=0.0400, worst_day=-0.0975\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0919 (i.e., a 9.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0919 = 1.0881, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.091905, "expected_loss": 0.091905, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240703_0675", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-07-03", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0693, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0037, std=0.0301, worst_day=-0.0806\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0693 (i.e., a 6.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0693 = 1.4431, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069295, "expected_loss": 0.069295, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240522_0676", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BNO"], "decision_date": "2024-05-22", "context_summary": "BNO: 60-day history, VaR(99%)=-0.0291, max drawdown threshold=10%.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=0.0007, std=0.0106, worst_day=-0.0297\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNO, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0291 (i.e., a 2.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0291 = 3.4350, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029112, "expected_loss": 0.029112, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240508_0679", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-05-08", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1241, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0073, std=0.0427, worst_day=-0.1409\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8057", "answer_numeric": 0.8057, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1241 (i.e., a 12.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1241 = 0.8057, capped at 1.0.\nMaximum position size = 0.8057 (80.6% of portfolio).", "metadata": {"var_99": -0.124117, "expected_loss": 0.124117, "max_drawdown_threshold": 0.1, "position_size": 0.8057, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230614_0682", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2023-06-14", "context_summary": "SGOV: 60-day history, VaR(99%)=-0.0000, max drawdown threshold=10%.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SGOV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0000 (i.e., a 0.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0000 = 2444.4292, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -4.1e-05, "expected_loss": 4.1e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230904_0685", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-09-04", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0199, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0009, std=0.0087, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-01] [\"Should You Buy the Dow Stock Outperforming Apple? When you think of top-performing Dow stocks to buy, you might automatically think of Apple (AAPL) - it's the world\\u2019s most valuable company, a favorite of legendary investor Warren Buffett, and a leader in consumer technology. But what if we told you there is another Dow Jones Industrial Average ($DOWI) component that has been crushing Apple on the charts over several time frames - and it's not even a tech stock? That stock is none other than Caterpillar (CAT), the world\\u2019s largest manufacturer of construction and mining equipment and a true old-school industrial name. And while CAT hasn't exactly collected AI stock-sized gains in 2023, it's worth taking a look at the stock's performance from a few different perspectives to get a sense of its real technical muscle. CAT's Long-Term Technical Dominance To be sure, Apple stock is outpacing comfortably CAT on a year-to-date basis - but let's not forget how much room for recovery Apple and its tech stock peers had after a brutal finish to 2022. Looking over the past 52 weeks, Caterpillar stock has gained nearly 60%, while AAPL is only 20% higher. The broader Dow, for perspective, is up about 10% in this time frame. www.barchart.com More recently, focusing in on the last three months, AAPL's impressive momentum from the first half of 2023 has slowed considerably, with the shares netting a return of less than 5% over this period. Meanwhile, CAT has gained more than 25%, powered in part by well-received Q2 earnings (by contrast, Apple missed iPhone sales estimates in its recent quarterly report). www.barchart.com So with CAT clearly holding its own against this tech powerhouse on the charts, let's take a look at the fundamentals. CAT\\u2019s Earnings Beat Expectations In its second-quarter earnings report, CAT reported revenue of $14.4 billion, marking a 29% surge compared to the previous year. Earnings per share also impressed, up 74% year-over-year to reach $5.55. Notably, both figures outperformed analysts' expectations, which were projected at $13.9 billion and $4.51 per share, respectively. Caterpillar also raised its full-year revenue and earnings guidance, and the stock led Dow gainers after the report with a rally of more than 8%. www.barchart.com CAT attributed its results to a global increase in infrastructure spending and investment. This surge in demand spanned all segments, with its construction, resource, and energy and transportation divisions all posting significant growth. The construction segment reported a 45% revenue increase, buoyed by higher sales volume and the introduction of new products like the electric mini excavator and autonomous dozer. At the same time, resource segment revenue was up 41%, driven by elevated sales volume in mining and entry into emerging markets like lithium and rare earths. Plus, the energy and transportation segment contributed 16% revenue growth, propelled by increased sales volume and innovative\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0199 (i.e., a 1.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0199 = 5.0205, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019918, "expected_loss": 0.019918, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241101_0688", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-11-01", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0394, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0036, std=0.0211, worst_day=-0.0394\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0394 (i.e., a 3.94% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0394 = 2.5402, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.039368, "expected_loss": 0.039368, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240820_0691", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-08-20", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0852, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0041, std=0.0370, worst_day=-0.1002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0852 (i.e., a 8.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0852 = 1.1740, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.085178, "expected_loss": 0.085178, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231027_0694", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2023-10-27", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0155, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0015, std=0.0074, worst_day=-0.0167\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-26] [\"Is WisdomTree U.S. Quality Dividend Growth ETF (DGRW) a Strong ETF Right Now? Launched on 05/22/2013, the WisdomTree U.S. Quality Dividend Growth ETF (DGRW) is a smart beta exchange traded fund offering broad exposure to the Style Box - Large Cap Value category of the market. What Are Smart Beta ETFs? The ETF industry has traditionally been dominated by products based on market capitalization weighted indexes that are designed to represent the market or a particular segment of the market. Investors who believe in market efficiency should consider market cap indexes, as they replicate market returns in a low-cost, convenient, and transparent way. There are some investors, though, who think it's possible to beat the market with great stock selection; this group likely invests in another class of funds known as smart beta, which track non-cap weighted strategies. Non-cap weighted indexes try to choose stocks that have a better chance of risk-return performance, which is based on specific fundamental characteristics, or a mix of other such characteristics. This area offers many different investment choices, such as simplest equal-weighting, fundamental weighting and volatility/momentum based weighting methodologies; however, not all of these strategies can deliver superior results. Fund Sponsor & Index DGRW is managed by Wisdomtree, and this fund has amassed over $9.75 billion, which makes it one of the larger ETFs in the Style Box - Large Cap Value. DGRW seeks to match the performance of the WisdomTree U.S. Quality Dividend Growth Index before fees and expenses. The WisdomTree U.S. Quality Dividend Growth Index is a fundamentally weighted index that consists of dividend-paying stocks with growth characteristics. Cost & Other Expenses Expense ratios are an important factor in the return of an ETF and in the long-term, cheaper funds can significantly outperform their more expensive cousins, other things remaining the same. Annual operating expenses for DGRW are 0.28%, which makes it on par with most peer products in the space. DGRW's 12-month trailing dividend yield is 1.94%. Sector Exposure and Top Holdings Most ETFs are very transparent products, and disclose their holdings on a daily basis. ETFs also offer diversified exposure, which minimizes single stock risk, though it's still important for investors to research a fund's holdings. DGRW's heaviest allocation is in the Information Technology sector, which is about 30.20% of the portfolio. Its Consumer Staples and Industrials round out the top three. Taking into account individual holdings, Microsoft Corp (MSFT) accounts for about 8.85% of the fund's total assets, followed by Apple Inc (AAPL) and Broadcom Inc (AVGO). DGRW's top 10 holdings account for about 35.91% of its total assets under management. Performance and Risk Year-to-date, the WisdomTree U.S. Quality Dividend Growth ETF has added roughly 5.32% so far, and is up about 9.32% over the last 12 months (as of 10/26/2023). DGRW has traded b\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ACWI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0155 (i.e., a 1.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0155 = 6.4531, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015496, "expected_loss": 0.015496, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231128_0696", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-11-28", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0695, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0012, std=0.0231, worst_day=-0.1070\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-27] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0695 (i.e., a 6.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0695 = 1.4398, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069453, "expected_loss": 0.069453, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231214_0699", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-12-14", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0122, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0009, std=0.0064, worst_day=-0.0123\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-13] [\"Zacks Investment Ideas feature highlights: Tesla, Apple and Rivian For Immediate Release Chicago, IL \\u2013 December 15, 2023 \\u2013 Today, Zacks Investment Ideas feature highlights Tesla TSLA, Apple AAPL and Rivian RIVN. Why Tesla's Cheap (2024 Outlook) An Up and Down Year for Tesla Tesla is the undisputed market leader in battery-powered electric car sales in the United States, enjoying roughly a 70% market share. Over the years, Tesla has shifted from developing niche products for affluent buyers to more affordable EVs for the masses. The firm's three-pronged business model approach of direct sales, servicing, and charging sets it apart from other carmakers. Year-to-date, shares are higher by 128%. However, investor concerns are mounting, including: \\u00b7 Valuation: The EV king's market capitalization is more than the combined value of all legacy automakers. \\u00b7 Underperformance: Though Tesla has more than doubled this year, it has underperformed the market and \\\"Magnificent 7\\\" recently. \\u00b7 Recall: This week, news broke that Tesla must recall more than 2 million vehicles. Below, I will debunk the most common investor concerns and lay out my bull case for the stock: Don't Judge a Book By its Cover: Tesla Valuation is Cheap The price-to-book ratio (P/B ratio) is a financial metric that compares a company's market value (its stock price) to its book value (the net value of its assets minus liabilities). P/B is calculated by dividing the market price per share by the book value per share. A low P/B ratio may suggest that a stock is undervalued, while a high ratio may indicate overvaluation. Investors use this ratio to assess a company's relative worth in the market compared to its accounting value. Tesla currently has a book value of 14.03. Compare that to another mainstream stock like Apple, whose book value is 49.54, and Tesla suddenly looks cheap. Furthermore, it is essential to remember that Wall Street is a discounting device. Over the past twelve years, Tesla has achieved a stunning compound annual growth rate (CAGR) of 72%, earning its premium above slower-growing legacy automakers. Rallying on Negative Recall News Earlier this week, Tesla was forced to recall over two million vehicles over autopilot safety concerns. As I always like to remind investors, the reaction to negative news supersedes the news itself. In the case of TSLA, the stock shook off the bad news and is green for the week. Technical \\\"Shakeout\\\" and Price Rotation Higher Savvy investors understand that price movement is the ultimate arbiter of decisions, because after all, price is the only thing that pays. TSLA shares sliced below the 50-day moving average on the recall news and then ripped higher. Such price action indicates a shakeout, where weak hands get stopped out of their positions, clearing the way for the next move higher. Now, TSLA is triggering a bullish swing trade signal by clearing last week's highs. Cybertruck Hype Real Many Tesla bears suggest t\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0122 (i.e., a 1.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0122 = 8.1935, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012205, "expected_loss": 0.012205, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230502_0701", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-05-02", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0784, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0035, std=0.0336, worst_day=-0.0851\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-01] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0784 (i.e., a 7.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0784 = 1.2763, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.078351, "expected_loss": 0.078351, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230704_0703", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2023-07-04", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0177, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0027, std=0.0118, worst_day=-0.0216\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-03] [\"Unity Software Stock Skyrockets 46% in June as AI Buzz Takes Over What happened Shares of Unity Software (NYSE: U) skyrocketed 46.1% in June, according to data provided by S&P Global Market Intelligence. The month started off with fireworks from Apple that are relevant to Unity shareholders. And it ended with a bang related to artificial intelligence (AI), Wall Street's favorite subject at the moment. So what To give this story some context, I want to point out that the market had lost a lot of confidence in Unity Software stock. When they first went public, shares regularly traded above a price-to-sales (P/S) ratio of 30. By comparison, they traded below a P/S of 7 at the start of June. That's still high in absolute terms. But in relative terms, this valuation was more than 80% below where it had routinely traded. Unity's own revenue growth was ample reason for the market's pessimism. And even though its growth has since rebounded, as the chart below shows, this is largely due to an acquisition. Its organic growth is still challenged. U Revenue (quarterly YoY growth) data by YCharts; YoY = year over year. But on June 5, Apple announced its upcoming Vision Pro headset, and this has reinvigorated investors' excitement for Unity's potential. Apple is looking for apps to be built for the headset between now and its launch in 2024. And for this, the company has partnered with Unity. Developers use Unity for building top-notch video games. And Apple has created a software development kit that will allow Unity users to modify their creations for the Vision Pro. Then on June 27, Unity announced a marketplace for AI applications. The marketplace has 10 apps available at launch that can be used in the video game space. And when the company announced this new focus on AI, the market celebrated by pushing the stock higher. So the stock started June with low expectations, but Apple and AI have investors rethinking the long-term potential. Now what When it comes to the AI space, I'm inclined to disregard most news as overhyped clickbait. But with Unity Software stock, I do believe that AI -- specifically generative AI -- could play an important role for the business. Many investors like Unity's potential in virtual reality and the metaverse. Its software creates realistic 3D images, and realism is needed to make these experiences something that consumers actually want. When building digital worlds, the problem is how big these need to be -- it's labor intensive for developers. And the workload is probably too much to physically handle at scale, which is where generative AI can help. Much of what Unity is doing involves generative AI, which I believe is just what the space needs. So as virtual reality and the metaverse grow -- perhaps thanks to Apple's Vision Pro headset -- the use cases for Unity Software could open up as well. That's good reason for optimism for a stock that's still down almost 80% from its all-time high. 10 stocks we like better than Unit\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0177 (i.e., a 1.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0177 = 5.6394, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017732, "expected_loss": 0.017732, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230523_0706", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-05-23", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0222, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0010, std=0.0088, worst_day=-0.0276\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-22] [\"Large-Cap Growth ETFs Actively Adding Value Large-cap growth ETFs continue to lead large-cap value ones in 2023. Through May 16, the iShares Russell 1000 Growth ETF (IWF) was up 16%, beating the iShares Russell 1000 Value ETF (IWD) by 1,700 basis points year-to-date. Meanwhile, the SPDR S&P 500 Growth ETF (SPYG) was up 11%, outperforming the SPDR S&P 500 Value ETF (SPYV) by 700 basis points over the same period. In a prior research piece, I explored the reasons behind the performance difference of Russell- and S&P-based index products this year. The short version: Index providers disagree on whether stocks like Amazon (AMZN), Exxon Mobil (XOM), or Microsoft (MSFT) should be classified as growth stocks, value stocks, or both. However, this relatively strong performance difference between growth and value has likely been the reason research into growth straetgies has been increasing recently across VettaFi\\u2019s platforms. Growth ETF Engagement Stronger Than Value Our Explorer data tool shows advisor research into both large-cap and total market growth ETFs (light purple) has been significantly higher than value ETFs (green) over the last three months. (However, growth strategies remain less popular than broad market products.) [caption id=\\\"attachment_518880\\\" align=\\\"aligncenter\\\" width=\\\"650\\\"] Over the past three months, growth strategies have seen more research on VettaFi than value strategies.[/caption] However, if performance is what investors are looking for, then it's worth pointing out that some active ETFs from well-established managers have been performing even better than the index ETFs, easily justifying their premium. Yet many active growth ETFs remain under the radar. I step through some of these hidden gems below: T. Rowe Price: Strong Performance For Its Active ETFs The T. Rowe Price Growth Stock ETF (TGRW) was up 21% to start 2023, but it has flown under the radar. This active equity ETF has just $42 million in assets. TGRW invests in growth stocks with one or more of the following characteristics: strong cash flow and above-average earnings growth; the ability to sustain earnings momentum in economic downturns; and occupation of a niche in the economy and the ability to expand during times of slow economic growth. T Rowe Price launched its first ETFs, including TGRW, in August 2020, and recently crossed the $1 billion asset milestone. TGRW is run by Joseph Faith, who has managed the growth strategy since 2014. (The ETF launched in August 2020, but his management history also includes the $47 billion T. Rowe Price Growth Stock Fund (PRGFX).) Compared to the mutual fund, TGRW offers an alternative for investors who prefer the ETF structure for tax efficiency and cost reasons. The strategy recently had 42% of its assets invested in information technology stocks. Its top three stakes were Apple (AAPL), Intuit (INTU), and Microsoft, TGRW has a 0.52% expense ratio. Growth Stalwarts Fidelity, Harbor Capital Now Offer ETFs Meanwhile,\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0222 (i.e., a 2.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0222 = 4.5108, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022169, "expected_loss": 0.022169, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240604_0708", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-06-04", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0007, std=0.0426, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230615_0710", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2023-06-15", "context_summary": "SGOV: 60-day history, VaR(99%)=-0.0000, max drawdown threshold=10%.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SGOV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0000 (i.e., a 0.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0000 = 2444.4292, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -4.1e-05, "expected_loss": 4.1e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230306_0712", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2023-03-06", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0205, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0010, std=0.0089, worst_day=-0.0259\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-03] [\"AI stocks surge as investors bet on growth prospects Updates prices to open; adds details, comments March 3 (Reuters) - Shares of artificial intelligence-based (AI) product makers zoomed on Friday, as a strong forecast from retail darling C3.ai Inc AI.N amplified an ongoing euphoria in the segment driven by the launch of OpenAI's ChatGPT. C3.a1 forecast better-than-expected revenue and profit for both the fourth quarter and fiscal year 2023, after its third-quarter results topped Wall Street estimates. Shares of the AI software provider were up 16% at $24.80, and were one of the top five trending stocks on StockTwits. If the gains hold, the stock is set to notch its strongest one-day gain in a month. \\\"The company is starting to gain momentum in building significant enterprise opportunities in its pipeline with its suite of innovative enterprise AI solutions,\\\" said Wedbush analyst Daniel Ives. The firm's aim to turn cash positive and adjusted profitable by the end of fiscal year 2024 also boosted the stock, but Ives believes the execution of these ambitions is key to regain the Street's confidence heading into 2023. Retail investors have flocked to small-cap firms building AI tools as companies such as Google-parent Alphabet Inc AAPL.O and Microsoft Corp MSFT.O have locked horns to make AI the next big growth driver. Microsoft's investment in OpenAI's ChatGPT boosted AI firms' popularity further. Chatbots like the ChatGPT are software applications that aim to mimic human conversation using artificial intelligence. Other major AI stocks also surged on Friday with BigBear.ai BBAI.N, conversation intelligence firm SoundHound AI SOUN.O, and Thailand's security firm Guardforce AI GFAI.O jumping between 5% and 20%. So far this year, these stocks, including C3.ai, have surged 33.9%-321.6%, as of the previous day's close. \\\"AI could become the new gold rush on Wall Street,\\\" said Adam Sarhan, chief executive officer of 50 Park Investments in Florida. (Reporting by Ankika Biswas in Bengaluru; editing by Uttaresh Venkateshwaran) ((Ankika.Biswas@thomsonreuters.com)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-Wall Street climbs as yields pull back By Sruthi Shankar and Shristi Achar A March 3 (Reuters) - U.S. stocks rose on Friday as Treasury yields took a breather from a week-long rally that was sparked by worries that the Federal Reserve would keep interest rates higher for longer to tame stubborn inflation. Wall Street indexes have had a volatile start to March after the latest economic data pointed to rising raw material costs and a resilient labor market, while signaling that the U.S. central bank was yet to see the desired impact of its policy tightening measures on inflation. The U.S. 10-year Treasury yield US10YT=RR fell on Friday after touching a four-month high in the previous session but stayed above the 4% level. US/ \\\"What is driving the op\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EFA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0205 (i.e., a 2.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0205 = 4.8725, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020523, "expected_loss": 0.020523, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240327_0714", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-03-27", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0180, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0008, std=0.0069, worst_day=-0.0180\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0180 (i.e., a 1.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0180 = 5.5595, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017987, "expected_loss": 0.017987, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240822_0716", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-08-22", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0343, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0008, std=0.0146, worst_day=-0.0360\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2024-08-09] unh-20240630 false 2024 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2024-01-01 2024-06-30 0000731766 2024-07-31 0000731766 2024-06-30 0000731766 2023-12-31 0000731766 2024-04-01 2024-06-30 0000731766 2023-04-01 2023-06-30 0000731766 2023-01-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-04-01 2023-06-30 0000731766 us-gaap:ProductMember 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2023-01-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-04-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-04-01 2023-06-30 0000731766 us-gaap:ServiceMember 2024-01-01 2024-06-30 0000731766 us-gaap:ServiceMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2024-03-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000731766 us-gaap:RetainedEarningsMember 2024-03-31 0000731766 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2024-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-06-30 0000731766 us-gaap:CommonStockMember 2022-12-31 0000731766 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2022-12-31 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000731766 us-gaap:NoncontrollingInterestMember 2022-12-31 0000731766 2022-12-31 0000731766 us-gaap:RetainedEarningsMember 2023-01-01 2023-06-30 0000731766 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-06-30 0000731766 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-06-30 0000731766 us-gaap:CommonStockMember 2023-01-01 2023-06-30 0000731766 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-06-30 0000731766 unh:ProductsAndServicesMember 2024-06-30 0000731766 unh:ProductsAndServicesMember 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us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0343 (i.e., a 3.43% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0343 = 2.9181, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034269, "expected_loss": 0.034269, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240724_0718", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-07-24", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0748, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0028, std=0.0350, worst_day=-0.0841\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0748 (i.e., a 7.48% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0748 = 1.3366, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.074815, "expected_loss": 0.074815, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230602_0720", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2023-06-02", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0172, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0003, std=0.0091, worst_day=-0.0172\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-01] [\"GRAPHIC-Nvidia runaway winner in market cap addition in May June 1 (Reuters) - Nvidia Corp's NVDA.OQ market capitalisation jumped the most in May among the top 20 global companies by market value, adding $248 billion, with a majority of the gains coming in the last four sessions, according to Refinitiv data. The chipmaker briefly joined the $1 trillion valuation club, as investors bet on its potential to become a major beneficiary of a boom in artificial intelligence following a revenue forecast that was more than 50% above the Wall Street estimate The company's shares are up 159% so far this year. Taiwan Semiconductor Manufacturing Co Ltd 2330.TW, a key manufacturer of Nvidia's chips, also saw a big jump in its market cap last month. Saudi Arabian Oil 2222.SE and Exxon Mobil Corp XOM.N were the biggest losers in terms of market cap, hit by a decline in oil prices last month. Apple AAPL.OQ and Microsoft MSFT.OQ led the list with the highest market capitalisation in the world. Top 20 companies in the world by market cap https://tmsnrt.rs/45JVJXt Change in market cap in May https://tmsnrt.rs/3qgKBRH (Reporting By Patturaja Murugaboopathy and Gaurav Dogra in Bengaluru; Editing by Sriraj Kalluvila) ((patturaja.muruga@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Meta's Zuckerberg unveils Quest 3 mixed reality headset NEW YORK, June 1 (Reuters) - Meta Platforms META.O CEO Mark Zuckerberg revealed the company's next generation mixed reality headset, the Quest 3, in an Instagram post on Thursday as part of its annual gaming conference. The announcement came less than a week before tech rival Apple AAPL.O was expected to unveil its first mixed reality device, which combines augmented and virtual reality elements. Meta currently dominates the market for AR/VR devices, with a nearly 80% share of the 8.8 million headsets sold in 2022, according to an estimate by market research firm IDC. (Reporting by Katie Paul; Editing by Lisa Shumaker) ((Katie.Paul@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Meta's Zuckerberg unveils Quest 3 mixed reality headset By Katie Paul NEW YORK, June 1 (Reuters) - Meta Platforms META.O CEO Mark Zuckerberg revealed the company's next generation mixed reality headset, the Quest 3, in an Instagram post on Thursday as part of its annual gaming conference. Priced starting at $499, the device will be 40% thinner than the company's previous device and feature color mixed reality, which combines augmented and virtual reality elements, Zuckerberg said in his post. The Quest 3 also will have a new Qualcomm chipset with twice the graphics performance, Zuckerberg said, and promised more details at the company's virtual reality conference in September. Zuckerberg's announcement came less than a week before tech rival\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MTUM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0172 (i.e., a 1.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0172 = 5.8288, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017156, "expected_loss": 0.017156, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240826_0722", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-08-26", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0806, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0497, worst_day=-0.0828\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0806 (i.e., a 8.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0806 = 1.2411, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080575, "expected_loss": 0.080575, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240108_0724", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-01-08", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0649, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0033, std=0.0255, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0649 (i.e., a 6.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0649 = 1.5399, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064941, "expected_loss": 0.064941, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240812_0726", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-08-12", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0220, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0001, std=0.0100, worst_day=-0.0222\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:FairValueInputsLevel2Member 2024-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2024-06-30 0000731766 us-gaap:Fair [...TRUNCATED...] ncorporation of UnitedHealth Group Incorporated (incorporated by reference to Exhibit 3.1 to the Company’s Registration Statement on Form 8-A/A filed on July 1, 2015) 3.2 Amended and Restated Bylaws of UnitedHealth Group Incorporated, effective February 23, 2021 (incorporated by reference to Exhibit 3.2 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ A NDREW W ITTY Chief Executive Officer (principal executive officer) Dated: August 9, 2024 Andrew Witty    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 9, 2024 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 9, 2024 Thomas Roos    28\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0220 (i.e., a 2.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0220 = 4.5545, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021957, "expected_loss": 0.021957, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20231103_0728", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-11-03", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0122, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=-0.0003, std=0.0061, worst_day=-0.0123\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-02] [\"Guru Fundamental Report for AAPL Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Apple (AAPL) Q4 2023 Earnings: What to Expect S ince mid June, Apple (AAPL) shares have not performed as well as investors would have liked. Its shares have fallen more than 14% over the past three months, including a 3% decline in the past thirty days. Apple has fallen victim to the market\\u2019s bearishness towards mega-cap tech amid rising interest rates. Despite that\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0122 (i.e., a 1.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0122 = 8.1935, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012205, "expected_loss": 0.012205, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231215_0730", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-12-15", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0198, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0014, std=0.0092, worst_day=-0.0244\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-14] [\"3 No-Brainer Dividend Stocks to Buy and Hold for 20 Years Successful investing is not as complicated as some make it out to be. Sticking with the brands you use every day, and holding for many years, is a great place to start. Top stocks, such as Apple (NASDAQ: AAPL), Starbucks (NASDAQ: SBUX), and Costco Wholesale (NASDAQ: COST), have a long record of beating the market's average return. The best part is that these companies are so consistent in generating profitable growth from their businesses that they dish out a steady stream of growing dividends to shareholders. Let's find out more why three Motley Fool contributors believe these stocks are no-brainer buys for the next 20 years. Apple has massive cash resources to fund a growing dividend John Ballard (Apple): Investors shouldn't focus only on buying stocks with high yields, since companies that pay high yields are either struggling financially or lacking growth. A smart way to build up dividend income you'll need for retirement is focusing on companies that offer dividend growth. A company that has a long record of raising its dividend payment usually reflects growing demand for the company's products. Moreover, a multiyear record of dividend increases reflects management's confidence in the future of the company. Apple is a great example. Over the past 10 years, its annual dividend grew by 130%, or more than double its fiscal 2013 dividend payment. It has increased the dividend for 12 consecutive years, and because it only pays out 14% of its earnings, Apple can continue increasing the dividend even if earnings are down during an investment year or recession. While the dividend yield on Apple stock is below average at just 0.49% right now, its yield could increase over the next two decades. If Apple doubles its dividend in each decade through 2043, investors who buys shares today could potentially earn a dividend yield on their cost basis approaching 2%. If Apple also doubles its payout closer to 30% of its earnings, the yield could approach 4%. Apple has attractive long-term growth prospects. It should continue to grow through expanding its installed base of active devices, launching new products (e.g., Vision Pro in 2024), and continuing to expand its services business, which should be a great source of profitable growth to help fund future dividend increases. The iPhone, which makes up half of the company's annual revenue, has made Apple one of the most profitable companies in the world. Apple generated $99 billion in free cash flow on $383 billion of revenue over the past year. The resources it has will pave the way for more new products, more profitable growth, and growing dividends for years to come. A buy-on-the-dip dividend opportunity Jennifer Saibil (Starbucks): Starbucks doesn't have any competition as the leader in coffee shops, and it's opening new stores, innovating with beverages, and making other important changes to keep its top spot. The company hired a new CEO this year\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0198 (i.e., a 1.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0198 = 5.0613, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019758, "expected_loss": 0.019758, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240722_0732", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-07-22", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0742, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0001, std=0.0303, worst_day=-0.0765\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0742 (i.e., a 7.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0742 = 1.3469, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.074243, "expected_loss": 0.074243, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240130_0733", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2024-01-30", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0195, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0023, std=0.0101, worst_day=-0.0204\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0195 (i.e., a 1.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0195 = 5.1313, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019488, "expected_loss": 0.019488, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240213_0735", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-02-13", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0234, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0021, std=0.0094, worst_day=-0.0265\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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2022-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-01-01 2023-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2022-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2021-01-01 2021-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-01-01 2023-09-30 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-09-30 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2022-12-31 0001018724 us-gaap:FairValueInputsLevel2Member us-gaap:WarrantMember 2023-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2022-12-31 0001018724 us-gaap:TradeAccountsReceivableMember 2023-12-31 0001018724 amzn:VendorAccountsReceivableMember 2022-12-31 0001018724 amzn:VendorAccountsReceivableMember 2023-12-31 0001018724 us-gaap:LoansReceivableMember 2022-12-31 0001018724 us-gaap:LoansReceivableMember 2023-12-31 00 [...TRUNCATED...] tents 32.2 Certification of Brian T. Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0234 (i.e., a 2.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0234 = 4.2735, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.0234, "expected_loss": 0.0234, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240718_0737", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2024-07-18", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0676, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0035, std=0.0313, worst_day=-0.0711\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0676 (i.e., a 6.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0676 = 1.4803, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.067555, "expected_loss": 0.067555, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231115_0739", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-11-15", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0177, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0005, std=0.0091, worst_day=-0.0191\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-14] [\"Berkshire invests in Atlanta Braves, sheds GM and other stocks Nov 14 (Reuters) - Berkshire Hathaway BRKa.N, the conglomerate run by billionaire Warren Buffett, on Tuesday said it has made a small investment in the company that indirectly owns the Atlanta Braves baseball team, and eliminated its holdings in General Motors GM.N and Procter & Gamble PG.N. The changes were disclosed in a regulatory filing that detailed Berkshire's U.S.-listed stock holdings, which comprise most of its $318.6 billion equity portfolio, as of Sept. 30. Berkshire sold $7 billion of stocks and bought just $1.7 billion in the third quarter, a down period for its stock holdings led by Apple AAPL.O, whose share price fell 12%. (Reporting by Jonathan Stempel in New York; Editing by Christian Schmollinger) ((jon.stempel@thomsonreuters.com; +1 646 223 6317; Reuters Messaging: jon.stempel.thomsonreuters.com@reuters.net)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Pilgrim's Pride and Malibu Boats have been highlighted as Zacks Bull and Bear of the Day For Immediate Release Chicago, IL \\u2013 November 14, 2023 \\u2013 Zacks Equity Research shares Pilgrim's Pride PPC as the Bull of the Day and Malibu Boats MBUU as the Bear of the Day. In addition, Zacks Equity Research provides analysis on The Walt Disney Company DIS, Apple Inc. AAPL and Amazon.com, Inc. AMZN. Here is a synopsis of all five stocks: Bull of the Day: Pilgrim's Pride is a Zacks Rank #1 (Strong Buy) that engages in the production, processing, marketing and distribution of fresh, frozen, and value-added chicken, and pork products to retailers, distributors, and foodservice operators. The stock is trading at 52-week highs after a revenue and earnings beat. While PPC is trading up about 15% on the year, it is still down 25% from 2022 highs. Investors should be looking for more upside if the stock can break the resistance level at $26.50. More About Pilgrim's Pride The company was founded in 1946 and is headquartered in Greeley, Colorado. It employs over 61,000 people and has a market cap of $6 billion. Pilgrim's Pride offers its products under the Pilgrim's, Just BARE, Gold'n Pump, Gold Kist, County Pride, Pierce Chicken, Pilgrim's Mexico, County Post, Savoro, To-Ricos, Del Dia, Moy Park, O'Kane, Richmond, Fridge Raiders, and Denny brands. The company sells its products to chain restaurants, food processors, broad-line distributors, and the retail market. PPC has a Zacks Style Score of \\\"A\\\" in Value and \\\"B\\\" in Growth. The stock has a Forward PE of 17 and pays no dividend. Q3 Earnings In late October, PPC reported a 14% earnings beat on revenues. This the seventh straight earnings beat for the company who has not missed on earnings expectations since late 2021. Q3 came in at $0.58 v $0.42 expected and revenues were $4.4B v $4.29Be. Adjusted EBITDA margins were 7.4%, which was down from the 10.3% last year. While the company e\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QUAL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0177 (i.e., a 1.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0177 = 5.6593, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01767, "expected_loss": 0.01767, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230725_0741", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-07-25", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0140, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0001, std=0.0061, worst_day=-0.0153\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-24] [\"Wells Fargo Maintains Apple (AAPL) Overweight Recommendation Fintel reports that on July 24, 2023, Wells Fargo maintained coverage of Apple (NASDAQ:AAPL) with a Overweight recommendation. Analyst Price Forecast Suggests 0.16% Upside As of July 6, 2023, the average one-year price target for Apple is 192.24. The forecasts range from a low of 141.40 to a high of $252.00. The average price target represents an increase of 0.16% from its latest reported closing price of 191.94. See our leaderboard of companies with the largest price target upside. The projected annual revenue for Apple is 413,641MM, an increase of 7.41%. The projected annual non-GAAP EPS is 6.36. For more in-depth coverage of Apple, view the free, crowd-sourced company research report on Finpedia. What is the Fund Sentiment? There are 6390 funds or institutions reporting positions in Apple. This is a decrease of 15 owner(s) or 0.23% in the last quarter. Average portfolio weight of all funds dedicated to AAPL is 3.91%, an increase of 45.88%. Total shares owned by institutions increased in the last three months by 37.90% to 14,010,479K shares. The put/call ratio of AAPL is 0.89, indicating a bullish outlook. What are Other Shareholders Doing? Berkshire Hathaway holds 915,560K shares representing 5.82% ownership of the company. In it's prior filing, the firm reported owning 895,136K shares, representing an increase of 2.23%. The firm increased its portfolio allocation in AAPL by 19.39% over the last quarter. VTSMX - Vanguard Total Stock Market Index Fund Investor Shares holds 465,280K shares representing 2.96% ownership of the company. In it's prior filing, the firm reported owning 459,387K shares, representing an increase of 1.27%. The firm increased its portfolio allocation in AAPL by 18.69% over the last quarter. VFINX - Vanguard 500 Index Fund Investor Shares holds 347,041K shares representing 2.21% ownership of the company. In it's prior filing, the firm reported owning 345,686K shares, representing an increase of 0.39%. The firm increased its portfolio allocation in AAPL by 18.16% over the last quarter. Geode Capital Management holds 285,171K shares representing 1.81% ownership of the company. In it's prior filing, the firm reported owning 282,750K shares, representing an increase of 0.85%. The firm increased its portfolio allocation in AAPL by 18.38% over the last quarter. Price T Rowe Associates holds 234,017K shares representing 1.49% ownership of the company. In it's prior filing, the firm reported owning 226,281K shares, representing an increase of 3.31%. The firm increased its portfolio allocation in AAPL by 22.14% over the last quarter. Apple Background Information (This description is provided by the company.) Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services. It is considered one of the Big Five companies in the U.S. information \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0140 (i.e., a 1.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0140 = 7.1441, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013998, "expected_loss": 0.013998, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230418_0743", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2023-04-18", "context_summary": "HYG: 60-day history, VaR(99%)=-0.0118, max drawdown threshold=10%.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0002, std=0.0059, worst_day=-0.0137\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to HYG, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0118 (i.e., a 1.18% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0118 = 8.4793, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011793, "expected_loss": 0.011793, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231207_0745", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-12-07", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.0976, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0015, std=0.0577, worst_day=-0.1157\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-06] [\"ROKU Collaborates With Tennis Channel to Launch T2 in the US Roku Inc. ROKU has announced a collaboration with Tennis Channel to launch T2, the sports network's second channel, on The Roku Channel in the United States. T2 is set to provide free and year-round access to live coverage of top tennis players and signature events for the vast audience of The Roku Channel, reaching an estimated 100 million people. For convenient access, viewers can easily navigate T2 through the Sports Experience on Roku's Home Screen. This feature simplifies the discovery and access of live, upcoming and on-demand sports content, enhancing engagement and awareness for Roku's content partners while providing a personalized viewing experience. T2's yearly live and encore calendar aligns with most tournaments covered by Tennis Channel, showcasing different matches and players. This unique approach allows viewers with access to both channels to choose between simultaneous competitions from prestigious events, such as the BNP Paribas Open, Roland Garros, Miami Open, Monte-Carlo Masters, Italian Open, Canadian Open, Davis Cup and the Billie Jean King Cup. Shares of this Zacks Rank #3 (Hold) company have gained 158.5% year to date compared with the Zacks Consumer Discretionary sector\\u2019s rise of 12.4% due to its extensive collection of content. You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. Roku, Inc. Price and Consensus Roku, Inc. price-consensus-chart | Roku, Inc. Quote ROKU\\u2019s Recent Efforts to Boost Streaming Hours The company recently unveiled two fresh additions to the Roku Home Screen, such as All Things Food and All Things Home. These new destinations bring together top-notch food, home and lifestyle content from various sources on the platform, creating seamless and engaging discovery experiences. These new features are expected to boost streaming hours as well as platform revenues in the upcoming quarters. The Zacks Consensus Estimate for ROKU\\u2019s 2023 streaming hours is pegged at 105.33 billion, indicating a year-over-year increase of 340.7%. The consensus estimate for 2023 platform revenues is pegged at $2.9 billion, indicating a year-over-year increase of 7.38%. Designed for user convenience, these hubs offer straightforward navigation and personalized recommendations, simplifying the exploration and viewing of genre entertainment directly from the home screen. Both All Things Food and All Things Home will showcase a diverse array of streaming options within their respective categories, encompassing free and subscription-based services, live and linear TV, Premium Subscriptions, Roku Originals and more. These features were added due to a recent survey commissioned by Roku. This recent survey revealed that 64% of streamers rely on genre-based searches when looking for new content, emphasizing the significance of genre preferences in content discovery. According to the survey, nearly 73% of streamers feel that the\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0976 (i.e., a 9.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0976 = 1.0247, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.097587, "expected_loss": 0.097587, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230530_0747", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2023-05-30", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0014, std=0.0119, worst_day=-0.0329\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-26] [\"Alphabet CEO Sundar Pichai Commits to \\\"AI Pact\\\": What Does This Really Mean? The world of artificial intelligence (AI) is moving at a breakneck speed, and top corporate and political leaders are trying to safely guide its evolution. Alphabet (NASDAQ: GOOG) (NASDAQ: GOOGL) CEO Sundar Pichai met with European Commissioner for the internal market Thierry Breton on Wednesday to discuss the progression of AI and map out possible actions to help ensure the emerging technology doesn't get out of hand. In the meeting, Pichai promised that his company would join an \\\"AI pact\\\" and collaborate with other players in the artificial intelligence space on a volunteer basis to shape and abide by guidelines for tech development. But while there's seemingly a lot to like about the prospect of guardrails being put on AI, it's not clear that voluntary pacts or even strict laws will be able to address many of the potential problems that could arise. Could an AI pact help stave off potential disasters? While detailed specifics of what rules and guidelines members of an AI pact would be adhering to haven't been made available, Pichai's discussion with other members of the European Commission suggest that privacy standards and fighting misinformation could be key focuses. The rapid progression for artificial intelligence tech over the last year is unprecedented, and continued advances could be unwieldy. Because legislative bodies can be slow to act and laws vary between territories, it could be important for technology leaders to attempt to establish some kind of presiding framework for artificial intelligence initiatives. Taking a proactive approach to the problems and questions raised by incredible leaps forward for artificial intelligence could help minimize the possibility of disastrous outcomes stemming from the tech. The AI pact mentioned by Pichai at the meeting with Breton seems to be a step in this direction. But there's a risk that rules surrounding AI might not amount to much. For one, it's possible that voluntary AI guidelines and restrictions will be followed very loosely or only in the most nominal senses. It's also possible that those who don't abide by rules for the artificial intelligence project, whether self-imposed or through regulations, could actually gain significant competitive advantages. Controlling AI could be incredibly difficult The European Parliament is currently finalizing a new set of rules and restrictions that will govern AI technologies. The EU AI Act isn't officially law yet, but it's seemingly headed in that direction and could be a landmark response that plays a big role in the tech's evolution in Europe. But it might not be enough, and it may have unintended consequences. Developing ways to work around restrictions could be incentivized by the proposed regulations, and the speed at which AI tech has been progressing will make it difficult for regulators to keep up. Additionally, there are already signs that influential player\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0289 (i.e., a 2.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0289 = 3.4613, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028891, "expected_loss": 0.028891, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230109_0748", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2023-01-09", "context_summary": "HYG: 60-day history, VaR(99%)=-0.0135, max drawdown threshold=10%.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0009, std=0.0074, worst_day=-0.0137\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to HYG, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0135 (i.e., a 1.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0135 = 7.3870, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013537, "expected_loss": 0.013537, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230609_0750", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-06-09", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0610, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0240, worst_day=-0.0799\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-08] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0610 (i.e., a 6.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0610 = 1.6387, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.061023, "expected_loss": 0.061023, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240906_0752", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-09-06", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0844, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0034, std=0.0438, worst_day=-0.0853\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0844 (i.e., a 8.44% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0844 = 1.1848, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.084405, "expected_loss": 0.084405, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230412_0754", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-04-12", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0831, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0032, std=0.0436, worst_day=-0.0901\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-11] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0831 (i.e., a 8.31% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0831 = 1.2036, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.083082, "expected_loss": 0.083082, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230831_0756", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2023-08-31", "context_summary": "BIL: 60-day history, VaR(99%)=-0.0000, max drawdown threshold=10%.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0001, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BIL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0000 (i.e., a 0.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0000 = 2242.4251, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -4.5e-05, "expected_loss": 4.5e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231212_0758", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-12-12", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0624, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0289, worst_day=-0.0625\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-11] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0624 (i.e., a 6.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0624 = 1.6024, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.062407, "expected_loss": 0.062407, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230222_0760", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-02-22", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0696, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0088, std=0.0400, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-21] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0696 (i.e., a 6.96% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0696 = 1.4368, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069599, "expected_loss": 0.069599, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241107_0762", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-11-07", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0621, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0023, std=0.0306, worst_day=-0.0632\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0621 (i.e., a 6.21% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0621 = 1.6101, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.062108, "expected_loss": 0.062108, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231211_0764", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-12-11", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1087, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0250, std=0.0600, worst_day=-0.1393\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-10] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9200", "answer_numeric": 0.92, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1087 (i.e., a 10.87% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1087 = 0.9200, capped at 1.0.\nMaximum position size = 0.9200 (92.0% of portfolio).", "metadata": {"var_99": -0.108699, "expected_loss": 0.108699, "max_drawdown_threshold": 0.1, "position_size": 0.92, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241213_0765", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-12-13", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0608, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0083, std=0.0376, worst_day=-0.0717\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0608 (i.e., a 6.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0608 = 1.6445, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.06081, "expected_loss": 0.06081, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230307_0767", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-03-07", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0189, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0009, std=0.0097, worst_day=-0.0246\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-06] [\"After Hours Most Active for Mar 6, 2023 : VALE, BAC, AMZN, QQQ, MRK, AAPL, IQ, MSFT, PFE, KO, ALIT, WDC The NASDAQ 100 After Hours Indicator is down -10.89 to 12,291.59. The total After hours volume is currently 79,432,799 shares traded. The following are the most active stocks for the after hours session: VALE S.A. (VALE) is -0.01 at $16.68, with 6,521,728 shares traded. VALE's current last sale is 87.79% of the target price of $19. Bank of America Corporation (BAC) is unchanged at $34.09, with 3,492,820 shares traded. BAC's current last sale is 89.71% of the target price of $38. Amazon.com, Inc. (AMZN) is -0.09 at $93.66, with 3,173,777 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Jun 2023. The consensus EPS forecast is $0.28. As reported by Zacks, the current mean recommendation for AMZN is in the \\\"buy range\\\". Invesco QQQ Trust, Series 1 (QQQ) is +1.21 at $301.23, with 3,064,552 shares traded. This represents a 18.47% increase from its 52 Week Low. Merck & Company, Inc. (MRK) is -0.09 at $111.01, with 2,632,264 shares traded. As reported by Zacks, the current mean recommendation for MRK is in the \\\"buy range\\\". Apple Inc. (AAPL) is -0.15 at $153.68, with 2,211,853 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2023. The consensus EPS forecast is $1.43. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". iQIYI, Inc. (IQ) is +0.0604 at $7.65, with 1,819,482 shares traded. As reported by Zacks, the current mean recommendation for IQ is in the \\\"buy range\\\". Microsoft Corporation (MSFT) is -0.02 at $256.85, with 1,791,083 shares traded. As reported by Zacks, the current mean recommendation for MSFT is in the \\\"buy range\\\". Pfizer, Inc. (PFE) is -0.0101 at $41.10, with 1,556,995 shares traded. PFE's current last sale is 82.2% of the target price of $50. Coca-Cola Company (The) (KO) is -0.01 at $60.35, with 1,519,857 shares traded. Over the last four weeks they have had 6 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2023. The consensus EPS forecast is $0.64. As reported by Zacks, the current mean recommendation for KO is in the \\\"buy range\\\". Alight, Inc. (ALIT) is unchanged at $9.81, with 1,492,772 shares traded. As reported by Zacks, the current mean recommendation for ALIT is in the \\\"buy range\\\". Western Digital Corporation (WDC) is unchanged at $37.78, with 1,388,099 shares traded. WDC's current last sale is 75.56% of the target price of $50. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-S&P 500 ends slightly higher ahead of Powell testimony, upcoming data By Sin\\u00e9ad Carew and Bansari Mayur Kamdar March 6 (Reuters) - The S&P 500 made little progress on Monday, closing slightly lower than its session high as U.S. \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0189 (i.e., a 1.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0189 = 5.2777, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018948, "expected_loss": 0.018948, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230201_0769", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-02-01", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0600, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0037, std=0.0265, worst_day=-0.0775\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-31] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0600 (i.e., a 6.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0600 = 1.6663, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060013, "expected_loss": 0.060013, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230620_0771", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-06-20", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1065, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0073, std=0.0317, worst_day=-0.1516\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9387", "answer_numeric": 0.9387, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1065 (i.e., a 10.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1065 = 0.9387, capped at 1.0.\nMaximum position size = 0.9387 (93.9% of portfolio).", "metadata": {"var_99": -0.106532, "expected_loss": 0.106532, "max_drawdown_threshold": 0.1, "position_size": 0.9387, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230623_0774", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-06-23", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0149, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0009, std=0.0079, worst_day=-0.0158\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-22] [\"After Hours Most Active for Jun 22, 2023 : BTE, PLTR, ABR, AAPL, STKL, AMZN, KDP, IGIB, IQ, KO, SU, T The NASDAQ 100 After Hours Indicator is up 11.63 to 15,053.95. The total After hours volume is currently 81,431,725 shares traded. The following are the most active stocks for the after hours session: Baytex Energy Corp (BTE) is unchanged at $3.02, with 19,760,377 shares traded., following a 52-week high recorded in today's regular session. Palantir Technologies Inc. (PLTR) is -0.09 at $13.96, with 16,613,117 shares traded. PLTR's current last sale is 174.5% of the target price of $8. Arbor Realty Trust (ABR) is -0.02 at $14.06, with 8,556,060 shares traded. As reported by Zacks, the current mean recommendation for ABR is in the \\\"buy range\\\". Apple Inc. (AAPL) is +0.11 at $187.11, with 3,168,168 shares traded., following a 52-week high recorded in today's regular session. SunOpta, Inc. (STKL) is +0.1 at $6.95, with 2,583,726 shares traded. As reported in the last short interest update the days to cover for STKL is 7.427717; this calculation is based on the average trading volume of the stock. Amazon.com, Inc. (AMZN) is +0.24 at $130.39, with 2,345,481 shares traded. As reported by Zacks, the current mean recommendation for AMZN is in the \\\"buy range\\\". Keurig Dr Pepper Inc. (KDP) is unchanged at $31.92, with 2,158,387 shares traded. KDP's current last sale is 81.85% of the target price of $39. iShares 5-10 Year Investment Grade Corporate Bond ETF (IGIB) is +0.0074 at $50.39, with 1,646,206 shares traded. This represents a 7.64% increase from its 52 Week Low. iQIYI, Inc. (IQ) is +0.04 at $5.17, with 1,552,708 shares traded. As reported by Zacks, the current mean recommendation for IQ is in the \\\"buy range\\\". Coca-Cola Company (The) (KO) is -0.05 at $61.80, with 1,549,093 shares traded. As reported by Zacks, the current mean recommendation for KO is in the \\\"buy range\\\". Suncor Energy Inc. (SU) is unchanged at $28.81, with 1,319,952 shares traded. SU's current last sale is 73.87% of the target price of $39. AT&T Inc. (T) is unchanged at $15.58, with 1,268,446 shares traded. As reported by Zacks, the current mean recommendation for T is in the \\\"buy range\\\". The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-Wall Street ends higher as Powell wraps up testimony By Stephen Culp June 22 (Reuters) - The S&P 500 and the Nasdaq closed higher on Thursday as U.S. Federal Reserve Chairman Jerome Powell continued to beat a hawkish drum and suggested the central bank has not reached the end of its tightening cycle, but provided reassurance that the Fed would proceed with caution. The tech-heavy Nasdaq's robust gain got a boost from momentum stocks led by Amazon.com AMZN.O Apple Inc AAPL.O, and Microsoft Corp MSFT.O, while the S&P 500's advance was more modest. Industrials .SPLRCI and financials .SPSY held the blue-chip Dow essentially flat. \\\"Investors are playin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0149 (i.e., a 1.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0149 = 6.7005, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014924, "expected_loss": 0.014924, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230419_0776", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2023-04-19", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0239, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0004, std=0.0103, worst_day=-0.0249\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-18] [\"Apple CEO Tim Cook Opens First Store In India (RTTNews) - Apple Inc. Chief Executive Officer Tim Cook has inaugurated the tech major's first retail store in India, which is being considered as its new manufacturing base as well as new growth market. The first store, called Apple BKC, is located in the country's financial capital Mumbai. On Thursday, the company will open its second store in India, Apple Saket, in the capital of Delhi. The launch comes as Apple is aiming to boost sales, manufacturing and exports of Apple products including iPhones in India. Apple BKC is located inside the Jio World Drive mall at Bandra Kurla Complex or BKC in Mumbai. According to the company, Apple BKC is one of the most energy-efficient Apple Store locations in the world, operationally carbon neutral, running on 100 percent renewable energy. Prior to the inauguration, Cook tweeted a photo of himself and Apple BKC staff. Apple BKC will offer a special Today at Apple series, \\\"Mumbai Rising,\\\" running from the store's opening day through the summer. These free sessions featuring Apple products and services are expected to bring visitors, local artists, and creatives together. The iPhone maker, which views India as a key market, has been present in the country for more than 25 years. Cook in an earlier statement said, \\\"India has such a beautiful culture and an incredible energy, and we're excited to build on our long-standing history.\\\" Apple, which assembles most of its iPhones in China, last year announced plans to shift some production of its flagship smartphone iPhone 14 from China to India amid continuing tensions between the US and China, along with the then prevailed COVID-19 issues. Foxconn, Apple's key iPhone assembler, already manufactures iPhones at its Sriperumbudur factory on the outskirts of Chennai, India. In March, Bloomberg reported that Foxconn plans to invest $700 million to set up a new iPhone plant in India's Karnataka state, which would create 100,000 jobs. Foxconn will build a new 300-acre facility in Bengaluru as part of its ongoing effort to pivot away from China. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"3 Things About Shopify That Smart Investors Know Shopify (NYSE: SHOP) has taken investors on a wild ride since its initial public offering (IPO). The e-commerce services provider went public at a split-adjusted price of $1.70 per share on May 21, 2015; skyrocketed to an all-time high of $169.06 on Nov. 19, 2021, at the peak of the buying frenzy in growth stocks, but now trades at about $46. A $1,000 investment in its IPO would have grown to nearly $100,000 before shrinking back to about $27,000 today. Nevertheless, a 27-bagger gain in just under eight years still easily beats the S&P 500's gain of 94% during the same period. Image source: Getty Images. Shopify's stock initially caught fire because investors were impressed by its ability to disr\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0239 (i.e., a 2.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0239 = 4.1849, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023896, "expected_loss": 0.023896, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240924_0778", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2024-09-24", "context_summary": "DBB: 60-day history, VaR(99%)=-0.0205, max drawdown threshold=10%.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=0.0002, std=0.0115, worst_day=-0.0224\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DBB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0205 (i.e., a 2.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0205 = 4.8676, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020544, "expected_loss": 0.020544, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240123_0780", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-01-23", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0397, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0048, std=0.0271, worst_day=-0.0405\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0397 (i.e., a 3.97% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0397 = 2.5213, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.039662, "expected_loss": 0.039662, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230406_0782", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-04-06", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0624, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0009, std=0.0377, worst_day=-0.0647\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-05] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0624 (i.e., a 6.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0624 = 1.6015, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.062443, "expected_loss": 0.062443, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240621_0783", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-06-21", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0612, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0034, std=0.0325, worst_day=-0.0678\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0612 (i.e., a 6.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0612 = 1.6340, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.061199, "expected_loss": 0.061199, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240530_0784", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-05-30", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0547, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0288, worst_day=-0.0610\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0547 (i.e., a 5.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0547 = 1.8296, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.054658, "expected_loss": 0.054658, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230814_0786", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-08-14", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0419, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0017, std=0.0238, worst_day=-0.0422\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-13] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0419 (i.e., a 4.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0419 = 2.3849, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.04193, "expected_loss": 0.04193, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230824_0788", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-08-24", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0522, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0428, worst_day=-0.0559\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-23] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0522 (i.e., a 5.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0522 = 1.9165, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.052177, "expected_loss": 0.052177, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230324_0790", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-03-24", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0411, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0016, std=0.0176, worst_day=-0.0481\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-23] [\"US STOCKS-Wall Street rallies on hopes of Fed policy pause For a Reuters live blog on U.S., UK and European stock markets, click LIVE/ or type LIVE/ in a news window Jobless claims remain low, new home sales rise Block Inc slides after Hindenburg discloses short position US SEC threatens to sue Coinbase, shares drop Regional banks head lower Indexes up: Dow 0.44%, S&P 0.66%, Nasdaq 1.30% New throughout, adds NEW YORK dateline, changes byline By Stephen Culp NEW YORK, March 23 (Reuters) - Wall Street advanced on Thursday as market participants looked past remarks by U.S. Federal Reserve Chairman Jerome Powell on Wednesday and weighed the possibility that the central bank will pause its restrictive interest rate hikes in the near future. All three indexes marked the three-year anniversary of the nadir of the COVID-19 crash by heading higher, with megacap growth stocks, led by Microsoft MSFT.O and Apple Inc AAPL.O, providing the most upside muscle and putting the tech-heavy Nasdaq out front. \\\"Today the market is bouncing back on what was a dovish Fed hike yesterday,\\\" said Ross Mayfield, investment strategy analyst at Baird in Louisville, Kentucky. \\\"Powell did a good job sticking to the party line on inflation and continued to jawbone hawkish even though the hike leaned dovish.\\\" \\\"It\\u2019s not too crazy for markets to see that pivot in the near future,\\\" Mayfield added. The risk-on session reversed Wednesday's late-session sell-off after the Fed's rate hike, Powell's subsequent Q&A session and Treasury Secretary Janet Yellen's testimony before congress in which she ruled out blanket protection for all deposits. In view of recent turmoil in the financial sector, which began with the failures of SVB Financial Group SIVB.O and Signature Bank SBNY.O, worries that the Fed was overtightening and pushing the economy perilously close to recession, Powell's reiterance of the Fed's determination to cool inflation sparked a late session flight to safety. Jitters among regional banks persist, with the KBW Regional Bank index .KRX sliding 2.3%. Comments from the Bank of England that inflation will probably quickly fade also helped fuel hopes of light at the end of the central bank tightening tunnel. The BoE's commentary \\\"paints a picture of a global central banking system that's ready to slow the pace of their hiking,\\\" Mayfield said. But economic data released on Thursday showed jobless claims inching lower and new home sales posting a surprise gain, providing fresh evidence that the economy is yet to show the kind of softening that would lend itself to cooling inflation. The Dow Jones Industrial Average .DJI rose 142.01 points, or 0.44%, to 32,172.12, the S&P 500 .SPX gained 26.11 points, or 0.66%, to 3,963.08 and the Nasdaq Composite .IXIC added 151.81 points, or 1.3%, to 11,821.77. Among the 11 sectors of the S&P 500, communication services .SPLRCL and tech .SPLRCT led the percentage gainers. First Republic Bank FRC.Ndropped 8.6% in volatile trading i\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0411 (i.e., a 4.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0411 = 2.4320, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.041118, "expected_loss": 0.041118, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240318_0792", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2024-03-18", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0210, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0014, std=0.0104, worst_day=-0.0241\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0210 (i.e., a 2.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0210 = 4.7555, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021028, "expected_loss": 0.021028, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240520_0794", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-05-20", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0161, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0009, std=0.0068, worst_day=-0.0176\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0161 (i.e., a 1.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0161 = 6.2010, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016126, "expected_loss": 0.016126, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230111_0796", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2023-01-11", "context_summary": "PALL: 60-day history, VaR(99%)=-0.0502, max drawdown threshold=10%.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=-0.0016, std=0.0283, worst_day=-0.0619\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PALL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0502 (i.e., a 5.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0502 = 1.9906, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.050236, "expected_loss": 0.050236, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241113_0798", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2024-11-13", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0195, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0008, std=0.0074, worst_day=-0.0218\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 000009 [...TRUNCATED...] ATION ISSUER PURCHASES OF EQUITY SECURITIES   Period Total Number of Shares Purchased (*) Average Price Paid per Share Total Number of Shares Purchased as Part of Publicly Announced Program Approximate Dollar Value of Shares that May Yet Be Purchased Under the 2023 Program (*) (Billions of dollars) July 1 - July 31, 2024 7,923,000  $156.56 7,923,000  $56.6 August 1 - August 31, 2024 12,057,000  $146.20 12,057,000  $54.8 September 1 - September 30, 2024 12,229,398  $142.84 12,229,398  $53.1 Total 32,209,398   $147.47 32,209,398   (*) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections A. Nigel Hearne , Executive Vice President, Senior Advisor , entered into a pre-arranged stock trading plan on August 19, 2024 . Mr. Hearne’s plan provides for the potential exercise of vested stock options and the associated sale of up to 60,468 shares of Chevron common stock between November 18, 2024, and February 28, 2025 . The trading plan was entered into during an open insider trading window and is intended to satisfy the affirmative defense of Rule 10b5-1(c) under the Securities Exchange Act of 1934, as amended, and Chevron’s policies regarding transactions in Chevron securities. 44 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 10.1+* Chevron Incentive Plan, amended and restated effective October 2, 2023 (refi l ed to correct formatting in the previo usly filed version) . 10.2+* Chevron Corporation Retirement Restoration Plan, amended and restated effective August 1, 2024. 10.3+* Chevron Corporation ESIP Restoration Plan, amended and restated effective August 1, 2024. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ +     Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 45 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 7, 2024 46\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QUAL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0195 (i.e., a 1.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0195 = 5.1190, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019535, "expected_loss": 0.019535, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240716_0800", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-16", "context_summary": "SPY: 60-day history, VaR(99%)=-0.0117, max drawdown threshold=10%.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0020, std=0.0058, worst_day=-0.0160\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SPY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0117 (i.e., a 1.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0117 = 8.5330, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011719, "expected_loss": 0.011719, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241104_0802", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2024-11-04", "context_summary": "IYR: 60-day history, VaR(99%)=-0.0182, max drawdown threshold=10%.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0005, std=0.0079, worst_day=-0.0200\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IYR, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0182 (i.e., a 1.82% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0182 = 5.4843, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018234, "expected_loss": 0.018234, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230524_0804", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-05-24", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0372, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=-0.0015, std=0.0142, worst_day=-0.0372\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-23] [\"Don't Count On Apple's New Headset To Move The Needle For The Stock Apple (NASDAQ:AAPL) is widely expected to launch its mixed-reality headset shortly, potentially as early as the beginning of June, when the company holds its annual worldwide developer conference (WWDC). The headset would be Apple\\u2019s first all-new product line since the Apple Watch and the potential launch comes at a time when Apple\\u2019s bread and butter smartphone and computing product businesses face a slowdown, with Covid-19 tailwinds easing. So will the new device move the needle for Apple stock? We don\\u2019t think it will, for a couple of reasons. While Apple is known for disrupting product categories with highly refined products with great software and design, the new headset appears to be entering a much more nascent market. Smartphone sales were rising and use cases were clear when Apple got into the game in 2007 with a highly refined product. Similarly, the templates for tablets were largely set when Apple launched iPad in 2010. However, the mixed-reality headset appears like a bit more of a speculative bet. While Apple\\u2019s products are typically sleek, with high-end industrial design, the headset could be more utilitarian and could resemble a pair of goggles connected to an external battery pack, per the Wall Street Journal. The device is expected to combine virtual reality \\u2013 used for games and experiences \\u2013 with augmented reality, which overlays digital information in the real world potentially using cameras. Apple would need to educate consumers on what the device is really for. Companies such as Facebook have invested considerable sums into this space thus far with little success. Worldwide shipments of VR headsets and augmented reality devices actually declined by over 12% year over year to 9.6 million in 2022, per data from analyst firm CCS Insight. Apple\\u2019s device is also initially going to be expensive, with reports pointing to a price tag of roughly $3,000, indicating that it will likely focus on a niche audience of early adopters in its first iteration. Overall, we don\\u2019t think the device will help Apple\\u2019s stock in the near term. Apple stock already trades at a relatively lofty $175 per share, or almost 30x forward earnings, despite the fact that consensus forecasts point to a revenue decline this year. We don\\u2019t think the pricey headset will do much to re-rate Apple stock higher in the near term. That being said, there is good reason to believe that Apple could eventually make its mark in the segment. Apple is known for cutting-edge hardware engineering and also emerging as a leader in semiconductor design. Apple also has a knack of working with developers and building a software ecosystem around its products, while refining future iterations of the device around particular areas that consumers like. For instance, with the Apple Watch, Apple took a few years to zone in that customers really valued the fitness capacities o\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0372 (i.e., a 3.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0372 = 2.6872, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037214, "expected_loss": 0.037214, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240807_0805", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-08-07", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0343, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0001, std=0.0138, worst_day=-0.0360\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-04-01 2024-06-30 0001364742 blk:EquityETFsMember blk:RevenueByClientTypeMember 2023-04-01 2023-06-3 [...TRUNCATED...] y primarily to satisfy income tax withholding obligations of employees and members of the Company’s Board of Directors related to the vesting of certain restricted stock unit awards and purchases made by the Company as part of the share repurchase program that the Company announced in July 2010, which initially authorized the repurchase of 5.1 million shares with no stated expiration. In January 2023, the Company announced that the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 70   Item 5. Other Information O n May 13, 2024 , Mark Wiedman , Senior Managing Director , adopted a Rule 10b5-1 trading plan, intended to satisfy the affirmative defense of Rule 10b5-1(c), for the sale of up to 36,000 shares of BlackRock common stock. The plan's expiration date is April 30, 2025 . 71   Item 6. Exh ibits Exhibit No.   Description       10.1(1)       Amendment No. 15, dated as of May 31, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein       10.2(2)   BlackRock, Inc. Third Amended and Restated 1999 Stock Award and Incentive Plan+       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on May 31, 2024. (2) Incorporated by reference to BlackRock’s Definitive Proxy Statement on Form DEF 14A filed on April 4, 2024. + Denotes compensatory plans or arrangements. 72   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.     BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: August 6, 2024     Martin S. Small       Senior Managing Director & Chief Financial Officer (Principal Financial Officer)   73\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0343 (i.e., a 3.43% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0343 = 2.9181, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034269, "expected_loss": 0.034269, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241018_0807", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2024-10-18", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0330, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0020, std=0.0162, worst_day=-0.0340\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XHB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0330 (i.e., a 3.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0330 = 3.0344, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032955, "expected_loss": 0.032955, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240209_0808", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2024-02-09", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0221, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0003, std=0.0105, worst_day=-0.0235\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLU, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0221 (i.e., a 2.21% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0221 = 4.5321, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022065, "expected_loss": 0.022065, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240705_0810", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2024-07-05", "context_summary": "REZ: 60-day history, VaR(99%)=-0.0256, max drawdown threshold=10%.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0011, std=0.0096, worst_day=-0.0332\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to REZ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0256 (i.e., a 2.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0256 = 3.9139, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02555, "expected_loss": 0.02555, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240405_0812", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-04-05", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0298, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0007, std=0.0125, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0298 (i.e., a 2.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0298 = 3.3568, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02979, "expected_loss": 0.02979, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240719_0814", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-07-19", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0489, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0003, std=0.0226, worst_day=-0.0531\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0489 (i.e., a 4.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0489 = 2.0454, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.04889, "expected_loss": 0.04889, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230105_0816", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-01-05", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.1337, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0039, std=0.0423, worst_day=-0.1754\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-04] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7480", "answer_numeric": 0.748, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1337 (i.e., a 13.37% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1337 = 0.7480, capped at 1.0.\nMaximum position size = 0.7480 (74.8% of portfolio).", "metadata": {"var_99": -0.133688, "expected_loss": 0.133688, "max_drawdown_threshold": 0.1, "position_size": 0.748, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230628_0817", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2023-06-28", "context_summary": "SHV: 60-day history, VaR(99%)=-0.0001, max drawdown threshold=10%.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, worst_day=-0.0002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SHV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0001 (i.e., a 0.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0001 = 722.1323, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000138, "expected_loss": 0.000138, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230421_0819", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-04-21", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0561, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0029, std=0.0294, worst_day=-0.0624\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-20] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0561 (i.e., a 5.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0561 = 1.7810, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056149, "expected_loss": 0.056149, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231009_0821", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-10-09", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0530, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0037, std=0.0182, worst_day=-0.0588\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-08] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0530 (i.e., a 5.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0530 = 1.8884, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.052956, "expected_loss": 0.052956, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231117_0823", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2023-11-17", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0177, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0004, std=0.0090, worst_day=-0.0191\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-16] [\"July 2024 Options Now Available For Apple Investors in Apple Inc (Symbol: AAPL) saw new options begin trading today, for the July 2024 expiration. One of the key data points that goes into the price an option buyer is willing to pay, is the time value, so with 246 days until expiration the newly trading contracts represent a potential opportunity for sellers of puts or calls to achieve a higher premium than would be available for the contracts with a closer expiration. At Stock Options Channel, our YieldBoost formula has looked up and down the AAPL options chain for the new July 2024 contracts and identified one put and one call contract of particular interest. The put contract at the $185.00 strike price has a current bid of $8.95. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $185.00, but will also collect the premium, putting the cost basis of the shares at $176.05 (before broker commissions). To an investor already interested in purchasing shares of AAPL, that could represent an attractive alternative to paying $188.92/share today. Because the $185.00 strike represents an approximate 2% discount to the current trading price of the stock (in other words it is out-of-the-money by that percentage), there is also the possibility that the put contract would expire worthless. The current analytical data (including greeks and implied greeks) suggest the current odds of that happening are 99%. Stock Options Channel will track those odds over time to see how they change, publishing a chart of those numbers on our website under the contract detail page for this contract. Should the contract expire worthless, the premium would represent a 4.84% return on the cash commitment, or 7.18% annualized \\u2014 at Stock Options Channel we call this the YieldBoost. Below is a chart showing the trailing twelve month trading history for Apple Inc, and highlighting in green where the $185.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $190.00 strike price has a current bid of $15.30. If an investor was to purchase shares of AAPL stock at the current price level of $188.92/share, and then sell-to-open that call contract as a \\\"covered call,\\\" they are committing to sell the stock at $190.00. Considering the call seller will also collect the premium, that would drive a total return (excluding dividends, if any) of 8.67% if the stock gets called away at the July 2024 expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if AAPL shares really soar, which is why looking at the trailing twelve month trading history for Apple Inc, as well as studying the business fundamentals becomes important. Below is a chart showing AAPL's trailing twelve month trading history, with the $190.00 strike highlighted in red: Considering the fact that the $190.00 strike represents an approximate 1% premium to the cur\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to QUAL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0177 (i.e., a 1.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0177 = 5.6593, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01767, "expected_loss": 0.01767, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230404_0825", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-04-04", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0192, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0014, std=0.0106, worst_day=-0.0200\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-04-03] [\"Top Research Reports for Apple, Meta Platforms & Visa Monday, April 3, 2023 The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc. (AAPL), Meta Platforms, Inc. (META) and Visa Inc. (V). These research reports have been hand-picked from the roughly 70 reports published by our analyst team today. You can see all of today\\u2019s research reports here >>> Apple shares are up +26.7% in the year-to-dater period vs. the Zacks Tech sector's 20.6% gain and the S&P 500 index's +7.4% gain. The company expects the March quarter\\u2019s year-over-year revenue growth to be similar to that of the December quarter due to unfavorable forex. For iPhone, Apple expects the March quarter\\u2019s year-over-year revenue growth to accelerate relative to the December quarter\\u2019s year-over-year revenue growth. For Mac and iPad, revenues are expected to decline in double digits on a year-over-year basis due to challenging comparison and macroeconomic headwinds. Services revenue growth is expected to be negatively impacted by challenging macroeconomic conditions, as well as weakness in digital advertising and gaming. However, revenues are expected to grow year over year. Growing services subscriber base and a strong liquidity position are key catalysts for Apple\\u2019s prospects. (You can read the full research report on Apple here >>>) Shares of Meta Platforms have outperformed the Zacks Internet - Software industry over the past six months (+51.1% vs. +14.1%). The company is benefiting from steady user growth across all regions, particularly Asia Pacific. Increased engagement for its products like Instagram, WhatsApp, Messenger, and Facebook has been a major growth driver. Its restructuring plan is expected to reduce expenses driving profitability. However, challenging macroeconomic conditions is negatively impacting Meta\\u2019s advertising revenues. Unfavorable forex, targeting and measurement headwinds due to Apple\\u2019s iOS changes, normalization of e-commerce after the pandemic peak and higher inflation hurt growth in the reported quarter. Meta\\u2019s first-quarter guidance reflects macroeconomic and forex concerns. Weak advertising demand is a headwind. Meta expects Reels to monetize much slower than feed or stories, which is a concern. (You can read the full research report on Meta Platforms here >>>) Visa shares have outperformed the Zacks Financial Transaction Services industry over the past six months (+22.0% vs. +15.2%). The company\\u2019s numerous buyouts and alliances paved the way for long-term growth and consistently drove its revenues. For fiscal 2023, net revenues are estimated to rise in the high single digits on a reported nominal dollar basis. Constant investments in technology are solidifying its position in the payments market. A shift in payments to the digital mode is a boon for Visa. Steady domestic volumes and transactions ris\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0192 (i.e., a 1.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0192 = 5.1994, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019233, "expected_loss": 0.019233, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230607_0827", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-06-07", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0699, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0046, std=0.0244, worst_day=-0.0737\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-06] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0699 (i.e., a 6.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0699 = 1.4304, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069913, "expected_loss": 0.069913, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230707_0829", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-07-07", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0225, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0007, std=0.0119, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-06] [\"Wall St logs sharp losses as labor market strength stokes rate-hike fears By Lewis Krauskopf, Bansari Mayur Kamdar and Johann M Cherian July 6 (Reuters) - Wall Street's main indexes ended sharply lower on Thursday in a broad sell-off after data showing a strong labor market boosted bond yields and fanned fears the Federal Reserve will be aggressive in raising U.S. interest rates. The S&P 500 posted its biggest daily percentage drop since May 23. The Dow logged its biggest single-day fall since May 2. Private payrolls surged far more than expected in June, data showed, suggesting the labor market remained solid despite growing risks of a recession. A separate report showed U.S. job openings dropped in May, but remained at elevated levels. A day before the monthly U.S employment report, evidence of a solid labor market spurred expectations the Fed will keep interest rates higher for longer to tame stubborn inflation. \\u201cWe don\\u2019t see any softening in the labor market,\\u201d said Brad McMillan, chief investment officer for Commonwealth Financial Network. \\u201cThe Fed doesn\\u2019t have to worry about the jobs market. When you look at their mandate, they have no reason not to keep hiking and to keep hiking for a while.\\u201d The Dow Jones Industrial Average .DJI fell 366.38 points, or 1.07%, to 33,922.26, the S&P 500 .SPX lost 35.23 points, or 0.79%, to 4,411.59 and the Nasdaq Composite .IXIC dropped 112.61 points, or 0.82%, to 13,679.04. All 11 S&P 500 sectors ended down. Energy .SPNY led declines among the sectors, dropping about 2.5%, while consumer discretionary .SPLRCD slumped nearly 1.7%. Gains in megacap stocks mitigated declines for the major indexes, which ended above their session lows. Microsoft MSFT.O rose 0.9% while Apple AAPL.O was up 0.3%. Treasury yields jumped following the labor market data. The benchmark 10-year yield US10YT=RR burst above 4% while the two-year US2YT=RR Treasury yield, which typically moves in step with interest rate expectations, hit a 16-year high. U.S. interest rate futures saw an increased probability of another rate hike by the Federal Reserve in November, according to CME's FedWatch. The Fed did not hike rates in June but is widely expected to resume increases at its July meeting. Dallas Fed President Lorie Logan said there was a case for a rate rise at the June policy meeting. In company news, Exxon Mobil Corp XOM.N shares fell 3.7% after the oil major signaled a sharp fall in second-quarter operating profits on lower natural gas prices and weaker oil refining margins. Second-quarter corporate reports will arrive in coming weeks with S&P 500 earnings expected to fall 5.7% from a year-ago, according to Refinitiv data. \\u201cYou have a situation where rates are going higher, profits are not really moving,\\\" said King Lip, chief strategist at Baker Avenue Wealth Management. \\\"That\\u2019s usually not a good combination for stocks.\\u201d JetBlue AirwaysJBLU.O shares dropped 7.2% a day after the company s\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0225 (i.e., a 2.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0225 = 4.4464, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02249, "expected_loss": 0.02249, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240507_0831", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-05-07", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0046, std=0.0420, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241030_0833", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2024-10-30", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0103, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0012, std=0.0051, worst_day=-0.0109\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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iso4217:USD iso4217:USD xbrli:shares iso4217:EUR xbrli:pure 0000021344 2024-01-01 2024-09-27 0000021344 ko:CommonStock0.25ParValueMember 2024-01-01 2024-09-27 0000021344 ko:A1.875NotesDue2026Member 2024-01-01 2024-09-27 0000021344 ko:A0.750NotesDue2026Member 2024-01-01 2024-09-27 0000021344 ko:A1.125NotesDue2027Member 2024-01-01 2024-09-27 0000021344 ko:A125NotesDue2029KO29AMember 2024-01-01 2024-09-27 0000021344 ko:A125NotesDue2029KO29BMember 2024-01-01 2024-09-27 0000021344 ko:A400NotesDue2030Member 2024-01-01 2024-09-27 0000021344 ko:A1.250NotesDue2031Member 2024-01-01 2024-09-27 0000021344 ko:A3.125NotesDue2032Member 2024-01-01 2024-09-27 0000021344 ko:A375NotesDue2033Member 2024-01-01 2024-09-27 0000021344 ko:A500NotesDue2033Member 2024-01-01 2024-09-27 0000021344 ko:A1.625NotesDue2035Member 2024-01-01 2024-09-27 0000021344 ko:A1.100NotesDue2036Member 2024-01-01 2024-09-27 0000021344 ko:A950NotesDue2036Member 2024-01-01 2024-09-27 0000021344 ko:A3.375NotesDue2037Member 2024-01-01 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ko:BangladeshBottlingOperationsMember 2024-01-01 2024-09-27 0000021344 ko:BangladeshBottlingOperationsMember 2024-09-27 0000021344 ko:PhilippinesBottlingOperationsMember 2024-01-01 2024-09-27 0000021344 country:US ko:ConcentrateOperationsMember 2024-06-29 2024-09-27 0000021344 ko:InternationalMember ko:ConcentrateOperationsMember 2024-06-29 2024-09-27 0000021344 ko:ConcentrateOperationsMember 2024-06-29 2024-09-27 0000021344 country:US ko:FinishedProductOperationsMember 2024-06-29 2024-09-27 0000021344 ko:InternationalMember ko:FinishedProductOperationsMember 2024-06-29 2024-09-27 0000021344 ko:FinishedProductOperationsMember 2024-06-29 2024-09-27 0000021344 country:US 2024-06-29 2024-09-27 0000021344 ko:InternationalMember 2024-06-29 2024-09-27 0000021344 country:US ko:ConcentrateOperationsMember 2023-07-01 2023-09-29 0000021344 ko:InternationalMember ko:ConcentrateOperationsMember 2023-07-01 2023-09-29 0000021344 ko:ConcentrateOperationsMember 2023-07-01 2023-09-29 0000021344 country:US ko:FinishedProductOperationsMember 2023-07-01 2023-09-29 0000021344 ko:InternationalMember ko:FinishedProductOperationsMember 2023-07-01 2023-09-29 0000021344 ko:FinishedProductOperationsMember 2 [...TRUNCATED...] among Coca-Cola Refreshments USA, Inc., the Company and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on June 2 3, 2017. 4.51 Third Supplemental Indenture, dated as of July 5, 2017, to the Indenture, dated as of July 30, 1991, as amended, among Coca-Cola Refreshments USA, Inc., the Company and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on July 6, 2017. 10.1 Supplemental Award Notification — 2022 and 2023 Performance Share Units under The Coca-Cola 2014 Equity Plan — incorporated herein by reference to Exhibit 10.1 to the Company’s Form 8-K filed on August 21, 2024. 10.2 Supplemental Award Notification — 2022 and 2023 Restricted Stock Units under The Coca-Cola 2014 Equity Plan — incorporated herein by reference to Exhibit 10.2 to the Company’s Form 8-K filed on August 21, 2024. 31.1 Rule 13a-14(a)/15d-14(a) Certification, executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company. 31.2 Rule 13a-14(a)/15d-14(a) Certification, executed by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 32.1 Certifications required by Rule 13a-14(b) or Rule 15d-14(b) and Section 1350 of Chapter 63 of Title 18 of the United States Code (18 U.S.C. Section 1350), executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company, and by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 101 The following financial information from The Coca-Cola Company’s Quarterly Report on Form 10-Q for the quarter ended September 27, 2024, formatted in iXBRL (Inline Extensible Business Reporting Language): (i) Consolidated Statements of Income for the three and nine months ended September 27, 2024 and September 29, 2023; (ii) Consolidated Statements of Comprehensive Income for the three and nine months ended September 27, 2024 and September 29, 2023; (iii) Consolidated Balance Sheets as of September 27, 2024 and December 31, 2023; (iv) Consolidated Statements of Cash Flows for the nine months ended September 27, 2024 and September 29, 2023; and (v) Notes to Consolidated Financial Statements. 104 Cover Page Interactive Data File (the cover page XBRL tags are embedded within the iXBRL document and included in Exhibit 101). 57 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     THE COCA-COLA COMPANY (Registrant) /s/ ERIN MAY Date: October 24, 2024 Erin May Senior Vice President, Controller and Chief Accounting Officer (Principal Accounting Officer) 58\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0103 (i.e., a 1.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0103 = 9.6808, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01033, "expected_loss": 0.01033, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20230322_0834", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-03-22", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0754, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0386, worst_day=-0.0799\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-21] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0754 (i.e., a 7.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0754 = 1.3260, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.075412, "expected_loss": 0.075412, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231228_0836", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2023-12-28", "context_summary": "SCHP: 60-day history, VaR(99%)=-0.0076, max drawdown threshold=10%.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0010, std=0.0042, worst_day=-0.0086\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SCHP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0076 (i.e., a 0.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0076 = 13.0884, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.00764, "expected_loss": 0.00764, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231227_0838", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-12-27", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0170, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0010, std=0.0097, worst_day=-0.0176\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-26] [\"Apple Watch ban goes into effect, Bristol Myers buying RayzeBio: Yahoo Finance Live Apple (AAPL) is appealing a ban on US sales of its Apple Watch Series 9 and Ultra 2. The ban stems from a patent dispute over pulse oximetry technology that is used in the watches. There is also deal news, with shares of RayzeBio (RYZB) doubling after it was announced Bristol Myers Squibb (BMY) was buying the company in a $4.1 billion agreement. Also on Yahoo Finance at 4 p.m. ET, Ark Invest\\u2019s Cathie Wood talks Tesla (TSLA) and the potential for a spot bitcoin ETF to be approved. Trending tickers on Yahoo Finance include Intel (INTC), Nio (NIO), and Nvidia (NVDA).Top guests on Yahoo Finance Live today include:3:05 p.m. ET - Tom Hainlin, U.S. Bank Wealth Management Senior Investment Strategist3:25 p.m. ET - Greg Martin, Managing Director of Rainmaker Securities3:50 p.m. ET - Shehzad Qazi, China Beige Book International Managing Director4:05 p.m. ET - Nick Powills, Mainland CEO, 1851 Franchise Publisher, and The Melting Pot Board Member\", \"Apple seeks a path to getting 2 of its best watches back on shelves during a bitter patent dispute Apple filed an emergency motion seeking court permission to begin selling two of its most popular watches again until a final decision on its broader appeal in a bitter patent dispute is decided. The company cut off sales right before the Christmas holiday and in a motion filed Tuesday, Apple said it would suffer \\u201cirreparable harm\\u201d if previous court orders remain for the two weeks that it said the U.S. International Trade Commission will take to respond to its appeal. The disruption will likely cost Apple about $300-400 million in holiday-season sales, estimated Wedbush Securities analyst Dan Ives.\", \"Bitcoin Dips Below $42,000 While Memecoin Rally Shows Signs of Stalling (Bloomberg) -- Bitcoin dropped below $42,000 for the first time in a week and the recent rally in memecoins has started to show signs of stalling. Most Read from BloombergGoldman\\u2019s Painful 2023 Lesson on China Forces Rethink of Emerging MarketsS&P 500 Trades Within a Whisker of All-Time High: Markets WrapApple to Fight Watch Ban in Court After White House Declines to ActHow Were So Many Economists So Wrong About the Recession?Ethiopia Fails to Pay Coupon, Becoming Latest African DefaulterThe lar\", \"25 Technologies That Have Changed the World In this article, we will be analyzing the evolution of technology while covering the 25 technologies that have changed the world. If you wish to skip our detailed analysis, you can move directly to the 5 Technologies That Have Changed the World. Technology Over the Years Following the dot com bubble burst, technology successfully rebounded. [\\u2026]\", \"South Korea\\u2019s Consumers Turn Less Pessimistic as Inflation Eases (Bloomberg) -- South Korean consumers turned less pessimistic this month as inflation eased and exports improved.Most Read from BloombergS&P 500 Trades Within a Whisker of All-Time High: Ma\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0170 (i.e., a 1.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0170 = 5.8797, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017008, "expected_loss": 0.017008, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240102_0840", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2024-01-02", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0695, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0056, std=0.0308, worst_day=-0.1070\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0695 (i.e., a 6.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0695 = 1.4398, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069453, "expected_loss": 0.069453, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240314_0841", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-03-14", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0702, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0062, std=0.0357, worst_day=-0.1009\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0702 (i.e., a 7.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0702 = 1.4243, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.070211, "expected_loss": 0.070211, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230118_0843", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-01-18", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0303, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0011, std=0.0147, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-17] [\"FAANG Stocks Look Ready to Soar Later This Month. Here's Why. FAANG stocks got crushed last year as a combination of slowing growth and compressing valuations hit even the mightiest tech stocks like Amazon (NASDAQ: AMZN), Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG), and Apple (NASDAQ: AAPL). 2023 offers investors the chance at a new beginning, and stocks jumped out of the gate on data showing that inflation is cooling while the economy remains stable. Looking ahead to earnings season, there's another reason why the stock market, and especially FAANG stocks, could get a boost. The dollar has weakened substantially over the last few months, which makes international revenue more valuable. Image source: Getty Images. The FX effect When big tech stocks reported third-quarter earnings nearly three months ago, a stronger dollar was a major headwind because all of these companies derive a significant percentage of their revenue from outside the U.S. In Amazon's third-quarter earnings report, the company reported 15% revenue growth, but it rose 19% in constant currency. Alphabet reported 6% revenue growth in its third quarter, or 11% in constant currency, and Netflix's (NASDAQ: NFLX) revenue rose 6%, or 13% in constant currency. As you can see from the chart below, the dollar index hit a 10-year high a few months ago, but the dollar cooled rapidly since then as interest rates have fallen and investors expect the Fed to stop hiking interest rates soon. ^DJFXCMD data by YCharts The chart below shows that the dollar plateaued in late September and October before falling sharply when the CPI report came out in November showing inflation falling faster than expected. It's continued to fall since then and now is the lowest it's been since last May. ^DJFXCMD data by YCharts Most multinational companies expected currency headwinds to strengthen from the third quarter to the fourth quarter. However, based on the chart above and the year-over-year comparisons, those currency headwinds seem to have actually weakened from the third quarter to the fourth, though they'll still weigh on results. That's a good indicator that FAANG results will beat guidance since these companies made their forecasts based on the value of the dollar in late October. Amazon, for example, called for 460 basis points of currency headwinds in its fourth quarter, but currency headwinds will almost certainly be more favorable than that. Similarly, Netflix, which gets most of its revenue from outside the U.S., expected nearly 8 percentage points of currency headwinds. Not only will these companies benefit from the weaker dollar in the fourth quarter, but their guidance is also likely to get a lift from the falling dollar. In fact, currency exchange could become a tailwind within a couple of quarters and for 2023 as a whole if the dollar continues to weaken. The weakening dollar is also a tailwind because of its impact on the bottom line. These companies typically have most of their expenses in U.\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0303 (i.e., a 3.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0303 = 3.2990, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030312, "expected_loss": 0.030312, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230119_0844", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2023-01-19", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0408, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0010, std=0.0176, worst_day=-0.0481\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-18] [\"AAPL September 2024 Options Begin Trading Investors in Apple Inc (Symbol: AAPL) saw new options become available today, for the September 2024 expiration. One of the key inputs that goes into the price an option buyer is willing to pay, is the time value, so with 611 days until expiration the newly available contracts represent a potential opportunity for sellers of puts or calls to achieve a higher premium than would be available for the contracts with a closer expiration. At Stock Options Channel, our YieldBoost formula has looked up and down the AAPL options chain for the new September 2024 contracts and identified one put and one call contract of particular interest. The put contract at the $135.00 strike price has a current bid of $15.20. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $135.00, but will also collect the premium, putting the cost basis of the shares at $119.80 (before broker commissions). To an investor already interested in purchasing shares of AAPL, that could represent an attractive alternative to paying $136.98/share today. Because the $135.00 strike represents an approximate 1% discount to the current trading price of the stock (in other words it is out-of-the-money by that percentage), there is also the possibility that the put contract would expire worthless. The current analytical data (including greeks and implied greeks) suggest the current odds of that happening are 99%. Stock Options Channel will track those odds over time to see how they change, publishing a chart of those numbers on our website under the contract detail page for this contract. Should the contract expire worthless, the premium would represent a 11.26% return on the cash commitment, or 6.73% annualized \\u2014 at Stock Options Channel we call this the YieldBoost. Below is a chart showing the trailing twelve month trading history for Apple Inc, and highlighting in green where the $135.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $140.00 strike price has a current bid of $22.40. If an investor was to purchase shares of AAPL stock at the current price level of $136.98/share, and then sell-to-open that call contract as a \\\"covered call,\\\" they are committing to sell the stock at $140.00. Considering the call seller will also collect the premium, that would drive a total return (excluding dividends, if any) of 18.56% if the stock gets called away at the September 2024 expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if AAPL shares really soar, which is why looking at the trailing twelve month trading history for Apple Inc, as well as studying the business fundamentals becomes important. Below is a chart showing AAPL's trailing twelve month trading history, with the $140.00 strike highlighted in red: Considering the fact that the $140.00 strike represents an approximate 2% \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0408 (i.e., a 4.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0408 = 2.4508, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.040804, "expected_loss": 0.040804, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241121_0845", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-11-21", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0379, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0070, std=0.0261, worst_day=-0.0394\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0379 (i.e., a 3.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0379 = 2.6420, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03785, "expected_loss": 0.03785, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240429_0847", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2024-04-29", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0220, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0012, std=0.0127, worst_day=-0.0258\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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0000104169 us-gaap:FairValueInputsLevel12And3Member 2021-02-01 2022-01-31 00001 [...TRUNCATED...] sentation Linkbase Document 104 Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 15, 2024   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 15, 2024   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 15, 2024   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 15, 2024   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 86 Date: March 15, 2024   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 15, 2024 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 15, 2024 By /s/ Sarah Friar Sarah Friar Director Date: March 15, 2024 By /s/ Carla A. Harris Carla A. Harris Director Date: March 15, 2024 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 15, 2024 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 15, 2024 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 15, 2024   By   /s/ S. Robson Walton     S. Robson Walton     Director Date: March 15, 2024   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2024 87\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MTUM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0220 (i.e., a 2.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0220 = 4.5524, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021967, "expected_loss": 0.021967, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240927_0850", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2024-09-27", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0236, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0013, std=0.0120, worst_day=-0.0288\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0236 (i.e., a 2.36% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0236 = 4.2346, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023615, "expected_loss": 0.023615, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241003_0851", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2024-10-03", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0257, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0005, std=0.0105, worst_day=-0.0298\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 2024-05-01 2024-07-31 0000104169 2023-05-01 2023-07-31 0000104169 2023-02-01 2023-07-31 0000104169 2024-07-31 0000104169 2024-01-31 0000104169 2023-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 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us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 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0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VTI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0257 (i.e., a 2.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0257 = 3.8985, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025651, "expected_loss": 0.025651, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230612_0852", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-06-12", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1243, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0071, std=0.0355, worst_day=-0.1516\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-11] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8048", "answer_numeric": 0.8048, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1243 (i.e., a 12.43% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1243 = 0.8048, capped at 1.0.\nMaximum position size = 0.8048 (80.5% of portfolio).", "metadata": {"var_99": -0.124257, "expected_loss": 0.124257, "max_drawdown_threshold": 0.1, "position_size": 0.8048, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231006_0853", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-10-06", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0564, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0325, worst_day=-0.0616\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-05] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0564 (i.e., a 5.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0564 = 1.7735, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056387, "expected_loss": 0.056387, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231003_0855", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-10-03", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0558, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0046, std=0.0222, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-02] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0558 (i.e., a 5.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0558 = 1.7912, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.055828, "expected_loss": 0.055828, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230605_0857", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-06-05", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0634, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0028, std=0.0228, worst_day=-0.0870\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-04] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0634 (i.e., a 6.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0634 = 1.5768, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.063419, "expected_loss": 0.063419, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240515_0859", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-05-15", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1241, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0079, std=0.0409, worst_day=-0.1409\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8057", "answer_numeric": 0.8057, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1241 (i.e., a 12.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1241 = 0.8057, capped at 1.0.\nMaximum position size = 0.8057 (80.6% of portfolio).", "metadata": {"var_99": -0.124117, "expected_loss": 0.124117, "max_drawdown_threshold": 0.1, "position_size": 0.8057, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230905_0861", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-09-05", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.0920, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0010, std=0.0498, worst_day=-0.0925\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-01] [\"Should You Buy the Dow Stock Outperforming Apple? When you think of top-performing Dow stocks to buy, you might automatically think of Apple (AAPL) - it's the world\\u2019s most valuable company, a favorite of legendary investor Warren Buffett, and a leader in consumer technology. But what if we told you there is another Dow Jones Industrial Average ($DOWI) component that has been crushing Apple on the charts over several time frames - and it's not even a tech stock? That stock is none other than Caterpillar (CAT), the world\\u2019s largest manufacturer of construction and mining equipment and a true old-school industrial name. And while CAT hasn't exactly collected AI stock-sized gains in 2023, it's worth taking a look at the stock's performance from a few different perspectives to get a sense of its real technical muscle. CAT's Long-Term Technical Dominance To be sure, Apple stock is outpacing comfortably CAT on a year-to-date basis - but let's not forget how much room for recovery Apple and its tech stock peers had after a brutal finish to 2022. Looking over the past 52 weeks, Caterpillar stock has gained nearly 60%, while AAPL is only 20% higher. The broader Dow, for perspective, is up about 10% in this time frame. www.barchart.com More recently, focusing in on the last three months, AAPL's impressive momentum from the first half of 2023 has slowed considerably, with the shares netting a return of less than 5% over this period. Meanwhile, CAT has gained more than 25%, powered in part by well-received Q2 earnings (by contrast, Apple missed iPhone sales estimates in its recent quarterly report). www.barchart.com So with CAT clearly holding its own against this tech powerhouse on the charts, let's take a look at the fundamentals. CAT\\u2019s Earnings Beat Expectations In its second-quarter earnings report, CAT reported revenue of $14.4 billion, marking a 29% surge compared to the previous year. Earnings per share also impressed, up 74% year-over-year to reach $5.55. Notably, both figures outperformed analysts' expectations, which were projected at $13.9 billion and $4.51 per share, respectively. Caterpillar also raised its full-year revenue and earnings guidance, and the stock led Dow gainers after the report with a rally of more than 8%. www.barchart.com CAT attributed its results to a global increase in infrastructure spending and investment. This surge in demand spanned all segments, with its construction, resource, and energy and transportation divisions all posting significant growth. The construction segment reported a 45% revenue increase, buoyed by higher sales volume and the introduction of new products like the electric mini excavator and autonomous dozer. At the same time, resource segment revenue was up 41%, driven by elevated sales volume in mining and entry into emerging markets like lithium and rare earths. Plus, the energy and transportation segment contributed 16% revenue growth, propelled by increased sales volume and innovative\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0920 (i.e., a 9.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0920 = 1.0867, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.092025, "expected_loss": 0.092025, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230608_0863", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2023-06-08", "context_summary": "SOYB: 60-day history, VaR(99%)=-0.0222, max drawdown threshold=10%.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=-0.0014, std=0.0094, worst_day=-0.0257\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOYB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0222 (i.e., a 2.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0222 = 4.4965, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02224, "expected_loss": 0.02224, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230803_0864", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-08-03", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0123, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0015, std=0.0065, worst_day=-0.0141\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-02] [\"Mediocre Earnings After the Bell; Selloff Continues Markets had a hard time today reconciling the first U.S. credit rating downgrade in 12 years, when Fitch Ratings \\u2014 one of the \\u201cbig three\\u201d credit rating agencies \\u2014 lowered its rating from the usual AAA to AA+. The reason for the move is the same as it was a dozen years ago: Congress is kicking the can on increasing its debt ceiling, which, if not raised, would cause the U.S. to default on its debts. Last time, it was also a Democratic White House and a Republican-led House of Representatives that saw this issue emerge. In any case, market indices were down across the board today. All the majors opened normal trading in the red and stayed there, closing off session lows, but not by much. The Dow shed -331 points, -0.93%, while the Nasdaq dropped -309 points, -2.17%. The S&P 500 and small-cap Russell 2000 were down -1.39% and -1.37%, respectively. So far, August looks to be giving back a significant amount of July gains, just in the first two days of the new month\\u2019s trading. Qualcomm QCOM is the latest major company to post mixed results in its quarterly report this afternoon: while fiscal Q3 earnings of $1.87 per share bettered the $1.81 in the Zacks consensus, revenues of $8.45 billion came up short of the $8.51 billion. Revenue guidance for fiscal Q4 are for a range of $8.1-8.9 billion, with a midpoint lower than the consensus $8.69 billion. A -25% drop in handset chip sales year over year and a slower recovery in China contributed to the performance. Shares are down -4.5% on the release. MGM Resorts MGM, however, outperformed estimates on both top and bottom lines, with earnings of 59 cents per share beating the 53 cents expected, and sales of $3.94 billion in the quarter easily surpassing the $3.76 billion consensus. Its MGM China business in Macau has surprised to the upside, notching +5% growth over 2019 (pre-Covid) levels, +21% on the key EBITDAR metric. However, after cranking +48% higher year to date, investors are selling this news; MGM is -7% in today\\u2019s after-market. PayPal PYPL reported in-line earnings at $1.16 per share on $7.29 billion in quarterly revenues, up nearly +7% year over year. Guidance for Q3 looks to be slightly above previous estimates, as Payment Volume grew +11% year over year. That said, Operating Margin of +21.4% in the quarter missed consensus expectations of +22%, and this may be adding fuel to the -7.5% selloff in today\\u2019s late trading. PayPal has also been an underperformer year to date. Etsy ETSY posted beats on both top and bottom lines this afternoon, with earnings of 45 cents per share improving by 4 cents over the Zacks consensus, on revenues of $629 million in the quarter. Gross merchandising came in at $3.01 billion, -20% year to date, even as the company noted Etsy Active Buyers reached an all-time high in the quarter. Shares are selling off -5% after normal hours. Closing on a positive note, DoorDash DASH shares are u\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0123 (i.e., a 1.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0123 = 8.1591, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012256, "expected_loss": 0.012256, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230616_0865", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2023-06-16", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0164, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0017, std=0.0078, worst_day=-0.0169\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-06-15] [\"US STOCKS-Wall St edges up as yields slip after economic data By Shristi Achar A and Sruthi Shankar June 15 (Reuters) - Wall Street's main indexes inched higher on Thursday as megacap stocks rose on lower Treasury yields, lifting investor sentiment soured by Federal Reserve's hawkish comments on interest rate hikes this year. U.S. retail sales unexpectedly rose in May as consumers spent on a range of goods including vehicles, which could help support the economy this quarter. Another set of numbers showed initial claims for state unemployment benefits were steady at a seasonally adjusted 262,0000 for the week ended June 10. Economists polled by Reuters had forecast 249,000 claims for the latest week. U.S. Treasury yields pulled back, lifting shares of rate-sensitive growth stocks. Apple AAPL.O, Microsoft MSFT.O and Meta Platforms META.O gained between 0.8% and 1.3%. US/ The Fed left rates unchanged at the 5%-5.25% range on Wednesday, but indicated they could rise by at least half a percentage point this year as inflation remains stubbornly persistent and the U.S. economy stays resilient. \\\"What has been encouraging is that the rate market has significantly reassessed the trajectory of expected interest rates but the equity market has largely ignored that and, if anything, continued to rise on the belief that the Fed is at or near the end of the rate hike cycle,\\\" said Ronald Temple, chief market strategist at Lazard. \\\"Yesterday's message was a bit of a splash of cold water on equity markets.\\\" Traders see a nearly 65% chance of a 25-basis-point rate hike in July, up from around 60% a day earlier, according to the CME Fedwatch tool. Energy stocks .SPNY led gains among the 11 major S&P 500 sectors, up 1.4%, tracking higher crude prices. O/R At 10:06 a.m. ET, the Dow Jones Industrial Average .DJI was up 188.05 points, or 0.55%, at 34,167.38, the S&P 500 .SPX was up 16.85 points, or 0.39%, at 4,389.44, and the Nasdaq Composite .IXIC was up 25.76 points, or 0.19%, at 13,652.23. Kroger CoKR.N dropped 3.9% after the big-box retailer missed first-quarter revenue estimates. Kohls Corp KSS.N added 3.1% after TD Cowen upgraded the department store operator to \\\"outperform\\\" from \\\"market perform\\\". U.S.-listed shares of Chinese companies including Alibaba Group BABA.N and JD.com JD.O rose almost 3% after the People's Bank of China cut the borrowing cost for its medium-term policy loans for the first time in 10 months. Advancing issues outnumbered decliners by a 1.90-to-1 ratio on the NYSE and a 1.46-to-1 ratio on the Nasdaq. The S&P index recorded 20 new 52-week highs and no new low, while the Nasdaq recorded 32 new highs and 38 new lows. (Reporting by Shristi Achar A and Sruthi Shankar in Bengaluru Editing by Vinay Dwivedi) ((Shristi.AcharA@thomsonreuters.com;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"US STOCKS-Wall Street rallies as yields slip after econom\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0164 (i.e., a 1.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0164 = 6.1081, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016372, "expected_loss": 0.016372, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240424_0867", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2024-04-24", "context_summary": "SGOV: 60-day history, VaR(99%)=0.0001, max drawdown threshold=10%.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, worst_day=0.0000\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SGOV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0001 (i.e., a 0.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0001 = 1708.0905, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": 5.9e-05, "expected_loss": 5.9e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240521_0868", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2024-05-21", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1228, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0408, worst_day=-0.1359\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8146", "answer_numeric": 0.8146, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1228 (i.e., a 12.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1228 = 0.8146, capped at 1.0.\nMaximum position size = 0.8146 (81.5% of portfolio).", "metadata": {"var_99": -0.122765, "expected_loss": 0.122765, "max_drawdown_threshold": 0.1, "position_size": 0.8146, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230516_0870", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-05-16", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0706, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0333, worst_day=-0.0940\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-15] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0706 (i.e., a 7.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0706 = 1.4161, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.070615, "expected_loss": 0.070615, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230509_0872", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-05-09", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0132, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0004, std=0.0072, worst_day=-0.0138\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-08] [\"Is Apple Stock a Buy Right Now? Apple (NASDAQ: AAPL) has demonstrated an ability to create innovative products consumers are willing to pay premium prices for. Fool.com contributor and finance professor Parkev Tatevosian considers whether Apple's stock is a buy right now. *Stock prices used were the afternoon prices of May 4, 2023. The video was published on May 6, 2023. 10 stocks we like better than Apple When our analyst team has a stock tip, it can pay to listen. After all, the newsletter they have run for over a decade, Motley Fool Stock Advisor, has tripled the market.* They just revealed what they believe are the ten best stocks for investors to buy right now... and Apple wasn't one of them! That's right -- they think these 10 stocks are even better buys. See the 10 stocks *Stock Advisor returns as of May 1, 2023 Parkev Tatevosian, CFA has positions in Apple. The Motley Fool has positions in and recommends Apple. The Motley Fool has a disclosure policy. Parkev Tatevosian is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through his link, he will earn some extra money that supports his channel. His opinions remain his own and are unaffected by The Motley Fool. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Invest Like Warren Buffett With These 3 Stocks Warren Buffett, also commonly called the Oracle of Omaha, is a name that jumps to the forefront of many minds when thinking of the financial world. As we\\u2019re all aware, many mimic his portfolio moves. And just over the weekend, Berkshire Hathaway hosted its annual shareholder meeting, putting the Oracle of Omaha and his go-to man, Charlie Munger, in full focus. With the legendary investing icon making headlines following the meeting, let\\u2019s take a look at three companies that Buffett has placed big bets on. Apple (AAPL) Apple is a long-time favorite of Buffett, reflecting the largest holding of Berkshire. Over the weekend, the icon spoke positively about the iPhone\\u2019s rock-solid status among consumers, a big reason why he believes in the company. Apple\\u2019s quarterly results took the spotlight last week, with the tech titan delivering a positive 5.6% EPS surprise and reporting revenue nearly 2% above expectations. The company also announced a 4% increase to its quarterly cash dividend, payable on May 18th. Image Source: Zacks Investment Research In addition, the company posted solid iPhone results; iPhone revenue throughout the reported quarter totaled $51.3 billion, 4% above the Zacks Consensus Estimate and improving 1.5% from the year-ago period. As we can see from the chart below, the better-than-expected iPhone results snapped a streak of back-to-back negative surprises. Suprise (%) - iPhone Revenue Image Source: Zacks Investment Research Bank of America (BAC) Despite the recent turmoil within banking, Buffett still remains\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0132 (i.e., a 1.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0132 = 7.5579, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013231, "expected_loss": 0.013231, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240122_0873", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-01-22", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0140, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0019, std=0.0084, worst_day=-0.0180\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0140 (i.e., a 1.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0140 = 7.1650, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013957, "expected_loss": 0.013957, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240829_0874", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EFA"], "decision_date": "2024-08-29", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0240, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0005, std=0.0096, worst_day=-0.0269\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:US [...TRUNCATED...] it basis through July 11, 2025 . 100,110 shares were sold under the plan prior to termination. 40 Item 6. Exhibits Incorporated by Reference Exhibit No.  Exhibit Description Schedule/Form Exhibit Filing Date 3.1 Amendment to Restated Certificate of Incorporation of NVIDIA Corporation 8-K 3.1 6/7/2024 10.1+* Amended and Restated 2007 Equity Incentive Plan 10.2+* Amended and Restated 2012 Employee Stock Purchase Plan 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: August 28, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EFA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0240 (i.e., a 2.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0240 = 4.1616, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024029, "expected_loss": 0.024029, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20230207_0876", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2023-02-07", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0204, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0002, std=0.0086, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-06] [\"A Rare Earnings Miss Couldn\\u2019t Stop Apple Stock (NASDAQ:AAPL) Shares of Apple (NASDAQ:AAPL) are fresh off a quarterly earnings miss, with sales slipping 5% year-over-year, marking the worst quarterly top-line decline in years. Still, Apple stock was resilient following the disappointing number, closing off Friday's session up 2.4% in a bloody day for tech stocks. I remain bullish as Apple stock shrugs off its forgettable quarter and moves on from headwinds that are bound to fade in time. The recent round of quarterly results themselves was nothing to write home about (weakness was broadly spread across categories). It was likely the words of management that helped soothed investor nerves, helping Apple stock outperform some FAANG rivals that also reported the previous day. The company didn't give formal guidance for Fiscal 2023 due to macro uncertainty. It's noteworthy that the words \\\"macro headwinds\\\" were used quite a bit throughout the conference call. In any case, I think it's only prudent not to attempt to provide any sort of concrete guidance with recession headwinds up ahead. Despite the lack of guidance, management didn't leave investors in the dark. CEO Tim Cook called for year-over-year sales growth to be \\\"similar to the December quarter.\\\" Such words, I believe, set the bar quite low for the coming quarter and could set the stage to impress. He also stated that \\\"from a supply chain point of view, we're now at a point where production is what we need it to be.\\\" That alone was likely enough to help Apple investors breathe a sigh of relief. Apple: The Worst of the Production Issues May Have Passed My takeaway from Cook's comments was that the worst of production headwinds may already be in the rearview mirror. Indeed, the next quarter could see iPhone revenue growth in the red. However, the second half could see Apple make up for lost time as production gets up to full speed while Apple users finally look to upgrade. Indeed, Apple can afford to have some sizeable supply-side hiccups without losing too much business. At the end of the day, customer loyalty is unparalleled, with many Apple users that will opt not to switch to a competing product, even if it means having to endure longer wait times. Lockdowns in China have weighed heavily on operations. Still, I am confident that Cook can promptly bring production back in order. The man is an operational genius who's effectively ironed out supply-chain wrinkles in the past. Once Apple moves past the current barrage of headwinds, it'll likely be right back to gaining meaningful market share in the smartphone market again. Further, amping up efforts to expand into India, a market where Apple is reportedly enjoying double-digit growth, could help fuel such market gains. Apple's Rough Quarter is Easy to Forgive There's no question that Apple was up against it going into what many expected would be a rough quarter. Going into the quarter, estimates were muted, thanks in part to manufact\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0204 (i.e., a 2.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0204 = 4.9096, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020368, "expected_loss": 0.020368, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230906_0877", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2023-09-06", "context_summary": "IYR: 60-day history, VaR(99%)=-0.0177, max drawdown threshold=10%.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=-0.0000, std=0.0086, worst_day=-0.0220\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IYR, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0177 (i.e., a 1.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0177 = 5.6627, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017659, "expected_loss": 0.017659, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231012_0879", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-10-12", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0426, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0150, worst_day=-0.0575\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-11] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0426 (i.e., a 4.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0426 = 2.3495, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042561, "expected_loss": 0.042561, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230823_0880", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2023-08-23", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0081, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0006, std=0.0048, worst_day=-0.0085\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-22] [\"Apple\\u2019s Buyback Blunder: 3 Reasons It\\u2019s Not a Win for AAPL Shareholders InvestorPlace - Stock Market News, Stock Advice & Trading Tips If there\\u2019s one thing that feels like Christmas to Warren Buffett is when Apple (NASDAQ:AAPL) repurchases AAPL stock. After all, the more Apple stock the iPhone maker buys back, the more significant percentage of Apple Berkshire Hathaway (NYSE:BRK.B) owns. In Berkshire\\u2019s 2021 shareholder letter, Buffett mentions that his company spent no money to increase its ownership stake to 5.5% from 5.39% in 2020. Share repurchases by Apple in 2021 added $1.1 billion in earnings controlled by Berkshire\\u2019s investment. \\u201cIt\\u2019s important to understand that only dividends from Apple are counted in the GAAP earnings Berkshire reports \\u2013 and last year, Apple paid us $785 million of those. Yet our \\u2018share\\u2019 of Apple\\u2019s earnings amounted to a staggering $5.6 billion,\\u201d Berkshire\\u2019s 2021 shareholder letter stated. \\u201cMuch of what the company retained was used to repurchase Apple shares, an act we applaud.\\u201d Warren Buffett might like the Apple buybacks, but the average investor has three reasons to consider why it\\u2019s not a win for regular AAPL stock investors. It Significantly Overpaid for AAPL Stock Source: Shutterstock Apple has spent more than $500 billion in share repurchases since 2012. The company had 929.4 million shares as of Oct. 14, 2011. On Oct. 14, 2023, it had 15.91 billion shares. Apple\\u2019s stock has split on two occasions over this period \\u2014 a 7-for-1 split on June 9, 2014, and a 4-for-1 split on Aug. 28, 2020 \\u2014 which increased the share count. Considering the two splits, it reduced its share count by 39% [929.4M x 7 x 4 minus 15.91B divided by 26.02B]. That seems like a great deal for Apple shareholders. Have you ever considered what it could have paid for these shares? In fiscal 2022, the company repurchased $90.2 billion of its stock at an average price of $158.52. It is the most repurchased in a single year in the company\\u2019s history. Based on its current share price, it has a 10.1% return on its investment. In the 12 months between Sept. 22, 2021, and Sept. 23, 2022, Apple\\u2019s high was $182.94 in January 2022, while its low was $129.04 in June 2022. The average of the high and low during the year was $155.99. It paid $2.53 more per share than the average. Conservatively, that\\u2019s over $1 billion too much. I would bet dollars to donuts; it\\u2019s done this every year since 2012. Reinvestment of Funds Used Could Have Developed a New Killer Product Source: Vit-Mar/Shutterstock Despite the possibility of a virtual reality (VR) headset and driverless car, the iPhone remains Apple\\u2019s key product and revenue generator. ZDNet reminded its readers in September 2022 that only 11.2 million VR headsets were shipped in 2021 compared to 1.3 billion smartphones. That\\u2019s 116x as many. In June this year, AAPL stock launched the Apple Vis\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0081 (i.e., a 0.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0081 = 12.3386, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008105, "expected_loss": 0.008105, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231020_0882", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2023-10-20", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0608, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0031, std=0.0281, worst_day=-0.0715\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0608 (i.e., a 6.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0608 = 1.6451, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060788, "expected_loss": 0.060788, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240909_0884", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-09-09", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0844, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0043, std=0.0432, worst_day=-0.0853\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0844 (i.e., a 8.44% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0844 = 1.1848, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.084405, "expected_loss": 0.084405, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240301_0886", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2024-03-01", "context_summary": "VCIT: 60-day history, VaR(99%)=-0.0081, max drawdown threshold=10%.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=0.0001, std=0.0038, worst_day=-0.0089\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VCIT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0081 (i.e., a 0.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0081 = 12.3954, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008067, "expected_loss": 0.008067, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230706_0887", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-07-06", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0174, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0029, std=0.0109, worst_day=-0.0200\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-07-05] [\"MORNING BID ASIA-Yellen in China By Jamie McGeever July 6 (Reuters) - A look at the day ahead in Asian markets from Jamie McGeever, financial markets columnist. U.S. Treasury Secretary Janet Yellen touches down in Beijing on Thursday for a three-day visit just as trade tensions between the world's two superpowers ratchet up another notch, while a Malaysian interest rate decision tops the region's economic calendar. Australian trade data and Taiwanese inflation figures are on tap too, and equity investors will digest a mixed earnings report from Taiwan's Foxconn2317.TW, a major iPhone assembler for Apple Inc AAPL.O. Asian stocks go into Thursday's session on the defensive, underperforming on Wednesday after figures showed that China's service sector activity expanded at the slowest pace in five months in June. Foxconn's results may help lift the gloom, after the firm on Wednesday forecast a brighter third quarter ahead of peak shopping season at the end of the year. But that is only relative to a near 14% drop in Q2 revenue year-on-year. China remains front and center for investors. U.S.-China trade tensions appear to be intensifying by the day - the latest flare up coming over Beijing's restrictions on exports of some metals - not the best backdrop for Yellen's visit on Thursday. U.S. officials says they expect \\\"candid\\\" discussions, and Washington has said it \\\"firmly\\\" opposes the new export controls on gallium and germanium, which go into producing semiconductors and other electronics. However well - or otherwise - Yellen's visit goes, there will be no quick fix. Former Vice Commerce Minister Wei Jianguo said the controls are \\\"just a start\\\". In Malaysia, meanwhile, the central bank on Thursday is expected to leave key rates unchanged at 3.00% and keep them there for the rest of the year, putting it in line with regional peers in India, South Korea, Indonesia and New Zealand who have already ended their tightening cycles. Headline inflation eased to a one-year low of 2.8% in May, but core inflation moderated only a bit to 3.5%, suggesting Bank Negara Malaysia (BNM) will hold its key rate higher for longer. The central bank delivered a surprise hike in May. Last week, it said it would intervene in the foreign exchange market to stabilize the ringgit to counter what it said were \\\"excessive\\\" recent losses. The ringgit was one of Asia's worst-performing currencies in the first half of the year, losing almost 6% of its value against the dollar. Here are key developments that could provide more direction to markets on Thursday: - U.S. Treasury Secretary Janet Yellen visits China - Australia trade (May) - Taiwan inflation (June) Malaysian interest rates https://tmsnrt.rs/3XBEzYx Asian FX vs U.S. dollar this year https://tmsnrt.rs/3NYLzvp (By Jamie McGeever; Editing by Lisa Shumaker) ((jamie.mcgeever@thomsonreuters.com; Reuters Messaging: jamie.mcgeever.thomsonreuters.com@reuters.net, Twitter: @ReutersJamie)) The views and opinions expressed her\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0174 (i.e., a 1.74% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0174 = 5.7393, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017424, "expected_loss": 0.017424, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20231017_0888", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2023-10-17", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0219, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0019, std=0.0095, worst_day=-0.0229\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-16] [\"US STOCKS-Wall St jumps 1% to kick-start earnings and data-heavy week, megacaps rise By Ankika Biswas and Shashwat Chauhan Oct 16 (Reuters) - Wall Street's main indexes jumped more than 1% on Monday as megacaps rose to kick-start a week packed with corporate earnings and economic data, while investors also monitored the Israel-Hamas conflict. The Dow touched a near four-week high and was on course for its best day in more than two months, while the S&P 500 and the Nasdaq were headed for their best days in nearly two weeks. Megacaps Microsoft MSFT.O, Meta Platforms META.O, Alphabet GOOGL.O and Amazon.com AMZN.O rose between 1% and 2%. Consumer discretionary .SPLRCD and materials .SPLRCM led the gains across major S&P 500 sectors, while utilities .SPLRCU and energy stocks .SPNY lagged behind. \\\"There's a little bit of risk-on sentiment coming from a pretty solid start to their earnings season,\\\" said Ross Mayfield, investment strategy analyst at Baird. \\\"It says that what the economic data is also saying, which is that the economy is stronger than we were giving it credit for at the year's start, certainly not recessionary.\\\" Results from large banks Goldman Sachs GS.N, Bank of America BAC.N, Morgan Stanley MS.N, pharmaceutical giant Johnson & Johnson JNJ.N, EV maker Tesla TSLA.O and video-streaming pioneer Netflix NFLX.O are due this week. Third-quarter earnings for S&P 500 companies are estimated to grow 2.2% year-on-year, LSEG data showed on Friday. Long-dated Treasury yields rose amid increased U.S. government debt issuance while a possible Israeli ground offensive in Gaza has led to uncertainty in the bond market. Investors also await economic data including retail sales for September and the Philly Fed Business Index for October later this week. Latest data showed the NY Fed's \\\"Empire State\\\" index, a gauge of manufacturing activity in New York State, fell to -4.60 in October, against expectations of a drop to -7. The Dow Jones Transport Average index .DJT, seen as an indicator of economic prosperity, was on track for its best day in nearly three months. Investors are focused on Federal Reserve Chair Jerome Powell's comments on Thursday, before Fed officials enter a blackout period starting Oct. 21 ahead of their policy meeting. Philadelphia Fed President Patrick Harker reiterated his view from Friday that the U.S. central bank was likely done with its rate-hike cycle. Among stocks, Apple AAPL.O bucked the trend among its growth peers, dipping 0.1% on a report the company's iPhones were off to a disappointing start in China. Lululemon AthleticaLULU.O added 9.6% as the sportswear apparel maker is set to join the S&P 500 index this week, replacing Activision Blizzard ATVI.O. ModernaMRNA.O reaffirmed its forecast of $6 billion to $8 billion in COVID vaccine sales for the year. The company's shares fell 5.0%. Charles SchwabSCHW.N jumped 4.8% as the brokerage posted a smaller-than-expected drop in quarterly profit. Advancing issues outnumbered \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0219 (i.e., a 2.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0219 = 4.5595, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021932, "expected_loss": 0.021932, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241106_0890", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2024-11-06", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0368, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0016, std=0.0148, worst_day=-0.0427\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PFE 2024-11-04] pfe-20240929 0000078003 12/31 2024 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares pfe:operatingSegment xbrli:pure pfe:facility pfe:patent pfe:treatmentCourse 0000078003 2024-01-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-01-01 2024-09-29 0000078003 pfe:NotesDue20271.000Member 2024-01-01 2024-09-29 0000078003 2024-10-30 0000078003 us-gaap:ProductMember 2024-07-01 2024-09-29 0000078003 us-gaap:ProductMember 2023-07-03 2023-10-01 0000078003 us-gaap:ProductMember 2024-01-01 2024-09-29 0000078003 us-gaap:ProductMember 2023-01-01 2023-10-01 0000078003 2024-07-01 2024-09-29 0000078003 2023-07-03 2023-10-01 0000078003 2023-01-01 2023-10-01 0000078003 us-gaap:RoyaltyMember 2024-07-01 2024-09-29 0000078003 us-gaap:RoyaltyMember 2023-07-03 2023-10-01 0000078003 us-gaap:RoyaltyMember 2024-01-01 2024-09-29 0000078003 us-gaap:RoyaltyMember 2023-01-01 2023-10-01 0000078003 2024-09-29 0000078003 2023-12-31 0000078003 us-gaap:CommonStockMember 2024-06-30 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000078003 us-gaap:TreasuryStockCommonMember 2024-06-30 0000078003 us-gaap:RetainedEarningsMember 2024-06-30 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000078003 us-gaap:ParentMember 2024-06-30 0000078003 us-gaap:NoncontrollingInterestMember 2024-06-30 0000078003 2024-06-30 0000078003 us-gaap:RetainedEarningsMember 2024-07-01 2024-09-29 0000078003 us-gaap:ParentMember 2024-07-01 2024-09-29 0000078003 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-09-29 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-07-01 2024-09-29 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-07-01 2024-09-29 0000078003 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-09-29 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-09-29 0000078003 us-gaap:TreasuryStockCommonMember 2024-09-29 0000078003 us-gaap:RetainedEarningsMember 2024-09-29 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-09-29 0000078003 us-gaap:ParentMember 2024-09-29 0000078003 us-gaap:NoncontrollingInterestMember 2024-09-29 0000078003 us-gaap:CommonStockMember 2023-07-02 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-07-02 0000078003 us-gaap:TreasuryStockCommonMember 2023-07-02 0000078003 us-gaap:RetainedEarningsMember 2023-07-02 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-02 0000078003 us-gaap:ParentMember 2023-07-02 0000078003 us-gaap:NoncontrollingInterestMember 2023-07-02 0000078003 2023-07-02 0000078003 us-gaap:RetainedEarningsMember 2023-07-03 2023-10-01 0000078003 us-gaap:ParentMember 2023-07-03 2023-10-01 0000078003 us-gaap:NoncontrollingInterestMember 2023-07-03 2023-10-01 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-03 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-07-03 2023-10-01 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-07-03 2023-10-01 0000078003 us-gaap:TreasuryStockCommonMember 2023-07-03 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-10-01 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-10-01 0000078003 us-gaap:TreasuryStockCommonMember 2023-10-01 0000078003 us-gaap:RetainedEarningsMember 2023-10-01 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-10-01 0000078003 us-gaap:ParentMember 2023-10-01 0000078003 us-gaap:NoncontrollingInterestMember 2023-10-01 0000078003 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-12-31 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000078003 us-gaap:TreasuryStockCommonMember 2023-12-31 0000078003 us-gaap:RetainedEarningsMember 2023-12-31 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000078003 us-gaap:ParentMember 2023-12-31 0000078003 us-gaap:NoncontrollingInterestMember 2023-12-31 0000078003 us-gaap:RetainedEarningsMember 2024-01-01 2024-09-29 0000078003 us-gaap:ParentMember 2024-01-01 2024-09-29 0000078003 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-09-29 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2024-01-01 2024-09-29 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-09-29 0000078003 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-29 0000078003 us-gaap:CommonStockMember 2022-12-31 0000078003 us-gaap:AdditionalPaidInCapitalMember 2022-12-31 0000078003 us-gaap:TreasuryStockCommonMember 2022-12-31 0000078003 us-gaap:RetainedEarningsMember 2022-12-31 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-12-31 0000078003 us-gaap:ParentMember 2022-12-31 0000078003 us-gaap:NoncontrollingInterestMember 2022-12-31 0000078003 2022-12-31 0000078003 us-gaap:RetainedEarningsMember 2023-01-01 2023-10-01 0000078003 us-gaap:ParentMember 2023-01-01 2023-10-01 0000078003 us-gaap:NoncontrollingInterestMember 2023-01-01 2023-10-01 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-01 2023-10-01 0000078003 us-gaap:CommonStockMember 2023-01-01 2023-10-01 0000078003 us-gaap:AdditionalPaidInCapitalMember 2023-01-01 2023-10-01 0000078003 us-gaap:TreasuryStockCommonMember 2023-01-01 2023-10-01 0000078003 us-gaap:AccountsReceivableMember 2024-09-29 0000078003 us-gaap:AccountsReceivableMember 2023-12-31 0000078003 us-gaap:OtherCurrentLiabilitiesMember 2024-09-29 0000078003 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0000078003 us-gaap:OtherNoncurrentLiabilitiesMember 2024-09-29 0000078003 us-gaap:OtherNoncurrentLiabilitiesMember 2023-12-31 0000078003 pfe:SeagenMember 2023-12-14 0000078003 pfe:SeagenMember 2023-12-14 2023-12-14 0000078003 pfe:SeagenMember 2024-01-01 2024-09-29 0000078003 pfe:SeagenMember 2024-09-29 0000078003 pfe:SeagenMember pfe:DevelopedTechnologyRightsAndOtherIntangibleAssetsMember 2023-12-14 0000078003 pfe:SeagenMember pfe:DevelopedTechnologyRightsAndOtherIntangibleAssetsMember 2024-01-01 2024-09-29 0000078003 pfe:SeagenMe [...TRUNCATED...] 2024 14,581  $ 27.73  —  $ 3,292,882,444  July 29 through August 25, 2024 22,257  $ 30.44  —  $ 3,292,882,444  August 26 through September 29, 2024 57,730  $ 29.02  —  $ 3,292,882,444  Total 94,568  $ 29.16  —  (a) Represents (i) 91,700 shares of common stock surrendered to the Company to satisfy tax withholding obligations in connection with the vesting of awards under our long-term incentive programs and (ii) the open market purchase by the trustee of 2,868 shares of common stock in connection with the reinvestment of dividends paid on common stock held in trust for employees who deferred receipt of performance share awards. (b) See the Analysis of Financial Condition, Liquidity, Capital Resources and Market Risk—Capital Allocation Framework section within MD&A of this Form 10-Q and Note 12 in our 2023 Form 10-K. ITEM 5. OTHER INFORMATION During the three months ended September 29, 2024, none of our directors or officers adopted or terminated a “Rule 10b5-1 trading arrangement” or “non-Rule 10b5-1 trading arrangement,” as each term is defined in Item 408 of Regulation S-K. 60 ITEM 6. EXHIBITS   Exhibit 31.1 Certification by the Chief Executive Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 31.2 Certification by the Chief Financial Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.1 Certification by the Chief Executive Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.2 Certification by the Chief Financial Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 101:     EX-101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document.   EX-101.SCH EX-101.CAL EX-101.LAB EX-101.PRE EX-101.DEF   Inline XBRL Taxonomy Extension Schema Inline XBRL Taxonomy Extension Calculation Linkbase Inline XBRL Taxonomy Extension Label Linkbase Inline XBRL Taxonomy Extension Presentation Linkbase Inline XBRL Taxonomy Extension Definition Document Exhibit 104 Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   Pfizer Inc.   (Registrant)         Dated: November 4, 2024 /s/ Jennifer B. Damico   Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) 61\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0368 (i.e., a 3.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0368 = 2.7202, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.036762, "expected_loss": 0.036762, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240506_0892", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-05-06", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1347, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0058, std=0.0477, worst_day=-0.1455\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7425", "answer_numeric": 0.7425, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1347 (i.e., a 13.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1347 = 0.7425, capped at 1.0.\nMaximum position size = 0.7425 (74.2% of portfolio).", "metadata": {"var_99": -0.134679, "expected_loss": 0.134679, "max_drawdown_threshold": 0.1, "position_size": 0.7425, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230519_0894", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-05-19", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0698, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0028, std=0.0275, worst_day=-0.0870\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-18] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0698 (i.e., a 6.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0698 = 1.4322, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069823, "expected_loss": 0.069823, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231018_0896", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-10-18", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0329, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0010, std=0.0161, worst_day=-0.0387\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-17] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0329 (i.e., a 3.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0329 = 3.0419, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032874, "expected_loss": 0.032874, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241001_0898", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2024-10-01", "context_summary": "EMB: 60-day history, VaR(99%)=-0.0091, max drawdown threshold=10%.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0010, std=0.0039, worst_day=-0.0102\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EMB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0091 (i.e., a 0.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0091 = 11.0071, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.009085, "expected_loss": 0.009085, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230529_0899", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2023-05-29", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0213, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0008, std=0.0110, worst_day=-0.0216\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-05-26] [\"Alphabet CEO Sundar Pichai Commits to \\\"AI Pact\\\": What Does This Really Mean? The world of artificial intelligence (AI) is moving at a breakneck speed, and top corporate and political leaders are trying to safely guide its evolution. Alphabet (NASDAQ: GOOG) (NASDAQ: GOOGL) CEO Sundar Pichai met with European Commissioner for the internal market Thierry Breton on Wednesday to discuss the progression of AI and map out possible actions to help ensure the emerging technology doesn't get out of hand. In the meeting, Pichai promised that his company would join an \\\"AI pact\\\" and collaborate with other players in the artificial intelligence space on a volunteer basis to shape and abide by guidelines for tech development. But while there's seemingly a lot to like about the prospect of guardrails being put on AI, it's not clear that voluntary pacts or even strict laws will be able to address many of the potential problems that could arise. Could an AI pact help stave off potential disasters? While detailed specifics of what rules and guidelines members of an AI pact would be adhering to haven't been made available, Pichai's discussion with other members of the European Commission suggest that privacy standards and fighting misinformation could be key focuses. The rapid progression for artificial intelligence tech over the last year is unprecedented, and continued advances could be unwieldy. Because legislative bodies can be slow to act and laws vary between territories, it could be important for technology leaders to attempt to establish some kind of presiding framework for artificial intelligence initiatives. Taking a proactive approach to the problems and questions raised by incredible leaps forward for artificial intelligence could help minimize the possibility of disastrous outcomes stemming from the tech. The AI pact mentioned by Pichai at the meeting with Breton seems to be a step in this direction. But there's a risk that rules surrounding AI might not amount to much. For one, it's possible that voluntary AI guidelines and restrictions will be followed very loosely or only in the most nominal senses. It's also possible that those who don't abide by rules for the artificial intelligence project, whether self-imposed or through regulations, could actually gain significant competitive advantages. Controlling AI could be incredibly difficult The European Parliament is currently finalizing a new set of rules and restrictions that will govern AI technologies. The EU AI Act isn't officially law yet, but it's seemingly headed in that direction and could be a landmark response that plays a big role in the tech's evolution in Europe. But it might not be enough, and it may have unintended consequences. Developing ways to work around restrictions could be incentivized by the proposed regulations, and the speed at which AI tech has been progressing will make it difficult for regulators to keep up. Additionally, there are already signs that influential player\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VLUE, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0213 (i.e., a 2.13% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0213 = 4.6961, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021294, "expected_loss": 0.021294, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240627_0901", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SHY"], "decision_date": "2024-06-27", "context_summary": "SHY: 60-day history, VaR(99%)=-0.0024, max drawdown threshold=10%.", "question": "Asset: SHY\nDaily returns (past 60 days): mean=0.0002, std=0.0010, worst_day=-0.0024\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SHY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0024 (i.e., a 0.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0024 = 41.0549, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.002436, "expected_loss": 0.002436, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230308_0903", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2023-03-08", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1009, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0082, std=0.0660, worst_day=-0.1182\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-07] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9913", "answer_numeric": 0.9913, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1009 (i.e., a 10.09% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1009 = 0.9913, capped at 1.0.\nMaximum position size = 0.9913 (99.1% of portfolio).", "metadata": {"var_99": -0.100873, "expected_loss": 0.100873, "max_drawdown_threshold": 0.1, "position_size": 0.9913, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230125_0905", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-01-25", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0341, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0011, std=0.0156, worst_day=-0.0385\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-24] [\"Mixed Reality, Digital Dust and Other Buzzwords You\\u2019ll Need to Know in 2023 V ocabularies can change fast in the worlds of business and technology. A year ago, both of those groups were borderline obsessed with wallstreetbets, the reddit community that was driving meme stocks. Today, it\\u2019s rarely whispered, beyond a sad shake of the head. The evolution of people\\u2019s language continues to occur at a staggering pace. And with the dawning of a new year, new buzzwords are beginning to emerge as well. Staying current on all of the new terms can be a challenge, so here\\u2019s a rundown of the big ones that are popping up these days. Some you might know. Others you\\u2019ll hear slipped into a conversation in the coming months. Here\\u2019s a chance to get ahead of the curve. Mixed Reality: Virtual reality hasn\\u2019t lit up the tech world like its advocates had hoped. Augmented reality is still in its infant stages. Now eyes are turning to mixed reality (XR), which lets you use real-world objects to interact with digital ones. Expect to hear a lot more about it when Apple (AAPL) finally unveils its VR/AR/XR headset, which is expected to happen later this year. Digital Dust: Every action you take in the online world leaves traces. Those could be text, photos, audio files or something else. That\\u2019s known as digital dust. And more and more smart devices are leaving a trail of it these days, including your preferences and behaviors. Proximity bias: Work-from-home holdouts could be doing more damage to their careers than they realize. Proximity bias is the tendency for employers to give preferential treatment or show favoritism to the employees physically closest to them. It's a very real threat. A 2021 survey by the Society for Human Resource Management (SHRM) spoke with over 800 supervisors, with two-thirds who oversaw remote workers saying they believed remote workers were more replaceable than onsite workers. Overemployment: Can\\u2019t pay the bills with one job? More and more people are adding a side hustle or even a second full time job to their plates (And remote working has made it easier for some people to do so). It\\u2019s called overemployment. And some people have managed to be \\u2018overemployed\\u2019 but still just work a 40-hour week. Career cushioning: Some workers, concerned that their positions could be eliminated in the coming months, are focusing less on getting things done and more on adding skills to their resumes, which would make them more attractive to companies if they have to look for a new gig. LinkedIn says 365 million people have added skills to their profiles over the last 12 months, up 43% from last year. Polycrisis: Everything old is new again, even our problems. Polycrisis is the latest term for the convergence of those problems all at once\\u2014and we\\u2019re in one now. We\\u2019ve got wars going on, a pandemic that\\u2019s still impacting the world, economic crises and more. The World Economic Forum describ\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0341 (i.e., a 3.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0341 = 2.9323, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034103, "expected_loss": 0.034103, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240524_0907", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["PALL"], "decision_date": "2024-05-24", "context_summary": "PALL: 60-day history, VaR(99%)=-0.0393, max drawdown threshold=10%.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=0.0004, std=0.0214, worst_day=-0.0421\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PALL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0393 (i.e., a 3.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0393 = 2.5459, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.039278, "expected_loss": 0.039278, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240729_0909", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2024-07-29", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0583, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0244, worst_day=-0.0724\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0583 (i.e., a 5.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0583 = 1.7148, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.058315, "expected_loss": 0.058315, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231004_0911", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-10-04", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0426, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0145, worst_day=-0.0575\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-03] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0426 (i.e., a 4.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0426 = 2.3495, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042561, "expected_loss": 0.042561, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230901_0912", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2023-09-01", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0480, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0026, std=0.0182, worst_day=-0.0669\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-31] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0480 (i.e., a 4.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0480 = 2.0837, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.047991, "expected_loss": 0.047991, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231123_0914", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2023-11-23", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.0976, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0020, std=0.0588, worst_day=-0.1157\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-22] [\"AAPL Factor-Based Stock Analysis Below is Validea's guru fundamental report for APPLE INC (AAPL). Of the 22 guru strategies we follow, AAPL rates highest using our Twin Momentum Investor model based on the published strategy of Dashan Huang. This momentum model looks for a combination of fundamental momentum and price momentum. APPLE INC (AAPL) is a large-cap growth stock in the Communications Equipment industry. The rating using this strategy is 94% based on the firm\\u2019s underlying fundamentals and the stock\\u2019s valuation. A score of 80% or above typically indicates that the strategy has some interest in the stock and a score above 90% typically indicates strong interest. The following table summarizes whether the stock meets each of this strategy's tests. Not all criteria in the below table receive equal weighting or are independent, but the table provides a brief overview of the strong and weak points of the security in the context of the strategy's criteria. FUNDAMENTAL MOMENTUM: PASS TWELVE MINUS ONE MOMENTUM: PASS FINAL RANK: PASS Detailed Analysis of APPLE INC AAPL Guru Analysis AAPL Fundamental Analysis More Information on Dashan Huang Dashan Huang Portfolio About Dashan Huang: Dashan Huang is an Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University. His paper \\\"Twin Momentum\\\" looked at combining traditional price momentum with improving fundamentals to generate market outperformance. In the paper, he identified seven fundamental variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets and net payout ratio) that he combined into a single fundamental momentum measure. He showed that stocks in the top 20% of the universe according to that measure outperformed the market going forward. When he combined that measure with price momentum, he was able to double its outperformance. Additional Research Links Top NASDAQ 100 Stocks Top Technology Stocks Top Large-Cap Growth Stocks High Momentum Stocks High Insider Ownership Stocks About Validea: Validea is aninvestment researchservice that follows the published strategies of investment legends. Validea offers both stock analysis and model portfolios based on gurus who have outperformed the market over the long-term, including Warren Buffett, Benjamin Graham, Peter Lynch and Martin Zweig. For more information about Validea, click here The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Actor Jamie Foxx accused of sexual abuse in New York lawsuit By Dawn Chmielewski and Steve Gorman Nov 22 (Reuters) - Oscar-winning actor Jamie Foxx was accused of sexual assault in a lawsuit filed in New York City on Wednesday that alleges he groped a woman at a rooftop bar and restaurant in Manhattan in August 2015. The plaintiff, identified in the complaint only as Jan\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0976 (i.e., a 9.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0976 = 1.0247, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.097587, "expected_loss": 0.097587, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240517_0915", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VEA"], "decision_date": "2024-05-17", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0161, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0010, std=0.0069, worst_day=-0.0176\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0161 (i.e., a 1.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0161 = 6.2010, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016126, "expected_loss": 0.016126, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230705_0917", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2023-07-05", "context_summary": "SCHH: 60-day history, VaR(99%)=-0.0228, max drawdown threshold=10%.", "question": "Asset: SCHH\nDaily returns (past 60 days): mean=0.0006, std=0.0108, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SCHH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0228 (i.e., a 2.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0228 = 4.3800, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022831, "expected_loss": 0.022831, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231225_0919", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2023-12-25", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0224, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0023, std=0.0136, worst_day=-0.0237\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VNQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0224 (i.e., a 2.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0224 = 4.4651, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022396, "expected_loss": 0.022396, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20240117_0921", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2024-01-17", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0155, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0017, std=0.0079, worst_day=-0.0163\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0155 (i.e., a 1.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0155 = 6.4399, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015528, "expected_loss": 0.015528, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240529_0923", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-05-29", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1264, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0425, worst_day=-0.1363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7911", "answer_numeric": 0.7911, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1264 (i.e., a 12.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1264 = 0.7911, capped at 1.0.\nMaximum position size = 0.7911 (79.1% of portfolio).", "metadata": {"var_99": -0.126408, "expected_loss": 0.126408, "max_drawdown_threshold": 0.1, "position_size": 0.7911, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230327_0925", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2023-03-27", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0754, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0385, worst_day=-0.0799\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-26] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0754 (i.e., a 7.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0754 = 1.3260, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.075412, "expected_loss": 0.075412, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230830_0927", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["GLD"], "decision_date": "2023-08-30", "context_summary": "GLD: 60-day history, VaR(99%)=-0.0126, max drawdown threshold=10%.", "question": "Asset: GLD\nDaily returns (past 60 days): mean=0.0001, std=0.0058, worst_day=-0.0157\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to GLD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0126 (i.e., a 1.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0126 = 7.9636, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012557, "expected_loss": 0.012557, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230112_0929", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-01-12", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0845, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0003, std=0.0332, worst_day=-0.0936\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-11] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0845 (i.e., a 8.45% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0845 = 1.1831, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.084524, "expected_loss": 0.084524, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240611_0931", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2024-06-11", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0181, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0001, std=0.0076, worst_day=-0.0183\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0181 (i.e., a 1.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0181 = 5.5396, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018052, "expected_loss": 0.018052, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240912_0933", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2024-09-12", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0325, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0010, std=0.0135, worst_day=-0.0325\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0325 (i.e., a 3.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0325 = 3.0761, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032508, "expected_loss": 0.032508, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241126_0935", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-11-26", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0694, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0159, std=0.0596, worst_day=-0.0757\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0694 (i.e., a 6.94% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0694 = 1.4416, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069367, "expected_loss": 0.069367, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241128_0937", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-11-28", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0772, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0066, std=0.0533, worst_day=-0.0971\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0772 (i.e., a 7.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0772 = 1.2954, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.077198, "expected_loss": 0.077198, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230103_0939", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-01-03", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1462, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0067, std=0.0509, worst_day=-0.1912\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-02] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6840", "answer_numeric": 0.684, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1462 (i.e., a 14.62% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1462 = 0.6840, capped at 1.0.\nMaximum position size = 0.6840 (68.4% of portfolio).", "metadata": {"var_99": -0.146204, "expected_loss": 0.146204, "max_drawdown_threshold": 0.1, "position_size": 0.684, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230417_0941", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2023-04-17", "context_summary": "VCIT: 60-day history, VaR(99%)=-0.0100, max drawdown threshold=10%.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=0.0001, std=0.0047, worst_day=-0.0100\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VCIT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0100 (i.e., a 1.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0100 = 10.0404, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.00996, "expected_loss": 0.00996, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20241219_0943", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-12-19", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0770, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0051, std=0.0407, worst_day=-0.0817\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0770 (i.e., a 7.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0770 = 1.2986, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.077006, "expected_loss": 0.077006, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240226_0945", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2024-02-26", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0600, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0032, std=0.0234, worst_day=-0.0758\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0600 (i.e., a 6.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0600 = 1.6658, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060032, "expected_loss": 0.060032, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231114_0947", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-11-14", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0519, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0094, std=0.0337, worst_day=-0.0560\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-11-13] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0519 (i.e., a 5.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0519 = 1.9259, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.051923, "expected_loss": 0.051923, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231101_0948", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2023-11-01", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0165, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=-0.0009, std=0.0091, worst_day=-0.0176\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-31] [\"The Zacks Analyst Blog Highlights Apple, McKesson, Emerson Electric and Bae Systems For Immediate Release Chicago, IL \\u2013 October 31, 2023 \\u2013 Zacks.com announces the list of stocks featured in the Analyst Blog. Every day the Zacks Equity Research analysts discuss the latest news and events impacting stocks and the financial markets. Stocks recently featured in the blog include: Apple AAPL, McKesson MCK, Emerson Electric EMR and Bae Systems BAESY. Here are highlights from Monday\\u2019s Analyst Blog: Apple, Bitcoin and the FOMC: Global Week Ahead Across the Global Week Ahead, central bankers keep stock traders on alert: \\u00b7 The Bank of Japan (BoJ) reports Tuesday \\u00b7 The U.S. Federal Reserve reports Wednesday, and \\u00b7 The Bank of England (BoE) reports Thursday Out AMC on Thursday, Apple tops the bill for earnings, on both sides of the Atlantic. On Friday at 8:30 am ET, we get the OCT U.S. nonfarm jobs report. Next are Reuters' five world market themes, reordered for equity traders\\u2014 (1) This week will be a core S&P500 earnings season week. Apple headlines another busy week of U.S. corporate earnings, with the iPhone maker reporting AMC on Thursday. Shares of Apple, the world's largest company by market value, have helped drive equity indexes higher this year, along with shares of other mega-cap U.S. tech and growth companies. But the stock has pulled back sharply since late July, when the S&P500 hit its high for 2023. Results already in from mega-caps have prompted a mixed reaction, with shares of Alphabet and Tesla slumping after their respective reports. Consumers' spending habits will also be on display. Other companies set to report include: \\u00b7 Caterpillar and Pfizer on Tuesday \\u00b7 Mondelez on Wednesday, and \\u00b7 Starbucks and Eli Lilly on Thursday (2) Bitcoin prices are rising, rising... and then? Bitcoin has had a stellar ride recently, with traders getting excited about the possibility that the U.S. Securities and Exchange Commission (SEC) could approve an application for a spot bitcoin ETF. Earlier this month, bitcoin jumped sharply on a false report that BlackRock's ETF application had been approved. Last week, a listing of BlackRock's planned ETF on a clearing house website sent speculators into a frenzy \\u2014 even after the clearing house said this was just standard practice for pending applications rather than a sign of any regulatory approval. Still, the cryptocurrency is trading at around half the $69,000 peak it reached in November 2021. Meanwhile, the fraud trial of Sam Bankman-Fried, whose crypto firm FTX collapsed a year ago, is captivating crypto watchers around the globe. (3) On Wednesday, a two-day U.S. Federal Reserve meeting breaks up. A bruised U.S. stock market will turn its attention to the Fed monetary policy meeting on Wednesday, with investors eager to hear policymakers' views on the state of the economy and the outlook for interest rates. Futures tied to the main policy rate show most tr\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0165 (i.e., a 1.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0165 = 6.0494, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016531, "expected_loss": 0.016531, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240119_0950", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2024-01-19", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0133, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0019, std=0.0072, worst_day=-0.0140\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2024-01-09] [\"Is iShares Semiconductor ETF (SOXX) a Strong ETF Right Now? The iShares Semiconductor ETF (SOXX) was launched on 07/10/2001, and is a smart beta exchange traded fund designed to offer broad exposure to the Technology ETFs category of the market. What Are Smart Beta ETFs? The ETF industry has long been dominated by products based on market cap weighted indexes, a strategy created to reflect the market or a particular market segment. Market cap weighted indexes offer a low-cost, convenient, and transparent way of replicating market returns, and are a good option for investors who believe in market efficiency. However, some investors believe in the possibility of beating the market through exceptional stock selection, and choose a different type of fund that tracks non-cap weighted strategies: smart beta. Based on specific fundamental characteristics, or a combination of such, these indexes attempt to pick stocks that have a better chance of risk-return performance. The smart beta space gives investors many different choices, from equal-weighting, one of the simplest strategies, to more complicated ones like fundamental and volatility/momentum based weighting. However, not all of these methodologies have been able to deliver remarkable returns. Fund Sponsor & Index The fund is managed by Blackrock, and has been able to amass over $9.93 billion, which makes it one of the largest ETFs in the Technology ETFs. SOXX, before fees and expenses, seeks to match the performance of the PHLX SOX Semiconductor Sector Index. The ICE Semiconductor Index measures the performance of U.S. traded securities of companies engaged in the semiconductor business. Cost & Other Expenses Investors should also pay attention to an ETF's expense ratio. Lower cost products will produce better results than those with a higher cost, assuming all other metrics remain the same. Operating expenses on an annual basis are 0.35% for SOXX, making it one of the least expensive products in the space. It's 12-month trailing dividend yield comes in at 0.81%. Sector Exposure and Top Holdings Even though ETFs offer diversified exposure that minimizes single stock risk, investors should also look at the actual holdings inside the fund. Luckily, most ETFs are very transparent products that disclose their holdings on a daily basis. Representing 100% of the portfolio, the fund has heaviest allocation to the Information Technology sector. Taking into account individual holdings, Advanced Micro Devices Inc (AMD) accounts for about 9.48% of the fund's total assets, followed by Broadcom Inc (AVGO) and Intel Corporation Corp (INTC). SOXX's top 10 holdings account for about 59.63% of its total assets under management. Performance and Risk So far this year, SOXX has lost about -2.88%, and was up about 55.09% in the last one year (as of 01/09/2024). During this past 52-week period, the fund has traded between $373.83 and $581.45. The ETF has a beta of 1.37 and standard deviation of 34.63% for the trailin\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ACWI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0133 (i.e., a 1.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0133 = 7.5103, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013315, "expected_loss": 0.013315, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240509_0952", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2024-05-09", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0340, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0009, std=0.0132, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XHB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0340 (i.e., a 3.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0340 = 2.9433, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033976, "expected_loss": 0.033976, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230320_0954", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2023-03-20", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0803, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0047, std=0.0462, worst_day=-0.0851\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0803 (i.e., a 8.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0803 = 1.2456, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080285, "expected_loss": 0.080285, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230809_0956", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2023-08-09", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0936, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0003, std=0.0515, worst_day=-0.1180\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-08-08] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0936 (i.e., a 9.36% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0936 = 1.0683, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.093603, "expected_loss": 0.093603, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240215_0958", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2024-02-15", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0324, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0021, std=0.0188, worst_day=-0.0334\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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amzn:VendorAccountsReceivableMember 2023-12-31 0001018724 us-gaap:LoansReceivableMember 2022-12-31 0001018724 us-gaap:LoansReceivableMember 2023-12-31 00 [...TRUNCATED...] tents 32.2 Certification of Brian T. Olsavsky, Senior Vice President and Chief Financial Officer of Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy. 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2023, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 77 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 1, 2024.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 1, 2024.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Judith A. McGrath Judith A. McGrath Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 78\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to FXI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0324 (i.e., a 3.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0324 = 3.0837, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032429, "expected_loss": 0.032429, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20241122_0959", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2024-11-22", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0201, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0011, std=0.0079, worst_day=-0.0205\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IVV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0201 (i.e., a 2.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0201 = 4.9786, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020086, "expected_loss": 0.020086, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240607_0960", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2024-06-07", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1230, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0036, std=0.0356, worst_day=-0.1409\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8130", "answer_numeric": 0.813, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1230 (i.e., a 12.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1230 = 0.8130, capped at 1.0.\nMaximum position size = 0.8130 (81.3% of portfolio).", "metadata": {"var_99": -0.123005, "expected_loss": 0.123005, "max_drawdown_threshold": 0.1, "position_size": 0.813, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240918_0961", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-09-18", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0343, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0015, std=0.0156, worst_day=-0.0360\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2023-02-01 2023-04-30 0000104169 us [...TRUNCATED...] acts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 30, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 30, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 30, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0343 (i.e., a 3.43% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0343 = 2.9181, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034269, "expected_loss": 0.034269, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230303_0962", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2023-03-03", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0175, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0014, std=0.0079, worst_day=-0.0185\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-02] [\"Here's Why Microsoft Isn't Sweating a Looming Recession Though nobody can say with certainty whether we'll be entering a recession in 2023, enough signs are pointing that way to cause both people and businesses to begin preparing accordingly. For investors, this could mean rough times ahead for many of their investments. Big tech has had its fair share of humble pie in the past 12 months, and with a looming recession in 2023, it might get worse before it gets better. However, of all big tech companies, none may be more recession-resistant than Microsoft (NASDAQ: MSFT). Microsoft is dividing and conquering One thing differentiating Microsoft from many competitors is just how diverse its revenue streams are. Its ecosystem of products and services all do a good job of pulling in their fair share of the revenue load. Having this many income streams isn't exclusive to Microsoft, but the difference is how spread out the revenue is among them. Of the $52.75 billion Microsoft made in the second quarter of its fiscal 2023, no segment accounted for more than 38%. For perspective, just the iPhone itself accounts for more than half of Apple's revenue, and Google advertising accounts for over 80% of Alphabet's revenue. Having diverse revenue streams ensures the business isn't too affected if one segment is hit hard by economic conditions. For example, spending on gaming may slow during a recession, but luckily, that represents less than 10% of Microsoft's revenue. It's the type of customers that benefit Microsoft Aside from the many different ways Microsoft makes money, what makes it more recession-resistant than its competitors is just who its customers are: other companies. There are countless companies in the world that rely on Microsoft products and services to run their business. Plenty of companies use Windows PCs for daily work. Industries like finance would go into a frenzy without Excel. Cloud services have increasingly become a necessity, especially for companies operating online. It's hard to imagine job recruiting and searching without LinkedIn. The list goes on of ways Microsoft is intertwined with many companies' daily operations. If a recession does occur, there's a good chance that consumers will slow down their spending, especially on consumer discretionary products and services. Microsoft's corporate clients, however, likely won't be going anywhere or drastically decreasing how much they spend with the company. It's easy for a consumer to forgo the latest iPhone when money is tight and the economy is less than ideal; it's much harder for a company to go from using cloud storage back to in-house storage. Services allow for a higher margin Since a lot of Microsoft's revenue comes from its services and software, it's able to operate with a higher gross profit margin than many other big tech companies that rely on hardware sales. Once most software is made, you can ship as much of it as you like without incurring too much extra cost (aside fro\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0175 (i.e., a 1.75% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0175 = 5.6992, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017546, "expected_loss": 0.017546, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240408_0964", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2024-04-08", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0968, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0025, std=0.0444, worst_day=-0.0987\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0968 (i.e., a 9.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0968 = 1.0333, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.096781, "expected_loss": 0.096781, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20241114_0965", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2024-11-14", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0241, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0014, std=0.0122, worst_day=-0.0311\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 000009 [...TRUNCATED...] ATION ISSUER PURCHASES OF EQUITY SECURITIES   Period Total Number of Shares Purchased (*) Average Price Paid per Share Total Number of Shares Purchased as Part of Publicly Announced Program Approximate Dollar Value of Shares that May Yet Be Purchased Under the 2023 Program (*) (Billions of dollars) July 1 - July 31, 2024 7,923,000  $156.56 7,923,000  $56.6 August 1 - August 31, 2024 12,057,000  $146.20 12,057,000  $54.8 September 1 - September 30, 2024 12,229,398  $142.84 12,229,398  $53.1 Total 32,209,398   $147.47 32,209,398   (*) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections A. Nigel Hearne , Executive Vice President, Senior Advisor , entered into a pre-arranged stock trading plan on August 19, 2024 . Mr. Hearne’s plan provides for the potential exercise of vested stock options and the associated sale of up to 60,468 shares of Chevron common stock between November 18, 2024, and February 28, 2025 . The trading plan was entered into during an open insider trading window and is intended to satisfy the affirmative defense of Rule 10b5-1(c) under the Securities Exchange Act of 1934, as amended, and Chevron’s policies regarding transactions in Chevron securities. 44 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 10.1+* Chevron Incentive Plan, amended and restated effective October 2, 2023 (refi l ed to correct formatting in the previo usly filed version) . 10.2+* Chevron Corporation Retirement Restoration Plan, amended and restated effective August 1, 2024. 10.3+* Chevron Corporation ESIP Restoration Plan, amended and restated effective August 1, 2024. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ +     Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 45 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 7, 2024 46\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IWM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0241 (i.e., a 2.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0241 = 4.1561, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024061, "expected_loss": 0.024061, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230914_0966", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2023-09-14", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0185, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=-0.0006, std=0.0082, worst_day=-0.0195\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-13] [\"US presses on with fight against Google's search and advertising clout By Diane Bartz WASHINGTON, Sept 13 (Reuters) - The Justice Department questioned a former Google executive about billion-dollar deals with mobile carriers and others that helped make Google the default search engine, in the second day of a once-in-a-generation antitrust trial on Wednesday. Chris Barton, who was at Google from 2004 to 2011, said the company was quick to see the advantage of people using Google search on handheld devices and early versions of smartphones, spurring dramatic growth in the number of Google executives working on deals to win default status with mobile carriers. Google's clout in search, the government argues, has helped Google, a $1 trillion company, build monopolies in some aspects of online search advertising. Since search is free, Google makes its money through advertising. The government says the Alphabet IncGOOGL.Ounit paid $10 billion annually to wireless companies like AT&T T.N, device makers like Apple AAPL.O and browser makers like Mozilla to fend off rivals and keep its search engine's market share at around 90%. Barton testified that in negotiating revenue-sharing deals with mobile carriers and Android smartphone makers, Google pressed for its search to be the default and to be exclusive. If Microsoft's search engine Bing was the default on an Android phone, Barton said, then users would have a \\\"difficult time finding or changing to Google.\\\" Barton said on his LinkedIn profile that he was responsible for leading Google's partnerships with mobile carriers like Verizon and AT&T, estimating that the deals \\\"drive hundreds of millions in revenue.\\\" Google attorney John Schmidtlein said in opening arguments on Tuesday that the government was wrong to say that Google broke the law to hold onto its massive market share, noting its search engine was wildly popular because of its quality and that the payments were fair compensation for partners. The fight has major implications for Big Tech, which has been accused of buying or strangling small rivals but has defended itself by pointing out that its services are free, as in the case of Google, or inexpensive, as in the case of Amazon.com AMZN.O. Previous major antitrust trials include Microsoft, filed in 1998, and AT&T, filed in 1974. The AT&T breakup in 1982 is credited with paving the way for the modern cell phone industry, while the fight with Microsoft is credited with opening space for Google and others on the internet. The government's first witness Tuesday was Google economist Hal Varian, who was asked about discussions inside the company about the importance of scale and of Google becoming the default on home pages. If Google is found to have broken the law, Judge Amit Mehta, who is deciding the case, will then decide how best to resolve it. He may decide simply to order Google to stop practices he has found to be illegal or he may order Google to sell assets. EXPLAINER-Why is the US su\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VEA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0185 (i.e., a 1.85% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0185 = 5.3949, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018536, "expected_loss": 0.018536, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20230301_0968", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2023-03-01", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0204, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0001, std=0.0096, worst_day=-0.0249\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-28] [\"The Zacks Analyst Blog Highlights Apple, Linde, Marsh & McLennan Companies, GSK and Expedia For Immediate Release Chicago, IL \\u2013 February 28, 2023 \\u2013 Zacks.com announces the list of stocks featured in the Analyst Blog. Every day the Zacks Equity Research analysts discuss the latest news and events impacting stocks and the financial markets. Stocks recently featured in the blog include: Apple Inc. AAPL, Linde plc LIN, Marsh & McLennan Companies, Inc. MMC, GSK plc GSK and Expedia Group, Inc. EXPE. Here are highlights from Monday\\u2019s Analyst Blog: Top Analyst Reports from Apple, Linde and Marsh & McLennan The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc., Linde plc and Marsh & McLennan Companies, Inc. These research reports have been hand-picked from the roughly 70 reports published by our analyst team today. You can see all of today\\u2019s research reports here >>> Shares of Apple have roughly matched the broader market over the past year (-10.4% for Apple vs. -10.9% for the S&P 500 index), but handily outperformed the Zacks Tech sector (down - 19.8%). The Zacks analyst covering Apple expects year-over-year revenue growth to decelerate in the fiscal first quarter compared with the fiscal fourth quarter due to unfavorable forex. Mac revenues are expected to be negatively impacted by forex. Apple expects Mac revenues to decline substantially year over year during the December quarter. Services revenue growth is expected to be negatively impacted by challenging macroeconomic conditions, unfavorable forex, as well as weakness in digital advertising and gaming. Nevertheless, a growing subscriber base in the Services business and a strong liquidity position are key catalysts. (You can read the full research report on Apple here >>>) Linde shares have outperformed the Zacks Chemical - Diversified industry over the past year (+18.6% vs. +10.3%). The company\\u2019s wide range of applications for its industrial gases, Linde is making the world more productive by the day. The company\\u2019s primary products in industrial gases include oxygen, which is used as life support in hospitals. Its process gas, like hydrogen, is being utilized for clean fuels, while its high-purity and specialty gases are employed to manufacture electronics. Linde has long-term contracts with on-site customers backed by minimum purchase requirements, thereby securing stable cashflows. In the profitable industrial gas market, the merger of Praxair and Linde has created an efficient player with considerable size advantages. However, the cost of sales continues to increase, hurting the firm\\u2019s bottom line. The firm has mostly been paying a lower dividend yield than the industry\\u2019s composite stocks over the past two years. (You can read the full research report on Linde here >>>) Marsh & McLennan shares have outperformed the Zacks Insurance - Bro\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ACWI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0204 (i.e., a 2.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0204 = 4.9096, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020368, "expected_loss": 0.020368, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20240709_0970", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2024-07-09", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0760, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0046, std=0.0427, worst_day=-0.0772\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0760 (i.e., a 7.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0760 = 1.3164, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.075963, "expected_loss": 0.075963, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240307_0972", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2024-03-07", "context_summary": "IGOV: 60-day history, VaR(99%)=-0.0134, max drawdown threshold=10%.", "question": "Asset: IGOV\nDaily returns (past 60 days): mean=0.0001, std=0.0057, worst_day=-0.0138\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IGOV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0134 (i.e., a 1.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0134 = 7.4440, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013434, "expected_loss": 0.013434, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20231025_0974", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2023-10-25", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0358, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0217, worst_day=-0.0500\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-10-24] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0358 (i.e., a 3.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0358 = 2.7928, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035807, "expected_loss": 0.035807, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20231206_0975", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2023-12-06", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0695, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0016, std=0.0230, worst_day=-0.1070\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-05] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0695 (i.e., a 6.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0695 = 1.4398, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069453, "expected_loss": 0.069453, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230131_0977", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2023-01-31", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0220, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0008, std=0.0114, worst_day=-0.0251\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-01-30] [\"No Hyperbole: This Really is a Critical Week for Stocks O ne of the dangers for investors of paying attention to financial media, whether it is TV channels such as CNBC or Fox Business, or internet sites that offer commentary and opinion (such as this one), is that it makes you prone to exaggerate the importance of everything that happens. Every writer, presenter, and editor knows that a piece with the words \\u201ccrisis,\\u201d \\u201ccrash,\\u201d or \\u201cboom\\u201d will do better than one that says that nothing much is going to happen, even though nothing much happening is always a far more likely scenario. In the world of financial media, every data release is \\u201ccritical,\\u201d and every stock is \\u201cset to soar\\u201d or \\u201cabout to collapse.\\u201d That is why I am reluctant in some ways to say that this week is \\u201ccritical\\u201d for stocks. I don\\u2019t want to employ the kind of hyperbole that distorts reality, but the more I look at the economic and earnings calendars for the week, the more convinced I am that that is the case. The economic calendar side of that may surprise some people, given that the calendar for this week doesn\\u2019t show any major data until the jobs report on Friday, and even then, unemployment has become a much less significant indicator than it once was. What makes this week so important, however, is not new data but the interpretation of existing data. What really matters right now is how central banks interpret that data. If the actual numbers mattered, the Fed would have started to hike rates a lot sooner than they did, and nobody would have uttered the word \\u201ctransient,\\u201d but that isn\\u2019t what happened. Instead, they looked at employment, price, and consumer spending data that screamed \\u201cinflation!\\u201d and told us that that was misleading, that price rises were driven primarily by supply chain disruptions and would quickly fade away. They delayed raising rates, and inflation is probably worse than it could have been as a result. The data at that time wasn't what mattered; it was the Fed\\u2019s interpretation of that data that drove policy. We are in the same place now in terms of whether to pause or even reverse the rising rate policy. The deliberations of the Fed, the ECB and the Bank of England this week are, in many ways, more important than the numbers they will be deliberating. Then there are earnings. It is a huge week for big tech, with Meta (META), Alphabet (GOOG, GOOGL), Apple (AAPL), and Amazon (AMZN) all reporting on either Wednesday or Thursday. This is always a significant part of earnings season, but especially now. These are the names that led the market lower last year but have bounced as optimism increased this month. They have all talked about a tough start to 2023 and, in most cases, have announced cutbacks and layoffs. If it turns out that pessimism was prompted by a bad Q4, and/or if it continues in terms of their outlook for the rest of the year, the midweek bi\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0220 (i.e., a 2.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0220 = 4.5494, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021981, "expected_loss": 0.021981, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20241205_0979", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-12-05", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1398, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0050, std=0.0610, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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nvda:PubliclyHeldEquitySecuritiesMember 2024-01-28 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasur [...TRUNCATED...] 30, 2024 , Ajay K. Puri , Executive Vice President , Worldwide Field Operations, adopted a Rule 10b5-1 Trading Arrangement for the sale of up to 204,890 shares of our common stock through December 30, 2025 . 40 Item 6. Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan – Global Restricted Stock Unit Grant Notice and Global Restricted Stock Unit Agreement (2024) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 41 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 20, 2024   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 42\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7156", "answer_numeric": 0.7156, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1398 (i.e., a 13.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1398 = 0.7156, capped at 1.0.\nMaximum position size = 0.7156 (71.6% of portfolio).", "metadata": {"var_99": -0.139751, "expected_loss": 0.139751, "max_drawdown_threshold": 0.1, "position_size": 0.7156, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20240528_0981", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-05-28", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.0968, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0019, std=0.0508, worst_day=-0.0994\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0968 (i.e., a 9.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0968 = 1.0328, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.096824, "expected_loss": 0.096824, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20230918_0983", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2023-09-18", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0558, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0069, std=0.0200, worst_day=-0.0684\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-09-17] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0558 (i.e., a 5.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0558 = 1.7912, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.055828, "expected_loss": 0.055828, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240606_0984", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2024-06-06", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0220, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0006, std=0.0110, worst_day=-0.0258\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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2023-03-31 0001364742 us-gaap:EquitySecuritiesMember blk:ConsolidatedVotingRightsEntitiesMember 2024-03-31 0001364742 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2024-03-31 0001364742 us-gaap:EquitySecuritiesMember us-gaap:VariableInterestEntityPrimaryBeneficiaryMember 2024-03-31 0001364742 us-gaap:ForeignExchangeForwardMember 2023-12-31 0001364742 blk:OnePointNineZeroPercentNotesDueTwoThousandThirtyOneMember 2024-03-31 0001364742 blk:EquityFixedIncomeAndMultiAssetMutualFundsMember us-gaap:FairValueMeasurementsRecurringMember 2023-12-31 0001364742 2022-10-01 2022-12-31 0001364742 us-gaap:FairValueMeasurementsRecurringMember us-gaap:PortionAtOtherThanFairValueFairValueDisclosureMember 2024-03-31 0001364742 blk:AlternativeInvestmentsProductsMember us-gaap:InvestmentPerformanceMember 2024-01-01 2024-03-31 0001364742 srt:AmericasMember 2023-12-31 0001364742 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MTUM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0220 (i.e., a 2.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0220 = 4.5524, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021967, "expected_loss": 0.021967, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20240711_0986", "template": "T3", "complexity": 1, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2024-07-11", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1051, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0050, std=0.0457, worst_day=-0.1133\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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blk:InvestmentsRelatedToDeferredCashCompensationPlansMember 2023-12-31 0001364742 us-gaap:CollateralizedLo [...TRUNCATED...] hat the Board of Directors authorized the repurchase of an additional seven million shares under the Company’s existing share repurchase program, for a total of up to approximately 7.9 million shares of BlackRock common stock. 64   Item 6. Exh ibits Exhibit No.   Description       4.1(1)   Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.2(1)   First Supplemental Indenture, dated March 14, 2024, among BlackRock Funding, Inc., BlackRock, Inc. and The Bank of New York Mellon, as trustee.       4.3(1)   Form of Note for the 4.700% Notes due 2029 (included in Exhibit 4.2).       4.4(1)   Form of Note for the 5.000% Notes due 2034 (included in Exhibit 4.2).       4.5(1)   Form of Note for the 5.250% Notes due 2054 (included in Exhibit 4.2).       10.1(2)   Amendment No. 14, dated as of March 12, 2024, by and among BlackRock, Inc., certain of its subsidiaries, Wells Fargo Bank, National Association, as administrative agent, a swingline lender, an issuing lender, L/C agent and a lender, and the banks and other financial institutions referred to therein.       22.1(3)   Subsidiary Issuer of Guaranteed Securities.       31.1   Section 302 Certification of Chief Executive Officer       31.2   Section 302 Certification of Chief Financial Officer       32.1   Section 906 Certification of Chief Executive Officer and Chief Financial Officer       101.INS   Inline XBRL Instance Document – the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document       101.SCH   Inline XBRL Taxonomy Extension Schema with Embedded Linkbases Document       104   Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101)         (1) Incorporated by reference to BlackRock’s Current Report on Form 8-K filed on March 14, 2024. (2) Incorporated by reference to BlackRock's Current Report on Form 8-K filed on March 15, 2024. (3) Incorporated by reference to BlackRock's Registration Statement on Form S-3 (Registration No. 333-278583) filed on April 9, 2024. 65   SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       BLACKROCK, INC.     (Registrant)             By: /s/ Martin S. Small Date: May 7, 2024        Martin S. Small          Senior Managing Director & Chief Financial Officer    (Principal Financial Officer)   66\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ^VIX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9516", "answer_numeric": 0.9516, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1051 (i.e., a 10.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1051 = 0.9516, capped at 1.0.\nMaximum position size = 0.9516 (95.2% of portfolio).", "metadata": {"var_99": -0.105088, "expected_loss": 0.105088, "max_drawdown_threshold": 0.1, "position_size": 0.9516, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20241115_0988", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-11-15", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0733, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0038, std=0.0397, worst_day=-0.0785\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0733 (i.e., a 7.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0733 = 1.3652, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.07325, "expected_loss": 0.07325, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230802_0990", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2023-08-02", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0231, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0009, std=0.0101, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to VNQ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0231 (i.e., a 2.31% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0231 = 4.3359, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023063, "expected_loss": 0.023063, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20230323_0992", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2023-03-23", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0710, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0004, std=0.0436, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-03-22] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0710 (i.e., a 7.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0710 = 1.4083, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.071008, "expected_loss": 0.071008, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240419_0994", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2024-04-19", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1191, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0531, worst_day=-0.1325\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8397", "answer_numeric": 0.8397, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1191 (i.e., a 11.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1191 = 0.8397, capped at 1.0.\nMaximum position size = 0.8397 (84.0% of portfolio).", "metadata": {"var_99": -0.119095, "expected_loss": 0.119095, "max_drawdown_threshold": 0.1, "position_size": 0.8397, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20240131_0996", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2024-01-31", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0802, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0015, std=0.0437, worst_day=-0.0960\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0802 (i.e., a 8.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0802 = 1.2466, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080216, "expected_loss": 0.080216, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20230221_0998", "template": "T3", "complexity": 1, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2023-02-21", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0301, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0014, std=0.0154, worst_day=-0.0313\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-02-17] [\"Zacks Value Trader Highlights: Taiwan Semiconductor, Chevron, US Bancorp, Apple and Amazon For Immediate Release Chicago, IL \\u2013 February 17, 2023 \\u2013 Zacks Value Trader is a podcast hosted weekly by Zacks Stock Strategist Tracey Ryniec. Every week, Tracey will be joined by guests to discuss the hottest investing topics in stocks, bonds and ETFs and how it impacts your life. To listen to the podcast, click here: https://www.zacks.com/stock/news/2055570/grading-berkshire-hathaways-q4-trades) Grading Berkshire Hathaway's Q4 Trades Welcome to Episode #317 of the Value Investor Podcast. (0:15) - What Can We Learn From Berkshire Hathaways 13F? (4:30) - Breaking Down Q4 Sells and Growing Positions: How Did They Perform? (15:50) - What Was Berkshire Hathaway Buying With Their Cash Reserves? (20:35) - Episode Roundup: TSM, USB, BK, BAC, CVX, AAPL, LPX, PARA Podcast@Zacks.com Every week, Tracey Ryniec, the editor of Zacks Value Investor portfolio, shares some of her top value investing tips and stock picks. The fourth quarter 2022 13-F filings are out and that means value investors get to see what stocks Warren Buffett, and Berkshire Hathaway, are buying, or selling. Many investors follow his trades to a \\\"t\\\" even going as far as replicating them. But should you? This filing had some surprising sales and few stock purchases, even though the stock market was still selling off, and many stocks were cheap on a valuation basis, and Berkshire was still sitting on a pile of cash. What is Buffett waiting for? Is his lack of purchases a sign that he thinks stocks have further to sell-off? Or did he \\\"miss\\\" the bottom again, like he did in 2020's pandemic sell-off when he also didn't jump in to buy? Let's look at 5 of the key buys and sales in Q4. Berkshire Hathaway's Big Buys, and Sales, in the Fourth Quarter of 2022 1. Taiwan Semiconductor TSM Berkshire Hathaway first bought a position in Taiwan Semiconductor in the third quarter of 2022 to much fanfare. It was a $4.2 billion position and the first semiconductor company to be in the portfolio for years. But in the fourth quarter, just a few months later, Berkshire sold 86% of its Taiwan Semiconductor shares. It went from 60 million shares to just 8.3 million. What happened to the infamous Buffett strategy of the best time to sell is never? Even worse, shares of Taiwan Semiconductor have rallied big in 2023, adding 24.5%. Does this sale of Taiwan Semiconductor make any sense? 2. Chevron CVX Berkshire Hathaway has gone all in on the energy companies over the last 2 years, buying billions of dollars of Chevron and Occidental Petroleum. But in the fourth quarter of 2022, it sold 1%, or 2.4 million shares, of its Chevron position. This was also a head scratcher to many. What's the point of selling such a small position? Is Buffett still a big believer in Chevron? 3. US Bancorp USB Berkshire continues to sell shares of its regional banks. It first bought US Bancorp in the first quarter of 2006. But in the fo\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0301 (i.e., a 3.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0301 = 3.3228, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030095, "expected_loss": 0.030095, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T4_all_20230601_0000", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "STIP"], "decision_date": "2023-06-01", "context_summary": "XLY \u03c3=0.0123, STIP \u03c3=0.0021, \u03c1=-0.006. Min-variance weights: XLY=0.028, STIP=0.972.", "question": "Assets: XLY, STIP\nXLY: annualized_mean_return=0.2016, daily_std=0.0123\nSTIP: annualized_mean_return=0.0504, daily_std=0.0021\nMinimum required portfolio return (annualized): 0.1224\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_STIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_STIP=X.XXXX", "answer": "w_XLY=0.4762, w_STIP=0.5238", "answer_numeric": 0.4762, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000004 - -0.000000) / (0.000152 + 0.000004 - -0.000000)\n Unconstrained: w_XLY=0.0279\n After long-only clamp: w_XLY=0.0279, w_STIP=0.9721.", "metadata": {"weights": {"XLY": 0.4762, "STIP": 0.5238}, "sigma_1": 0.012324, "sigma_2": 0.002053, "covariance": -0.0, "correlation": -0.0059, "has_text": true, "text_chars": 3020, "mu_floor": 0.1224, "constraint_binding": true}} +{"id": "T4_all_20231219_0002", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ICSH"], "decision_date": "2023-12-19", "context_summary": "XLI \u03c3=0.0088, ICSH \u03c3=0.0003, \u03c1=0.174. Min-variance weights: XLI=0.000, ICSH=1.000.", "question": "Assets: XLI, ICSH\nXLI: annualized_mean_return=0.4284, daily_std=0.0088\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.3232\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLI=0.7018, w_ICSH=0.2982", "answer_numeric": 0.7018, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000077 + 0.000000 - 0.000001)\n Unconstrained: w_XLI=-0.0052\n After long-only clamp: w_XLI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLI": 0.7018, "ICSH": 0.2982}, "sigma_1": 0.008755, "sigma_2": 0.00033, "covariance": 1e-06, "correlation": 0.1735, "has_text": true, "text_chars": 3020, "mu_floor": 0.3232, "constraint_binding": true}} +{"id": "T4_all_20230407_0005", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "IGOV"], "decision_date": "2023-04-07", "context_summary": "VEA \u03c3=0.0090, IGOV \u03c3=0.0068, \u03c1=0.095. Min-variance weights: VEA=0.353, IGOV=0.647.", "question": "Assets: VEA, IGOV\nVEA: annualized_mean_return=0.1764, daily_std=0.0090\nIGOV: annualized_mean_return=0.0000, daily_std=0.0068\nMinimum required portfolio return (annualized): 0.0557\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_IGOV=X.XXXX", "answer": "w_VEA=0.3530, w_IGOV=0.6470", "answer_numeric": 0.353, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000047 - 0.000006) / (0.000081 + 0.000047 - 0.000012)\n Unconstrained: w_VEA=0.3533\n After long-only clamp: w_VEA=0.3533, w_IGOV=0.6467.", "metadata": {"weights": {"VEA": 0.353, "IGOV": 0.647}, "sigma_1": 0.008991, "sigma_2": 0.006843, "covariance": 6e-06, "correlation": 0.0953, "has_text": true, "text_chars": 3020, "mu_floor": 0.0557, "constraint_binding": false}} +{"id": "T4_all_20230517_0007", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ICSH"], "decision_date": "2023-05-17", "context_summary": "XLV \u03c3=0.0080, ICSH \u03c3=0.0004, \u03c1=-0.260. Min-variance weights: XLV=0.016, ICSH=0.984.", "question": "Assets: XLV, ICSH\nXLV: annualized_mean_return=-0.0252, daily_std=0.0080\nICSH: annualized_mean_return=0.0504, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0334\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLV=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLV=0.0178, w_ICSH=0.9822", "answer_numeric": 0.0178, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000064 + 0.000000 - -0.000002)\n Unconstrained: w_XLV=0.0162\n After long-only clamp: w_XLV=0.0162, w_ICSH=0.9838.", "metadata": {"weights": {"XLV": 0.0178, "ICSH": 0.9822}, "sigma_1": 0.00801, "sigma_2": 0.000426, "covariance": -1e-06, "correlation": -0.26, "has_text": true, "text_chars": 3020, "mu_floor": 0.0334, "constraint_binding": false}} +{"id": "T4_all_20230919_0010", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "TLT"], "decision_date": "2023-09-19", "context_summary": "AVAX-USD \u03c3=0.0199, TLT \u03c3=0.0096, \u03c1=0.006. Min-variance weights: AVAX-USD=0.186, TLT=0.814.", "question": "Assets: AVAX-USD, TLT\nAVAX-USD: annualized_mean_return=-1.7136, daily_std=0.0199\nTLT: annualized_mean_return=-0.4788, daily_std=0.0096\nMinimum required portfolio return (annualized): -0.5548\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_TLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_TLT=X.XXXX", "answer": "w_AVAX-USD=0.0615, w_TLT=0.9385", "answer_numeric": 0.0615, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000091 - 0.000001) / (0.000396 + 0.000091 - 0.000002)\n Unconstrained: w_AVAX-USD=0.1858\n After long-only clamp: w_AVAX-USD=0.1858, w_TLT=0.8142.", "metadata": {"weights": {"AVAX-USD": 0.0615, "TLT": 0.9385}, "sigma_1": 0.019893, "sigma_2": 0.009551, "covariance": 1e-06, "correlation": 0.0064, "has_text": true, "text_chars": 20, "mu_floor": -0.5548, "constraint_binding": true}} +{"id": "T4_all_20240626_0013", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD", "VNQI"], "decision_date": "2024-06-26", "context_summary": "AVAX-USD \u03c3=0.0388, VNQI \u03c3=0.0092, \u03c1=0.216. Min-variance weights: AVAX-USD=0.005, VNQI=0.995.", "question": "Assets: AVAX-USD, VNQI\nAVAX-USD: annualized_mean_return=-1.0836, daily_std=0.0388\nVNQI: annualized_mean_return=-0.1512, daily_std=0.0092\nMinimum required portfolio return (annualized): -0.2978\nMarket regime: bull\n\nCompute portfolio weights (w_AVAX-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_AVAX-USD=0.0047, w_VNQI=0.9953", "answer_numeric": 0.0047, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000084 - 0.000077) / (0.001509 + 0.000084 - 0.000153)\n Unconstrained: w_AVAX-USD=0.0050\n After long-only clamp: w_AVAX-USD=0.0050, w_VNQI=0.9950.", "metadata": {"weights": {"AVAX-USD": 0.0047, "VNQI": 0.9953}, "sigma_1": 0.038846, "sigma_2": 0.009156, "covariance": 7.7e-05, "correlation": 0.2156, "has_text": true, "text_chars": 20, "mu_floor": -0.2978, "constraint_binding": false}} +{"id": "T4_all_20231122_0016", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "PDBC"], "decision_date": "2023-11-22", "context_summary": "XLF \u03c3=0.0090, PDBC \u03c3=0.0099, \u03c1=-0.107. Min-variance weights: XLF=0.544, PDBC=0.456.", "question": "Assets: XLF, PDBC\nXLF: annualized_mean_return=0.1260, daily_std=0.0090\nPDBC: annualized_mean_return=-0.0252, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.1001\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_PDBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_PDBC=X.XXXX", "answer": "w_XLF=0.8287, w_PDBC=0.1713", "answer_numeric": 0.8287, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000098 - -0.000009) / (0.000080 + 0.000098 - -0.000019)\n Unconstrained: w_XLF=0.5438\n After long-only clamp: w_XLF=0.5438, w_PDBC=0.4562.", "metadata": {"weights": {"XLF": 0.8287, "PDBC": 0.1713}, "sigma_1": 0.008963, "sigma_2": 0.009879, "covariance": -9e-06, "correlation": -0.1069, "has_text": true, "text_chars": 3020, "mu_floor": 0.1001, "constraint_binding": true}} +{"id": "T4_all_20230505_0019", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD"], "decision_date": "2023-05-05", "context_summary": "VEA \u03c3=0.0089, AVAX-USD \u03c3=0.0395, \u03c1=-0.201. Min-variance weights: VEA=0.916, AVAX-USD=0.084.", "question": "Assets: VEA, AVAX-USD\nVEA: annualized_mean_return=0.0504, daily_std=0.0089\nAVAX-USD: annualized_mean_return=0.3780, daily_std=0.0395\nMinimum required portfolio return (annualized): 0.0644\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_AVAX-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_AVAX-USD=X.XXXX", "answer": "w_VEA=0.9158, w_AVAX-USD=0.0842", "answer_numeric": 0.9158, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001561 - -0.000071) / (0.000079 + 0.001561 - -0.000141)\n Unconstrained: w_VEA=0.9160\n After long-only clamp: w_VEA=0.9160, w_AVAX-USD=0.0840.", "metadata": {"weights": {"VEA": 0.9158, "AVAX-USD": 0.0842}, "sigma_1": 0.008892, "sigma_2": 0.039516, "covariance": -7.1e-05, "correlation": -0.2009, "has_text": true, "text_chars": 3020, "mu_floor": 0.0644, "constraint_binding": false}} +{"id": "T4_all_20240423_0021", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "CORN"], "decision_date": "2024-04-23", "context_summary": "SOL-USD \u03c3=0.0529, CORN \u03c3=0.0099, \u03c1=-0.078. Min-variance weights: SOL-USD=0.046, CORN=0.954.", "question": "Assets: SOL-USD, CORN\nSOL-USD: annualized_mean_return=2.1924, daily_std=0.0529\nCORN: annualized_mean_return=-0.0504, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.0180\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_CORN) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_CORN=X.XXXX", "answer": "w_SOL-USD=0.0466, w_CORN=0.9534", "answer_numeric": 0.0466, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000098 - -0.000041) / (0.002795 + 0.000098 - -0.000082)\n Unconstrained: w_SOL-USD=0.0465\n After long-only clamp: w_SOL-USD=0.0465, w_CORN=0.9535.", "metadata": {"weights": {"SOL-USD": 0.0466, "CORN": 0.9534}, "sigma_1": 0.052867, "sigma_2": 0.009876, "covariance": -4.1e-05, "correlation": -0.0781, "has_text": true, "text_chars": 20, "mu_floor": 0.018, "constraint_binding": false}} +{"id": "T4_all_20230124_0024", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "BIL"], "decision_date": "2023-01-24", "context_summary": "AVAX-USD \u03c3=0.0458, BIL \u03c3=0.0002, \u03c1=-0.141. Min-variance weights: AVAX-USD=0.001, BIL=0.999.", "question": "Assets: AVAX-USD, BIL\nAVAX-USD: annualized_mean_return=1.6380, daily_std=0.0458\nBIL: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 1.2417\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_AVAX-USD=0.7543, w_BIL=0.2457", "answer_numeric": 0.7543, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.002099 + 0.000000 - -0.000003)\n Unconstrained: w_AVAX-USD=0.0006\n After long-only clamp: w_AVAX-USD=0.0006, w_BIL=0.9994.", "metadata": {"weights": {"AVAX-USD": 0.7543, "BIL": 0.2457}, "sigma_1": 0.045816, "sigma_2": 0.000195, "covariance": -1e-06, "correlation": -0.1412, "has_text": true, "text_chars": 20, "mu_floor": 1.2417, "constraint_binding": true}} +{"id": "T4_all_20230728_0026", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BIL"], "decision_date": "2023-07-28", "context_summary": "QQQ \u03c3=0.0100, BIL \u03c3=0.0001, \u03c1=0.119. Min-variance weights: QQQ=0.000, BIL=1.000.", "question": "Assets: QQQ, BIL\nQQQ: annualized_mean_return=0.6552, daily_std=0.0100\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.4104\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QQQ=X.XXXX, w_BIL=X.XXXX", "answer": "w_QQQ=0.5952, w_BIL=0.4048", "answer_numeric": 0.5952, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000100 + 0.000000 - 0.000000)\n Unconstrained: w_QQQ=-0.0015\n After long-only clamp: w_QQQ=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"QQQ": 0.5952, "BIL": 0.4048}, "sigma_1": 0.010007, "sigma_2": 0.000142, "covariance": 0.0, "correlation": 0.1192, "has_text": true, "text_chars": 9046, "mu_floor": 0.4104, "constraint_binding": true}} +{"id": "T4_all_20240202_0029", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "PPLT"], "decision_date": "2024-02-02", "context_summary": "SOL-USD \u03c3=0.0544, PPLT \u03c3=0.0135, \u03c1=-0.054. Min-variance weights: SOL-USD=0.069, PPLT=0.931.", "question": "Assets: SOL-USD, PPLT\nSOL-USD: annualized_mean_return=2.2176, daily_std=0.0544\nPPLT: annualized_mean_return=0.0756, daily_std=0.0135\nMinimum required portfolio return (annualized): 0.1431\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_PPLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_PPLT=X.XXXX", "answer": "w_SOL-USD=0.0693, w_PPLT=0.9307", "answer_numeric": 0.0693, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000183 - -0.000040) / (0.002956 + 0.000183 - -0.000080)\n Unconstrained: w_SOL-USD=0.0693\n After long-only clamp: w_SOL-USD=0.0693, w_PPLT=0.9307.", "metadata": {"weights": {"SOL-USD": 0.0693, "PPLT": 0.9307}, "sigma_1": 0.054366, "sigma_2": 0.013531, "covariance": -4e-05, "correlation": -0.0543, "has_text": true, "text_chars": 20, "mu_floor": 0.1431, "constraint_binding": false}} +{"id": "T4_all_20231013_0031", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "XLRE"], "decision_date": "2023-10-13", "context_summary": "SOL-USD \u03c3=0.0324, XLRE \u03c3=0.0101, \u03c1=-0.225. Min-variance weights: SOL-USD=0.136, XLRE=0.864.", "question": "Assets: SOL-USD, XLRE\nSOL-USD: annualized_mean_return=-0.4032, daily_std=0.0324\nXLRE: annualized_mean_return=-0.4536, daily_std=0.0101\nMinimum required portfolio return (annualized): -0.4489\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_XLRE) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_XLRE=X.XXXX", "answer": "w_SOL-USD=0.1357, w_XLRE=0.8643", "answer_numeric": 0.1357, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000103 - -0.000074) / (0.001052 + 0.000103 - -0.000148)\n Unconstrained: w_SOL-USD=0.1357\n After long-only clamp: w_SOL-USD=0.1357, w_XLRE=0.8643.", "metadata": {"weights": {"SOL-USD": 0.1357, "XLRE": 0.8643}, "sigma_1": 0.032435, "sigma_2": 0.010136, "covariance": -7.4e-05, "correlation": -0.2254, "has_text": true, "text_chars": 20, "mu_floor": -0.4489, "constraint_binding": false}} +{"id": "T4_all_20231024_0034", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XHB"], "decision_date": "2023-10-24", "context_summary": "XLP \u03c3=0.0066, XHB \u03c3=0.0142, \u03c1=0.482. Min-variance weights: XLP=1.000, XHB=0.000.", "question": "Assets: XLP, XHB\nXLP: annualized_mean_return=-0.5040, daily_std=0.0066\nXHB: annualized_mean_return=-0.6804, daily_std=0.0142\nMinimum required portfolio return (annualized): -0.5577\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_XHB=X.XXXX", "answer": "w_XLP=1.0000, w_XHB=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000202 - 0.000045) / (0.000043 + 0.000202 - 0.000090)\n Unconstrained: w_XLP=1.0118\n After long-only clamp: w_XLP=1.0000, w_XHB=0.0000.", "metadata": {"weights": {"XLP": 1.0, "XHB": 0.0}, "sigma_1": 0.006566, "sigma_2": 0.01421, "covariance": 4.5e-05, "correlation": 0.4817, "has_text": true, "text_chars": 3020, "mu_floor": -0.5577, "constraint_binding": false}} +{"id": "T4_all_20240815_0036", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "CSHI"], "decision_date": "2024-08-15", "context_summary": "AVAX-USD \u03c3=0.0485, CSHI \u03c3=0.0010, \u03c1=0.491. Min-variance weights: AVAX-USD=0.000, CSHI=1.000.", "question": "Assets: AVAX-USD, CSHI\nAVAX-USD: annualized_mean_return=-1.2096, daily_std=0.0485\nCSHI: annualized_mean_return=0.0504, daily_std=0.0010\nMinimum required portfolio return (annualized): -0.3762\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_AVAX-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000024) / (0.002356 + 0.000001 - 0.000048)\n Unconstrained: w_AVAX-USD=-0.0099\n After long-only clamp: w_AVAX-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"AVAX-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.048534, "sigma_2": 0.001001, "covariance": 2.4e-05, "correlation": 0.4906, "has_text": true, "text_chars": 20, "mu_floor": -0.3762, "constraint_binding": false}} +{"id": "T4_all_20230626_0038", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNDX"], "decision_date": "2023-06-26", "context_summary": "XLI \u03c3=0.0101, BNDX \u03c3=0.0032, \u03c1=-0.119. Min-variance weights: XLI=0.115, BNDX=0.885.", "question": "Assets: XLI, BNDX\nXLI: annualized_mean_return=0.2268, daily_std=0.0101\nBNDX: annualized_mean_return=0.0252, daily_std=0.0032\nMinimum required portfolio return (annualized): 0.1125\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_BNDX=X.XXXX", "answer": "w_XLI=0.4330, w_BNDX=0.5670", "answer_numeric": 0.433, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - -0.000004) / (0.000102 + 0.000010 - -0.000008)\n Unconstrained: w_XLI=0.1151\n After long-only clamp: w_XLI=0.1151, w_BNDX=0.8849.", "metadata": {"weights": {"XLI": 0.433, "BNDX": 0.567}, "sigma_1": 0.010085, "sigma_2": 0.003153, "covariance": -4e-06, "correlation": -0.1187, "has_text": true, "text_chars": 3020, "mu_floor": 0.1125, "constraint_binding": true}} +{"id": "T4_all_20230928_0041", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SCHH"], "decision_date": "2023-09-28", "context_summary": "FXI \u03c3=0.0175, SCHH \u03c3=0.0091, \u03c1=0.344. Min-variance weights: FXI=0.099, SCHH=0.901.", "question": "Assets: FXI, SCHH\nFXI: annualized_mean_return=-0.2268, daily_std=0.0175\nSCHH: annualized_mean_return=-0.4536, daily_std=0.0091\nMinimum required portfolio return (annualized): -0.4428\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_SCHH=X.XXXX", "answer": "w_FXI=0.0980, w_SCHH=0.9020", "answer_numeric": 0.098, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000082 - 0.000055) / (0.000307 + 0.000082 - 0.000110)\n Unconstrained: w_FXI=0.0987\n After long-only clamp: w_FXI=0.0987, w_SCHH=0.9013.", "metadata": {"weights": {"FXI": 0.098, "SCHH": 0.902}, "sigma_1": 0.017529, "sigma_2": 0.009078, "covariance": 5.5e-05, "correlation": 0.3442, "has_text": true, "text_chars": 3020, "mu_floor": -0.4428, "constraint_binding": false}} +{"id": "T4_all_20230531_0044", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ICSH"], "decision_date": "2023-05-31", "context_summary": "FXI \u03c3=0.0174, ICSH \u03c3=0.0004, \u03c1=-0.175. Min-variance weights: FXI=0.004, ICSH=0.996.", "question": "Assets: FXI, ICSH\nFXI: annualized_mean_return=-0.5292, daily_std=0.0174\nICSH: annualized_mean_return=0.0252, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0237\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_ICSH=X.XXXX", "answer": "w_FXI=0.0027, w_ICSH=0.9973", "answer_numeric": 0.0027, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000302 + 0.000000 - -0.000002)\n Unconstrained: w_FXI=0.0045\n After long-only clamp: w_FXI=0.0045, w_ICSH=0.9955.", "metadata": {"weights": {"FXI": 0.0027, "ICSH": 0.9973}, "sigma_1": 0.01739, "sigma_2": 0.000402, "covariance": -1e-06, "correlation": -0.1754, "has_text": true, "text_chars": 3020, "mu_floor": 0.0237, "constraint_binding": true}} +{"id": "T4_all_20241212_0047", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "BIL"], "decision_date": "2024-12-12", "context_summary": "XLF \u03c3=0.0089, BIL \u03c3=0.0002, \u03c1=0.129. Min-variance weights: XLF=0.000, BIL=1.000.", "question": "Assets: XLF, BIL\nXLF: annualized_mean_return=0.3024, daily_std=0.0089\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\n\nCompute portfolio weights (w_XLF, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLF=0.0003, w_BIL=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000080 + 0.000000 - 0.000000)\n Unconstrained: w_XLF=-0.0020\n After long-only clamp: w_XLF=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLF": 0.0003, "BIL": 0.9997}, "sigma_1": 0.008942, "sigma_2": 0.000165, "covariance": 0.0, "correlation": 0.129, "has_text": true, "text_chars": 9045, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20230117_0050", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LQD"], "decision_date": "2023-01-17", "context_summary": "XLY \u03c3=0.0159, LQD \u03c3=0.0069, \u03c1=0.159. Min-variance weights: XLY=0.114, LQD=0.886.", "question": "Assets: XLY, LQD\nXLY: annualized_mean_return=-0.2268, daily_std=0.0159\nLQD: annualized_mean_return=0.3780, daily_std=0.0069\nMinimum required portfolio return (annualized): 0.3299\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_LQD=X.XXXX", "answer": "w_XLY=0.0795, w_LQD=0.9205", "answer_numeric": 0.0795, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000048 - 0.000017) / (0.000253 + 0.000048 - 0.000035)\n Unconstrained: w_XLY=0.1142\n After long-only clamp: w_XLY=0.1142, w_LQD=0.8858.", "metadata": {"weights": {"XLY": 0.0795, "LQD": 0.9205}, "sigma_1": 0.015906, "sigma_2": 0.006916, "covariance": 1.7e-05, "correlation": 0.1588, "has_text": true, "text_chars": 3020, "mu_floor": 0.3299, "constraint_binding": true}} +{"id": "T4_all_20240610_0053", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "BIL"], "decision_date": "2024-06-10", "context_summary": "BTC-USD \u03c3=0.0262, BIL \u03c3=0.0002, \u03c1=0.147. Min-variance weights: BTC-USD=0.000, BIL=1.000.", "question": "Assets: BTC-USD, BIL\nBTC-USD: annualized_mean_return=0.0252, daily_std=0.0262\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0394\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_BTC-USD=0.0000, w_BIL=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000684 + 0.000000 - 0.000001)\n Unconstrained: w_BTC-USD=-0.0009\n After long-only clamp: w_BTC-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.026155, "sigma_2": 0.00016, "covariance": 1e-06, "correlation": 0.147, "has_text": true, "text_chars": 20, "mu_floor": 0.0394, "constraint_binding": false}} +{"id": "T4_all_20240201_0056", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "PALL"], "decision_date": "2024-02-01", "context_summary": "DOT-USD \u03c3=0.0515, PALL \u03c3=0.0243, \u03c1=-0.066. Min-variance weights: DOT-USD=0.198, PALL=0.802.", "question": "Assets: DOT-USD, PALL\nDOT-USD: annualized_mean_return=1.0584, daily_std=0.0515\nPALL: annualized_mean_return=-0.6804, daily_std=0.0243\nMinimum required portfolio return (annualized): 0.7411\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_PALL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_PALL=X.XXXX", "answer": "w_DOT-USD=0.8175, w_PALL=0.1825", "answer_numeric": 0.8175, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000592 - -0.000083) / (0.002653 + 0.000592 - -0.000166)\n Unconstrained: w_DOT-USD=0.1978\n After long-only clamp: w_DOT-USD=0.1978, w_PALL=0.8022.", "metadata": {"weights": {"DOT-USD": 0.8175, "PALL": 0.1825}, "sigma_1": 0.051503, "sigma_2": 0.024321, "covariance": -8.3e-05, "correlation": -0.0664, "has_text": true, "text_chars": 20, "mu_floor": 0.7411, "constraint_binding": true}} +{"id": "T4_all_20241225_0059", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "GLD"], "decision_date": "2024-12-25", "context_summary": "MATIC-USD \u03c3=0.0615, GLD \u03c3=0.0097, \u03c1=-0.069. Min-variance weights: MATIC-USD=0.034, GLD=0.966.", "question": "Assets: MATIC-USD, GLD\nMATIC-USD: annualized_mean_return=2.5704, daily_std=0.0615\nGLD: annualized_mean_return=0.0252, daily_std=0.0097\nMinimum required portfolio return (annualized): 0.0678\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_GLD=X.XXXX", "answer": "w_MATIC-USD=0.0342, w_GLD=0.9658", "answer_numeric": 0.0342, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000094 - -0.000041) / (0.003776 + 0.000094 - -0.000082)\n Unconstrained: w_MATIC-USD=0.0342\n After long-only clamp: w_MATIC-USD=0.0342, w_GLD=0.9658.", "metadata": {"weights": {"MATIC-USD": 0.0342, "GLD": 0.9658}, "sigma_1": 0.061451, "sigma_2": 0.009709, "covariance": -4.1e-05, "correlation": -0.0686, "has_text": true, "text_chars": 20, "mu_floor": 0.0678, "constraint_binding": false}} +{"id": "T4_all_20230920_0062", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "SOYB"], "decision_date": "2023-09-20", "context_summary": "LINK-USD \u03c3=0.0273, SOYB \u03c3=0.0130, \u03c1=-0.148. Min-variance weights: LINK-USD=0.217, SOYB=0.783.", "question": "Assets: LINK-USD, SOYB\nLINK-USD: annualized_mean_return=-0.6300, daily_std=0.0273\nSOYB: annualized_mean_return=0.4032, daily_std=0.0130\nMinimum required portfolio return (annualized): 0.3449\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_SOYB=X.XXXX", "answer": "w_LINK-USD=0.0564, w_SOYB=0.9436", "answer_numeric": 0.0564, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000168 - -0.000052) / (0.000745 + 0.000168 - -0.000105)\n Unconstrained: w_LINK-USD=0.2170\n After long-only clamp: w_LINK-USD=0.2170, w_SOYB=0.7830.", "metadata": {"weights": {"LINK-USD": 0.0564, "SOYB": 0.9436}, "sigma_1": 0.027286, "sigma_2": 0.01298, "covariance": -5.2e-05, "correlation": -0.1479, "has_text": true, "text_chars": 20, "mu_floor": 0.3449, "constraint_binding": true}} +{"id": "T4_all_20230512_0065", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "INDS"], "decision_date": "2023-05-12", "context_summary": "XLP \u03c3=0.0063, INDS \u03c3=0.0120, \u03c1=0.649. Min-variance weights: XLP=1.000, INDS=0.000.", "question": "Assets: XLP, INDS\nXLP: annualized_mean_return=0.2268, daily_std=0.0063\nINDS: annualized_mean_return=-0.0504, daily_std=0.0120\nMinimum required portfolio return (annualized): 0.0893\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_INDS=X.XXXX", "answer": "w_XLP=1.0000, w_INDS=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000145 - 0.000049) / (0.000040 + 0.000145 - 0.000098)\n Unconstrained: w_XLP=1.1113\n After long-only clamp: w_XLP=1.0000, w_INDS=0.0000.", "metadata": {"weights": {"XLP": 1.0, "INDS": 0.0}, "sigma_1": 0.006285, "sigma_2": 0.012024, "covariance": 4.9e-05, "correlation": 0.6493, "has_text": true, "text_chars": 3020, "mu_floor": 0.0893, "constraint_binding": false}} +{"id": "T4_all_20230504_0067", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ADA-USD"], "decision_date": "2023-05-04", "context_summary": "XLU \u03c3=0.0116, ADA-USD \u03c3=0.0345, \u03c1=0.192. Min-variance weights: XLU=0.950, ADA-USD=0.050.", "question": "Assets: XLU, ADA-USD\nXLU: annualized_mean_return=-0.0000, daily_std=0.0116\nADA-USD: annualized_mean_return=0.8064, daily_std=0.0345\nMinimum required portfolio return (annualized): 0.0198\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_ADA-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_ADA-USD=X.XXXX", "answer": "w_XLU=0.9502, w_ADA-USD=0.0498", "answer_numeric": 0.9502, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001191 - 0.000077) / (0.000135 + 0.001191 - 0.000154)\n Unconstrained: w_XLU=0.9504\n After long-only clamp: w_XLU=0.9504, w_ADA-USD=0.0496.", "metadata": {"weights": {"XLU": 0.9502, "ADA-USD": 0.0498}, "sigma_1": 0.011634, "sigma_2": 0.03451, "covariance": 7.7e-05, "correlation": 0.1922, "has_text": true, "text_chars": 3020, "mu_floor": 0.0198, "constraint_binding": false}} +{"id": "T4_all_20240620_0069", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "ADA-USD"], "decision_date": "2024-06-20", "context_summary": "FXI \u03c3=0.0140, ADA-USD \u03c3=0.0251, \u03c1=-0.108. Min-variance weights: FXI=0.742, ADA-USD=0.258.", "question": "Assets: FXI, ADA-USD\nFXI: annualized_mean_return=0.4536, daily_std=0.0140\nADA-USD: annualized_mean_return=-1.0836, daily_std=0.0251\nMinimum required portfolio return (annualized): -0.2179\nMarket regime: bull\n\nCompute portfolio weights (w_FXI, w_ADA-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_ADA-USD=X.XXXX", "answer": "w_FXI=0.7416, w_ADA-USD=0.2584", "answer_numeric": 0.7416, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000632 - -0.000038) / (0.000195 + 0.000632 - -0.000076)\n Unconstrained: w_FXI=0.7417\n After long-only clamp: w_FXI=0.7417, w_ADA-USD=0.2583.", "metadata": {"weights": {"FXI": 0.7416, "ADA-USD": 0.2584}, "sigma_1": 0.013977, "sigma_2": 0.025134, "covariance": -3.8e-05, "correlation": -0.1077, "has_text": true, "text_chars": 9045, "mu_floor": -0.2179, "constraint_binding": false}} +{"id": "T4_all_20240503_0072", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "INDS"], "decision_date": "2024-05-03", "context_summary": "ACWI \u03c3=0.0071, INDS \u03c3=0.0112, \u03c1=0.658. Min-variance weights: ACWI=1.000, INDS=0.000.", "question": "Assets: ACWI, INDS\nACWI: annualized_mean_return=0.1260, daily_std=0.0071\nINDS: annualized_mean_return=-0.2772, daily_std=0.0112\nMinimum required portfolio return (annualized): 0.0725\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ACWI=X.XXXX, w_INDS=X.XXXX", "answer": "w_ACWI=1.0000, w_INDS=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000125 - 0.000053) / (0.000051 + 0.000125 - 0.000105)\n Unconstrained: w_ACWI=1.0206\n After long-only clamp: w_ACWI=1.0000, w_INDS=0.0000.", "metadata": {"weights": {"ACWI": 1.0, "INDS": 0.0}, "sigma_1": 0.007146, "sigma_2": 0.011177, "covariance": 5.3e-05, "correlation": 0.6576, "has_text": true, "text_chars": 9045, "mu_floor": 0.0725, "constraint_binding": false}} +{"id": "T4_all_20230410_0075", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "JNK"], "decision_date": "2023-04-10", "context_summary": "DOT-USD \u03c3=0.0397, JNK \u03c3=0.0059, \u03c1=-0.160. Min-variance weights: DOT-USD=0.043, JNK=0.957.", "question": "Assets: DOT-USD, JNK\nDOT-USD: annualized_mean_return=-0.1512, daily_std=0.0397\nJNK: annualized_mean_return=0.0252, daily_std=0.0059\nMinimum required portfolio return (annualized): -0.0622\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_JNK) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_JNK=X.XXXX", "answer": "w_DOT-USD=0.0427, w_JNK=0.9573", "answer_numeric": 0.0427, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000035 - -0.000037) / (0.001572 + 0.000035 - -0.000075)\n Unconstrained: w_DOT-USD=0.0429\n After long-only clamp: w_DOT-USD=0.0429, w_JNK=0.9571.", "metadata": {"weights": {"DOT-USD": 0.0427, "JNK": 0.9573}, "sigma_1": 0.039652, "sigma_2": 0.0059, "covariance": -3.7e-05, "correlation": -0.16, "has_text": true, "text_chars": 20, "mu_floor": -0.0622, "constraint_binding": false}} +{"id": "T4_all_20230911_0077", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "XLK"], "decision_date": "2023-09-11", "context_summary": "DOT-USD \u03c3=0.0205, XLK \u03c3=0.0108, \u03c1=0.281. Min-variance weights: DOT-USD=0.130, XLK=0.870.", "question": "Assets: DOT-USD, XLK\nDOT-USD: annualized_mean_return=-0.8568, daily_std=0.0205\nXLK: annualized_mean_return=0.0504, daily_std=0.0108\nMinimum required portfolio return (annualized): -0.3861\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_XLK) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_XLK=X.XXXX", "answer": "w_DOT-USD=0.1299, w_XLK=0.8701", "answer_numeric": 0.1299, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000116 - 0.000062) / (0.000422 + 0.000116 - 0.000124)\n Unconstrained: w_DOT-USD=0.1297\n After long-only clamp: w_DOT-USD=0.1297, w_XLK=0.8703.", "metadata": {"weights": {"DOT-USD": 0.1299, "XLK": 0.8701}, "sigma_1": 0.020531, "sigma_2": 0.010755, "covariance": 6.2e-05, "correlation": 0.2814, "has_text": true, "text_chars": 20, "mu_floor": -0.3861, "constraint_binding": false}} +{"id": "T4_all_20240411_0080", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SCHH"], "decision_date": "2024-04-11", "context_summary": "ETH-USD \u03c3=0.0358, SCHH \u03c3=0.0112, \u03c1=-0.102. Min-variance weights: ETH-USD=0.111, SCHH=0.889.", "question": "Assets: ETH-USD, SCHH\nETH-USD: annualized_mean_return=1.6380, daily_std=0.0358\nSCHH: annualized_mean_return=-0.1764, daily_std=0.0112\nMinimum required portfolio return (annualized): 1.0002\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_SCHH=X.XXXX", "answer": "w_ETH-USD=0.6485, w_SCHH=0.3515", "answer_numeric": 0.6485, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000125 - -0.000041) / (0.001285 + 0.000125 - -0.000081)\n Unconstrained: w_ETH-USD=0.1110\n After long-only clamp: w_ETH-USD=0.1110, w_SCHH=0.8890.", "metadata": {"weights": {"ETH-USD": 0.6485, "SCHH": 0.3515}, "sigma_1": 0.035849, "sigma_2": 0.011174, "covariance": -4.1e-05, "correlation": -0.1017, "has_text": true, "text_chars": 20, "mu_floor": 1.0002, "constraint_binding": true}} +{"id": "T4_all_20231106_0083", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "XHB"], "decision_date": "2023-11-06", "context_summary": "DOT-USD \u03c3=0.0244, XHB \u03c3=0.0158, \u03c1=0.087. Min-variance weights: DOT-USD=0.279, XHB=0.721.", "question": "Assets: DOT-USD, XHB\nDOT-USD: annualized_mean_return=0.5544, daily_std=0.0244\nXHB: annualized_mean_return=-0.2772, daily_std=0.0158\nMinimum required portfolio return (annualized): -0.1398\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_XHB=X.XXXX", "answer": "w_DOT-USD=0.2783, w_XHB=0.7217", "answer_numeric": 0.2783, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000250 - 0.000034) / (0.000594 + 0.000250 - 0.000067)\n Unconstrained: w_DOT-USD=0.2786\n After long-only clamp: w_DOT-USD=0.2786, w_XHB=0.7214.", "metadata": {"weights": {"DOT-USD": 0.2783, "XHB": 0.7217}, "sigma_1": 0.024375, "sigma_2": 0.015813, "covariance": 3.4e-05, "correlation": 0.087, "has_text": true, "text_chars": 20, "mu_floor": -0.1398, "constraint_binding": false}} +{"id": "T4_all_20240619_0085", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD", "SHY"], "decision_date": "2024-06-19", "context_summary": "SOL-USD \u03c3=0.0396, SHY \u03c3=0.0010, \u03c1=0.236. Min-variance weights: SOL-USD=0.000, SHY=1.000.", "question": "Assets: SOL-USD, SHY\nSOL-USD: annualized_mean_return=0.0504, daily_std=0.0396\nSHY: annualized_mean_return=0.0504, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\n\nCompute portfolio weights (w_SOL-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_SOL-USD=0.0000, w_SHY=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000010) / (0.001568 + 0.000001 - 0.000019)\n Unconstrained: w_SOL-USD=-0.0055\n After long-only clamp: w_SOL-USD=0.0000, w_SHY=1.0000.", "metadata": {"weights": {"SOL-USD": 0.0, "SHY": 1.0}, "sigma_1": 0.039593, "sigma_2": 0.001017, "covariance": 1e-05, "correlation": 0.2361, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20231102_0087", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "XHB"], "decision_date": "2023-11-02", "context_summary": "ACWI \u03c3=0.0076, XHB \u03c3=0.0151, \u03c1=0.771. Min-variance weights: ACWI=1.000, XHB=0.000.", "question": "Assets: ACWI, XHB\nACWI: annualized_mean_return=-0.2520, daily_std=0.0076\nXHB: annualized_mean_return=-0.5292, daily_std=0.0151\nMinimum required portfolio return (annualized): -0.3245\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ACWI=X.XXXX, w_XHB=X.XXXX", "answer": "w_ACWI=1.0000, w_XHB=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000229 - 0.000089) / (0.000058 + 0.000229 - 0.000178)\n Unconstrained: w_ACWI=1.2828\n After long-only clamp: w_ACWI=1.0000, w_XHB=0.0000.", "metadata": {"weights": {"ACWI": 1.0, "XHB": 0.0}, "sigma_1": 0.007613, "sigma_2": 0.015128, "covariance": 8.9e-05, "correlation": 0.7713, "has_text": true, "text_chars": 3020, "mu_floor": -0.3245, "constraint_binding": false}} +{"id": "T4_all_20230126_0090", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "BNO"], "decision_date": "2023-01-26", "context_summary": "AVAX-USD \u03c3=0.0467, BNO \u03c3=0.0228, \u03c1=-0.027. Min-variance weights: AVAX-USD=0.199, BNO=0.801.", "question": "Assets: AVAX-USD, BNO\nAVAX-USD: annualized_mean_return=1.6632, daily_std=0.0467\nBNO: annualized_mean_return=-0.2520, daily_std=0.0228\nMinimum required portfolio return (annualized): 1.2517\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_BNO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_BNO=X.XXXX", "answer": "w_AVAX-USD=0.7851, w_BNO=0.2149", "answer_numeric": 0.7851, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000519 - -0.000029) / (0.002182 + 0.000519 - -0.000058)\n Unconstrained: w_AVAX-USD=0.1986\n After long-only clamp: w_AVAX-USD=0.1986, w_BNO=0.8014.", "metadata": {"weights": {"AVAX-USD": 0.7851, "BNO": 0.2149}, "sigma_1": 0.046707, "sigma_2": 0.022781, "covariance": -2.9e-05, "correlation": -0.0271, "has_text": true, "text_chars": 20, "mu_floor": 1.2517, "constraint_binding": true}} +{"id": "T4_all_20230503_0093", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BNDX"], "decision_date": "2023-05-03", "context_summary": "MTUM \u03c3=0.0092, BNDX \u03c3=0.0037, \u03c1=0.002. Min-variance weights: MTUM=0.135, BNDX=0.865.", "question": "Assets: MTUM, BNDX\nMTUM: annualized_mean_return=-0.0000, daily_std=0.0092\nBNDX: annualized_mean_return=0.0504, daily_std=0.0037\nMinimum required portfolio return (annualized): 0.0407\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_BNDX=X.XXXX", "answer": "w_MTUM=0.1360, w_BNDX=0.8640", "answer_numeric": 0.136, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000013 - 0.000000) / (0.000085 + 0.000013 - 0.000000)\n Unconstrained: w_MTUM=0.1354\n After long-only clamp: w_MTUM=0.1354, w_BNDX=0.8646.", "metadata": {"weights": {"MTUM": 0.136, "BNDX": 0.864}, "sigma_1": 0.009206, "sigma_2": 0.003653, "covariance": 0.0, "correlation": 0.0024, "has_text": true, "text_chars": 3020, "mu_floor": 0.0407, "constraint_binding": false}} +{"id": "T4_all_20230130_0096", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "BIL"], "decision_date": "2023-01-30", "context_summary": "MATIC-USD \u03c3=0.0345, BIL \u03c3=0.0002, \u03c1=0.155. Min-variance weights: MATIC-USD=0.000, BIL=1.000.", "question": "Assets: MATIC-USD, BIL\nMATIC-USD: annualized_mean_return=1.1088, daily_std=0.0345\nBIL: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.6258\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_MATIC-USD=0.5543, w_BIL=0.4457", "answer_numeric": 0.5543, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.001190 + 0.000000 - 0.000002)\n Unconstrained: w_MATIC-USD=-0.0009\n After long-only clamp: w_MATIC-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.5543, "BIL": 0.4457}, "sigma_1": 0.034491, "sigma_2": 0.0002, "covariance": 1e-06, "correlation": 0.1549, "has_text": true, "text_chars": 20, "mu_floor": 0.6258, "constraint_binding": true}} +{"id": "T4_all_20230810_0099", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BIL"], "decision_date": "2023-08-10", "context_summary": "QUAL \u03c3=0.0073, BIL \u03c3=0.0001, \u03c1=0.070. Min-variance weights: QUAL=0.000, BIL=1.000.", "question": "Assets: QUAL, BIL\nQUAL: annualized_mean_return=0.4032, daily_std=0.0073\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0505\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_BIL=X.XXXX", "answer": "w_QUAL=0.0003, w_BIL=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000053 + 0.000000 - 0.000000)\n Unconstrained: w_QUAL=-0.0009\n After long-only clamp: w_QUAL=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"QUAL": 0.0003, "BIL": 0.9997}, "sigma_1": 0.00726, "sigma_2": 0.00013, "covariance": 0.0, "correlation": 0.0699, "has_text": true, "text_chars": 3020, "mu_floor": 0.0505, "constraint_binding": false}} +{"id": "T4_all_20231030_0102", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "EMB"], "decision_date": "2023-10-30", "context_summary": "XLV \u03c3=0.0064, EMB \u03c3=0.0054, \u03c1=0.145. Min-variance weights: XLV=0.406, EMB=0.594.", "question": "Assets: XLV, EMB\nXLV: annualized_mean_return=-0.3024, daily_std=0.0064\nEMB: annualized_mean_return=-0.2268, daily_std=0.0054\nMinimum required portfolio return (annualized): -0.2435\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_EMB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLV=X.XXXX, w_EMB=X.XXXX", "answer": "w_XLV=0.2209, w_EMB=0.7791", "answer_numeric": 0.2209, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000029 - 0.000005) / (0.000041 + 0.000029 - 0.000010)\n Unconstrained: w_XLV=0.4065\n After long-only clamp: w_XLV=0.4065, w_EMB=0.5935.", "metadata": {"weights": {"XLV": 0.2209, "EMB": 0.7791}, "sigma_1": 0.006369, "sigma_2": 0.005418, "covariance": 5e-06, "correlation": 0.1445, "has_text": true, "text_chars": 3020, "mu_floor": -0.2435, "constraint_binding": true}} +{"id": "T4_all_20241129_0105", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "ICSH"], "decision_date": "2024-11-29", "context_summary": "VLUE \u03c3=0.0079, ICSH \u03c3=0.0003, \u03c1=-0.096. Min-variance weights: VLUE=0.005, ICSH=0.995.", "question": "Assets: VLUE, ICSH\nVLUE: annualized_mean_return=0.3528, daily_std=0.0079\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0507\nMarket regime: bull\n\nCompute portfolio weights (w_VLUE, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_ICSH=X.XXXX", "answer": "w_VLUE=0.0012, w_ICSH=0.9988", "answer_numeric": 0.0012, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000062 + 0.000000 - -0.000000)\n Unconstrained: w_VLUE=0.0046\n After long-only clamp: w_VLUE=0.0046, w_ICSH=0.9954.", "metadata": {"weights": {"VLUE": 0.0012, "ICSH": 0.9988}, "sigma_1": 0.007886, "sigma_2": 0.000276, "covariance": -0.0, "correlation": -0.0965, "has_text": true, "text_chars": 9046, "mu_floor": 0.0507, "constraint_binding": false}} +{"id": "T4_all_20231107_0109", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "LQD"], "decision_date": "2023-11-07", "context_summary": "BTC-USD \u03c3=0.0191, LQD \u03c3=0.0062, \u03c1=-0.186. Min-variance weights: BTC-USD=0.134, LQD=0.866.", "question": "Assets: BTC-USD, LQD\nBTC-USD: annualized_mean_return=1.2600, daily_std=0.0191\nLQD: annualized_mean_return=-0.1260, daily_std=0.0062\nMinimum required portfolio return (annualized): 0.0224\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_LQD=X.XXXX", "answer": "w_BTC-USD=0.1343, w_LQD=0.8657", "answer_numeric": 0.1343, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000038 - -0.000022) / (0.000365 + 0.000038 - -0.000044)\n Unconstrained: w_BTC-USD=0.1343\n After long-only clamp: w_BTC-USD=0.1343, w_LQD=0.8657.", "metadata": {"weights": {"BTC-USD": 0.1343, "LQD": 0.8657}, "sigma_1": 0.019114, "sigma_2": 0.006173, "covariance": -2.2e-05, "correlation": -0.1862, "has_text": true, "text_chars": 20, "mu_floor": 0.0224, "constraint_binding": false}} +{"id": "T4_all_20240617_0111", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "STIP"], "decision_date": "2024-06-17", "context_summary": "SPY \u03c3=0.0067, STIP \u03c3=0.0012, \u03c1=0.096. Min-variance weights: SPY=0.013, STIP=0.987.", "question": "Assets: SPY, STIP\nSPY: annualized_mean_return=0.1764, daily_std=0.0067\nSTIP: annualized_mean_return=0.0504, daily_std=0.0012\nMinimum required portfolio return (annualized): 0.0509\nMarket regime: sideways\n\nCompute portfolio weights (w_SPY, w_STIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_STIP=X.XXXX", "answer": "w_SPY=0.0079, w_STIP=0.9921", "answer_numeric": 0.0079, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000001) / (0.000045 + 0.000001 - 0.000001)\n Unconstrained: w_SPY=0.0135\n After long-only clamp: w_SPY=0.0135, w_STIP=0.9865.", "metadata": {"weights": {"SPY": 0.0079, "STIP": 0.9921}, "sigma_1": 0.006688, "sigma_2": 0.001161, "covariance": 1e-06, "correlation": 0.0961, "has_text": true, "text_chars": 9045, "mu_floor": 0.0509, "constraint_binding": false}} +{"id": "T4_all_20231201_0113", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SCHH"], "decision_date": "2023-12-01", "context_summary": "QUAL \u03c3=0.0084, SCHH \u03c3=0.0132, \u03c1=0.672. Min-variance weights: QUAL=1.000, SCHH=0.000.", "question": "Assets: QUAL, SCHH\nQUAL: annualized_mean_return=0.1008, daily_std=0.0084\nSCHH: annualized_mean_return=0.0252, daily_std=0.0132\nMinimum required portfolio return (annualized): 0.0854\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_SCHH=X.XXXX", "answer": "w_QUAL=1.0000, w_SCHH=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000174 - 0.000075) / (0.000071 + 0.000174 - 0.000150)\n Unconstrained: w_QUAL=1.0394\n After long-only clamp: w_QUAL=1.0000, w_SCHH=0.0000.", "metadata": {"weights": {"QUAL": 1.0, "SCHH": 0.0}, "sigma_1": 0.008428, "sigma_2": 0.0132, "covariance": 7.5e-05, "correlation": 0.6724, "has_text": true, "text_chars": 3020, "mu_floor": 0.0854, "constraint_binding": false}} +{"id": "T4_all_20231113_0116", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "CSHI"], "decision_date": "2023-11-13", "context_summary": "EEM \u03c3=0.0091, CSHI \u03c3=0.0005, \u03c1=0.114. Min-variance weights: EEM=0.000, CSHI=1.000.", "question": "Assets: EEM, CSHI\nEEM: annualized_mean_return=-0.0252, daily_std=0.0091\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0064\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_CSHI=X.XXXX", "answer": "w_EEM=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000082 + 0.000000 - 0.000001)\n Unconstrained: w_EEM=-0.0033\n After long-only clamp: w_EEM=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"EEM": 0.0, "CSHI": 1.0}, "sigma_1": 0.009068, "sigma_2": 0.000512, "covariance": 1e-06, "correlation": 0.1142, "has_text": true, "text_chars": 3020, "mu_floor": 0.0064, "constraint_binding": false}} +{"id": "T4_all_20231116_0118", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ITB"], "decision_date": "2023-11-16", "context_summary": "XLRE \u03c3=0.0135, ITB \u03c3=0.0180, \u03c1=0.756. Min-variance weights: XLRE=1.000, ITB=0.000.", "question": "Assets: XLRE, ITB\nXLRE: annualized_mean_return=-0.0504, daily_std=0.0135\nITB: annualized_mean_return=0.1260, daily_std=0.0180\nMinimum required portfolio return (annualized): 0.0889\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_ITB=X.XXXX", "answer": "w_XLRE=0.2103, w_ITB=0.7897", "answer_numeric": 0.2103, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000324 - 0.000184) / (0.000183 + 0.000324 - 0.000368)\n Unconstrained: w_XLRE=1.0096\n After long-only clamp: w_XLRE=1.0000, w_ITB=0.0000.", "metadata": {"weights": {"XLRE": 0.2103, "ITB": 0.7897}, "sigma_1": 0.013513, "sigma_2": 0.017997, "covariance": 0.000184, "correlation": 0.7563, "has_text": true, "text_chars": 3020, "mu_floor": 0.0889, "constraint_binding": true}} +{"id": "T4_all_20241111_0121", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "CSHI"], "decision_date": "2024-11-11", "context_summary": "XLK \u03c3=0.0143, CSHI \u03c3=0.0004, \u03c1=-0.282. Min-variance weights: XLK=0.009, CSHI=0.991.", "question": "Assets: XLK, CSHI\nXLK: annualized_mean_return=0.3276, daily_std=0.0143\nCSHI: annualized_mean_return=0.0504, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0516\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLK=0.0103, w_CSHI=0.9897", "answer_numeric": 0.0103, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000002) / (0.000205 + 0.000000 - -0.000003)\n Unconstrained: w_XLK=0.0087\n After long-only clamp: w_XLK=0.0087, w_CSHI=0.9913.", "metadata": {"weights": {"XLK": 0.0103, "CSHI": 0.9897}, "sigma_1": 0.01433, "sigma_2": 0.00041, "covariance": -2e-06, "correlation": -0.2824, "has_text": true, "text_chars": 9045, "mu_floor": 0.0516, "constraint_binding": false}} +{"id": "T4_all_20240305_0123", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ICSH"], "decision_date": "2024-03-05", "context_summary": "XLB \u03c3=0.0085, ICSH \u03c3=0.0003, \u03c1=-0.068. Min-variance weights: XLB=0.004, ICSH=0.996.", "question": "Assets: XLB, ICSH\nXLB: annualized_mean_return=0.4032, daily_std=0.0085\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0508\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLB=0.0014, w_ICSH=0.9986", "answer_numeric": 0.0014, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000073 + 0.000000 - -0.000000)\n Unconstrained: w_XLB=0.0038\n After long-only clamp: w_XLB=0.0038, w_ICSH=0.9962.", "metadata": {"weights": {"XLB": 0.0014, "ICSH": 0.9986}, "sigma_1": 0.008536, "sigma_2": 0.000314, "covariance": -0.0, "correlation": -0.0677, "has_text": true, "text_chars": 9045, "mu_floor": 0.0508, "constraint_binding": false}} +{"id": "T4_all_20230302_0125", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SGOV"], "decision_date": "2023-03-02", "context_summary": "VTI \u03c3=0.0109, SGOV \u03c3=0.0001, \u03c1=0.079. Min-variance weights: VTI=0.000, SGOV=1.000.", "question": "Assets: VTI, SGOV\nVTI: annualized_mean_return=-0.0756, daily_std=0.0109\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0329\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_SGOV=X.XXXX", "answer": "w_VTI=0.0002, w_SGOV=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000119 + 0.000000 - 0.000000)\n Unconstrained: w_VTI=-0.0009\n After long-only clamp: w_VTI=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"VTI": 0.0002, "SGOV": 0.9998}, "sigma_1": 0.010929, "sigma_2": 0.000144, "covariance": 0.0, "correlation": 0.0791, "has_text": true, "text_chars": 3020, "mu_floor": 0.0329, "constraint_binding": false}} +{"id": "T4_all_20241015_0127", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "REZ"], "decision_date": "2024-10-15", "context_summary": "LINK-USD \u03c3=0.0333, REZ \u03c3=0.0093, \u03c1=0.016. Min-variance weights: LINK-USD=0.068, REZ=0.932.", "question": "Assets: LINK-USD, REZ\nLINK-USD: annualized_mean_return=0.5796, daily_std=0.0333\nREZ: annualized_mean_return=0.3528, daily_std=0.0093\nMinimum required portfolio return (annualized): 0.3601\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_REZ=X.XXXX", "answer": "w_LINK-USD=0.0682, w_REZ=0.9318", "answer_numeric": 0.0682, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000086 - 0.000005) / (0.001109 + 0.000086 - 0.000010)\n Unconstrained: w_LINK-USD=0.0682\n After long-only clamp: w_LINK-USD=0.0682, w_REZ=0.9318.", "metadata": {"weights": {"LINK-USD": 0.0682, "REZ": 0.9318}, "sigma_1": 0.033307, "sigma_2": 0.009261, "covariance": 5e-06, "correlation": 0.0159, "has_text": true, "text_chars": 20, "mu_floor": 0.3601, "constraint_binding": false}} +{"id": "T4_all_20240701_0129", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "ICSH"], "decision_date": "2024-07-01", "context_summary": "XRP-USD \u03c3=0.0182, ICSH \u03c3=0.0002, \u03c1=0.173. Min-variance weights: XRP-USD=0.000, ICSH=1.000.", "question": "Assets: XRP-USD, ICSH\nXRP-USD: annualized_mean_return=-0.3024, daily_std=0.0182\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.1168\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XRP-USD=0.0000, w_ICSH=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000332 + 0.000000 - 0.000001)\n Unconstrained: w_XRP-USD=-0.0020\n After long-only clamp: w_XRP-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XRP-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.018228, "sigma_2": 0.000231, "covariance": 1e-06, "correlation": 0.1726, "has_text": true, "text_chars": 20, "mu_floor": -0.1168, "constraint_binding": false}} +{"id": "T4_all_20240313_0131", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "TIP"], "decision_date": "2024-03-13", "context_summary": "EFA \u03c3=0.0071, TIP \u03c3=0.0013, \u03c1=-0.042. Min-variance weights: EFA=0.040, TIP=0.960.", "question": "Assets: EFA, TIP\nEFA: annualized_mean_return=0.3276, daily_std=0.0071\nTIP: annualized_mean_return=0.0504, daily_std=0.0013\nMinimum required portfolio return (annualized): 0.0552\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_TIP=X.XXXX", "answer": "w_EFA=0.0333, w_TIP=0.9667", "answer_numeric": 0.0333, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000002 - -0.000000) / (0.000051 + 0.000002 - -0.000001)\n Unconstrained: w_EFA=0.0402\n After long-only clamp: w_EFA=0.0402, w_TIP=0.9598.", "metadata": {"weights": {"EFA": 0.0333, "TIP": 0.9667}, "sigma_1": 0.007106, "sigma_2": 0.001318, "covariance": -0.0, "correlation": -0.0421, "has_text": true, "text_chars": 9045, "mu_floor": 0.0552, "constraint_binding": false}} +{"id": "T4_all_20230526_0134", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "UNG"], "decision_date": "2023-05-26", "context_summary": "XLP \u03c3=0.0065, UNG \u03c3=0.0404, \u03c1=0.229. Min-variance weights: XLP=1.000, UNG=0.000.", "question": "Assets: XLP, UNG\nXLP: annualized_mean_return=0.1260, daily_std=0.0065\nUNG: annualized_mean_return=-0.7308, daily_std=0.0404\nMinimum required portfolio return (annualized): -0.2148\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_UNG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_UNG=X.XXXX", "answer": "w_XLP=1.0000, w_UNG=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001633 - 0.000060) / (0.000042 + 0.001633 - 0.000120)\n Unconstrained: w_XLP=1.0116\n After long-only clamp: w_XLP=1.0000, w_UNG=0.0000.", "metadata": {"weights": {"XLP": 1.0, "UNG": 0.0}, "sigma_1": 0.006457, "sigma_2": 0.040409, "covariance": 6e-05, "correlation": 0.2291, "has_text": true, "text_chars": 3020, "mu_floor": -0.2148, "constraint_binding": false}} +{"id": "T4_all_20230727_0137", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MORT"], "decision_date": "2023-07-27", "context_summary": "FXI \u03c3=0.0180, MORT \u03c3=0.0155, \u03c1=0.450. Min-variance weights: FXI=0.371, MORT=0.629.", "question": "Assets: FXI, MORT\nFXI: annualized_mean_return=0.1260, daily_std=0.0180\nMORT: annualized_mean_return=0.6552, daily_std=0.0155\nMinimum required portfolio return (annualized): 0.2642\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_MORT=X.XXXX", "answer": "w_FXI=0.3702, w_MORT=0.6298", "answer_numeric": 0.3702, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000241 - 0.000126) / (0.000322 + 0.000241 - 0.000251)\n Unconstrained: w_FXI=0.3706\n After long-only clamp: w_FXI=0.3706, w_MORT=0.6294.", "metadata": {"weights": {"FXI": 0.3702, "MORT": 0.6298}, "sigma_1": 0.017955, "sigma_2": 0.015538, "covariance": 0.000126, "correlation": 0.4499, "has_text": true, "text_chars": 3020, "mu_floor": 0.2642, "constraint_binding": false}} +{"id": "T4_all_20230627_0140", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ICSH"], "decision_date": "2023-06-27", "context_summary": "XLK \u03c3=0.0117, ICSH \u03c3=0.0005, \u03c1=0.079. Min-variance weights: XLK=0.000, ICSH=1.000.", "question": "Assets: XLK, ICSH\nXLK: annualized_mean_return=0.5544, daily_std=0.0117\nICSH: annualized_mean_return=0.0252, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.1497\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLK=0.2353, w_ICSH=0.7647", "answer_numeric": 0.2353, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000137 + 0.000000 - 0.000001)\n Unconstrained: w_XLK=-0.0016\n After long-only clamp: w_XLK=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLK": 0.2353, "ICSH": 0.7647}, "sigma_1": 0.011685, "sigma_2": 0.000471, "covariance": 0.0, "correlation": 0.0795, "has_text": true, "text_chars": 3020, "mu_floor": 0.1497, "constraint_binding": true}} +{"id": "T4_all_20240819_0143", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD", "ICSH"], "decision_date": "2024-08-19", "context_summary": "SOL-USD \u03c3=0.0487, ICSH \u03c3=0.0003, \u03c1=-0.307. Min-variance weights: SOL-USD=0.002, ICSH=0.998.", "question": "Assets: SOL-USD, ICSH\nSOL-USD: annualized_mean_return=0.5040, daily_std=0.0487\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0761\nMarket regime: bull\n\nCompute portfolio weights (w_SOL-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_SOL-USD=0.0017, w_ICSH=0.9983", "answer_numeric": 0.0017, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000004) / (0.002376 + 0.000000 - -0.000009)\n Unconstrained: w_SOL-USD=0.0019\n After long-only clamp: w_SOL-USD=0.0019, w_ICSH=0.9981.", "metadata": {"weights": {"SOL-USD": 0.0017, "ICSH": 0.9983}, "sigma_1": 0.048745, "sigma_2": 0.000297, "covariance": -4e-06, "correlation": -0.3075, "has_text": true, "text_chars": 20, "mu_floor": 0.0761, "constraint_binding": false}} +{"id": "T4_all_20230102_0146", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "VNQ"], "decision_date": "2023-01-02", "context_summary": "EEM \u03c3=0.0142, VNQ \u03c3=0.0151, \u03c1=0.589. Min-variance weights: EEM=0.574, VNQ=0.426.", "question": "Assets: EEM, VNQ\nEEM: annualized_mean_return=0.1764, daily_std=0.0142\nVNQ: annualized_mean_return=-0.0756, daily_std=0.0151\nMinimum required portfolio return (annualized): 0.1385\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_VNQ=X.XXXX", "answer": "w_EEM=0.8496, w_VNQ=0.1504", "answer_numeric": 0.8496, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000227 - 0.000126) / (0.000201 + 0.000227 - 0.000252)\n Unconstrained: w_EEM=0.5739\n After long-only clamp: w_EEM=0.5739, w_VNQ=0.4261.", "metadata": {"weights": {"EEM": 0.8496, "VNQ": 0.1504}, "sigma_1": 0.01418, "sigma_2": 0.015072, "covariance": 0.000126, "correlation": 0.5889, "has_text": true, "text_chars": 3020, "mu_floor": 0.1385, "constraint_binding": true}} +{"id": "T4_all_20240702_0149", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNDX"], "decision_date": "2024-07-02", "context_summary": "IVV \u03c3=0.0064, BNDX \u03c3=0.0026, \u03c1=-0.074. Min-variance weights: IVV=0.156, BNDX=0.844.", "question": "Assets: IVV, BNDX\nIVV: annualized_mean_return=0.2772, daily_std=0.0064\nBNDX: annualized_mean_return=-0.0252, daily_std=0.0026\nMinimum required portfolio return (annualized): 0.0013\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_BNDX=X.XXXX", "answer": "w_IVV=0.1528, w_BNDX=0.8472", "answer_numeric": 0.1528, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000007 - -0.000001) / (0.000042 + 0.000007 - -0.000002)\n Unconstrained: w_IVV=0.1560\n After long-only clamp: w_IVV=0.1560, w_BNDX=0.8440.", "metadata": {"weights": {"IVV": 0.1528, "BNDX": 0.8472}, "sigma_1": 0.006445, "sigma_2": 0.002583, "covariance": -1e-06, "correlation": -0.074, "has_text": true, "text_chars": 9045, "mu_floor": 0.0013, "constraint_binding": false}} +{"id": "T4_all_20240814_0151", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "VNQ"], "decision_date": "2024-08-14", "context_summary": "AVAX-USD \u03c3=0.0485, VNQ \u03c3=0.0097, \u03c1=0.253. Min-variance weights: AVAX-USD=0.000, VNQ=1.000.", "question": "Assets: AVAX-USD, VNQ\nAVAX-USD: annualized_mean_return=-1.1592, daily_std=0.0485\nVNQ: annualized_mean_return=0.3528, daily_std=0.0097\nMinimum required portfolio return (annualized): -0.4825\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_AVAX-USD=0.0000, w_VNQ=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000093 - 0.000119) / (0.002352 + 0.000093 - 0.000237)\n Unconstrained: w_AVAX-USD=-0.0115\n After long-only clamp: w_AVAX-USD=0.0000, w_VNQ=1.0000.", "metadata": {"weights": {"AVAX-USD": 0.0, "VNQ": 1.0}, "sigma_1": 0.048497, "sigma_2": 0.009656, "covariance": 0.000119, "correlation": 0.2533, "has_text": true, "text_chars": 20, "mu_floor": -0.4825, "constraint_binding": false}} +{"id": "T4_all_20231121_0154", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "CSHI"], "decision_date": "2023-11-21", "context_summary": "XRP-USD \u03c3=0.0265, CSHI \u03c3=0.0005, \u03c1=0.136. Min-variance weights: XRP-USD=0.000, CSHI=1.000.", "question": "Assets: XRP-USD, CSHI\nXRP-USD: annualized_mean_return=0.8820, daily_std=0.0265\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.2876\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XRP-USD=0.2852, w_CSHI=0.7148", "answer_numeric": 0.2852, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000002) / (0.000704 + 0.000000 - 0.000003)\n Unconstrained: w_XRP-USD=-0.0022\n After long-only clamp: w_XRP-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"XRP-USD": 0.2852, "CSHI": 0.7148}, "sigma_1": 0.026541, "sigma_2": 0.000486, "covariance": 2e-06, "correlation": 0.1356, "has_text": true, "text_chars": 20, "mu_floor": 0.2876, "constraint_binding": true}} +{"id": "T4_all_20230110_0156", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "REZ"], "decision_date": "2023-01-10", "context_summary": "SOL-USD \u03c3=0.0574, REZ \u03c3=0.0158, \u03c1=0.119. Min-variance weights: SOL-USD=0.043, REZ=0.957.", "question": "Assets: SOL-USD, REZ\nSOL-USD: annualized_mean_return=0.0756, daily_std=0.0574\nREZ: annualized_mean_return=0.0504, daily_std=0.0158\nMinimum required portfolio return (annualized): 0.0662\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_REZ=X.XXXX", "answer": "w_SOL-USD=0.6270, w_REZ=0.3730", "answer_numeric": 0.627, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000250 - 0.000108) / (0.003298 + 0.000250 - 0.000215)\n Unconstrained: w_SOL-USD=0.0427\n After long-only clamp: w_SOL-USD=0.0427, w_REZ=0.9573.", "metadata": {"weights": {"SOL-USD": 0.627, "REZ": 0.373}, "sigma_1": 0.057427, "sigma_2": 0.015813, "covariance": 0.000108, "correlation": 0.1186, "has_text": true, "text_chars": 20, "mu_floor": 0.0662, "constraint_binding": true}} +{"id": "T4_all_20240510_0159", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD", "IYR"], "decision_date": "2024-05-10", "context_summary": "MATIC-USD \u03c3=0.0461, IYR \u03c3=0.0106, \u03c1=-0.166. Min-variance weights: MATIC-USD=0.081, IYR=0.919.", "question": "Assets: MATIC-USD, IYR\nMATIC-USD: annualized_mean_return=-2.1168, daily_std=0.0461\nIYR: annualized_mean_return=0.1008, daily_std=0.0106\nMinimum required portfolio return (annualized): -0.5342\nMarket regime: bull\n\nCompute portfolio weights (w_MATIC-USD, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_IYR=X.XXXX", "answer": "w_MATIC-USD=0.0809, w_IYR=0.9191", "answer_numeric": 0.0809, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000113 - -0.000081) / (0.002126 + 0.000113 - -0.000163)\n Unconstrained: w_MATIC-USD=0.0811\n After long-only clamp: w_MATIC-USD=0.0811, w_IYR=0.9189.", "metadata": {"weights": {"MATIC-USD": 0.0809, "IYR": 0.9191}, "sigma_1": 0.046108, "sigma_2": 0.010645, "covariance": -8.1e-05, "correlation": -0.1659, "has_text": true, "text_chars": 20, "mu_floor": -0.5342, "constraint_binding": false}} +{"id": "T4_all_20230227_0162", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD"], "decision_date": "2023-02-27", "context_summary": "XLF \u03c3=0.0098, SOL-USD \u03c3=0.0697, \u03c1=-0.077. Min-variance weights: XLF=0.971, SOL-USD=0.029.", "question": "Assets: XLF, SOL-USD\nXLF: annualized_mean_return=0.0504, daily_std=0.0097\nSOL-USD: annualized_mean_return=4.1076, daily_std=0.0697\nMinimum required portfolio return (annualized): 2.9773\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_SOL-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_SOL-USD=X.XXXX", "answer": "w_XLF=0.2786, w_SOL-USD=0.7214", "answer_numeric": 0.2786, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.004857 - -0.000052) / (0.000095 + 0.004857 - -0.000104)\n Unconstrained: w_XLF=0.9709\n After long-only clamp: w_XLF=0.9709, w_SOL-USD=0.0291.", "metadata": {"weights": {"XLF": 0.2786, "SOL-USD": 0.7214}, "sigma_1": 0.00975, "sigma_2": 0.069691, "covariance": -5.2e-05, "correlation": -0.0768, "has_text": true, "text_chars": 9046, "mu_floor": 2.9773, "constraint_binding": true}} +{"id": "T4_all_20240104_0165", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SLV"], "decision_date": "2024-01-04", "context_summary": "VLUE \u03c3=0.0094, SLV \u03c3=0.0155, \u03c1=0.030. Min-variance weights: VLUE=0.736, SLV=0.264.", "question": "Assets: VLUE, SLV\nVLUE: annualized_mean_return=0.5040, daily_std=0.0094\nSLV: annualized_mean_return=0.2016, daily_std=0.0155\nMinimum required portfolio return (annualized): 0.2965\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_SLV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_SLV=X.XXXX", "answer": "w_VLUE=0.7352, w_SLV=0.2648", "answer_numeric": 0.7352, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000239 - 0.000004) / (0.000089 + 0.000239 - 0.000009)\n Unconstrained: w_VLUE=0.7358\n After long-only clamp: w_VLUE=0.7358, w_SLV=0.2642.", "metadata": {"weights": {"VLUE": 0.7352, "SLV": 0.2648}, "sigma_1": 0.009418, "sigma_2": 0.015463, "covariance": 4e-06, "correlation": 0.0303, "has_text": true, "text_chars": 3020, "mu_floor": 0.2965, "constraint_binding": false}} +{"id": "T4_all_20230807_0168", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "CSHI"], "decision_date": "2023-08-07", "context_summary": "BNB-USD \u03c3=0.0223, CSHI \u03c3=0.0004, \u03c1=0.232. Min-variance weights: BNB-USD=0.000, CSHI=1.000.", "question": "Assets: BNB-USD, CSHI\nBNB-USD: annualized_mean_return=-0.2268, daily_std=0.0223\nCSHI: annualized_mean_return=0.0504, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0057\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_BNB-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000002) / (0.000499 + 0.000000 - 0.000004)\n Unconstrained: w_BNB-USD=-0.0041\n After long-only clamp: w_BNB-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"BNB-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.022334, "sigma_2": 0.00043, "covariance": 2e-06, "correlation": 0.2319, "has_text": true, "text_chars": 20, "mu_floor": 0.0057, "constraint_binding": false}} +{"id": "T4_all_20240325_0171", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD", "FXI"], "decision_date": "2024-03-25", "context_summary": "DOT-USD \u03c3=0.0404, FXI \u03c3=0.0188, \u03c1=-0.051. Min-variance weights: DOT-USD=0.190, FXI=0.810.", "question": "Assets: DOT-USD, FXI\nDOT-USD: annualized_mean_return=1.7640, daily_std=0.0404\nFXI: annualized_mean_return=0.0504, daily_std=0.0188\nMinimum required portfolio return (annualized): 0.1957\nMarket regime: bull\n\nCompute portfolio weights (w_DOT-USD, w_FXI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_FXI=X.XXXX", "answer": "w_DOT-USD=0.1904, w_FXI=0.8096", "answer_numeric": 0.1904, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000354 - -0.000039) / (0.001634 + 0.000354 - -0.000077)\n Unconstrained: w_DOT-USD=0.1903\n After long-only clamp: w_DOT-USD=0.1903, w_FXI=0.8097.", "metadata": {"weights": {"DOT-USD": 0.1904, "FXI": 0.8096}, "sigma_1": 0.040424, "sigma_2": 0.018828, "covariance": -3.9e-05, "correlation": -0.0509, "has_text": true, "text_chars": 20, "mu_floor": 0.1957, "constraint_binding": false}} +{"id": "T4_all_20240101_0173", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "IEF"], "decision_date": "2024-01-01", "context_summary": "MTUM \u03c3=0.0085, IEF \u03c3=0.0057, \u03c1=0.151. Min-variance weights: MTUM=0.283, IEF=0.717.", "question": "Assets: MTUM, IEF\nMTUM: annualized_mean_return=0.5292, daily_std=0.0085\nIEF: annualized_mean_return=0.2772, daily_std=0.0057\nMinimum required portfolio return (annualized): 0.3168\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_IEF) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_IEF=X.XXXX", "answer": "w_MTUM=0.2849, w_IEF=0.7151", "answer_numeric": 0.2849, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000033 - 0.000007) / (0.000072 + 0.000033 - 0.000015)\n Unconstrained: w_MTUM=0.2831\n After long-only clamp: w_MTUM=0.2831, w_IEF=0.7169.", "metadata": {"weights": {"MTUM": 0.2849, "IEF": 0.7151}, "sigma_1": 0.00849, "sigma_2": 0.005738, "covariance": 7e-06, "correlation": 0.1514, "has_text": true, "text_chars": 3020, "mu_floor": 0.3168, "constraint_binding": false}} +{"id": "T4_all_20230811_0176", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "INDS"], "decision_date": "2023-08-11", "context_summary": "DOT-USD \u03c3=0.0237, INDS \u03c3=0.0108, \u03c1=0.087. Min-variance weights: DOT-USD=0.149, INDS=0.851.", "question": "Assets: DOT-USD, INDS\nDOT-USD: annualized_mean_return=0.5040, daily_std=0.0237\nINDS: annualized_mean_return=-0.1764, daily_std=0.0108\nMinimum required portfolio return (annualized): 0.3311\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_INDS=X.XXXX", "answer": "w_DOT-USD=0.7459, w_INDS=0.2541", "answer_numeric": 0.7459, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000117 - 0.000022) / (0.000563 + 0.000117 - 0.000044)\n Unconstrained: w_DOT-USD=0.1487\n After long-only clamp: w_DOT-USD=0.1487, w_INDS=0.8513.", "metadata": {"weights": {"DOT-USD": 0.7459, "INDS": 0.2541}, "sigma_1": 0.023738, "sigma_2": 0.010804, "covariance": 2.2e-05, "correlation": 0.0865, "has_text": true, "text_chars": 20, "mu_floor": 0.3311, "constraint_binding": true}} +{"id": "T4_all_20241211_0179", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD", "ICSH"], "decision_date": "2024-12-11", "context_summary": "ETH-USD \u03c3=0.0368, ICSH \u03c3=0.0003, \u03c1=0.039. Min-variance weights: ETH-USD=0.000, ICSH=1.000.", "question": "Assets: ETH-USD, ICSH\nETH-USD: annualized_mean_return=1.8396, daily_std=0.0368\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\n\nCompute portfolio weights (w_ETH-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_ETH-USD=0.0001, w_ICSH=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.001353 + 0.000000 - 0.000001)\n Unconstrained: w_ETH-USD=-0.0002\n After long-only clamp: w_ETH-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0001, "ICSH": 0.9999}, "sigma_1": 0.036777, "sigma_2": 0.000279, "covariance": 0.0, "correlation": 0.0395, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240222_0182", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "HAUZ"], "decision_date": "2024-02-22", "context_summary": "XLF \u03c3=0.0068, HAUZ \u03c3=0.0105, \u03c1=0.594. Min-variance weights: XLF=0.942, HAUZ=0.058.", "question": "Assets: XLF, HAUZ\nXLF: annualized_mean_return=0.5040, daily_std=0.0068\nHAUZ: annualized_mean_return=0.1512, daily_std=0.0105\nMinimum required portfolio return (annualized): 0.4952\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_XLF=0.9751, w_HAUZ=0.0249", "answer_numeric": 0.9751, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000110 - 0.000042) / (0.000047 + 0.000110 - 0.000085)\n Unconstrained: w_XLF=0.9424\n After long-only clamp: w_XLF=0.9424, w_HAUZ=0.0576.", "metadata": {"weights": {"XLF": 0.9751, "HAUZ": 0.0249}, "sigma_1": 0.006826, "sigma_2": 0.010473, "covariance": 4.2e-05, "correlation": 0.5944, "has_text": true, "text_chars": 9046, "mu_floor": 0.4952, "constraint_binding": true}} +{"id": "T4_all_20240425_0185", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "IYR"], "decision_date": "2024-04-25", "context_summary": "USMV \u03c3=0.0049, IYR \u03c3=0.0110, \u03c1=0.737. Min-variance weights: USMV=1.000, IYR=0.000.", "question": "Assets: USMV, IYR\nUSMV: annualized_mean_return=0.0756, daily_std=0.0049\nIYR: annualized_mean_return=-0.1764, daily_std=0.0110\nMinimum required portfolio return (annualized): 0.0556\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_IYR=X.XXXX", "answer": "w_USMV=1.0000, w_IYR=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000122 - 0.000040) / (0.000024 + 0.000122 - 0.000080)\n Unconstrained: w_USMV=1.2399\n After long-only clamp: w_USMV=1.0000, w_IYR=0.0000.", "metadata": {"weights": {"USMV": 1.0, "IYR": 0.0}, "sigma_1": 0.004921, "sigma_2": 0.011038, "covariance": 4e-05, "correlation": 0.7372, "has_text": true, "text_chars": 9045, "mu_floor": 0.0556, "constraint_binding": false}} +{"id": "T4_all_20240430_0188", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "DBC"], "decision_date": "2024-04-30", "context_summary": "ETH-USD \u03c3=0.0376, DBC \u03c3=0.0059, \u03c1=0.220. Min-variance weights: ETH-USD=0.000, DBC=1.000.", "question": "Assets: ETH-USD, DBC\nETH-USD: annualized_mean_return=0.0252, daily_std=0.0376\nDBC: annualized_mean_return=0.3528, daily_std=0.0059\nMinimum required portfolio return (annualized): 0.2909\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_DBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_DBC=X.XXXX", "answer": "w_ETH-USD=0.0000, w_DBC=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000035 - 0.000049) / (0.001414 + 0.000035 - 0.000098)\n Unconstrained: w_ETH-USD=-0.0104\n After long-only clamp: w_ETH-USD=0.0000, w_DBC=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "DBC": 1.0}, "sigma_1": 0.037597, "sigma_2": 0.005907, "covariance": 4.9e-05, "correlation": 0.2201, "has_text": true, "text_chars": 20, "mu_floor": 0.2909, "constraint_binding": false}} +{"id": "T4_all_20230915_0190", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "ICSH"], "decision_date": "2023-09-15", "context_summary": "MATIC-USD \u03c3=0.0235, ICSH \u03c3=0.0003, \u03c1=-0.075. Min-variance weights: MATIC-USD=0.001, ICSH=0.999.", "question": "Assets: MATIC-USD, ICSH\nMATIC-USD: annualized_mean_return=-1.5372, daily_std=0.0235\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0503\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MATIC-USD=0.0001, w_ICSH=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000552 + 0.000000 - -0.000001)\n Unconstrained: w_MATIC-USD=0.0010\n After long-only clamp: w_MATIC-USD=0.0010, w_ICSH=0.9990.", "metadata": {"weights": {"MATIC-USD": 0.0001, "ICSH": 0.9999}, "sigma_1": 0.023491, "sigma_2": 0.000279, "covariance": -0.0, "correlation": -0.075, "has_text": true, "text_chars": 20, "mu_floor": 0.0503, "constraint_binding": true}} +{"id": "T4_all_20230912_0193", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "TLT"], "decision_date": "2023-09-12", "context_summary": "XLE \u03c3=0.0109, TLT \u03c3=0.0097, \u03c1=0.160. Min-variance weights: XLE=0.431, TLT=0.569.", "question": "Assets: XLE, TLT\nXLE: annualized_mean_return=0.5544, daily_std=0.0109\nTLT: annualized_mean_return=-0.4284, daily_std=0.0097\nMinimum required portfolio return (annualized): -0.0582\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_TLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLE=X.XXXX, w_TLT=X.XXXX", "answer": "w_XLE=0.4310, w_TLT=0.5690", "answer_numeric": 0.431, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000094 - 0.000017) / (0.000119 + 0.000094 - 0.000034)\n Unconstrained: w_XLE=0.4311\n After long-only clamp: w_XLE=0.4311, w_TLT=0.5689.", "metadata": {"weights": {"XLE": 0.431, "TLT": 0.569}, "sigma_1": 0.010908, "sigma_2": 0.009709, "covariance": 1.7e-05, "correlation": 0.1602, "has_text": true, "text_chars": 3020, "mu_floor": -0.0582, "constraint_binding": false}} +{"id": "T4_all_20240827_0196", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MATIC-USD", "ICSH"], "decision_date": "2024-08-27", "context_summary": "MATIC-USD \u03c3=0.0451, ICSH \u03c3=0.0003, \u03c1=-0.125. Min-variance weights: MATIC-USD=0.001, ICSH=0.999.", "question": "Assets: MATIC-USD, ICSH\nMATIC-USD: annualized_mean_return=-0.2520, daily_std=0.0451\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0753\nMarket regime: bull\n\nCompute portfolio weights (w_MATIC-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MATIC-USD=0.0009, w_ICSH=0.9991", "answer_numeric": 0.0009, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000002) / (0.002038 + 0.000000 - -0.000003)\n Unconstrained: w_MATIC-USD=0.0008\n After long-only clamp: w_MATIC-USD=0.0008, w_ICSH=0.9992.", "metadata": {"weights": {"MATIC-USD": 0.0009, "ICSH": 0.9991}, "sigma_1": 0.04514, "sigma_2": 0.000288, "covariance": -2e-06, "correlation": -0.1251, "has_text": true, "text_chars": 20, "mu_floor": 0.0753, "constraint_binding": true}} +{"id": "T4_all_20241010_0197", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "DBB"], "decision_date": "2024-10-10", "context_summary": "USMV \u03c3=0.0059, DBB \u03c3=0.0126, \u03c1=0.336. Min-variance weights: USMV=0.929, DBB=0.071.", "question": "Assets: USMV, DBB\nUSMV: annualized_mean_return=0.2520, daily_std=0.0059\nDBB: annualized_mean_return=0.2268, daily_std=0.0126\nMinimum required portfolio return (annualized): 0.2497\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_DBB=X.XXXX", "answer": "w_USMV=0.9290, w_DBB=0.0710", "answer_numeric": 0.929, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000158 - 0.000025) / (0.000035 + 0.000158 - 0.000050)\n Unconstrained: w_USMV=0.9290\n After long-only clamp: w_USMV=0.9290, w_DBB=0.0710.", "metadata": {"weights": {"USMV": 0.929, "DBB": 0.071}, "sigma_1": 0.005929, "sigma_2": 0.012561, "covariance": 2.5e-05, "correlation": 0.3356, "has_text": true, "text_chars": 9045, "mu_floor": 0.2497, "constraint_binding": false}} +{"id": "T4_all_20241209_0200", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD", "TIP"], "decision_date": "2024-12-09", "context_summary": "ADA-USD \u03c3=0.0576, TIP \u03c3=0.0011, \u03c1=0.236. Min-variance weights: ADA-USD=0.000, TIP=1.000.", "question": "Assets: ADA-USD, TIP\nADA-USD: annualized_mean_return=5.6952, daily_std=0.0576\nTIP: annualized_mean_return=0.0252, daily_std=0.0011\nMinimum required portfolio return (annualized): 3.9342\nMarket regime: bull\n\nCompute portfolio weights (w_ADA-USD, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_TIP=X.XXXX", "answer": "w_ADA-USD=0.6894, w_TIP=0.3106", "answer_numeric": 0.6894, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000015) / (0.003317 + 0.000001 - 0.000030)\n Unconstrained: w_ADA-USD=-0.0042\n After long-only clamp: w_ADA-USD=0.0000, w_TIP=1.0000.", "metadata": {"weights": {"ADA-USD": 0.6894, "TIP": 0.3106}, "sigma_1": 0.05759, "sigma_2": 0.001109, "covariance": 1.5e-05, "correlation": 0.2363, "has_text": true, "text_chars": 20, "mu_floor": 3.9342, "constraint_binding": true}} +{"id": "T4_all_20240920_0203", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "VNQI"], "decision_date": "2024-09-20", "context_summary": "ADA-USD \u03c3=0.0342, VNQI \u03c3=0.0087, \u03c1=-0.044. Min-variance weights: ADA-USD=0.070, VNQI=0.930.", "question": "Assets: ADA-USD, VNQI\nADA-USD: annualized_mean_return=-0.8568, daily_std=0.0342\nVNQI: annualized_mean_return=0.5292, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.2552\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_ADA-USD=0.0699, w_VNQI=0.9301", "answer_numeric": 0.0699, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000076 - -0.000013) / (0.001170 + 0.000076 - -0.000026)\n Unconstrained: w_ADA-USD=0.0701\n After long-only clamp: w_ADA-USD=0.0701, w_VNQI=0.9299.", "metadata": {"weights": {"ADA-USD": 0.0699, "VNQI": 0.9301}, "sigma_1": 0.034207, "sigma_2": 0.008715, "covariance": -1.3e-05, "correlation": -0.0443, "has_text": true, "text_chars": 20, "mu_floor": 0.2552, "constraint_binding": false}} +{"id": "T4_all_20230120_0205", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "XRP-USD"], "decision_date": "2023-01-20", "context_summary": "FXI \u03c3=0.0254, XRP-USD \u03c3=0.0243, \u03c1=0.078. Min-variance weights: FXI=0.476, XRP-USD=0.524.", "question": "Assets: FXI, XRP-USD\nFXI: annualized_mean_return=1.2852, daily_std=0.0254\nXRP-USD: annualized_mean_return=0.4284, daily_std=0.0243\nMinimum required portfolio return (annualized): 0.6799\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_XRP-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_XRP-USD=X.XXXX", "answer": "w_FXI=0.4756, w_XRP-USD=0.5244", "answer_numeric": 0.4756, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000590 - 0.000048) / (0.000645 + 0.000590 - 0.000096)\n Unconstrained: w_FXI=0.4756\n After long-only clamp: w_FXI=0.4756, w_XRP-USD=0.5244.", "metadata": {"weights": {"FXI": 0.4756, "XRP-USD": 0.5244}, "sigma_1": 0.025405, "sigma_2": 0.024286, "covariance": 4.8e-05, "correlation": 0.0777, "has_text": true, "text_chars": 3020, "mu_floor": 0.6799, "constraint_binding": false}} +{"id": "T4_all_20231019_0207", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "DBA"], "decision_date": "2023-10-19", "context_summary": "IWM \u03c3=0.0098, DBA \u03c3=0.0064, \u03c1=-0.028. Min-variance weights: IWM=0.302, DBA=0.698.", "question": "Assets: IWM, DBA\nIWM: annualized_mean_return=-0.5292, daily_std=0.0098\nDBA: annualized_mean_return=-0.1008, daily_std=0.0064\nMinimum required portfolio return (annualized): -0.2881\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_DBA=X.XXXX", "answer": "w_IWM=0.3024, w_DBA=0.6976", "answer_numeric": 0.3024, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000041 - -0.000002) / (0.000096 + 0.000041 - -0.000003)\n Unconstrained: w_IWM=0.3017\n After long-only clamp: w_IWM=0.3017, w_DBA=0.6983.", "metadata": {"weights": {"IWM": 0.3024, "DBA": 0.6976}, "sigma_1": 0.009808, "sigma_2": 0.00637, "covariance": -2e-06, "correlation": -0.0276, "has_text": true, "text_chars": 3020, "mu_floor": -0.2881, "constraint_binding": false}} +{"id": "T4_all_20230414_0209", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "DBB"], "decision_date": "2023-04-14", "context_summary": "ADA-USD \u03c3=0.0370, DBB \u03c3=0.0119, \u03c1=0.202. Min-variance weights: ADA-USD=0.039, DBB=0.961.", "question": "Assets: ADA-USD, DBB\nADA-USD: annualized_mean_return=0.8316, daily_std=0.0370\nDBB: annualized_mean_return=-0.3528, daily_std=0.0119\nMinimum required portfolio return (annualized): -0.3182\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_DBB=X.XXXX", "answer": "w_ADA-USD=0.0396, w_DBB=0.9604", "answer_numeric": 0.0396, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000142 - 0.000089) / (0.001372 + 0.000142 - 0.000179)\n Unconstrained: w_ADA-USD=0.0393\n After long-only clamp: w_ADA-USD=0.0393, w_DBB=0.9607.", "metadata": {"weights": {"ADA-USD": 0.0396, "DBB": 0.9604}, "sigma_1": 0.037046, "sigma_2": 0.011911, "covariance": 8.9e-05, "correlation": 0.2024, "has_text": true, "text_chars": 20, "mu_floor": -0.3182, "constraint_binding": false}} +{"id": "T4_all_20230106_0211", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "XLP"], "decision_date": "2023-01-06", "context_summary": "XRP-USD \u03c3=0.0473, XLP \u03c3=0.0096, \u03c1=-0.313. Min-variance weights: XRP-USD=0.089, XLP=0.911.", "question": "Assets: XRP-USD, XLP\nXRP-USD: annualized_mean_return=-1.1088, daily_std=0.0473\nXLP: annualized_mean_return=0.4536, daily_std=0.0096\nMinimum required portfolio return (annualized): -0.3653\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_XLP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_XLP=X.XXXX", "answer": "w_XRP-USD=0.0892, w_XLP=0.9108", "answer_numeric": 0.0892, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000091 - -0.000142) / (0.002242 + 0.000091 - -0.000284)\n Unconstrained: w_XRP-USD=0.0892\n After long-only clamp: w_XRP-USD=0.0892, w_XLP=0.9108.", "metadata": {"weights": {"XRP-USD": 0.0892, "XLP": 0.9108}, "sigma_1": 0.047346, "sigma_2": 0.009564, "covariance": -0.000142, "correlation": -0.3133, "has_text": true, "text_chars": 20, "mu_floor": -0.3653, "constraint_binding": false}} +{"id": "T4_all_20241224_0213", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "VCIT"], "decision_date": "2024-12-24", "context_summary": "XLRE \u03c3=0.0108, VCIT \u03c3=0.0035, \u03c1=0.221. Min-variance weights: XLRE=0.034, VCIT=0.966.", "question": "Assets: XLRE, VCIT\nXLRE: annualized_mean_return=-0.3276, daily_std=0.0108\nVCIT: annualized_mean_return=-0.1008, daily_std=0.0035\nMinimum required portfolio return (annualized): -0.1491\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_VCIT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_VCIT=X.XXXX", "answer": "w_XLRE=0.0360, w_VCIT=0.9640", "answer_numeric": 0.036, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000012 - 0.000008) / (0.000116 + 0.000012 - 0.000016)\n Unconstrained: w_XLRE=0.0340\n After long-only clamp: w_XLRE=0.0340, w_VCIT=0.9660.", "metadata": {"weights": {"XLRE": 0.036, "VCIT": 0.964}, "sigma_1": 0.010753, "sigma_2": 0.003467, "covariance": 8e-06, "correlation": 0.2211, "has_text": true, "text_chars": 9045, "mu_floor": -0.1491, "constraint_binding": false}} +{"id": "T4_all_20240614_0215", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "BNDX"], "decision_date": "2024-06-14", "context_summary": "AVAX-USD \u03c3=0.0415, BNDX \u03c3=0.0026, \u03c1=-0.082. Min-variance weights: AVAX-USD=0.009, BNDX=0.991.", "question": "Assets: AVAX-USD, BNDX\nAVAX-USD: annualized_mean_return=-0.5796, daily_std=0.0415\nBNDX: annualized_mean_return=0.0000, daily_std=0.0026\nMinimum required portfolio return (annualized): -0.3117\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_BNDX=X.XXXX", "answer": "w_AVAX-USD=0.0091, w_BNDX=0.9909", "answer_numeric": 0.0091, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000007 - -0.000009) / (0.001720 + 0.000007 - -0.000018)\n Unconstrained: w_AVAX-USD=0.0091\n After long-only clamp: w_AVAX-USD=0.0091, w_BNDX=0.9909.", "metadata": {"weights": {"AVAX-USD": 0.0091, "BNDX": 0.9909}, "sigma_1": 0.041474, "sigma_2": 0.002634, "covariance": -9e-06, "correlation": -0.0817, "has_text": true, "text_chars": 20, "mu_floor": -0.3117, "constraint_binding": false}} +{"id": "T4_all_20240725_0217", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "DOT-USD"], "decision_date": "2024-07-25", "context_summary": "XLV \u03c3=0.0063, DOT-USD \u03c3=0.0347, \u03c1=-0.135. Min-variance weights: XLV=0.947, DOT-USD=0.053.", "question": "Assets: XLV, DOT-USD\nXLV: annualized_mean_return=0.3024, daily_std=0.0063\nDOT-USD: annualized_mean_return=-0.9324, daily_std=0.0347\nMinimum required portfolio return (annualized): 0.1858\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_DOT-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLV=X.XXXX, w_DOT-USD=X.XXXX", "answer": "w_XLV=0.9466, w_DOT-USD=0.0534", "answer_numeric": 0.9466, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001204 - -0.000030) / (0.000040 + 0.001204 - -0.000059)\n Unconstrained: w_XLV=0.9470\n After long-only clamp: w_XLV=0.9470, w_DOT-USD=0.0530.", "metadata": {"weights": {"XLV": 0.9466, "DOT-USD": 0.0534}, "sigma_1": 0.00629, "sigma_2": 0.034701, "covariance": -3e-05, "correlation": -0.1354, "has_text": true, "text_chars": 9047, "mu_floor": 0.1858, "constraint_binding": false}} +{"id": "T4_all_20240212_0219", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "PALL"], "decision_date": "2024-02-12", "context_summary": "DOT-USD \u03c3=0.0468, PALL \u03c3=0.0237, \u03c1=-0.138. Min-variance weights: DOT-USD=0.234, PALL=0.766.", "question": "Assets: DOT-USD, PALL\nDOT-USD: annualized_mean_return=-0.0252, daily_std=0.0468\nPALL: annualized_mean_return=-1.1592, daily_std=0.0237\nMinimum required portfolio return (annualized): -1.0120\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_PALL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_PALL=X.XXXX", "answer": "w_DOT-USD=0.2337, w_PALL=0.7663", "answer_numeric": 0.2337, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000562 - -0.000153) / (0.002191 + 0.000562 - -0.000305)\n Unconstrained: w_DOT-USD=0.2336\n After long-only clamp: w_DOT-USD=0.2336, w_PALL=0.7664.", "metadata": {"weights": {"DOT-USD": 0.2337, "PALL": 0.7663}, "sigma_1": 0.046803, "sigma_2": 0.023699, "covariance": -0.000153, "correlation": -0.1376, "has_text": true, "text_chars": 20, "mu_floor": -1.012, "constraint_binding": false}} +{"id": "T4_all_20241021_0221", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "GLD"], "decision_date": "2024-10-21", "context_summary": "ADA-USD \u03c3=0.0281, GLD \u03c3=0.0083, \u03c1=0.177. Min-variance weights: ADA-USD=0.035, GLD=0.965.", "question": "Assets: ADA-USD, GLD\nADA-USD: annualized_mean_return=0.0504, daily_std=0.0281\nGLD: annualized_mean_return=0.5040, daily_std=0.0083\nMinimum required portfolio return (annualized): 0.4581\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_GLD=X.XXXX", "answer": "w_ADA-USD=0.0354, w_GLD=0.9646", "answer_numeric": 0.0354, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000068 - 0.000041) / (0.000789 + 0.000068 - 0.000082)\n Unconstrained: w_ADA-USD=0.0352\n After long-only clamp: w_ADA-USD=0.0352, w_GLD=0.9648.", "metadata": {"weights": {"ADA-USD": 0.0354, "GLD": 0.9646}, "sigma_1": 0.028082, "sigma_2": 0.008273, "covariance": 4.1e-05, "correlation": 0.1771, "has_text": true, "text_chars": 20, "mu_floor": 0.4581, "constraint_binding": false}} +{"id": "T4_all_20230425_0224", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DBB"], "decision_date": "2023-04-25", "context_summary": "XLP \u03c3=0.0066, DBB \u03c3=0.0119, \u03c1=-0.193. Min-variance weights: XLP=0.726, DBB=0.274.", "question": "Assets: XLP, DBB\nXLP: annualized_mean_return=0.2268, daily_std=0.0066\nDBB: annualized_mean_return=-0.4284, daily_std=0.0119\nMinimum required portfolio return (annualized): 0.1375\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_DBB=X.XXXX", "answer": "w_XLP=0.8637, w_DBB=0.1363", "answer_numeric": 0.8637, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000141 - -0.000015) / (0.000044 + 0.000141 - -0.000030)\n Unconstrained: w_XLP=0.7260\n After long-only clamp: w_XLP=0.7260, w_DBB=0.2740.", "metadata": {"weights": {"XLP": 0.8637, "DBB": 0.1363}, "sigma_1": 0.00662, "sigma_2": 0.011883, "covariance": -1.5e-05, "correlation": -0.1931, "has_text": true, "text_chars": 3020, "mu_floor": 0.1375, "constraint_binding": true}} +{"id": "T4_all_20240111_0227", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LQD"], "decision_date": "2024-01-11", "context_summary": "XLF \u03c3=0.0085, LQD \u03c3=0.0061, \u03c1=0.200. Min-variance weights: XLF=0.298, LQD=0.702.", "question": "Assets: XLF, LQD\nXLF: annualized_mean_return=0.5544, daily_std=0.0085\nLQD: annualized_mean_return=0.4032, daily_std=0.0061\nMinimum required portfolio return (annualized): 0.4338\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_LQD=X.XXXX", "answer": "w_XLF=0.2996, w_LQD=0.7004", "answer_numeric": 0.2996, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000037 - 0.000010) / (0.000073 + 0.000037 - 0.000021)\n Unconstrained: w_XLF=0.2981\n After long-only clamp: w_XLF=0.2981, w_LQD=0.7019.", "metadata": {"weights": {"XLF": 0.2996, "LQD": 0.7004}, "sigma_1": 0.008527, "sigma_2": 0.006068, "covariance": 1e-05, "correlation": 0.1998, "has_text": true, "text_chars": 3020, "mu_floor": 0.4338, "constraint_binding": false}} +{"id": "T4_all_20230711_0229", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "TLH"], "decision_date": "2023-07-11", "context_summary": "DOT-USD \u03c3=0.0250, TLH \u03c3=0.0079, \u03c1=0.168. Min-variance weights: DOT-USD=0.046, TLH=0.954.", "question": "Assets: DOT-USD, TLH\nDOT-USD: annualized_mean_return=-0.0504, daily_std=0.0250\nTLH: annualized_mean_return=-0.1260, daily_std=0.0079\nMinimum required portfolio return (annualized): -0.1225\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_TLH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_TLH=X.XXXX", "answer": "w_DOT-USD=0.0464, w_TLH=0.9536", "answer_numeric": 0.0464, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000062 - 0.000033) / (0.000625 + 0.000062 - 0.000066)\n Unconstrained: w_DOT-USD=0.0464\n After long-only clamp: w_DOT-USD=0.0464, w_TLH=0.9536.", "metadata": {"weights": {"DOT-USD": 0.0464, "TLH": 0.9536}, "sigma_1": 0.025009, "sigma_2": 0.007864, "covariance": 3.3e-05, "correlation": 0.1679, "has_text": true, "text_chars": 20, "mu_floor": -0.1225, "constraint_binding": false}} +{"id": "T4_all_20231205_0232", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "EWJ"], "decision_date": "2023-12-05", "context_summary": "BNB-USD \u03c3=0.0229, EWJ \u03c3=0.0100, \u03c1=-0.402. Min-variance weights: BNB-USD=0.239, EWJ=0.761.", "question": "Assets: BNB-USD, EWJ\nBNB-USD: annualized_mean_return=0.5040, daily_std=0.0229\nEWJ: annualized_mean_return=0.0504, daily_std=0.0100\nMinimum required portfolio return (annualized): 0.4117\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_EWJ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_EWJ=X.XXXX", "answer": "w_BNB-USD=0.7965, w_EWJ=0.2035", "answer_numeric": 0.7965, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000101 - -0.000092) / (0.000523 + 0.000101 - -0.000185)\n Unconstrained: w_BNB-USD=0.2391\n After long-only clamp: w_BNB-USD=0.2391, w_EWJ=0.7609.", "metadata": {"weights": {"BNB-USD": 0.7965, "EWJ": 0.2035}, "sigma_1": 0.022867, "sigma_2": 0.010049, "covariance": -9.2e-05, "correlation": -0.4017, "has_text": true, "text_chars": 20, "mu_floor": 0.4117, "constraint_binding": true}} +{"id": "T4_all_20241210_0234", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "BIL"], "decision_date": "2024-12-10", "context_summary": "XLY \u03c3=0.0106, BIL \u03c3=0.0002, \u03c1=0.110. Min-variance weights: XLY=0.000, BIL=1.000.", "question": "Assets: XLY, BIL\nXLY: annualized_mean_return=0.8064, daily_std=0.0106\nBIL: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.6233\nMarket regime: bull\n\nCompute portfolio weights (w_XLY, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLY=0.7495, w_BIL=0.2505", "answer_numeric": 0.7495, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000113 + 0.000000 - 0.000000)\n Unconstrained: w_XLY=-0.0015\n After long-only clamp: w_XLY=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLY": 0.7495, "BIL": 0.2505}, "sigma_1": 0.010626, "sigma_2": 0.000173, "covariance": 0.0, "correlation": 0.1102, "has_text": true, "text_chars": 9045, "mu_floor": 0.6233, "constraint_binding": true}} +{"id": "T4_all_20230908_0237", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "INDS"], "decision_date": "2023-09-08", "context_summary": "BTC-USD \u03c3=0.0174, INDS \u03c3=0.0101, \u03c1=0.085. Min-variance weights: BTC-USD=0.231, INDS=0.769.", "question": "Assets: BTC-USD, INDS\nBTC-USD: annualized_mean_return=-0.5544, daily_std=0.0174\nINDS: annualized_mean_return=-0.1008, daily_std=0.0101\nMinimum required portfolio return (annualized): -0.2231\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_INDS=X.XXXX", "answer": "w_BTC-USD=0.2308, w_INDS=0.7692", "answer_numeric": 0.2308, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000101 - 0.000015) / (0.000303 + 0.000101 - 0.000030)\n Unconstrained: w_BTC-USD=0.2309\n After long-only clamp: w_BTC-USD=0.2309, w_INDS=0.7691.", "metadata": {"weights": {"BTC-USD": 0.2308, "INDS": 0.7692}, "sigma_1": 0.0174, "sigma_2": 0.010066, "covariance": 1.5e-05, "correlation": 0.0853, "has_text": true, "text_chars": 20, "mu_floor": -0.2231, "constraint_binding": false}} +{"id": "T4_all_20241118_0240", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "XHB"], "decision_date": "2024-11-18", "context_summary": "SOL-USD \u03c3=0.0372, XHB \u03c3=0.0145, \u03c1=0.071. Min-variance weights: SOL-USD=0.112, XHB=0.888.", "question": "Assets: SOL-USD, XHB\nSOL-USD: annualized_mean_return=2.5956, daily_std=0.0372\nXHB: annualized_mean_return=0.0756, daily_std=0.0145\nMinimum required portfolio return (annualized): 2.0436\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_XHB=X.XXXX", "answer": "w_SOL-USD=0.7810, w_XHB=0.2190", "answer_numeric": 0.781, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000209 - 0.000038) / (0.001387 + 0.000209 - 0.000077)\n Unconstrained: w_SOL-USD=0.1124\n After long-only clamp: w_SOL-USD=0.1124, w_XHB=0.8876.", "metadata": {"weights": {"SOL-USD": 0.781, "XHB": 0.219}, "sigma_1": 0.037241, "sigma_2": 0.014465, "covariance": 3.8e-05, "correlation": 0.0714, "has_text": true, "text_chars": 20, "mu_floor": 2.0436, "constraint_binding": true}} +{"id": "T4_all_20240802_0243", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "CSHI"], "decision_date": "2024-08-02", "context_summary": "XRP-USD \u03c3=0.0340, CSHI \u03c3=0.0004, \u03c1=-0.075. Min-variance weights: XRP-USD=0.001, CSHI=0.999.", "question": "Assets: XRP-USD, CSHI\nXRP-USD: annualized_mean_return=0.7812, daily_std=0.0340\nCSHI: annualized_mean_return=0.0504, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0511\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XRP-USD=0.0010, w_CSHI=0.9990", "answer_numeric": 0.001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.001155 + 0.000000 - -0.000002)\n Unconstrained: w_XRP-USD=0.0010\n After long-only clamp: w_XRP-USD=0.0010, w_CSHI=0.9990.", "metadata": {"weights": {"XRP-USD": 0.001, "CSHI": 0.999}, "sigma_1": 0.033984, "sigma_2": 0.000407, "covariance": -1e-06, "correlation": -0.0751, "has_text": true, "text_chars": 20, "mu_floor": 0.0511, "constraint_binding": false}} +{"id": "T4_all_20230613_0246", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD"], "decision_date": "2023-06-13", "context_summary": "XLK \u03c3=0.0116, BNB-USD \u03c3=0.0251, \u03c1=-0.059. Min-variance weights: XLK=0.810, BNB-USD=0.190.", "question": "Assets: XLK, BNB-USD\nXLK: annualized_mean_return=0.7056, daily_std=0.0116\nBNB-USD: annualized_mean_return=-1.3356, daily_std=0.0251\nMinimum required portfolio return (annualized): 0.6212\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_BNB-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_BNB-USD=X.XXXX", "answer": "w_XLK=0.9587, w_BNB-USD=0.0413", "answer_numeric": 0.9587, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000630 - -0.000017) / (0.000135 + 0.000630 - -0.000034)\n Unconstrained: w_XLK=0.8099\n After long-only clamp: w_XLK=0.8099, w_BNB-USD=0.1901.", "metadata": {"weights": {"XLK": 0.9587, "BNB-USD": 0.0413}, "sigma_1": 0.011605, "sigma_2": 0.025097, "covariance": -1.7e-05, "correlation": -0.0591, "has_text": true, "text_chars": 3020, "mu_floor": 0.6212, "constraint_binding": true}} +{"id": "T4_all_20231213_0249", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "CSHI"], "decision_date": "2023-12-13", "context_summary": "IVV \u03c3=0.0080, CSHI \u03c3=0.0005, \u03c1=-0.086. Min-variance weights: IVV=0.010, CSHI=0.990.", "question": "Assets: IVV, CSHI\nIVV: annualized_mean_return=0.2016, daily_std=0.0080\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0509\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_CSHI=X.XXXX", "answer": "w_IVV=0.0042, w_CSHI=0.9958", "answer_numeric": 0.0042, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000064 + 0.000000 - -0.000001)\n Unconstrained: w_IVV=0.0096\n After long-only clamp: w_IVV=0.0096, w_CSHI=0.9904.", "metadata": {"weights": {"IVV": 0.0042, "CSHI": 0.9958}, "sigma_1": 0.007969, "sigma_2": 0.000516, "covariance": -0.0, "correlation": -0.086, "has_text": true, "text_chars": 3020, "mu_floor": 0.0509, "constraint_binding": false}} +{"id": "T4_all_20241203_0252", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD", "LQD"], "decision_date": "2024-12-03", "context_summary": "ETH-USD \u03c3=0.0344, LQD \u03c3=0.0045, \u03c1=-0.075. Min-variance weights: ETH-USD=0.026, LQD=0.974.", "question": "Assets: ETH-USD, LQD\nETH-USD: annualized_mean_return=1.9908, daily_std=0.0344\nLQD: annualized_mean_return=-0.0000, daily_std=0.0045\nMinimum required portfolio return (annualized): 0.8256\nMarket regime: bull\n\nCompute portfolio weights (w_ETH-USD, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_LQD=X.XXXX", "answer": "w_ETH-USD=0.4147, w_LQD=0.5853", "answer_numeric": 0.4147, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000020 - -0.000012) / (0.001181 + 0.000020 - -0.000023)\n Unconstrained: w_ETH-USD=0.0262\n After long-only clamp: w_ETH-USD=0.0262, w_LQD=0.9738.", "metadata": {"weights": {"ETH-USD": 0.4147, "LQD": 0.5853}, "sigma_1": 0.034371, "sigma_2": 0.004517, "covariance": -1.2e-05, "correlation": -0.0753, "has_text": true, "text_chars": 20, "mu_floor": 0.8256, "constraint_binding": true}} +{"id": "T4_all_20230718_0255", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD"], "decision_date": "2023-07-18", "context_summary": "XLI \u03c3=0.0096, BNB-USD \u03c3=0.0270, \u03c1=-0.135. Min-variance weights: XLI=0.857, BNB-USD=0.143.", "question": "Assets: XLI, BNB-USD\nXLI: annualized_mean_return=0.3276, daily_std=0.0096\nBNB-USD: annualized_mean_return=-0.9072, daily_std=0.0270\nMinimum required portfolio return (annualized): -0.0334\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_BNB-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_BNB-USD=X.XXXX", "answer": "w_XLI=0.8569, w_BNB-USD=0.1431", "answer_numeric": 0.8569, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000731 - -0.000035) / (0.000093 + 0.000731 - -0.000070)\n Unconstrained: w_XLI=0.8568\n After long-only clamp: w_XLI=0.8568, w_BNB-USD=0.1432.", "metadata": {"weights": {"XLI": 0.8569, "BNB-USD": 0.1431}, "sigma_1": 0.009637, "sigma_2": 0.027032, "covariance": -3.5e-05, "correlation": -0.1347, "has_text": true, "text_chars": 3020, "mu_floor": -0.0334, "constraint_binding": false}} +{"id": "T4_all_20230721_0257", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "GLD"], "decision_date": "2023-07-21", "context_summary": "ADA-USD \u03c3=0.0431, GLD \u03c3=0.0072, \u03c1=-0.089. Min-variance weights: ADA-USD=0.040, GLD=0.960.", "question": "Assets: ADA-USD, GLD\nADA-USD: annualized_mean_return=-0.3780, daily_std=0.0431\nGLD: annualized_mean_return=0.0000, daily_std=0.0072\nMinimum required portfolio return (annualized): -0.1173\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_GLD=X.XXXX", "answer": "w_ADA-USD=0.0400, w_GLD=0.9600", "answer_numeric": 0.04, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000052 - -0.000027) / (0.001858 + 0.000052 - -0.000055)\n Unconstrained: w_ADA-USD=0.0403\n After long-only clamp: w_ADA-USD=0.0403, w_GLD=0.9597.", "metadata": {"weights": {"ADA-USD": 0.04, "GLD": 0.96}, "sigma_1": 0.04311, "sigma_2": 0.007187, "covariance": -2.7e-05, "correlation": -0.0886, "has_text": true, "text_chars": 20, "mu_floor": -0.1173, "constraint_binding": false}} +{"id": "T4_all_20230822_0259", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SCHH"], "decision_date": "2023-08-22", "context_summary": "VTI \u03c3=0.0066, SCHH \u03c3=0.0091, \u03c1=0.496. Min-variance weights: VTI=0.793, SCHH=0.207.", "question": "Assets: VTI, SCHH\nVTI: annualized_mean_return=0.3024, daily_std=0.0066\nSCHH: annualized_mean_return=0.1260, daily_std=0.0091\nMinimum required portfolio return (annualized): 0.2019\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_SCHH=X.XXXX", "answer": "w_VTI=0.7915, w_SCHH=0.2085", "answer_numeric": 0.7915, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000084 - 0.000030) / (0.000044 + 0.000084 - 0.000060)\n Unconstrained: w_VTI=0.7928\n After long-only clamp: w_VTI=0.7928, w_SCHH=0.2072.", "metadata": {"weights": {"VTI": 0.7915, "SCHH": 0.2085}, "sigma_1": 0.006644, "sigma_2": 0.009148, "covariance": 3e-05, "correlation": 0.4961, "has_text": true, "text_chars": 3020, "mu_floor": 0.2019, "constraint_binding": false}} +{"id": "T4_all_20231023_0261", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "SOL-USD"], "decision_date": "2023-10-23", "context_summary": "XLV \u03c3=0.0059, SOL-USD \u03c3=0.0357, \u03c1=-0.268. Min-variance weights: XLV=0.936, SOL-USD=0.064.", "question": "Assets: XLV, SOL-USD\nXLV: annualized_mean_return=-0.2016, daily_std=0.0059\nSOL-USD: annualized_mean_return=1.3860, daily_std=0.0357\nMinimum required portfolio return (annualized): -0.1508\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_SOL-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLV=X.XXXX, w_SOL-USD=X.XXXX", "answer": "w_XLV=0.9361, w_SOL-USD=0.0639", "answer_numeric": 0.9361, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001273 - -0.000056) / (0.000035 + 0.001273 - -0.000113)\n Unconstrained: w_XLV=0.9358\n After long-only clamp: w_XLV=0.9358, w_SOL-USD=0.0642.", "metadata": {"weights": {"XLV": 0.9361, "SOL-USD": 0.0639}, "sigma_1": 0.005896, "sigma_2": 0.035685, "covariance": -5.6e-05, "correlation": -0.2684, "has_text": true, "text_chars": 3020, "mu_floor": -0.1508, "constraint_binding": false}} +{"id": "T4_all_20240531_0264", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "DBB"], "decision_date": "2024-05-31", "context_summary": "LINK-USD \u03c3=0.0423, DBB \u03c3=0.0107, \u03c1=0.002. Min-variance weights: LINK-USD=0.060, DBB=0.940.", "question": "Assets: LINK-USD, DBB\nLINK-USD: annualized_mean_return=-0.0504, daily_std=0.0423\nDBB: annualized_mean_return=0.8316, daily_std=0.0107\nMinimum required portfolio return (annualized): 0.8183\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_DBB=X.XXXX", "answer": "w_LINK-USD=0.0151, w_DBB=0.9849", "answer_numeric": 0.0151, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000115 - 0.000001) / (0.001792 + 0.000115 - 0.000002)\n Unconstrained: w_LINK-USD=0.0599\n After long-only clamp: w_LINK-USD=0.0599, w_DBB=0.9401.", "metadata": {"weights": {"LINK-USD": 0.0151, "DBB": 0.9849}, "sigma_1": 0.042326, "sigma_2": 0.010727, "covariance": 1e-06, "correlation": 0.002, "has_text": true, "text_chars": 20, "mu_floor": 0.8183, "constraint_binding": true}} +{"id": "T4_all_20240910_0266", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "SCHH"], "decision_date": "2024-09-10", "context_summary": "ACWI \u03c3=0.0094, SCHH \u03c3=0.0087, \u03c1=0.400. Min-variance weights: ACWI=0.439, SCHH=0.561.", "question": "Assets: ACWI, SCHH\nACWI: annualized_mean_return=0.0504, daily_std=0.0094\nSCHH: annualized_mean_return=0.6300, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.4903\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ACWI=X.XXXX, w_SCHH=X.XXXX", "answer": "w_ACWI=0.2410, w_SCHH=0.7590", "answer_numeric": 0.241, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000076 - 0.000033) / (0.000088 + 0.000076 - 0.000065)\n Unconstrained: w_ACWI=0.4391\n After long-only clamp: w_ACWI=0.4391, w_SCHH=0.5609.", "metadata": {"weights": {"ACWI": 0.241, "SCHH": 0.759}, "sigma_1": 0.009361, "sigma_2": 0.0087, "covariance": 3.3e-05, "correlation": 0.4002, "has_text": true, "text_chars": 9045, "mu_floor": 0.4903, "constraint_binding": true}} +{"id": "T4_all_20230724_0267", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "EMB"], "decision_date": "2023-07-24", "context_summary": "ADA-USD \u03c3=0.0431, EMB \u03c3=0.0049, \u03c1=-0.031. Min-variance weights: ADA-USD=0.016, EMB=0.984.", "question": "Assets: ADA-USD, EMB\nADA-USD: annualized_mean_return=-0.4032, daily_std=0.0431\nEMB: annualized_mean_return=0.1008, daily_std=0.0049\nMinimum required portfolio return (annualized): -0.1357\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_EMB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_EMB=X.XXXX", "answer": "w_ADA-USD=0.0158, w_EMB=0.9842", "answer_numeric": 0.0158, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000024 - -0.000006) / (0.001858 + 0.000024 - -0.000013)\n Unconstrained: w_ADA-USD=0.0160\n After long-only clamp: w_ADA-USD=0.0160, w_EMB=0.9840.", "metadata": {"weights": {"ADA-USD": 0.0158, "EMB": 0.9842}, "sigma_1": 0.043104, "sigma_2": 0.004885, "covariance": -6e-06, "correlation": -0.0308, "has_text": true, "text_chars": 20, "mu_floor": -0.1357, "constraint_binding": false}} +{"id": "T4_all_20230424_0270", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "REZ"], "decision_date": "2023-04-24", "context_summary": "XLB \u03c3=0.0118, REZ \u03c3=0.0136, \u03c1=0.555. Min-variance weights: XLB=0.659, REZ=0.341.", "question": "Assets: XLB, REZ\nXLB: annualized_mean_return=-0.1260, daily_std=0.0118\nREZ: annualized_mean_return=-0.0252, daily_std=0.0136\nMinimum required portfolio return (annualized): -0.0389\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_REZ=X.XXXX", "answer": "w_XLB=0.1359, w_REZ=0.8641", "answer_numeric": 0.1359, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000185 - 0.000089) / (0.000138 + 0.000185 - 0.000178)\n Unconstrained: w_XLB=0.6592\n After long-only clamp: w_XLB=0.6592, w_REZ=0.3408.", "metadata": {"weights": {"XLB": 0.1359, "REZ": 0.8641}, "sigma_1": 0.011766, "sigma_2": 0.013593, "covariance": 8.9e-05, "correlation": 0.5555, "has_text": true, "text_chars": 3020, "mu_floor": -0.0389, "constraint_binding": true}} +{"id": "T4_all_20240219_0272", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BIL"], "decision_date": "2024-02-19", "context_summary": "MTUM \u03c3=0.0096, BIL \u03c3=0.0002, \u03c1=-0.011. Min-variance weights: MTUM=0.001, BIL=1.000.", "question": "Assets: MTUM, BIL\nMTUM: annualized_mean_return=0.6804, daily_std=0.0096\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.4408\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_BIL=X.XXXX", "answer": "w_MTUM=0.6197, w_BIL=0.3803", "answer_numeric": 0.6197, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000093 + 0.000000 - -0.000000)\n Unconstrained: w_MTUM=0.0005\n After long-only clamp: w_MTUM=0.0005, w_BIL=0.9995.", "metadata": {"weights": {"MTUM": 0.6197, "BIL": 0.3803}, "sigma_1": 0.009637, "sigma_2": 0.000159, "covariance": -0.0, "correlation": -0.0108, "has_text": true, "text_chars": 9045, "mu_floor": 0.4408, "constraint_binding": true}} +{"id": "T4_all_20230703_0274", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "XHB"], "decision_date": "2023-07-03", "context_summary": "SOL-USD \u03c3=0.0385, XHB \u03c3=0.0129, \u03c1=0.181. Min-variance weights: SOL-USD=0.052, XHB=0.948.", "question": "Assets: SOL-USD, XHB\nSOL-USD: annualized_mean_return=-0.3780, daily_std=0.0385\nXHB: annualized_mean_return=0.8568, daily_std=0.0129\nMinimum required portfolio return (annualized): 0.8080\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_XHB=X.XXXX", "answer": "w_SOL-USD=0.0395, w_XHB=0.9605", "answer_numeric": 0.0395, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000166 - 0.000090) / (0.001481 + 0.000166 - 0.000180)\n Unconstrained: w_SOL-USD=0.0519\n After long-only clamp: w_SOL-USD=0.0519, w_XHB=0.9481.", "metadata": {"weights": {"SOL-USD": 0.0395, "XHB": 0.9605}, "sigma_1": 0.038481, "sigma_2": 0.012881, "covariance": 9e-05, "correlation": 0.1811, "has_text": true, "text_chars": 20, "mu_floor": 0.808, "constraint_binding": true}} +{"id": "T4_all_20230202_0277", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SGOV"], "decision_date": "2023-02-02", "context_summary": "VEA \u03c3=0.0105, SGOV \u03c3=0.0002, \u03c1=0.238. Min-variance weights: VEA=0.000, SGOV=1.000.", "question": "Assets: VEA, SGOV\nVEA: annualized_mean_return=0.7056, daily_std=0.0105\nSGOV: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0253\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_SGOV=X.XXXX", "answer": "w_VEA=0.0002, w_SGOV=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000109 + 0.000000 - 0.000001)\n Unconstrained: w_VEA=-0.0035\n After long-only clamp: w_VEA=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"VEA": 0.0002, "SGOV": 0.9998}, "sigma_1": 0.010464, "sigma_2": 0.000163, "covariance": 0.0, "correlation": 0.2384, "has_text": true, "text_chars": 3020, "mu_floor": 0.0253, "constraint_binding": false}} +{"id": "T4_all_20240315_0280", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "INDS"], "decision_date": "2024-03-15", "context_summary": "AVAX-USD \u03c3=0.0450, INDS \u03c3=0.0099, \u03c1=-0.026. Min-variance weights: AVAX-USD=0.051, INDS=0.949.", "question": "Assets: AVAX-USD, INDS\nAVAX-USD: annualized_mean_return=2.0412, daily_std=0.0450\nINDS: annualized_mean_return=-0.1764, daily_std=0.0099\nMinimum required portfolio return (annualized): 1.0864\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_INDS=X.XXXX", "answer": "w_AVAX-USD=0.5694, w_INDS=0.4306", "answer_numeric": 0.5694, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000098 - -0.000012) / (0.002023 + 0.000098 - -0.000024)\n Unconstrained: w_AVAX-USD=0.0514\n After long-only clamp: w_AVAX-USD=0.0514, w_INDS=0.9486.", "metadata": {"weights": {"AVAX-USD": 0.5694, "INDS": 0.4306}, "sigma_1": 0.04498, "sigma_2": 0.009924, "covariance": -1.2e-05, "correlation": -0.0265, "has_text": true, "text_chars": 20, "mu_floor": 1.0864, "constraint_binding": true}} +{"id": "T4_all_20230313_0282", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "DBA"], "decision_date": "2023-03-13", "context_summary": "ADA-USD \u03c3=0.0350, DBA \u03c3=0.0063, \u03c1=0.053. Min-variance weights: ADA-USD=0.022, DBA=0.978.", "question": "Assets: ADA-USD, DBA\nADA-USD: annualized_mean_return=0.2772, daily_std=0.0350\nDBA: annualized_mean_return=0.1008, daily_std=0.0063\nMinimum required portfolio return (annualized): 0.1733\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_DBA=X.XXXX", "answer": "w_ADA-USD=0.4110, w_DBA=0.5890", "answer_numeric": 0.411, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000039 - 0.000012) / (0.001226 + 0.000039 - 0.000023)\n Unconstrained: w_ADA-USD=0.0223\n After long-only clamp: w_ADA-USD=0.0223, w_DBA=0.9777.", "metadata": {"weights": {"ADA-USD": 0.411, "DBA": 0.589}, "sigma_1": 0.035021, "sigma_2": 0.00628, "covariance": 1.2e-05, "correlation": 0.0533, "has_text": true, "text_chars": 20, "mu_floor": 0.1733, "constraint_binding": true}} +{"id": "T4_all_20240916_0284", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "CSHI"], "decision_date": "2024-09-16", "context_summary": "EFA \u03c3=0.0096, CSHI \u03c3=0.0012, \u03c1=0.010. Min-variance weights: EFA=0.014, CSHI=0.986.", "question": "Assets: EFA, CSHI\nEFA: annualized_mean_return=0.1512, daily_std=0.0096\nCSHI: annualized_mean_return=0.0504, daily_std=0.0012\nMinimum required portfolio return (annualized): 0.0822\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_CSHI=X.XXXX", "answer": "w_EFA=0.3155, w_CSHI=0.6845", "answer_numeric": 0.3155, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000000) / (0.000091 + 0.000001 - 0.000000)\n Unconstrained: w_EFA=0.0138\n After long-only clamp: w_EFA=0.0138, w_CSHI=0.9862.", "metadata": {"weights": {"EFA": 0.3155, "CSHI": 0.6845}, "sigma_1": 0.009559, "sigma_2": 0.001179, "covariance": 0.0, "correlation": 0.0103, "has_text": true, "text_chars": 9045, "mu_floor": 0.0822, "constraint_binding": true}} +{"id": "T4_all_20231031_0286", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "IEF"], "decision_date": "2023-10-31", "context_summary": "ETH-USD \u03c3=0.0171, IEF \u03c3=0.0050, \u03c1=-0.183. Min-variance weights: ETH-USD=0.117, IEF=0.883.", "question": "Assets: ETH-USD, IEF\nETH-USD: annualized_mean_return=0.4284, daily_std=0.0171\nIEF: annualized_mean_return=-0.2520, daily_std=0.0050\nMinimum required portfolio return (annualized): 0.2420\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_IEF) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_IEF=X.XXXX", "answer": "w_ETH-USD=0.7260, w_IEF=0.2740", "answer_numeric": 0.726, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000025 - -0.000016) / (0.000293 + 0.000025 - -0.000031)\n Unconstrained: w_ETH-USD=0.1166\n After long-only clamp: w_ETH-USD=0.1166, w_IEF=0.8834.", "metadata": {"weights": {"ETH-USD": 0.726, "IEF": 0.274}, "sigma_1": 0.017109, "sigma_2": 0.005004, "covariance": -1.6e-05, "correlation": -0.183, "has_text": true, "text_chars": 20, "mu_floor": 0.242, "constraint_binding": true}} +{"id": "T4_all_20230922_0289", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "TLT"], "decision_date": "2023-09-22", "context_summary": "BTC-USD \u03c3=0.0173, TLT \u03c3=0.0097, \u03c1=-0.100. Min-variance weights: BTC-USD=0.260, TLT=0.740.", "question": "Assets: BTC-USD, TLT\nBTC-USD: annualized_mean_return=-0.4788, daily_std=0.0173\nTLT: annualized_mean_return=-0.5040, daily_std=0.0097\nMinimum required portfolio return (annualized): -0.4984\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_TLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_TLT=X.XXXX", "answer": "w_BTC-USD=0.2606, w_TLT=0.7394", "answer_numeric": 0.2606, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000094 - -0.000017) / (0.000299 + 0.000094 - -0.000034)\n Unconstrained: w_BTC-USD=0.2604\n After long-only clamp: w_BTC-USD=0.2604, w_TLT=0.7396.", "metadata": {"weights": {"BTC-USD": 0.2606, "TLT": 0.7394}, "sigma_1": 0.017289, "sigma_2": 0.009714, "covariance": -1.7e-05, "correlation": -0.1, "has_text": true, "text_chars": 20, "mu_floor": -0.4984, "constraint_binding": false}} +{"id": "T4_all_20240416_0292", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "MORT"], "decision_date": "2024-04-16", "context_summary": "XLK \u03c3=0.0116, MORT \u03c3=0.0150, \u03c1=0.364. Min-variance weights: XLK=0.694, MORT=0.306.", "question": "Assets: XLK, MORT\nXLK: annualized_mean_return=0.1260, daily_std=0.0116\nMORT: annualized_mean_return=-0.2268, daily_std=0.0150\nMinimum required portfolio return (annualized): 0.0535\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_MORT=X.XXXX", "answer": "w_XLK=0.7945, w_MORT=0.2055", "answer_numeric": 0.7945, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000225 - 0.000063) / (0.000135 + 0.000225 - 0.000127)\n Unconstrained: w_XLK=0.6939\n After long-only clamp: w_XLK=0.6939, w_MORT=0.3061.", "metadata": {"weights": {"XLK": 0.7945, "MORT": 0.2055}, "sigma_1": 0.011607, "sigma_2": 0.015002, "covariance": 6.3e-05, "correlation": 0.3643, "has_text": true, "text_chars": 9045, "mu_floor": 0.0535, "constraint_binding": true}} +{"id": "T4_all_20240415_0295", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "SOYB"], "decision_date": "2024-04-15", "context_summary": "SPY \u03c3=0.0072, SOYB \u03c3=0.0083, \u03c1=0.197. Min-variance weights: SPY=0.581, SOYB=0.419.", "question": "Assets: SPY, SOYB\nSPY: annualized_mean_return=0.3528, daily_std=0.0072\nSOYB: annualized_mean_return=-0.0756, daily_std=0.0083\nMinimum required portfolio return (annualized): 0.0240\nMarket regime: sideways\n\nCompute portfolio weights (w_SPY, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_SOYB=X.XXXX", "answer": "w_SPY=0.5811, w_SOYB=0.4189", "answer_numeric": 0.5811, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000068 - 0.000012) / (0.000053 + 0.000068 - 0.000024)\n Unconstrained: w_SPY=0.5807\n After long-only clamp: w_SPY=0.5807, w_SOYB=0.4193.", "metadata": {"weights": {"SPY": 0.5811, "SOYB": 0.4189}, "sigma_1": 0.007248, "sigma_2": 0.00826, "covariance": 1.2e-05, "correlation": 0.1968, "has_text": true, "text_chars": 9045, "mu_floor": 0.024, "constraint_binding": false}} +{"id": "T4_all_20241009_0298", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "IYR"], "decision_date": "2024-10-09", "context_summary": "XLE \u03c3=0.0132, IYR \u03c3=0.0086, \u03c1=0.130. Min-variance weights: XLE=0.270, IYR=0.730.", "question": "Assets: XLE, IYR\nXLE: annualized_mean_return=-0.0000, daily_std=0.0132\nIYR: annualized_mean_return=0.3276, daily_std=0.0086\nMinimum required portfolio return (annualized): 0.2911\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLE=X.XXXX, w_IYR=X.XXXX", "answer": "w_XLE=0.1114, w_IYR=0.8886", "answer_numeric": 0.1114, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000074 - 0.000015) / (0.000174 + 0.000074 - 0.000029)\n Unconstrained: w_XLE=0.2701\n After long-only clamp: w_XLE=0.2701, w_IYR=0.7299.", "metadata": {"weights": {"XLE": 0.1114, "IYR": 0.8886}, "sigma_1": 0.013182, "sigma_2": 0.008575, "covariance": 1.5e-05, "correlation": 0.1296, "has_text": true, "text_chars": 9045, "mu_floor": 0.2911, "constraint_binding": true}} +{"id": "T4_all_20230525_0301", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "UNG"], "decision_date": "2023-05-25", "context_summary": "LINK-USD \u03c3=0.0284, UNG \u03c3=0.0401, \u03c1=-0.127. Min-variance weights: LINK-USD=0.648, UNG=0.351.", "question": "Assets: LINK-USD, UNG\nLINK-USD: annualized_mean_return=-0.3780, daily_std=0.0284\nUNG: annualized_mean_return=-0.6048, daily_std=0.0401\nMinimum required portfolio return (annualized): -0.4846\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_UNG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_UNG=X.XXXX", "answer": "w_LINK-USD=0.6486, w_UNG=0.3514", "answer_numeric": 0.6486, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001609 - -0.000144) / (0.000806 + 0.001609 - -0.000288)\n Unconstrained: w_LINK-USD=0.6485\n After long-only clamp: w_LINK-USD=0.6485, w_UNG=0.3515.", "metadata": {"weights": {"LINK-USD": 0.6486, "UNG": 0.3514}, "sigma_1": 0.028385, "sigma_2": 0.040107, "covariance": -0.000144, "correlation": -0.1266, "has_text": true, "text_chars": 20, "mu_floor": -0.4846, "constraint_binding": false}} +{"id": "T4_all_20240306_0304", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "VCIT"], "decision_date": "2024-03-06", "context_summary": "XLP \u03c3=0.0071, VCIT \u03c3=0.0038, \u03c1=-0.277. Min-variance weights: XLP=0.276, VCIT=0.724.", "question": "Assets: XLP, VCIT\nXLP: annualized_mean_return=0.2772, daily_std=0.0071\nVCIT: annualized_mean_return=0.0756, daily_std=0.0038\nMinimum required portfolio return (annualized): 0.2458\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_VCIT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_VCIT=X.XXXX", "answer": "w_XLP=0.8442, w_VCIT=0.1558", "answer_numeric": 0.8442, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000015 - -0.000008) / (0.000051 + 0.000015 - -0.000015)\n Unconstrained: w_XLP=0.2758\n After long-only clamp: w_XLP=0.2758, w_VCIT=0.7242.", "metadata": {"weights": {"XLP": 0.8442, "VCIT": 0.1558}, "sigma_1": 0.007126, "sigma_2": 0.003829, "covariance": -8e-06, "correlation": -0.2768, "has_text": true, "text_chars": 9045, "mu_floor": 0.2458, "constraint_binding": true}} +{"id": "T4_all_20231208_0306", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOYB"], "decision_date": "2023-12-08", "context_summary": "IVV \u03c3=0.0082, SOYB \u03c3=0.0098, \u03c1=0.203. Min-variance weights: IVV=0.608, SOYB=0.392.", "question": "Assets: IVV, SOYB\nIVV: annualized_mean_return=0.1260, daily_std=0.0082\nSOYB: annualized_mean_return=-0.1512, daily_std=0.0098\nMinimum required portfolio return (annualized): 0.0951\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_SOYB=X.XXXX", "answer": "w_IVV=0.8885, w_SOYB=0.1115", "answer_numeric": 0.8885, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000095 - 0.000016) / (0.000067 + 0.000095 - 0.000032)\n Unconstrained: w_IVV=0.6083\n After long-only clamp: w_IVV=0.6083, w_SOYB=0.3917.", "metadata": {"weights": {"IVV": 0.8885, "SOYB": 0.1115}, "sigma_1": 0.008188, "sigma_2": 0.009756, "covariance": 1.6e-05, "correlation": 0.2026, "has_text": true, "text_chars": 3020, "mu_floor": 0.0951, "constraint_binding": true}} +{"id": "T4_all_20240704_0309", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "PALL"], "decision_date": "2024-07-04", "context_summary": "SOL-USD \u03c3=0.0404, PALL \u03c3=0.0198, \u03c1=-0.095. Min-variance weights: SOL-USD=0.215, PALL=0.785.", "question": "Assets: SOL-USD, PALL\nSOL-USD: annualized_mean_return=0.0504, daily_std=0.0404\nPALL: annualized_mean_return=-0.2016, daily_std=0.0198\nMinimum required portfolio return (annualized): -0.1488\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_PALL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_PALL=X.XXXX", "answer": "w_SOL-USD=0.2154, w_PALL=0.7846", "answer_numeric": 0.2154, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000394 - -0.000076) / (0.001635 + 0.000394 - -0.000152)\n Unconstrained: w_SOL-USD=0.2154\n After long-only clamp: w_SOL-USD=0.2154, w_PALL=0.7846.", "metadata": {"weights": {"SOL-USD": 0.2154, "PALL": 0.7846}, "sigma_1": 0.040431, "sigma_2": 0.019838, "covariance": -7.6e-05, "correlation": -0.0947, "has_text": true, "text_chars": 20, "mu_floor": -0.1488, "constraint_binding": false}} +{"id": "T4_all_20240502_0311", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BTC-USD"], "decision_date": "2024-05-02", "context_summary": "QQQ \u03c3=0.0104, BTC-USD \u03c3=0.0345, \u03c1=-0.003. Min-variance weights: QQQ=0.917, BTC-USD=0.083.", "question": "Assets: QQQ, BTC-USD\nQQQ: annualized_mean_return=-0.0504, daily_std=0.0104\nBTC-USD: annualized_mean_return=-0.1008, daily_std=0.0345\nMinimum required portfolio return (annualized): -0.0778\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_BTC-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QQQ=X.XXXX, w_BTC-USD=X.XXXX", "answer": "w_QQQ=0.9168, w_BTC-USD=0.0832", "answer_numeric": 0.9168, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001193 - -0.000001) / (0.000107 + 0.001193 - -0.000002)\n Unconstrained: w_QQQ=0.9167\n After long-only clamp: w_QQQ=0.9167, w_BTC-USD=0.0833.", "metadata": {"weights": {"QQQ": 0.9168, "BTC-USD": 0.0832}, "sigma_1": 0.010359, "sigma_2": 0.034539, "covariance": -1e-06, "correlation": -0.0034, "has_text": true, "text_chars": 9045, "mu_floor": -0.0778, "constraint_binding": false}} +{"id": "T4_all_20230925_0314", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "SOYB"], "decision_date": "2023-09-25", "context_summary": "DOT-USD \u03c3=0.0171, SOYB \u03c3=0.0122, \u03c1=0.135. Min-variance weights: DOT-USD=0.314, SOYB=0.686.", "question": "Assets: DOT-USD, SOYB\nDOT-USD: annualized_mean_return=-1.1088, daily_std=0.0171\nSOYB: annualized_mean_return=0.1260, daily_std=0.0122\nMinimum required portfolio return (annualized): -0.0453\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_SOYB=X.XXXX", "answer": "w_DOT-USD=0.1387, w_SOYB=0.8613", "answer_numeric": 0.1387, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000149 - 0.000028) / (0.000292 + 0.000149 - 0.000056)\n Unconstrained: w_DOT-USD=0.3142\n After long-only clamp: w_DOT-USD=0.3142, w_SOYB=0.6858.", "metadata": {"weights": {"DOT-USD": 0.1387, "SOYB": 0.8613}, "sigma_1": 0.017082, "sigma_2": 0.012201, "covariance": 2.8e-05, "correlation": 0.1346, "has_text": true, "text_chars": 20, "mu_floor": -0.0453, "constraint_binding": true}} +{"id": "T4_all_20230113_0317", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "ICSH"], "decision_date": "2023-01-13", "context_summary": "MATIC-USD \u03c3=0.0323, ICSH \u03c3=0.0003, \u03c1=0.163. Min-variance weights: MATIC-USD=0.000, ICSH=1.000.", "question": "Assets: MATIC-USD, ICSH\nMATIC-USD: annualized_mean_return=0.2520, daily_std=0.0323\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MATIC-USD=0.0000, w_ICSH=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000002) / (0.001043 + 0.000000 - 0.000003)\n Unconstrained: w_MATIC-USD=-0.0014\n After long-only clamp: w_MATIC-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.032293, "sigma_2": 0.000301, "covariance": 2e-06, "correlation": 0.1627, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240328_0319", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "DBB"], "decision_date": "2024-03-28", "context_summary": "XLF \u03c3=0.0063, DBB \u03c3=0.0083, \u03c1=0.147. Min-variance weights: XLF=0.651, DBB=0.349.", "question": "Assets: XLF, DBB\nXLF: annualized_mean_return=0.4788, daily_std=0.0063\nDBB: annualized_mean_return=0.0000, daily_std=0.0083\nMinimum required portfolio return (annualized): 0.2458\nMarket regime: bull\n\nCompute portfolio weights (w_XLF, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_DBB=X.XXXX", "answer": "w_XLF=0.6519, w_DBB=0.3481", "answer_numeric": 0.6519, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000068 - 0.000008) / (0.000040 + 0.000068 - 0.000015)\n Unconstrained: w_XLF=0.6511\n After long-only clamp: w_XLF=0.6511, w_DBB=0.3489.", "metadata": {"weights": {"XLF": 0.6519, "DBB": 0.3481}, "sigma_1": 0.006344, "sigma_2": 0.00827, "covariance": 8e-06, "correlation": 0.1473, "has_text": true, "text_chars": 9045, "mu_floor": 0.2458, "constraint_binding": false}} +{"id": "T4_all_20230223_0322", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "HAUZ"], "decision_date": "2023-02-23", "context_summary": "MATIC-USD \u03c3=0.0398, HAUZ \u03c3=0.0099, \u03c1=0.104. Min-variance weights: MATIC-USD=0.035, HAUZ=0.965.", "question": "Assets: MATIC-USD, HAUZ\nMATIC-USD: annualized_mean_return=2.5704, daily_std=0.0398\nHAUZ: annualized_mean_return=0.1764, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.8894\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_MATIC-USD=0.2978, w_HAUZ=0.7022", "answer_numeric": 0.2978, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000097 - 0.000041) / (0.001586 + 0.000097 - 0.000081)\n Unconstrained: w_MATIC-USD=0.0354\n After long-only clamp: w_MATIC-USD=0.0354, w_HAUZ=0.9646.", "metadata": {"weights": {"MATIC-USD": 0.2978, "HAUZ": 0.7022}, "sigma_1": 0.039829, "sigma_2": 0.009868, "covariance": 4.1e-05, "correlation": 0.1035, "has_text": true, "text_chars": 20, "mu_floor": 0.8894, "constraint_binding": true}} +{"id": "T4_all_20240808_0325", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "BNDX"], "decision_date": "2024-08-08", "context_summary": "BTC-USD \u03c3=0.0250, BNDX \u03c3=0.0024, \u03c1=-0.085. Min-variance weights: BTC-USD=0.017, BNDX=0.983.", "question": "Assets: BTC-USD, BNDX\nBTC-USD: annualized_mean_return=-0.8820, daily_std=0.0250\nBNDX: annualized_mean_return=0.1008, daily_std=0.0024\nMinimum required portfolio return (annualized): 0.0829\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_BNDX=X.XXXX", "answer": "w_BTC-USD=0.0170, w_BNDX=0.9830", "answer_numeric": 0.017, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000006 - -0.000005) / (0.000625 + 0.000006 - -0.000010)\n Unconstrained: w_BTC-USD=0.0173\n After long-only clamp: w_BTC-USD=0.0173, w_BNDX=0.9827.", "metadata": {"weights": {"BTC-USD": 0.017, "BNDX": 0.983}, "sigma_1": 0.025003, "sigma_2": 0.002432, "covariance": -5e-06, "correlation": -0.085, "has_text": true, "text_chars": 20, "mu_floor": 0.0829, "constraint_binding": false}} +{"id": "T4_all_20230209_0328", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "HAUZ"], "decision_date": "2023-02-09", "context_summary": "SOL-USD \u03c3=0.0696, HAUZ \u03c3=0.0102, \u03c1=-0.043. Min-variance weights: SOL-USD=0.027, HAUZ=0.973.", "question": "Assets: SOL-USD, HAUZ\nSOL-USD: annualized_mean_return=2.6964, daily_std=0.0696\nHAUZ: annualized_mean_return=0.3528, daily_std=0.0102\nMinimum required portfolio return (annualized): 1.7785\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_SOL-USD=0.6083, w_HAUZ=0.3917", "answer_numeric": 0.6083, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000104 - -0.000030) / (0.004839 + 0.000104 - -0.000061)\n Unconstrained: w_SOL-USD=0.0268\n After long-only clamp: w_SOL-USD=0.0268, w_HAUZ=0.9732.", "metadata": {"weights": {"SOL-USD": 0.6083, "HAUZ": 0.3917}, "sigma_1": 0.069561, "sigma_2": 0.010193, "covariance": -3e-05, "correlation": -0.0427, "has_text": true, "text_chars": 20, "mu_floor": 1.7785, "constraint_binding": true}} +{"id": "T4_all_20231002_0330", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "PALL"], "decision_date": "2023-10-02", "context_summary": "XLY \u03c3=0.0115, PALL \u03c3=0.0167, \u03c1=-0.167. Min-variance weights: XLY=0.653, PALL=0.347.", "question": "Assets: XLY, PALL\nXLY: annualized_mean_return=-0.2016, daily_std=0.0115\nPALL: annualized_mean_return=-0.0504, daily_std=0.0167\nMinimum required portfolio return (annualized): -0.0893\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_PALL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_PALL=X.XXXX", "answer": "w_XLY=0.2573, w_PALL=0.7427", "answer_numeric": 0.2573, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000278 - -0.000032) / (0.000133 + 0.000278 - -0.000064)\n Unconstrained: w_XLY=0.6531\n After long-only clamp: w_XLY=0.6531, w_PALL=0.3469.", "metadata": {"weights": {"XLY": 0.2573, "PALL": 0.7427}, "sigma_1": 0.011523, "sigma_2": 0.016683, "covariance": -3.2e-05, "correlation": -0.1671, "has_text": true, "text_chars": 3020, "mu_floor": -0.0893, "constraint_binding": true}} +{"id": "T4_all_20240105_0332", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "USO"], "decision_date": "2024-01-05", "context_summary": "AVAX-USD \u03c3=0.0651, USO \u03c3=0.0208, \u03c1=0.018. Min-variance weights: AVAX-USD=0.088, USO=0.912.", "question": "Assets: AVAX-USD, USO\nAVAX-USD: annualized_mean_return=5.3676, daily_std=0.0651\nUSO: annualized_mean_return=-0.5040, daily_std=0.0208\nMinimum required portfolio return (annualized): 3.6135\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_USO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_USO=X.XXXX", "answer": "w_AVAX-USD=0.7013, w_USO=0.2987", "answer_numeric": 0.7013, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000431 - 0.000024) / (0.004243 + 0.000431 - 0.000048)\n Unconstrained: w_AVAX-USD=0.0880\n After long-only clamp: w_AVAX-USD=0.0880, w_USO=0.9120.", "metadata": {"weights": {"AVAX-USD": 0.7013, "USO": 0.2987}, "sigma_1": 0.06514, "sigma_2": 0.020769, "covariance": 2.4e-05, "correlation": 0.0178, "has_text": true, "text_chars": 20, "mu_floor": 3.6135, "constraint_binding": true}} +{"id": "T4_all_20231109_0335", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "UNG"], "decision_date": "2023-11-09", "context_summary": "AVAX-USD \u03c3=0.0295, UNG \u03c3=0.0273, \u03c1=-0.288. Min-variance weights: AVAX-USD=0.470, UNG=0.530.", "question": "Assets: AVAX-USD, UNG\nAVAX-USD: annualized_mean_return=1.2852, daily_std=0.0295\nUNG: annualized_mean_return=-0.2772, daily_std=0.0273\nMinimum required portfolio return (annualized): 0.3552\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_UNG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_UNG=X.XXXX", "answer": "w_AVAX-USD=0.4698, w_UNG=0.5302", "answer_numeric": 0.4698, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000743 - -0.000231) / (0.000868 + 0.000743 - -0.000463)\n Unconstrained: w_AVAX-USD=0.4698\n After long-only clamp: w_AVAX-USD=0.4698, w_UNG=0.5302.", "metadata": {"weights": {"AVAX-USD": 0.4698, "UNG": 0.5302}, "sigma_1": 0.029461, "sigma_2": 0.027257, "covariance": -0.000231, "correlation": -0.288, "has_text": true, "text_chars": 20, "mu_floor": 0.3552, "constraint_binding": false}} +{"id": "T4_all_20230329_0338", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "STIP"], "decision_date": "2023-03-29", "context_summary": "MATIC-USD \u03c3=0.0434, STIP \u03c3=0.0022, \u03c1=0.186. Min-variance weights: MATIC-USD=0.000, STIP=1.000.", "question": "Assets: MATIC-USD, STIP\nMATIC-USD: annualized_mean_return=-0.0252, daily_std=0.0434\nSTIP: annualized_mean_return=0.0504, daily_std=0.0022\nMinimum required portfolio return (annualized): 0.0389\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_STIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_STIP=X.XXXX", "answer": "w_MATIC-USD=0.0000, w_STIP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000005 - 0.000018) / (0.001880 + 0.000005 - 0.000035)\n Unconstrained: w_MATIC-USD=-0.0070\n After long-only clamp: w_MATIC-USD=0.0000, w_STIP=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0, "STIP": 1.0}, "sigma_1": 0.043358, "sigma_2": 0.002181, "covariance": 1.8e-05, "correlation": 0.1865, "has_text": true, "text_chars": 20, "mu_floor": 0.0389, "constraint_binding": false}} +{"id": "T4_all_20231026_0341", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MORT"], "decision_date": "2023-10-26", "context_summary": "FXI \u03c3=0.0159, MORT \u03c3=0.0146, \u03c1=0.500. Min-variance weights: FXI=0.416, MORT=0.584.", "question": "Assets: FXI, MORT\nFXI: annualized_mean_return=-0.6300, daily_std=0.0159\nMORT: annualized_mean_return=-0.8820, daily_std=0.0146\nMinimum required portfolio return (annualized): -0.7855\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_MORT=X.XXXX", "answer": "w_FXI=0.4157, w_MORT=0.5843", "answer_numeric": 0.4157, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000214 - 0.000117) / (0.000254 + 0.000214 - 0.000233)\n Unconstrained: w_FXI=0.4160\n After long-only clamp: w_FXI=0.4160, w_MORT=0.5840.", "metadata": {"weights": {"FXI": 0.4157, "MORT": 0.5843}, "sigma_1": 0.015937, "sigma_2": 0.014645, "covariance": 0.000117, "correlation": 0.5001, "has_text": true, "text_chars": 3020, "mu_floor": -0.7855, "constraint_binding": false}} +{"id": "T4_all_20230314_0344", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "SCHH"], "decision_date": "2023-03-14", "context_summary": "BNB-USD \u03c3=0.0254, SCHH \u03c3=0.0139, \u03c1=0.066. Min-variance weights: BNB-USD=0.213, SCHH=0.786.", "question": "Assets: BNB-USD, SCHH\nBNB-USD: annualized_mean_return=0.3780, daily_std=0.0254\nSCHH: annualized_mean_return=-0.2520, daily_std=0.0139\nMinimum required portfolio return (annualized): 0.0538\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_SCHH=X.XXXX", "answer": "w_BNB-USD=0.4854, w_SCHH=0.5146", "answer_numeric": 0.4854, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000193 - 0.000023) / (0.000647 + 0.000193 - 0.000047)\n Unconstrained: w_BNB-USD=0.2135\n After long-only clamp: w_BNB-USD=0.2135, w_SCHH=0.7865.", "metadata": {"weights": {"BNB-USD": 0.4854, "SCHH": 0.5146}, "sigma_1": 0.025443, "sigma_2": 0.013886, "covariance": 2.3e-05, "correlation": 0.0663, "has_text": true, "text_chars": 20, "mu_floor": 0.0538, "constraint_binding": true}} +{"id": "T4_all_20240311_0347", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "ICSH"], "decision_date": "2024-03-11", "context_summary": "XRP-USD \u03c3=0.0261, ICSH \u03c3=0.0003, \u03c1=-0.115. Min-variance weights: XRP-USD=0.002, ICSH=0.998.", "question": "Assets: XRP-USD, ICSH\nXRP-USD: annualized_mean_return=0.1512, daily_std=0.0261\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0505\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XRP-USD=0.0016, w_ICSH=0.9984", "answer_numeric": 0.0016, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000679 + 0.000000 - -0.000002)\n Unconstrained: w_XRP-USD=0.0016\n After long-only clamp: w_XRP-USD=0.0016, w_ICSH=0.9984.", "metadata": {"weights": {"XRP-USD": 0.0016, "ICSH": 0.9984}, "sigma_1": 0.026067, "sigma_2": 0.000322, "covariance": -1e-06, "correlation": -0.1147, "has_text": true, "text_chars": 20, "mu_floor": 0.0505, "constraint_binding": false}} +{"id": "T4_all_20230321_0349", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SGOV"], "decision_date": "2023-03-21", "context_summary": "XLF \u03c3=0.0132, SGOV \u03c3=0.0001, \u03c1=0.007. Min-variance weights: XLF=0.000, SGOV=1.000.", "question": "Assets: XLF, SGOV\nXLF: annualized_mean_return=-0.2520, daily_std=0.0132\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0843\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_SGOV=X.XXXX", "answer": "w_XLF=0.0001, w_SGOV=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000175 + 0.000000 - 0.000000)\n Unconstrained: w_XLF=0.0000\n After long-only clamp: w_XLF=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"XLF": 0.0001, "SGOV": 0.9999}, "sigma_1": 0.013221, "sigma_2": 0.000124, "covariance": 0.0, "correlation": 0.007, "has_text": true, "text_chars": 3020, "mu_floor": -0.0843, "constraint_binding": false}} +{"id": "T4_all_20230804_0352", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "IGOV"], "decision_date": "2023-08-04", "context_summary": "LINK-USD \u03c3=0.0453, IGOV \u03c3=0.0060, \u03c1=-0.176. Min-variance weights: LINK-USD=0.038, IGOV=0.962.", "question": "Assets: LINK-USD, IGOV\nLINK-USD: annualized_mean_return=0.5796, daily_std=0.0453\nIGOV: annualized_mean_return=-0.1512, daily_std=0.0060\nMinimum required portfolio return (annualized): 0.3599\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_IGOV=X.XXXX", "answer": "w_LINK-USD=0.6994, w_IGOV=0.3006", "answer_numeric": 0.6994, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000036 - -0.000048) / (0.002054 + 0.000036 - -0.000096)\n Unconstrained: w_LINK-USD=0.0384\n After long-only clamp: w_LINK-USD=0.0384, w_IGOV=0.9616.", "metadata": {"weights": {"LINK-USD": 0.6994, "IGOV": 0.3006}, "sigma_1": 0.045325, "sigma_2": 0.00601, "covariance": -4.8e-05, "correlation": -0.1758, "has_text": true, "text_chars": 20, "mu_floor": 0.3599, "constraint_binding": true}} +{"id": "T4_all_20230828_0355", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SCHH"], "decision_date": "2023-08-28", "context_summary": "IWM \u03c3=0.0107, SCHH \u03c3=0.0092, \u03c1=0.656. Min-variance weights: IWM=0.292, SCHH=0.708.", "question": "Assets: IWM, SCHH\nIWM: annualized_mean_return=0.2520, daily_std=0.0107\nSCHH: annualized_mean_return=0.1008, daily_std=0.0092\nMinimum required portfolio return (annualized): 0.1298\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_SCHH=X.XXXX", "answer": "w_IWM=0.2922, w_SCHH=0.7078", "answer_numeric": 0.2922, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000086 - 0.000065) / (0.000115 + 0.000086 - 0.000130)\n Unconstrained: w_IWM=0.2925\n After long-only clamp: w_IWM=0.2925, w_SCHH=0.7075.", "metadata": {"weights": {"IWM": 0.2922, "SCHH": 0.7078}, "sigma_1": 0.010713, "sigma_2": 0.009249, "covariance": 6.5e-05, "correlation": 0.6556, "has_text": true, "text_chars": 3020, "mu_floor": 0.1298, "constraint_binding": false}} +{"id": "T4_all_20230123_0358", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "CSHI"], "decision_date": "2023-01-23", "context_summary": "AVAX-USD \u03c3=0.0457, CSHI \u03c3=0.0005, \u03c1=-0.025. Min-variance weights: AVAX-USD=0.000, CSHI=1.000.", "question": "Assets: AVAX-USD, CSHI\nAVAX-USD: annualized_mean_return=1.4616, daily_std=0.0457\nCSHI: annualized_mean_return=0.0756, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.5781\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_AVAX-USD=0.3626, w_CSHI=0.6374", "answer_numeric": 0.3626, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.002086 + 0.000000 - -0.000001)\n Unconstrained: w_AVAX-USD=0.0004\n After long-only clamp: w_AVAX-USD=0.0004, w_CSHI=0.9996.", "metadata": {"weights": {"AVAX-USD": 0.3626, "CSHI": 0.6374}, "sigma_1": 0.045673, "sigma_2": 0.000511, "covariance": -1e-06, "correlation": -0.025, "has_text": true, "text_chars": 20, "mu_floor": 0.5781, "constraint_binding": true}} +{"id": "T4_all_20231120_0360", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "SCHH"], "decision_date": "2023-11-20", "context_summary": "AVAX-USD \u03c3=0.0513, SCHH \u03c3=0.0133, \u03c1=0.188. Min-variance weights: AVAX-USD=0.019, SCHH=0.981.", "question": "Assets: AVAX-USD, SCHH\nAVAX-USD: annualized_mean_return=4.2336, daily_std=0.0513\nSCHH: annualized_mean_return=-0.1008, daily_std=0.0133\nMinimum required portfolio return (annualized): 2.2719\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_SCHH=X.XXXX", "answer": "w_AVAX-USD=0.5474, w_SCHH=0.4526", "answer_numeric": 0.5474, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000176 - 0.000128) / (0.002628 + 0.000176 - 0.000256)\n Unconstrained: w_AVAX-USD=0.0187\n After long-only clamp: w_AVAX-USD=0.0187, w_SCHH=0.9813.", "metadata": {"weights": {"AVAX-USD": 0.5474, "SCHH": 0.4526}, "sigma_1": 0.051266, "sigma_2": 0.013254, "covariance": 0.000128, "correlation": 0.1884, "has_text": true, "text_chars": 20, "mu_floor": 2.2719, "constraint_binding": true}} +{"id": "T4_all_20240205_0363", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "IGOV"], "decision_date": "2024-02-05", "context_summary": "ACWI \u03c3=0.0064, IGOV \u03c3=0.0061, \u03c1=0.150. Min-variance weights: ACWI=0.468, IGOV=0.532.", "question": "Assets: ACWI, IGOV\nACWI: annualized_mean_return=0.4536, daily_std=0.0064\nIGOV: annualized_mean_return=0.1764, daily_std=0.0061\nMinimum required portfolio return (annualized): 0.2473\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ACWI=X.XXXX, w_IGOV=X.XXXX", "answer": "w_ACWI=0.4680, w_IGOV=0.5320", "answer_numeric": 0.468, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000037 - 0.000006) / (0.000041 + 0.000037 - 0.000012)\n Unconstrained: w_ACWI=0.4681\n After long-only clamp: w_ACWI=0.4681, w_IGOV=0.5319.", "metadata": {"weights": {"ACWI": 0.468, "IGOV": 0.532}, "sigma_1": 0.006437, "sigma_2": 0.006097, "covariance": 6e-06, "correlation": 0.1498, "has_text": true, "text_chars": 9046, "mu_floor": 0.2473, "constraint_binding": false}} +{"id": "T4_all_20240513_0366", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX", "TLH"], "decision_date": "2024-05-13", "context_summary": "^VIX \u03c3=0.0493, TLH \u03c3=0.0064, \u03c1=-0.163. Min-variance weights: ^VIX=0.036, TLH=0.964.", "question": "Assets: ^VIX, TLH\n^VIX: annualized_mean_return=-0.5796, daily_std=0.0493\nTLH: annualized_mean_return=-0.0504, daily_std=0.0064\nMinimum required portfolio return (annualized): -0.0598\nMarket regime: bull\n\nCompute portfolio weights (w_^VIX, w_TLH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_^VIX=X.XXXX, w_TLH=X.XXXX", "answer": "w_^VIX=0.0178, w_TLH=0.9822", "answer_numeric": 0.0178, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000041 - -0.000051) / (0.002435 + 0.000041 - -0.000103)\n Unconstrained: w_^VIX=0.0357\n After long-only clamp: w_^VIX=0.0357, w_TLH=0.9643.", "metadata": {"weights": {"^VIX": 0.0178, "TLH": 0.9822}, "sigma_1": 0.049348, "sigma_2": 0.006387, "covariance": -5.1e-05, "correlation": -0.163, "has_text": true, "text_chars": 9045, "mu_floor": -0.0598, "constraint_binding": true}} +{"id": "T4_all_20231129_0369", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "LQD"], "decision_date": "2023-11-29", "context_summary": "ETH-USD \u03c3=0.0264, LQD \u03c3=0.0064, \u03c1=0.127. Min-variance weights: ETH-USD=0.028, LQD=0.972.", "question": "Assets: ETH-USD, LQD\nETH-USD: annualized_mean_return=0.9576, daily_std=0.0264\nLQD: annualized_mean_return=0.1008, daily_std=0.0064\nMinimum required portfolio return (annualized): 0.1127\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_LQD=X.XXXX", "answer": "w_ETH-USD=0.0283, w_LQD=0.9717", "answer_numeric": 0.0283, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000041 - 0.000021) / (0.000695 + 0.000041 - 0.000043)\n Unconstrained: w_ETH-USD=0.0277\n After long-only clamp: w_ETH-USD=0.0277, w_LQD=0.9723.", "metadata": {"weights": {"ETH-USD": 0.0283, "LQD": 0.9717}, "sigma_1": 0.026371, "sigma_2": 0.006376, "covariance": 2.1e-05, "correlation": 0.1275, "has_text": true, "text_chars": 20, "mu_floor": 0.1127, "constraint_binding": false}} +{"id": "T4_all_20240527_0371", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ITB"], "decision_date": "2024-05-27", "context_summary": "BNB-USD \u03c3=0.0250, ITB \u03c3=0.0155, \u03c1=-0.044. Min-variance weights: BNB-USD=0.286, ITB=0.714.", "question": "Assets: BNB-USD, ITB\nBNB-USD: annualized_mean_return=0.2520, daily_std=0.0250\nITB: annualized_mean_return=-0.0756, daily_std=0.0155\nMinimum required portfolio return (annualized): -0.0279\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_ITB=X.XXXX", "answer": "w_BNB-USD=0.2865, w_ITB=0.7135", "answer_numeric": 0.2865, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000242 - -0.000017) / (0.000627 + 0.000242 - -0.000034)\n Unconstrained: w_BNB-USD=0.2864\n After long-only clamp: w_BNB-USD=0.2864, w_ITB=0.7136.", "metadata": {"weights": {"BNB-USD": 0.2865, "ITB": 0.7135}, "sigma_1": 0.025039, "sigma_2": 0.015542, "covariance": -1.7e-05, "correlation": -0.0435, "has_text": true, "text_chars": 20, "mu_floor": -0.0279, "constraint_binding": false}} +{"id": "T4_all_20230808_0374", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "VNQ"], "decision_date": "2023-08-08", "context_summary": "BNB-USD \u03c3=0.0223, VNQ \u03c3=0.0101, \u03c1=0.103. Min-variance weights: BNB-USD=0.141, VNQ=0.859.", "question": "Assets: BNB-USD, VNQ\nBNB-USD: annualized_mean_return=-0.2772, daily_std=0.0223\nVNQ: annualized_mean_return=0.1260, daily_std=0.0101\nMinimum required portfolio return (annualized): 0.0906\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_BNB-USD=0.0878, w_VNQ=0.9122", "answer_numeric": 0.0878, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000101 - 0.000023) / (0.000497 + 0.000101 - 0.000046)\n Unconstrained: w_BNB-USD=0.1415\n After long-only clamp: w_BNB-USD=0.1415, w_VNQ=0.8585.", "metadata": {"weights": {"BNB-USD": 0.0878, "VNQ": 0.9122}, "sigma_1": 0.022288, "sigma_2": 0.010056, "covariance": 2.3e-05, "correlation": 0.1029, "has_text": true, "text_chars": 20, "mu_floor": 0.0906, "constraint_binding": true}} +{"id": "T4_all_20240206_0376", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "USO"], "decision_date": "2024-02-06", "context_summary": "BTC-USD \u03c3=0.0243, USO \u03c3=0.0194, \u03c1=0.250. Min-variance weights: BTC-USD=0.353, USO=0.646.", "question": "Assets: BTC-USD, USO\nBTC-USD: annualized_mean_return=0.0252, daily_std=0.0243\nUSO: annualized_mean_return=-0.2268, daily_std=0.0194\nMinimum required portfolio return (annualized): -0.0765\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_USO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_USO=X.XXXX", "answer": "w_BTC-USD=0.5964, w_USO=0.4036", "answer_numeric": 0.5964, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000377 - 0.000118) / (0.000592 + 0.000377 - 0.000236)\n Unconstrained: w_BTC-USD=0.3535\n After long-only clamp: w_BTC-USD=0.3535, w_USO=0.6465.", "metadata": {"weights": {"BTC-USD": 0.5964, "USO": 0.4036}, "sigma_1": 0.024326, "sigma_2": 0.019415, "covariance": 0.000118, "correlation": 0.2495, "has_text": true, "text_chars": 20, "mu_floor": -0.0765, "constraint_binding": true}} +{"id": "T4_all_20240124_0378", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "SOYB"], "decision_date": "2024-01-24", "context_summary": "MATIC-USD \u03c3=0.0442, SOYB \u03c3=0.0095, \u03c1=-0.171. Min-variance weights: MATIC-USD=0.074, SOYB=0.926.", "question": "Assets: MATIC-USD, SOYB\nMATIC-USD: annualized_mean_return=0.0504, daily_std=0.0442\nSOYB: annualized_mean_return=-0.3024, daily_std=0.0095\nMinimum required portfolio return (annualized): -0.0663\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_SOYB=X.XXXX", "answer": "w_MATIC-USD=0.6692, w_SOYB=0.3308", "answer_numeric": 0.6692, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000090 - -0.000072) / (0.001953 + 0.000090 - -0.000143)\n Unconstrained: w_MATIC-USD=0.0737\n After long-only clamp: w_MATIC-USD=0.0737, w_SOYB=0.9263.", "metadata": {"weights": {"MATIC-USD": 0.6692, "SOYB": 0.3308}, "sigma_1": 0.044197, "sigma_2": 0.009462, "covariance": -7.2e-05, "correlation": -0.171, "has_text": true, "text_chars": 20, "mu_floor": -0.0663, "constraint_binding": true}} +{"id": "T4_all_20240418_0381", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "ICSH"], "decision_date": "2024-04-18", "context_summary": "ETH-USD \u03c3=0.0383, ICSH \u03c3=0.0002, \u03c1=0.007. Min-variance weights: ETH-USD=0.000, ICSH=1.000.", "question": "Assets: ETH-USD, ICSH\nETH-USD: annualized_mean_return=0.4788, daily_std=0.0383\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_ETH-USD=0.0000, w_ICSH=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.001463 + 0.000000 - 0.000000)\n Unconstrained: w_ETH-USD=-0.0000\n After long-only clamp: w_ETH-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.038255, "sigma_2": 0.000221, "covariance": 0.0, "correlation": 0.007, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20230719_0384", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "USO"], "decision_date": "2023-07-19", "context_summary": "XLU \u03c3=0.0089, USO \u03c3=0.0205, \u03c1=0.146. Min-variance weights: XLU=0.882, USO=0.118.", "question": "Assets: XLU, USO\nXLU: annualized_mean_return=-0.2016, daily_std=0.0089\nUSO: annualized_mean_return=0.3528, daily_std=0.0205\nMinimum required portfolio return (annualized): 0.1685\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_USO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_USO=X.XXXX", "answer": "w_XLU=0.3324, w_USO=0.6676", "answer_numeric": 0.3324, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000422 - 0.000027) / (0.000080 + 0.000422 - 0.000054)\n Unconstrained: w_XLU=0.8816\n After long-only clamp: w_XLU=0.8816, w_USO=0.1184.", "metadata": {"weights": {"XLU": 0.3324, "USO": 0.6676}, "sigma_1": 0.008941, "sigma_2": 0.020542, "covariance": 2.7e-05, "correlation": 0.1462, "has_text": true, "text_chars": 3020, "mu_floor": 0.1685, "constraint_binding": true}} +{"id": "T4_all_20230816_0386", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "PPLT"], "decision_date": "2023-08-16", "context_summary": "XLP \u03c3=0.0063, PPLT \u03c3=0.0129, \u03c1=0.090. Min-variance weights: XLP=0.831, PPLT=0.169.", "question": "Assets: XLP, PPLT\nXLP: annualized_mean_return=-0.1008, daily_std=0.0063\nPPLT: annualized_mean_return=-0.5544, daily_std=0.0129\nMinimum required portfolio return (annualized): -0.1227\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_PPLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_PPLT=X.XXXX", "answer": "w_XLP=0.9517, w_PPLT=0.0483", "answer_numeric": 0.9517, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000165 - 0.000007) / (0.000039 + 0.000165 - 0.000014)\n Unconstrained: w_XLP=0.8310\n After long-only clamp: w_XLP=0.8310, w_PPLT=0.1690.", "metadata": {"weights": {"XLP": 0.9517, "PPLT": 0.0483}, "sigma_1": 0.006276, "sigma_2": 0.012858, "covariance": 7e-06, "correlation": 0.0895, "has_text": true, "text_chars": 3020, "mu_floor": -0.1227, "constraint_binding": true}} +{"id": "T4_all_20230116_0388", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "IYR"], "decision_date": "2023-01-16", "context_summary": "IWM \u03c3=0.0147, IYR \u03c3=0.0145, \u03c1=0.860. Min-variance weights: IWM=0.441, IYR=0.559.", "question": "Assets: IWM, IYR\nIWM: annualized_mean_return=0.2268, daily_std=0.0147\nIYR: annualized_mean_return=0.2772, daily_std=0.0145\nMinimum required portfolio return (annualized): 0.2634\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_IYR=X.XXXX", "answer": "w_IWM=0.2738, w_IYR=0.7262", "answer_numeric": 0.2738, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000210 - 0.000183) / (0.000217 + 0.000210 - 0.000367)\n Unconstrained: w_IWM=0.4407\n After long-only clamp: w_IWM=0.4407, w_IYR=0.5593.", "metadata": {"weights": {"IWM": 0.2738, "IYR": 0.7262}, "sigma_1": 0.014727, "sigma_2": 0.014484, "covariance": 0.000183, "correlation": 0.86, "has_text": true, "text_chars": 3020, "mu_floor": 0.2634, "constraint_binding": true}} +{"id": "T4_all_20241023_0391", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "SHY"], "decision_date": "2024-10-23", "context_summary": "LINK-USD \u03c3=0.0317, SHY \u03c3=0.0011, \u03c1=0.082. Min-variance weights: LINK-USD=0.000, SHY=1.000.", "question": "Assets: LINK-USD, SHY\nLINK-USD: annualized_mean_return=0.1008, daily_std=0.0317\nSHY: annualized_mean_return=0.0504, daily_std=0.0011\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_LINK-USD=0.0000, w_SHY=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000003) / (0.001006 + 0.000001 - 0.000006)\n Unconstrained: w_LINK-USD=-0.0016\n After long-only clamp: w_LINK-USD=0.0000, w_SHY=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "SHY": 1.0}, "sigma_1": 0.031719, "sigma_2": 0.001108, "covariance": 3e-06, "correlation": 0.0819, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20230405_0394", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "PPLT"], "decision_date": "2023-04-05", "context_summary": "BNB-USD \u03c3=0.0262, PPLT \u03c3=0.0165, \u03c1=0.080. Min-variance weights: BNB-USD=0.267, PPLT=0.733.", "question": "Assets: BNB-USD, PPLT\nBNB-USD: annualized_mean_return=-0.2016, daily_std=0.0262\nPPLT: annualized_mean_return=-0.1260, daily_std=0.0165\nMinimum required portfolio return (annualized): -0.1398\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_PPLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_PPLT=X.XXXX", "answer": "w_BNB-USD=0.1825, w_PPLT=0.8175", "answer_numeric": 0.1825, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000273 - 0.000035) / (0.000689 + 0.000273 - 0.000070)\n Unconstrained: w_BNB-USD=0.2673\n After long-only clamp: w_BNB-USD=0.2673, w_PPLT=0.7327.", "metadata": {"weights": {"BNB-USD": 0.1825, "PPLT": 0.8175}, "sigma_1": 0.026244, "sigma_2": 0.016532, "covariance": 3.5e-05, "correlation": 0.0801, "has_text": true, "text_chars": 20, "mu_floor": -0.1398, "constraint_binding": true}} +{"id": "T4_all_20241127_0397", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "MTUM"], "decision_date": "2024-11-27", "context_summary": "XRP-USD \u03c3=0.0577, MTUM \u03c3=0.0084, \u03c1=0.086. Min-variance weights: XRP-USD=0.009, MTUM=0.992.", "question": "Assets: XRP-USD, MTUM\nXRP-USD: annualized_mean_return=4.0572, daily_std=0.0577\nMTUM: annualized_mean_return=0.5292, daily_std=0.0084\nMinimum required portfolio return (annualized): 0.5570\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_MTUM) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_MTUM=X.XXXX", "answer": "w_XRP-USD=0.0084, w_MTUM=0.9916", "answer_numeric": 0.0084, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000070 - 0.000042) / (0.003333 + 0.000070 - 0.000083)\n Unconstrained: w_XRP-USD=0.0085\n After long-only clamp: w_XRP-USD=0.0085, w_MTUM=0.9915.", "metadata": {"weights": {"XRP-USD": 0.0084, "MTUM": 0.9916}, "sigma_1": 0.05773, "sigma_2": 0.008366, "covariance": 4.2e-05, "correlation": 0.0864, "has_text": true, "text_chars": 20, "mu_floor": 0.557, "constraint_binding": false}} +{"id": "T4_all_20240805_0398", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "VNQ"], "decision_date": "2024-08-05", "context_summary": "XLK \u03c3=0.0154, VNQ \u03c3=0.0089, \u03c1=-0.073. Min-variance weights: XLK=0.265, VNQ=0.736.", "question": "Assets: XLK, VNQ\nXLK: annualized_mean_return=-0.0000, daily_std=0.0154\nVNQ: annualized_mean_return=0.5040, daily_std=0.0089\nMinimum required portfolio return (annualized): 0.4550\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_VNQ=X.XXXX", "answer": "w_XLK=0.0972, w_VNQ=0.9028", "answer_numeric": 0.0972, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000079 - -0.000010) / (0.000237 + 0.000079 - -0.000020)\n Unconstrained: w_XLK=0.2645\n After long-only clamp: w_XLK=0.2645, w_VNQ=0.7355.", "metadata": {"weights": {"XLK": 0.0972, "VNQ": 0.9028}, "sigma_1": 0.01541, "sigma_2": 0.008886, "covariance": -1e-05, "correlation": -0.0733, "has_text": true, "text_chars": 9046, "mu_floor": 0.455, "constraint_binding": true}} +{"id": "T4_all_20240904_0401", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "IGOV"], "decision_date": "2024-09-04", "context_summary": "XLI \u03c3=0.0100, IGOV \u03c3=0.0052, \u03c1=0.023. Min-variance weights: XLI=0.209, IGOV=0.791.", "question": "Assets: XLI, IGOV\nXLI: annualized_mean_return=0.2268, daily_std=0.0100\nIGOV: annualized_mean_return=0.2268, daily_std=0.0052\nMinimum required portfolio return (annualized): 0.2268\nMarket regime: bull\n\nCompute portfolio weights (w_XLI, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_IGOV=X.XXXX", "answer": "w_XLI=0.2096, w_IGOV=0.7904", "answer_numeric": 0.2096, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000027 - 0.000001) / (0.000099 + 0.000027 - 0.000002)\n Unconstrained: w_XLI=0.2087\n After long-only clamp: w_XLI=0.2087, w_IGOV=0.7913.", "metadata": {"weights": {"XLI": 0.2096, "IGOV": 0.7904}, "sigma_1": 0.009953, "sigma_2": 0.005196, "covariance": 1e-06, "correlation": 0.0229, "has_text": true, "text_chars": 9045, "mu_floor": 0.2268, "constraint_binding": false}} +{"id": "T4_all_20241004_0404", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "INDS"], "decision_date": "2024-10-04", "context_summary": "MTUM \u03c3=0.0150, INDS \u03c3=0.0106, \u03c1=0.333. Min-variance weights: MTUM=0.260, INDS=0.740.", "question": "Assets: MTUM, INDS\nMTUM: annualized_mean_return=-0.0252, daily_std=0.0150\nINDS: annualized_mean_return=0.4032, daily_std=0.0106\nMinimum required portfolio return (annualized): 0.3619\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_INDS=X.XXXX", "answer": "w_MTUM=0.0964, w_INDS=0.9036", "answer_numeric": 0.0964, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000113 - 0.000053) / (0.000224 + 0.000113 - 0.000106)\n Unconstrained: w_MTUM=0.2596\n After long-only clamp: w_MTUM=0.2596, w_INDS=0.7404.", "metadata": {"weights": {"MTUM": 0.0964, "INDS": 0.9036}, "sigma_1": 0.014966, "sigma_2": 0.010627, "covariance": 5.3e-05, "correlation": 0.3332, "has_text": true, "text_chars": 9045, "mu_floor": 0.3619, "constraint_binding": true}} +{"id": "T4_all_20241230_0407", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ICSH"], "decision_date": "2024-12-30", "context_summary": "QUAL \u03c3=0.0074, ICSH \u03c3=0.0003, \u03c1=0.017. Min-variance weights: QUAL=0.001, ICSH=0.999.", "question": "Assets: QUAL, ICSH\nQUAL: annualized_mean_return=0.0504, daily_std=0.0074\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0739\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_ICSH=X.XXXX", "answer": "w_QUAL=0.0018, w_ICSH=0.9982", "answer_numeric": 0.0018, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000055 + 0.000000 - 0.000000)\n Unconstrained: w_QUAL=0.0011\n After long-only clamp: w_QUAL=0.0011, w_ICSH=0.9989.", "metadata": {"weights": {"QUAL": 0.0018, "ICSH": 0.9982}, "sigma_1": 0.007424, "sigma_2": 0.000311, "covariance": 0.0, "correlation": 0.0166, "has_text": true, "text_chars": 9045, "mu_floor": 0.0739, "constraint_binding": false}} +{"id": "T4_all_20230621_0410", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "VNQ"], "decision_date": "2023-06-21", "context_summary": "ETH-USD \u03c3=0.0209, VNQ \u03c3=0.0112, \u03c1=0.006. Min-variance weights: ETH-USD=0.221, VNQ=0.779.", "question": "Assets: ETH-USD, VNQ\nETH-USD: annualized_mean_return=-0.0756, daily_std=0.0209\nVNQ: annualized_mean_return=0.3276, daily_std=0.0112\nMinimum required portfolio return (annualized): 0.3001\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_ETH-USD=0.0682, w_VNQ=0.9318", "answer_numeric": 0.0682, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000125 - 0.000001) / (0.000437 + 0.000125 - 0.000003)\n Unconstrained: w_ETH-USD=0.2209\n After long-only clamp: w_ETH-USD=0.2209, w_VNQ=0.7791.", "metadata": {"weights": {"ETH-USD": 0.0682, "VNQ": 0.9318}, "sigma_1": 0.020904, "sigma_2": 0.011178, "covariance": 1e-06, "correlation": 0.0062, "has_text": true, "text_chars": 20, "mu_floor": 0.3001, "constraint_binding": true}} +{"id": "T4_all_20240116_0411", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "CPER"], "decision_date": "2024-01-16", "context_summary": "MATIC-USD \u03c3=0.0458, CPER \u03c3=0.0102, \u03c1=0.010. Min-variance weights: MATIC-USD=0.045, CPER=0.955.", "question": "Assets: MATIC-USD, CPER\nMATIC-USD: annualized_mean_return=0.2520, daily_std=0.0458\nCPER: annualized_mean_return=0.1260, daily_std=0.0102\nMinimum required portfolio return (annualized): 0.1311\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_CPER) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_CPER=X.XXXX", "answer": "w_MATIC-USD=0.0449, w_CPER=0.9551", "answer_numeric": 0.0449, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000103 - 0.000005) / (0.002095 + 0.000103 - 0.000009)\n Unconstrained: w_MATIC-USD=0.0450\n After long-only clamp: w_MATIC-USD=0.0450, w_CPER=0.9550.", "metadata": {"weights": {"MATIC-USD": 0.0449, "CPER": 0.9551}, "sigma_1": 0.045776, "sigma_2": 0.010157, "covariance": 5e-06, "correlation": 0.01, "has_text": true, "text_chars": 20, "mu_floor": 0.1311, "constraint_binding": false}} +{"id": "T4_all_20240723_0414", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ICSH"], "decision_date": "2024-07-23", "context_summary": "VTI \u03c3=0.0061, ICSH \u03c3=0.0002, \u03c1=-0.039. Min-variance weights: VTI=0.003, ICSH=0.997.", "question": "Assets: VTI, ICSH\nVTI: annualized_mean_return=0.3780, daily_std=0.0061\nICSH: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.1969\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_ICSH=X.XXXX", "answer": "w_VTI=0.4011, w_ICSH=0.5989", "answer_numeric": 0.4011, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000037 + 0.000000 - -0.000000)\n Unconstrained: w_VTI=0.0032\n After long-only clamp: w_VTI=0.0032, w_ICSH=0.9968.", "metadata": {"weights": {"VTI": 0.4011, "ICSH": 0.5989}, "sigma_1": 0.006116, "sigma_2": 0.000247, "covariance": -0.0, "correlation": -0.0387, "has_text": true, "text_chars": 9045, "mu_floor": 0.1969, "constraint_binding": true}} +{"id": "T4_all_20240221_0416", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "FXI"], "decision_date": "2024-02-21", "context_summary": "ETH-USD \u03c3=0.0279, FXI \u03c3=0.0184, \u03c1=0.070. Min-variance weights: ETH-USD=0.289, FXI=0.711.", "question": "Assets: ETH-USD, FXI\nETH-USD: annualized_mean_return=1.1844, daily_std=0.0279\nFXI: annualized_mean_return=-0.4788, daily_std=0.0184\nMinimum required portfolio return (annualized): 0.3192\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_FXI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_FXI=X.XXXX", "answer": "w_ETH-USD=0.4798, w_FXI=0.5202", "answer_numeric": 0.4798, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000337 - 0.000036) / (0.000776 + 0.000337 - 0.000071)\n Unconstrained: w_ETH-USD=0.2894\n After long-only clamp: w_ETH-USD=0.2894, w_FXI=0.7106.", "metadata": {"weights": {"ETH-USD": 0.4798, "FXI": 0.5202}, "sigma_1": 0.027853, "sigma_2": 0.01836, "covariance": 3.6e-05, "correlation": 0.0698, "has_text": true, "text_chars": 20, "mu_floor": 0.3192, "constraint_binding": true}} +{"id": "T4_all_20231130_0419", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "VNQ"], "decision_date": "2023-11-30", "context_summary": "ETH-USD \u03c3=0.0264, VNQ \u03c3=0.0131, \u03c1=0.152. Min-variance weights: ETH-USD=0.157, VNQ=0.843.", "question": "Assets: ETH-USD, VNQ\nETH-USD: annualized_mean_return=0.9072, daily_std=0.0264\nVNQ: annualized_mean_return=-0.0504, daily_std=0.0131\nMinimum required portfolio return (annualized): 0.0911\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_ETH-USD=0.1567, w_VNQ=0.8433", "answer_numeric": 0.1567, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000173 - 0.000053) / (0.000698 + 0.000173 - 0.000106)\n Unconstrained: w_ETH-USD=0.1568\n After long-only clamp: w_ETH-USD=0.1568, w_VNQ=0.8432.", "metadata": {"weights": {"ETH-USD": 0.1567, "VNQ": 0.8433}, "sigma_1": 0.026425, "sigma_2": 0.013148, "covariance": 5.3e-05, "correlation": 0.152, "has_text": true, "text_chars": 20, "mu_floor": 0.0911, "constraint_binding": false}} +{"id": "T4_all_20241014_0422", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD"], "decision_date": "2024-10-14", "context_summary": "FXI \u03c3=0.0189, LINK-USD \u03c3=0.0329, \u03c1=-0.109. Min-variance weights: FXI=0.731, LINK-USD=0.269.", "question": "Assets: FXI, LINK-USD\nFXI: annualized_mean_return=0.8568, daily_std=0.0189\nLINK-USD: annualized_mean_return=0.2772, daily_std=0.0329\nMinimum required portfolio return (annualized): 0.7513\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_LINK-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_LINK-USD=X.XXXX", "answer": "w_FXI=0.8180, w_LINK-USD=0.1820", "answer_numeric": 0.818, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001080 - -0.000067) / (0.000356 + 0.001080 - -0.000135)\n Unconstrained: w_FXI=0.7306\n After long-only clamp: w_FXI=0.7306, w_LINK-USD=0.2694.", "metadata": {"weights": {"FXI": 0.818, "LINK-USD": 0.182}, "sigma_1": 0.018863, "sigma_2": 0.032867, "covariance": -6.7e-05, "correlation": -0.1087, "has_text": true, "text_chars": 9045, "mu_floor": 0.7513, "constraint_binding": true}} +{"id": "T4_all_20230829_0425", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SHY"], "decision_date": "2023-08-29", "context_summary": "VTI \u03c3=0.0067, SHY \u03c3=0.0012, \u03c1=0.215. Min-variance weights: VTI=0.000, SHY=1.000.", "question": "Assets: VTI, SHY\nVTI: annualized_mean_return=0.2268, daily_std=0.0067\nSHY: annualized_mean_return=-0.0000, daily_std=0.0012\nMinimum required portfolio return (annualized): -0.0000\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_SHY=X.XXXX", "answer": "w_VTI=0.0000, w_SHY=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000002) / (0.000045 + 0.000001 - 0.000003)\n Unconstrained: w_VTI=-0.0073\n After long-only clamp: w_VTI=0.0000, w_SHY=1.0000.", "metadata": {"weights": {"VTI": 0.0, "SHY": 1.0}, "sigma_1": 0.006738, "sigma_2": 0.001186, "covariance": 2e-06, "correlation": 0.2154, "has_text": true, "text_chars": 3020, "mu_floor": -0.0, "constraint_binding": false}} +{"id": "T4_all_20230413_0428", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "GLD"], "decision_date": "2023-04-13", "context_summary": "MTUM \u03c3=0.0095, GLD \u03c3=0.0100, \u03c1=-0.194. Min-variance weights: MTUM=0.520, GLD=0.480.", "question": "Assets: MTUM, GLD\nMTUM: annualized_mean_return=-0.0504, daily_std=0.0095\nGLD: annualized_mean_return=0.2268, daily_std=0.0100\nMinimum required portfolio return (annualized): 0.1146\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_GLD=X.XXXX", "answer": "w_MTUM=0.4048, w_GLD=0.5952", "answer_numeric": 0.4048, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000099 - -0.000018) / (0.000090 + 0.000099 - -0.000037)\n Unconstrained: w_MTUM=0.5200\n After long-only clamp: w_MTUM=0.5200, w_GLD=0.4800.", "metadata": {"weights": {"MTUM": 0.4048, "GLD": 0.5952}, "sigma_1": 0.009493, "sigma_2": 0.009957, "covariance": -1.8e-05, "correlation": -0.1944, "has_text": true, "text_chars": 3020, "mu_floor": 0.1146, "constraint_binding": true}} +{"id": "T4_all_20240816_0431", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BIL"], "decision_date": "2024-08-16", "context_summary": "VEA \u03c3=0.0095, BIL \u03c3=0.0002, \u03c1=0.048. Min-variance weights: VEA=0.000, BIL=1.000.", "question": "Assets: VEA, BIL\nVEA: annualized_mean_return=-0.0000, daily_std=0.0095\nBIL: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0625\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_BIL=X.XXXX", "answer": "w_VEA=0.0003, w_BIL=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000090 + 0.000000 - 0.000000)\n Unconstrained: w_VEA=-0.0005\n After long-only clamp: w_VEA=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"VEA": 0.0003, "BIL": 0.9997}, "sigma_1": 0.009507, "sigma_2": 0.000152, "covariance": 0.0, "correlation": 0.0482, "has_text": true, "text_chars": 9045, "mu_floor": 0.0625, "constraint_binding": false}} +{"id": "T4_all_20230622_0434", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "IAU"], "decision_date": "2023-06-22", "context_summary": "VTI \u03c3=0.0077, IAU \u03c3=0.0080, \u03c1=0.213. Min-variance weights: VTI=0.529, IAU=0.471.", "question": "Assets: VTI, IAU\nVTI: annualized_mean_return=0.4032, daily_std=0.0077\nIAU: annualized_mean_return=-0.0756, daily_std=0.0080\nMinimum required portfolio return (annualized): 0.2661\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_IAU) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_IAU=X.XXXX", "answer": "w_VTI=0.7137, w_IAU=0.2863", "answer_numeric": 0.7137, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000065 - 0.000013) / (0.000059 + 0.000065 - 0.000026)\n Unconstrained: w_VTI=0.5293\n After long-only clamp: w_VTI=0.5293, w_IAU=0.4707.", "metadata": {"weights": {"VTI": 0.7137, "IAU": 0.2863}, "sigma_1": 0.007677, "sigma_2": 0.008039, "covariance": 1.3e-05, "correlation": 0.2131, "has_text": true, "text_chars": 3020, "mu_floor": 0.2661, "constraint_binding": true}} +{"id": "T4_all_20240813_0437", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "IAU"], "decision_date": "2024-08-13", "context_summary": "XLP \u03c3=0.0069, IAU \u03c3=0.0102, \u03c1=0.110. Min-variance weights: XLP=0.707, IAU=0.293.", "question": "Assets: XLP, IAU\nXLP: annualized_mean_return=0.1008, daily_std=0.0069\nIAU: annualized_mean_return=0.1764, daily_std=0.0102\nMinimum required portfolio return (annualized): 0.1181\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_IAU) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_IAU=X.XXXX", "answer": "w_XLP=0.7073, w_IAU=0.2927", "answer_numeric": 0.7073, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000104 - 0.000008) / (0.000048 + 0.000104 - 0.000015)\n Unconstrained: w_XLP=0.7065\n After long-only clamp: w_XLP=0.7065, w_IAU=0.2935.", "metadata": {"weights": {"XLP": 0.7073, "IAU": 0.2927}, "sigma_1": 0.006897, "sigma_2": 0.01018, "covariance": 8e-06, "correlation": 0.1103, "has_text": true, "text_chars": 9045, "mu_floor": 0.1181, "constraint_binding": false}} +{"id": "T4_all_20230104_0439", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ITB"], "decision_date": "2023-01-04", "context_summary": "IWM \u03c3=0.0158, ITB \u03c3=0.0196, \u03c1=0.803. Min-variance weights: IWM=0.994, ITB=0.006.", "question": "Assets: IWM, ITB\nIWM: annualized_mean_return=-0.1008, daily_std=0.0158\nITB: annualized_mean_return=0.2016, daily_std=0.0196\nMinimum required portfolio return (annualized): -0.0994\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_ITB=X.XXXX", "answer": "w_IWM=0.9946, w_ITB=0.0054", "answer_numeric": 0.9946, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000384 - 0.000249) / (0.000250 + 0.000384 - 0.000498)\n Unconstrained: w_IWM=0.9940\n After long-only clamp: w_IWM=0.9940, w_ITB=0.0060.", "metadata": {"weights": {"IWM": 0.9946, "ITB": 0.0054}, "sigma_1": 0.015803, "sigma_2": 0.019606, "covariance": 0.000249, "correlation": 0.8034, "has_text": true, "text_chars": 3020, "mu_floor": -0.0994, "constraint_binding": false}} +{"id": "T4_all_20241217_0441", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VEA", "MORT"], "decision_date": "2024-12-17", "context_summary": "VEA \u03c3=0.0072, MORT \u03c3=0.0087, \u03c1=0.438. Min-variance weights: VEA=0.672, MORT=0.328.", "question": "Assets: VEA, MORT\nVEA: annualized_mean_return=-0.1764, daily_std=0.0072\nMORT: annualized_mean_return=-0.1512, daily_std=0.0087\nMinimum required portfolio return (annualized): -0.1705\nMarket regime: bull\n\nCompute portfolio weights (w_VEA, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_MORT=X.XXXX", "answer": "w_VEA=0.6698, w_MORT=0.3302", "answer_numeric": 0.6698, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000076 - 0.000027) / (0.000051 + 0.000076 - 0.000055)\n Unconstrained: w_VEA=0.6719\n After long-only clamp: w_VEA=0.6719, w_MORT=0.3281.", "metadata": {"weights": {"VEA": 0.6698, "MORT": 0.3302}, "sigma_1": 0.007166, "sigma_2": 0.008741, "covariance": 2.7e-05, "correlation": 0.4383, "has_text": true, "text_chars": 9045, "mu_floor": -0.1705, "constraint_binding": false}} +{"id": "T4_all_20230821_0444", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "INDS"], "decision_date": "2023-08-21", "context_summary": "LINK-USD \u03c3=0.0424, INDS \u03c3=0.0107, \u03c1=-0.052. Min-variance weights: LINK-USD=0.070, INDS=0.930.", "question": "Assets: LINK-USD, INDS\nLINK-USD: annualized_mean_return=0.5796, daily_std=0.0424\nINDS: annualized_mean_return=-0.2016, daily_std=0.0107\nMinimum required portfolio return (annualized): 0.0878\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_INDS=X.XXXX", "answer": "w_LINK-USD=0.3705, w_INDS=0.6295", "answer_numeric": 0.3705, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000114 - -0.000024) / (0.001802 + 0.000114 - -0.000047)\n Unconstrained: w_LINK-USD=0.0700\n After long-only clamp: w_LINK-USD=0.0700, w_INDS=0.9300.", "metadata": {"weights": {"LINK-USD": 0.3705, "INDS": 0.6295}, "sigma_1": 0.042445, "sigma_2": 0.010662, "covariance": -2.4e-05, "correlation": -0.0524, "has_text": true, "text_chars": 20, "mu_floor": 0.0878, "constraint_binding": true}} +{"id": "T4_all_20230713_0447", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "USO"], "decision_date": "2023-07-13", "context_summary": "BNB-USD \u03c3=0.0256, USO \u03c3=0.0208, \u03c1=0.095. Min-variance weights: BNB-USD=0.388, USO=0.612.", "question": "Assets: BNB-USD, USO\nBNB-USD: annualized_mean_return=-0.9324, daily_std=0.0256\nUSO: annualized_mean_return=0.2016, daily_std=0.0208\nMinimum required portfolio return (annualized): -0.3831\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_USO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_USO=X.XXXX", "answer": "w_BNB-USD=0.3877, w_USO=0.6123", "answer_numeric": 0.3877, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000432 - 0.000050) / (0.000653 + 0.000432 - 0.000101)\n Unconstrained: w_BNB-USD=0.3876\n After long-only clamp: w_BNB-USD=0.3876, w_USO=0.6124.", "metadata": {"weights": {"BNB-USD": 0.3877, "USO": 0.6123}, "sigma_1": 0.025552, "sigma_2": 0.020778, "covariance": 5e-05, "correlation": 0.095, "has_text": true, "text_chars": 20, "mu_floor": -0.3831, "constraint_binding": false}} +{"id": "T4_all_20230619_0449", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "IYR"], "decision_date": "2023-06-19", "context_summary": "XLY \u03c3=0.0111, IYR \u03c3=0.0110, \u03c1=0.533. Min-variance weights: XLY=0.491, IYR=0.509.", "question": "Assets: XLY, IYR\nXLY: annualized_mean_return=0.6552, daily_std=0.0111\nIYR: annualized_mean_return=0.3780, daily_std=0.0110\nMinimum required portfolio return (annualized): 0.4581\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_IYR=X.XXXX", "answer": "w_XLY=0.4913, w_IYR=0.5087", "answer_numeric": 0.4913, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000120 - 0.000065) / (0.000122 + 0.000120 - 0.000129)\n Unconstrained: w_XLY=0.4914\n After long-only clamp: w_XLY=0.4914, w_IYR=0.5086.", "metadata": {"weights": {"XLY": 0.4913, "IYR": 0.5087}, "sigma_1": 0.011061, "sigma_2": 0.010972, "covariance": 6.5e-05, "correlation": 0.5326, "has_text": true, "text_chars": 3020, "mu_floor": 0.4581, "constraint_binding": false}} +{"id": "T4_all_20230720_0452", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "CORN"], "decision_date": "2023-07-20", "context_summary": "SOL-USD \u03c3=0.0459, CORN \u03c3=0.0198, \u03c1=-0.252. Min-variance weights: SOL-USD=0.210, CORN=0.790.", "question": "Assets: SOL-USD, CORN\nSOL-USD: annualized_mean_return=1.3608, daily_std=0.0459\nCORN: annualized_mean_return=0.4788, daily_std=0.0198\nMinimum required portfolio return (annualized): 1.1776\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_CORN) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_CORN=X.XXXX", "answer": "w_SOL-USD=0.7923, w_CORN=0.2077", "answer_numeric": 0.7923, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000394 - -0.000229) / (0.002108 + 0.000394 - -0.000458)\n Unconstrained: w_SOL-USD=0.2103\n After long-only clamp: w_SOL-USD=0.2103, w_CORN=0.7897.", "metadata": {"weights": {"SOL-USD": 0.7923, "CORN": 0.2077}, "sigma_1": 0.045917, "sigma_2": 0.019837, "covariance": -0.000229, "correlation": -0.2516, "has_text": true, "text_chars": 20, "mu_floor": 1.1776, "constraint_binding": true}} +{"id": "T4_all_20231222_0455", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "VNQ"], "decision_date": "2023-12-22", "context_summary": "AVAX-USD \u03c3=0.0602, VNQ \u03c3=0.0135, \u03c1=0.140. Min-variance weights: AVAX-USD=0.019, VNQ=0.981.", "question": "Assets: AVAX-USD, VNQ\nAVAX-USD: annualized_mean_return=6.9048, daily_std=0.0602\nVNQ: annualized_mean_return=0.6048, daily_std=0.0135\nMinimum required portfolio return (annualized): 0.6582\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_AVAX-USD=0.0191, w_VNQ=0.9809", "answer_numeric": 0.0191, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000183 - 0.000114) / (0.003630 + 0.000183 - 0.000228)\n Unconstrained: w_AVAX-USD=0.0192\n After long-only clamp: w_AVAX-USD=0.0192, w_VNQ=0.9808.", "metadata": {"weights": {"AVAX-USD": 0.0191, "VNQ": 0.9809}, "sigma_1": 0.060247, "sigma_2": 0.013513, "covariance": 0.000114, "correlation": 0.1397, "has_text": true, "text_chars": 20, "mu_floor": 0.6582, "constraint_binding": false}} +{"id": "T4_all_20230815_0458", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "CSHI"], "decision_date": "2023-08-15", "context_summary": "XLK \u03c3=0.0118, CSHI \u03c3=0.0005, \u03c1=0.005. Min-variance weights: XLK=0.002, CSHI=0.998.", "question": "Assets: XLK, CSHI\nXLK: annualized_mean_return=0.4032, daily_std=0.0118\nCSHI: annualized_mean_return=0.0756, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.2091\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLK=0.4075, w_CSHI=0.5925", "answer_numeric": 0.4075, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000138 + 0.000000 - 0.000000)\n Unconstrained: w_XLK=0.0018\n After long-only clamp: w_XLK=0.0018, w_CSHI=0.9982.", "metadata": {"weights": {"XLK": 0.4075, "CSHI": 0.5925}, "sigma_1": 0.011752, "sigma_2": 0.000526, "covariance": 0.0, "correlation": 0.0053, "has_text": true, "text_chars": 3020, "mu_floor": 0.2091, "constraint_binding": true}} +{"id": "T4_all_20240326_0461", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "ICSH"], "decision_date": "2024-03-26", "context_summary": "USMV \u03c3=0.0042, ICSH \u03c3=0.0003, \u03c1=-0.081. Min-variance weights: USMV=0.009, ICSH=0.991.", "question": "Assets: USMV, ICSH\nUSMV: annualized_mean_return=0.2520, daily_std=0.0042\nICSH: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0260\nMarket regime: bull\n\nCompute portfolio weights (w_USMV, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_ICSH=X.XXXX", "answer": "w_USMV=0.0040, w_ICSH=0.9960", "answer_numeric": 0.004, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000018 + 0.000000 - -0.000000)\n Unconstrained: w_USMV=0.0091\n After long-only clamp: w_USMV=0.0091, w_ICSH=0.9909.", "metadata": {"weights": {"USMV": 0.004, "ICSH": 0.996}, "sigma_1": 0.004218, "sigma_2": 0.000268, "covariance": -0.0, "correlation": -0.0811, "has_text": true, "text_chars": 9045, "mu_floor": 0.026, "constraint_binding": false}} +{"id": "T4_all_20241227_0464", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "CSHI"], "decision_date": "2024-12-27", "context_summary": "XLB \u03c3=0.0080, CSHI \u03c3=0.0003, \u03c1=-0.100. Min-variance weights: XLB=0.005, CSHI=0.995.", "question": "Assets: XLB, CSHI\nXLB: annualized_mean_return=-0.4788, daily_std=0.0080\nCSHI: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0752\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLB=0.0007, w_CSHI=0.9993", "answer_numeric": 0.0007, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000065 + 0.000000 - -0.000000)\n Unconstrained: w_XLB=0.0053\n After long-only clamp: w_XLB=0.0053, w_CSHI=0.9947.", "metadata": {"weights": {"XLB": 0.0007, "CSHI": 0.9993}, "sigma_1": 0.008034, "sigma_2": 0.000311, "covariance": -0.0, "correlation": -0.0999, "has_text": true, "text_chars": 9045, "mu_floor": 0.0752, "constraint_binding": true}} +{"id": "T4_all_20240118_0466", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "VNQ"], "decision_date": "2024-01-18", "context_summary": "AVAX-USD \u03c3=0.0555, VNQ \u03c3=0.0128, \u03c1=-0.128. Min-variance weights: AVAX-USD=0.075, VNQ=0.925.", "question": "Assets: AVAX-USD, VNQ\nAVAX-USD: annualized_mean_return=2.4696, daily_std=0.0555\nVNQ: annualized_mean_return=0.5796, daily_std=0.0128\nMinimum required portfolio return (annualized): 2.0541\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_AVAX-USD=0.7802, w_VNQ=0.2198", "answer_numeric": 0.7802, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000164 - -0.000091) / (0.003077 + 0.000164 - -0.000182)\n Unconstrained: w_AVAX-USD=0.0746\n After long-only clamp: w_AVAX-USD=0.0746, w_VNQ=0.9254.", "metadata": {"weights": {"AVAX-USD": 0.7802, "VNQ": 0.2198}, "sigma_1": 0.055469, "sigma_2": 0.012816, "covariance": -9.1e-05, "correlation": -0.1281, "has_text": true, "text_chars": 20, "mu_floor": 2.0541, "constraint_binding": true}} +{"id": "T4_all_20240726_0469", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SGOV"], "decision_date": "2024-07-26", "context_summary": "IWM \u03c3=0.0118, SGOV \u03c3=0.0001, \u03c1=-0.193. Min-variance weights: IWM=0.003, SGOV=0.997.", "question": "Assets: IWM, SGOV\nIWM: annualized_mean_return=0.4284, daily_std=0.0118\nSGOV: annualized_mean_return=0.0756, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0757\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_SGOV=X.XXXX", "answer": "w_IWM=0.0002, w_SGOV=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000138 + 0.000000 - -0.000001)\n Unconstrained: w_IWM=0.0026\n After long-only clamp: w_IWM=0.0026, w_SGOV=0.9974.", "metadata": {"weights": {"IWM": 0.0002, "SGOV": 0.9998}, "sigma_1": 0.011757, "sigma_2": 0.000149, "covariance": -0.0, "correlation": -0.1932, "has_text": true, "text_chars": 9045, "mu_floor": 0.0757, "constraint_binding": false}} +{"id": "T4_all_20230522_0472", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNDX"], "decision_date": "2023-05-22", "context_summary": "XLF \u03c3=0.0141, BNDX \u03c3=0.0036, \u03c1=-0.129. Min-variance weights: XLF=0.088, BNDX=0.912.", "question": "Assets: XLF, BNDX\nXLF: annualized_mean_return=-0.3276, daily_std=0.0141\nBNDX: annualized_mean_return=0.0756, daily_std=0.0036\nMinimum required portfolio return (annualized): 0.0584\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_BNDX=X.XXXX", "answer": "w_XLF=0.0427, w_BNDX=0.9573", "answer_numeric": 0.0427, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000013 - -0.000007) / (0.000198 + 0.000013 - -0.000013)\n Unconstrained: w_XLF=0.0876\n After long-only clamp: w_XLF=0.0876, w_BNDX=0.9124.", "metadata": {"weights": {"XLF": 0.0427, "BNDX": 0.9573}, "sigma_1": 0.014064, "sigma_2": 0.003614, "covariance": -7e-06, "correlation": -0.1289, "has_text": true, "text_chars": 3020, "mu_floor": 0.0584, "constraint_binding": true}} +{"id": "T4_all_20240624_0475", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD", "SOYB"], "decision_date": "2024-06-24", "context_summary": "XRP-USD \u03c3=0.0191, SOYB \u03c3=0.0080, \u03c1=0.063. Min-variance weights: XRP-USD=0.133, SOYB=0.867.", "question": "Assets: XRP-USD, SOYB\nXRP-USD: annualized_mean_return=-0.3528, daily_std=0.0191\nSOYB: annualized_mean_return=-0.1512, daily_std=0.0080\nMinimum required portfolio return (annualized): -0.2224\nMarket regime: bull\n\nCompute portfolio weights (w_XRP-USD, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_SOYB=X.XXXX", "answer": "w_XRP-USD=0.1321, w_SOYB=0.8679", "answer_numeric": 0.1321, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000064 - 0.000010) / (0.000366 + 0.000064 - 0.000019)\n Unconstrained: w_XRP-USD=0.1326\n After long-only clamp: w_XRP-USD=0.1326, w_SOYB=0.8674.", "metadata": {"weights": {"XRP-USD": 0.1321, "SOYB": 0.8679}, "sigma_1": 0.019137, "sigma_2": 0.008013, "covariance": 1e-05, "correlation": 0.0634, "has_text": true, "text_chars": 20, "mu_floor": -0.2224, "constraint_binding": false}} +{"id": "T4_all_20231220_0478", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "EWJ"], "decision_date": "2023-12-20", "context_summary": "AVAX-USD \u03c3=0.0596, EWJ \u03c3=0.0098, \u03c1=0.061. Min-variance weights: AVAX-USD=0.017, EWJ=0.983.", "question": "Assets: AVAX-USD, EWJ\nAVAX-USD: annualized_mean_return=6.6528, daily_std=0.0596\nEWJ: annualized_mean_return=0.1008, daily_std=0.0098\nMinimum required portfolio return (annualized): 2.7864\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_EWJ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_EWJ=X.XXXX", "answer": "w_AVAX-USD=0.4099, w_EWJ=0.5901", "answer_numeric": 0.4099, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000095 - 0.000036) / (0.003556 + 0.000095 - 0.000071)\n Unconstrained: w_AVAX-USD=0.0167\n After long-only clamp: w_AVAX-USD=0.0167, w_EWJ=0.9833.", "metadata": {"weights": {"AVAX-USD": 0.4099, "EWJ": 0.5901}, "sigma_1": 0.059634, "sigma_2": 0.009769, "covariance": 3.6e-05, "correlation": 0.0611, "has_text": true, "text_chars": 20, "mu_floor": 2.7864, "constraint_binding": true}} +{"id": "T4_all_20241226_0480", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ICSH"], "decision_date": "2024-12-26", "context_summary": "QUAL \u03c3=0.0074, ICSH \u03c3=0.0003, \u03c1=0.187. Min-variance weights: QUAL=0.000, ICSH=1.000.", "question": "Assets: QUAL, ICSH\nQUAL: annualized_mean_return=0.0756, daily_std=0.0074\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0643\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_ICSH=X.XXXX", "answer": "w_QUAL=0.5516, w_ICSH=0.4484", "answer_numeric": 0.5516, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000054 + 0.000000 - 0.000001)\n Unconstrained: w_QUAL=-0.0063\n After long-only clamp: w_QUAL=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"QUAL": 0.5516, "ICSH": 0.4484}, "sigma_1": 0.007369, "sigma_2": 0.000319, "covariance": 0.0, "correlation": 0.1874, "has_text": true, "text_chars": 9045, "mu_floor": 0.0643, "constraint_binding": true}} +{"id": "T4_all_20231127_0482", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "XRP-USD"], "decision_date": "2023-11-27", "context_summary": "EEM \u03c3=0.0095, XRP-USD \u03c3=0.0282, \u03c1=0.075. Min-variance weights: EEM=0.917, XRP-USD=0.083.", "question": "Assets: EEM, XRP-USD\nEEM: annualized_mean_return=-0.0252, daily_std=0.0095\nXRP-USD: annualized_mean_return=0.9828, daily_std=0.0282\nMinimum required portfolio return (annualized): 0.7774\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_XRP-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_XRP-USD=X.XXXX", "answer": "w_EEM=0.2038, w_XRP-USD=0.7962", "answer_numeric": 0.2038, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000795 - 0.000020) / (0.000090 + 0.000795 - 0.000040)\n Unconstrained: w_EEM=0.9172\n After long-only clamp: w_EEM=0.9172, w_XRP-USD=0.0828.", "metadata": {"weights": {"EEM": 0.2038, "XRP-USD": 0.7962}, "sigma_1": 0.009487, "sigma_2": 0.028196, "covariance": 2e-05, "correlation": 0.075, "has_text": true, "text_chars": 3020, "mu_floor": 0.7774, "constraint_binding": true}} +{"id": "T4_all_20230203_0485", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "REZ"], "decision_date": "2023-02-03", "context_summary": "USMV \u03c3=0.0088, REZ \u03c3=0.0145, \u03c1=0.731. Min-variance weights: USMV=1.000, REZ=0.000.", "question": "Assets: USMV, REZ\nUSMV: annualized_mean_return=0.1764, daily_std=0.0088\nREZ: annualized_mean_return=0.4536, daily_std=0.0145\nMinimum required portfolio return (annualized): 0.1764\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_REZ=X.XXXX", "answer": "w_USMV=1.0000, w_REZ=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000209 - 0.000093) / (0.000078 + 0.000209 - 0.000187)\n Unconstrained: w_USMV=1.1534\n After long-only clamp: w_USMV=1.0000, w_REZ=0.0000.", "metadata": {"weights": {"USMV": 1.0, "REZ": 0.0}, "sigma_1": 0.008826, "sigma_2": 0.014455, "covariance": 9.3e-05, "correlation": 0.7311, "has_text": true, "text_chars": 3020, "mu_floor": 0.1764, "constraint_binding": false}} +{"id": "T4_all_20241206_0488", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "IEF"], "decision_date": "2024-12-06", "context_summary": "XLY \u03c3=0.0104, IEF \u03c3=0.0038, \u03c1=0.114. Min-variance weights: XLY=0.090, IEF=0.910.", "question": "Assets: XLY, IEF\nXLY: annualized_mean_return=0.8064, daily_std=0.0104\nIEF: annualized_mean_return=-0.1008, daily_std=0.0038\nMinimum required portfolio return (annualized): 0.2628\nMarket regime: bull\n\nCompute portfolio weights (w_XLY, w_IEF) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_IEF=X.XXXX", "answer": "w_XLY=0.4008, w_IEF=0.5992", "answer_numeric": 0.4008, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000015 - 0.000005) / (0.000108 + 0.000015 - 0.000009)\n Unconstrained: w_XLY=0.0896\n After long-only clamp: w_XLY=0.0896, w_IEF=0.9104.", "metadata": {"weights": {"XLY": 0.4008, "IEF": 0.5992}, "sigma_1": 0.010408, "sigma_2": 0.003843, "covariance": 5e-06, "correlation": 0.1139, "has_text": true, "text_chars": 9046, "mu_floor": 0.2628, "constraint_binding": true}} +{"id": "T4_all_20230629_0491", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ITB"], "decision_date": "2023-06-29", "context_summary": "IVV \u03c3=0.0073, ITB \u03c3=0.0130, \u03c1=0.551. Min-variance weights: IVV=0.990, ITB=0.010.", "question": "Assets: IVV, ITB\nIVV: annualized_mean_return=0.2772, daily_std=0.0073\nITB: annualized_mean_return=0.8064, daily_std=0.0130\nMinimum required portfolio return (annualized): 0.2816\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_ITB=X.XXXX", "answer": "w_IVV=0.9871, w_ITB=0.0129", "answer_numeric": 0.9871, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000168 - 0.000052) / (0.000054 + 0.000168 - 0.000105)\n Unconstrained: w_IVV=0.9899\n After long-only clamp: w_IVV=0.9899, w_ITB=0.0101.", "metadata": {"weights": {"IVV": 0.9871, "ITB": 0.0129}, "sigma_1": 0.007316, "sigma_2": 0.012977, "covariance": 5.2e-05, "correlation": 0.5513, "has_text": true, "text_chars": 3020, "mu_floor": 0.2816, "constraint_binding": false}} +{"id": "T4_all_20240919_0493", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "DBA"], "decision_date": "2024-09-19", "context_summary": "XLU \u03c3=0.0082, DBA \u03c3=0.0098, \u03c1=-0.049. Min-variance weights: XLU=0.586, DBA=0.414.", "question": "Assets: XLU, DBA\nXLU: annualized_mean_return=0.5040, daily_std=0.0082\nDBA: annualized_mean_return=0.3528, daily_std=0.0098\nMinimum required portfolio return (annualized): 0.4052\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_DBA=X.XXXX", "answer": "w_XLU=0.5862, w_DBA=0.4138", "answer_numeric": 0.5862, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000096 - -0.000004) / (0.000067 + 0.000096 - -0.000008)\n Unconstrained: w_XLU=0.5863\n After long-only clamp: w_XLU=0.5863, w_DBA=0.4137.", "metadata": {"weights": {"XLU": 0.5862, "DBA": 0.4138}, "sigma_1": 0.008169, "sigma_2": 0.009809, "covariance": -4e-06, "correlation": -0.0494, "has_text": true, "text_chars": 9045, "mu_floor": 0.4052, "constraint_binding": false}} +{"id": "T4_all_20240715_0496", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD", "VNQ"], "decision_date": "2024-07-15", "context_summary": "ADA-USD \u03c3=0.0326, VNQ \u03c3=0.0088, \u03c1=0.124. Min-variance weights: ADA-USD=0.038, VNQ=0.962.", "question": "Assets: ADA-USD, VNQ\nADA-USD: annualized_mean_return=-0.0504, daily_std=0.0326\nVNQ: annualized_mean_return=0.4788, daily_std=0.0088\nMinimum required portfolio return (annualized): 0.4698\nMarket regime: bull\n\nCompute portfolio weights (w_ADA-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_ADA-USD=0.0170, w_VNQ=0.9830", "answer_numeric": 0.017, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000077 - 0.000035) / (0.001062 + 0.000077 - 0.000071)\n Unconstrained: w_ADA-USD=0.0385\n After long-only clamp: w_ADA-USD=0.0385, w_VNQ=0.9615.", "metadata": {"weights": {"ADA-USD": 0.017, "VNQ": 0.983}, "sigma_1": 0.032594, "sigma_2": 0.008751, "covariance": 3.5e-05, "correlation": 0.1244, "has_text": true, "text_chars": 20, "mu_floor": 0.4698, "constraint_binding": true}} +{"id": "T4_all_20240514_0499", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD", "BIL"], "decision_date": "2024-05-14", "context_summary": "AVAX-USD \u03c3=0.0524, BIL \u03c3=0.0002, \u03c1=0.062. Min-variance weights: AVAX-USD=0.000, BIL=1.000.", "question": "Assets: AVAX-USD, BIL\nAVAX-USD: annualized_mean_return=-1.7892, daily_std=0.0524\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.2786\nMarket regime: bull\n\nCompute portfolio weights (w_AVAX-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_AVAX-USD=0.0000, w_BIL=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.002747 + 0.000000 - 0.000001)\n Unconstrained: w_AVAX-USD=-0.0002\n After long-only clamp: w_AVAX-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"AVAX-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.05241, "sigma_2": 0.000154, "covariance": 1e-06, "correlation": 0.0624, "has_text": true, "text_chars": 20, "mu_floor": -0.2786, "constraint_binding": false}} +{"id": "T4_all_20230217_0502", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "BIL"], "decision_date": "2023-02-17", "context_summary": "MATIC-USD \u03c3=0.0373, BIL \u03c3=0.0002, \u03c1=0.052. Min-variance weights: MATIC-USD=0.000, BIL=1.000.", "question": "Assets: MATIC-USD, BIL\nMATIC-USD: annualized_mean_return=2.3688, daily_std=0.0373\nBIL: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.7988\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_MATIC-USD=0.3301, w_BIL=0.6699", "answer_numeric": 0.3301, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.001388 + 0.000000 - 0.000001)\n Unconstrained: w_MATIC-USD=-0.0002\n After long-only clamp: w_MATIC-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.3301, "BIL": 0.6699}, "sigma_1": 0.037261, "sigma_2": 0.000191, "covariance": 0.0, "correlation": 0.0523, "has_text": true, "text_chars": 20, "mu_floor": 0.7988, "constraint_binding": true}} +{"id": "T4_all_20230510_0505", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "INDS"], "decision_date": "2023-05-10", "context_summary": "VEA \u03c3=0.0091, INDS \u03c3=0.0119, \u03c1=0.571. Min-variance weights: VEA=0.794, INDS=0.206.", "question": "Assets: VEA, INDS\nVEA: annualized_mean_return=0.1512, daily_std=0.0091\nINDS: annualized_mean_return=-0.0000, daily_std=0.0119\nMinimum required portfolio return (annualized): 0.0576\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_INDS=X.XXXX", "answer": "w_VEA=0.7953, w_INDS=0.2047", "answer_numeric": 0.7953, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000142 - 0.000062) / (0.000083 + 0.000142 - 0.000124)\n Unconstrained: w_VEA=0.7941\n After long-only clamp: w_VEA=0.7941, w_INDS=0.2059.", "metadata": {"weights": {"VEA": 0.7953, "INDS": 0.2047}, "sigma_1": 0.009088, "sigma_2": 0.011917, "covariance": 6.2e-05, "correlation": 0.5706, "has_text": true, "text_chars": 3020, "mu_floor": 0.0576, "constraint_binding": false}} +{"id": "T4_all_20241119_0507", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "ICSH"], "decision_date": "2024-11-19", "context_summary": "ADA-USD \u03c3=0.0510, ICSH \u03c3=0.0003, \u03c1=0.246. Min-variance weights: ADA-USD=0.000, ICSH=1.000.", "question": "Assets: ADA-USD, ICSH\nADA-USD: annualized_mean_return=3.4272, daily_std=0.0510\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_ADA-USD=0.0000, w_ICSH=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000003) / (0.002605 + 0.000000 - 0.000007)\n Unconstrained: w_ADA-USD=-0.0013\n After long-only clamp: w_ADA-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"ADA-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.051038, "sigma_2": 0.000267, "covariance": 3e-06, "correlation": 0.2463, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20230926_0510", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ICSH"], "decision_date": "2023-09-26", "context_summary": "BNB-USD \u03c3=0.0147, ICSH \u03c3=0.0003, \u03c1=0.037. Min-variance weights: BNB-USD=0.000, ICSH=1.000.", "question": "Assets: BNB-USD, ICSH\nBNB-USD: annualized_mean_return=-0.5292, daily_std=0.0147\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0503\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_BNB-USD=0.0002, w_ICSH=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000217 + 0.000000 - 0.000000)\n Unconstrained: w_BNB-USD=-0.0003\n After long-only clamp: w_BNB-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"BNB-USD": 0.0002, "ICSH": 0.9998}, "sigma_1": 0.014744, "sigma_2": 0.000271, "covariance": 0.0, "correlation": 0.0369, "has_text": true, "text_chars": 20, "mu_floor": 0.0503, "constraint_binding": true}} +{"id": "T4_all_20230208_0511", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD"], "decision_date": "2023-02-08", "context_summary": "QUAL \u03c3=0.0123, BTC-USD \u03c3=0.0205, \u03c1=-0.006. Min-variance weights: QUAL=0.735, BTC-USD=0.265.", "question": "Assets: QUAL, BTC-USD\nQUAL: annualized_mean_return=0.4032, daily_std=0.0123\nBTC-USD: annualized_mean_return=1.3356, daily_std=0.0205\nMinimum required portfolio return (annualized): 0.6170\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_BTC-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_BTC-USD=X.XXXX", "answer": "w_QUAL=0.7356, w_BTC-USD=0.2644", "answer_numeric": 0.7356, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000420 - -0.000001) / (0.000150 + 0.000420 - -0.000003)\n Unconstrained: w_QUAL=0.7352\n After long-only clamp: w_QUAL=0.7352, w_BTC-USD=0.2648.", "metadata": {"weights": {"QUAL": 0.7356, "BTC-USD": 0.2644}, "sigma_1": 0.012266, "sigma_2": 0.020501, "covariance": -1e-06, "correlation": -0.0059, "has_text": true, "text_chars": 3020, "mu_floor": 0.617, "constraint_binding": false}} +{"id": "T4_all_20240731_0513", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "ITB"], "decision_date": "2024-07-31", "context_summary": "XRP-USD \u03c3=0.0334, ITB \u03c3=0.0176, \u03c1=0.069. Min-variance weights: XRP-USD=0.201, ITB=0.799.", "question": "Assets: XRP-USD, ITB\nXRP-USD: annualized_mean_return=0.9576, daily_std=0.0334\nITB: annualized_mean_return=0.5040, daily_std=0.0176\nMinimum required portfolio return (annualized): 0.5656\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_ITB=X.XXXX", "answer": "w_XRP-USD=0.2004, w_ITB=0.7996", "answer_numeric": 0.2004, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000311 - 0.000041) / (0.001119 + 0.000311 - 0.000081)\n Unconstrained: w_XRP-USD=0.2005\n After long-only clamp: w_XRP-USD=0.2005, w_ITB=0.7995.", "metadata": {"weights": {"XRP-USD": 0.2004, "ITB": 0.7996}, "sigma_1": 0.033446, "sigma_2": 0.017636, "covariance": 4.1e-05, "correlation": 0.0691, "has_text": true, "text_chars": 20, "mu_floor": 0.5656, "constraint_binding": false}} +{"id": "T4_all_20240612_0516", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "IAU"], "decision_date": "2024-06-12", "context_summary": "MATIC-USD \u03c3=0.0388, IAU \u03c3=0.0103, \u03c1=-0.293. Min-variance weights: MATIC-USD=0.121, IAU=0.879.", "question": "Assets: MATIC-USD, IAU\nMATIC-USD: annualized_mean_return=-0.7056, daily_std=0.0388\nIAU: annualized_mean_return=0.3528, daily_std=0.0103\nMinimum required portfolio return (annualized): 0.3180\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_IAU) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_IAU=X.XXXX", "answer": "w_MATIC-USD=0.0329, w_IAU=0.9671", "answer_numeric": 0.0329, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000106 - -0.000117) / (0.001502 + 0.000106 - -0.000234)\n Unconstrained: w_MATIC-USD=0.1209\n After long-only clamp: w_MATIC-USD=0.1209, w_IAU=0.8791.", "metadata": {"weights": {"MATIC-USD": 0.0329, "IAU": 0.9671}, "sigma_1": 0.038758, "sigma_2": 0.010294, "covariance": -0.000117, "correlation": -0.2927, "has_text": true, "text_chars": 20, "mu_floor": 0.318, "constraint_binding": true}} +{"id": "T4_all_20230710_0518", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SHV"], "decision_date": "2023-07-10", "context_summary": "^VIX \u03c3=0.0547, SHV \u03c3=0.0002, \u03c1=-0.145. Min-variance weights: ^VIX=0.001, SHV=1.000.", "question": "Assets: ^VIX, SHV\n^VIX: annualized_mean_return=-1.0584, daily_std=0.0547\nSHV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0503\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_SHV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_^VIX=X.XXXX, w_SHV=X.XXXX", "answer": "w_^VIX=0.0001, w_SHV=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.002995 + 0.000000 - -0.000003)\n Unconstrained: w_^VIX=0.0005\n After long-only clamp: w_^VIX=0.0005, w_SHV=0.9995.", "metadata": {"weights": {"^VIX": 0.0001, "SHV": 0.9999}, "sigma_1": 0.054728, "sigma_2": 0.000176, "covariance": -1e-06, "correlation": -0.1446, "has_text": true, "text_chars": 3020, "mu_floor": 0.0503, "constraint_binding": true}} +{"id": "T4_all_20231204_0520", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "TIP"], "decision_date": "2023-12-04", "context_summary": "XRP-USD \u03c3=0.0272, TIP \u03c3=0.0016, \u03c1=-0.014. Min-variance weights: XRP-USD=0.004, TIP=0.996.", "question": "Assets: XRP-USD, TIP\nXRP-USD: annualized_mean_return=0.7560, daily_std=0.0272\nTIP: annualized_mean_return=0.0504, daily_std=0.0016\nMinimum required portfolio return (annualized): 0.2418\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_TIP=X.XXXX", "answer": "w_XRP-USD=0.2713, w_TIP=0.7287", "answer_numeric": 0.2713, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000003 - -0.000001) / (0.000742 + 0.000003 - -0.000001)\n Unconstrained: w_XRP-USD=0.0042\n After long-only clamp: w_XRP-USD=0.0042, w_TIP=0.9958.", "metadata": {"weights": {"XRP-USD": 0.2713, "TIP": 0.7287}, "sigma_1": 0.027243, "sigma_2": 0.001586, "covariance": -1e-06, "correlation": -0.0139, "has_text": true, "text_chars": 20, "mu_floor": 0.2418, "constraint_binding": true}} +{"id": "T4_all_20231218_0523", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BIL"], "decision_date": "2023-12-18", "context_summary": "MTUM \u03c3=0.0085, BIL \u03c3=0.0001, \u03c1=0.066. Min-variance weights: MTUM=0.000, BIL=1.000.", "question": "Assets: MTUM, BIL\nMTUM: annualized_mean_return=0.4284, daily_std=0.0085\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_BIL=X.XXXX", "answer": "w_MTUM=0.0002, w_BIL=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000072 + 0.000000 - 0.000000)\n Unconstrained: w_MTUM=-0.0008\n After long-only clamp: w_MTUM=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"MTUM": 0.0002, "BIL": 0.9998}, "sigma_1": 0.008468, "sigma_2": 0.000131, "covariance": 0.0, "correlation": 0.0663, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240404_0525", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SCHH"], "decision_date": "2024-04-04", "context_summary": "QUAL \u03c3=0.0077, SCHH \u03c3=0.0103, \u03c1=0.430. Min-variance weights: QUAL=0.746, SCHH=0.254.", "question": "Assets: QUAL, SCHH\nQUAL: annualized_mean_return=0.5040, daily_std=0.0077\nSCHH: annualized_mean_return=-0.1008, daily_std=0.0103\nMinimum required portfolio return (annualized): 0.2539\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_SCHH=X.XXXX", "answer": "w_QUAL=0.7459, w_SCHH=0.2541", "answer_numeric": 0.7459, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000107 - 0.000034) / (0.000059 + 0.000107 - 0.000068)\n Unconstrained: w_QUAL=0.7459\n After long-only clamp: w_QUAL=0.7459, w_SCHH=0.2541.", "metadata": {"weights": {"QUAL": 0.7459, "SCHH": 0.2541}, "sigma_1": 0.007663, "sigma_2": 0.010323, "covariance": 3.4e-05, "correlation": 0.4299, "has_text": true, "text_chars": 9045, "mu_floor": 0.2539, "constraint_binding": false}} +{"id": "T4_all_20241002_0528", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "INDS"], "decision_date": "2024-10-02", "context_summary": "IVV \u03c3=0.0102, INDS \u03c3=0.0105, \u03c1=0.519. Min-variance weights: IVV=0.536, INDS=0.464.", "question": "Assets: IVV, INDS\nIVV: annualized_mean_return=0.1008, daily_std=0.0102\nINDS: annualized_mean_return=0.5292, daily_std=0.0105\nMinimum required portfolio return (annualized): 0.3923\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_INDS=X.XXXX", "answer": "w_IVV=0.3196, w_INDS=0.6804", "answer_numeric": 0.3196, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000111 - 0.000056) / (0.000103 + 0.000111 - 0.000111)\n Unconstrained: w_IVV=0.5360\n After long-only clamp: w_IVV=0.5360, w_INDS=0.4640.", "metadata": {"weights": {"IVV": 0.3196, "INDS": 0.6804}, "sigma_1": 0.010169, "sigma_2": 0.010528, "covariance": 5.6e-05, "correlation": 0.5191, "has_text": true, "text_chars": 9045, "mu_floor": 0.3923, "constraint_binding": true}} +{"id": "T4_all_20230913_0531", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ICSH"], "decision_date": "2023-09-13", "context_summary": "FXI \u03c3=0.0181, ICSH \u03c3=0.0003, \u03c1=0.094. Min-variance weights: FXI=0.000, ICSH=1.000.", "question": "Assets: FXI, ICSH\nFXI: annualized_mean_return=-0.3024, daily_std=0.0181\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0063\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_ICSH=X.XXXX", "answer": "w_FXI=0.0003, w_ICSH=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000329 + 0.000000 - 0.000001)\n Unconstrained: w_FXI=-0.0012\n After long-only clamp: w_FXI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"FXI": 0.0003, "ICSH": 0.9997}, "sigma_1": 0.018131, "sigma_2": 0.000287, "covariance": 0.0, "correlation": 0.0936, "has_text": true, "text_chars": 3020, "mu_floor": 0.0063, "constraint_binding": false}} +{"id": "T4_all_20240801_0533", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "VCIT"], "decision_date": "2024-08-01", "context_summary": "LINK-USD \u03c3=0.0364, VCIT \u03c3=0.0033, \u03c1=0.167. Min-variance weights: LINK-USD=0.000, VCIT=1.000.", "question": "Assets: LINK-USD, VCIT\nLINK-USD: annualized_mean_return=-1.3356, daily_std=0.0364\nVCIT: annualized_mean_return=0.1764, daily_std=0.0033\nMinimum required portfolio return (annualized): -0.5876\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_VCIT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_VCIT=X.XXXX", "answer": "w_LINK-USD=0.0000, w_VCIT=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000011 - 0.000020) / (0.001325 + 0.000011 - 0.000040)\n Unconstrained: w_LINK-USD=-0.0071\n After long-only clamp: w_LINK-USD=0.0000, w_VCIT=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "VCIT": 1.0}, "sigma_1": 0.036402, "sigma_2": 0.0033, "covariance": 2e-05, "correlation": 0.1673, "has_text": true, "text_chars": 20, "mu_floor": -0.5876, "constraint_binding": false}} +{"id": "T4_all_20230630_0535", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "GLD"], "decision_date": "2023-06-30", "context_summary": "XRP-USD \u03c3=0.0242, GLD \u03c3=0.0075, \u03c1=0.082. Min-variance weights: XRP-USD=0.069, GLD=0.931.", "question": "Assets: XRP-USD, GLD\nXRP-USD: annualized_mean_return=0.1008, daily_std=0.0242\nGLD: annualized_mean_return=-0.2268, daily_std=0.0075\nMinimum required portfolio return (annualized): -0.2167\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_GLD=X.XXXX", "answer": "w_XRP-USD=0.0686, w_GLD=0.9314", "answer_numeric": 0.0686, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000057 - 0.000015) / (0.000584 + 0.000057 - 0.000030)\n Unconstrained: w_XRP-USD=0.0687\n After long-only clamp: w_XRP-USD=0.0687, w_GLD=0.9313.", "metadata": {"weights": {"XRP-USD": 0.0686, "GLD": 0.9314}, "sigma_1": 0.024165, "sigma_2": 0.007545, "covariance": 1.5e-05, "correlation": 0.0821, "has_text": true, "text_chars": 20, "mu_floor": -0.2167, "constraint_binding": false}} +{"id": "T4_all_20230731_0538", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "MORT"], "decision_date": "2023-07-31", "context_summary": "SOL-USD \u03c3=0.0472, MORT \u03c3=0.0150, \u03c1=-0.090. Min-variance weights: SOL-USD=0.112, MORT=0.888.", "question": "Assets: SOL-USD, MORT\nSOL-USD: annualized_mean_return=0.9072, daily_std=0.0472\nMORT: annualized_mean_return=0.8568, daily_std=0.0150\nMinimum required portfolio return (annualized): 0.8963\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_MORT=X.XXXX", "answer": "w_SOL-USD=0.7837, w_MORT=0.2163", "answer_numeric": 0.7837, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000226 - -0.000064) / (0.002227 + 0.000226 - -0.000127)\n Unconstrained: w_SOL-USD=0.1122\n After long-only clamp: w_SOL-USD=0.1122, w_MORT=0.8878.", "metadata": {"weights": {"SOL-USD": 0.7837, "MORT": 0.2163}, "sigma_1": 0.047186, "sigma_2": 0.015032, "covariance": -6.4e-05, "correlation": -0.0896, "has_text": true, "text_chars": 20, "mu_floor": 0.8963, "constraint_binding": true}} +{"id": "T4_all_20230818_0541", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "CSHI"], "decision_date": "2023-08-18", "context_summary": "XLU \u03c3=0.0092, CSHI \u03c3=0.0005, \u03c1=-0.129. Min-variance weights: XLU=0.011, CSHI=0.989.", "question": "Assets: XLU, CSHI\nXLU: annualized_mean_return=-0.1512, daily_std=0.0092\nCSHI: annualized_mean_return=0.0756, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0272\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLU=0.0147, w_CSHI=0.9853", "answer_numeric": 0.0147, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000085 + 0.000000 - -0.000001)\n Unconstrained: w_XLU=0.0106\n After long-only clamp: w_XLU=0.0106, w_CSHI=0.9894.", "metadata": {"weights": {"XLU": 0.0147, "CSHI": 0.9853}, "sigma_1": 0.009236, "sigma_2": 0.000534, "covariance": -1e-06, "correlation": -0.1287, "has_text": true, "text_chars": 3020, "mu_floor": 0.0272, "constraint_binding": false}} +{"id": "T4_all_20240925_0544", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ICSH"], "decision_date": "2024-09-25", "context_summary": "XLV \u03c3=0.0077, ICSH \u03c3=0.0003, \u03c1=0.300. Min-variance weights: XLV=0.000, ICSH=1.000.", "question": "Assets: XLV, ICSH\nXLV: annualized_mean_return=0.2520, daily_std=0.0077\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.1994\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLV=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLV=0.7018, w_ICSH=0.2982", "answer_numeric": 0.7018, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000060 + 0.000000 - 0.000001)\n Unconstrained: w_XLV=-0.0099\n After long-only clamp: w_XLV=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLV": 0.7018, "ICSH": 0.2982}, "sigma_1": 0.007725, "sigma_2": 0.000286, "covariance": 1e-06, "correlation": 0.2995, "has_text": true, "text_chars": 9045, "mu_floor": 0.1994, "constraint_binding": true}} +{"id": "T4_all_20241016_0547", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD"], "decision_date": "2024-10-16", "context_summary": "XLI \u03c3=0.0097, LINK-USD \u03c3=0.0333, \u03c1=0.022. Min-variance weights: XLI=0.927, LINK-USD=0.073.", "question": "Assets: XLI, LINK-USD\nXLI: annualized_mean_return=0.4032, daily_std=0.0097\nLINK-USD: annualized_mean_return=0.6552, daily_std=0.0333\nMinimum required portfolio return (annualized): 0.4203\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_LINK-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_LINK-USD=X.XXXX", "answer": "w_XLI=0.9270, w_LINK-USD=0.0730", "answer_numeric": 0.927, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001112 - 0.000007) / (0.000094 + 0.001112 - 0.000014)\n Unconstrained: w_XLI=0.9272\n After long-only clamp: w_XLI=0.9272, w_LINK-USD=0.0728.", "metadata": {"weights": {"XLI": 0.927, "LINK-USD": 0.073}, "sigma_1": 0.009693, "sigma_2": 0.033341, "covariance": 7e-06, "correlation": 0.0224, "has_text": true, "text_chars": 9045, "mu_floor": 0.4203, "constraint_binding": false}} +{"id": "T4_all_20240229_0549", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "ICSH"], "decision_date": "2024-02-29", "context_summary": "MATIC-USD \u03c3=0.0401, ICSH \u03c3=0.0003, \u03c1=-0.025. Min-variance weights: MATIC-USD=0.000, ICSH=1.000.", "question": "Assets: MATIC-USD, ICSH\nMATIC-USD: annualized_mean_return=0.4536, daily_std=0.0401\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MATIC-USD=0.0001, w_ICSH=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.001606 + 0.000000 - -0.000001)\n Unconstrained: w_MATIC-USD=0.0003\n After long-only clamp: w_MATIC-USD=0.0003, w_ICSH=0.9997.", "metadata": {"weights": {"MATIC-USD": 0.0001, "ICSH": 0.9999}, "sigma_1": 0.040071, "sigma_2": 0.000313, "covariance": -0.0, "correlation": -0.0251, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240417_0552", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "PALL"], "decision_date": "2024-04-17", "context_summary": "EWJ \u03c3=0.0084, PALL \u03c3=0.0235, \u03c1=0.074. Min-variance weights: EWJ=0.906, PALL=0.094.", "question": "Assets: EWJ, PALL\nEWJ: annualized_mean_return=0.1260, daily_std=0.0084\nPALL: annualized_mean_return=0.1512, daily_std=0.0235\nMinimum required portfolio return (annualized): 0.1383\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_PALL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EWJ=X.XXXX, w_PALL=X.XXXX", "answer": "w_EWJ=0.5119, w_PALL=0.4881", "answer_numeric": 0.5119, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000550 - 0.000015) / (0.000070 + 0.000550 - 0.000029)\n Unconstrained: w_EWJ=0.9062\n After long-only clamp: w_EWJ=0.9062, w_PALL=0.0938.", "metadata": {"weights": {"EWJ": 0.5119, "PALL": 0.4881}, "sigma_1": 0.008369, "sigma_2": 0.023454, "covariance": 1.5e-05, "correlation": 0.0743, "has_text": true, "text_chars": 9045, "mu_floor": 0.1383, "constraint_binding": true}} +{"id": "T4_all_20241017_0555", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "DBB"], "decision_date": "2024-10-17", "context_summary": "ETH-USD \u03c3=0.0279, DBB \u03c3=0.0127, \u03c1=-0.046. Min-variance weights: ETH-USD=0.182, DBB=0.818.", "question": "Assets: ETH-USD, DBB\nETH-USD: annualized_mean_return=0.1008, daily_std=0.0279\nDBB: annualized_mean_return=0.4032, daily_std=0.0127\nMinimum required portfolio return (annualized): 0.2336\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_DBB=X.XXXX", "answer": "w_ETH-USD=0.1819, w_DBB=0.8181", "answer_numeric": 0.1819, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000161 - -0.000016) / (0.000780 + 0.000161 - -0.000033)\n Unconstrained: w_ETH-USD=0.1822\n After long-only clamp: w_ETH-USD=0.1822, w_DBB=0.8178.", "metadata": {"weights": {"ETH-USD": 0.1819, "DBB": 0.8181}, "sigma_1": 0.027929, "sigma_2": 0.012689, "covariance": -1.6e-05, "correlation": -0.0465, "has_text": true, "text_chars": 20, "mu_floor": 0.2336, "constraint_binding": false}} +{"id": "T4_all_20241204_0557", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ", "WEAT"], "decision_date": "2024-12-04", "context_summary": "QQQ \u03c3=0.0096, WEAT \u03c3=0.0118, \u03c1=0.094. Min-variance weights: QQQ=0.612, WEAT=0.389.", "question": "Assets: QQQ, WEAT\nQQQ: annualized_mean_return=0.5544, daily_std=0.0096\nWEAT: annualized_mean_return=-0.3780, daily_std=0.0118\nMinimum required portfolio return (annualized): 0.1026\nMarket regime: bull\n\nCompute portfolio weights (w_QQQ, w_WEAT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QQQ=X.XXXX, w_WEAT=X.XXXX", "answer": "w_QQQ=0.6117, w_WEAT=0.3883", "answer_numeric": 0.6117, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000140 - 0.000011) / (0.000093 + 0.000140 - 0.000022)\n Unconstrained: w_QQQ=0.6115\n After long-only clamp: w_QQQ=0.6115, w_WEAT=0.3885.", "metadata": {"weights": {"QQQ": 0.6117, "WEAT": 0.3883}, "sigma_1": 0.009647, "sigma_2": 0.011844, "covariance": 1.1e-05, "correlation": 0.0945, "has_text": true, "text_chars": 9046, "mu_floor": 0.1026, "constraint_binding": false}} +{"id": "T4_all_20230216_0560", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "IGOV"], "decision_date": "2023-02-16", "context_summary": "BNB-USD \u03c3=0.0250, IGOV \u03c3=0.0072, \u03c1=-0.312. Min-variance weights: BNB-USD=0.137, IGOV=0.863.", "question": "Assets: BNB-USD, IGOV\nBNB-USD: annualized_mean_return=1.2096, daily_std=0.0250\nIGOV: annualized_mean_return=0.0756, daily_std=0.0072\nMinimum required portfolio return (annualized): 1.0041\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_IGOV=X.XXXX", "answer": "w_BNB-USD=0.8188, w_IGOV=0.1812", "answer_numeric": 0.8188, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000052 - -0.000056) / (0.000627 + 0.000052 - -0.000113)\n Unconstrained: w_BNB-USD=0.1366\n After long-only clamp: w_BNB-USD=0.1366, w_IGOV=0.8634.", "metadata": {"weights": {"BNB-USD": 0.8188, "IGOV": 0.1812}, "sigma_1": 0.025045, "sigma_2": 0.007199, "covariance": -5.6e-05, "correlation": -0.3122, "has_text": true, "text_chars": 20, "mu_floor": 1.0041, "constraint_binding": true}} +{"id": "T4_all_20240125_0562", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "JNK"], "decision_date": "2024-01-25", "context_summary": "EEM \u03c3=0.0096, JNK \u03c3=0.0042, \u03c1=0.015. Min-variance weights: EEM=0.159, JNK=0.841.", "question": "Assets: EEM, JNK\nEEM: annualized_mean_return=0.3276, daily_std=0.0096\nJNK: annualized_mean_return=0.3276, daily_std=0.0042\nMinimum required portfolio return (annualized): 0.3276\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_JNK) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_JNK=X.XXXX", "answer": "w_EEM=0.1569, w_JNK=0.8431", "answer_numeric": 0.1569, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000018 - 0.000001) / (0.000092 + 0.000018 - 0.000001)\n Unconstrained: w_EEM=0.1592\n After long-only clamp: w_EEM=0.1592, w_JNK=0.8408.", "metadata": {"weights": {"EEM": 0.1569, "JNK": 0.8431}, "sigma_1": 0.009579, "sigma_2": 0.004229, "covariance": 1e-06, "correlation": 0.0154, "has_text": true, "text_chars": 3020, "mu_floor": 0.3276, "constraint_binding": false}} +{"id": "T4_all_20240403_0564", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "DBC"], "decision_date": "2024-04-03", "context_summary": "BNB-USD \u03c3=0.0435, DBC \u03c3=0.0065, \u03c1=-0.049. Min-variance weights: BNB-USD=0.029, DBC=0.971.", "question": "Assets: BNB-USD, DBC\nBNB-USD: annualized_mean_return=2.7720, daily_std=0.0435\nDBC: annualized_mean_return=0.3024, daily_std=0.0065\nMinimum required portfolio return (annualized): 2.0654\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_DBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_DBC=X.XXXX", "answer": "w_BNB-USD=0.7139, w_DBC=0.2861", "answer_numeric": 0.7139, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000043 - -0.000014) / (0.001896 + 0.000043 - -0.000028)\n Unconstrained: w_BNB-USD=0.0289\n After long-only clamp: w_BNB-USD=0.0289, w_DBC=0.9711.", "metadata": {"weights": {"BNB-USD": 0.7139, "DBC": 0.2861}, "sigma_1": 0.043544, "sigma_2": 0.006539, "covariance": -1.4e-05, "correlation": -0.0495, "has_text": true, "text_chars": 20, "mu_floor": 2.0654, "constraint_binding": true}} +{"id": "T4_all_20240112_0566", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "MORT"], "decision_date": "2024-01-12", "context_summary": "DOT-USD \u03c3=0.0525, MORT \u03c3=0.0174, \u03c1=0.094. Min-variance weights: DOT-USD=0.075, MORT=0.925.", "question": "Assets: DOT-USD, MORT\nDOT-USD: annualized_mean_return=1.8396, daily_std=0.0525\nMORT: annualized_mean_return=0.5040, daily_std=0.0174\nMinimum required portfolio return (annualized): 1.5257\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_MORT=X.XXXX", "answer": "w_DOT-USD=0.7650, w_MORT=0.2350", "answer_numeric": 0.765, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000302 - 0.000086) / (0.002760 + 0.000302 - 0.000172)\n Unconstrained: w_DOT-USD=0.0746\n After long-only clamp: w_DOT-USD=0.0746, w_MORT=0.9254.", "metadata": {"weights": {"DOT-USD": 0.765, "MORT": 0.235}, "sigma_1": 0.052535, "sigma_2": 0.01737, "covariance": 8.6e-05, "correlation": 0.0945, "has_text": true, "text_chars": 20, "mu_floor": 1.5257, "constraint_binding": true}} +{"id": "T4_all_20240208_0569", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "SLV"], "decision_date": "2024-02-08", "context_summary": "BTC-USD \u03c3=0.0245, SLV \u03c3=0.0144, \u03c1=-0.096. Min-variance weights: BTC-USD=0.276, SLV=0.724.", "question": "Assets: BTC-USD, SLV\nBTC-USD: annualized_mean_return=0.1260, daily_std=0.0245\nSLV: annualized_mean_return=-0.1260, daily_std=0.0144\nMinimum required portfolio return (annualized): -0.0952\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_SLV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_SLV=X.XXXX", "answer": "w_BTC-USD=0.2760, w_SLV=0.7240", "answer_numeric": 0.276, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000207 - -0.000034) / (0.000598 + 0.000207 - -0.000068)\n Unconstrained: w_BTC-USD=0.2759\n After long-only clamp: w_BTC-USD=0.2759, w_SLV=0.7241.", "metadata": {"weights": {"BTC-USD": 0.276, "SLV": 0.724}, "sigma_1": 0.024461, "sigma_2": 0.014389, "covariance": -3.4e-05, "correlation": -0.096, "has_text": true, "text_chars": 20, "mu_floor": -0.0952, "constraint_binding": false}} +{"id": "T4_all_20240730_0572", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ETH-USD"], "decision_date": "2024-07-30", "context_summary": "XLE \u03c3=0.0100, ETH-USD \u03c3=0.0243, \u03c1=-0.105. Min-variance weights: XLE=0.829, ETH-USD=0.171.", "question": "Assets: XLE, ETH-USD\nXLE: annualized_mean_return=0.0000, daily_std=0.0100\nETH-USD: annualized_mean_return=-0.4284, daily_std=0.0243\nMinimum required portfolio return (annualized): -0.0363\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_ETH-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLE=X.XXXX, w_ETH-USD=X.XXXX", "answer": "w_XLE=0.9153, w_ETH-USD=0.0847", "answer_numeric": 0.9153, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000589 - -0.000026) / (0.000101 + 0.000589 - -0.000051)\n Unconstrained: w_XLE=0.8293\n After long-only clamp: w_XLE=0.8293, w_ETH-USD=0.1707.", "metadata": {"weights": {"XLE": 0.9153, "ETH-USD": 0.0847}, "sigma_1": 0.010046, "sigma_2": 0.02427, "covariance": -2.6e-05, "correlation": -0.1048, "has_text": true, "text_chars": 9044, "mu_floor": -0.0363, "constraint_binding": true}} +{"id": "T4_all_20240710_0574", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD", "TIP"], "decision_date": "2024-07-10", "context_summary": "XRP-USD \u03c3=0.0229, TIP \u03c3=0.0010, \u03c1=-0.183. Min-variance weights: XRP-USD=0.010, TIP=0.990.", "question": "Assets: XRP-USD, TIP\nXRP-USD: annualized_mean_return=-0.5292, daily_std=0.0229\nTIP: annualized_mean_return=0.1008, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.0969\nMarket regime: bull\n\nCompute portfolio weights (w_XRP-USD, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_TIP=X.XXXX", "answer": "w_XRP-USD=0.0062, w_TIP=0.9938", "answer_numeric": 0.0062, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000004) / (0.000524 + 0.000001 - -0.000009)\n Unconstrained: w_XRP-USD=0.0102\n After long-only clamp: w_XRP-USD=0.0102, w_TIP=0.9898.", "metadata": {"weights": {"XRP-USD": 0.0062, "TIP": 0.9938}, "sigma_1": 0.022896, "sigma_2": 0.001039, "covariance": -4e-06, "correlation": -0.1826, "has_text": true, "text_chars": 20, "mu_floor": 0.0969, "constraint_binding": true}} +{"id": "T4_all_20241022_0576", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "XHB"], "decision_date": "2024-10-22", "context_summary": "MATIC-USD \u03c3=0.0273, XHB \u03c3=0.0160, \u03c1=0.244. Min-variance weights: MATIC-USD=0.190, XHB=0.810.", "question": "Assets: MATIC-USD, XHB\nMATIC-USD: annualized_mean_return=-1.4112, daily_std=0.0273\nXHB: annualized_mean_return=0.2016, daily_std=0.0160\nMinimum required portfolio return (annualized): 0.0997\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_XHB=X.XXXX", "answer": "w_MATIC-USD=0.0632, w_XHB=0.9368", "answer_numeric": 0.0632, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000257 - 0.000107) / (0.000746 + 0.000257 - 0.000214)\n Unconstrained: w_MATIC-USD=0.1901\n After long-only clamp: w_MATIC-USD=0.1901, w_XHB=0.8099.", "metadata": {"weights": {"MATIC-USD": 0.0632, "XHB": 0.9368}, "sigma_1": 0.027307, "sigma_2": 0.016024, "covariance": 0.000107, "correlation": 0.244, "has_text": true, "text_chars": 20, "mu_floor": 0.0997, "constraint_binding": true}} +{"id": "T4_all_20240320_0579", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XHB"], "decision_date": "2024-03-20", "context_summary": "XLY \u03c3=0.0097, XHB \u03c3=0.0128, \u03c1=0.667. Min-variance weights: XLY=0.883, XHB=0.117.", "question": "Assets: XLY, XHB\nXLY: annualized_mean_return=0.0756, daily_std=0.0097\nXHB: annualized_mean_return=0.5544, daily_std=0.0128\nMinimum required portfolio return (annualized): 0.1125\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_XHB=X.XXXX", "answer": "w_XLY=0.8856, w_XHB=0.1144", "answer_numeric": 0.8856, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000164 - 0.000083) / (0.000094 + 0.000164 - 0.000165)\n Unconstrained: w_XLY=0.8829\n After long-only clamp: w_XLY=0.8829, w_XHB=0.1171.", "metadata": {"weights": {"XLY": 0.8856, "XHB": 0.1144}, "sigma_1": 0.00967, "sigma_2": 0.012821, "covariance": 8.3e-05, "correlation": 0.6667, "has_text": true, "text_chars": 9045, "mu_floor": 0.1125, "constraint_binding": false}} +{"id": "T4_all_20230328_0582", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "VNQ"], "decision_date": "2023-03-28", "context_summary": "XRP-USD \u03c3=0.0433, VNQ \u03c3=0.0146, \u03c1=-0.127. Min-variance weights: XRP-USD=0.131, VNQ=0.869.", "question": "Assets: XRP-USD, VNQ\nXRP-USD: annualized_mean_return=0.8820, daily_std=0.0433\nVNQ: annualized_mean_return=-0.0756, daily_std=0.0146\nMinimum required portfolio return (annualized): 0.3623\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_XRP-USD=0.4573, w_VNQ=0.5427", "answer_numeric": 0.4573, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000214 - -0.000081) / (0.001878 + 0.000214 - -0.000161)\n Unconstrained: w_XRP-USD=0.1309\n After long-only clamp: w_XRP-USD=0.1309, w_VNQ=0.8691.", "metadata": {"weights": {"XRP-USD": 0.4573, "VNQ": 0.5427}, "sigma_1": 0.043331, "sigma_2": 0.014639, "covariance": -8.1e-05, "correlation": -0.127, "has_text": true, "text_chars": 20, "mu_floor": 0.3623, "constraint_binding": true}} +{"id": "T4_all_20230606_0585", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "UNG"], "decision_date": "2023-06-06", "context_summary": "ACWI \u03c3=0.0082, UNG \u03c3=0.0368, \u03c1=0.165. Min-variance weights: ACWI=0.987, UNG=0.013.", "question": "Assets: ACWI, UNG\nACWI: annualized_mean_return=0.3024, daily_std=0.0082\nUNG: annualized_mean_return=-1.1592, daily_std=0.0368\nMinimum required portfolio return (annualized): -0.2424\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_UNG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ACWI=X.XXXX, w_UNG=X.XXXX", "answer": "w_ACWI=0.9868, w_UNG=0.0132", "answer_numeric": 0.9868, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001357 - 0.000050) / (0.000067 + 0.001357 - 0.000100)\n Unconstrained: w_ACWI=0.9867\n After long-only clamp: w_ACWI=0.9867, w_UNG=0.0133.", "metadata": {"weights": {"ACWI": 0.9868, "UNG": 0.0132}, "sigma_1": 0.008214, "sigma_2": 0.036844, "covariance": 5e-05, "correlation": 0.1646, "has_text": true, "text_chars": 3020, "mu_floor": -0.2424, "constraint_binding": false}} +{"id": "T4_all_20240312_0589", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "CSHI"], "decision_date": "2024-03-12", "context_summary": "MATIC-USD \u03c3=0.0376, CSHI \u03c3=0.0004, \u03c1=0.062. Min-variance weights: MATIC-USD=0.000, CSHI=1.000.", "question": "Assets: MATIC-USD, CSHI\nMATIC-USD: annualized_mean_return=1.4112, daily_std=0.0376\nCSHI: annualized_mean_return=0.0504, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_MATIC-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.001412 + 0.000000 - 0.000002)\n Unconstrained: w_MATIC-USD=-0.0005\n After long-only clamp: w_MATIC-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.03758, "sigma_2": 0.00036, "covariance": 1e-06, "correlation": 0.062, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20241007_0592", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "SHY"], "decision_date": "2024-10-07", "context_summary": "MATIC-USD \u03c3=0.0386, SHY \u03c3=0.0011, \u03c1=0.192. Min-variance weights: MATIC-USD=0.000, SHY=1.000.", "question": "Assets: MATIC-USD, SHY\nMATIC-USD: annualized_mean_return=0.0756, daily_std=0.0386\nSHY: annualized_mean_return=0.0756, daily_std=0.0011\nMinimum required portfolio return (annualized): 0.0756\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_MATIC-USD=0.0000, w_SHY=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000008) / (0.001486 + 0.000001 - 0.000016)\n Unconstrained: w_MATIC-USD=-0.0046\n After long-only clamp: w_MATIC-USD=0.0000, w_SHY=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0, "SHY": 1.0}, "sigma_1": 0.038551, "sigma_2": 0.001076, "covariance": 8e-06, "correlation": 0.1921, "has_text": true, "text_chars": 20, "mu_floor": 0.0756, "constraint_binding": false}} +{"id": "T4_all_20240109_0594", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "XLU"], "decision_date": "2024-01-09", "context_summary": "AVAX-USD \u03c3=0.0668, XLU \u03c3=0.0103, \u03c1=0.075. Min-variance weights: AVAX-USD=0.012, XLU=0.988.", "question": "Assets: AVAX-USD, XLU\nAVAX-USD: annualized_mean_return=4.8888, daily_std=0.0668\nXLU: annualized_mean_return=0.3024, daily_std=0.0103\nMinimum required portfolio return (annualized): 2.5818\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_XLU) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_XLU=X.XXXX", "answer": "w_AVAX-USD=0.4970, w_XLU=0.5030", "answer_numeric": 0.497, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000107 - 0.000052) / (0.004457 + 0.000107 - 0.000103)\n Unconstrained: w_AVAX-USD=0.0124\n After long-only clamp: w_AVAX-USD=0.0124, w_XLU=0.9876.", "metadata": {"weights": {"AVAX-USD": 0.497, "XLU": 0.503}, "sigma_1": 0.06676, "sigma_2": 0.01033, "covariance": 5.2e-05, "correlation": 0.0748, "has_text": true, "text_chars": 20, "mu_floor": 2.5818, "constraint_binding": true}} +{"id": "T4_all_20231011_0597", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "CSHI"], "decision_date": "2023-10-11", "context_summary": "XLF \u03c3=0.0074, CSHI \u03c3=0.0006, \u03c1=0.078. Min-variance weights: XLF=0.000, CSHI=1.000.", "question": "Assets: XLF, CSHI\nXLF: annualized_mean_return=-0.1512, daily_std=0.0074\nCSHI: annualized_mean_return=0.1008, daily_std=0.0006\nMinimum required portfolio return (annualized): 0.0187\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLF=0.0064, w_CSHI=0.9936", "answer_numeric": 0.0064, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000055 + 0.000000 - 0.000001)\n Unconstrained: w_XLF=0.0002\n After long-only clamp: w_XLF=0.0002, w_CSHI=0.9998.", "metadata": {"weights": {"XLF": 0.0064, "CSHI": 0.9936}, "sigma_1": 0.007425, "sigma_2": 0.000596, "covariance": 0.0, "correlation": 0.0784, "has_text": true, "text_chars": 3020, "mu_floor": 0.0187, "constraint_binding": false}} +{"id": "T4_all_20240628_0600", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "CPER"], "decision_date": "2024-06-28", "context_summary": "BTC-USD \u03c3=0.0242, CPER \u03c3=0.0153, \u03c1=-0.075. Min-variance weights: BTC-USD=0.299, CPER=0.701.", "question": "Assets: BTC-USD, CPER\nBTC-USD: annualized_mean_return=-0.0252, daily_std=0.0242\nCPER: annualized_mean_return=0.1764, daily_std=0.0153\nMinimum required portfolio return (annualized): 0.1576\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_CPER) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_CPER=X.XXXX", "answer": "w_BTC-USD=0.0933, w_CPER=0.9067", "answer_numeric": 0.0933, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000234 - -0.000028) / (0.000585 + 0.000234 - -0.000055)\n Unconstrained: w_BTC-USD=0.2994\n After long-only clamp: w_BTC-USD=0.2994, w_CPER=0.7006.", "metadata": {"weights": {"BTC-USD": 0.0933, "CPER": 0.9067}, "sigma_1": 0.024178, "sigma_2": 0.015294, "covariance": -2.8e-05, "correlation": -0.075, "has_text": true, "text_chars": 20, "mu_floor": 0.1576, "constraint_binding": true}} +{"id": "T4_all_20230316_0603", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "VNQ"], "decision_date": "2023-03-16", "context_summary": "ADA-USD \u03c3=0.0354, VNQ \u03c3=0.0139, \u03c1=0.168. Min-variance weights: ADA-USD=0.086, VNQ=0.913.", "question": "Assets: ADA-USD, VNQ\nADA-USD: annualized_mean_return=-0.1764, daily_std=0.0354\nVNQ: annualized_mean_return=-0.1260, daily_std=0.0139\nMinimum required portfolio return (annualized): -0.1431\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_ADA-USD=0.0865, w_VNQ=0.9135", "answer_numeric": 0.0865, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000194 - 0.000083) / (0.001254 + 0.000194 - 0.000166)\n Unconstrained: w_ADA-USD=0.0865\n After long-only clamp: w_ADA-USD=0.0865, w_VNQ=0.9135.", "metadata": {"weights": {"ADA-USD": 0.0865, "VNQ": 0.9135}, "sigma_1": 0.035407, "sigma_2": 0.013923, "covariance": 8.3e-05, "correlation": 0.1683, "has_text": true, "text_chars": 20, "mu_floor": -0.1431, "constraint_binding": false}} +{"id": "T4_all_20240523_0606", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "IGOV"], "decision_date": "2024-05-23", "context_summary": "EWJ \u03c3=0.0094, IGOV \u03c3=0.0050, \u03c1=0.494. Min-variance weights: EWJ=0.026, IGOV=0.974.", "question": "Assets: EWJ, IGOV\nEWJ: annualized_mean_return=-0.0756, daily_std=0.0094\nIGOV: annualized_mean_return=-0.0504, daily_std=0.0050\nMinimum required portfolio return (annualized): -0.0506\nMarket regime: bull\n\nCompute portfolio weights (w_EWJ, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EWJ=X.XXXX, w_IGOV=X.XXXX", "answer": "w_EWJ=0.0079, w_IGOV=0.9921", "answer_numeric": 0.0079, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000025 - 0.000023) / (0.000088 + 0.000025 - 0.000046)\n Unconstrained: w_EWJ=0.0260\n After long-only clamp: w_EWJ=0.0260, w_IGOV=0.9740.", "metadata": {"weights": {"EWJ": 0.0079, "IGOV": 0.9921}, "sigma_1": 0.009385, "sigma_2": 0.00498, "covariance": 2.3e-05, "correlation": 0.4936, "has_text": true, "text_chars": 9045, "mu_floor": -0.0506, "constraint_binding": true}} +{"id": "T4_all_20241008_0608", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "SOYB"], "decision_date": "2024-10-08", "context_summary": "SOL-USD \u03c3=0.0330, SOYB \u03c3=0.0116, \u03c1=0.028. Min-variance weights: SOL-USD=0.104, SOYB=0.896.", "question": "Assets: SOL-USD, SOYB\nSOL-USD: annualized_mean_return=-0.3780, daily_std=0.0330\nSOYB: annualized_mean_return=0.0504, daily_std=0.0116\nMinimum required portfolio return (annualized): 0.0177\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_SOYB=X.XXXX", "answer": "w_SOL-USD=0.0763, w_SOYB=0.9237", "answer_numeric": 0.0763, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000135 - 0.000011) / (0.001088 + 0.000135 - 0.000022)\n Unconstrained: w_SOL-USD=0.1036\n After long-only clamp: w_SOL-USD=0.1036, w_SOYB=0.8964.", "metadata": {"weights": {"SOL-USD": 0.0763, "SOYB": 0.9237}, "sigma_1": 0.032989, "sigma_2": 0.011634, "covariance": 1.1e-05, "correlation": 0.0282, "has_text": true, "text_chars": 20, "mu_floor": 0.0177, "constraint_binding": true}} +{"id": "T4_all_20240401_0610", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "BIL"], "decision_date": "2024-04-01", "context_summary": "LINK-USD \u03c3=0.0389, BIL \u03c3=0.0001, \u03c1=-0.061. Min-variance weights: LINK-USD=0.000, BIL=1.000.", "question": "Assets: LINK-USD, BIL\nLINK-USD: annualized_mean_return=1.1088, daily_std=0.0389\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.3867\nMarket regime: bull\n\nCompute portfolio weights (w_LINK-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_LINK-USD=0.3177, w_BIL=0.6823", "answer_numeric": 0.3177, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.001516 + 0.000000 - -0.000001)\n Unconstrained: w_LINK-USD=0.0002\n After long-only clamp: w_LINK-USD=0.0002, w_BIL=0.9998.", "metadata": {"weights": {"LINK-USD": 0.3177, "BIL": 0.6823}, "sigma_1": 0.038937, "sigma_2": 0.00015, "covariance": -0.0, "correlation": -0.061, "has_text": true, "text_chars": 20, "mu_floor": 0.3867, "constraint_binding": true}} +{"id": "T4_all_20230427_0613", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "SCHH"], "decision_date": "2023-04-27", "context_summary": "XLE \u03c3=0.0171, SCHH \u03c3=0.0132, \u03c1=0.183. Min-variance weights: XLE=0.344, SCHH=0.656.", "question": "Assets: XLE, SCHH\nXLE: annualized_mean_return=-0.2016, daily_std=0.0171\nSCHH: annualized_mean_return=-0.3276, daily_std=0.0132\nMinimum required portfolio return (annualized): -0.2894\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLE=X.XXXX, w_SCHH=X.XXXX", "answer": "w_XLE=0.3436, w_SCHH=0.6564", "answer_numeric": 0.3436, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000173 - 0.000041) / (0.000294 + 0.000173 - 0.000082)\n Unconstrained: w_XLE=0.3435\n After long-only clamp: w_XLE=0.3435, w_SCHH=0.6565.", "metadata": {"weights": {"XLE": 0.3436, "SCHH": 0.6564}, "sigma_1": 0.017145, "sigma_2": 0.013169, "covariance": 4.1e-05, "correlation": 0.1826, "has_text": true, "text_chars": 3020, "mu_floor": -0.2894, "constraint_binding": false}} +{"id": "T4_all_20240207_0616", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SHY"], "decision_date": "2024-02-07", "context_summary": "ETH-USD \u03c3=0.0278, SHY \u03c3=0.0013, \u03c1=0.095. Min-variance weights: ETH-USD=0.000, SHY=1.000.", "question": "Assets: ETH-USD, SHY\nETH-USD: annualized_mean_return=0.1260, daily_std=0.0278\nSHY: annualized_mean_return=0.0756, daily_std=0.0013\nMinimum required portfolio return (annualized): 0.1055\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_ETH-USD=0.5933, w_SHY=0.4067", "answer_numeric": 0.5933, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000002 - 0.000003) / (0.000775 + 0.000002 - 0.000007)\n Unconstrained: w_ETH-USD=-0.0023\n After long-only clamp: w_ETH-USD=0.0000, w_SHY=1.0000.", "metadata": {"weights": {"ETH-USD": 0.5933, "SHY": 0.4067}, "sigma_1": 0.027839, "sigma_2": 0.001301, "covariance": 3e-06, "correlation": 0.0955, "has_text": true, "text_chars": 20, "mu_floor": 0.1055, "constraint_binding": true}} +{"id": "T4_all_20230907_0619", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "DBB"], "decision_date": "2023-09-07", "context_summary": "BTC-USD \u03c3=0.0172, DBB \u03c3=0.0107, \u03c1=-0.018. Min-variance weights: BTC-USD=0.282, DBB=0.718.", "question": "Assets: BTC-USD, DBB\nBTC-USD: annualized_mean_return=-0.6552, daily_std=0.0172\nDBB: annualized_mean_return=0.1008, daily_std=0.0107\nMinimum required portfolio return (annualized): -0.4253\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_DBB=X.XXXX", "answer": "w_BTC-USD=0.2815, w_DBB=0.7185", "answer_numeric": 0.2815, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000114 - -0.000003) / (0.000295 + 0.000114 - -0.000007)\n Unconstrained: w_BTC-USD=0.2818\n After long-only clamp: w_BTC-USD=0.2818, w_DBB=0.7182.", "metadata": {"weights": {"BTC-USD": 0.2815, "DBB": 0.7185}, "sigma_1": 0.017183, "sigma_2": 0.010669, "covariance": -3e-06, "correlation": -0.0182, "has_text": true, "text_chars": 20, "mu_floor": -0.4253, "constraint_binding": false}} +{"id": "T4_all_20241218_0622", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "SCHH"], "decision_date": "2024-12-18", "context_summary": "XLB \u03c3=0.0077, SCHH \u03c3=0.0084, \u03c1=0.261. Min-variance weights: XLB=0.561, SCHH=0.439.", "question": "Assets: XLB, SCHH\nXLB: annualized_mean_return=-0.3024, daily_std=0.0077\nSCHH: annualized_mean_return=-0.2268, daily_std=0.0084\nMinimum required portfolio return (annualized): -0.2464\nMarket regime: bull\n\nCompute portfolio weights (w_XLB, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_SCHH=X.XXXX", "answer": "w_XLB=0.2593, w_SCHH=0.7407", "answer_numeric": 0.2593, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000071 - 0.000017) / (0.000059 + 0.000071 - 0.000034)\n Unconstrained: w_XLB=0.5607\n After long-only clamp: w_XLB=0.5607, w_SCHH=0.4393.", "metadata": {"weights": {"XLB": 0.2593, "SCHH": 0.7407}, "sigma_1": 0.007701, "sigma_2": 0.008427, "covariance": 1.7e-05, "correlation": 0.2609, "has_text": true, "text_chars": 9045, "mu_floor": -0.2464, "constraint_binding": true}} +{"id": "T4_all_20240402_0625", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "REZ"], "decision_date": "2024-04-02", "context_summary": "XLK \u03c3=0.0111, REZ \u03c3=0.0106, \u03c1=0.225. Min-variance weights: XLK=0.470, REZ=0.530.", "question": "Assets: XLK, REZ\nXLK: annualized_mean_return=0.5040, daily_std=0.0111\nREZ: annualized_mean_return=-0.0504, daily_std=0.0106\nMinimum required portfolio return (annualized): 0.0822\nMarket regime: bull\n\nCompute portfolio weights (w_XLK, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_REZ=X.XXXX", "answer": "w_XLK=0.4705, w_REZ=0.5295", "answer_numeric": 0.4705, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000112 - 0.000026) / (0.000123 + 0.000112 - 0.000053)\n Unconstrained: w_XLK=0.4704\n After long-only clamp: w_XLK=0.4704, w_REZ=0.5296.", "metadata": {"weights": {"XLK": 0.4705, "REZ": 0.5295}, "sigma_1": 0.011093, "sigma_2": 0.010594, "covariance": 2.6e-05, "correlation": 0.2246, "has_text": true, "text_chars": 9045, "mu_floor": 0.0822, "constraint_binding": false}} +{"id": "T4_all_20241223_0628", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "WEAT"], "decision_date": "2024-12-23", "context_summary": "BTC-USD \u03c3=0.0286, WEAT \u03c3=0.0109, \u03c1=0.028. Min-variance weights: BTC-USD=0.120, WEAT=0.879.", "question": "Assets: BTC-USD, WEAT\nBTC-USD: annualized_mean_return=1.6128, daily_std=0.0286\nWEAT: annualized_mean_return=-0.5544, daily_std=0.0109\nMinimum required portfolio return (annualized): 0.9388\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_WEAT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_WEAT=X.XXXX", "answer": "w_BTC-USD=0.6890, w_WEAT=0.3110", "answer_numeric": 0.689, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000120 - 0.000009) / (0.000818 + 0.000120 - 0.000018)\n Unconstrained: w_BTC-USD=0.1205\n After long-only clamp: w_BTC-USD=0.1205, w_WEAT=0.8795.", "metadata": {"weights": {"BTC-USD": 0.689, "WEAT": 0.311}, "sigma_1": 0.028609, "sigma_2": 0.010947, "covariance": 9e-06, "correlation": 0.0284, "has_text": true, "text_chars": 20, "mu_floor": 0.9388, "constraint_binding": true}} +{"id": "T4_all_20241105_0631", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "INDS"], "decision_date": "2024-11-05", "context_summary": "VLUE \u03c3=0.0075, INDS \u03c3=0.0099, \u03c1=0.599. Min-variance weights: VLUE=0.816, INDS=0.184.", "question": "Assets: VLUE, INDS\nVLUE: annualized_mean_return=0.2772, daily_std=0.0075\nINDS: annualized_mean_return=-0.1008, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.1080\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_INDS=X.XXXX", "answer": "w_VLUE=0.8194, w_INDS=0.1806", "answer_numeric": 0.8194, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000098 - 0.000045) / (0.000057 + 0.000098 - 0.000089)\n Unconstrained: w_VLUE=0.8156\n After long-only clamp: w_VLUE=0.8156, w_INDS=0.1844.", "metadata": {"weights": {"VLUE": 0.8194, "INDS": 0.1806}, "sigma_1": 0.007528, "sigma_2": 0.009897, "covariance": 4.5e-05, "correlation": 0.5989, "has_text": true, "text_chars": 9045, "mu_floor": 0.108, "constraint_binding": false}} +{"id": "T4_all_20240913_0633", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD"], "decision_date": "2024-09-13", "context_summary": "QQQ \u03c3=0.0148, BNB-USD \u03c3=0.0294, \u03c1=0.065. Min-variance weights: QQQ=0.815, BNB-USD=0.185.", "question": "Assets: QQQ, BNB-USD\nQQQ: annualized_mean_return=-0.1008, daily_std=0.0148\nBNB-USD: annualized_mean_return=0.1008, daily_std=0.0294\nMinimum required portfolio return (annualized): -0.0740\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_BNB-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QQQ=X.XXXX, w_BNB-USD=X.XXXX", "answer": "w_QQQ=0.8152, w_BNB-USD=0.1848", "answer_numeric": 0.8152, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000865 - 0.000028) / (0.000218 + 0.000865 - 0.000057)\n Unconstrained: w_QQQ=0.8154\n After long-only clamp: w_QQQ=0.8154, w_BNB-USD=0.1846.", "metadata": {"weights": {"QQQ": 0.8152, "BNB-USD": 0.1848}, "sigma_1": 0.014756, "sigma_2": 0.02941, "covariance": 2.8e-05, "correlation": 0.0652, "has_text": true, "text_chars": 9045, "mu_floor": -0.074, "constraint_binding": false}} +{"id": "T4_all_20240917_0636", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "SHY"], "decision_date": "2024-09-17", "context_summary": "XLY \u03c3=0.0146, SHY \u03c3=0.0010, \u03c1=0.084. Min-variance weights: XLY=0.000, SHY=1.000.", "question": "Assets: XLY, SHY\nXLY: annualized_mean_return=0.2772, daily_std=0.0146\nSHY: annualized_mean_return=0.1260, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.2319\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_SHY=X.XXXX", "answer": "w_XLY=0.7004, w_SHY=0.2996", "answer_numeric": 0.7004, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000001) / (0.000213 + 0.000001 - 0.000002)\n Unconstrained: w_XLY=-0.0011\n After long-only clamp: w_XLY=0.0000, w_SHY=1.0000.", "metadata": {"weights": {"XLY": 0.7004, "SHY": 0.2996}, "sigma_1": 0.014587, "sigma_2": 0.001003, "covariance": 1e-06, "correlation": 0.0844, "has_text": true, "text_chars": 9045, "mu_floor": 0.2319, "constraint_binding": true}} +{"id": "T4_all_20241120_0639", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "TLH"], "decision_date": "2024-11-20", "context_summary": "IWM \u03c3=0.0117, TLH \u03c3=0.0066, \u03c1=-0.119. Min-variance weights: IWM=0.268, TLH=0.732.", "question": "Assets: IWM, TLH\nIWM: annualized_mean_return=0.1260, daily_std=0.0117\nTLH: annualized_mean_return=-0.2520, daily_std=0.0066\nMinimum required portfolio return (annualized): -0.1556\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_TLH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_TLH=X.XXXX", "answer": "w_IWM=0.2675, w_TLH=0.7325", "answer_numeric": 0.2675, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000044 - -0.000009) / (0.000136 + 0.000044 - -0.000018)\n Unconstrained: w_IWM=0.2679\n After long-only clamp: w_IWM=0.2679, w_TLH=0.7321.", "metadata": {"weights": {"IWM": 0.2675, "TLH": 0.7325}, "sigma_1": 0.011658, "sigma_2": 0.006627, "covariance": -9e-06, "correlation": -0.1189, "has_text": true, "text_chars": 9045, "mu_floor": -0.1556, "constraint_binding": false}} +{"id": "T4_all_20231016_0641", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BIL"], "decision_date": "2023-10-16", "context_summary": "XLP \u03c3=0.0066, BIL \u03c3=0.0002, \u03c1=0.107. Min-variance weights: XLP=0.000, BIL=1.000.", "question": "Assets: XLP, BIL\nXLP: annualized_mean_return=-0.4788, daily_std=0.0066\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.0494\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLP=0.0005, w_BIL=0.9995", "answer_numeric": 0.0005, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000043 + 0.000000 - 0.000000)\n Unconstrained: w_XLP=-0.0019\n After long-only clamp: w_XLP=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLP": 0.0005, "BIL": 0.9995}, "sigma_1": 0.006591, "sigma_2": 0.000151, "covariance": 0.0, "correlation": 0.1072, "has_text": true, "text_chars": 3020, "mu_floor": -0.0494, "constraint_binding": false}} +{"id": "T4_all_20241202_0644", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "TLT"], "decision_date": "2024-12-02", "context_summary": "XLV \u03c3=0.0068, TLT \u03c3=0.0086, \u03c1=0.184. Min-variance weights: XLV=0.638, TLT=0.362.", "question": "Assets: XLV, TLT\nXLV: annualized_mean_return=-0.1764, daily_std=0.0068\nTLT: annualized_mean_return=-0.1512, daily_std=0.0086\nMinimum required portfolio return (annualized): -0.1614\nMarket regime: bull\n\nCompute portfolio weights (w_XLV, w_TLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLV=X.XXXX, w_TLT=X.XXXX", "answer": "w_XLV=0.4048, w_TLT=0.5952", "answer_numeric": 0.4048, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000073 - 0.000011) / (0.000046 + 0.000073 - 0.000021)\n Unconstrained: w_XLV=0.6379\n After long-only clamp: w_XLV=0.6379, w_TLT=0.3621.", "metadata": {"weights": {"XLV": 0.4048, "TLT": 0.5952}, "sigma_1": 0.006796, "sigma_2": 0.008557, "covariance": 1.1e-05, "correlation": 0.1838, "has_text": true, "text_chars": 9046, "mu_floor": -0.1614, "constraint_binding": true}} +{"id": "T4_all_20230220_0645", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD"], "decision_date": "2023-02-20", "context_summary": "XLRE \u03c3=0.0135, ETH-USD \u03c3=0.0259, \u03c1=-0.042. Min-variance weights: XLRE=0.778, ETH-USD=0.222.", "question": "Assets: XLRE, ETH-USD\nXLRE: annualized_mean_return=0.1764, daily_std=0.0135\nETH-USD: annualized_mean_return=1.4616, daily_std=0.0259\nMinimum required portfolio return (annualized): 0.3440\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_ETH-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_ETH-USD=X.XXXX", "answer": "w_XLRE=0.7773, w_ETH-USD=0.2227", "answer_numeric": 0.7773, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000673 - -0.000015) / (0.000182 + 0.000673 - -0.000029)\n Unconstrained: w_XLRE=0.7776\n After long-only clamp: w_XLRE=0.7776, w_ETH-USD=0.2224.", "metadata": {"weights": {"XLRE": 0.7773, "ETH-USD": 0.2227}, "sigma_1": 0.013494, "sigma_2": 0.025942, "covariance": -1.5e-05, "correlation": -0.0417, "has_text": true, "text_chars": 3020, "mu_floor": 0.344, "constraint_binding": false}} +{"id": "T4_all_20240329_0648", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD", "IEF"], "decision_date": "2024-03-29", "context_summary": "ETH-USD \u03c3=0.0325, IEF \u03c3=0.0042, \u03c1=0.045. Min-variance weights: ETH-USD=0.011, IEF=0.989.", "question": "Assets: ETH-USD, IEF\nETH-USD: annualized_mean_return=2.0664, daily_std=0.0325\nIEF: annualized_mean_return=-0.0252, daily_std=0.0042\nMinimum required portfolio return (annualized): 0.7199\nMarket regime: bull\n\nCompute portfolio weights (w_ETH-USD, w_IEF) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_IEF=X.XXXX", "answer": "w_ETH-USD=0.3562, w_IEF=0.6438", "answer_numeric": 0.3562, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000017 - 0.000006) / (0.001054 + 0.000017 - 0.000012)\n Unconstrained: w_ETH-USD=0.0106\n After long-only clamp: w_ETH-USD=0.0106, w_IEF=0.9894.", "metadata": {"weights": {"ETH-USD": 0.3562, "IEF": 0.6438}, "sigma_1": 0.032471, "sigma_2": 0.004153, "covariance": 6e-06, "correlation": 0.0447, "has_text": true, "text_chars": 20, "mu_floor": 0.7199, "constraint_binding": true}} +{"id": "T4_all_20240703_0650", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "CSHI"], "decision_date": "2024-07-03", "context_summary": "MTUM \u03c3=0.0103, CSHI \u03c3=0.0003, \u03c1=-0.007. Min-variance weights: MTUM=0.001, CSHI=0.999.", "question": "Assets: MTUM, CSHI\nMTUM: annualized_mean_return=0.2016, daily_std=0.0103\nCSHI: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.1352\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_CSHI=X.XXXX", "answer": "w_MTUM=0.4730, w_CSHI=0.5270", "answer_numeric": 0.473, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000106 + 0.000000 - -0.000000)\n Unconstrained: w_MTUM=0.0012\n After long-only clamp: w_MTUM=0.0012, w_CSHI=0.9988.", "metadata": {"weights": {"MTUM": 0.473, "CSHI": 0.527}, "sigma_1": 0.010276, "sigma_2": 0.000325, "covariance": -0.0, "correlation": -0.0069, "has_text": true, "text_chars": 9045, "mu_floor": 0.1352, "constraint_binding": true}} +{"id": "T4_all_20240522_0653", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD", "SHY"], "decision_date": "2024-05-22", "context_summary": "AVAX-USD \u03c3=0.0509, SHY \u03c3=0.0010, \u03c1=-0.031. Min-variance weights: AVAX-USD=0.001, SHY=0.999.", "question": "Assets: AVAX-USD, SHY\nAVAX-USD: annualized_mean_return=-0.7560, daily_std=0.0509\nSHY: annualized_mean_return=0.0252, daily_std=0.0010\nMinimum required portfolio return (annualized): -0.3986\nMarket regime: bull\n\nCompute portfolio weights (w_AVAX-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_AVAX-USD=0.0011, w_SHY=0.9989", "answer_numeric": 0.0011, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000002) / (0.002590 + 0.000001 - -0.000003)\n Unconstrained: w_AVAX-USD=0.0010\n After long-only clamp: w_AVAX-USD=0.0010, w_SHY=0.9990.", "metadata": {"weights": {"AVAX-USD": 0.0011, "SHY": 0.9989}, "sigma_1": 0.050887, "sigma_2": 0.000963, "covariance": -2e-06, "correlation": -0.0314, "has_text": true, "text_chars": 20, "mu_floor": -0.3986, "constraint_binding": false}} +{"id": "T4_all_20240508_0656", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "BNDX"], "decision_date": "2024-05-08", "context_summary": "ETH-USD \u03c3=0.0369, BNDX \u03c3=0.0025, \u03c1=0.015. Min-variance weights: ETH-USD=0.004, BNDX=0.996.", "question": "Assets: ETH-USD, BNDX\nETH-USD: annualized_mean_return=-0.9072, daily_std=0.0369\nBNDX: annualized_mean_return=0.0504, daily_std=0.0025\nMinimum required portfolio return (annualized): 0.0487\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_BNDX=X.XXXX", "answer": "w_ETH-USD=0.0018, w_BNDX=0.9982", "answer_numeric": 0.0018, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000006 - 0.000001) / (0.001362 + 0.000006 - 0.000003)\n Unconstrained: w_ETH-USD=0.0037\n After long-only clamp: w_ETH-USD=0.0037, w_BNDX=0.9963.", "metadata": {"weights": {"ETH-USD": 0.0018, "BNDX": 0.9982}, "sigma_1": 0.036908, "sigma_2": 0.002528, "covariance": 1e-06, "correlation": 0.0148, "has_text": true, "text_chars": 20, "mu_floor": 0.0487, "constraint_binding": true}} +{"id": "T4_all_20230614_0658", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "VTI"], "decision_date": "2023-06-14", "context_summary": "BNB-USD \u03c3=0.0262, VTI \u03c3=0.0081, \u03c1=0.077. Min-variance weights: BNB-USD=0.068, VTI=0.932.", "question": "Assets: BNB-USD, VTI\nBNB-USD: annualized_mean_return=-1.1592, daily_std=0.0262\nVTI: annualized_mean_return=0.4788, daily_std=0.0081\nMinimum required portfolio return (annualized): 0.4526\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_VTI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_VTI=X.XXXX", "answer": "w_BNB-USD=0.0160, w_VTI=0.9840", "answer_numeric": 0.016, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000065 - 0.000016) / (0.000686 + 0.000065 - 0.000033)\n Unconstrained: w_BNB-USD=0.0680\n After long-only clamp: w_BNB-USD=0.0680, w_VTI=0.9320.", "metadata": {"weights": {"BNB-USD": 0.016, "VTI": 0.984}, "sigma_1": 0.026183, "sigma_2": 0.008075, "covariance": 1.6e-05, "correlation": 0.0775, "has_text": true, "text_chars": 20, "mu_floor": 0.4526, "constraint_binding": true}} +{"id": "T4_all_20230904_0661", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "UNG"], "decision_date": "2023-09-04", "context_summary": "SOL-USD \u03c3=0.0402, UNG \u03c3=0.0305, \u03c1=0.019. Min-variance weights: SOL-USD=0.363, UNG=0.637.", "question": "Assets: SOL-USD, UNG\nSOL-USD: annualized_mean_return=0.3276, daily_std=0.0402\nUNG: annualized_mean_return=0.7560, daily_std=0.0305\nMinimum required portfolio return (annualized): 0.5220\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_UNG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_UNG=X.XXXX", "answer": "w_SOL-USD=0.3627, w_UNG=0.6373", "answer_numeric": 0.3627, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000931 - 0.000023) / (0.001619 + 0.000931 - 0.000046)\n Unconstrained: w_SOL-USD=0.3627\n After long-only clamp: w_SOL-USD=0.3627, w_UNG=0.6373.", "metadata": {"weights": {"SOL-USD": 0.3627, "UNG": 0.6373}, "sigma_1": 0.040237, "sigma_2": 0.030517, "covariance": 2.3e-05, "correlation": 0.0189, "has_text": true, "text_chars": 20, "mu_floor": 0.522, "constraint_binding": false}} +{"id": "T4_all_20241101_0664", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "GLD"], "decision_date": "2024-11-01", "context_summary": "VTI \u03c3=0.0082, GLD \u03c3=0.0081, \u03c1=0.372. Min-variance weights: VTI=0.493, GLD=0.507.", "question": "Assets: VTI, GLD\nVTI: annualized_mean_return=0.4032, daily_std=0.0082\nGLD: annualized_mean_return=0.4536, daily_std=0.0081\nMinimum required portfolio return (annualized): 0.4344\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_GLD=X.XXXX", "answer": "w_VTI=0.3810, w_GLD=0.6190", "answer_numeric": 0.381, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000066 - 0.000025) / (0.000067 + 0.000066 - 0.000049)\n Unconstrained: w_VTI=0.4927\n After long-only clamp: w_VTI=0.4927, w_GLD=0.5073.", "metadata": {"weights": {"VTI": 0.381, "GLD": 0.619}, "sigma_1": 0.008177, "sigma_2": 0.008103, "covariance": 2.5e-05, "correlation": 0.3722, "has_text": true, "text_chars": 9046, "mu_floor": 0.4344, "constraint_binding": true}} +{"id": "T4_all_20240820_0666", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "HAUZ"], "decision_date": "2024-08-20", "context_summary": "IWM \u03c3=0.0146, HAUZ \u03c3=0.0100, \u03c1=0.637. Min-variance weights: IWM=0.060, HAUZ=0.940.", "question": "Assets: IWM, HAUZ\nIWM: annualized_mean_return=0.1764, daily_std=0.0146\nHAUZ: annualized_mean_return=0.1764, daily_std=0.0100\nMinimum required portfolio return (annualized): 0.1763\nMarket regime: bull\n\nCompute portfolio weights (w_IWM, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_IWM=0.0614, w_HAUZ=0.9386", "answer_numeric": 0.0614, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000101 - 0.000093) / (0.000213 + 0.000101 - 0.000186)\n Unconstrained: w_IWM=0.0601\n After long-only clamp: w_IWM=0.0601, w_HAUZ=0.9399.", "metadata": {"weights": {"IWM": 0.0614, "HAUZ": 0.9386}, "sigma_1": 0.01458, "sigma_2": 0.010041, "covariance": 9.3e-05, "correlation": 0.6365, "has_text": true, "text_chars": 9045, "mu_floor": 0.1763, "constraint_binding": false}} +{"id": "T4_all_20231027_0669", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "CSHI"], "decision_date": "2023-10-27", "context_summary": "AVAX-USD \u03c3=0.0270, CSHI \u03c3=0.0005, \u03c1=-0.136. Min-variance weights: AVAX-USD=0.003, CSHI=0.997.", "question": "Assets: AVAX-USD, CSHI\nAVAX-USD: annualized_mean_return=0.4284, daily_std=0.0270\nCSHI: annualized_mean_return=0.0756, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0762\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_AVAX-USD=0.0031, w_CSHI=0.9969", "answer_numeric": 0.0031, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000002) / (0.000727 + 0.000000 - -0.000004)\n Unconstrained: w_AVAX-USD=0.0029\n After long-only clamp: w_AVAX-USD=0.0029, w_CSHI=0.9971.", "metadata": {"weights": {"AVAX-USD": 0.0031, "CSHI": 0.9969}, "sigma_1": 0.026955, "sigma_2": 0.000507, "covariance": -2e-06, "correlation": -0.1356, "has_text": true, "text_chars": 20, "mu_floor": 0.0762, "constraint_binding": false}} +{"id": "T4_all_20231128_0672", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "CSHI"], "decision_date": "2023-11-28", "context_summary": "IVV \u03c3=0.0082, CSHI \u03c3=0.0005, \u03c1=-0.069. Min-variance weights: IVV=0.009, CSHI=0.992.", "question": "Assets: IVV, CSHI\nIVV: annualized_mean_return=0.0504, daily_std=0.0082\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_CSHI=X.XXXX", "answer": "w_IVV=0.0041, w_CSHI=0.9959", "answer_numeric": 0.0041, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000067 + 0.000000 - -0.000001)\n Unconstrained: w_IVV=0.0085\n After long-only clamp: w_IVV=0.0085, w_CSHI=0.9915.", "metadata": {"weights": {"IVV": 0.0041, "CSHI": 0.9959}, "sigma_1": 0.008208, "sigma_2": 0.000528, "covariance": -0.0, "correlation": -0.0691, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20231214_0674", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SOYB"], "decision_date": "2023-12-14", "context_summary": "EFA \u03c3=0.0085, SOYB \u03c3=0.0098, \u03c1=0.104. Min-variance weights: EFA=0.576, SOYB=0.424.", "question": "Assets: EFA, SOYB\nEFA: annualized_mean_return=0.2016, daily_std=0.0085\nSOYB: annualized_mean_return=-0.0252, daily_std=0.0098\nMinimum required portfolio return (annualized): 0.1608\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_SOYB=X.XXXX", "answer": "w_EFA=0.8201, w_SOYB=0.1799", "answer_numeric": 0.8201, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000096 - 0.000009) / (0.000073 + 0.000096 - 0.000017)\n Unconstrained: w_EFA=0.5756\n After long-only clamp: w_EFA=0.5756, w_SOYB=0.4244.", "metadata": {"weights": {"EFA": 0.8201, "SOYB": 0.1799}, "sigma_1": 0.008536, "sigma_2": 0.009783, "covariance": 9e-06, "correlation": 0.1042, "has_text": true, "text_chars": 3020, "mu_floor": 0.1608, "constraint_binding": true}} +{"id": "T4_all_20230502_0676", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MORT"], "decision_date": "2023-05-02", "context_summary": "FXI \u03c3=0.0167, MORT \u03c3=0.0172, \u03c1=0.189. Min-variance weights: FXI=0.519, MORT=0.481.", "question": "Assets: FXI, MORT\nFXI: annualized_mean_return=-0.5040, daily_std=0.0167\nMORT: annualized_mean_return=-0.8820, daily_std=0.0172\nMinimum required portfolio return (annualized): -0.6236\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_MORT=X.XXXX", "answer": "w_FXI=0.6836, w_MORT=0.3164", "answer_numeric": 0.6836, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000297 - 0.000055) / (0.000279 + 0.000297 - 0.000109)\n Unconstrained: w_FXI=0.5193\n After long-only clamp: w_FXI=0.5193, w_MORT=0.4807.", "metadata": {"weights": {"FXI": 0.6836, "MORT": 0.3164}, "sigma_1": 0.01671, "sigma_2": 0.017242, "covariance": 5.5e-05, "correlation": 0.1895, "has_text": true, "text_chars": 3020, "mu_floor": -0.6236, "constraint_binding": true}} +{"id": "T4_all_20230704_0678", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BIL"], "decision_date": "2023-07-04", "context_summary": "EFA \u03c3=0.0077, BIL \u03c3=0.0002, \u03c1=0.075. Min-variance weights: EFA=0.000, BIL=1.000.", "question": "Assets: EFA, BIL\nEFA: annualized_mean_return=0.1260, daily_std=0.0077\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0680\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_BIL=X.XXXX", "answer": "w_EFA=0.2328, w_BIL=0.7672", "answer_numeric": 0.2328, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000060 + 0.000000 - 0.000000)\n Unconstrained: w_EFA=-0.0011\n After long-only clamp: w_EFA=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"EFA": 0.2328, "BIL": 0.7672}, "sigma_1": 0.007727, "sigma_2": 0.00016, "covariance": 0.0, "correlation": 0.0752, "has_text": true, "text_chars": 3020, "mu_floor": 0.068, "constraint_binding": true}} +{"id": "T4_all_20230213_0680", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "HYG"], "decision_date": "2023-02-13", "context_summary": "IWM \u03c3=0.0131, HYG \u03c3=0.0063, \u03c1=0.056. Min-variance weights: IWM=0.175, HYG=0.825.", "question": "Assets: IWM, HYG\nIWM: annualized_mean_return=0.1512, daily_std=0.0131\nHYG: annualized_mean_return=0.1260, daily_std=0.0063\nMinimum required portfolio return (annualized): 0.1393\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_HYG=X.XXXX", "answer": "w_IWM=0.5278, w_HYG=0.4722", "answer_numeric": 0.5278, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000040 - 0.000005) / (0.000171 + 0.000040 - 0.000009)\n Unconstrained: w_IWM=0.1753\n After long-only clamp: w_IWM=0.1753, w_HYG=0.8247.", "metadata": {"weights": {"IWM": 0.5278, "HYG": 0.4722}, "sigma_1": 0.013082, "sigma_2": 0.006326, "covariance": 5e-06, "correlation": 0.0561, "has_text": true, "text_chars": 3020, "mu_floor": 0.1393, "constraint_binding": true}} +{"id": "T4_all_20230523_0682", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SGOV"], "decision_date": "2023-05-23", "context_summary": "EEM \u03c3=0.0090, SGOV \u03c3=0.0002, \u03c1=0.056. Min-variance weights: EEM=0.000, SGOV=1.000.", "question": "Assets: EEM, SGOV\nEEM: annualized_mean_return=0.1008, daily_std=0.0090\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0755\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_SGOV=X.XXXX", "answer": "w_EEM=0.4980, w_SGOV=0.5020", "answer_numeric": 0.498, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000082 + 0.000000 - 0.000000)\n Unconstrained: w_EEM=-0.0007\n After long-only clamp: w_EEM=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"EEM": 0.498, "SGOV": 0.502}, "sigma_1": 0.009045, "sigma_2": 0.000155, "covariance": 0.0, "correlation": 0.056, "has_text": true, "text_chars": 3020, "mu_floor": 0.0755, "constraint_binding": true}} +{"id": "T4_all_20240604_0684", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "JNK"], "decision_date": "2024-06-04", "context_summary": "DOT-USD \u03c3=0.0390, JNK \u03c3=0.0032, \u03c1=0.050. Min-variance weights: DOT-USD=0.003, JNK=0.997.", "question": "Assets: DOT-USD, JNK\nDOT-USD: annualized_mean_return=-0.6048, daily_std=0.0390\nJNK: annualized_mean_return=0.0504, daily_std=0.0032\nMinimum required portfolio return (annualized): 0.0489\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_JNK) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_JNK=X.XXXX", "answer": "w_DOT-USD=0.0023, w_JNK=0.9977", "answer_numeric": 0.0023, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - 0.000006) / (0.001518 + 0.000010 - 0.000013)\n Unconstrained: w_DOT-USD=0.0027\n After long-only clamp: w_DOT-USD=0.0027, w_JNK=0.9973.", "metadata": {"weights": {"DOT-USD": 0.0023, "JNK": 0.9977}, "sigma_1": 0.038959, "sigma_2": 0.003225, "covariance": 6e-06, "correlation": 0.05, "has_text": true, "text_chars": 20, "mu_floor": 0.0489, "constraint_binding": true}} +{"id": "T4_all_20230615_0686", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SGOV"], "decision_date": "2023-06-15", "context_summary": "ETH-USD \u03c3=0.0234, SGOV \u03c3=0.0002, \u03c1=-0.001. Min-variance weights: ETH-USD=0.000, SGOV=1.000.", "question": "Assets: ETH-USD, SGOV\nETH-USD: annualized_mean_return=-0.9324, daily_std=0.0234\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_SGOV=X.XXXX", "answer": "w_ETH-USD=-0.0000, w_SGOV=1.0000", "answer_numeric": -0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000546 + 0.000000 - -0.000000)\n Unconstrained: w_ETH-USD=0.0001\n After long-only clamp: w_ETH-USD=0.0001, w_SGOV=0.9999.", "metadata": {"weights": {"ETH-USD": -0.0, "SGOV": 1.0}, "sigma_1": 0.023357, "sigma_2": 0.000161, "covariance": -0.0, "correlation": -0.0012, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20230306_0688", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ITB"], "decision_date": "2023-03-06", "context_summary": "XLI \u03c3=0.0103, ITB \u03c3=0.0160, \u03c1=0.703. Min-variance weights: XLI=1.000, ITB=0.000.", "question": "Assets: XLI, ITB\nXLI: annualized_mean_return=0.1512, daily_std=0.0103\nITB: annualized_mean_return=0.5796, daily_std=0.0160\nMinimum required portfolio return (annualized): 0.4617\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_ITB=X.XXXX", "answer": "w_XLI=0.2752, w_ITB=0.7248", "answer_numeric": 0.2752, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000257 - 0.000116) / (0.000107 + 0.000257 - 0.000233)\n Unconstrained: w_XLI=1.0744\n After long-only clamp: w_XLI=1.0000, w_ITB=0.0000.", "metadata": {"weights": {"XLI": 0.2752, "ITB": 0.7248}, "sigma_1": 0.010331, "sigma_2": 0.016025, "covariance": 0.000116, "correlation": 0.7034, "has_text": true, "text_chars": 3020, "mu_floor": 0.4617, "constraint_binding": true}} +{"id": "T4_all_20240327_0690", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ICSH"], "decision_date": "2024-03-27", "context_summary": "MTUM \u03c3=0.0117, ICSH \u03c3=0.0003, \u03c1=0.037. Min-variance weights: MTUM=0.000, ICSH=1.000.", "question": "Assets: MTUM, ICSH\nMTUM: annualized_mean_return=0.7056, daily_std=0.0117\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.2962\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MTUM=0.3752, w_ICSH=0.6248", "answer_numeric": 0.3752, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000137 + 0.000000 - 0.000000)\n Unconstrained: w_MTUM=-0.0003\n After long-only clamp: w_MTUM=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"MTUM": 0.3752, "ICSH": 0.6248}, "sigma_1": 0.011711, "sigma_2": 0.000266, "covariance": 0.0, "correlation": 0.0369, "has_text": true, "text_chars": 9045, "mu_floor": 0.2962, "constraint_binding": true}} +{"id": "T4_all_20240822_0692", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "PALL"], "decision_date": "2024-08-22", "context_summary": "LINK-USD \u03c3=0.0455, PALL \u03c3=0.0213, \u03c1=0.230. Min-variance weights: LINK-USD=0.112, PALL=0.888.", "question": "Assets: LINK-USD, PALL\nLINK-USD: annualized_mean_return=-0.5040, daily_std=0.0455\nPALL: annualized_mean_return=-0.0756, daily_std=0.0213\nMinimum required portfolio return (annualized): -0.1099\nMarket regime: bull\n\nCompute portfolio weights (w_LINK-USD, w_PALL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_PALL=X.XXXX", "answer": "w_LINK-USD=0.0801, w_PALL=0.9199", "answer_numeric": 0.0801, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000455 - 0.000223) / (0.002068 + 0.000455 - 0.000445)\n Unconstrained: w_LINK-USD=0.1117\n After long-only clamp: w_LINK-USD=0.1117, w_PALL=0.8883.", "metadata": {"weights": {"LINK-USD": 0.0801, "PALL": 0.9199}, "sigma_1": 0.045474, "sigma_2": 0.02132, "covariance": 0.000223, "correlation": 0.2295, "has_text": true, "text_chars": 20, "mu_floor": -0.1099, "constraint_binding": true}} +{"id": "T4_all_20240724_0693", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "CORN"], "decision_date": "2024-07-24", "context_summary": "XLE \u03c3=0.0107, CORN \u03c3=0.0114, \u03c1=-0.193. Min-variance weights: XLE=0.524, CORN=0.476.", "question": "Assets: XLE, CORN\nXLE: annualized_mean_return=-0.2520, daily_std=0.0107\nCORN: annualized_mean_return=-0.3780, daily_std=0.0114\nMinimum required portfolio return (annualized): -0.3365\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_CORN) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLE=X.XXXX, w_CORN=X.XXXX", "answer": "w_XLE=0.5243, w_CORN=0.4757", "answer_numeric": 0.5243, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000130 - -0.000024) / (0.000115 + 0.000130 - -0.000047)\n Unconstrained: w_XLE=0.5244\n After long-only clamp: w_XLE=0.5244, w_CORN=0.4756.", "metadata": {"weights": {"XLE": 0.5243, "CORN": 0.4757}, "sigma_1": 0.010741, "sigma_2": 0.011385, "covariance": -2.4e-05, "correlation": -0.1928, "has_text": true, "text_chars": 9045, "mu_floor": -0.3365, "constraint_binding": false}} +{"id": "T4_all_20230602_0695", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "CPER"], "decision_date": "2023-06-02", "context_summary": "EWJ \u03c3=0.0086, CPER \u03c3=0.0128, \u03c1=0.156. Min-variance weights: EWJ=0.721, CPER=0.279.", "question": "Assets: EWJ, CPER\nEWJ: annualized_mean_return=0.2772, daily_std=0.0086\nCPER: annualized_mean_return=-0.2268, daily_std=0.0128\nMinimum required portfolio return (annualized): 0.0382\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_CPER) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EWJ=X.XXXX, w_CPER=X.XXXX", "answer": "w_EWJ=0.7209, w_CPER=0.2791", "answer_numeric": 0.7209, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000164 - 0.000017) / (0.000074 + 0.000164 - 0.000034)\n Unconstrained: w_EWJ=0.7212\n After long-only clamp: w_EWJ=0.7212, w_CPER=0.2788.", "metadata": {"weights": {"EWJ": 0.7209, "CPER": 0.2791}, "sigma_1": 0.008592, "sigma_2": 0.012796, "covariance": 1.7e-05, "correlation": 0.1561, "has_text": true, "text_chars": 3020, "mu_floor": 0.0382, "constraint_binding": false}} +{"id": "T4_all_20240826_0697", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD", "FXI"], "decision_date": "2024-08-26", "context_summary": "SOL-USD \u03c3=0.0493, FXI \u03c3=0.0126, \u03c1=0.147. Min-variance weights: SOL-USD=0.028, FXI=0.972.", "question": "Assets: SOL-USD, FXI\nSOL-USD: annualized_mean_return=0.9324, daily_std=0.0493\nFXI: annualized_mean_return=-0.0756, daily_std=0.0126\nMinimum required portfolio return (annualized): -0.0581\nMarket regime: bull\n\nCompute portfolio weights (w_SOL-USD, w_FXI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_FXI=X.XXXX", "answer": "w_SOL-USD=0.0282, w_FXI=0.9718", "answer_numeric": 0.0282, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000160 - 0.000092) / (0.002431 + 0.000160 - 0.000183)\n Unconstrained: w_SOL-USD=0.0283\n After long-only clamp: w_SOL-USD=0.0283, w_FXI=0.9717.", "metadata": {"weights": {"SOL-USD": 0.0282, "FXI": 0.9718}, "sigma_1": 0.049307, "sigma_2": 0.012642, "covariance": 9.2e-05, "correlation": 0.147, "has_text": true, "text_chars": 20, "mu_floor": -0.0581, "constraint_binding": false}} +{"id": "T4_all_20240108_0699", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "WEAT"], "decision_date": "2024-01-08", "context_summary": "ADA-USD \u03c3=0.0489, WEAT \u03c3=0.0147, \u03c1=0.028. Min-variance weights: ADA-USD=0.076, WEAT=0.924.", "question": "Assets: ADA-USD, WEAT\nADA-USD: annualized_mean_return=1.6380, daily_std=0.0489\nWEAT: annualized_mean_return=0.1008, daily_std=0.0147\nMinimum required portfolio return (annualized): 0.1733\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_WEAT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_WEAT=X.XXXX", "answer": "w_ADA-USD=0.0761, w_WEAT=0.9239", "answer_numeric": 0.0761, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000215 - 0.000020) / (0.002391 + 0.000215 - 0.000040)\n Unconstrained: w_ADA-USD=0.0760\n After long-only clamp: w_ADA-USD=0.0760, w_WEAT=0.9240.", "metadata": {"weights": {"ADA-USD": 0.0761, "WEAT": 0.9239}, "sigma_1": 0.0489, "sigma_2": 0.014675, "covariance": 2e-05, "correlation": 0.0282, "has_text": true, "text_chars": 20, "mu_floor": 0.1733, "constraint_binding": false}} +{"id": "T4_all_20240812_0700", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "IWM"], "decision_date": "2024-08-12", "context_summary": "DOT-USD \u03c3=0.0386, IWM \u03c3=0.0141, \u03c1=0.095. Min-variance weights: DOT-USD=0.092, IWM=0.908.", "question": "Assets: DOT-USD, IWM\nDOT-USD: annualized_mean_return=-1.5120, daily_std=0.0386\nIWM: annualized_mean_return=0.0000, daily_std=0.0141\nMinimum required portfolio return (annualized): -0.0702\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_IWM) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_IWM=X.XXXX", "answer": "w_DOT-USD=0.0464, w_IWM=0.9536", "answer_numeric": 0.0464, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000198 - 0.000052) / (0.001490 + 0.000198 - 0.000104)\n Unconstrained: w_DOT-USD=0.0922\n After long-only clamp: w_DOT-USD=0.0922, w_IWM=0.9078.", "metadata": {"weights": {"DOT-USD": 0.0464, "IWM": 0.9536}, "sigma_1": 0.038598, "sigma_2": 0.014067, "covariance": 5.2e-05, "correlation": 0.0955, "has_text": true, "text_chars": 20, "mu_floor": -0.0702, "constraint_binding": true}} +{"id": "T4_all_20231103_0701", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SCHH"], "decision_date": "2023-11-03", "context_summary": "VTI \u03c3=0.0084, SCHH \u03c3=0.0122, \u03c1=0.732. Min-variance weights: VTI=1.000, SCHH=0.000.", "question": "Assets: VTI, SCHH\nVTI: annualized_mean_return=-0.1512, daily_std=0.0084\nSCHH: annualized_mean_return=-0.3024, daily_std=0.0122\nMinimum required portfolio return (annualized): -0.2353\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_SCHH=X.XXXX", "answer": "w_VTI=1.0000, w_SCHH=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000150 - 0.000075) / (0.000071 + 0.000150 - 0.000151)\n Unconstrained: w_VTI=1.0655\n After long-only clamp: w_VTI=1.0000, w_SCHH=0.0000.", "metadata": {"weights": {"VTI": 1.0, "SCHH": 0.0}, "sigma_1": 0.008408, "sigma_2": 0.012228, "covariance": 7.5e-05, "correlation": 0.732, "has_text": true, "text_chars": 3020, "mu_floor": -0.2353, "constraint_binding": false}} +{"id": "T4_all_20231215_0703", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "CSHI"], "decision_date": "2023-12-15", "context_summary": "AVAX-USD \u03c3=0.0593, CSHI \u03c3=0.0005, \u03c1=-0.058. Min-variance weights: AVAX-USD=0.001, CSHI=0.999.", "question": "Assets: AVAX-USD, CSHI\nAVAX-USD: annualized_mean_return=6.6024, daily_std=0.0593\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0526\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_AVAX-USD=0.0006, w_CSHI=0.9994", "answer_numeric": 0.0006, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000002) / (0.003519 + 0.000000 - -0.000004)\n Unconstrained: w_AVAX-USD=0.0006\n After long-only clamp: w_AVAX-USD=0.0006, w_CSHI=0.9994.", "metadata": {"weights": {"AVAX-USD": 0.0006, "CSHI": 0.9994}, "sigma_1": 0.059323, "sigma_2": 0.000515, "covariance": -2e-06, "correlation": -0.058, "has_text": true, "text_chars": 20, "mu_floor": 0.0526, "constraint_binding": false}} +{"id": "T4_all_20240722_0704", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "DBB"], "decision_date": "2024-07-22", "context_summary": "DOT-USD \u03c3=0.0343, DBB \u03c3=0.0113, \u03c1=0.165. Min-variance weights: DOT-USD=0.055, DBB=0.945.", "question": "Assets: DOT-USD, DBB\nDOT-USD: annualized_mean_return=-0.4788, daily_std=0.0343\nDBB: annualized_mean_return=-0.1764, daily_std=0.0113\nMinimum required portfolio return (annualized): -0.1840\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_DBB=X.XXXX", "answer": "w_DOT-USD=0.0251, w_DBB=0.9749", "answer_numeric": 0.0251, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000129 - 0.000064) / (0.001175 + 0.000129 - 0.000128)\n Unconstrained: w_DOT-USD=0.0550\n After long-only clamp: w_DOT-USD=0.0550, w_DBB=0.9450.", "metadata": {"weights": {"DOT-USD": 0.0251, "DBB": 0.9749}, "sigma_1": 0.034284, "sigma_2": 0.011344, "covariance": 6.4e-05, "correlation": 0.1646, "has_text": true, "text_chars": 20, "mu_floor": -0.184, "constraint_binding": true}} +{"id": "T4_all_20240130_0705", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SGOV"], "decision_date": "2024-01-30", "context_summary": "IWM \u03c3=0.0134, SGOV \u03c3=0.0002, \u03c1=-0.167. Min-variance weights: IWM=0.002, SGOV=0.998.", "question": "Assets: IWM, SGOV\nIWM: annualized_mean_return=0.7560, daily_std=0.0134\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_SGOV=X.XXXX", "answer": "w_IWM=0.0001, w_SGOV=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000181 + 0.000000 - -0.000001)\n Unconstrained: w_IWM=0.0021\n After long-only clamp: w_IWM=0.0021, w_SGOV=0.9979.", "metadata": {"weights": {"IWM": 0.0001, "SGOV": 0.9999}, "sigma_1": 0.013439, "sigma_2": 0.000158, "covariance": -0.0, "correlation": -0.1672, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240213_0707", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "SHY"], "decision_date": "2024-02-13", "context_summary": "BNB-USD \u03c3=0.0274, SHY \u03c3=0.0012, \u03c1=-0.003. Min-variance weights: BNB-USD=0.002, SHY=0.998.", "question": "Assets: BNB-USD, SHY\nBNB-USD: annualized_mean_return=1.1844, daily_std=0.0274\nSHY: annualized_mean_return=0.0756, daily_std=0.0012\nMinimum required portfolio return (annualized): 0.0771\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_BNB-USD=0.0020, w_SHY=0.9980", "answer_numeric": 0.002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000000) / (0.000752 + 0.000001 - -0.000000)\n Unconstrained: w_BNB-USD=0.0021\n After long-only clamp: w_BNB-USD=0.0021, w_SHY=0.9979.", "metadata": {"weights": {"BNB-USD": 0.002, "SHY": 0.998}, "sigma_1": 0.027423, "sigma_2": 0.001213, "covariance": -0.0, "correlation": -0.003, "has_text": true, "text_chars": 20, "mu_floor": 0.0771, "constraint_binding": false}} +{"id": "T4_all_20240718_0709", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "WEAT"], "decision_date": "2024-07-18", "context_summary": "MTUM \u03c3=0.0103, WEAT \u03c3=0.0168, \u03c1=-0.182. Min-variance weights: MTUM=0.697, WEAT=0.303.", "question": "Assets: MTUM, WEAT\nMTUM: annualized_mean_return=0.4788, daily_std=0.0103\nWEAT: annualized_mean_return=-0.6048, daily_std=0.0168\nMinimum required portfolio return (annualized): 0.0302\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_WEAT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_WEAT=X.XXXX", "answer": "w_MTUM=0.6972, w_WEAT=0.3028", "answer_numeric": 0.6972, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000284 - -0.000031) / (0.000106 + 0.000284 - -0.000063)\n Unconstrained: w_MTUM=0.6968\n After long-only clamp: w_MTUM=0.6968, w_WEAT=0.3032.", "metadata": {"weights": {"MTUM": 0.6972, "WEAT": 0.3028}, "sigma_1": 0.010285, "sigma_2": 0.016849, "covariance": -3.1e-05, "correlation": -0.1816, "has_text": true, "text_chars": 9045, "mu_floor": 0.0302, "constraint_binding": false}} +{"id": "T4_all_20231115_0711", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SCHH"], "decision_date": "2023-11-15", "context_summary": "VLUE \u03c3=0.0089, SCHH \u03c3=0.0134, \u03c1=0.838. Min-variance weights: VLUE=1.000, SCHH=0.000.", "question": "Assets: VLUE, SCHH\nVLUE: annualized_mean_return=0.0000, daily_std=0.0089\nSCHH: annualized_mean_return=-0.0504, daily_std=0.0134\nMinimum required portfolio return (annualized): -0.0034\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_SCHH=X.XXXX", "answer": "w_VLUE=1.0000, w_SCHH=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000180 - 0.000100) / (0.000079 + 0.000180 - 0.000200)\n Unconstrained: w_VLUE=1.3524\n After long-only clamp: w_VLUE=1.0000, w_SCHH=0.0000.", "metadata": {"weights": {"VLUE": 1.0, "SCHH": 0.0}, "sigma_1": 0.00891, "sigma_2": 0.013427, "covariance": 0.0001, "correlation": 0.8379, "has_text": true, "text_chars": 3020, "mu_floor": -0.0034, "constraint_binding": false}} +{"id": "T4_all_20230725_0713", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "VNQI"], "decision_date": "2023-07-25", "context_summary": "DOT-USD \u03c3=0.0279, VNQI \u03c3=0.0098, \u03c1=0.078. Min-variance weights: DOT-USD=0.091, VNQI=0.909.", "question": "Assets: DOT-USD, VNQI\nDOT-USD: annualized_mean_return=0.0756, daily_std=0.0279\nVNQI: annualized_mean_return=0.0504, daily_std=0.0098\nMinimum required portfolio return (annualized): 0.0526\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_DOT-USD=0.0911, w_VNQI=0.9089", "answer_numeric": 0.0911, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000097 - 0.000021) / (0.000778 + 0.000097 - 0.000043)\n Unconstrained: w_DOT-USD=0.0908\n After long-only clamp: w_DOT-USD=0.0908, w_VNQI=0.9092.", "metadata": {"weights": {"DOT-USD": 0.0911, "VNQI": 0.9089}, "sigma_1": 0.02789, "sigma_2": 0.009844, "covariance": 2.1e-05, "correlation": 0.0778, "has_text": true, "text_chars": 20, "mu_floor": 0.0526, "constraint_binding": false}} +{"id": "T4_all_20230418_0714", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "LQD"], "decision_date": "2023-04-18", "context_summary": "VEA \u03c3=0.0090, LQD \u03c3=0.0056, \u03c1=0.068. Min-variance weights: VEA=0.268, LQD=0.732.", "question": "Assets: VEA, LQD\nVEA: annualized_mean_return=0.1512, daily_std=0.0090\nLQD: annualized_mean_return=-0.0000, daily_std=0.0056\nMinimum required portfolio return (annualized): 0.0835\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_LQD=X.XXXX", "answer": "w_VEA=0.5522, w_LQD=0.4478", "answer_numeric": 0.5522, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000032 - 0.000003) / (0.000080 + 0.000032 - 0.000007)\n Unconstrained: w_VEA=0.2683\n After long-only clamp: w_VEA=0.2683, w_LQD=0.7317.", "metadata": {"weights": {"VEA": 0.5522, "LQD": 0.4478}, "sigma_1": 0.008969, "sigma_2": 0.005628, "covariance": 3e-06, "correlation": 0.0679, "has_text": true, "text_chars": 3020, "mu_floor": 0.0835, "constraint_binding": true}} +{"id": "T4_all_20231207_0716", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "SOYB"], "decision_date": "2023-12-07", "context_summary": "XLRE \u03c3=0.0135, SOYB \u03c3=0.0099, \u03c1=0.229. Min-variance weights: XLRE=0.303, SOYB=0.697.", "question": "Assets: XLRE, SOYB\nXLRE: annualized_mean_return=0.1008, daily_std=0.0135\nSOYB: annualized_mean_return=-0.2520, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.0227\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_SOYB=X.XXXX", "answer": "w_XLRE=0.7786, w_SOYB=0.2214", "answer_numeric": 0.7786, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000097 - 0.000031) / (0.000183 + 0.000097 - 0.000061)\n Unconstrained: w_XLRE=0.3033\n After long-only clamp: w_XLRE=0.3033, w_SOYB=0.6967.", "metadata": {"weights": {"XLRE": 0.7786, "SOYB": 0.2214}, "sigma_1": 0.013542, "sigma_2": 0.009854, "covariance": 3.1e-05, "correlation": 0.229, "has_text": true, "text_chars": 3020, "mu_floor": 0.0227, "constraint_binding": true}} +{"id": "T4_all_20230530_0718", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "DBB"], "decision_date": "2023-05-30", "context_summary": "XLRE \u03c3=0.0141, DBB \u03c3=0.0119, \u03c1=-0.060. Min-variance weights: XLRE=0.420, DBB=0.580.", "question": "Assets: XLRE, DBB\nXLRE: annualized_mean_return=-0.2520, daily_std=0.0141\nDBB: annualized_mean_return=-0.4032, daily_std=0.0119\nMinimum required portfolio return (annualized): -0.3140\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_DBB=X.XXXX", "answer": "w_XLRE=0.5899, w_DBB=0.4101", "answer_numeric": 0.5899, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000140 - -0.000010) / (0.000197 + 0.000140 - -0.000020)\n Unconstrained: w_XLRE=0.4205\n After long-only clamp: w_XLRE=0.4205, w_DBB=0.5795.", "metadata": {"weights": {"XLRE": 0.5899, "DBB": 0.4101}, "sigma_1": 0.014051, "sigma_2": 0.011853, "covariance": -1e-05, "correlation": -0.0603, "has_text": true, "text_chars": 3020, "mu_floor": -0.314, "constraint_binding": true}} +{"id": "T4_all_20230109_0719", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "BNDX"], "decision_date": "2023-01-09", "context_summary": "ADA-USD \u03c3=0.0344, BNDX \u03c3=0.0039, \u03c1=0.055. Min-variance weights: ADA-USD=0.007, BNDX=0.993.", "question": "Assets: ADA-USD, BNDX\nADA-USD: annualized_mean_return=-0.1512, daily_std=0.0344\nBNDX: annualized_mean_return=0.1008, daily_std=0.0039\nMinimum required portfolio return (annualized): 0.0428\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_BNDX=X.XXXX", "answer": "w_ADA-USD=0.0072, w_BNDX=0.9928", "answer_numeric": 0.0072, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000015 - 0.000007) / (0.001184 + 0.000015 - 0.000015)\n Unconstrained: w_ADA-USD=0.0068\n After long-only clamp: w_ADA-USD=0.0068, w_BNDX=0.9932.", "metadata": {"weights": {"ADA-USD": 0.0072, "BNDX": 0.9928}, "sigma_1": 0.034412, "sigma_2": 0.003935, "covariance": 7e-06, "correlation": 0.0553, "has_text": true, "text_chars": 20, "mu_floor": 0.0428, "constraint_binding": false}} +{"id": "T4_all_20230609_0720", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "EWJ"], "decision_date": "2023-06-09", "context_summary": "SOL-USD \u03c3=0.0351, EWJ \u03c3=0.0096, \u03c1=0.247. Min-variance weights: SOL-USD=0.007, EWJ=0.993.", "question": "Assets: SOL-USD, EWJ\nSOL-USD: annualized_mean_return=-0.1512, daily_std=0.0351\nEWJ: annualized_mean_return=0.4284, daily_std=0.0096\nMinimum required portfolio return (annualized): 0.4257\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_EWJ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_EWJ=X.XXXX", "answer": "w_SOL-USD=0.0047, w_EWJ=0.9953", "answer_numeric": 0.0047, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000091 - 0.000083) / (0.001229 + 0.000091 - 0.000165)\n Unconstrained: w_SOL-USD=0.0075\n After long-only clamp: w_SOL-USD=0.0075, w_EWJ=0.9925.", "metadata": {"weights": {"SOL-USD": 0.0047, "EWJ": 0.9953}, "sigma_1": 0.035058, "sigma_2": 0.009553, "covariance": 8.3e-05, "correlation": 0.2466, "has_text": true, "text_chars": 20, "mu_floor": 0.4257, "constraint_binding": true}} +{"id": "T4_all_20240906_0722", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "PDBC"], "decision_date": "2024-09-06", "context_summary": "XLRE \u03c3=0.0087, PDBC \u03c3=0.0086, \u03c1=0.025. Min-variance weights: XLRE=0.499, PDBC=0.501.", "question": "Assets: XLRE, PDBC\nXLRE: annualized_mean_return=0.6048, daily_std=0.0087\nPDBC: annualized_mean_return=-0.3276, daily_std=0.0086\nMinimum required portfolio return (annualized): 0.3929\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_PDBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_PDBC=X.XXXX", "answer": "w_XLRE=0.7727, w_PDBC=0.2273", "answer_numeric": 0.7727, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000074 - 0.000002) / (0.000075 + 0.000074 - 0.000004)\n Unconstrained: w_XLRE=0.4986\n After long-only clamp: w_XLRE=0.4986, w_PDBC=0.5014.", "metadata": {"weights": {"XLRE": 0.7727, "PDBC": 0.2273}, "sigma_1": 0.008653, "sigma_2": 0.00863, "covariance": 2e-06, "correlation": 0.025, "has_text": true, "text_chars": 9045, "mu_floor": 0.3929, "constraint_binding": true}} +{"id": "T4_all_20230412_0724", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "CSHI"], "decision_date": "2023-04-12", "context_summary": "EFA \u03c3=0.0088, CSHI \u03c3=0.0008, \u03c1=0.076. Min-variance weights: EFA=0.001, CSHI=0.999.", "question": "Assets: EFA, CSHI\nEFA: annualized_mean_return=0.1260, daily_std=0.0088\nCSHI: annualized_mean_return=0.0756, daily_std=0.0008\nMinimum required portfolio return (annualized): 0.0943\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_CSHI=X.XXXX", "answer": "w_EFA=0.3710, w_CSHI=0.6290", "answer_numeric": 0.371, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000001) / (0.000078 + 0.000001 - 0.000001)\n Unconstrained: w_EFA=0.0012\n After long-only clamp: w_EFA=0.0012, w_CSHI=0.9988.", "metadata": {"weights": {"EFA": 0.371, "CSHI": 0.629}, "sigma_1": 0.008817, "sigma_2": 0.000793, "covariance": 1e-06, "correlation": 0.0764, "has_text": true, "text_chars": 3020, "mu_floor": 0.0943, "constraint_binding": true}} +{"id": "T4_all_20230831_0726", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "DBC"], "decision_date": "2023-08-31", "context_summary": "XRP-USD \u03c3=0.0534, DBC \u03c3=0.0084, \u03c1=0.059. Min-variance weights: XRP-USD=0.015, DBC=0.985.", "question": "Assets: XRP-USD, DBC\nXRP-USD: annualized_mean_return=-0.3276, daily_std=0.0534\nDBC: annualized_mean_return=0.4032, daily_std=0.0084\nMinimum required portfolio return (annualized): 0.3945\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_DBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_DBC=X.XXXX", "answer": "w_XRP-USD=0.0119, w_DBC=0.9881", "answer_numeric": 0.0119, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000071 - 0.000027) / (0.002848 + 0.000071 - 0.000053)\n Unconstrained: w_XRP-USD=0.0155\n After long-only clamp: w_XRP-USD=0.0155, w_DBC=0.9845.", "metadata": {"weights": {"XRP-USD": 0.0119, "DBC": 0.9881}, "sigma_1": 0.053366, "sigma_2": 0.00843, "covariance": 2.7e-05, "correlation": 0.0593, "has_text": true, "text_chars": 20, "mu_floor": 0.3945, "constraint_binding": true}} +{"id": "T4_all_20231212_0728", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "IAU"], "decision_date": "2023-12-12", "context_summary": "MATIC-USD \u03c3=0.0396, IAU \u03c3=0.0086, \u03c1=-0.044. Min-variance weights: MATIC-USD=0.053, IAU=0.947.", "question": "Assets: MATIC-USD, IAU\nMATIC-USD: annualized_mean_return=2.3184, daily_std=0.0396\nIAU: annualized_mean_return=0.0252, daily_std=0.0086\nMinimum required portfolio return (annualized): 1.2637\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_IAU) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_IAU=X.XXXX", "answer": "w_MATIC-USD=0.5401, w_IAU=0.4599", "answer_numeric": 0.5401, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000073 - -0.000015) / (0.001567 + 0.000073 - -0.000030)\n Unconstrained: w_MATIC-USD=0.0529\n After long-only clamp: w_MATIC-USD=0.0529, w_IAU=0.9471.", "metadata": {"weights": {"MATIC-USD": 0.5401, "IAU": 0.4599}, "sigma_1": 0.039588, "sigma_2": 0.00856, "covariance": -1.5e-05, "correlation": -0.0443, "has_text": true, "text_chars": 20, "mu_floor": 1.2637, "constraint_binding": true}} +{"id": "T4_all_20230222_0729", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "IYR"], "decision_date": "2023-02-22", "context_summary": "MATIC-USD \u03c3=0.0399, IYR \u03c3=0.0133, \u03c1=0.100. Min-variance weights: MATIC-USD=0.074, IYR=0.926.", "question": "Assets: MATIC-USD, IYR\nMATIC-USD: annualized_mean_return=2.5200, daily_std=0.0399\nIYR: annualized_mean_return=0.1008, daily_std=0.0133\nMinimum required portfolio return (annualized): 0.2641\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_IYR=X.XXXX", "answer": "w_MATIC-USD=0.0742, w_IYR=0.9258", "answer_numeric": 0.0742, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000176 - 0.000053) / (0.001589 + 0.000176 - 0.000106)\n Unconstrained: w_MATIC-USD=0.0741\n After long-only clamp: w_MATIC-USD=0.0741, w_IYR=0.9259.", "metadata": {"weights": {"MATIC-USD": 0.0742, "IYR": 0.9258}, "sigma_1": 0.039867, "sigma_2": 0.013269, "covariance": 5.3e-05, "correlation": 0.1005, "has_text": true, "text_chars": 20, "mu_floor": 0.2641, "constraint_binding": false}} +{"id": "T4_all_20241107_0731", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "SCHP"], "decision_date": "2024-11-07", "context_summary": "EWJ \u03c3=0.0118, SCHP \u03c3=0.0028, \u03c1=-0.011. Min-variance weights: EWJ=0.055, SCHP=0.945.", "question": "Assets: EWJ, SCHP\nEWJ: annualized_mean_return=0.1260, daily_std=0.0118\nSCHP: annualized_mean_return=-0.0252, daily_std=0.0028\nMinimum required portfolio return (annualized): -0.0190\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_SCHP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EWJ=X.XXXX, w_SCHP=X.XXXX", "answer": "w_EWJ=0.0523, w_SCHP=0.9477", "answer_numeric": 0.0523, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000008 - -0.000000) / (0.000139 + 0.000008 - -0.000001)\n Unconstrained: w_EWJ=0.0546\n After long-only clamp: w_EWJ=0.0546, w_SCHP=0.9454.", "metadata": {"weights": {"EWJ": 0.0523, "SCHP": 0.9477}, "sigma_1": 0.011778, "sigma_2": 0.002768, "covariance": -0.0, "correlation": -0.0112, "has_text": true, "text_chars": 9045, "mu_floor": -0.019, "constraint_binding": false}} +{"id": "T4_all_20231211_0733", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "MATIC-USD"], "decision_date": "2023-12-11", "context_summary": "XLF \u03c3=0.0089, MATIC-USD \u03c3=0.0377, \u03c1=-0.086. Min-variance weights: XLF=0.931, MATIC-USD=0.069.", "question": "Assets: XLF, MATIC-USD\nXLF: annualized_mean_return=0.1512, daily_std=0.0089\nMATIC-USD: annualized_mean_return=2.6460, daily_std=0.0377\nMinimum required portfolio return (annualized): 0.3071\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_MATIC-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_MATIC-USD=X.XXXX", "answer": "w_XLF=0.9306, w_MATIC-USD=0.0694", "answer_numeric": 0.9306, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001420 - -0.000029) / (0.000079 + 0.001420 - -0.000058)\n Unconstrained: w_XLF=0.9306\n After long-only clamp: w_XLF=0.9306, w_MATIC-USD=0.0694.", "metadata": {"weights": {"XLF": 0.9306, "MATIC-USD": 0.0694}, "sigma_1": 0.008893, "sigma_2": 0.037678, "covariance": -2.9e-05, "correlation": -0.0861, "has_text": true, "text_chars": 3020, "mu_floor": 0.3071, "constraint_binding": false}} +{"id": "T4_all_20241213_0735", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "VNQI"], "decision_date": "2024-12-13", "context_summary": "BTC-USD \u03c3=0.0276, VNQI \u03c3=0.0087, \u03c1=-0.191. Min-variance weights: BTC-USD=0.131, VNQI=0.869.", "question": "Assets: BTC-USD, VNQI\nBTC-USD: annualized_mean_return=2.0412, daily_std=0.0276\nVNQI: annualized_mean_return=-0.2772, daily_std=0.0087\nMinimum required portfolio return (annualized): -0.1054\nMarket regime: bull\n\nCompute portfolio weights (w_BTC-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_BTC-USD=0.1310, w_VNQI=0.8690", "answer_numeric": 0.131, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000076 - -0.000046) / (0.000763 + 0.000076 - -0.000092)\n Unconstrained: w_BTC-USD=0.1310\n After long-only clamp: w_BTC-USD=0.1310, w_VNQI=0.8690.", "metadata": {"weights": {"BTC-USD": 0.131, "VNQI": 0.869}, "sigma_1": 0.027619, "sigma_2": 0.008715, "covariance": -4.6e-05, "correlation": -0.191, "has_text": true, "text_chars": 20, "mu_floor": -0.1054, "constraint_binding": false}} +{"id": "T4_all_20230307_0737", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "DBB"], "decision_date": "2023-03-07", "context_summary": "DOT-USD \u03c3=0.0418, DBB \u03c3=0.0131, \u03c1=-0.034. Min-variance weights: DOT-USD=0.097, DBB=0.903.", "question": "Assets: DOT-USD, DBB\nDOT-USD: annualized_mean_return=1.2600, daily_std=0.0418\nDBB: annualized_mean_return=0.0252, daily_std=0.0131\nMinimum required portfolio return (annualized): 0.1113\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_DBB=X.XXXX", "answer": "w_DOT-USD=0.0972, w_DBB=0.9028", "answer_numeric": 0.0972, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000171 - -0.000019) / (0.001748 + 0.000171 - -0.000037)\n Unconstrained: w_DOT-USD=0.0970\n After long-only clamp: w_DOT-USD=0.0970, w_DBB=0.9030.", "metadata": {"weights": {"DOT-USD": 0.0972, "DBB": 0.9028}, "sigma_1": 0.041806, "sigma_2": 0.013083, "covariance": -1.9e-05, "correlation": -0.0338, "has_text": true, "text_chars": 20, "mu_floor": 0.1113, "constraint_binding": false}} +{"id": "T4_all_20230201_0739", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "REZ"], "decision_date": "2023-02-01", "context_summary": "XLF \u03c3=0.0113, REZ \u03c3=0.0142, \u03c1=0.740. Min-variance weights: XLF=0.906, REZ=0.093.", "question": "Assets: XLF, REZ\nXLF: annualized_mean_return=0.3276, daily_std=0.0113\nREZ: annualized_mean_return=0.3024, daily_std=0.0142\nMinimum required portfolio return (annualized): 0.3163\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_REZ=X.XXXX", "answer": "w_XLF=0.9059, w_REZ=0.0941", "answer_numeric": 0.9059, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000201 - 0.000118) / (0.000127 + 0.000201 - 0.000236)\n Unconstrained: w_XLF=0.9065\n After long-only clamp: w_XLF=0.9065, w_REZ=0.0935.", "metadata": {"weights": {"XLF": 0.9059, "REZ": 0.0941}, "sigma_1": 0.011252, "sigma_2": 0.014171, "covariance": 0.000118, "correlation": 0.7405, "has_text": true, "text_chars": 3020, "mu_floor": 0.3163, "constraint_binding": false}} +{"id": "T4_all_20230620_0741", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "ICSH"], "decision_date": "2023-06-20", "context_summary": "MATIC-USD \u03c3=0.0334, ICSH \u03c3=0.0005, \u03c1=0.023. Min-variance weights: MATIC-USD=0.000, ICSH=1.000.", "question": "Assets: MATIC-USD, ICSH\nMATIC-USD: annualized_mean_return=-2.0916, daily_std=0.0334\nICSH: annualized_mean_return=0.0252, daily_std=0.0005\nMinimum required portfolio return (annualized): -1.1678\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MATIC-USD=0.0002, w_ICSH=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.001117 + 0.000000 - 0.000001)\n Unconstrained: w_MATIC-USD=-0.0001\n After long-only clamp: w_MATIC-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0002, "ICSH": 0.9998}, "sigma_1": 0.03342, "sigma_2": 0.000457, "covariance": 0.0, "correlation": 0.0233, "has_text": true, "text_chars": 20, "mu_floor": -1.1678, "constraint_binding": false}} +{"id": "T4_all_20240319_0743", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "DBB"], "decision_date": "2024-03-19", "context_summary": "LINK-USD \u03c3=0.0381, DBB \u03c3=0.0086, \u03c1=-0.130. Min-variance weights: LINK-USD=0.072, DBB=0.928.", "question": "Assets: LINK-USD, DBB\nLINK-USD: annualized_mean_return=1.1340, daily_std=0.0381\nDBB: annualized_mean_return=0.0504, daily_std=0.0086\nMinimum required portfolio return (annualized): 0.1117\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_DBB=X.XXXX", "answer": "w_LINK-USD=0.0725, w_DBB=0.9275", "answer_numeric": 0.0725, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000074 - -0.000043) / (0.001455 + 0.000074 - -0.000085)\n Unconstrained: w_LINK-USD=0.0723\n After long-only clamp: w_LINK-USD=0.0723, w_DBB=0.9277.", "metadata": {"weights": {"LINK-USD": 0.0725, "DBB": 0.9275}, "sigma_1": 0.038148, "sigma_2": 0.008612, "covariance": -4.3e-05, "correlation": -0.1296, "has_text": true, "text_chars": 20, "mu_floor": 0.1117, "constraint_binding": false}} +{"id": "T4_all_20230623_0745", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "BIL"], "decision_date": "2023-06-23", "context_summary": "LINK-USD \u03c3=0.0280, BIL \u03c3=0.0002, \u03c1=-0.045. Min-variance weights: LINK-USD=0.000, BIL=1.000.", "question": "Assets: LINK-USD, BIL\nLINK-USD: annualized_mean_return=-0.9072, daily_std=0.0280\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.4043\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_LINK-USD=0.0000, w_BIL=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000783 + 0.000000 - -0.000000)\n Unconstrained: w_LINK-USD=0.0003\n After long-only clamp: w_LINK-USD=0.0003, w_BIL=0.9997.", "metadata": {"weights": {"LINK-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.027989, "sigma_2": 0.000174, "covariance": -0.0, "correlation": -0.045, "has_text": true, "text_chars": 20, "mu_floor": -0.4043, "constraint_binding": false}} +{"id": "T4_all_20230419_0746", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "TLH"], "decision_date": "2023-04-19", "context_summary": "XLU \u03c3=0.0115, TLH \u03c3=0.0085, \u03c1=-0.111. Min-variance weights: XLU=0.368, TLH=0.631.", "question": "Assets: XLU, TLH\nXLU: annualized_mean_return=-0.0000, daily_std=0.0115\nTLH: annualized_mean_return=-0.0756, daily_std=0.0085\nMinimum required portfolio return (annualized): -0.0104\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_TLH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_TLH=X.XXXX", "answer": "w_XLU=0.8624, w_TLH=0.1376", "answer_numeric": 0.8624, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000073 - -0.000011) / (0.000133 + 0.000073 - -0.000022)\n Unconstrained: w_XLU=0.3685\n After long-only clamp: w_XLU=0.3685, w_TLH=0.6315.", "metadata": {"weights": {"XLU": 0.8624, "TLH": 0.1376}, "sigma_1": 0.011535, "sigma_2": 0.008547, "covariance": -1.1e-05, "correlation": -0.1115, "has_text": true, "text_chars": 3020, "mu_floor": -0.0104, "constraint_binding": true}} +{"id": "T4_all_20240924_0748", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SCHH"], "decision_date": "2024-09-24", "context_summary": "FXI \u03c3=0.0128, SCHH \u03c3=0.0087, \u03c1=0.157. Min-variance weights: FXI=0.286, SCHH=0.714.", "question": "Assets: FXI, SCHH\nFXI: annualized_mean_return=0.2772, daily_std=0.0128\nSCHH: annualized_mean_return=0.7308, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.6991\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_SCHH=X.XXXX", "answer": "w_FXI=0.0699, w_SCHH=0.9301", "answer_numeric": 0.0699, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000075 - 0.000017) / (0.000163 + 0.000075 - 0.000035)\n Unconstrained: w_FXI=0.2856\n After long-only clamp: w_FXI=0.2856, w_SCHH=0.7144.", "metadata": {"weights": {"FXI": 0.0699, "SCHH": 0.9301}, "sigma_1": 0.012754, "sigma_2": 0.008686, "covariance": 1.7e-05, "correlation": 0.1567, "has_text": true, "text_chars": 9045, "mu_floor": 0.6991, "constraint_binding": true}} +{"id": "T4_all_20240123_0749", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "CSHI"], "decision_date": "2024-01-23", "context_summary": "EEM \u03c3=0.0096, CSHI \u03c3=0.0003, \u03c1=-0.020. Min-variance weights: EEM=0.002, CSHI=0.998.", "question": "Assets: EEM, CSHI\nEEM: annualized_mean_return=0.1764, daily_std=0.0096\nCSHI: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0505\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_CSHI=X.XXXX", "answer": "w_EEM=0.0010, w_CSHI=0.9990", "answer_numeric": 0.001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000093 + 0.000000 - -0.000000)\n Unconstrained: w_EEM=0.0016\n After long-only clamp: w_EEM=0.0016, w_CSHI=0.9984.", "metadata": {"weights": {"EEM": 0.001, "CSHI": 0.999}, "sigma_1": 0.009645, "sigma_2": 0.0003, "covariance": -0.0, "correlation": -0.0201, "has_text": true, "text_chars": 3020, "mu_floor": 0.0505, "constraint_binding": false}} +{"id": "T4_all_20230406_0751", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "ITB"], "decision_date": "2023-04-06", "context_summary": "BTC-USD \u03c3=0.0312, ITB \u03c3=0.0155, \u03c1=-0.073. Min-variance weights: BTC-USD=0.216, ITB=0.784.", "question": "Assets: BTC-USD, ITB\nBTC-USD: annualized_mean_return=0.9072, daily_std=0.0312\nITB: annualized_mean_return=0.3780, daily_std=0.0155\nMinimum required portfolio return (annualized): 0.4618\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_ITB=X.XXXX", "answer": "w_BTC-USD=0.2156, w_ITB=0.7844", "answer_numeric": 0.2156, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000241 - -0.000035) / (0.000971 + 0.000241 - -0.000071)\n Unconstrained: w_BTC-USD=0.2157\n After long-only clamp: w_BTC-USD=0.2157, w_ITB=0.7843.", "metadata": {"weights": {"BTC-USD": 0.2156, "ITB": 0.7844}, "sigma_1": 0.031157, "sigma_2": 0.015538, "covariance": -3.5e-05, "correlation": -0.0729, "has_text": true, "text_chars": 20, "mu_floor": 0.4618, "constraint_binding": false}} +{"id": "T4_all_20240621_0753", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "HYG"], "decision_date": "2024-06-21", "context_summary": "AVAX-USD \u03c3=0.0394, HYG \u03c3=0.0032, \u03c1=0.050. Min-variance weights: AVAX-USD=0.002, HYG=0.998.", "question": "Assets: AVAX-USD, HYG\nAVAX-USD: annualized_mean_return=-1.0584, daily_std=0.0394\nHYG: annualized_mean_return=0.0504, daily_std=0.0032\nMinimum required portfolio return (annualized): -0.3188\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_HYG=X.XXXX", "answer": "w_AVAX-USD=0.0026, w_HYG=0.9974", "answer_numeric": 0.0026, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - 0.000006) / (0.001548 + 0.000010 - 0.000013)\n Unconstrained: w_AVAX-USD=0.0024\n After long-only clamp: w_AVAX-USD=0.0024, w_HYG=0.9976.", "metadata": {"weights": {"AVAX-USD": 0.0026, "HYG": 0.9974}, "sigma_1": 0.03935, "sigma_2": 0.003174, "covariance": 6e-06, "correlation": 0.0504, "has_text": true, "text_chars": 20, "mu_floor": -0.3188, "constraint_binding": false}} +{"id": "T4_all_20240530_0755", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "CSHI"], "decision_date": "2024-05-30", "context_summary": "XLY \u03c3=0.0094, CSHI \u03c3=0.0004, \u03c1=0.009. Min-variance weights: XLY=0.002, CSHI=0.998.", "question": "Assets: XLY, CSHI\nXLY: annualized_mean_return=-0.2016, daily_std=0.0094\nCSHI: annualized_mean_return=0.0504, daily_std=0.0004\nMinimum required portfolio return (annualized): -0.0812\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLY=0.0020, w_CSHI=0.9980", "answer_numeric": 0.002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000089 + 0.000000 - 0.000000)\n Unconstrained: w_XLY=0.0016\n After long-only clamp: w_XLY=0.0016, w_CSHI=0.9984.", "metadata": {"weights": {"XLY": 0.002, "CSHI": 0.998}, "sigma_1": 0.009409, "sigma_2": 0.000424, "covariance": 0.0, "correlation": 0.0093, "has_text": true, "text_chars": 9045, "mu_floor": -0.0812, "constraint_binding": false}} +{"id": "T4_all_20230814_0756", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ITB"], "decision_date": "2023-08-14", "context_summary": "BNB-USD \u03c3=0.0178, ITB \u03c3=0.0133, \u03c1=-0.045. Min-variance weights: BNB-USD=0.366, ITB=0.634.", "question": "Assets: BNB-USD, ITB\nBNB-USD: annualized_mean_return=0.0756, daily_std=0.0178\nITB: annualized_mean_return=0.6048, daily_std=0.0134\nMinimum required portfolio return (annualized): 0.4863\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_ITB=X.XXXX", "answer": "w_BNB-USD=0.2239, w_ITB=0.7761", "answer_numeric": 0.2239, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000178 - -0.000011) / (0.000317 + 0.000178 - -0.000021)\n Unconstrained: w_BNB-USD=0.3659\n After long-only clamp: w_BNB-USD=0.3659, w_ITB=0.6341.", "metadata": {"weights": {"BNB-USD": 0.2239, "ITB": 0.7761}, "sigma_1": 0.017796, "sigma_2": 0.01335, "covariance": -1.1e-05, "correlation": -0.045, "has_text": true, "text_chars": 20, "mu_floor": 0.4863, "constraint_binding": true}} +{"id": "T4_all_20230824_0758", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "^VIX"], "decision_date": "2023-08-24", "context_summary": "MATIC-USD \u03c3=0.0367, ^VIX \u03c3=0.0506, \u03c1=0.093. Min-variance weights: MATIC-USD=0.670, ^VIX=0.330.", "question": "Assets: MATIC-USD, ^VIX\nMATIC-USD: annualized_mean_return=-0.5292, daily_std=0.0367\n^VIX: annualized_mean_return=-0.4788, daily_std=0.0506\nMinimum required portfolio return (annualized): -0.4935\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_^VIX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_^VIX=X.XXXX", "answer": "w_MATIC-USD=0.2917, w_^VIX=0.7083", "answer_numeric": 0.2917, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.002561 - 0.000172) / (0.001347 + 0.002561 - 0.000344)\n Unconstrained: w_MATIC-USD=0.6703\n After long-only clamp: w_MATIC-USD=0.6703, w_^VIX=0.3297.", "metadata": {"weights": {"MATIC-USD": 0.2917, "^VIX": 0.7083}, "sigma_1": 0.036697, "sigma_2": 0.050603, "covariance": 0.000172, "correlation": 0.0926, "has_text": true, "text_chars": 20, "mu_floor": -0.4935, "constraint_binding": true}} +{"id": "T4_all_20230324_0760", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "XLE"], "decision_date": "2023-03-24", "context_summary": "XRP-USD \u03c3=0.0429, XLE \u03c3=0.0175, \u03c1=0.212. Min-variance weights: XRP-USD=0.080, XLE=0.920.", "question": "Assets: XRP-USD, XLE\nXRP-USD: annualized_mean_return=0.6552, daily_std=0.0429\nXLE: annualized_mean_return=-0.4032, daily_std=0.0175\nMinimum required portfolio return (annualized): 0.2524\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_XLE) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_XLE=X.XXXX", "answer": "w_XRP-USD=0.6194, w_XLE=0.3806", "answer_numeric": 0.6194, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000305 - 0.000159) / (0.001841 + 0.000305 - 0.000317)\n Unconstrained: w_XRP-USD=0.0798\n After long-only clamp: w_XRP-USD=0.0798, w_XLE=0.9202.", "metadata": {"weights": {"XRP-USD": 0.6194, "XLE": 0.3806}, "sigma_1": 0.042908, "sigma_2": 0.017453, "covariance": 0.000159, "correlation": 0.212, "has_text": true, "text_chars": 20, "mu_floor": 0.2524, "constraint_binding": true}} +{"id": "T4_all_20240318_0761", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "EMB"], "decision_date": "2024-03-18", "context_summary": "QQQ \u03c3=0.0101, EMB \u03c3=0.0049, \u03c1=0.094. Min-variance weights: QQQ=0.165, EMB=0.835.", "question": "Assets: QQQ, EMB\nQQQ: annualized_mean_return=0.2772, daily_std=0.0101\nEMB: annualized_mean_return=-0.0504, daily_std=0.0049\nMinimum required portfolio return (annualized): -0.0153\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_EMB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QQQ=X.XXXX, w_EMB=X.XXXX", "answer": "w_QQQ=0.1627, w_EMB=0.8373", "answer_numeric": 0.1627, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000024 - 0.000005) / (0.000102 + 0.000024 - 0.000009)\n Unconstrained: w_QQQ=0.1649\n After long-only clamp: w_QQQ=0.1649, w_EMB=0.8351.", "metadata": {"weights": {"QQQ": 0.1627, "EMB": 0.8373}, "sigma_1": 0.010095, "sigma_2": 0.004882, "covariance": 5e-06, "correlation": 0.0938, "has_text": true, "text_chars": 9045, "mu_floor": -0.0153, "constraint_binding": false}} +{"id": "T4_all_20240520_0763", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "CSHI"], "decision_date": "2024-05-20", "context_summary": "ACWI \u03c3=0.0066, CSHI \u03c3=0.0005, \u03c1=-0.127. Min-variance weights: ACWI=0.014, CSHI=0.986.", "question": "Assets: ACWI, CSHI\nACWI: annualized_mean_return=0.2016, daily_std=0.0066\nCSHI: annualized_mean_return=0.0252, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0259\nMarket regime: bull\n\nCompute portfolio weights (w_ACWI, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ACWI=X.XXXX, w_CSHI=X.XXXX", "answer": "w_ACWI=0.0049, w_CSHI=0.9951", "answer_numeric": 0.0049, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000044 + 0.000000 - -0.000001)\n Unconstrained: w_ACWI=0.0136\n After long-only clamp: w_ACWI=0.0136, w_CSHI=0.9864.", "metadata": {"weights": {"ACWI": 0.0049, "CSHI": 0.9951}, "sigma_1": 0.006637, "sigma_2": 0.000468, "covariance": -0.0, "correlation": -0.1273, "has_text": true, "text_chars": 9045, "mu_floor": 0.0259, "constraint_binding": false}} +{"id": "T4_all_20230111_0765", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "GLD"], "decision_date": "2023-01-11", "context_summary": "XLP \u03c3=0.0098, GLD \u03c3=0.0097, \u03c1=0.070. Min-variance weights: XLP=0.496, GLD=0.504.", "question": "Assets: XLP, GLD\nXLP: annualized_mean_return=0.3528, daily_std=0.0098\nGLD: annualized_mean_return=0.5544, daily_std=0.0097\nMinimum required portfolio return (annualized): 0.4038\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_GLD=X.XXXX", "answer": "w_XLP=0.4957, w_GLD=0.5043", "answer_numeric": 0.4957, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000094 - 0.000007) / (0.000096 + 0.000094 - 0.000013)\n Unconstrained: w_XLP=0.4958\n After long-only clamp: w_XLP=0.4958, w_GLD=0.5042.", "metadata": {"weights": {"XLP": 0.4957, "GLD": 0.5043}, "sigma_1": 0.009773, "sigma_2": 0.009696, "covariance": 7e-06, "correlation": 0.07, "has_text": true, "text_chars": 3020, "mu_floor": 0.4038, "constraint_binding": false}} +{"id": "T4_all_20241113_0767", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNDX"], "decision_date": "2024-11-13", "context_summary": "SPY \u03c3=0.0076, BNDX \u03c3=0.0020, \u03c1=-0.056. Min-variance weights: SPY=0.075, BNDX=0.925.", "question": "Assets: SPY, BNDX\nSPY: annualized_mean_return=0.2772, daily_std=0.0076\nBNDX: annualized_mean_return=0.0000, daily_std=0.0020\nMinimum required portfolio return (annualized): 0.0091\nMarket regime: sideways\n\nCompute portfolio weights (w_SPY, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_BNDX=X.XXXX", "answer": "w_SPY=0.0769, w_BNDX=0.9231", "answer_numeric": 0.0769, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000004 - -0.000001) / (0.000058 + 0.000004 - -0.000002)\n Unconstrained: w_SPY=0.0748\n After long-only clamp: w_SPY=0.0748, w_BNDX=0.9252.", "metadata": {"weights": {"SPY": 0.0769, "BNDX": 0.9231}, "sigma_1": 0.007594, "sigma_2": 0.001972, "covariance": -1e-06, "correlation": -0.0563, "has_text": true, "text_chars": 9045, "mu_floor": 0.0091, "constraint_binding": false}} +{"id": "T4_all_20240716_0769", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "SOYB"], "decision_date": "2024-07-16", "context_summary": "LINK-USD \u03c3=0.0380, SOYB \u03c3=0.0094, \u03c1=-0.130. Min-variance weights: LINK-USD=0.083, SOYB=0.917.", "question": "Assets: LINK-USD, SOYB\nLINK-USD: annualized_mean_return=-0.1260, daily_std=0.0380\nSOYB: annualized_mean_return=-0.3528, daily_std=0.0094\nMinimum required portfolio return (annualized): -0.3391\nMarket regime: bull\n\nCompute portfolio weights (w_LINK-USD, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_SOYB=X.XXXX", "answer": "w_LINK-USD=0.0831, w_SOYB=0.9169", "answer_numeric": 0.0831, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000088 - -0.000047) / (0.001447 + 0.000088 - -0.000093)\n Unconstrained: w_LINK-USD=0.0829\n After long-only clamp: w_LINK-USD=0.0829, w_SOYB=0.9171.", "metadata": {"weights": {"LINK-USD": 0.0831, "SOYB": 0.9169}, "sigma_1": 0.038042, "sigma_2": 0.009406, "covariance": -4.7e-05, "correlation": -0.1301, "has_text": true, "text_chars": 20, "mu_floor": -0.3391, "constraint_binding": false}} +{"id": "T4_all_20241104_0771", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "LQD"], "decision_date": "2024-11-04", "context_summary": "ETH-USD \u03c3=0.0258, LQD \u03c3=0.0036, \u03c1=-0.035. Min-variance weights: ETH-USD=0.024, LQD=0.977.", "question": "Assets: ETH-USD, LQD\nETH-USD: annualized_mean_return=0.1008, daily_std=0.0258\nLQD: annualized_mean_return=-0.0504, daily_std=0.0036\nMinimum required portfolio return (annualized): -0.0470\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_LQD=X.XXXX", "answer": "w_ETH-USD=0.0232, w_LQD=0.9768", "answer_numeric": 0.0232, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000013 - -0.000003) / (0.000665 + 0.000013 - -0.000006)\n Unconstrained: w_ETH-USD=0.0235\n After long-only clamp: w_ETH-USD=0.0235, w_LQD=0.9765.", "metadata": {"weights": {"ETH-USD": 0.0232, "LQD": 0.9768}, "sigma_1": 0.025788, "sigma_2": 0.003586, "covariance": -3e-06, "correlation": -0.0348, "has_text": true, "text_chars": 20, "mu_floor": -0.047, "constraint_binding": false}} +{"id": "T4_all_20230524_0772", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "CSHI"], "decision_date": "2023-05-24", "context_summary": "XRP-USD \u03c3=0.0277, CSHI \u03c3=0.0008, \u03c1=-0.028. Min-variance weights: XRP-USD=0.002, CSHI=0.998.", "question": "Assets: XRP-USD, CSHI\nXRP-USD: annualized_mean_return=0.4788, daily_std=0.0277\nCSHI: annualized_mean_return=0.0756, daily_std=0.0008\nMinimum required portfolio return (annualized): 0.1838\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XRP-USD=0.2684, w_CSHI=0.7316", "answer_numeric": 0.2684, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000001) / (0.000770 + 0.000001 - -0.000001)\n Unconstrained: w_XRP-USD=0.0016\n After long-only clamp: w_XRP-USD=0.0016, w_CSHI=0.9984.", "metadata": {"weights": {"XRP-USD": 0.2684, "CSHI": 0.7316}, "sigma_1": 0.027747, "sigma_2": 0.000788, "covariance": -1e-06, "correlation": -0.0278, "has_text": true, "text_chars": 20, "mu_floor": 0.1838, "constraint_binding": true}} +{"id": "T4_all_20240807_0773", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "IGOV"], "decision_date": "2024-08-07", "context_summary": "IVV \u03c3=0.0082, IGOV \u03c3=0.0052, \u03c1=-0.140. Min-variance weights: IVV=0.308, IGOV=0.692.", "question": "Assets: IVV, IGOV\nIVV: annualized_mean_return=0.0252, daily_std=0.0082\nIGOV: annualized_mean_return=0.1764, daily_std=0.0052\nMinimum required portfolio return (annualized): 0.0672\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_IGOV=X.XXXX", "answer": "w_IVV=0.3082, w_IGOV=0.6918", "answer_numeric": 0.3082, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000027 - -0.000006) / (0.000067 + 0.000027 - -0.000012)\n Unconstrained: w_IVV=0.3079\n After long-only clamp: w_IVV=0.3079, w_IGOV=0.6921.", "metadata": {"weights": {"IVV": 0.3082, "IGOV": 0.6918}, "sigma_1": 0.008194, "sigma_2": 0.005156, "covariance": -6e-06, "correlation": -0.1398, "has_text": true, "text_chars": 9045, "mu_floor": 0.0672, "constraint_binding": false}} +{"id": "T4_all_20241018_0775", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "GLD"], "decision_date": "2024-10-18", "context_summary": "AVAX-USD \u03c3=0.0385, GLD \u03c3=0.0082, \u03c1=-0.075. Min-variance weights: AVAX-USD=0.057, GLD=0.943.", "question": "Assets: AVAX-USD, GLD\nAVAX-USD: annualized_mean_return=1.3104, daily_std=0.0385\nGLD: annualized_mean_return=0.4536, daily_std=0.0082\nMinimum required portfolio return (annualized): 0.4975\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_GLD=X.XXXX", "answer": "w_AVAX-USD=0.0572, w_GLD=0.9428", "answer_numeric": 0.0572, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000067 - -0.000024) / (0.001483 + 0.000067 - -0.000048)\n Unconstrained: w_AVAX-USD=0.0571\n After long-only clamp: w_AVAX-USD=0.0571, w_GLD=0.9429.", "metadata": {"weights": {"AVAX-USD": 0.0572, "GLD": 0.9428}, "sigma_1": 0.038506, "sigma_2": 0.008207, "covariance": -2.4e-05, "correlation": -0.0755, "has_text": true, "text_chars": 20, "mu_floor": 0.4975, "constraint_binding": false}} +{"id": "T4_all_20240209_0777", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ICSH"], "decision_date": "2024-02-09", "context_summary": "VEA \u03c3=0.0075, ICSH \u03c3=0.0003, \u03c1=-0.228. Min-variance weights: VEA=0.011, ICSH=0.989.", "question": "Assets: VEA, ICSH\nVEA: annualized_mean_return=0.3780, daily_std=0.0075\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0564\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_ICSH=X.XXXX", "answer": "w_VEA=0.0188, w_ICSH=0.9812", "answer_numeric": 0.0188, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000056 + 0.000000 - -0.000001)\n Unconstrained: w_VEA=0.0111\n After long-only clamp: w_VEA=0.0111, w_ICSH=0.9889.", "metadata": {"weights": {"VEA": 0.0188, "ICSH": 0.9812}, "sigma_1": 0.007511, "sigma_2": 0.000316, "covariance": -1e-06, "correlation": -0.2275, "has_text": true, "text_chars": 9046, "mu_floor": 0.0564, "constraint_binding": false}} +{"id": "T4_all_20240705_0779", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ICSH"], "decision_date": "2024-07-05", "context_summary": "ACWI \u03c3=0.0063, ICSH \u03c3=0.0002, \u03c1=0.247. Min-variance weights: ACWI=0.000, ICSH=1.000.", "question": "Assets: ACWI, ICSH\nACWI: annualized_mean_return=0.2016, daily_std=0.0063\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0506\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ACWI=X.XXXX, w_ICSH=X.XXXX", "answer": "w_ACWI=0.0014, w_ICSH=0.9986", "answer_numeric": 0.0014, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000040 + 0.000000 - 0.000001)\n Unconstrained: w_ACWI=-0.0079\n After long-only clamp: w_ACWI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"ACWI": 0.0014, "ICSH": 0.9986}, "sigma_1": 0.006337, "sigma_2": 0.000234, "covariance": 0.0, "correlation": 0.247, "has_text": true, "text_chars": 9045, "mu_floor": 0.0506, "constraint_binding": false}} +{"id": "T4_all_20240405_0780", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BIL"], "decision_date": "2024-04-05", "context_summary": "XLB \u03c3=0.0084, BIL \u03c3=0.0001, \u03c1=-0.248. Min-variance weights: XLB=0.005, BIL=0.995.", "question": "Assets: XLB, BIL\nXLB: annualized_mean_return=0.3528, daily_std=0.0084\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.2195\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLB=0.5592, w_BIL=0.4408", "answer_numeric": 0.5592, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000070 + 0.000000 - -0.000001)\n Unconstrained: w_XLB=0.0047\n After long-only clamp: w_XLB=0.0047, w_BIL=0.9953.", "metadata": {"weights": {"XLB": 0.5592, "BIL": 0.4408}, "sigma_1": 0.008352, "sigma_2": 0.00015, "covariance": -0.0, "correlation": -0.2481, "has_text": true, "text_chars": 9045, "mu_floor": 0.2195, "constraint_binding": true}} +{"id": "T4_all_20240719_0782", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "PPLT"], "decision_date": "2024-07-19", "context_summary": "XLU \u03c3=0.0092, PPLT \u03c3=0.0168, \u03c1=0.087. Min-variance weights: XLU=0.791, PPLT=0.209.", "question": "Assets: XLU, PPLT\nXLU: annualized_mean_return=0.2772, daily_std=0.0092\nPPLT: annualized_mean_return=0.3780, daily_std=0.0168\nMinimum required portfolio return (annualized): 0.3453\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_PPLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_PPLT=X.XXXX", "answer": "w_XLU=0.3244, w_PPLT=0.6756", "answer_numeric": 0.3244, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000283 - 0.000014) / (0.000085 + 0.000283 - 0.000027)\n Unconstrained: w_XLU=0.7909\n After long-only clamp: w_XLU=0.7909, w_PPLT=0.2091.", "metadata": {"weights": {"XLU": 0.3244, "PPLT": 0.6756}, "sigma_1": 0.009211, "sigma_2": 0.01683, "covariance": 1.4e-05, "correlation": 0.0872, "has_text": true, "text_chars": 9045, "mu_floor": 0.3453, "constraint_binding": true}} +{"id": "T4_all_20230105_0784", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "IYR"], "decision_date": "2023-01-05", "context_summary": "EFA \u03c3=0.0117, IYR \u03c3=0.0144, \u03c1=0.804. Min-variance weights: EFA=0.984, IYR=0.016.", "question": "Assets: EFA, IYR\nEFA: annualized_mean_return=0.5292, daily_std=0.0117\nIYR: annualized_mean_return=0.2016, daily_std=0.0144\nMinimum required portfolio return (annualized): 0.5265\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_IYR=X.XXXX", "answer": "w_EFA=0.9918, w_IYR=0.0082", "answer_numeric": 0.9918, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000207 - 0.000135) / (0.000136 + 0.000207 - 0.000269)\n Unconstrained: w_EFA=0.9842\n After long-only clamp: w_EFA=0.9842, w_IYR=0.0158.", "metadata": {"weights": {"EFA": 0.9918, "IYR": 0.0082}, "sigma_1": 0.011657, "sigma_2": 0.01437, "covariance": 0.000135, "correlation": 0.8043, "has_text": true, "text_chars": 3020, "mu_floor": 0.5265, "constraint_binding": true}} +{"id": "T4_all_20230628_0785", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DBA"], "decision_date": "2023-06-28", "context_summary": "XLB \u03c3=0.0103, DBA \u03c3=0.0080, \u03c1=-0.041. Min-variance weights: XLB=0.382, DBA=0.618.", "question": "Assets: XLB, DBA\nXLB: annualized_mean_return=0.1260, daily_std=0.0103\nDBA: annualized_mean_return=0.2772, daily_std=0.0080\nMinimum required portfolio return (annualized): 0.1867\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_DBA=X.XXXX", "answer": "w_XLB=0.3816, w_DBA=0.6184", "answer_numeric": 0.3816, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000064 - -0.000003) / (0.000106 + 0.000064 - -0.000007)\n Unconstrained: w_XLB=0.3820\n After long-only clamp: w_XLB=0.3820, w_DBA=0.6180.", "metadata": {"weights": {"XLB": 0.3816, "DBA": 0.6184}, "sigma_1": 0.010279, "sigma_2": 0.008003, "covariance": -3e-06, "correlation": -0.0407, "has_text": true, "text_chars": 3020, "mu_floor": 0.1867, "constraint_binding": false}} +{"id": "T4_all_20230421_0786", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SHV"], "decision_date": "2023-04-21", "context_summary": "EFA \u03c3=0.0089, SHV \u03c3=0.0002, \u03c1=0.182. Min-variance weights: EFA=0.000, SHV=1.000.", "question": "Assets: EFA, SHV\nEFA: annualized_mean_return=0.1260, daily_std=0.0089\nSHV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0862\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_SHV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_SHV=X.XXXX", "answer": "w_EFA=0.4735, w_SHV=0.5265", "answer_numeric": 0.4735, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000080 + 0.000000 - 0.000001)\n Unconstrained: w_EFA=-0.0040\n After long-only clamp: w_EFA=0.0000, w_SHV=1.0000.", "metadata": {"weights": {"EFA": 0.4735, "SHV": 0.5265}, "sigma_1": 0.008924, "sigma_2": 0.000224, "covariance": 0.0, "correlation": 0.1821, "has_text": true, "text_chars": 3020, "mu_floor": 0.0862, "constraint_binding": true}} +{"id": "T4_all_20231009_0788", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "CSHI"], "decision_date": "2023-10-09", "context_summary": "EWJ \u03c3=0.0091, CSHI \u03c3=0.0006, \u03c1=0.078. Min-variance weights: EWJ=0.000, CSHI=1.000.", "question": "Assets: EWJ, CSHI\nEWJ: annualized_mean_return=-0.2520, daily_std=0.0091\nCSHI: annualized_mean_return=0.1008, daily_std=0.0006\nMinimum required portfolio return (annualized): 0.1003\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EWJ=X.XXXX, w_CSHI=X.XXXX", "answer": "w_EWJ=0.0014, w_CSHI=0.9986", "answer_numeric": 0.0014, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000082 + 0.000000 - 0.000001)\n Unconstrained: w_EWJ=-0.0006\n After long-only clamp: w_EWJ=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"EWJ": 0.0014, "CSHI": 0.9986}, "sigma_1": 0.009074, "sigma_2": 0.000622, "covariance": 0.0, "correlation": 0.0777, "has_text": true, "text_chars": 3020, "mu_floor": 0.1003, "constraint_binding": true}} +{"id": "T4_all_20231117_0790", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "CSHI"], "decision_date": "2023-11-17", "context_summary": "XLU \u03c3=0.0122, CSHI \u03c3=0.0005, \u03c1=0.219. Min-variance weights: XLU=0.000, CSHI=1.000.", "question": "Assets: XLU, CSHI\nXLU: annualized_mean_return=-0.0504, daily_std=0.0122\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0158\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLU=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000149 + 0.000000 - 0.000003)\n Unconstrained: w_XLU=-0.0073\n After long-only clamp: w_XLU=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"XLU": 0.0, "CSHI": 1.0}, "sigma_1": 0.012196, "sigma_2": 0.000492, "covariance": 1e-06, "correlation": 0.2188, "has_text": true, "text_chars": 3020, "mu_floor": 0.0158, "constraint_binding": false}} +{"id": "T4_all_20230404_0792", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "TIP"], "decision_date": "2023-04-04", "context_summary": "XLP \u03c3=0.0080, TIP \u03c3=0.0022, \u03c1=0.008. Min-variance weights: XLP=0.069, TIP=0.931.", "question": "Assets: XLP, TIP\nXLP: annualized_mean_return=0.0756, daily_std=0.0080\nTIP: annualized_mean_return=0.0756, daily_std=0.0022\nMinimum required portfolio return (annualized): 0.0756\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_TIP=X.XXXX", "answer": "w_XLP=0.0705, w_TIP=0.9295", "answer_numeric": 0.0705, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000005 - 0.000000) / (0.000065 + 0.000005 - 0.000000)\n Unconstrained: w_XLP=0.0688\n After long-only clamp: w_XLP=0.0688, w_TIP=0.9312.", "metadata": {"weights": {"XLP": 0.0705, "TIP": 0.9295}, "sigma_1": 0.008037, "sigma_2": 0.002213, "covariance": 0.0, "correlation": 0.0075, "has_text": true, "text_chars": 3020, "mu_floor": 0.0756, "constraint_binding": false}} +{"id": "T4_all_20230607_0794", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "IYR"], "decision_date": "2023-06-07", "context_summary": "XRP-USD \u03c3=0.0255, IYR \u03c3=0.0123, \u03c1=0.056. Min-variance weights: XRP-USD=0.173, IYR=0.827.", "question": "Assets: XRP-USD, IYR\nXRP-USD: annualized_mean_return=0.2268, daily_std=0.0255\nIYR: annualized_mean_return=0.1512, daily_std=0.0123\nMinimum required portfolio return (annualized): 0.1832\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_IYR=X.XXXX", "answer": "w_XRP-USD=0.4233, w_IYR=0.5767", "answer_numeric": 0.4233, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000150 - 0.000018) / (0.000650 + 0.000150 - 0.000035)\n Unconstrained: w_XRP-USD=0.1734\n After long-only clamp: w_XRP-USD=0.1734, w_IYR=0.8266.", "metadata": {"weights": {"XRP-USD": 0.4233, "IYR": 0.5767}, "sigma_1": 0.025496, "sigma_2": 0.012262, "covariance": 1.8e-05, "correlation": 0.0564, "has_text": true, "text_chars": 20, "mu_floor": 0.1832, "constraint_binding": true}} +{"id": "T4_all_20230707_0796", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "IVV"], "decision_date": "2023-07-07", "context_summary": "XRP-USD \u03c3=0.0244, IVV \u03c3=0.0075, \u03c1=-0.044. Min-variance weights: XRP-USD=0.096, IVV=0.904.", "question": "Assets: XRP-USD, IVV\nXRP-USD: annualized_mean_return=0.2016, daily_std=0.0244\nIVV: annualized_mean_return=0.3024, daily_std=0.0075\nMinimum required portfolio return (annualized): 0.2957\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_IVV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_IVV=X.XXXX", "answer": "w_XRP-USD=0.0665, w_IVV=0.9335", "answer_numeric": 0.0665, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000056 - -0.000008) / (0.000597 + 0.000056 - -0.000016)\n Unconstrained: w_XRP-USD=0.0961\n After long-only clamp: w_XRP-USD=0.0961, w_IVV=0.9039.", "metadata": {"weights": {"XRP-USD": 0.0665, "IVV": 0.9335}, "sigma_1": 0.024432, "sigma_2": 0.007497, "covariance": -8e-06, "correlation": -0.0444, "has_text": true, "text_chars": 20, "mu_floor": 0.2957, "constraint_binding": true}} +{"id": "T4_all_20240507_0798", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "PDBC"], "decision_date": "2024-05-07", "context_summary": "MATIC-USD \u03c3=0.0471, PDBC \u03c3=0.0066, \u03c1=-0.367. Min-variance weights: MATIC-USD=0.063, PDBC=0.937.", "question": "Assets: MATIC-USD, PDBC\nMATIC-USD: annualized_mean_return=-1.7640, daily_std=0.0471\nPDBC: annualized_mean_return=0.2268, daily_std=0.0066\nMinimum required portfolio return (annualized): 0.1597\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_PDBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_PDBC=X.XXXX", "answer": "w_MATIC-USD=0.0337, w_PDBC=0.9663", "answer_numeric": 0.0337, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000043 - -0.000114) / (0.002218 + 0.000043 - -0.000228)\n Unconstrained: w_MATIC-USD=0.0632\n After long-only clamp: w_MATIC-USD=0.0632, w_PDBC=0.9368.", "metadata": {"weights": {"MATIC-USD": 0.0337, "PDBC": 0.9663}, "sigma_1": 0.047091, "sigma_2": 0.006595, "covariance": -0.000114, "correlation": -0.3668, "has_text": true, "text_chars": 20, "mu_floor": 0.1597, "constraint_binding": true}} +{"id": "T4_all_20241030_0800", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "SCHH"], "decision_date": "2024-10-30", "context_summary": "XLY \u03c3=0.0116, SCHH \u03c3=0.0076, \u03c1=0.340. Min-variance weights: XLY=0.210, SCHH=0.790.", "question": "Assets: XLY, SCHH\nXLY: annualized_mean_return=0.6552, daily_std=0.0116\nSCHH: annualized_mean_return=0.3276, daily_std=0.0076\nMinimum required portfolio return (annualized): 0.5777\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_SCHH=X.XXXX", "answer": "w_XLY=0.7634, w_SCHH=0.2366", "answer_numeric": 0.7634, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000058 - 0.000030) / (0.000135 + 0.000058 - 0.000060)\n Unconstrained: w_XLY=0.2103\n After long-only clamp: w_XLY=0.2103, w_SCHH=0.7897.", "metadata": {"weights": {"XLY": 0.7634, "SCHH": 0.2366}, "sigma_1": 0.01164, "sigma_2": 0.007632, "covariance": 3e-05, "correlation": 0.3401, "has_text": true, "text_chars": 9044, "mu_floor": 0.5777, "constraint_binding": true}} +{"id": "T4_all_20230322_0802", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNDX"], "decision_date": "2023-03-22", "context_summary": "FXI \u03c3=0.0193, BNDX \u03c3=0.0039, \u03c1=-0.002. Min-variance weights: FXI=0.039, BNDX=0.961.", "question": "Assets: FXI, BNDX\nFXI: annualized_mean_return=-0.0756, daily_std=0.0193\nBNDX: annualized_mean_return=0.0504, daily_std=0.0039\nMinimum required portfolio return (annualized): 0.0491\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_BNDX=X.XXXX", "answer": "w_FXI=0.0103, w_BNDX=0.9897", "answer_numeric": 0.0103, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000015 - -0.000000) / (0.000373 + 0.000015 - -0.000000)\n Unconstrained: w_FXI=0.0387\n After long-only clamp: w_FXI=0.0387, w_BNDX=0.9613.", "metadata": {"weights": {"FXI": 0.0103, "BNDX": 0.9897}, "sigma_1": 0.019302, "sigma_2": 0.003852, "covariance": -0.0, "correlation": -0.0024, "has_text": true, "text_chars": 3020, "mu_floor": 0.0491, "constraint_binding": true}} +{"id": "T4_all_20231228_0803", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "CSHI"], "decision_date": "2023-12-28", "context_summary": "LINK-USD \u03c3=0.0473, CSHI \u03c3=0.0005, \u03c1=-0.117. Min-variance weights: LINK-USD=0.001, CSHI=0.999.", "question": "Assets: LINK-USD, CSHI\nLINK-USD: annualized_mean_return=2.0664, daily_std=0.0473\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0533\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_LINK-USD=0.0015, w_CSHI=0.9985", "answer_numeric": 0.0015, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000003) / (0.002235 + 0.000000 - -0.000006)\n Unconstrained: w_LINK-USD=0.0014\n After long-only clamp: w_LINK-USD=0.0014, w_CSHI=0.9986.", "metadata": {"weights": {"LINK-USD": 0.0015, "CSHI": 0.9985}, "sigma_1": 0.047273, "sigma_2": 0.000515, "covariance": -3e-06, "correlation": -0.1173, "has_text": true, "text_chars": 20, "mu_floor": 0.0533, "constraint_binding": false}} +{"id": "T4_all_20231227_0804", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "XLU"], "decision_date": "2023-12-27", "context_summary": "BNB-USD \u03c3=0.0283, XLU \u03c3=0.0116, \u03c1=0.015. Min-variance weights: BNB-USD=0.141, XLU=0.859.", "question": "Assets: BNB-USD, XLU\nBNB-USD: annualized_mean_return=1.2852, daily_std=0.0283\nXLU: annualized_mean_return=0.2772, daily_std=0.0116\nMinimum required portfolio return (annualized): 1.0986\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_XLU) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_XLU=X.XXXX", "answer": "w_BNB-USD=0.8149, w_XLU=0.1851", "answer_numeric": 0.8149, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000135 - 0.000005) / (0.000798 + 0.000135 - 0.000010)\n Unconstrained: w_BNB-USD=0.1410\n After long-only clamp: w_BNB-USD=0.1410, w_XLU=0.8590.", "metadata": {"weights": {"BNB-USD": 0.8149, "XLU": 0.1851}, "sigma_1": 0.028258, "sigma_2": 0.011635, "covariance": 5e-06, "correlation": 0.0155, "has_text": true, "text_chars": 20, "mu_floor": 1.0986, "constraint_binding": true}} +{"id": "T4_all_20240102_0805", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SLV"], "decision_date": "2024-01-02", "context_summary": "FXI \u03c3=0.0161, SLV \u03c3=0.0151, \u03c1=-0.020. Min-variance weights: FXI=0.470, SLV=0.530.", "question": "Assets: FXI, SLV\nFXI: annualized_mean_return=-0.1512, daily_std=0.0161\nSLV: annualized_mean_return=0.3780, daily_std=0.0151\nMinimum required portfolio return (annualized): -0.0009\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_SLV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_SLV=X.XXXX", "answer": "w_FXI=0.4699, w_SLV=0.5301", "answer_numeric": 0.4699, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000229 - -0.000005) / (0.000259 + 0.000229 - -0.000010)\n Unconstrained: w_FXI=0.4699\n After long-only clamp: w_FXI=0.4699, w_SLV=0.5301.", "metadata": {"weights": {"FXI": 0.4699, "SLV": 0.5301}, "sigma_1": 0.016104, "sigma_2": 0.015143, "covariance": -5e-06, "correlation": -0.0198, "has_text": true, "text_chars": 3020, "mu_floor": -0.0009, "constraint_binding": false}} +{"id": "T4_all_20240314_0806", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "DBC"], "decision_date": "2024-03-14", "context_summary": "DOT-USD \u03c3=0.0333, DBC \u03c3=0.0071, \u03c1=0.229. Min-variance weights: DOT-USD=0.000, DBC=1.000.", "question": "Assets: DOT-USD, DBC\nDOT-USD: annualized_mean_return=1.8144, daily_std=0.0333\nDBC: annualized_mean_return=0.0252, daily_std=0.0071\nMinimum required portfolio return (annualized): 0.5686\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_DBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_DBC=X.XXXX", "answer": "w_DOT-USD=0.3037, w_DBC=0.6963", "answer_numeric": 0.3037, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000050 - 0.000054) / (0.001111 + 0.000050 - 0.000108)\n Unconstrained: w_DOT-USD=-0.0037\n After long-only clamp: w_DOT-USD=0.0000, w_DBC=1.0000.", "metadata": {"weights": {"DOT-USD": 0.3037, "DBC": 0.6963}, "sigma_1": 0.033324, "sigma_2": 0.007061, "covariance": 5.4e-05, "correlation": 0.2285, "has_text": true, "text_chars": 20, "mu_floor": 0.5686, "constraint_binding": true}} +{"id": "T4_all_20240126_0808", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "DBA"], "decision_date": "2024-01-26", "context_summary": "XLK \u03c3=0.0095, DBA \u03c3=0.0079, \u03c1=0.276. Min-variance weights: XLK=0.375, DBA=0.625.", "question": "Assets: XLK, DBA\nXLK: annualized_mean_return=1.0080, daily_std=0.0095\nDBA: annualized_mean_return=-0.0252, daily_std=0.0079\nMinimum required portfolio return (annualized): 0.6548\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_DBA=X.XXXX", "answer": "w_XLK=0.6581, w_DBA=0.3419", "answer_numeric": 0.6581, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000062 - 0.000021) / (0.000089 + 0.000062 - 0.000041)\n Unconstrained: w_XLK=0.3753\n After long-only clamp: w_XLK=0.3753, w_DBA=0.6247.", "metadata": {"weights": {"XLK": 0.6581, "DBA": 0.3419}, "sigma_1": 0.009459, "sigma_2": 0.007871, "covariance": 2.1e-05, "correlation": 0.2761, "has_text": true, "text_chars": 3020, "mu_floor": 0.6548, "constraint_binding": true}} +{"id": "T4_all_20230118_0810", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "BNO"], "decision_date": "2023-01-18", "context_summary": "AVAX-USD \u03c3=0.0445, BNO \u03c3=0.0230, \u03c1=0.031. Min-variance weights: AVAX-USD=0.203, BNO=0.797.", "question": "Assets: AVAX-USD, BNO\nAVAX-USD: annualized_mean_return=1.3860, daily_std=0.0445\nBNO: annualized_mean_return=-0.1008, daily_std=0.0230\nMinimum required portfolio return (annualized): 1.0884\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_BNO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_BNO=X.XXXX", "answer": "w_AVAX-USD=0.7998, w_BNO=0.2002", "answer_numeric": 0.7998, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000529 - 0.000031) / (0.001980 + 0.000529 - 0.000063)\n Unconstrained: w_AVAX-USD=0.2034\n After long-only clamp: w_AVAX-USD=0.2034, w_BNO=0.7966.", "metadata": {"weights": {"AVAX-USD": 0.7998, "BNO": 0.2002}, "sigma_1": 0.0445, "sigma_2": 0.022998, "covariance": 3.1e-05, "correlation": 0.0306, "has_text": true, "text_chars": 20, "mu_floor": 1.0884, "constraint_binding": true}} +{"id": "T4_all_20230119_0811", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "XLU"], "decision_date": "2023-01-19", "context_summary": "ADA-USD \u03c3=0.0295, XLU \u03c3=0.0120, \u03c1=0.263. Min-variance weights: ADA-USD=0.061, XLU=0.939.", "question": "Assets: ADA-USD, XLU\nADA-USD: annualized_mean_return=0.1008, daily_std=0.0295\nXLU: annualized_mean_return=0.4284, daily_std=0.0120\nMinimum required portfolio return (annualized): 0.2881\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_XLU) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_XLU=X.XXXX", "answer": "w_ADA-USD=0.0614, w_XLU=0.9386", "answer_numeric": 0.0614, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000144 - 0.000093) / (0.000870 + 0.000144 - 0.000186)\n Unconstrained: w_ADA-USD=0.0612\n After long-only clamp: w_ADA-USD=0.0612, w_XLU=0.9388.", "metadata": {"weights": {"ADA-USD": 0.0614, "XLU": 0.9386}, "sigma_1": 0.029495, "sigma_2": 0.011992, "covariance": 9.3e-05, "correlation": 0.2635, "has_text": true, "text_chars": 20, "mu_floor": 0.2881, "constraint_binding": false}} +{"id": "T4_all_20241121_0813", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "LINK-USD"], "decision_date": "2024-11-21", "context_summary": "EEM \u03c3=0.0118, LINK-USD \u03c3=0.0433, \u03c1=0.024. Min-variance weights: EEM=0.936, LINK-USD=0.064.", "question": "Assets: EEM, LINK-USD\nEEM: annualized_mean_return=-0.0504, daily_std=0.0118\nLINK-USD: annualized_mean_return=1.1340, daily_std=0.0433\nMinimum required portfolio return (annualized): 0.0014\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_LINK-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_LINK-USD=X.XXXX", "answer": "w_EEM=0.9360, w_LINK-USD=0.0640", "answer_numeric": 0.936, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001878 - 0.000012) / (0.000140 + 0.001878 - 0.000025)\n Unconstrained: w_EEM=0.9362\n After long-only clamp: w_EEM=0.9362, w_LINK-USD=0.0638.", "metadata": {"weights": {"EEM": 0.936, "LINK-USD": 0.064}, "sigma_1": 0.011813, "sigma_2": 0.043339, "covariance": 1.2e-05, "correlation": 0.024, "has_text": true, "text_chars": 9046, "mu_floor": 0.0014, "constraint_binding": false}} +{"id": "T4_all_20240429_0815", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "VNQI"], "decision_date": "2024-04-29", "context_summary": "XRP-USD \u03c3=0.0452, VNQI \u03c3=0.0083, \u03c1=-0.107. Min-variance weights: XRP-USD=0.050, VNQI=0.950.", "question": "Assets: XRP-USD, VNQI\nXRP-USD: annualized_mean_return=-0.2520, daily_std=0.0452\nVNQI: annualized_mean_return=0.0000, daily_std=0.0083\nMinimum required portfolio return (annualized): -0.0948\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_XRP-USD=0.0498, w_VNQI=0.9502", "answer_numeric": 0.0498, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000069 - -0.000040) / (0.002041 + 0.000069 - -0.000081)\n Unconstrained: w_XRP-USD=0.0499\n After long-only clamp: w_XRP-USD=0.0499, w_VNQI=0.9501.", "metadata": {"weights": {"XRP-USD": 0.0498, "VNQI": 0.9502}, "sigma_1": 0.045174, "sigma_2": 0.008313, "covariance": -4e-05, "correlation": -0.1073, "has_text": true, "text_chars": 20, "mu_floor": -0.0948, "constraint_binding": false}} +{"id": "T4_all_20231226_0816", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "VNQI"], "decision_date": "2023-12-26", "context_summary": "ADA-USD \u03c3=0.0462, VNQI \u03c3=0.0108, \u03c1=-0.182. Min-variance weights: ADA-USD=0.085, VNQI=0.915.", "question": "Assets: ADA-USD, VNQI\nADA-USD: annualized_mean_return=3.5532, daily_std=0.0462\nVNQI: annualized_mean_return=0.4032, daily_std=0.0108\nMinimum required portfolio return (annualized): 1.5900\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_ADA-USD=0.3768, w_VNQI=0.6232", "answer_numeric": 0.3768, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000116 - -0.000091) / (0.002131 + 0.000116 - -0.000181)\n Unconstrained: w_ADA-USD=0.0850\n After long-only clamp: w_ADA-USD=0.0850, w_VNQI=0.9150.", "metadata": {"weights": {"ADA-USD": 0.3768, "VNQI": 0.6232}, "sigma_1": 0.046166, "sigma_2": 0.010759, "covariance": -9.1e-05, "correlation": -0.1824, "has_text": true, "text_chars": 20, "mu_floor": 1.59, "constraint_binding": true}} +{"id": "T4_all_20240927_0818", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ICSH"], "decision_date": "2024-09-27", "context_summary": "VTI \u03c3=0.0103, ICSH \u03c3=0.0003, \u03c1=0.147. Min-variance weights: VTI=0.000, ICSH=1.000.", "question": "Assets: VTI, ICSH\nVTI: annualized_mean_return=0.2016, daily_std=0.0103\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.1578\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_ICSH=X.XXXX", "answer": "w_VTI=0.6524, w_ICSH=0.3476", "answer_numeric": 0.6524, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000106 + 0.000000 - 0.000001)\n Unconstrained: w_VTI=-0.0034\n After long-only clamp: w_VTI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"VTI": 0.6524, "ICSH": 0.3476}, "sigma_1": 0.010304, "sigma_2": 0.000291, "covariance": 0.0, "correlation": 0.1471, "has_text": true, "text_chars": 9045, "mu_floor": 0.1578, "constraint_binding": true}} +{"id": "T4_all_20241003_0820", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "CSHI"], "decision_date": "2024-10-03", "context_summary": "VEA \u03c3=0.0103, CSHI \u03c3=0.0012, \u03c1=0.206. Min-variance weights: VEA=0.000, CSHI=1.000.", "question": "Assets: VEA, CSHI\nVEA: annualized_mean_return=0.2016, daily_std=0.0103\nCSHI: annualized_mean_return=0.0504, daily_std=0.0012\nMinimum required portfolio return (annualized): 0.0940\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_CSHI=X.XXXX", "answer": "w_VEA=0.2884, w_CSHI=0.7116", "answer_numeric": 0.2884, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000003) / (0.000107 + 0.000001 - 0.000005)\n Unconstrained: w_VEA=-0.0109\n After long-only clamp: w_VEA=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"VEA": 0.2884, "CSHI": 0.7116}, "sigma_1": 0.010347, "sigma_2": 0.001178, "covariance": 3e-06, "correlation": 0.2063, "has_text": true, "text_chars": 9045, "mu_floor": 0.094, "constraint_binding": true}} +{"id": "T4_all_20230612_0821", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "HYG"], "decision_date": "2023-06-12", "context_summary": "SOL-USD \u03c3=0.0352, HYG \u03c3=0.0044, \u03c1=-0.099. Min-variance weights: SOL-USD=0.027, HYG=0.973.", "question": "Assets: SOL-USD, HYG\nSOL-USD: annualized_mean_return=-1.6632, daily_std=0.0352\nHYG: annualized_mean_return=0.2016, daily_std=0.0044\nMinimum required portfolio return (annualized): -0.2829\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_HYG=X.XXXX", "answer": "w_SOL-USD=0.0268, w_HYG=0.9732", "answer_numeric": 0.0268, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000020 - -0.000015) / (0.001243 + 0.000020 - -0.000031)\n Unconstrained: w_SOL-USD=0.0271\n After long-only clamp: w_SOL-USD=0.0271, w_HYG=0.9729.", "metadata": {"weights": {"SOL-USD": 0.0268, "HYG": 0.9732}, "sigma_1": 0.035249, "sigma_2": 0.004427, "covariance": -1.5e-05, "correlation": -0.0992, "has_text": true, "text_chars": 20, "mu_floor": -0.2829, "constraint_binding": false}} +{"id": "T4_all_20231006_0822", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "XRP-USD"], "decision_date": "2023-10-06", "context_summary": "IVV \u03c3=0.0070, XRP-USD \u03c3=0.0261, \u03c1=0.062. Min-variance weights: IVV=0.947, XRP-USD=0.053.", "question": "Assets: IVV, XRP-USD\nIVV: annualized_mean_return=-0.2016, daily_std=0.0070\nXRP-USD: annualized_mean_return=-0.6300, daily_std=0.0261\nMinimum required portfolio return (annualized): -0.2148\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_XRP-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_XRP-USD=X.XXXX", "answer": "w_IVV=0.9692, w_XRP-USD=0.0308", "answer_numeric": 0.9692, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000683 - 0.000011) / (0.000049 + 0.000683 - 0.000023)\n Unconstrained: w_IVV=0.9473\n After long-only clamp: w_IVV=0.9473, w_XRP-USD=0.0527.", "metadata": {"weights": {"IVV": 0.9692, "XRP-USD": 0.0308}, "sigma_1": 0.006972, "sigma_2": 0.02613, "covariance": 1.1e-05, "correlation": 0.0619, "has_text": true, "text_chars": 3020, "mu_floor": -0.2148, "constraint_binding": true}} +{"id": "T4_all_20231003_0823", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "DBA"], "decision_date": "2023-10-03", "context_summary": "BNB-USD \u03c3=0.0143, DBA \u03c3=0.0071, \u03c1=0.017. Min-variance weights: BNB-USD=0.193, DBA=0.807.", "question": "Assets: BNB-USD, DBA\nBNB-USD: annualized_mean_return=-0.4536, daily_std=0.0143\nDBA: annualized_mean_return=-0.0252, daily_std=0.0071\nMinimum required portfolio return (annualized): -0.2350\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_DBA=X.XXXX", "answer": "w_BNB-USD=0.1927, w_DBA=0.8073", "answer_numeric": 0.1927, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000051 - 0.000002) / (0.000205 + 0.000051 - 0.000003)\n Unconstrained: w_BNB-USD=0.1933\n After long-only clamp: w_BNB-USD=0.1933, w_DBA=0.8067.", "metadata": {"weights": {"BNB-USD": 0.1927, "DBA": 0.8073}, "sigma_1": 0.014334, "sigma_2": 0.00711, "covariance": 2e-06, "correlation": 0.0171, "has_text": true, "text_chars": 20, "mu_floor": -0.235, "constraint_binding": false}} +{"id": "T4_all_20230605_0825", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "HYG"], "decision_date": "2023-06-05", "context_summary": "EEM \u03c3=0.0095, HYG \u03c3=0.0046, \u03c1=0.105. Min-variance weights: EEM=0.160, HYG=0.840.", "question": "Assets: EEM, HYG\nEEM: annualized_mean_return=0.0756, daily_std=0.0095\nHYG: annualized_mean_return=0.2016, daily_std=0.0046\nMinimum required portfolio return (annualized): 0.1720\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_HYG=X.XXXX", "answer": "w_EEM=0.1566, w_HYG=0.8434", "answer_numeric": 0.1566, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000021 - 0.000005) / (0.000090 + 0.000021 - 0.000009)\n Unconstrained: w_EEM=0.1597\n After long-only clamp: w_EEM=0.1597, w_HYG=0.8403.", "metadata": {"weights": {"EEM": 0.1566, "HYG": 0.8434}, "sigma_1": 0.009507, "sigma_2": 0.004567, "covariance": 5e-06, "correlation": 0.1048, "has_text": true, "text_chars": 3020, "mu_floor": 0.172, "constraint_binding": false}} +{"id": "T4_all_20240515_0827", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD", "VNQ"], "decision_date": "2024-05-15", "context_summary": "SOL-USD \u03c3=0.0505, VNQ \u03c3=0.0103, \u03c1=0.017. Min-variance weights: SOL-USD=0.037, VNQ=0.963.", "question": "Assets: SOL-USD, VNQ\nSOL-USD: annualized_mean_return=-0.7308, daily_std=0.0505\nVNQ: annualized_mean_return=0.0504, daily_std=0.0103\nMinimum required portfolio return (annualized): -0.1310\nMarket regime: bull\n\nCompute portfolio weights (w_SOL-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_SOL-USD=0.0366, w_VNQ=0.9634", "answer_numeric": 0.0366, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000105 - 0.000009) / (0.002547 + 0.000105 - 0.000018)\n Unconstrained: w_SOL-USD=0.0367\n After long-only clamp: w_SOL-USD=0.0367, w_VNQ=0.9633.", "metadata": {"weights": {"SOL-USD": 0.0366, "VNQ": 0.9634}, "sigma_1": 0.050473, "sigma_2": 0.01027, "covariance": 9e-06, "correlation": 0.0169, "has_text": true, "text_chars": 20, "mu_floor": -0.131, "constraint_binding": false}} +{"id": "T4_all_20230905_0829", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "UNG"], "decision_date": "2023-09-05", "context_summary": "FXI \u03c3=0.0180, UNG \u03c3=0.0304, \u03c1=-0.034. Min-variance weights: FXI=0.733, UNG=0.267.", "question": "Assets: FXI, UNG\nFXI: annualized_mean_return=0.0504, daily_std=0.0180\nUNG: annualized_mean_return=0.6048, daily_std=0.0304\nMinimum required portfolio return (annualized): 0.1857\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_UNG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_UNG=X.XXXX", "answer": "w_FXI=0.7326, w_UNG=0.2674", "answer_numeric": 0.7326, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000922 - -0.000019) / (0.000324 + 0.000922 - -0.000037)\n Unconstrained: w_FXI=0.7327\n After long-only clamp: w_FXI=0.7327, w_UNG=0.2673.", "metadata": {"weights": {"FXI": 0.7326, "UNG": 0.2674}, "sigma_1": 0.018011, "sigma_2": 0.030363, "covariance": -1.9e-05, "correlation": -0.0341, "has_text": true, "text_chars": 3020, "mu_floor": 0.1857, "constraint_binding": false}} +{"id": "T4_all_20230608_0831", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "WEAT"], "decision_date": "2023-06-08", "context_summary": "ETH-USD \u03c3=0.0238, WEAT \u03c3=0.0181, \u03c1=-0.054. Min-variance weights: ETH-USD=0.373, WEAT=0.627.", "question": "Assets: ETH-USD, WEAT\nETH-USD: annualized_mean_return=0.0252, daily_std=0.0238\nWEAT: annualized_mean_return=-0.4032, daily_std=0.0181\nMinimum required portfolio return (annualized): -0.3289\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_WEAT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_WEAT=X.XXXX", "answer": "w_ETH-USD=0.3731, w_WEAT=0.6269", "answer_numeric": 0.3731, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000327 - -0.000023) / (0.000566 + 0.000327 - -0.000047)\n Unconstrained: w_ETH-USD=0.3732\n After long-only clamp: w_ETH-USD=0.3732, w_WEAT=0.6268.", "metadata": {"weights": {"ETH-USD": 0.3731, "WEAT": 0.6269}, "sigma_1": 0.02379, "sigma_2": 0.018096, "covariance": -2.3e-05, "correlation": -0.0544, "has_text": true, "text_chars": 20, "mu_floor": -0.3289, "constraint_binding": false}} +{"id": "T4_all_20230803_0832", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "HAUZ"], "decision_date": "2023-08-03", "context_summary": "MATIC-USD \u03c3=0.0449, HAUZ \u03c3=0.0097, \u03c1=0.110. Min-variance weights: MATIC-USD=0.023, HAUZ=0.977.", "question": "Assets: MATIC-USD, HAUZ\nMATIC-USD: annualized_mean_return=-0.9072, daily_std=0.0449\nHAUZ: annualized_mean_return=-0.1008, daily_std=0.0097\nMinimum required portfolio return (annualized): -0.1102\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_MATIC-USD=0.0117, w_HAUZ=0.9883", "answer_numeric": 0.0117, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000095 - 0.000048) / (0.002018 + 0.000095 - 0.000096)\n Unconstrained: w_MATIC-USD=0.0230\n After long-only clamp: w_MATIC-USD=0.0230, w_HAUZ=0.9770.", "metadata": {"weights": {"MATIC-USD": 0.0117, "HAUZ": 0.9883}, "sigma_1": 0.044924, "sigma_2": 0.009726, "covariance": 4.8e-05, "correlation": 0.1103, "has_text": true, "text_chars": 20, "mu_floor": -0.1102, "constraint_binding": true}} +{"id": "T4_all_20230616_0833", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XHB"], "decision_date": "2023-06-16", "context_summary": "MTUM \u03c3=0.0080, XHB \u03c3=0.0136, \u03c1=0.479. Min-variance weights: MTUM=0.914, XHB=0.086.", "question": "Assets: MTUM, XHB\nMTUM: annualized_mean_return=0.2268, daily_std=0.0080\nXHB: annualized_mean_return=0.6300, daily_std=0.0136\nMinimum required portfolio return (annualized): 0.2416\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_XHB=X.XXXX", "answer": "w_MTUM=0.9130, w_XHB=0.0870", "answer_numeric": 0.913, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000184 - 0.000052) / (0.000065 + 0.000184 - 0.000104)\n Unconstrained: w_MTUM=0.9143\n After long-only clamp: w_MTUM=0.9143, w_XHB=0.0857.", "metadata": {"weights": {"MTUM": 0.913, "XHB": 0.087}, "sigma_1": 0.008035, "sigma_2": 0.013561, "covariance": 5.2e-05, "correlation": 0.4791, "has_text": true, "text_chars": 3020, "mu_floor": 0.2416, "constraint_binding": false}} +{"id": "T4_all_20240424_0834", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "CORN"], "decision_date": "2024-04-24", "context_summary": "IWM \u03c3=0.0130, CORN \u03c3=0.0098, \u03c1=0.148. Min-variance weights: IWM=0.342, CORN=0.658.", "question": "Assets: IWM, CORN\nIWM: annualized_mean_return=0.0756, daily_std=0.0130\nCORN: annualized_mean_return=0.0000, daily_std=0.0098\nMinimum required portfolio return (annualized): 0.0472\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_CORN) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_CORN=X.XXXX", "answer": "w_IWM=0.6243, w_CORN=0.3757", "answer_numeric": 0.6243, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000096 - 0.000019) / (0.000168 + 0.000096 - 0.000038)\n Unconstrained: w_IWM=0.3416\n After long-only clamp: w_IWM=0.3416, w_CORN=0.6584.", "metadata": {"weights": {"IWM": 0.6243, "CORN": 0.3757}, "sigma_1": 0.012973, "sigma_2": 0.009818, "covariance": 1.9e-05, "correlation": 0.1479, "has_text": true, "text_chars": 9045, "mu_floor": 0.0472, "constraint_binding": true}} +{"id": "T4_all_20240521_0836", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD", "DBA"], "decision_date": "2024-05-21", "context_summary": "ADA-USD \u03c3=0.0371, DBA \u03c3=0.0121, \u03c1=-0.040. Min-variance weights: ADA-USD=0.105, DBA=0.895.", "question": "Assets: ADA-USD, DBA\nADA-USD: annualized_mean_return=-0.7812, daily_std=0.0371\nDBA: annualized_mean_return=0.4788, daily_std=0.0121\nMinimum required portfolio return (annualized): 0.4159\nMarket regime: bull\n\nCompute portfolio weights (w_ADA-USD, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_DBA=X.XXXX", "answer": "w_ADA-USD=0.0499, w_DBA=0.9501", "answer_numeric": 0.0499, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000147 - -0.000018) / (0.001380 + 0.000147 - -0.000036)\n Unconstrained: w_ADA-USD=0.1053\n After long-only clamp: w_ADA-USD=0.1053, w_DBA=0.8947.", "metadata": {"weights": {"ADA-USD": 0.0499, "DBA": 0.9501}, "sigma_1": 0.037149, "sigma_2": 0.012106, "covariance": -1.8e-05, "correlation": -0.0398, "has_text": true, "text_chars": 20, "mu_floor": 0.4159, "constraint_binding": true}} +{"id": "T4_all_20230516_0838", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "STIP"], "decision_date": "2023-05-16", "context_summary": "BNB-USD \u03c3=0.0200, STIP \u03c3=0.0021, \u03c1=0.155. Min-variance weights: BNB-USD=0.000, STIP=1.000.", "question": "Assets: BNB-USD, STIP\nBNB-USD: annualized_mean_return=-0.1512, daily_std=0.0200\nSTIP: annualized_mean_return=0.0756, daily_std=0.0021\nMinimum required portfolio return (annualized): -0.0257\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_STIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_STIP=X.XXXX", "answer": "w_BNB-USD=0.0000, w_STIP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000005 - 0.000007) / (0.000400 + 0.000005 - 0.000013)\n Unconstrained: w_BNB-USD=-0.0053\n After long-only clamp: w_BNB-USD=0.0000, w_STIP=1.0000.", "metadata": {"weights": {"BNB-USD": 0.0, "STIP": 1.0}, "sigma_1": 0.020007, "sigma_2": 0.002127, "covariance": 7e-06, "correlation": 0.1554, "has_text": true, "text_chars": 20, "mu_floor": -0.0257, "constraint_binding": false}} +{"id": "T4_all_20230509_0840", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "JNK"], "decision_date": "2023-05-09", "context_summary": "XLK \u03c3=0.0121, JNK \u03c3=0.0054, \u03c1=-0.001. Min-variance weights: XLK=0.165, JNK=0.835.", "question": "Assets: XLK, JNK\nXLK: annualized_mean_return=0.3024, daily_std=0.0121\nJNK: annualized_mean_return=0.1008, daily_std=0.0054\nMinimum required portfolio return (annualized): 0.1912\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_JNK) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_JNK=X.XXXX", "answer": "w_XLK=0.4484, w_JNK=0.5516", "answer_numeric": 0.4484, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000029 - -0.000000) / (0.000147 + 0.000029 - -0.000000)\n Unconstrained: w_XLK=0.1646\n After long-only clamp: w_XLK=0.1646, w_JNK=0.8354.", "metadata": {"weights": {"XLK": 0.4484, "JNK": 0.5516}, "sigma_1": 0.012114, "sigma_2": 0.005373, "covariance": -0.0, "correlation": -0.0009, "has_text": true, "text_chars": 3020, "mu_floor": 0.1912, "constraint_binding": true}} +{"id": "T4_all_20240122_0841", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ICSH"], "decision_date": "2024-01-22", "context_summary": "IVV \u03c3=0.0071, ICSH \u03c3=0.0003, \u03c1=-0.111. Min-variance weights: IVV=0.007, ICSH=0.993.", "question": "Assets: IVV, ICSH\nIVV: annualized_mean_return=0.6048, daily_std=0.0071\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0764\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_ICSH=X.XXXX", "answer": "w_IVV=0.0019, w_ICSH=0.9981", "answer_numeric": 0.0019, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000051 + 0.000000 - -0.000000)\n Unconstrained: w_IVV=0.0068\n After long-only clamp: w_IVV=0.0068, w_ICSH=0.9932.", "metadata": {"weights": {"IVV": 0.0019, "ICSH": 0.9981}, "sigma_1": 0.00711, "sigma_2": 0.000314, "covariance": -0.0, "correlation": -0.1107, "has_text": true, "text_chars": 3020, "mu_floor": 0.0764, "constraint_binding": false}} +{"id": "T4_all_20240829_0843", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD", "BIL"], "decision_date": "2024-08-29", "context_summary": "ETH-USD \u03c3=0.0389, BIL \u03c3=0.0002, \u03c1=-0.006. Min-variance weights: ETH-USD=0.000, BIL=1.000.", "question": "Assets: ETH-USD, BIL\nETH-USD: annualized_mean_return=-1.0080, daily_std=0.0389\nBIL: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.1064\nMarket regime: bull\n\nCompute portfolio weights (w_ETH-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_ETH-USD=0.0000, w_BIL=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.001516 + 0.000000 - -0.000000)\n Unconstrained: w_ETH-USD=0.0000\n After long-only clamp: w_ETH-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.03894, "sigma_2": 0.000172, "covariance": -0.0, "correlation": -0.0057, "has_text": true, "text_chars": 20, "mu_floor": -0.1064, "constraint_binding": false}} +{"id": "T4_all_20230207_0845", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "PPLT"], "decision_date": "2023-02-07", "context_summary": "DOT-USD \u03c3=0.0349, PPLT \u03c3=0.0169, \u03c1=-0.042. Min-variance weights: DOT-USD=0.200, PPLT=0.800.", "question": "Assets: DOT-USD, PPLT\nDOT-USD: annualized_mean_return=0.9072, daily_std=0.0349\nPPLT: annualized_mean_return=-0.1764, daily_std=0.0169\nMinimum required portfolio return (annualized): -0.0110\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_PPLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_PPLT=X.XXXX", "answer": "w_DOT-USD=0.2001, w_PPLT=0.7999", "answer_numeric": 0.2001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000286 - -0.000025) / (0.001219 + 0.000286 - -0.000049)\n Unconstrained: w_DOT-USD=0.2000\n After long-only clamp: w_DOT-USD=0.2000, w_PPLT=0.8000.", "metadata": {"weights": {"DOT-USD": 0.2001, "PPLT": 0.7999}, "sigma_1": 0.034912, "sigma_2": 0.016919, "covariance": -2.5e-05, "correlation": -0.0418, "has_text": true, "text_chars": 20, "mu_floor": -0.011, "constraint_binding": false}} +{"id": "T4_all_20230906_0846", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "HYG"], "decision_date": "2023-09-06", "context_summary": "IVV \u03c3=0.0065, HYG \u03c3=0.0039, \u03c1=-0.022. Min-variance weights: IVV=0.269, HYG=0.731.", "question": "Assets: IVV, HYG\nIVV: annualized_mean_return=0.2016, daily_std=0.0065\nHYG: annualized_mean_return=0.0504, daily_std=0.0039\nMinimum required portfolio return (annualized): 0.1329\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_HYG=X.XXXX", "answer": "w_IVV=0.5456, w_HYG=0.4544", "answer_numeric": 0.5456, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000015 - -0.000001) / (0.000043 + 0.000015 - -0.000001)\n Unconstrained: w_IVV=0.2690\n After long-only clamp: w_IVV=0.2690, w_HYG=0.7310.", "metadata": {"weights": {"IVV": 0.5456, "HYG": 0.4544}, "sigma_1": 0.006524, "sigma_2": 0.003912, "covariance": -1e-06, "correlation": -0.0221, "has_text": true, "text_chars": 3020, "mu_floor": 0.1329, "constraint_binding": true}} +{"id": "T4_all_20231012_0848", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "TIP"], "decision_date": "2023-10-12", "context_summary": "XLRE \u03c3=0.0102, TIP \u03c3=0.0015, \u03c1=0.100. Min-variance weights: XLRE=0.006, TIP=0.994.", "question": "Assets: XLRE, TIP\nXLRE: annualized_mean_return=-0.3528, daily_std=0.0102\nTIP: annualized_mean_return=0.0000, daily_std=0.0015\nMinimum required portfolio return (annualized): -0.0021\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_TIP=X.XXXX", "answer": "w_XLRE=0.0060, w_TIP=0.9940", "answer_numeric": 0.006, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000002 - 0.000001) / (0.000103 + 0.000002 - 0.000003)\n Unconstrained: w_XLRE=0.0065\n After long-only clamp: w_XLRE=0.0065, w_TIP=0.9935.", "metadata": {"weights": {"XLRE": 0.006, "TIP": 0.994}, "sigma_1": 0.010152, "sigma_2": 0.001469, "covariance": 1e-06, "correlation": 0.1001, "has_text": true, "text_chars": 3020, "mu_floor": -0.0021, "constraint_binding": true}} +{"id": "T4_all_20230823_0850", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "HYG"], "decision_date": "2023-08-23", "context_summary": "LINK-USD \u03c3=0.0410, HYG \u03c3=0.0038, \u03c1=-0.241. Min-variance weights: LINK-USD=0.029, HYG=0.971.", "question": "Assets: LINK-USD, HYG\nLINK-USD: annualized_mean_return=0.1512, daily_std=0.0410\nHYG: annualized_mean_return=0.0252, daily_std=0.0038\nMinimum required portfolio return (annualized): 0.1122\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_HYG=X.XXXX", "answer": "w_LINK-USD=0.6905, w_HYG=0.3095", "answer_numeric": 0.6905, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000014 - -0.000037) / (0.001680 + 0.000014 - -0.000074)\n Unconstrained: w_LINK-USD=0.0290\n After long-only clamp: w_LINK-USD=0.0290, w_HYG=0.9710.", "metadata": {"weights": {"LINK-USD": 0.6905, "HYG": 0.3095}, "sigma_1": 0.040988, "sigma_2": 0.003765, "covariance": -3.7e-05, "correlation": -0.2409, "has_text": true, "text_chars": 20, "mu_floor": 0.1122, "constraint_binding": true}} +{"id": "T4_all_20231020_0852", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD"], "decision_date": "2023-10-20", "context_summary": "EEM \u03c3=0.0093, BTC-USD \u03c3=0.0167, \u03c1=-0.051. Min-variance weights: EEM=0.754, BTC-USD=0.246.", "question": "Assets: EEM, BTC-USD\nEEM: annualized_mean_return=-0.4536, daily_std=0.0093\nBTC-USD: annualized_mean_return=0.4284, daily_std=0.0167\nMinimum required portfolio return (annualized): -0.0374\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_BTC-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_BTC-USD=X.XXXX", "answer": "w_EEM=0.5281, w_BTC-USD=0.4719", "answer_numeric": 0.5281, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000279 - -0.000008) / (0.000086 + 0.000279 - -0.000016)\n Unconstrained: w_EEM=0.7537\n After long-only clamp: w_EEM=0.7537, w_BTC-USD=0.2463.", "metadata": {"weights": {"EEM": 0.5281, "BTC-USD": 0.4719}, "sigma_1": 0.009269, "sigma_2": 0.016704, "covariance": -8e-06, "correlation": -0.0506, "has_text": true, "text_chars": 3020, "mu_floor": -0.0374, "constraint_binding": true}} +{"id": "T4_all_20240909_0854", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SCHH"], "decision_date": "2024-09-09", "context_summary": "ETH-USD \u03c3=0.0387, SCHH \u03c3=0.0087, \u03c1=-0.121. Min-variance weights: ETH-USD=0.070, SCHH=0.930.", "question": "Assets: ETH-USD, SCHH\nETH-USD: annualized_mean_return=-1.0836, daily_std=0.0387\nSCHH: annualized_mean_return=0.6300, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.5438\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_SCHH=X.XXXX", "answer": "w_ETH-USD=0.0503, w_SCHH=0.9497", "answer_numeric": 0.0503, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000075 - -0.000041) / (0.001501 + 0.000075 - -0.000082)\n Unconstrained: w_ETH-USD=0.0699\n After long-only clamp: w_ETH-USD=0.0699, w_SCHH=0.9301.", "metadata": {"weights": {"ETH-USD": 0.0503, "SCHH": 0.9497}, "sigma_1": 0.038744, "sigma_2": 0.008662, "covariance": -4.1e-05, "correlation": -0.1215, "has_text": true, "text_chars": 20, "mu_floor": 0.5438, "constraint_binding": true}} +{"id": "T4_all_20240301_0856", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ICSH"], "decision_date": "2024-03-01", "context_summary": "XLU \u03c3=0.0108, ICSH \u03c3=0.0003, \u03c1=0.008. Min-variance weights: XLU=0.001, ICSH=0.999.", "question": "Assets: XLU, ICSH\nXLU: annualized_mean_return=-0.1008, daily_std=0.0108\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0503\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLU=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLU=0.0007, w_ICSH=0.9993", "answer_numeric": 0.0007, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000117 + 0.000000 - 0.000000)\n Unconstrained: w_XLU=0.0006\n After long-only clamp: w_XLU=0.0006, w_ICSH=0.9994.", "metadata": {"weights": {"XLU": 0.0007, "ICSH": 0.9993}, "sigma_1": 0.01083, "sigma_2": 0.000314, "covariance": 0.0, "correlation": 0.0083, "has_text": true, "text_chars": 9045, "mu_floor": 0.0503, "constraint_binding": true}} +{"id": "T4_all_20230706_0857", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "JNK"], "decision_date": "2023-07-06", "context_summary": "ETH-USD \u03c3=0.0204, JNK \u03c3=0.0036, \u03c1=0.201. Min-variance weights: ETH-USD=0.000, JNK=1.000.", "question": "Assets: ETH-USD, JNK\nETH-USD: annualized_mean_return=0.0756, daily_std=0.0204\nJNK: annualized_mean_return=0.0252, daily_std=0.0036\nMinimum required portfolio return (annualized): 0.0252\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_JNK) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_JNK=X.XXXX", "answer": "w_ETH-USD=0.0000, w_JNK=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000013 - 0.000015) / (0.000415 + 0.000013 - 0.000030)\n Unconstrained: w_ETH-USD=-0.0045\n After long-only clamp: w_ETH-USD=0.0000, w_JNK=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "JNK": 1.0}, "sigma_1": 0.020363, "sigma_2": 0.003604, "covariance": 1.5e-05, "correlation": 0.2012, "has_text": true, "text_chars": 20, "mu_floor": 0.0252, "constraint_binding": false}} +{"id": "T4_all_20231017_0858", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "INDS"], "decision_date": "2023-10-17", "context_summary": "BNB-USD \u03c3=0.0132, INDS \u03c3=0.0109, \u03c1=-0.091. Min-variance weights: BNB-USD=0.411, INDS=0.589.", "question": "Assets: BNB-USD, INDS\nBNB-USD: annualized_mean_return=-0.0504, daily_std=0.0132\nINDS: annualized_mean_return=-0.4788, daily_std=0.0109\nMinimum required portfolio return (annualized): -0.1808\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_INDS=X.XXXX", "answer": "w_BNB-USD=0.6956, w_INDS=0.3044", "answer_numeric": 0.6956, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000118 - -0.000013) / (0.000175 + 0.000118 - -0.000026)\n Unconstrained: w_BNB-USD=0.4115\n After long-only clamp: w_BNB-USD=0.4115, w_INDS=0.5885.", "metadata": {"weights": {"BNB-USD": 0.6956, "INDS": 0.3044}, "sigma_1": 0.013212, "sigma_2": 0.010868, "covariance": -1.3e-05, "correlation": -0.091, "has_text": true, "text_chars": 20, "mu_floor": -0.1808, "constraint_binding": true}} +{"id": "T4_all_20241106_0859", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "BIL"], "decision_date": "2024-11-06", "context_summary": "SOL-USD \u03c3=0.0304, BIL \u03c3=0.0002, \u03c1=-0.110. Min-variance weights: SOL-USD=0.001, BIL=0.999.", "question": "Assets: SOL-USD, BIL\nSOL-USD: annualized_mean_return=1.3356, daily_std=0.0304\nBIL: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0767\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_BIL=X.XXXX", "answer": "w_SOL-USD=0.0011, w_BIL=0.9989", "answer_numeric": 0.0011, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000924 + 0.000000 - -0.000001)\n Unconstrained: w_SOL-USD=0.0007\n After long-only clamp: w_SOL-USD=0.0007, w_BIL=0.9993.", "metadata": {"weights": {"SOL-USD": 0.0011, "BIL": 0.9989}, "sigma_1": 0.030405, "sigma_2": 0.000179, "covariance": -1e-06, "correlation": -0.1099, "has_text": true, "text_chars": 20, "mu_floor": 0.0767, "constraint_binding": false}} +{"id": "T4_all_20240506_0860", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SGOV"], "decision_date": "2024-05-06", "context_summary": "VEA \u03c3=0.0073, SGOV \u03c3=0.0001, \u03c1=-0.036. Min-variance weights: VEA=0.001, SGOV=0.999.", "question": "Assets: VEA, SGOV\nVEA: annualized_mean_return=0.2016, daily_std=0.0073\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0888\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_SGOV=X.XXXX", "answer": "w_VEA=0.2540, w_SGOV=0.7460", "answer_numeric": 0.254, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000053 + 0.000000 - -0.000000)\n Unconstrained: w_VEA=0.0009\n After long-only clamp: w_VEA=0.0009, w_SGOV=0.9991.", "metadata": {"weights": {"VEA": 0.254, "SGOV": 0.746}, "sigma_1": 0.007256, "sigma_2": 0.000124, "covariance": -0.0, "correlation": -0.0364, "has_text": true, "text_chars": 9045, "mu_floor": 0.0888, "constraint_binding": true}} +{"id": "T4_all_20230519_0861", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "ITB"], "decision_date": "2023-05-19", "context_summary": "SOL-USD \u03c3=0.0332, ITB \u03c3=0.0118, \u03c1=0.106. Min-variance weights: SOL-USD=0.084, ITB=0.916.", "question": "Assets: SOL-USD, ITB\nSOL-USD: annualized_mean_return=-0.1764, daily_std=0.0332\nITB: annualized_mean_return=0.6804, daily_std=0.0118\nMinimum required portfolio return (annualized): 0.4445\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_ITB=X.XXXX", "answer": "w_SOL-USD=0.0835, w_ITB=0.9165", "answer_numeric": 0.0835, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000139 - 0.000042) / (0.001103 + 0.000139 - 0.000083)\n Unconstrained: w_SOL-USD=0.0839\n After long-only clamp: w_SOL-USD=0.0839, w_ITB=0.9161.", "metadata": {"weights": {"SOL-USD": 0.0835, "ITB": 0.9165}, "sigma_1": 0.033213, "sigma_2": 0.011778, "covariance": 4.2e-05, "correlation": 0.1061, "has_text": true, "text_chars": 20, "mu_floor": 0.4445, "constraint_binding": false}} +{"id": "T4_all_20231018_0863", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "SHY"], "decision_date": "2023-10-18", "context_summary": "BTC-USD \u03c3=0.0166, SHY \u03c3=0.0010, \u03c1=-0.038. Min-variance weights: BTC-USD=0.006, SHY=0.994.", "question": "Assets: BTC-USD, SHY\nBTC-USD: annualized_mean_return=0.4032, daily_std=0.0166\nSHY: annualized_mean_return=0.0000, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.0020\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_BTC-USD=0.0074, w_SHY=0.9926", "answer_numeric": 0.0074, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000001) / (0.000276 + 0.000001 - -0.000001)\n Unconstrained: w_BTC-USD=0.0062\n After long-only clamp: w_BTC-USD=0.0062, w_SHY=0.9938.", "metadata": {"weights": {"BTC-USD": 0.0074, "SHY": 0.9926}, "sigma_1": 0.01662, "sigma_2": 0.001035, "covariance": -1e-06, "correlation": -0.0379, "has_text": true, "text_chars": 20, "mu_floor": 0.002, "constraint_binding": false}} +{"id": "T4_all_20241001_0865", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "ICSH"], "decision_date": "2024-10-01", "context_summary": "AVAX-USD \u03c3=0.0457, ICSH \u03c3=0.0003, \u03c1=-0.193. Min-variance weights: AVAX-USD=0.001, ICSH=0.999.", "question": "Assets: AVAX-USD, ICSH\nAVAX-USD: annualized_mean_return=0.5796, daily_std=0.0457\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0763\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_AVAX-USD=0.0015, w_ICSH=0.9985", "answer_numeric": 0.0015, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000003) / (0.002092 + 0.000000 - -0.000005)\n Unconstrained: w_AVAX-USD=0.0013\n After long-only clamp: w_AVAX-USD=0.0013, w_ICSH=0.9987.", "metadata": {"weights": {"AVAX-USD": 0.0015, "ICSH": 0.9985}, "sigma_1": 0.045737, "sigma_2": 0.000298, "covariance": -3e-06, "correlation": -0.1934, "has_text": true, "text_chars": 20, "mu_floor": 0.0763, "constraint_binding": false}} +{"id": "T4_all_20230529_0866", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "SLV"], "decision_date": "2023-05-29", "context_summary": "LINK-USD \u03c3=0.0265, SLV \u03c3=0.0163, \u03c1=-0.137. Min-variance weights: LINK-USD=0.299, SLV=0.701.", "question": "Assets: LINK-USD, SLV\nLINK-USD: annualized_mean_return=-0.3528, daily_std=0.0265\nSLV: annualized_mean_return=0.4032, daily_std=0.0163\nMinimum required portfolio return (annualized): 0.3553\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_SLV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_SLV=X.XXXX", "answer": "w_LINK-USD=0.0634, w_SLV=0.9366", "answer_numeric": 0.0634, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000266 - -0.000059) / (0.000705 + 0.000266 - -0.000118)\n Unconstrained: w_LINK-USD=0.2988\n After long-only clamp: w_LINK-USD=0.2988, w_SLV=0.7012.", "metadata": {"weights": {"LINK-USD": 0.0634, "SLV": 0.9366}, "sigma_1": 0.026543, "sigma_2": 0.016314, "covariance": -5.9e-05, "correlation": -0.1368, "has_text": true, "text_chars": 20, "mu_floor": 0.3553, "constraint_binding": true}} +{"id": "T4_all_20240627_0867", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "DBB"], "decision_date": "2024-06-27", "context_summary": "EEM \u03c3=0.0084, DBB \u03c3=0.0115, \u03c1=-0.190. Min-variance weights: EEM=0.629, DBB=0.371.", "question": "Assets: EEM, DBB\nEEM: annualized_mean_return=0.1512, daily_std=0.0084\nDBB: annualized_mean_return=0.3024, daily_std=0.0115\nMinimum required portfolio return (annualized): 0.1853\nMarket regime: bull\n\nCompute portfolio weights (w_EEM, w_DBB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_DBB=X.XXXX", "answer": "w_EEM=0.6293, w_DBB=0.3707", "answer_numeric": 0.6293, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000131 - -0.000018) / (0.000070 + 0.000131 - -0.000036)\n Unconstrained: w_EEM=0.6290\n After long-only clamp: w_EEM=0.6290, w_DBB=0.3710.", "metadata": {"weights": {"EEM": 0.6293, "DBB": 0.3707}, "sigma_1": 0.008366, "sigma_2": 0.011461, "covariance": -1.8e-05, "correlation": -0.1898, "has_text": true, "text_chars": 9045, "mu_floor": 0.1853, "constraint_binding": false}} +{"id": "T4_all_20230308_0869", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "MORT"], "decision_date": "2023-03-08", "context_summary": "QQQ \u03c3=0.0148, MORT \u03c3=0.0149, \u03c1=0.718. Min-variance weights: QQQ=0.509, MORT=0.491.", "question": "Assets: QQQ, MORT\nQQQ: annualized_mean_return=0.2268, daily_std=0.0148\nMORT: annualized_mean_return=0.0252, daily_std=0.0149\nMinimum required portfolio return (annualized): 0.1258\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QQQ=X.XXXX, w_MORT=X.XXXX", "answer": "w_QQQ=0.5088, w_MORT=0.4912", "answer_numeric": 0.5088, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000222 - 0.000158) / (0.000220 + 0.000222 - 0.000317)\n Unconstrained: w_QQQ=0.5089\n After long-only clamp: w_QQQ=0.5089, w_MORT=0.4911.", "metadata": {"weights": {"QQQ": 0.5088, "MORT": 0.4912}, "sigma_1": 0.014817, "sigma_2": 0.014891, "covariance": 0.000158, "correlation": 0.7183, "has_text": true, "text_chars": 3020, "mu_floor": 0.1258, "constraint_binding": false}} +{"id": "T4_all_20230125_0871", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LQD"], "decision_date": "2023-01-25", "context_summary": "XLE \u03c3=0.0171, LQD \u03c3=0.0069, \u03c1=0.123. Min-variance weights: XLE=0.108, LQD=0.891.", "question": "Assets: XLE, LQD\nXLE: annualized_mean_return=0.1260, daily_std=0.0171\nLQD: annualized_mean_return=0.3276, daily_std=0.0069\nMinimum required portfolio return (annualized): 0.2173\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLE=X.XXXX, w_LQD=X.XXXX", "answer": "w_XLE=0.1073, w_LQD=0.8927", "answer_numeric": 0.1073, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000048 - 0.000015) / (0.000291 + 0.000048 - 0.000029)\n Unconstrained: w_XLE=0.1085\n After long-only clamp: w_XLE=0.1085, w_LQD=0.8915.", "metadata": {"weights": {"XLE": 0.1073, "LQD": 0.8927}, "sigma_1": 0.017071, "sigma_2": 0.006944, "covariance": 1.5e-05, "correlation": 0.1226, "has_text": true, "text_chars": 3020, "mu_floor": 0.2173, "constraint_binding": false}} +{"id": "T4_all_20240524_0872", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "ICSH"], "decision_date": "2024-05-24", "context_summary": "EEM \u03c3=0.0078, ICSH \u03c3=0.0002, \u03c1=0.161. Min-variance weights: EEM=0.000, ICSH=1.000.", "question": "Assets: EEM, ICSH\nEEM: annualized_mean_return=0.3024, daily_std=0.0078\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.1014\nMarket regime: bull\n\nCompute portfolio weights (w_EEM, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_ICSH=X.XXXX", "answer": "w_EEM=0.2024, w_ICSH=0.7976", "answer_numeric": 0.2024, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000061 + 0.000000 - 0.000001)\n Unconstrained: w_EEM=-0.0035\n After long-only clamp: w_EEM=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"EEM": 0.2024, "ICSH": 0.7976}, "sigma_1": 0.00784, "sigma_2": 0.000204, "covariance": 0.0, "correlation": 0.1607, "has_text": true, "text_chars": 9045, "mu_floor": 0.1014, "constraint_binding": true}} +{"id": "T4_all_20240729_0874", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "DBA"], "decision_date": "2024-07-29", "context_summary": "LINK-USD \u03c3=0.0364, DBA \u03c3=0.0110, \u03c1=0.059. Min-variance weights: LINK-USD=0.070, DBA=0.930.", "question": "Assets: LINK-USD, DBA\nLINK-USD: annualized_mean_return=-1.2096, daily_std=0.0364\nDBA: annualized_mean_return=0.0756, daily_std=0.0110\nMinimum required portfolio return (annualized): 0.0140\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_DBA) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_DBA=X.XXXX", "answer": "w_LINK-USD=0.0479, w_DBA=0.9521", "answer_numeric": 0.0479, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000122 - 0.000024) / (0.001325 + 0.000122 - 0.000048)\n Unconstrained: w_LINK-USD=0.0701\n After long-only clamp: w_LINK-USD=0.0701, w_DBA=0.9299.", "metadata": {"weights": {"LINK-USD": 0.0479, "DBA": 0.9521}, "sigma_1": 0.036402, "sigma_2": 0.011042, "covariance": 2.4e-05, "correlation": 0.0592, "has_text": true, "text_chars": 20, "mu_floor": 0.014, "constraint_binding": true}} +{"id": "T4_all_20231004_0875", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "CPER"], "decision_date": "2023-10-04", "context_summary": "ADA-USD \u03c3=0.0189, CPER \u03c3=0.0114, \u03c1=-0.234. Min-variance weights: ADA-USD=0.308, CPER=0.692.", "question": "Assets: ADA-USD, CPER\nADA-USD: annualized_mean_return=-0.4536, daily_std=0.0189\nCPER: annualized_mean_return=-0.1764, daily_std=0.0114\nMinimum required portfolio return (annualized): -0.2684\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_CPER) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_CPER=X.XXXX", "answer": "w_ADA-USD=0.3081, w_CPER=0.6919", "answer_numeric": 0.3081, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000131 - -0.000051) / (0.000357 + 0.000131 - -0.000101)\n Unconstrained: w_ADA-USD=0.3078\n After long-only clamp: w_ADA-USD=0.3078, w_CPER=0.6922.", "metadata": {"weights": {"ADA-USD": 0.3081, "CPER": 0.6919}, "sigma_1": 0.018891, "sigma_2": 0.011428, "covariance": -5.1e-05, "correlation": -0.2341, "has_text": true, "text_chars": 20, "mu_floor": -0.2684, "constraint_binding": false}} +{"id": "T4_all_20230901_0876", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "CORN"], "decision_date": "2023-09-01", "context_summary": "LINK-USD \u03c3=0.0402, CORN \u03c3=0.0199, \u03c1=-0.072. Min-variance weights: LINK-USD=0.213, CORN=0.787.", "question": "Assets: LINK-USD, CORN\nLINK-USD: annualized_mean_return=-0.3528, daily_std=0.0402\nCORN: annualized_mean_return=-0.1512, daily_std=0.0199\nMinimum required portfolio return (annualized): -0.1690\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_CORN) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_CORN=X.XXXX", "answer": "w_LINK-USD=0.0883, w_CORN=0.9117", "answer_numeric": 0.0883, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000395 - -0.000057) / (0.001615 + 0.000395 - -0.000115)\n Unconstrained: w_LINK-USD=0.2129\n After long-only clamp: w_LINK-USD=0.2129, w_CORN=0.7871.", "metadata": {"weights": {"LINK-USD": 0.0883, "CORN": 0.9117}, "sigma_1": 0.040183, "sigma_2": 0.019876, "covariance": -5.7e-05, "correlation": -0.0717, "has_text": true, "text_chars": 20, "mu_floor": -0.169, "constraint_binding": true}} +{"id": "T4_all_20231123_0877", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SGOV"], "decision_date": "2023-11-23", "context_summary": "EEM \u03c3=0.0095, SGOV \u03c3=0.0002, \u03c1=0.119. Min-variance weights: EEM=0.000, SGOV=1.000.", "question": "Assets: EEM, SGOV\nEEM: annualized_mean_return=-0.0252, daily_std=0.0095\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0488\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_SGOV=X.XXXX", "answer": "w_EEM=0.0003, w_SGOV=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000090 + 0.000000 - 0.000000)\n Unconstrained: w_EEM=-0.0017\n After long-only clamp: w_EEM=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"EEM": 0.0003, "SGOV": 0.9997}, "sigma_1": 0.009496, "sigma_2": 0.000157, "covariance": 0.0, "correlation": 0.1195, "has_text": true, "text_chars": 3020, "mu_floor": 0.0488, "constraint_binding": false}} +{"id": "T4_all_20240517_0878", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "DBC"], "decision_date": "2024-05-17", "context_summary": "XLI \u03c3=0.0068, DBC \u03c3=0.0065, \u03c1=0.191. Min-variance weights: XLI=0.472, DBC=0.528.", "question": "Assets: XLI, DBC\nXLI: annualized_mean_return=0.2520, daily_std=0.0068\nDBC: annualized_mean_return=0.2772, daily_std=0.0065\nMinimum required portfolio return (annualized): 0.2685\nMarket regime: bull\n\nCompute portfolio weights (w_XLI, w_DBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_DBC=X.XXXX", "answer": "w_XLI=0.3452, w_DBC=0.6548", "answer_numeric": 0.3452, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000042 - 0.000008) / (0.000046 + 0.000042 - 0.000017)\n Unconstrained: w_XLI=0.4723\n After long-only clamp: w_XLI=0.4723, w_DBC=0.5277.", "metadata": {"weights": {"XLI": 0.3452, "DBC": 0.6548}, "sigma_1": 0.006752, "sigma_2": 0.006456, "covariance": 8e-06, "correlation": 0.1911, "has_text": true, "text_chars": 9045, "mu_floor": 0.2685, "constraint_binding": true}} +{"id": "T4_all_20230705_0879", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "CORN"], "decision_date": "2023-07-05", "context_summary": "XLK \u03c3=0.0117, CORN \u03c3=0.0179, \u03c1=0.149. Min-variance weights: XLK=0.734, CORN=0.266.", "question": "Assets: XLK, CORN\nXLK: annualized_mean_return=0.6804, daily_std=0.0117\nCORN: annualized_mean_return=-0.1008, daily_std=0.0179\nMinimum required portfolio return (annualized): 0.3093\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_CORN) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_CORN=X.XXXX", "answer": "w_XLK=0.7336, w_CORN=0.2664", "answer_numeric": 0.7336, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000322 - 0.000031) / (0.000137 + 0.000322 - 0.000062)\n Unconstrained: w_XLK=0.7338\n After long-only clamp: w_XLK=0.7338, w_CORN=0.2662.", "metadata": {"weights": {"XLK": 0.7336, "CORN": 0.2664}, "sigma_1": 0.011685, "sigma_2": 0.017933, "covariance": 3.1e-05, "correlation": 0.1489, "has_text": true, "text_chars": 3020, "mu_floor": 0.3093, "constraint_binding": false}} +{"id": "T4_all_20231225_0881", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "TLT"], "decision_date": "2023-12-25", "context_summary": "XLY \u03c3=0.0120, TLT \u03c3=0.0135, \u03c1=-0.006. Min-variance weights: XLY=0.560, TLT=0.440.", "question": "Assets: XLY, TLT\nXLY: annualized_mean_return=0.4788, daily_std=0.0120\nTLT: annualized_mean_return=0.5544, daily_std=0.0135\nMinimum required portfolio return (annualized): 0.5096\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_TLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_TLT=X.XXXX", "answer": "w_XLY=0.5597, w_TLT=0.4403", "answer_numeric": 0.5597, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000183 - -0.000001) / (0.000144 + 0.000183 - -0.000002)\n Unconstrained: w_XLY=0.5597\n After long-only clamp: w_XLY=0.5597, w_TLT=0.4403.", "metadata": {"weights": {"XLY": 0.5597, "TLT": 0.4403}, "sigma_1": 0.011981, "sigma_2": 0.013519, "covariance": -1e-06, "correlation": -0.0064, "has_text": true, "text_chars": 3020, "mu_floor": 0.5096, "constraint_binding": false}} +{"id": "T4_all_20240117_0883", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "STIP"], "decision_date": "2024-01-17", "context_summary": "MTUM \u03c3=0.0089, STIP \u03c3=0.0016, \u03c1=0.133. Min-variance weights: MTUM=0.009, STIP=0.991.", "question": "Assets: MTUM, STIP\nMTUM: annualized_mean_return=0.5544, daily_std=0.0089\nSTIP: annualized_mean_return=0.1008, daily_std=0.0016\nMinimum required portfolio return (annualized): 0.1033\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_STIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_STIP=X.XXXX", "answer": "w_MTUM=0.0075, w_STIP=0.9925", "answer_numeric": 0.0075, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000003 - 0.000002) / (0.000079 + 0.000003 - 0.000004)\n Unconstrained: w_MTUM=0.0088\n After long-only clamp: w_MTUM=0.0088, w_STIP=0.9912.", "metadata": {"weights": {"MTUM": 0.0075, "STIP": 0.9925}, "sigma_1": 0.008873, "sigma_2": 0.001606, "covariance": 2e-06, "correlation": 0.1331, "has_text": true, "text_chars": 3020, "mu_floor": 0.1033, "constraint_binding": false}} +{"id": "T4_all_20240529_0884", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "XLE"], "decision_date": "2024-05-29", "context_summary": "BTC-USD \u03c3=0.0285, XLE \u03c3=0.0089, \u03c1=0.109. Min-variance weights: BTC-USD=0.062, XLE=0.938.", "question": "Assets: BTC-USD, XLE\nBTC-USD: annualized_mean_return=0.0000, daily_std=0.0285\nXLE: annualized_mean_return=0.2772, daily_std=0.0089\nMinimum required portfolio return (annualized): 0.2678\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_XLE) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_XLE=X.XXXX", "answer": "w_BTC-USD=0.0339, w_XLE=0.9661", "answer_numeric": 0.0339, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000080 - 0.000028) / (0.000812 + 0.000080 - 0.000055)\n Unconstrained: w_BTC-USD=0.0624\n After long-only clamp: w_BTC-USD=0.0624, w_XLE=0.9376.", "metadata": {"weights": {"BTC-USD": 0.0339, "XLE": 0.9661}, "sigma_1": 0.028496, "sigma_2": 0.008941, "covariance": 2.8e-05, "correlation": 0.1089, "has_text": true, "text_chars": 20, "mu_floor": 0.2678, "constraint_binding": true}} +{"id": "T4_all_20230327_0886", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "REZ"], "decision_date": "2023-03-27", "context_summary": "QUAL \u03c3=0.0113, REZ \u03c3=0.0149, \u03c1=0.766. Min-variance weights: QUAL=1.000, REZ=0.000.", "question": "Assets: QUAL, REZ\nQUAL: annualized_mean_return=0.2268, daily_std=0.0113\nREZ: annualized_mean_return=-0.0504, daily_std=0.0149\nMinimum required portfolio return (annualized): 0.0717\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_REZ=X.XXXX", "answer": "w_QUAL=1.0000, w_REZ=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000222 - 0.000129) / (0.000129 + 0.000222 - 0.000259)\n Unconstrained: w_QUAL=1.0083\n After long-only clamp: w_QUAL=1.0000, w_REZ=0.0000.", "metadata": {"weights": {"QUAL": 1.0, "REZ": 0.0}, "sigma_1": 0.011345, "sigma_2": 0.014889, "covariance": 0.000129, "correlation": 0.7665, "has_text": true, "text_chars": 3020, "mu_floor": 0.0717, "constraint_binding": false}} +{"id": "T4_all_20230830_0888", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "INDS"], "decision_date": "2023-08-30", "context_summary": "ADA-USD \u03c3=0.0368, INDS \u03c3=0.0102, \u03c1=-0.188. Min-variance weights: ADA-USD=0.109, INDS=0.891.", "question": "Assets: ADA-USD, INDS\nADA-USD: annualized_mean_return=-0.1260, daily_std=0.0368\nINDS: annualized_mean_return=-0.1008, daily_std=0.0102\nMinimum required portfolio return (annualized): -0.1030\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_INDS=X.XXXX", "answer": "w_ADA-USD=0.0873, w_INDS=0.9127", "answer_numeric": 0.0873, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000104 - -0.000071) / (0.001353 + 0.000104 - -0.000141)\n Unconstrained: w_ADA-USD=0.1092\n After long-only clamp: w_ADA-USD=0.1092, w_INDS=0.8908.", "metadata": {"weights": {"ADA-USD": 0.0873, "INDS": 0.9127}, "sigma_1": 0.036783, "sigma_2": 0.010192, "covariance": -7.1e-05, "correlation": -0.1883, "has_text": true, "text_chars": 20, "mu_floor": -0.103, "constraint_binding": true}} +{"id": "T4_all_20230112_0890", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "XHB"], "decision_date": "2023-01-12", "context_summary": "FXI \u03c3=0.0259, XHB \u03c3=0.0185, \u03c1=0.370. Min-variance weights: FXI=0.249, XHB=0.750.", "question": "Assets: FXI, XHB\nFXI: annualized_mean_return=1.2852, daily_std=0.0259\nXHB: annualized_mean_return=0.6300, daily_std=0.0185\nMinimum required portfolio return (annualized): 1.1610\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_XHB=X.XXXX", "answer": "w_FXI=0.8104, w_XHB=0.1896", "answer_numeric": 0.8104, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000343 - 0.000178) / (0.000673 + 0.000343 - 0.000356)\n Unconstrained: w_FXI=0.2495\n After long-only clamp: w_FXI=0.2495, w_XHB=0.7505.", "metadata": {"weights": {"FXI": 0.8104, "XHB": 0.1896}, "sigma_1": 0.025948, "sigma_2": 0.018511, "covariance": 0.000178, "correlation": 0.3705, "has_text": true, "text_chars": 3020, "mu_floor": 1.161, "constraint_binding": true}} +{"id": "T4_all_20240611_0892", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "REZ"], "decision_date": "2024-06-11", "context_summary": "IWM \u03c3=0.0108, REZ \u03c3=0.0107, \u03c1=0.779. Min-variance weights: IWM=0.495, REZ=0.505.", "question": "Assets: IWM, REZ\nIWM: annualized_mean_return=0.0000, daily_std=0.0108\nREZ: annualized_mean_return=0.3024, daily_std=0.0107\nMinimum required portfolio return (annualized): 0.2631\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_REZ=X.XXXX", "answer": "w_IWM=0.1300, w_REZ=0.8700", "answer_numeric": 0.13, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000115 - 0.000090) / (0.000116 + 0.000115 - 0.000180)\n Unconstrained: w_IWM=0.4953\n After long-only clamp: w_IWM=0.4953, w_REZ=0.5047.", "metadata": {"weights": {"IWM": 0.13, "REZ": 0.87}, "sigma_1": 0.010761, "sigma_2": 0.010738, "covariance": 9e-05, "correlation": 0.7792, "has_text": true, "text_chars": 9045, "mu_floor": 0.2631, "constraint_binding": true}} +{"id": "T4_all_20240912_0894", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "IYR"], "decision_date": "2024-09-12", "context_summary": "BNB-USD \u03c3=0.0294, IYR \u03c3=0.0089, \u03c1=0.037. Min-variance weights: BNB-USD=0.076, IYR=0.924.", "question": "Assets: BNB-USD, IYR\nBNB-USD: annualized_mean_return=0.1008, daily_std=0.0294\nIYR: annualized_mean_return=0.6804, daily_std=0.0089\nMinimum required portfolio return (annualized): 0.6702\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_IYR=X.XXXX", "answer": "w_BNB-USD=0.0176, w_IYR=0.9824", "answer_numeric": 0.0176, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000080 - 0.000010) / (0.000862 + 0.000080 - 0.000019)\n Unconstrained: w_BNB-USD=0.0760\n After long-only clamp: w_BNB-USD=0.0760, w_IYR=0.9240.", "metadata": {"weights": {"BNB-USD": 0.0176, "IYR": 0.9824}, "sigma_1": 0.029366, "sigma_2": 0.008935, "covariance": 1e-05, "correlation": 0.0369, "has_text": true, "text_chars": 20, "mu_floor": 0.6702, "constraint_binding": true}} +{"id": "T4_all_20241126_0896", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "DBC"], "decision_date": "2024-11-26", "context_summary": "AVAX-USD \u03c3=0.0493, DBC \u03c3=0.0115, \u03c1=-0.010. Min-variance weights: AVAX-USD=0.054, DBC=0.946.", "question": "Assets: AVAX-USD, DBC\nAVAX-USD: annualized_mean_return=1.7640, daily_std=0.0493\nDBC: annualized_mean_return=0.0504, daily_std=0.0115\nMinimum required portfolio return (annualized): 0.4776\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_DBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_DBC=X.XXXX", "answer": "w_AVAX-USD=0.2493, w_DBC=0.7507", "answer_numeric": 0.2493, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000133 - -0.000005) / (0.002429 + 0.000133 - -0.000011)\n Unconstrained: w_AVAX-USD=0.0539\n After long-only clamp: w_AVAX-USD=0.0539, w_DBC=0.9461.", "metadata": {"weights": {"AVAX-USD": 0.2493, "DBC": 0.7507}, "sigma_1": 0.049282, "sigma_2": 0.011543, "covariance": -5e-06, "correlation": -0.0096, "has_text": true, "text_chars": 20, "mu_floor": 0.4776, "constraint_binding": true}} +{"id": "T4_all_20241128_0897", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "HAUZ"], "decision_date": "2024-11-28", "context_summary": "BTC-USD \u03c3=0.0275, HAUZ \u03c3=0.0092, \u03c1=0.214. Min-variance weights: BTC-USD=0.042, HAUZ=0.958.", "question": "Assets: BTC-USD, HAUZ\nBTC-USD: annualized_mean_return=1.6884, daily_std=0.0275\nHAUZ: annualized_mean_return=-0.1512, daily_std=0.0092\nMinimum required portfolio return (annualized): -0.0926\nMarket regime: bull\n\nCompute portfolio weights (w_BTC-USD, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_BTC-USD=0.0422, w_HAUZ=0.9578", "answer_numeric": 0.0422, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000085 - 0.000054) / (0.000759 + 0.000085 - 0.000109)\n Unconstrained: w_BTC-USD=0.0418\n After long-only clamp: w_BTC-USD=0.0418, w_HAUZ=0.9582.", "metadata": {"weights": {"BTC-USD": 0.0422, "HAUZ": 0.9578}, "sigma_1": 0.027543, "sigma_2": 0.00922, "covariance": 5.4e-05, "correlation": 0.2138, "has_text": true, "text_chars": 20, "mu_floor": -0.0926, "constraint_binding": false}} +{"id": "T4_all_20230103_0899", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "HYG"], "decision_date": "2023-01-03", "context_summary": "BNB-USD \u03c3=0.0425, HYG \u03c3=0.0072, \u03c1=-0.097. Min-variance weights: BNB-USD=0.043, HYG=0.958.", "question": "Assets: BNB-USD, HYG\nBNB-USD: annualized_mean_return=-0.9576, daily_std=0.0425\nHYG: annualized_mean_return=0.1008, daily_std=0.0072\nMinimum required portfolio return (annualized): -0.4052\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_HYG=X.XXXX", "answer": "w_BNB-USD=0.0426, w_HYG=0.9574", "answer_numeric": 0.0426, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000052 - -0.000030) / (0.001809 + 0.000052 - -0.000059)\n Unconstrained: w_BNB-USD=0.0425\n After long-only clamp: w_BNB-USD=0.0425, w_HYG=0.9575.", "metadata": {"weights": {"BNB-USD": 0.0426, "HYG": 0.9574}, "sigma_1": 0.042537, "sigma_2": 0.007205, "covariance": -3e-05, "correlation": -0.0969, "has_text": true, "text_chars": 20, "mu_floor": -0.4052, "constraint_binding": false}} +{"id": "T4_all_20230417_0901", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "HYG"], "decision_date": "2023-04-17", "context_summary": "USMV \u03c3=0.0070, HYG \u03c3=0.0058, \u03c1=0.104. Min-variance weights: USMV=0.397, HYG=0.603.", "question": "Assets: USMV, HYG\nUSMV: annualized_mean_return=0.1008, daily_std=0.0070\nHYG: annualized_mean_return=0.0504, daily_std=0.0058\nMinimum required portfolio return (annualized): 0.0655\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_HYG=X.XXXX", "answer": "w_USMV=0.3981, w_HYG=0.6019", "answer_numeric": 0.3981, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000034 - 0.000004) / (0.000049 + 0.000034 - 0.000009)\n Unconstrained: w_USMV=0.3974\n After long-only clamp: w_USMV=0.3974, w_HYG=0.6026.", "metadata": {"weights": {"USMV": 0.3981, "HYG": 0.6019}, "sigma_1": 0.007014, "sigma_2": 0.005822, "covariance": 4e-06, "correlation": 0.1043, "has_text": true, "text_chars": 3020, "mu_floor": 0.0655, "constraint_binding": false}} +{"id": "T4_all_20241219_0902", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "SCHH"], "decision_date": "2024-12-19", "context_summary": "DOT-USD \u03c3=0.0661, SCHH \u03c3=0.0094, \u03c1=0.057. Min-variance weights: DOT-USD=0.012, SCHH=0.988.", "question": "Assets: DOT-USD, SCHH\nDOT-USD: annualized_mean_return=2.8476, daily_std=0.0661\nSCHH: annualized_mean_return=-0.3780, daily_std=0.0094\nMinimum required portfolio return (annualized): 0.5337\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_SCHH=X.XXXX", "answer": "w_DOT-USD=0.2826, w_SCHH=0.7174", "answer_numeric": 0.2826, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000089 - 0.000035) / (0.004368 + 0.000089 - 0.000071)\n Unconstrained: w_DOT-USD=0.0122\n After long-only clamp: w_DOT-USD=0.0122, w_SCHH=0.9878.", "metadata": {"weights": {"DOT-USD": 0.2826, "SCHH": 0.7174}, "sigma_1": 0.066091, "sigma_2": 0.009428, "covariance": 3.5e-05, "correlation": 0.0569, "has_text": true, "text_chars": 20, "mu_floor": 0.5337, "constraint_binding": true}} +{"id": "T4_all_20240226_0904", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "LQD"], "decision_date": "2024-02-26", "context_summary": "SOL-USD \u03c3=0.0402, LQD \u03c3=0.0053, \u03c1=-0.140. Min-variance weights: SOL-USD=0.034, LQD=0.966.", "question": "Assets: SOL-USD, LQD\nSOL-USD: annualized_mean_return=0.0504, daily_std=0.0402\nLQD: annualized_mean_return=0.0756, daily_std=0.0053\nMinimum required portfolio return (annualized): 0.0752\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_LQD=X.XXXX", "answer": "w_SOL-USD=0.0159, w_LQD=0.9841", "answer_numeric": 0.0159, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000028 - -0.000030) / (0.001619 + 0.000028 - -0.000060)\n Unconstrained: w_SOL-USD=0.0338\n After long-only clamp: w_SOL-USD=0.0338, w_LQD=0.9662.", "metadata": {"weights": {"SOL-USD": 0.0159, "LQD": 0.9841}, "sigma_1": 0.040231, "sigma_2": 0.005273, "covariance": -3e-05, "correlation": -0.1404, "has_text": true, "text_chars": 20, "mu_floor": 0.0752, "constraint_binding": true}} +{"id": "T4_all_20231114_0906", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "IEF"], "decision_date": "2023-11-14", "context_summary": "XLI \u03c3=0.0089, IEF \u03c3=0.0055, \u03c1=0.229. Min-variance weights: XLI=0.218, IEF=0.782.", "question": "Assets: XLI, IEF\nXLI: annualized_mean_return=-0.1260, daily_std=0.0089\nIEF: annualized_mean_return=-0.0756, daily_std=0.0055\nMinimum required portfolio return (annualized): -0.0798\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_IEF) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_IEF=X.XXXX", "answer": "w_XLI=0.0833, w_IEF=0.9167", "answer_numeric": 0.0833, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000030 - 0.000011) / (0.000079 + 0.000030 - 0.000022)\n Unconstrained: w_XLI=0.2183\n After long-only clamp: w_XLI=0.2183, w_IEF=0.7817.", "metadata": {"weights": {"XLI": 0.0833, "IEF": 0.9167}, "sigma_1": 0.00891, "sigma_2": 0.0055, "covariance": 1.1e-05, "correlation": 0.2289, "has_text": true, "text_chars": 3020, "mu_floor": -0.0798, "constraint_binding": true}} +{"id": "T4_all_20231101_0908", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "USMV"], "decision_date": "2023-11-01", "context_summary": "BTC-USD \u03c3=0.0189, USMV \u03c3=0.0058, \u03c1=-0.105. Min-variance weights: BTC-USD=0.108, USMV=0.892.", "question": "Assets: BTC-USD, USMV\nBTC-USD: annualized_mean_return=1.2852, daily_std=0.0189\nUSMV: annualized_mean_return=-0.1512, daily_std=0.0058\nMinimum required portfolio return (annualized): 0.6296\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_USMV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_USMV=X.XXXX", "answer": "w_BTC-USD=0.5436, w_USMV=0.4564", "answer_numeric": 0.5436, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000033 - -0.000011) / (0.000358 + 0.000033 - -0.000023)\n Unconstrained: w_BTC-USD=0.1082\n After long-only clamp: w_BTC-USD=0.1082, w_USMV=0.8918.", "metadata": {"weights": {"BTC-USD": 0.5436, "USMV": 0.4564}, "sigma_1": 0.018908, "sigma_2": 0.00577, "covariance": -1.1e-05, "correlation": -0.1051, "has_text": true, "text_chars": 20, "mu_floor": 0.6296, "constraint_binding": true}} +{"id": "T4_all_20240119_0910", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "CSHI"], "decision_date": "2024-01-19", "context_summary": "XLRE \u03c3=0.0125, CSHI \u03c3=0.0004, \u03c1=-0.014. Min-variance weights: XLRE=0.002, CSHI=0.999.", "question": "Assets: XLRE, CSHI\nXLRE: annualized_mean_return=0.6048, daily_std=0.0125\nCSHI: annualized_mean_return=0.0252, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.1495\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLRE=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLRE=0.2145, w_CSHI=0.7855", "answer_numeric": 0.2145, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000156 + 0.000000 - -0.000000)\n Unconstrained: w_XLRE=0.0015\n After long-only clamp: w_XLRE=0.0015, w_CSHI=0.9985.", "metadata": {"weights": {"XLRE": 0.2145, "CSHI": 0.7855}, "sigma_1": 0.012476, "sigma_2": 0.000407, "covariance": -0.0, "correlation": -0.0136, "has_text": true, "text_chars": 3020, "mu_floor": 0.1495, "constraint_binding": true}} +{"id": "T4_all_20240509_0912", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SLV"], "decision_date": "2024-05-09", "context_summary": "^VIX \u03c3=0.0535, SLV \u03c3=0.0171, \u03c1=0.009. Min-variance weights: ^VIX=0.091, SLV=0.909.", "question": "Assets: ^VIX, SLV\n^VIX: annualized_mean_return=-0.3024, daily_std=0.0535\nSLV: annualized_mean_return=1.0332, daily_std=0.0171\nMinimum required portfolio return (annualized): 0.9901\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_SLV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_^VIX=X.XXXX, w_SLV=X.XXXX", "answer": "w_^VIX=0.0323, w_SLV=0.9677", "answer_numeric": 0.0323, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000293 - 0.000008) / (0.002863 + 0.000293 - 0.000016)\n Unconstrained: w_^VIX=0.0908\n After long-only clamp: w_^VIX=0.0908, w_SLV=0.9092.", "metadata": {"weights": {"^VIX": 0.0323, "SLV": 0.9677}, "sigma_1": 0.053508, "sigma_2": 0.017119, "covariance": 8e-06, "correlation": 0.0086, "has_text": true, "text_chars": 9045, "mu_floor": 0.9901, "constraint_binding": true}} +{"id": "T4_all_20230320_0914", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "VNQI"], "decision_date": "2023-03-20", "context_summary": "SOL-USD \u03c3=0.0535, VNQI \u03c3=0.0098, \u03c1=-0.138. Min-variance weights: SOL-USD=0.055, VNQI=0.945.", "question": "Assets: SOL-USD, VNQI\nSOL-USD: annualized_mean_return=0.5544, daily_std=0.0535\nVNQI: annualized_mean_return=-0.1260, daily_std=0.0098\nMinimum required portfolio return (annualized): 0.2149\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_SOL-USD=0.5010, w_VNQI=0.4990", "answer_numeric": 0.501, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000097 - -0.000073) / (0.002860 + 0.000097 - -0.000146)\n Unconstrained: w_SOL-USD=0.0547\n After long-only clamp: w_SOL-USD=0.0547, w_VNQI=0.9453.", "metadata": {"weights": {"SOL-USD": 0.501, "VNQI": 0.499}, "sigma_1": 0.053482, "sigma_2": 0.009844, "covariance": -7.3e-05, "correlation": -0.1384, "has_text": true, "text_chars": 20, "mu_floor": 0.2149, "constraint_binding": true}} +{"id": "T4_all_20230809_0916", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XHB"], "decision_date": "2023-08-09", "context_summary": "XLY \u03c3=0.0110, XHB \u03c3=0.0125, \u03c1=0.617. Min-variance weights: XLY=0.658, XHB=0.342.", "question": "Assets: XLY, XHB\nXLY: annualized_mean_return=0.6048, daily_std=0.0110\nXHB: annualized_mean_return=0.7560, daily_std=0.0125\nMinimum required portfolio return (annualized): 0.6791\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_XHB=X.XXXX", "answer": "w_XLY=0.5086, w_XHB=0.4914", "answer_numeric": 0.5086, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000156 - 0.000085) / (0.000122 + 0.000156 - 0.000170)\n Unconstrained: w_XLY=0.6577\n After long-only clamp: w_XLY=0.6577, w_XHB=0.3423.", "metadata": {"weights": {"XLY": 0.5086, "XHB": 0.4914}, "sigma_1": 0.011035, "sigma_2": 0.012475, "covariance": 8.5e-05, "correlation": 0.6175, "has_text": true, "text_chars": 3020, "mu_floor": 0.6791, "constraint_binding": true}} +{"id": "T4_all_20240215_0918", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "CORN"], "decision_date": "2024-02-15", "context_summary": "SOL-USD \u03c3=0.0502, CORN \u03c3=0.0075, \u03c1=0.036. Min-variance weights: SOL-USD=0.017, CORN=0.983.", "question": "Assets: SOL-USD, CORN\nSOL-USD: annualized_mean_return=2.2680, daily_std=0.0502\nCORN: annualized_mean_return=-0.5796, daily_std=0.0075\nMinimum required portfolio return (annualized): 1.1975\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_CORN) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_CORN=X.XXXX", "answer": "w_SOL-USD=0.6241, w_CORN=0.3759", "answer_numeric": 0.6241, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000057 - 0.000014) / (0.002523 + 0.000057 - 0.000027)\n Unconstrained: w_SOL-USD=0.0169\n After long-only clamp: w_SOL-USD=0.0169, w_CORN=0.9831.", "metadata": {"weights": {"SOL-USD": 0.6241, "CORN": 0.3759}, "sigma_1": 0.050227, "sigma_2": 0.007534, "covariance": 1.4e-05, "correlation": 0.036, "has_text": true, "text_chars": 20, "mu_floor": 1.1975, "constraint_binding": true}} +{"id": "T4_all_20241122_0920", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "ICSH"], "decision_date": "2024-11-22", "context_summary": "MATIC-USD \u03c3=0.0461, ICSH \u03c3=0.0003, \u03c1=0.070. Min-variance weights: MATIC-USD=0.000, ICSH=1.000.", "question": "Assets: MATIC-USD, ICSH\nMATIC-USD: annualized_mean_return=0.7812, daily_std=0.0461\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.3931\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MATIC-USD=0.4689, w_ICSH=0.5311", "answer_numeric": 0.4689, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.002128 + 0.000000 - 0.000002)\n Unconstrained: w_MATIC-USD=-0.0004\n After long-only clamp: w_MATIC-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.4689, "ICSH": 0.5311}, "sigma_1": 0.046125, "sigma_2": 0.000267, "covariance": 1e-06, "correlation": 0.0702, "has_text": true, "text_chars": 20, "mu_floor": 0.3931, "constraint_binding": true}} +{"id": "T4_all_20240607_0922", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "SCHP"], "decision_date": "2024-06-07", "context_summary": "USMV \u03c3=0.0052, SCHP \u03c3=0.0029, \u03c1=0.135. Min-variance weights: USMV=0.199, SCHP=0.801.", "question": "Assets: USMV, SCHP\nUSMV: annualized_mean_return=0.0504, daily_std=0.0052\nSCHP: annualized_mean_return=0.1008, daily_std=0.0029\nMinimum required portfolio return (annualized): 0.0942\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_SCHP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_SCHP=X.XXXX", "answer": "w_USMV=0.1310, w_SCHP=0.8690", "answer_numeric": 0.131, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000008 - 0.000002) / (0.000027 + 0.000008 - 0.000004)\n Unconstrained: w_USMV=0.1994\n After long-only clamp: w_USMV=0.1994, w_SCHP=0.8006.", "metadata": {"weights": {"USMV": 0.131, "SCHP": 0.869}, "sigma_1": 0.005189, "sigma_2": 0.002865, "covariance": 2e-06, "correlation": 0.1347, "has_text": true, "text_chars": 9045, "mu_floor": 0.0942, "constraint_binding": true}} +{"id": "T4_all_20240918_0923", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "QUAL"], "decision_date": "2024-09-18", "context_summary": "LINK-USD \u03c3=0.0424, QUAL \u03c3=0.0100, \u03c1=0.197. Min-variance weights: LINK-USD=0.010, QUAL=0.990.", "question": "Assets: LINK-USD, QUAL\nLINK-USD: annualized_mean_return=-0.9576, daily_std=0.0424\nQUAL: annualized_mean_return=0.1260, daily_std=0.0100\nMinimum required portfolio return (annualized): -0.1140\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_QUAL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_QUAL=X.XXXX", "answer": "w_LINK-USD=0.0098, w_QUAL=0.9902", "answer_numeric": 0.0098, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000101 - 0.000084) / (0.001801 + 0.000101 - 0.000168)\n Unconstrained: w_LINK-USD=0.0098\n After long-only clamp: w_LINK-USD=0.0098, w_QUAL=0.9902.", "metadata": {"weights": {"LINK-USD": 0.0098, "QUAL": 0.9902}, "sigma_1": 0.042433, "sigma_2": 0.01005, "covariance": 8.4e-05, "correlation": 0.1971, "has_text": true, "text_chars": 20, "mu_floor": -0.114, "constraint_binding": false}} +{"id": "T4_all_20230303_0924", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "VNQ"], "decision_date": "2023-03-03", "context_summary": "ADA-USD \u03c3=0.0356, VNQ \u03c3=0.0129, \u03c1=0.015. Min-variance weights: ADA-USD=0.112, VNQ=0.888.", "question": "Assets: ADA-USD, VNQ\nADA-USD: annualized_mean_return=1.5876, daily_std=0.0356\nVNQ: annualized_mean_return=-0.0252, daily_std=0.0129\nMinimum required portfolio return (annualized): 1.0957\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_ADA-USD=0.6950, w_VNQ=0.3050", "answer_numeric": 0.695, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000166 - 0.000007) / (0.001266 + 0.000166 - 0.000014)\n Unconstrained: w_ADA-USD=0.1119\n After long-only clamp: w_ADA-USD=0.1119, w_VNQ=0.8881.", "metadata": {"weights": {"ADA-USD": 0.695, "VNQ": 0.305}, "sigma_1": 0.035577, "sigma_2": 0.01287, "covariance": 7e-06, "correlation": 0.0153, "has_text": true, "text_chars": 20, "mu_floor": 1.0957, "constraint_binding": true}} +{"id": "T4_all_20240408_0925", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "INDS"], "decision_date": "2024-04-08", "context_summary": "XLB \u03c3=0.0082, INDS \u03c3=0.0099, \u03c1=0.663. Min-variance weights: XLB=0.764, INDS=0.236.", "question": "Assets: XLB, INDS\nXLB: annualized_mean_return=0.4536, daily_std=0.0082\nINDS: annualized_mean_return=-0.2016, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.2595\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_INDS=X.XXXX", "answer": "w_XLB=0.7628, w_INDS=0.2372", "answer_numeric": 0.7628, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000098 - 0.000054) / (0.000068 + 0.000098 - 0.000108)\n Unconstrained: w_XLB=0.7640\n After long-only clamp: w_XLB=0.7640, w_INDS=0.2360.", "metadata": {"weights": {"XLB": 0.7628, "INDS": 0.2372}, "sigma_1": 0.008234, "sigma_2": 0.009919, "covariance": 5.4e-05, "correlation": 0.6627, "has_text": true, "text_chars": 9045, "mu_floor": 0.2595, "constraint_binding": false}} +{"id": "T4_all_20241114_0927", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SHV"], "decision_date": "2024-11-14", "context_summary": "VTI \u03c3=0.0080, SHV \u03c3=0.0002, \u03c1=-0.055. Min-variance weights: VTI=0.002, SHV=0.998.", "question": "Assets: VTI, SHV\nVTI: annualized_mean_return=0.3276, daily_std=0.0080\nSHV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0505\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_SHV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VTI=X.XXXX, w_SHV=X.XXXX", "answer": "w_VTI=0.0004, w_SHV=0.9996", "answer_numeric": 0.0004, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000064 + 0.000000 - -0.000000)\n Unconstrained: w_VTI=0.0016\n After long-only clamp: w_VTI=0.0016, w_SHV=0.9984.", "metadata": {"weights": {"VTI": 0.0004, "SHV": 0.9996}, "sigma_1": 0.007975, "sigma_2": 0.000167, "covariance": -0.0, "correlation": -0.055, "has_text": true, "text_chars": 9045, "mu_floor": 0.0505, "constraint_binding": false}} +{"id": "T4_all_20230914_0929", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "TIP"], "decision_date": "2023-09-14", "context_summary": "XLI \u03c3=0.0069, TIP \u03c3=0.0016, \u03c1=0.012. Min-variance weights: XLI=0.047, TIP=0.953.", "question": "Assets: XLI, TIP\nXLI: annualized_mean_return=-0.0252, daily_std=0.0069\nTIP: annualized_mean_return=0.0252, daily_std=0.0016\nMinimum required portfolio return (annualized): 0.0198\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_TIP=X.XXXX", "answer": "w_XLI=0.0498, w_TIP=0.9502", "answer_numeric": 0.0498, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000002 - 0.000000) / (0.000047 + 0.000002 - 0.000000)\n Unconstrained: w_XLI=0.0474\n After long-only clamp: w_XLI=0.0474, w_TIP=0.9526.", "metadata": {"weights": {"XLI": 0.0498, "TIP": 0.9502}, "sigma_1": 0.006892, "sigma_2": 0.001577, "covariance": 0.0, "correlation": 0.0118, "has_text": true, "text_chars": 3020, "mu_floor": 0.0198, "constraint_binding": false}} +{"id": "T4_all_20230301_0931", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SOL-USD"], "decision_date": "2023-03-01", "context_summary": "EFA \u03c3=0.0088, SOL-USD \u03c3=0.0701, \u03c1=-0.066. Min-variance weights: EFA=0.977, SOL-USD=0.024.", "question": "Assets: EFA, SOL-USD\nEFA: annualized_mean_return=0.1512, daily_std=0.0088\nSOL-USD: annualized_mean_return=3.8304, daily_std=0.0701\nMinimum required portfolio return (annualized): 0.1925\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_SOL-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_SOL-USD=X.XXXX", "answer": "w_EFA=0.9765, w_SOL-USD=0.0235", "answer_numeric": 0.9765, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.004912 - -0.000041) / (0.000078 + 0.004912 - -0.000082)\n Unconstrained: w_EFA=0.9765\n After long-only clamp: w_EFA=0.9765, w_SOL-USD=0.0235.", "metadata": {"weights": {"EFA": 0.9765, "SOL-USD": 0.0235}, "sigma_1": 0.008848, "sigma_2": 0.070088, "covariance": -4.1e-05, "correlation": -0.0663, "has_text": true, "text_chars": 3020, "mu_floor": 0.1925, "constraint_binding": false}} +{"id": "T4_all_20240709_0933", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XHB"], "decision_date": "2024-07-09", "context_summary": "USMV \u03c3=0.0047, XHB \u03c3=0.0137, \u03c1=0.410. Min-variance weights: USMV=1.000, XHB=0.000.", "question": "Assets: USMV, XHB\nUSMV: annualized_mean_return=0.1512, daily_std=0.0047\nXHB: annualized_mean_return=-0.1764, daily_std=0.0137\nMinimum required portfolio return (annualized): 0.0603\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_XHB=X.XXXX", "answer": "w_USMV=1.0000, w_XHB=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000187 - 0.000027) / (0.000022 + 0.000187 - 0.000053)\n Unconstrained: w_USMV=1.0264\n After long-only clamp: w_USMV=1.0000, w_XHB=0.0000.", "metadata": {"weights": {"USMV": 1.0, "XHB": 0.0}, "sigma_1": 0.00473, "sigma_2": 0.013671, "covariance": 2.7e-05, "correlation": 0.4098, "has_text": true, "text_chars": 9045, "mu_floor": 0.0603, "constraint_binding": false}} +{"id": "T4_all_20240307_0935", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD"], "decision_date": "2024-03-07", "context_summary": "QUAL \u03c3=0.0074, BTC-USD \u03c3=0.0293, \u03c1=0.240. Min-variance weights: QUAL=0.996, BTC-USD=0.004.", "question": "Assets: QUAL, BTC-USD\nQUAL: annualized_mean_return=0.5544, daily_std=0.0074\nBTC-USD: annualized_mean_return=1.8144, daily_std=0.0293\nMinimum required portfolio return (annualized): 0.5579\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_BTC-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QUAL=X.XXXX, w_BTC-USD=X.XXXX", "answer": "w_QUAL=0.9963, w_BTC-USD=0.0037", "answer_numeric": 0.9963, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000856 - 0.000052) / (0.000055 + 0.000856 - 0.000104)\n Unconstrained: w_QUAL=0.9964\n After long-only clamp: w_QUAL=0.9964, w_BTC-USD=0.0036.", "metadata": {"weights": {"QUAL": 0.9963, "BTC-USD": 0.0037}, "sigma_1": 0.007417, "sigma_2": 0.029261, "covariance": 5.2e-05, "correlation": 0.2403, "has_text": true, "text_chars": 9045, "mu_floor": 0.5579, "constraint_binding": false}} +{"id": "T4_all_20231025_0937", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "VNQ"], "decision_date": "2023-10-25", "context_summary": "MATIC-USD \u03c3=0.0271, VNQ \u03c3=0.0105, \u03c1=-0.399. Min-variance weights: MATIC-USD=0.209, VNQ=0.791.", "question": "Assets: MATIC-USD, VNQ\nMATIC-USD: annualized_mean_return=0.6552, daily_std=0.0271\nVNQ: annualized_mean_return=-0.6300, daily_std=0.0105\nMinimum required portfolio return (annualized): -0.5114\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_MATIC-USD=0.2088, w_VNQ=0.7912", "answer_numeric": 0.2088, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000110 - -0.000113) / (0.000732 + 0.000110 - -0.000227)\n Unconstrained: w_MATIC-USD=0.2090\n After long-only clamp: w_MATIC-USD=0.2090, w_VNQ=0.7910.", "metadata": {"weights": {"MATIC-USD": 0.2088, "VNQ": 0.7912}, "sigma_1": 0.027059, "sigma_2": 0.01049, "covariance": -0.000113, "correlation": -0.3994, "has_text": true, "text_chars": 20, "mu_floor": -0.5114, "constraint_binding": false}} +{"id": "T4_all_20231206_0939", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "GLD"], "decision_date": "2023-12-06", "context_summary": "QQQ \u03c3=0.0105, GLD \u03c3=0.0083, \u03c1=0.046. Min-variance weights: QQQ=0.382, GLD=0.618.", "question": "Assets: QQQ, GLD\nQQQ: annualized_mean_return=0.1260, daily_std=0.0105\nGLD: annualized_mean_return=0.1512, daily_std=0.0083\nMinimum required portfolio return (annualized): 0.1396\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_QQQ=X.XXXX, w_GLD=X.XXXX", "answer": "w_QQQ=0.3821, w_GLD=0.6179", "answer_numeric": 0.3821, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000069 - 0.000004) / (0.000110 + 0.000069 - 0.000008)\n Unconstrained: w_QQQ=0.3821\n After long-only clamp: w_QQQ=0.3821, w_GLD=0.6179.", "metadata": {"weights": {"QQQ": 0.3821, "GLD": 0.6179}, "sigma_1": 0.010476, "sigma_2": 0.00833, "covariance": 4e-06, "correlation": 0.0462, "has_text": true, "text_chars": 3020, "mu_floor": 0.1396, "constraint_binding": false}} +{"id": "T4_all_20230131_0941", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "IYR"], "decision_date": "2023-01-31", "context_summary": "BNB-USD \u03c3=0.0260, IYR \u03c3=0.0137, \u03c1=0.006. Min-variance weights: BNB-USD=0.217, IYR=0.783.", "question": "Assets: BNB-USD, IYR\nBNB-USD: annualized_mean_return=0.3024, daily_std=0.0260\nIYR: annualized_mean_return=0.2016, daily_std=0.0137\nMinimum required portfolio return (annualized): 0.2190\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_IYR=X.XXXX", "answer": "w_BNB-USD=0.2169, w_IYR=0.7831", "answer_numeric": 0.2169, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000188 - 0.000002) / (0.000674 + 0.000188 - 0.000004)\n Unconstrained: w_BNB-USD=0.2169\n After long-only clamp: w_BNB-USD=0.2169, w_IYR=0.7831.", "metadata": {"weights": {"BNB-USD": 0.2169, "IYR": 0.7831}, "sigma_1": 0.025967, "sigma_2": 0.013719, "covariance": 2e-06, "correlation": 0.0055, "has_text": true, "text_chars": 20, "mu_floor": 0.219, "constraint_binding": false}} +{"id": "T4_all_20241205_0943", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "SHV"], "decision_date": "2024-12-05", "context_summary": "BTC-USD \u03c3=0.0266, SHV \u03c3=0.0002, \u03c1=0.032. Min-variance weights: BTC-USD=0.000, SHV=1.000.", "question": "Assets: BTC-USD, SHV\nBTC-USD: annualized_mean_return=2.0412, daily_std=0.0266\nSHV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0505\nMarket regime: bull\n\nCompute portfolio weights (w_BTC-USD, w_SHV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_SHV=X.XXXX", "answer": "w_BTC-USD=0.0000, w_SHV=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000709 + 0.000000 - 0.000000)\n Unconstrained: w_BTC-USD=-0.0002\n After long-only clamp: w_BTC-USD=0.0000, w_SHV=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "SHV": 1.0}, "sigma_1": 0.026628, "sigma_2": 0.00016, "covariance": 0.0, "correlation": 0.0318, "has_text": true, "text_chars": 20, "mu_floor": 0.0505, "constraint_binding": false}} +{"id": "T4_all_20240528_0945", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BIL"], "decision_date": "2024-05-28", "context_summary": "XLK \u03c3=0.0116, BIL \u03c3=0.0002, \u03c1=-0.082. Min-variance weights: XLK=0.001, BIL=0.999.", "question": "Assets: XLK, BIL\nXLK: annualized_mean_return=0.1764, daily_std=0.0116\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLK=0.0002, w_BIL=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000134 + 0.000000 - -0.000000)\n Unconstrained: w_XLK=0.0013\n After long-only clamp: w_XLK=0.0013, w_BIL=0.9987.", "metadata": {"weights": {"XLK": 0.0002, "BIL": 0.9998}, "sigma_1": 0.011584, "sigma_2": 0.000155, "covariance": -0.0, "correlation": -0.0817, "has_text": true, "text_chars": 9045, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20230918_0946", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "SGOV"], "decision_date": "2023-09-18", "context_summary": "MATIC-USD \u03c3=0.0227, SGOV \u03c3=0.0001, \u03c1=-0.010. Min-variance weights: MATIC-USD=0.000, SGOV=1.000.", "question": "Assets: MATIC-USD, SGOV\nMATIC-USD: annualized_mean_return=-1.4616, daily_std=0.0227\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_SGOV=X.XXXX", "answer": "w_MATIC-USD=-0.0000, w_SGOV=1.0000", "answer_numeric": -0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000517 + 0.000000 - -0.000000)\n Unconstrained: w_MATIC-USD=0.0001\n After long-only clamp: w_MATIC-USD=0.0001, w_SGOV=0.9999.", "metadata": {"weights": {"MATIC-USD": -0.0, "SGOV": 1.0}, "sigma_1": 0.022736, "sigma_2": 0.000114, "covariance": -0.0, "correlation": -0.0099, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20240606_0947", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "BIL"], "decision_date": "2024-06-06", "context_summary": "FXI \u03c3=0.0141, BIL \u03c3=0.0001, \u03c1=0.145. Min-variance weights: FXI=0.000, BIL=1.000.", "question": "Assets: FXI, BIL\nFXI: annualized_mean_return=0.4788, daily_std=0.0141\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\n\nCompute portfolio weights (w_FXI, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_BIL=X.XXXX", "answer": "w_FXI=0.0001, w_BIL=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000199 + 0.000000 - 0.000001)\n Unconstrained: w_FXI=-0.0014\n After long-only clamp: w_FXI=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"FXI": 0.0001, "BIL": 0.9999}, "sigma_1": 0.014097, "sigma_2": 0.00015, "covariance": 0.0, "correlation": 0.1448, "has_text": true, "text_chars": 9045, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240711_0949", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "ICSH"], "decision_date": "2024-07-11", "context_summary": "XLK \u03c3=0.0113, ICSH \u03c3=0.0002, \u03c1=0.115. Min-variance weights: XLK=0.000, ICSH=1.000.", "question": "Assets: XLK, ICSH\nXLK: annualized_mean_return=0.6300, daily_std=0.0113\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0506\nMarket regime: bull\n\nCompute portfolio weights (w_XLK, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLK=0.0005, w_ICSH=0.9995", "answer_numeric": 0.0005, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000128 + 0.000000 - 0.000001)\n Unconstrained: w_XLK=-0.0020\n After long-only clamp: w_XLK=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLK": 0.0005, "ICSH": 0.9995}, "sigma_1": 0.011335, "sigma_2": 0.000245, "covariance": 0.0, "correlation": 0.1151, "has_text": true, "text_chars": 9045, "mu_floor": 0.0506, "constraint_binding": false}} +{"id": "T4_all_20241115_0951", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BNO"], "decision_date": "2024-11-15", "context_summary": "MTUM \u03c3=0.0096, BNO \u03c3=0.0212, \u03c1=0.005. Min-variance weights: MTUM=0.831, BNO=0.169.", "question": "Assets: MTUM, BNO\nMTUM: annualized_mean_return=0.2520, daily_std=0.0096\nBNO: annualized_mean_return=-0.3780, daily_std=0.0212\nMinimum required portfolio return (annualized): -0.1640\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_BNO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_BNO=X.XXXX", "answer": "w_MTUM=0.8314, w_BNO=0.1686", "answer_numeric": 0.8314, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000448 - 0.000001) / (0.000092 + 0.000448 - 0.000002)\n Unconstrained: w_MTUM=0.8313\n After long-only clamp: w_MTUM=0.8313, w_BNO=0.1687.", "metadata": {"weights": {"MTUM": 0.8314, "BNO": 0.1686}, "sigma_1": 0.009575, "sigma_2": 0.021167, "covariance": 1e-06, "correlation": 0.0045, "has_text": true, "text_chars": 9045, "mu_floor": -0.164, "constraint_binding": false}} +{"id": "T4_all_20230802_0953", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "VTI"], "decision_date": "2023-08-02", "context_summary": "XRP-USD \u03c3=0.0513, VTI \u03c3=0.0067, \u03c1=0.083. Min-variance weights: XRP-USD=0.006, VTI=0.994.", "question": "Assets: XRP-USD, VTI\nXRP-USD: annualized_mean_return=0.4284, daily_std=0.0513\nVTI: annualized_mean_return=0.5292, daily_std=0.0067\nMinimum required portfolio return (annualized): 0.4831\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_VTI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_VTI=X.XXXX", "answer": "w_XRP-USD=0.0063, w_VTI=0.9937", "answer_numeric": 0.0063, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000044 - 0.000028) / (0.002628 + 0.000044 - 0.000057)\n Unconstrained: w_XRP-USD=0.0062\n After long-only clamp: w_XRP-USD=0.0062, w_VTI=0.9938.", "metadata": {"weights": {"XRP-USD": 0.0063, "VTI": 0.9937}, "sigma_1": 0.051262, "sigma_2": 0.00667, "covariance": 2.8e-05, "correlation": 0.083, "has_text": true, "text_chars": 20, "mu_floor": 0.4831, "constraint_binding": false}} +{"id": "T4_all_20230323_0955", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SHY"], "decision_date": "2023-03-23", "context_summary": "VEA \u03c3=0.0099, SHY \u03c3=0.0016, \u03c1=-0.229. Min-variance weights: VEA=0.057, SHY=0.943.", "question": "Assets: VEA, SHY\nVEA: annualized_mean_return=0.1764, daily_std=0.0099\nSHY: annualized_mean_return=0.0000, daily_std=0.0016\nMinimum required portfolio return (annualized): 0.0073\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_SHY=X.XXXX", "answer": "w_VEA=0.0599, w_SHY=0.9401", "answer_numeric": 0.0599, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000003 - -0.000004) / (0.000098 + 0.000003 - -0.000007)\n Unconstrained: w_VEA=0.0568\n After long-only clamp: w_VEA=0.0568, w_SHY=0.9432.", "metadata": {"weights": {"VEA": 0.0599, "SHY": 0.9401}, "sigma_1": 0.009924, "sigma_2": 0.00159, "covariance": -4e-06, "correlation": -0.2294, "has_text": true, "text_chars": 3020, "mu_floor": 0.0073, "constraint_binding": false}} +{"id": "T4_all_20240419_0957", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "ITB"], "decision_date": "2024-04-19", "context_summary": "SOL-USD \u03c3=0.0526, ITB \u03c3=0.0150, \u03c1=0.108. Min-variance weights: SOL-USD=0.049, ITB=0.951.", "question": "Assets: SOL-USD, ITB\nSOL-USD: annualized_mean_return=1.3356, daily_std=0.0526\nITB: annualized_mean_return=0.2016, daily_std=0.0150\nMinimum required portfolio return (annualized): 0.2346\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_ITB=X.XXXX", "answer": "w_SOL-USD=0.0494, w_ITB=0.9506", "answer_numeric": 0.0494, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000224 - 0.000085) / (0.002771 + 0.000224 - 0.000170)\n Unconstrained: w_SOL-USD=0.0494\n After long-only clamp: w_SOL-USD=0.0494, w_ITB=0.9506.", "metadata": {"weights": {"SOL-USD": 0.0494, "ITB": 0.9506}, "sigma_1": 0.052644, "sigma_2": 0.014983, "covariance": 8.5e-05, "correlation": 0.1077, "has_text": true, "text_chars": 20, "mu_floor": 0.2346, "constraint_binding": false}} +{"id": "T4_all_20240131_0959", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "USMV"], "decision_date": "2024-01-31", "context_summary": "XRP-USD \u03c3=0.0250, USMV \u03c3=0.0051, \u03c1=-0.022. Min-variance weights: XRP-USD=0.044, USMV=0.956.", "question": "Assets: XRP-USD, USMV\nXRP-USD: annualized_mean_return=-0.6804, daily_std=0.0250\nUSMV: annualized_mean_return=0.4788, daily_std=0.0051\nMinimum required portfolio return (annualized): 0.3356\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_USMV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_USMV=X.XXXX", "answer": "w_XRP-USD=0.0446, w_USMV=0.9554", "answer_numeric": 0.0446, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000026 - -0.000003) / (0.000623 + 0.000026 - -0.000006)\n Unconstrained: w_XRP-USD=0.0443\n After long-only clamp: w_XRP-USD=0.0443, w_USMV=0.9557.", "metadata": {"weights": {"XRP-USD": 0.0446, "USMV": 0.9554}, "sigma_1": 0.024968, "sigma_2": 0.005123, "covariance": -3e-06, "correlation": -0.0216, "has_text": true, "text_chars": 20, "mu_floor": 0.3356, "constraint_binding": false}} +{"id": "T4_all_20230221_0961", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ETH-USD"], "decision_date": "2023-02-21", "context_summary": "EWJ \u03c3=0.0098, ETH-USD \u03c3=0.0260, \u03c1=0.023. Min-variance weights: EWJ=0.881, ETH-USD=0.119.", "question": "Assets: EWJ, ETH-USD\nEWJ: annualized_mean_return=0.2520, daily_std=0.0098\nETH-USD: annualized_mean_return=1.4868, daily_std=0.0260\nMinimum required portfolio return (annualized): 0.3788\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_ETH-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EWJ=X.XXXX, w_ETH-USD=X.XXXX", "answer": "w_EWJ=0.8809, w_ETH-USD=0.1191", "answer_numeric": 0.8809, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000674 - 0.000006) / (0.000096 + 0.000674 - 0.000012)\n Unconstrained: w_EWJ=0.8808\n After long-only clamp: w_EWJ=0.8808, w_ETH-USD=0.1192.", "metadata": {"weights": {"EWJ": 0.8809, "ETH-USD": 0.1191}, "sigma_1": 0.009811, "sigma_2": 0.025956, "covariance": 6e-06, "correlation": 0.0232, "has_text": true, "text_chars": 3020, "mu_floor": 0.3788, "constraint_binding": false}} +{"id": "T4_all_20240308_0963", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "HAUZ"], "decision_date": "2024-03-08", "context_summary": "USMV \u03c3=0.0052, HAUZ \u03c3=0.0102, \u03c1=0.442. Min-variance weights: USMV=0.956, HAUZ=0.044.", "question": "Assets: USMV, HAUZ\nUSMV: annualized_mean_return=0.3276, daily_std=0.0052\nHAUZ: annualized_mean_return=0.1260, daily_std=0.0102\nMinimum required portfolio return (annualized): 0.3092\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_USMV=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_USMV=0.9586, w_HAUZ=0.0414", "answer_numeric": 0.9586, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000105 - 0.000024) / (0.000027 + 0.000105 - 0.000047)\n Unconstrained: w_USMV=0.9555\n After long-only clamp: w_USMV=0.9555, w_HAUZ=0.0445.", "metadata": {"weights": {"USMV": 0.9586, "HAUZ": 0.0414}, "sigma_1": 0.005243, "sigma_2": 0.010234, "covariance": 2.4e-05, "correlation": 0.4421, "has_text": true, "text_chars": 9045, "mu_floor": 0.3092, "constraint_binding": false}} +{"id": "T4_all_20240426_0965", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "BNO"], "decision_date": "2024-04-26", "context_summary": "BTC-USD \u03c3=0.0368, BNO \u03c3=0.0113, \u03c1=-0.096. Min-variance weights: BTC-USD=0.107, BNO=0.893.", "question": "Assets: BTC-USD, BNO\nBTC-USD: annualized_mean_return=1.0836, daily_std=0.0368\nBNO: annualized_mean_return=0.5544, daily_std=0.0113\nMinimum required portfolio return (annualized): 0.5974\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_BNO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_BNO=X.XXXX", "answer": "w_BTC-USD=0.1072, w_BNO=0.8928", "answer_numeric": 0.1072, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000127 - -0.000040) / (0.001352 + 0.000127 - -0.000080)\n Unconstrained: w_BTC-USD=0.1071\n After long-only clamp: w_BTC-USD=0.1071, w_BNO=0.8929.", "metadata": {"weights": {"BTC-USD": 0.1072, "BNO": 0.8928}, "sigma_1": 0.036765, "sigma_2": 0.01127, "covariance": -4e-05, "correlation": -0.0964, "has_text": true, "text_chars": 20, "mu_floor": 0.5974, "constraint_binding": false}} +{"id": "T4_all_20241028_0966", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "ICSH"], "decision_date": "2024-10-28", "context_summary": "MATIC-USD \u03c3=0.0240, ICSH \u03c3=0.0002, \u03c1=-0.005. Min-variance weights: MATIC-USD=0.000, ICSH=1.000.", "question": "Assets: MATIC-USD, ICSH\nMATIC-USD: annualized_mean_return=-1.1088, daily_std=0.0240\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0503\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_MATIC-USD=0.0001, w_ICSH=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000577 + 0.000000 - -0.000000)\n Unconstrained: w_MATIC-USD=0.0001\n After long-only clamp: w_MATIC-USD=0.0001, w_ICSH=0.9999.", "metadata": {"weights": {"MATIC-USD": 0.0001, "ICSH": 0.9999}, "sigma_1": 0.024024, "sigma_2": 0.000229, "covariance": -0.0, "correlation": -0.0051, "has_text": true, "text_chars": 20, "mu_floor": 0.0503, "constraint_binding": true}} +{"id": "T4_all_20240605_0968", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BIL"], "decision_date": "2024-06-05", "context_summary": "XLF \u03c3=0.0076, BIL \u03c3=0.0001, \u03c1=0.170. Min-variance weights: XLF=0.000, BIL=1.000.", "question": "Assets: XLF, BIL\nXLF: annualized_mean_return=0.0756, daily_std=0.0076\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0595\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLF=0.3611, w_BIL=0.6389", "answer_numeric": 0.3611, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000058 + 0.000000 - 0.000000)\n Unconstrained: w_XLF=-0.0030\n After long-only clamp: w_XLF=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLF": 0.3611, "BIL": 0.6389}, "sigma_1": 0.007648, "sigma_2": 0.000149, "covariance": 0.0, "correlation": 0.1696, "has_text": true, "text_chars": 9045, "mu_floor": 0.0595, "constraint_binding": true}} +{"id": "T4_all_20230921_0969", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "HAUZ"], "decision_date": "2023-09-21", "context_summary": "DOT-USD \u03c3=0.0175, HAUZ \u03c3=0.0080, \u03c1=0.104. Min-variance weights: DOT-USD=0.145, HAUZ=0.855.", "question": "Assets: DOT-USD, HAUZ\nDOT-USD: annualized_mean_return=-1.0080, daily_std=0.0175\nHAUZ: annualized_mean_return=0.0504, daily_std=0.0080\nMinimum required portfolio return (annualized): -0.6142\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_DOT-USD=0.1445, w_HAUZ=0.8555", "answer_numeric": 0.1445, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000064 - 0.000015) / (0.000305 + 0.000064 - 0.000029)\n Unconstrained: w_DOT-USD=0.1455\n After long-only clamp: w_DOT-USD=0.1455, w_HAUZ=0.8545.", "metadata": {"weights": {"DOT-USD": 0.1445, "HAUZ": 0.8555}, "sigma_1": 0.017453, "sigma_2": 0.007995, "covariance": 1.5e-05, "correlation": 0.1041, "has_text": true, "text_chars": 20, "mu_floor": -0.6142, "constraint_binding": false}} +{"id": "T4_all_20230712_0971", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "SGOV"], "decision_date": "2023-07-12", "context_summary": "BNB-USD \u03c3=0.0255, SGOV \u03c3=0.0002, \u03c1=-0.102. Min-variance weights: BNB-USD=0.001, SGOV=0.999.", "question": "Assets: BNB-USD, SGOV\nBNB-USD: annualized_mean_return=-0.8316, daily_std=0.0255\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.4499\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_SGOV=X.XXXX", "answer": "w_BNB-USD=0.0000, w_SGOV=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000652 + 0.000000 - -0.000001)\n Unconstrained: w_BNB-USD=0.0007\n After long-only clamp: w_BNB-USD=0.0007, w_SGOV=0.9993.", "metadata": {"weights": {"BNB-USD": 0.0, "SGOV": 1.0}, "sigma_1": 0.025525, "sigma_2": 0.000166, "covariance": -0.0, "correlation": -0.1017, "has_text": true, "text_chars": 20, "mu_floor": -0.4499, "constraint_binding": false}} +{"id": "T4_all_20240228_0973", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "CSHI"], "decision_date": "2024-02-28", "context_summary": "MTUM \u03c3=0.0105, CSHI \u03c3=0.0003, \u03c1=-0.029. Min-variance weights: MTUM=0.002, CSHI=0.998.", "question": "Assets: MTUM, CSHI\nMTUM: annualized_mean_return=0.7560, daily_std=0.0105\nCSHI: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0257\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MTUM=X.XXXX, w_CSHI=X.XXXX", "answer": "w_MTUM=0.0011, w_CSHI=0.9989", "answer_numeric": 0.0011, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000111 + 0.000000 - -0.000000)\n Unconstrained: w_MTUM=0.0020\n After long-only clamp: w_MTUM=0.0020, w_CSHI=0.9980.", "metadata": {"weights": {"MTUM": 0.0011, "CSHI": 0.9989}, "sigma_1": 0.010539, "sigma_2": 0.000346, "covariance": -0.0, "correlation": -0.0293, "has_text": true, "text_chars": 9045, "mu_floor": 0.0257, "constraint_binding": false}} +{"id": "T4_all_20241031_0975", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SGOV"], "decision_date": "2024-10-31", "context_summary": "XLI \u03c3=0.0078, SGOV \u03c3=0.0002, \u03c1=0.048. Min-variance weights: XLI=0.000, SGOV=1.000.", "question": "Assets: XLI, SGOV\nXLI: annualized_mean_return=0.4536, daily_std=0.0078\nSGOV: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0758\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_SGOV=X.XXXX", "answer": "w_XLI=0.0005, w_SGOV=0.9995", "answer_numeric": 0.0005, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000061 + 0.000000 - 0.000000)\n Unconstrained: w_XLI=-0.0006\n After long-only clamp: w_XLI=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"XLI": 0.0005, "SGOV": 0.9995}, "sigma_1": 0.007802, "sigma_2": 0.000176, "covariance": 0.0, "correlation": 0.0476, "has_text": true, "text_chars": 9047, "mu_floor": 0.0758, "constraint_binding": false}} +{"id": "T4_all_20230817_0977", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BIL"], "decision_date": "2023-08-17", "context_summary": "XLI \u03c3=0.0083, BIL \u03c3=0.0001, \u03c1=0.102. Min-variance weights: XLI=0.000, BIL=1.000.", "question": "Assets: XLI, BIL\nXLI: annualized_mean_return=0.3024, daily_std=0.0083\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLI=0.0003, w_BIL=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000068 + 0.000000 - 0.000000)\n Unconstrained: w_XLI=-0.0014\n After long-only clamp: w_XLI=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLI": 0.0003, "BIL": 0.9997}, "sigma_1": 0.008252, "sigma_2": 0.000134, "covariance": 0.0, "correlation": 0.1019, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240712_0979", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNO"], "decision_date": "2024-07-12", "context_summary": "SPY \u03c3=0.0058, BNO \u03c3=0.0124, \u03c1=-0.014. Min-variance weights: SPY=0.816, BNO=0.184.", "question": "Assets: SPY, BNO\nSPY: annualized_mean_return=0.4284, daily_std=0.0058\nBNO: annualized_mean_return=0.1512, daily_std=0.0124\nMinimum required portfolio return (annualized): 0.2617\nMarket regime: sideways\n\nCompute portfolio weights (w_SPY, w_BNO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_BNO=X.XXXX", "answer": "w_SPY=0.8155, w_BNO=0.1845", "answer_numeric": 0.8155, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000153 - -0.000001) / (0.000034 + 0.000153 - -0.000002)\n Unconstrained: w_SPY=0.8155\n After long-only clamp: w_SPY=0.8155, w_BNO=0.1845.", "metadata": {"weights": {"SPY": 0.8155, "BNO": 0.1845}, "sigma_1": 0.005817, "sigma_2": 0.012369, "covariance": -1e-06, "correlation": -0.0138, "has_text": true, "text_chars": 9045, "mu_floor": 0.2617, "constraint_binding": false}} +{"id": "T4_all_20230228_0981", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "CSHI"], "decision_date": "2023-02-28", "context_summary": "XLI \u03c3=0.0106, CSHI \u03c3=0.0007, \u03c1=-0.218. Min-variance weights: XLI=0.017, CSHI=0.983.", "question": "Assets: XLI, CSHI\nXLI: annualized_mean_return=0.0756, daily_std=0.0106\nCSHI: annualized_mean_return=0.0756, daily_std=0.0007\nMinimum required portfolio return (annualized): 0.0755\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLI=0.0209, w_CSHI=0.9791", "answer_numeric": 0.0209, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000002) / (0.000112 + 0.000000 - -0.000003)\n Unconstrained: w_XLI=0.0170\n After long-only clamp: w_XLI=0.0170, w_CSHI=0.9830.", "metadata": {"weights": {"XLI": 0.0209, "CSHI": 0.9791}, "sigma_1": 0.010591, "sigma_2": 0.000662, "covariance": -2e-06, "correlation": -0.2176, "has_text": true, "text_chars": 3020, "mu_floor": 0.0755, "constraint_binding": false}} +{"id": "T4_all_20240830_0983", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "BIL"], "decision_date": "2024-08-30", "context_summary": "VLUE \u03c3=0.0096, BIL \u03c3=0.0002, \u03c1=0.028. Min-variance weights: VLUE=0.000, BIL=1.000.", "question": "Assets: VLUE, BIL\nVLUE: annualized_mean_return=0.1764, daily_std=0.0096\nBIL: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0756\nMarket regime: bull\n\nCompute portfolio weights (w_VLUE, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_BIL=X.XXXX", "answer": "w_VLUE=0.0003, w_BIL=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000092 + 0.000000 - 0.000000)\n Unconstrained: w_VLUE=-0.0002\n After long-only clamp: w_VLUE=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"VLUE": 0.0003, "BIL": 0.9997}, "sigma_1": 0.009572, "sigma_2": 0.000175, "covariance": 0.0, "correlation": 0.0284, "has_text": true, "text_chars": 9046, "mu_floor": 0.0756, "constraint_binding": false}} +{"id": "T4_all_20230331_0985", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "^VIX"], "decision_date": "2023-03-31", "context_summary": "ADA-USD \u03c3=0.0391, ^VIX \u03c3=0.0614, \u03c1=0.064. Min-variance weights: ADA-USD=0.724, ^VIX=0.276.", "question": "Assets: ADA-USD, ^VIX\nADA-USD: annualized_mean_return=-0.0252, daily_std=0.0391\n^VIX: annualized_mean_return=-0.7812, daily_std=0.0614\nMinimum required portfolio return (annualized): -0.2697\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_^VIX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_^VIX=X.XXXX", "answer": "w_ADA-USD=0.7242, w_^VIX=0.2758", "answer_numeric": 0.7242, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.003765 - 0.000153) / (0.001529 + 0.003765 - 0.000305)\n Unconstrained: w_ADA-USD=0.7241\n After long-only clamp: w_ADA-USD=0.7241, w_^VIX=0.2759.", "metadata": {"weights": {"ADA-USD": 0.7242, "^VIX": 0.2758}, "sigma_1": 0.039096, "sigma_2": 0.061356, "covariance": 0.000153, "correlation": 0.0636, "has_text": true, "text_chars": 20, "mu_floor": -0.2697, "constraint_binding": false}} +{"id": "T4_all_20230501_0987", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ITB"], "decision_date": "2023-05-01", "context_summary": "VEA \u03c3=0.0091, ITB \u03c3=0.0147, \u03c1=0.549. Min-variance weights: VEA=0.938, ITB=0.062.", "question": "Assets: VEA, ITB\nVEA: annualized_mean_return=0.0504, daily_std=0.0091\nITB: annualized_mean_return=0.3024, daily_std=0.0147\nMinimum required portfolio return (annualized): 0.0636\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_ITB=X.XXXX", "answer": "w_VEA=0.9369, w_ITB=0.0631", "answer_numeric": 0.9369, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000215 - 0.000073) / (0.000083 + 0.000215 - 0.000146)\n Unconstrained: w_VEA=0.9381\n After long-only clamp: w_VEA=0.9381, w_ITB=0.0619.", "metadata": {"weights": {"VEA": 0.9369, "ITB": 0.0631}, "sigma_1": 0.009088, "sigma_2": 0.014673, "covariance": 7.3e-05, "correlation": 0.5491, "has_text": true, "text_chars": 3020, "mu_floor": 0.0636, "constraint_binding": false}} +{"id": "T4_all_20231110_0989", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SHV"], "decision_date": "2023-11-10", "context_summary": "ETH-USD \u03c3=0.0234, SHV \u03c3=0.0002, \u03c1=0.105. Min-variance weights: ETH-USD=0.000, SHV=1.000.", "question": "Assets: ETH-USD, SHV\nETH-USD: annualized_mean_return=1.2096, daily_std=0.0234\nSHV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_SHV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_SHV=X.XXXX", "answer": "w_ETH-USD=0.0001, w_SHV=0.9999", "answer_numeric": 0.0001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000546 + 0.000000 - 0.000001)\n Unconstrained: w_ETH-USD=-0.0007\n After long-only clamp: w_ETH-USD=0.0000, w_SHV=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0001, "SHV": 0.9999}, "sigma_1": 0.023377, "sigma_2": 0.000167, "covariance": 0.0, "correlation": 0.1049, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20240516_0990", "template": "T4", "complexity": 2, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD", "HYG"], "decision_date": "2024-05-16", "context_summary": "DOT-USD \u03c3=0.0430, HYG \u03c3=0.0031, \u03c1=0.183. Min-variance weights: DOT-USD=0.000, HYG=1.000.", "question": "Assets: DOT-USD, HYG\nDOT-USD: annualized_mean_return=-1.1592, daily_std=0.0430\nHYG: annualized_mean_return=0.0756, daily_std=0.0031\nMinimum required portfolio return (annualized): -0.2730\nMarket regime: bull\n\nCompute portfolio weights (w_DOT-USD, w_HYG) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_HYG=X.XXXX", "answer": "w_DOT-USD=0.0000, w_HYG=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - 0.000024) / (0.001850 + 0.000010 - 0.000049)\n Unconstrained: w_DOT-USD=-0.0082\n After long-only clamp: w_DOT-USD=0.0000, w_HYG=1.0000.", "metadata": {"weights": {"DOT-USD": 0.0, "HYG": 1.0}, "sigma_1": 0.043011, "sigma_2": 0.003084, "covariance": 2.4e-05, "correlation": 0.1834, "has_text": true, "text_chars": 20, "mu_floor": -0.273, "constraint_binding": false}} +{"id": "T4_all_20240422_0991", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BNO"], "decision_date": "2024-04-22", "context_summary": "XLV \u03c3=0.0065, BNO \u03c3=0.0119, \u03c1=-0.060. Min-variance weights: XLV=0.760, BNO=0.240.", "question": "Assets: XLV, BNO\nXLV: annualized_mean_return=0.0252, daily_std=0.0065\nBNO: annualized_mean_return=0.4032, daily_std=0.0119\nMinimum required portfolio return (annualized): 0.1022\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_BNO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLV=X.XXXX, w_BNO=X.XXXX", "answer": "w_XLV=0.7588, w_BNO=0.2412", "answer_numeric": 0.7588, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000142 - -0.000005) / (0.000042 + 0.000142 - -0.000009)\n Unconstrained: w_XLV=0.7599\n After long-only clamp: w_XLV=0.7599, w_BNO=0.2401.", "metadata": {"weights": {"XLV": 0.7588, "BNO": 0.2412}, "sigma_1": 0.006463, "sigma_2": 0.011923, "covariance": -5e-06, "correlation": -0.0596, "has_text": true, "text_chars": 9045, "mu_floor": 0.1022, "constraint_binding": false}} +{"id": "T4_all_20240115_0993", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "PDBC"], "decision_date": "2024-01-15", "context_summary": "XLP \u03c3=0.0072, PDBC \u03c3=0.0101, \u03c1=0.039. Min-variance weights: XLP=0.670, PDBC=0.330.", "question": "Assets: XLP, PDBC\nXLP: annualized_mean_return=0.3276, daily_std=0.0072\nPDBC: annualized_mean_return=-0.4284, daily_std=0.0101\nMinimum required portfolio return (annualized): -0.0805\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_PDBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLP=X.XXXX, w_PDBC=X.XXXX", "answer": "w_XLP=0.6702, w_PDBC=0.3298", "answer_numeric": 0.6702, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000103 - 0.000003) / (0.000052 + 0.000103 - 0.000006)\n Unconstrained: w_XLP=0.6698\n After long-only clamp: w_XLP=0.6698, w_PDBC=0.3302.", "metadata": {"weights": {"XLP": 0.6702, "PDBC": 0.3298}, "sigma_1": 0.007212, "sigma_2": 0.010129, "covariance": 3e-06, "correlation": 0.0386, "has_text": true, "text_chars": 3020, "mu_floor": -0.0805, "constraint_binding": false}} +{"id": "T4_all_20240923_0995", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "GLD"], "decision_date": "2024-09-23", "context_summary": "LINK-USD \u03c3=0.0419, GLD \u03c3=0.0094, \u03c1=-0.012. Min-variance weights: LINK-USD=0.050, GLD=0.950.", "question": "Assets: LINK-USD, GLD\nLINK-USD: annualized_mean_return=-0.5544, daily_std=0.0419\nGLD: annualized_mean_return=0.4788, daily_std=0.0094\nMinimum required portfolio return (annualized): 0.0984\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_GLD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_GLD=X.XXXX", "answer": "w_LINK-USD=0.0504, w_GLD=0.9496", "answer_numeric": 0.0504, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000088 - -0.000005) / (0.001752 + 0.000088 - -0.000010)\n Unconstrained: w_LINK-USD=0.0502\n After long-only clamp: w_LINK-USD=0.0502, w_GLD=0.9498.", "metadata": {"weights": {"LINK-USD": 0.0504, "GLD": 0.9496}, "sigma_1": 0.041853, "sigma_2": 0.009389, "covariance": -5e-06, "correlation": -0.0121, "has_text": true, "text_chars": 20, "mu_floor": 0.0984, "constraint_binding": false}} +{"id": "T4_all_20230825_0996", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "VNQI"], "decision_date": "2023-08-25", "context_summary": "BNB-USD \u03c3=0.0187, VNQI \u03c3=0.0090, \u03c1=0.075. Min-variance weights: BNB-USD=0.168, VNQI=0.832.", "question": "Assets: BNB-USD, VNQI\nBNB-USD: annualized_mean_return=-0.3276, daily_std=0.0187\nVNQI: annualized_mean_return=0.0252, daily_std=0.0090\nMinimum required portfolio return (annualized): -0.0010\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_VNQI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_VNQI=X.XXXX", "answer": "w_BNB-USD=0.0743, w_VNQI=0.9257", "answer_numeric": 0.0743, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000080 - 0.000012) / (0.000348 + 0.000080 - 0.000025)\n Unconstrained: w_BNB-USD=0.1680\n After long-only clamp: w_BNB-USD=0.1680, w_VNQI=0.8320.", "metadata": {"weights": {"BNB-USD": 0.0743, "VNQI": 0.9257}, "sigma_1": 0.018653, "sigma_2": 0.008956, "covariance": 1.2e-05, "correlation": 0.0747, "has_text": true, "text_chars": 20, "mu_floor": -0.001, "constraint_binding": true}} +{"id": "T4_all_20240603_0998", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "IYR"], "decision_date": "2024-06-03", "context_summary": "SPY \u03c3=0.0070, IYR \u03c3=0.0108, \u03c1=0.620. Min-variance weights: SPY=0.973, IYR=0.027.", "question": "Assets: SPY, IYR\nSPY: annualized_mean_return=0.1512, daily_std=0.0070\nIYR: annualized_mean_return=-0.0756, daily_std=0.0108\nMinimum required portfolio return (annualized): 0.1489\nMarket regime: sideways\n\nCompute portfolio weights (w_SPY, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_IYR=X.XXXX", "answer": "w_SPY=0.9899, w_IYR=0.0101", "answer_numeric": 0.9899, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000116 - 0.000047) / (0.000049 + 0.000116 - 0.000093)\n Unconstrained: w_SPY=0.9731\n After long-only clamp: w_SPY=0.9731, w_IYR=0.0269.", "metadata": {"weights": {"SPY": 0.9899, "IYR": 0.0101}, "sigma_1": 0.006969, "sigma_2": 0.010791, "covariance": 4.7e-05, "correlation": 0.6202, "has_text": true, "text_chars": 9045, "mu_floor": 0.1489, "constraint_binding": true}} +{"id": "T4_all_20240409_0999", "template": "T4", "complexity": 2, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "TIP"], "decision_date": "2024-04-09", "context_summary": "ETH-USD \u03c3=0.0351, TIP \u03c3=0.0013, \u03c1=0.084. Min-variance weights: ETH-USD=0.000, TIP=1.000.", "question": "Assets: ETH-USD, TIP\nETH-USD: annualized_mean_return=1.9404, daily_std=0.0351\nTIP: annualized_mean_return=0.0252, daily_std=0.0013\nMinimum required portfolio return (annualized): 0.0252\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_TIP=X.XXXX", "answer": "w_ETH-USD=0.0000, w_TIP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000002 - 0.000004) / (0.001235 + 0.000002 - 0.000007)\n Unconstrained: w_ETH-USD=-0.0017\n After long-only clamp: w_ETH-USD=0.0000, w_TIP=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "TIP": 1.0}, "sigma_1": 0.035144, "sigma_2": 0.001257, "covariance": 4e-06, "correlation": 0.0842, "has_text": true, "text_chars": 20, "mu_floor": 0.0252, "constraint_binding": false}} +{"id": "T5_all_20230601_0000", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "DBC", "BIL"], "decision_date": "2023-06-01", "context_summary": "4-asset optimization. Max-Sharpe: 1.544. Portfolio: return=4.54%, vol=0.35%. Weights: w_VLUE=0.0000, w_XRP-USD=0.0013, w_DBC=0.0000, w_BIL=0.9987.", "question": "Assets: VLUE, XRP-USD, DBC, BIL\nAnnualized mean returns: VLUE:-0.2972, XRP-USD:0.0846, DBC:-0.4397, BIL:0.0453\nCovariance matrix (annualized):\n[[0.021207, 0.017628, 0.015836, 7.9e-05], [0.017628, 0.179242, 0.002871, -0.000129], [0.015836, 0.002871, 0.028205, -1.9e-05], [7.9e-05, -0.000129, -1.9e-05, 1.2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_XRP-USD=0.0013, w_DBC=0.0000, w_BIL=0.9987", "answer_numeric": 1.5444240133562828, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_XRP-USD=0.0013, w_DBC=0.0000, w_BIL=0.9987\nPortfolio annualized return: 4.54%, volatility: 0.35%\nSharpe ratio: (0.0454 - 0.0400) / 0.0035 = 1.5444", "metadata": {"weights": {"VLUE": 0.0, "XRP-USD": 0.0013, "DBC": 0.0, "BIL": 0.9987}, "sharpe_ratio": 1.5444, "portfolio_return": 0.04535, "portfolio_vol": 0.003464, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231219_0002", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "DBA", "TIP"], "decision_date": "2023-12-19", "context_summary": "4-asset optimization. Max-Sharpe: 4.944. Portfolio: return=37.27%, vol=6.73%. Weights: w_XLB=0.3475, w_LINK-USD=0.0380, w_DBA=0.0000, w_TIP=0.6144.", "question": "Assets: XLB, LINK-USD, DBA, TIP\nAnnualized mean returns: XLB:0.6919, LINK-USD:1.5813, DBA:0.0106, TIP:0.1174\nCovariance matrix (annualized):\n[[0.023476, -0.008387, 0.00371, 0.001682], [-0.008387, 0.630498, 0.005426, -0.00014], [0.00371, 0.005426, 0.015518, 0.000623], [0.001682, -0.00014, 0.000623, 0.000772]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.3475, w_LINK-USD=0.0380, w_DBA=0.0000, w_TIP=0.6144", "answer_numeric": 4.944359383748045, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.3475, w_LINK-USD=0.0380, w_DBA=0.0000, w_TIP=0.6144\nPortfolio annualized return: 37.27%, volatility: 6.73%\nSharpe ratio: (0.3727 - 0.0400) / 0.0673 = 4.9444", "metadata": {"weights": {"XLB": 0.3475, "LINK-USD": 0.038, "DBA": 0.0, "TIP": 0.6144}, "sharpe_ratio": 4.9444, "portfolio_return": 0.372735, "portfolio_vol": 0.067296, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230407_0005", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "SOL-USD", "BIL", "JNK"], "decision_date": "2023-04-07", "context_summary": "4-asset optimization. Max-Sharpe: 1.992. Portfolio: return=4.52%, vol=0.26%. Weights: w_XLV=0.0005, w_SOL-USD=0.0000, w_BIL=0.9995, w_JNK=0.0000.", "question": "Assets: XLV, SOL-USD, BIL, JNK\nAnnualized mean returns: XLV:0.0594, SOL-USD:-2.1331, BIL:0.0452, JNK:-0.0370\nCovariance matrix (annualized):\n[[0.019542, 0.016427, 1.5e-05, 0.006159], [0.016427, 0.540059, -0.000412, 0.021847], [1.5e-05, -0.000412, 7e-06, -5e-05], [0.006159, 0.021847, -5e-05, 0.009941]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0005, w_SOL-USD=0.0000, w_BIL=0.9995, w_JNK=0.0000", "answer_numeric": 1.9920385464475006, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0005, w_SOL-USD=0.0000, w_BIL=0.9995, w_JNK=0.0000\nPortfolio annualized return: 4.52%, volatility: 0.26%\nSharpe ratio: (0.0452 - 0.0400) / 0.0026 = 1.9920", "metadata": {"weights": {"XLV": 0.0005, "SOL-USD": 0.0, "BIL": 0.9995, "JNK": 0.0}, "sharpe_ratio": 1.992, "portfolio_return": 0.045248, "portfolio_vol": 0.002634, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230517_0007", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "MATIC-USD", "VNQ", "CPER"], "decision_date": "2023-05-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.082. Portfolio: return=38.35%, vol=16.50%. Weights: w_XLK=1.0000, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_CPER=0.0000.", "question": "Assets: XLK, MATIC-USD, VNQ, CPER\nAnnualized mean returns: XLK:0.3835, MATIC-USD:-1.4395, VNQ:0.0494, CPER:-0.3140\nCovariance matrix (annualized):\n[[0.027219, 0.018986, 0.018216, 0.012045], [0.018986, 0.242286, 0.005151, -0.000519], [0.018216, 0.005151, 0.041624, 0.008861], [0.012045, -0.000519, 0.008861, 0.036803]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=1.0000, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_CPER=0.0000", "answer_numeric": 2.08207740915417, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=1.0000, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_CPER=0.0000\nPortfolio annualized return: 38.35%, volatility: 16.50%\nSharpe ratio: (0.3835 - 0.0400) / 0.1650 = 2.0821", "metadata": {"weights": {"XLK": 1.0, "MATIC-USD": 0.0, "VNQ": 0.0, "CPER": 0.0}, "sharpe_ratio": 2.0821, "portfolio_return": 0.383502, "portfolio_vol": 0.16498, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230919_0010", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "ITB", "BIL"], "decision_date": "2023-09-19", "context_summary": "4-asset optimization. Max-Sharpe: 3.855. Portfolio: return=5.03%, vol=0.27%. Weights: w_XLU=0.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_BIL=1.0000.", "question": "Assets: XLU, LINK-USD, ITB, BIL\nAnnualized mean returns: XLU:-0.2377, LINK-USD:-0.5109, ITB:-0.3178, BIL:0.0503\nCovariance matrix (annualized):\n[[0.018733, 0.007285, 0.007694, -0.000115], [0.007285, 0.242623, 0.022476, -0.000144], [0.007694, 0.022476, 0.058992, -0.000236], [-0.000115, -0.000144, -0.000236, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_BIL=1.0000", "answer_numeric": 3.855242027436289, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_BIL=1.0000\nPortfolio annualized return: 5.03%, volatility: 0.27%\nSharpe ratio: (0.0503 - 0.0400) / 0.0027 = 3.8552", "metadata": {"weights": {"XLU": 0.0, "LINK-USD": 0.0, "ITB": 0.0, "BIL": 1.0}, "sharpe_ratio": 3.8552, "portfolio_return": 0.050251, "portfolio_vol": 0.002659, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240626_0013", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "REZ", "SGOV"], "decision_date": "2024-06-26", "context_summary": "4-asset optimization. Max-Sharpe: 6.036. Portfolio: return=5.82%, vol=0.30%. Weights: w_VLUE=0.0000, w_BTC-USD=0.0000, w_REZ=0.0131, w_SGOV=0.9869.", "question": "Assets: VLUE, BTC-USD, REZ, SGOV\nAnnualized mean returns: VLUE:0.0943, BTC-USD:-0.2190, REZ:0.5300, SGOV:0.0519\nCovariance matrix (annualized):\n[[0.012158, 0.016911, 0.011514, -3.2e-05], [0.016911, 0.215594, 0.01475, -0.00015], [0.011514, 0.01475, 0.019974, -1.8e-05], [-3.2e-05, -0.00015, -1.8e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_BTC-USD=0.0000, w_REZ=0.0131, w_SGOV=0.9869", "answer_numeric": 6.036043776736162, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_BTC-USD=0.0000, w_REZ=0.0131, w_SGOV=0.9869\nPortfolio annualized return: 5.82%, volatility: 0.30%\nSharpe ratio: (0.0582 - 0.0400) / 0.0030 = 6.0360", "metadata": {"weights": {"VLUE": 0.0, "BTC-USD": 0.0, "REZ": 0.0131, "SGOV": 0.9869}, "sharpe_ratio": 6.036, "portfolio_return": 0.058198, "portfolio_vol": 0.003015, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231122_0016", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "WEAT", "JNK"], "decision_date": "2023-11-22", "context_summary": "4-asset optimization. Max-Sharpe: 2.512. Portfolio: return=50.66%, vol=18.58%. Weights: w_EEM=0.0000, w_AVAX-USD=0.1782, w_WEAT=0.0000, w_JNK=0.8218.", "question": "Assets: EEM, AVAX-USD, WEAT, JNK\nAnnualized mean returns: EEM:0.1737, AVAX-USD:2.2243, WEAT:-0.1687, JNK:0.1340\nCovariance matrix (annualized):\n[[0.025354, 0.02737, -0.007474, 0.007899], [0.02737, 0.854757, -0.04558, 0.011221], [-0.007474, -0.04558, 0.053962, -0.001572], [0.007899, 0.011221, -0.001572, 0.006029]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_AVAX-USD=0.1782, w_WEAT=0.0000, w_JNK=0.8218", "answer_numeric": 2.511563249908591, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_AVAX-USD=0.1782, w_WEAT=0.0000, w_JNK=0.8218\nPortfolio annualized return: 50.66%, volatility: 18.58%\nSharpe ratio: (0.5066 - 0.0400) / 0.1858 = 2.5116", "metadata": {"weights": {"EEM": 0.0, "AVAX-USD": 0.1782, "WEAT": 0.0, "JNK": 0.8218}, "sharpe_ratio": 2.5116, "portfolio_return": 0.506578, "portfolio_vol": 0.185772, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230505_0019", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "BNO", "TIP"], "decision_date": "2023-05-05", "context_summary": "4-asset optimization. Max-Sharpe: 2.098. Portfolio: return=12.07%, vol=3.84%. Weights: w_EWJ=0.1636, w_ADA-USD=0.0301, w_BNO=0.0000, w_TIP=0.8063.", "question": "Assets: EWJ, ADA-USD, BNO, TIP\nAnnualized mean returns: EWJ:0.1373, ADA-USD:0.8307, BNO:-0.8924, TIP:0.0907\nCovariance matrix (annualized):\n[[0.018059, 0.009057, 0.018051, -0.001792], [0.009057, 0.348933, 0.013469, 0.003089], [0.018051, 0.013469, 0.13288, -0.001454], [-0.001792, 0.003089, -0.001454, 0.001401]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.1636, w_ADA-USD=0.0301, w_BNO=0.0000, w_TIP=0.8063", "answer_numeric": 2.097914223927825, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.1636, w_ADA-USD=0.0301, w_BNO=0.0000, w_TIP=0.8063\nPortfolio annualized return: 12.07%, volatility: 3.84%\nSharpe ratio: (0.1207 - 0.0400) / 0.0384 = 2.0979", "metadata": {"weights": {"EWJ": 0.1636, "ADA-USD": 0.0301, "BNO": 0.0, "TIP": 0.8063}, "sharpe_ratio": 2.0979, "portfolio_return": 0.120656, "portfolio_vol": 0.038446, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240423_0022", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ETH-USD", "SGOV", "PDBC"], "decision_date": "2024-04-23", "context_summary": "4-asset optimization. Max-Sharpe: 7.306. Portfolio: return=5.62%, vol=0.22%. Weights: w_XLV=0.0000, w_ETH-USD=0.0000, w_SGOV=0.9888, w_PDBC=0.0112.", "question": "Assets: XLV, ETH-USD, SGOV, PDBC\nAnnualized mean returns: XLV:-0.3073, ETH-USD:-0.2695, SGOV:0.0526, PDBC:0.3769\nCovariance matrix (annualized):\n[[0.010609, 0.008905, 1.3e-05, -0.001532], [0.008905, 0.425563, -0.000131, 0.009116], [1.3e-05, -0.000131, 4e-06, -1.9e-05], [-0.001532, 0.009116, -1.9e-05, 0.010901]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_ETH-USD=0.0000, w_SGOV=0.9888, w_PDBC=0.0112", "answer_numeric": 7.3055692285216605, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_ETH-USD=0.0000, w_SGOV=0.9888, w_PDBC=0.0112\nPortfolio annualized return: 5.62%, volatility: 0.22%\nSharpe ratio: (0.0562 - 0.0400) / 0.0022 = 7.3056", "metadata": {"weights": {"XLV": 0.0, "ETH-USD": 0.0, "SGOV": 0.9888, "PDBC": 0.0112}, "sharpe_ratio": 7.3056, "portfolio_return": 0.056223, "portfolio_vol": 0.002221, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230124_0024", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "SGOV", "WEAT"], "decision_date": "2023-01-24", "context_summary": "4-asset optimization. Max-Sharpe: 1.473. Portfolio: return=6.65%, vol=1.80%. Weights: w_IVV=0.0000, w_SOL-USD=0.0174, w_SGOV=0.9826, w_WEAT=0.0000.", "question": "Assets: IVV, SOL-USD, SGOV, WEAT\nAnnualized mean returns: IVV:-0.0279, SOL-USD:1.5294, SGOV:0.0406, WEAT:-0.7051\nCovariance matrix (annualized):\n[[0.035625, 0.068326, -0.000105, 0.009821], [0.068326, 1.052109, -7.2e-05, -0.003283], [-0.000105, -7.2e-05, 9e-06, -7.4e-05], [0.009821, -0.003283, -7.4e-05, 0.059749]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_SOL-USD=0.0174, w_SGOV=0.9826, w_WEAT=0.0000", "answer_numeric": 1.4726734803424841, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_SOL-USD=0.0174, w_SGOV=0.9826, w_WEAT=0.0000\nPortfolio annualized return: 6.65%, volatility: 1.80%\nSharpe ratio: (0.0665 - 0.0400) / 0.0180 = 1.4727", "metadata": {"weights": {"IVV": 0.0, "SOL-USD": 0.0174, "SGOV": 0.9826, "WEAT": 0.0}, "sharpe_ratio": 1.4727, "portfolio_return": 0.066506, "portfolio_vol": 0.017998, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230728_0026", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ADA-USD", "CPER", "MORT"], "decision_date": "2023-07-28", "context_summary": "4-asset optimization. Max-Sharpe: 4.498. Portfolio: return=80.64%, vol=17.04%. Weights: w_XLU=0.1861, w_ADA-USD=0.0000, w_CPER=0.0928, w_MORT=0.7211.", "question": "Assets: XLU, ADA-USD, CPER, MORT\nAnnualized mean returns: XLU:0.2918, ADA-USD:-0.3255, CPER:0.3194, MORT:1.0019\nCovariance matrix (annualized):\n[[0.022708, 0.007636, 0.010089, 0.006071], [0.007636, 0.638421, 0.042997, 0.037087], [0.010089, 0.042997, 0.029456, 0.008286], [0.006071, 0.037087, 0.008286, 0.047899]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.1861, w_ADA-USD=0.0000, w_CPER=0.0928, w_MORT=0.7211", "answer_numeric": 4.497816836686937, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.1861, w_ADA-USD=0.0000, w_CPER=0.0928, w_MORT=0.7211\nPortfolio annualized return: 80.64%, volatility: 17.04%\nSharpe ratio: (0.8064 - 0.0400) / 0.1704 = 4.4978", "metadata": {"weights": {"XLU": 0.1861, "ADA-USD": 0.0, "CPER": 0.0928, "MORT": 0.7211}, "sharpe_ratio": 4.4978, "portfolio_return": 0.806406, "portfolio_vol": 0.170395, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240202_0029", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BNB-USD", "XHB", "DBB"], "decision_date": "2024-02-02", "context_summary": "4-asset optimization. Max-Sharpe: 4.171. Portfolio: return=110.04%, vol=25.43%. Weights: w_EFA=0.0000, w_BNB-USD=0.3851, w_XHB=0.6149, w_DBB=0.0000.", "question": "Assets: EFA, BNB-USD, XHB, DBB\nAnnualized mean returns: EFA:0.2888, BNB-USD:1.7520, XHB:0.6923, DBB:0.0099\nCovariance matrix (annualized):\n[[0.01314, 0.015769, 0.016113, 0.005181], [0.015769, 0.238289, 0.020501, 0.010078], [0.016113, 0.020501, 0.051838, -0.000539], [0.005181, 0.010078, -0.000539, 0.026429]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_BNB-USD=0.3851, w_XHB=0.6149, w_DBB=0.0000", "answer_numeric": 4.170650757807628, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_BNB-USD=0.3851, w_XHB=0.6149, w_DBB=0.0000\nPortfolio annualized return: 110.04%, volatility: 25.43%\nSharpe ratio: (1.1004 - 0.0400) / 0.2543 = 4.1707", "metadata": {"weights": {"EFA": 0.0, "BNB-USD": 0.3851, "XHB": 0.6149, "DBB": 0.0}, "sharpe_ratio": 4.1707, "portfolio_return": 1.10044, "portfolio_vol": 0.254263, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20231024_0032", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "SGOV", "MORT"], "decision_date": "2023-10-24", "context_summary": "4-asset optimization. Max-Sharpe: 5.774. Portfolio: return=5.36%, vol=0.24%. Weights: w_VLUE=0.0000, w_XRP-USD=0.0015, w_SGOV=0.9985, w_MORT=0.0000.", "question": "Assets: VLUE, XRP-USD, SGOV, MORT\nAnnualized mean returns: VLUE:-0.2960, XRP-USD:0.5660, SGOV:0.0528, MORT:-0.7379\nCovariance matrix (annualized):\n[[0.013969, -0.003946, -1.2e-05, 0.023363], [-0.003946, 0.134741, 1.1e-05, -0.015322], [-1.2e-05, 1.1e-05, 5e-06, 5.1e-05], [0.023363, -0.015322, 5.1e-05, 0.062528]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_XRP-USD=0.0015, w_SGOV=0.9985, w_MORT=0.0000", "answer_numeric": 5.773520235392381, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_XRP-USD=0.0015, w_SGOV=0.9985, w_MORT=0.0000\nPortfolio annualized return: 5.36%, volatility: 0.24%\nSharpe ratio: (0.0536 - 0.0400) / 0.0024 = 5.7735", "metadata": {"weights": {"VLUE": 0.0, "XRP-USD": 0.0015, "SGOV": 0.9985, "MORT": 0.0}, "sharpe_ratio": 5.7735, "portfolio_return": 0.053582, "portfolio_vol": 0.002352, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240815_0033", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BNB-USD", "IGOV", "VNQ"], "decision_date": "2024-08-15", "context_summary": "4-asset optimization. Max-Sharpe: 4.585. Portfolio: return=41.05%, vol=8.08%. Weights: w_EFA=0.0000, w_BNB-USD=0.0000, w_IGOV=0.6229, w_VNQ=0.3771.", "question": "Assets: EFA, BNB-USD, IGOV, VNQ\nAnnualized mean returns: EFA:0.0863, BNB-USD:-0.0522, IGOV:0.2891, VNQ:0.6110\nCovariance matrix (annualized):\n[[0.024045, 0.015257, 0.001795, 0.009686], [0.015257, 0.230954, -0.012396, 0.026409], [0.001795, -0.012396, 0.006327, 0.00119], [0.009686, 0.026409, 0.00119, 0.02472]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_BNB-USD=0.0000, w_IGOV=0.6229, w_VNQ=0.3771", "answer_numeric": 4.584919907170154, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_BNB-USD=0.0000, w_IGOV=0.6229, w_VNQ=0.3771\nPortfolio annualized return: 41.05%, volatility: 8.08%\nSharpe ratio: (0.4105 - 0.0400) / 0.0808 = 4.5849", "metadata": {"weights": {"EFA": 0.0, "BNB-USD": 0.0, "IGOV": 0.6229, "VNQ": 0.3771}, "sharpe_ratio": 4.5849, "portfolio_return": 0.410483, "portfolio_vol": 0.080805, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230626_0036", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "REZ", "IGOV"], "decision_date": "2023-06-26", "context_summary": "4-asset optimization. Max-Sharpe: 0.035. Portfolio: return=4.61%, vol=17.48%. Weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_REZ=1.0000, w_IGOV=0.0000.", "question": "Assets: VEA, ADA-USD, REZ, IGOV\nAnnualized mean returns: VEA:-0.0238, ADA-USD:-1.0110, REZ:0.0461, IGOV:-0.0895\nCovariance matrix (annualized):\n[[0.019123, 0.010543, 0.01429, 0.002011], [0.010543, 0.227738, -0.002848, 0.004517], [0.01429, -0.002848, 0.03057, 0.000454], [0.002011, 0.004517, 0.000454, 0.010489]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_ADA-USD=0.0000, w_REZ=1.0000, w_IGOV=0.0000", "answer_numeric": 0.03482423116138154, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_REZ=1.0000, w_IGOV=0.0000\nPortfolio annualized return: 4.61%, volatility: 17.48%\nSharpe ratio: (0.0461 - 0.0400) / 0.1748 = 0.0348", "metadata": {"weights": {"VEA": 0.0, "ADA-USD": 0.0, "REZ": 1.0, "IGOV": 0.0}, "sharpe_ratio": 0.0348, "portfolio_return": 0.046089, "portfolio_vol": 0.174842, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230928_0038", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "MORT", "SGOV"], "decision_date": "2023-09-28", "context_summary": "4-asset optimization. Max-Sharpe: 5.855. Portfolio: return=5.16%, vol=0.20%. Weights: w_QUAL=0.0000, w_ADA-USD=0.0000, w_MORT=0.0000, w_SGOV=1.0000.", "question": "Assets: QUAL, ADA-USD, MORT, SGOV\nAnnualized mean returns: QUAL:-0.3690, ADA-USD:-1.3348, MORT:-0.5714, SGOV:0.0516\nCovariance matrix (annualized):\n[[0.015192, 0.012688, 0.012485, -2.9e-05], [0.012688, 0.111582, 0.02687, -9.1e-05], [0.012485, 0.02687, 0.037248, 5e-06], [-2.9e-05, -9.1e-05, 5e-06, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_ADA-USD=0.0000, w_MORT=0.0000, w_SGOV=1.0000", "answer_numeric": 5.855138073137804, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_ADA-USD=0.0000, w_MORT=0.0000, w_SGOV=1.0000\nPortfolio annualized return: 5.16%, volatility: 0.20%\nSharpe ratio: (0.0516 - 0.0400) / 0.0020 = 5.8551", "metadata": {"weights": {"QUAL": 0.0, "ADA-USD": 0.0, "MORT": 0.0, "SGOV": 1.0}, "sharpe_ratio": 5.8551, "portfolio_return": 0.051569, "portfolio_vol": 0.001976, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230531_0040", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD", "DBC", "SGOV"], "decision_date": "2023-05-31", "context_summary": "4-asset optimization. Max-Sharpe: 2.879. Portfolio: return=4.80%, vol=0.28%. Weights: w_ACWI=0.0000, w_DOT-USD=0.0000, w_DBC=0.0000, w_SGOV=1.0000.", "question": "Assets: ACWI, DOT-USD, DBC, SGOV\nAnnualized mean returns: ACWI:0.0769, DOT-USD:-0.7643, DBC:-0.3801, SGOV:0.0480\nCovariance matrix (annualized):\n[[0.013214, 0.011926, 0.010528, 3.7e-05], [0.011926, 0.164188, 0.023027, -0.000106], [0.010528, 0.023027, 0.028335, -0.000117], [3.7e-05, -0.000106, -0.000117, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_DOT-USD=0.0000, w_DBC=0.0000, w_SGOV=1.0000", "answer_numeric": 2.8791023830093785, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_DOT-USD=0.0000, w_DBC=0.0000, w_SGOV=1.0000\nPortfolio annualized return: 4.80%, volatility: 0.28%\nSharpe ratio: (0.0480 - 0.0400) / 0.0028 = 2.8791", "metadata": {"weights": {"ACWI": 0.0, "DOT-USD": 0.0, "DBC": 0.0, "SGOV": 1.0}, "sharpe_ratio": 2.8791, "portfolio_return": 0.047953, "portfolio_vol": 0.002762, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241212_0042", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "XHB", "SOYB"], "decision_date": "2024-12-12", "context_summary": "4-asset optimization. Max-Sharpe: 5.526. Portfolio: return=614.52%, vol=110.48%. Weights: w_VLUE=0.0000, w_XRP-USD=1.0000, w_XHB=0.0000, w_SOYB=0.0000.", "question": "Assets: VLUE, XRP-USD, XHB, SOYB\nAnnualized mean returns: VLUE:0.0066, XRP-USD:6.1452, XHB:-0.1787, SOYB:-0.1976\nCovariance matrix (annualized):\n[[0.016611, 0.028993, 0.016854, -0.000881], [0.028993, 1.220607, 0.011497, -0.015341], [0.016854, 0.011497, 0.052113, -0.003476], [-0.000881, -0.015341, -0.003476, 0.014772]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_XRP-USD=1.0000, w_XHB=0.0000, w_SOYB=0.0000", "answer_numeric": 5.52599520699285, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_XRP-USD=1.0000, w_XHB=0.0000, w_SOYB=0.0000\nPortfolio annualized return: 614.52%, volatility: 110.48%\nSharpe ratio: (6.1452 - 0.0400) / 1.1048 = 5.5260", "metadata": {"weights": {"VLUE": 0.0, "XRP-USD": 1.0, "XHB": 0.0, "SOYB": 0.0}, "sharpe_ratio": 5.526, "portfolio_return": 6.145178, "portfolio_vol": 1.104811, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230117_0045", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "SGOV", "JNK"], "decision_date": "2023-01-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.663. Portfolio: return=11.07%, vol=1.93%. Weights: w_XLF=0.0000, w_BTC-USD=0.0471, w_SGOV=0.9079, w_JNK=0.0450.", "question": "Assets: XLF, BTC-USD, SGOV, JNK\nAnnualized mean returns: XLF:0.2352, BTC-USD:1.2395, SGOV:0.0424, JNK:0.3075\nCovariance matrix (annualized):\n[[0.026941, 0.025649, -0.000111, 0.014105], [0.025649, 0.113895, 0.000134, 0.018557], [-0.000111, 0.000134, 9e-06, -4.6e-05], [0.014105, 0.018557, -4.6e-05, 0.012828]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_BTC-USD=0.0471, w_SGOV=0.9079, w_JNK=0.0450", "answer_numeric": 3.6626866226858854, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BTC-USD=0.0471, w_SGOV=0.9079, w_JNK=0.0450\nPortfolio annualized return: 11.07%, volatility: 1.93%\nSharpe ratio: (0.1107 - 0.0400) / 0.0193 = 3.6627", "metadata": {"weights": {"XLF": 0.0, "BTC-USD": 0.0471, "SGOV": 0.9079, "JNK": 0.045}, "sharpe_ratio": 3.6627, "portfolio_return": 0.110709, "portfolio_vol": 0.019305, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240610_0048", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "PALL", "SCHH"], "decision_date": "2024-06-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.627. Portfolio: return=12.36%, vol=13.33%. Weights: w_MTUM=0.4977, w_LINK-USD=0.0000, w_PALL=0.0000, w_SCHH=0.5023.", "question": "Assets: MTUM, LINK-USD, PALL, SCHH\nAnnualized mean returns: MTUM:0.1353, LINK-USD:-0.5799, PALL:-0.8427, SCHH:0.1120\nCovariance matrix (annualized):\n[[0.033323, 0.041693, 0.021057, 0.00728], [0.041693, 0.447598, 0.034074, 0.034727], [0.021057, 0.034074, 0.083793, 0.01203], [0.00728, 0.034727, 0.01203, 0.023253]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.4977, w_LINK-USD=0.0000, w_PALL=0.0000, w_SCHH=0.5023", "answer_numeric": 0.6271917480387615, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.4977, w_LINK-USD=0.0000, w_PALL=0.0000, w_SCHH=0.5023\nPortfolio annualized return: 12.36%, volatility: 13.33%\nSharpe ratio: (0.1236 - 0.0400) / 0.1333 = 0.6272", "metadata": {"weights": {"MTUM": 0.4977, "LINK-USD": 0.0, "PALL": 0.0, "SCHH": 0.5023}, "sharpe_ratio": 0.6272, "portfolio_return": 0.123585, "portfolio_vol": 0.133269, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240201_0050", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "SOL-USD", "IYR", "TLT"], "decision_date": "2024-02-01", "context_summary": "4-asset optimization. Max-Sharpe: 2.808. Portfolio: return=67.03%, vol=22.45%. Weights: w_XLB=0.0000, w_SOL-USD=0.2058, w_IYR=0.0000, w_TLT=0.7942.", "question": "Assets: XLB, SOL-USD, IYR, TLT\nAnnualized mean returns: XLB:-0.0429, SOL-USD:2.2444, IYR:0.0374, TLT:0.2624\nCovariance matrix (annualized):\n[[0.01587, 0.008619, 0.015673, 0.004445], [0.008619, 0.903805, 0.014567, -0.012382], [0.015673, 0.014567, 0.030762, 0.010405], [0.004445, -0.012382, 0.010405, 0.025592]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_SOL-USD=0.2058, w_IYR=0.0000, w_TLT=0.7942", "answer_numeric": 2.808306786085954, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_SOL-USD=0.2058, w_IYR=0.0000, w_TLT=0.7942\nPortfolio annualized return: 67.03%, volatility: 22.45%\nSharpe ratio: (0.6703 - 0.0400) / 0.2245 = 2.8083", "metadata": {"weights": {"XLB": 0.0, "SOL-USD": 0.2058, "IYR": 0.0, "TLT": 0.7942}, "sharpe_ratio": 2.8083, "portfolio_return": 0.670341, "portfolio_vol": 0.224456, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20241225_0052", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "DOT-USD", "SGOV", "EMB"], "decision_date": "2024-12-25", "context_summary": "4-asset optimization. Max-Sharpe: 2.755. Portfolio: return=4.82%, vol=0.30%. Weights: w_XLU=0.0000, w_DOT-USD=0.0014, w_SGOV=0.9986, w_EMB=0.0000.", "question": "Assets: XLU, DOT-USD, SGOV, EMB\nAnnualized mean returns: XLU:-0.2550, DOT-USD:1.4808, SGOV:0.0462, EMB:-0.0178\nCovariance matrix (annualized):\n[[0.031143, 0.042026, 5e-06, 0.004389], [0.042026, 0.94802, 0.000264, 0.019685], [5e-06, 0.000264, 6e-06, 1e-06], [0.004389, 0.019685, 1e-06, 0.005317]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_DOT-USD=0.0014, w_SGOV=0.9986, w_EMB=0.0000", "answer_numeric": 2.7548003438886415, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_DOT-USD=0.0014, w_SGOV=0.9986, w_EMB=0.0000\nPortfolio annualized return: 4.82%, volatility: 0.30%\nSharpe ratio: (0.0482 - 0.0400) / 0.0030 = 2.7548", "metadata": {"weights": {"XLU": 0.0, "DOT-USD": 0.0014, "SGOV": 0.9986, "EMB": 0.0}, "sharpe_ratio": 2.7548, "portfolio_return": 0.048159, "portfolio_vol": 0.002962, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230920_0054", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "AVAX-USD", "HAUZ", "BIL"], "decision_date": "2023-09-20", "context_summary": "4-asset optimization. Max-Sharpe: -5.079. Portfolio: return=-52.13%, vol=11.05%. Weights: w_USMV=0.2500, w_AVAX-USD=0.2500, w_HAUZ=0.2500, w_BIL=0.2500.", "question": "Assets: USMV, AVAX-USD, HAUZ, BIL\nAnnualized mean returns: USMV:-0.0652, AVAX-USD:-1.8088, HAUZ:-0.2619, BIL:0.0509\nCovariance matrix (annualized):\n[[0.005446, 0.011043, 0.0039, -7.7e-05], [0.011043, 0.127681, 0.009535, -0.000204], [0.0039, 0.009535, 0.013842, 3e-06], [-7.7e-05, -0.000204, 3e-06, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.2500, w_AVAX-USD=0.2500, w_HAUZ=0.2500, w_BIL=0.2500", "answer_numeric": -5.079189467944674, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.2500, w_AVAX-USD=0.2500, w_HAUZ=0.2500, w_BIL=0.2500\nPortfolio annualized return: -52.13%, volatility: 11.05%\nSharpe ratio: (-0.5213 - 0.0400) / 0.1105 = -5.0792", "metadata": {"weights": {"USMV": 0.25, "AVAX-USD": 0.25, "HAUZ": 0.25, "BIL": 0.25}, "sharpe_ratio": -5.0792, "portfolio_return": -0.521266, "portfolio_vol": 0.110503, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230512_0057", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "AVAX-USD", "STIP", "BIL"], "decision_date": "2023-05-12", "context_summary": "4-asset optimization. Max-Sharpe: 4.996. Portfolio: return=10.91%, vol=1.38%. Weights: w_QQQ=0.0778, w_AVAX-USD=0.0000, w_STIP=0.2432, w_BIL=0.6790.", "question": "Assets: QQQ, AVAX-USD, STIP, BIL\nAnnualized mean returns: QQQ:0.7278, AVAX-USD:0.2103, STIP:0.0897, BIL:0.0451\nCovariance matrix (annualized):\n[[0.029387, 0.02024, -0.00178, 7.4e-05], [0.02024, 0.426145, 0.001149, -0.000243], [-0.00178, 0.001149, 0.00113, 2e-06], [7.4e-05, -0.000243, 2e-06, 1.2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0778, w_AVAX-USD=0.0000, w_STIP=0.2432, w_BIL=0.6790", "answer_numeric": 4.996239749289554, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0778, w_AVAX-USD=0.0000, w_STIP=0.2432, w_BIL=0.6790\nPortfolio annualized return: 10.91%, volatility: 1.38%\nSharpe ratio: (0.1091 - 0.0400) / 0.0138 = 4.9962", "metadata": {"weights": {"QQQ": 0.0778, "AVAX-USD": 0.0, "STIP": 0.2432, "BIL": 0.679}, "sharpe_ratio": 4.9962, "portfolio_return": 0.10906, "portfolio_vol": 0.013822, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240620_0060", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "AVAX-USD", "INDS", "CSHI"], "decision_date": "2024-06-20", "context_summary": "4-asset optimization. Max-Sharpe: 7.798. Portfolio: return=13.11%, vol=1.17%. Weights: w_QUAL=0.1085, w_AVAX-USD=0.0000, w_INDS=0.0000, w_CSHI=0.8915.", "question": "Assets: QUAL, AVAX-USD, INDS, CSHI\nAnnualized mean returns: QUAL:0.7121, AVAX-USD:-1.4722, INDS:0.4296, CSHI:0.0604\nCovariance matrix (annualized):\n[[0.009313, 0.022991, 0.007449, -4e-06], [0.022991, 0.508932, 0.051705, -5.4e-05], [0.007449, 0.051705, 0.027709, 1.7e-05], [-4e-06, -5.4e-05, 1.7e-05, 3.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.1085, w_AVAX-USD=0.0000, w_INDS=0.0000, w_CSHI=0.8915", "answer_numeric": 7.7980429498886, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.1085, w_AVAX-USD=0.0000, w_INDS=0.0000, w_CSHI=0.8915\nPortfolio annualized return: 13.11%, volatility: 1.17%\nSharpe ratio: (0.1311 - 0.0400) / 0.0117 = 7.7980", "metadata": {"weights": {"QUAL": 0.1085, "AVAX-USD": 0.0, "INDS": 0.0, "CSHI": 0.8915}, "sharpe_ratio": 7.798, "portfolio_return": 0.131146, "portfolio_vol": 0.011688, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240503_0062", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ADA-USD", "XHB", "WEAT"], "decision_date": "2024-05-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.084. Portfolio: return=51.94%, vol=23.00%. Weights: w_XLF=0.0000, w_ADA-USD=0.0000, w_XHB=0.0000, w_WEAT=1.0000.", "question": "Assets: XLF, ADA-USD, XHB, WEAT\nAnnualized mean returns: XLF:0.0467, ADA-USD:-2.3709, XHB:-0.0172, WEAT:0.5194\nCovariance matrix (annualized):\n[[0.012944, 0.029405, 0.015934, 0.008132], [0.029405, 0.5242, 0.024877, 0.002513], [0.015934, 0.024877, 0.044784, 0.008474], [0.008132, 0.002513, 0.008474, 0.052917]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_ADA-USD=0.0000, w_XHB=0.0000, w_WEAT=1.0000", "answer_numeric": 2.083843011715529, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_ADA-USD=0.0000, w_XHB=0.0000, w_WEAT=1.0000\nPortfolio annualized return: 51.94%, volatility: 23.00%\nSharpe ratio: (0.5194 - 0.0400) / 0.2300 = 2.0838", "metadata": {"weights": {"XLF": 0.0, "ADA-USD": 0.0, "XHB": 0.0, "WEAT": 1.0}, "sharpe_ratio": 2.0838, "portfolio_return": 0.519363, "portfolio_vol": 0.230038, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230410_0064", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNB-USD", "BIL", "TLT"], "decision_date": "2023-04-10", "context_summary": "4-asset optimization. Max-Sharpe: -1.611. Portfolio: return=-20.54%, vol=15.23%. Weights: w_FXI=0.2500, w_BNB-USD=0.2500, w_BIL=0.2500, w_TLT=0.2500.", "question": "Assets: FXI, BNB-USD, BIL, TLT\nAnnualized mean returns: FXI:-0.2447, BNB-USD:-0.7822, BIL:0.0473, TLT:0.1578\nCovariance matrix (annualized):\n[[0.076759, 0.014324, 0.00014, -0.002328], [0.014324, 0.231056, 8.9e-05, 0.003159], [0.00014, 8.9e-05, 7e-06, 0.000107], [-0.002328, 0.003159, 0.000107, 0.032389]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.2500, w_BNB-USD=0.2500, w_BIL=0.2500, w_TLT=0.2500", "answer_numeric": -1.6114576751529308, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.2500, w_BNB-USD=0.2500, w_BIL=0.2500, w_TLT=0.2500\nPortfolio annualized return: -20.54%, volatility: 15.23%\nSharpe ratio: (-0.2054 - 0.0400) / 0.1523 = -1.6115", "metadata": {"weights": {"FXI": 0.25, "BNB-USD": 0.25, "BIL": 0.25, "TLT": 0.25}, "sharpe_ratio": -1.6115, "portfolio_return": -0.205447, "portfolio_vol": 0.152314, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230911_0066", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BTC-USD", "GLD", "SGOV"], "decision_date": "2023-09-11", "context_summary": "4-asset optimization. Max-Sharpe: 6.592. Portfolio: return=5.34%, vol=0.20%. Weights: w_XLI=0.0000, w_BTC-USD=0.0000, w_GLD=0.0000, w_SGOV=1.0000.", "question": "Assets: XLI, BTC-USD, GLD, SGOV\nAnnualized mean returns: XLI:-0.1812, BTC-USD:-0.9494, GLD:-0.1262, SGOV:0.0534\nCovariance matrix (annualized):\n[[0.011129, 0.011529, 0.004462, -3.9e-05], [0.011529, 0.110936, 0.006769, -5.4e-05], [0.004462, 0.006769, 0.007178, -3.4e-05], [-3.9e-05, -5.4e-05, -3.4e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_BTC-USD=0.0000, w_GLD=0.0000, w_SGOV=1.0000", "answer_numeric": 6.592448925810181, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_BTC-USD=0.0000, w_GLD=0.0000, w_SGOV=1.0000\nPortfolio annualized return: 5.34%, volatility: 0.20%\nSharpe ratio: (0.0534 - 0.0400) / 0.0020 = 6.5924", "metadata": {"weights": {"XLI": 0.0, "BTC-USD": 0.0, "GLD": 0.0, "SGOV": 1.0}, "sharpe_ratio": 6.5924, "portfolio_return": 0.053437, "portfolio_vol": 0.002038, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240411_0068", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "HAUZ", "ICSH"], "decision_date": "2024-04-11", "context_summary": "4-asset optimization. Max-Sharpe: 1.991. Portfolio: return=4.96%, vol=0.48%. Weights: w_USMV=0.0158, w_ADA-USD=0.0006, w_HAUZ=0.0000, w_ICSH=0.9836.", "question": "Assets: USMV, ADA-USD, HAUZ, ICSH\nAnnualized mean returns: USMV:0.1148, ADA-USD:0.2557, HAUZ:0.1376, ICSH:0.0484\nCovariance matrix (annualized):\n[[0.005712, 0.010973, 0.007551, 8.5e-05], [0.010973, 0.536349, 0.015868, 4.2e-05], [0.007551, 0.015868, 0.020915, 0.000307], [8.5e-05, 4.2e-05, 0.000307, 1.9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0158, w_ADA-USD=0.0006, w_HAUZ=0.0000, w_ICSH=0.9836", "answer_numeric": 1.991242446256464, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0158, w_ADA-USD=0.0006, w_HAUZ=0.0000, w_ICSH=0.9836\nPortfolio annualized return: 4.96%, volatility: 0.48%\nSharpe ratio: (0.0496 - 0.0400) / 0.0048 = 1.9912", "metadata": {"weights": {"USMV": 0.0158, "ADA-USD": 0.0006, "HAUZ": 0.0, "ICSH": 0.9836}, "sharpe_ratio": 1.9912, "portfolio_return": 0.049551, "portfolio_vol": 0.004797, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230929_0070", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "LINK-USD", "SOYB", "TLH"], "decision_date": "2023-09-29", "context_summary": "4-asset optimization. Max-Sharpe: 1.335. Portfolio: return=72.50%, vol=51.31%. Weights: w_IVV=0.0000, w_LINK-USD=1.0000, w_SOYB=0.0000, w_TLH=0.0000.", "question": "Assets: IVV, LINK-USD, SOYB, TLH\nAnnualized mean returns: IVV:-0.3535, LINK-USD:0.7250, SOYB:-0.1683, TLH:-0.4794\nCovariance matrix (annualized):\n[[0.013755, 0.021702, 0.003269, 0.003444], [0.021702, 0.263237, -0.007383, 0.014209], [0.003269, -0.007383, 0.030126, 0.001146], [0.003444, 0.014209, 0.001146, 0.016747]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_LINK-USD=1.0000, w_SOYB=0.0000, w_TLH=0.0000", "answer_numeric": 1.3351582303138407, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_LINK-USD=1.0000, w_SOYB=0.0000, w_TLH=0.0000\nPortfolio annualized return: 72.50%, volatility: 51.31%\nSharpe ratio: (0.7250 - 0.0400) / 0.5131 = 1.3352", "metadata": {"weights": {"IVV": 0.0, "LINK-USD": 1.0, "SOYB": 0.0, "TLH": 0.0}, "sharpe_ratio": 1.3352, "portfolio_return": 0.725024, "portfolio_vol": 0.513066, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231106_0072", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ETH-USD", "HAUZ", "GLD"], "decision_date": "2023-11-06", "context_summary": "4-asset optimization. Max-Sharpe: 1.930. Portfolio: return=26.48%, vol=11.65%. Weights: w_XLB=0.0000, w_ETH-USD=0.2803, w_HAUZ=0.0000, w_GLD=0.7197.", "question": "Assets: XLB, ETH-USD, HAUZ, GLD\nAnnualized mean returns: XLB:-0.2173, ETH-USD:0.4528, HAUZ:-0.1625, GLD:0.1916\nCovariance matrix (annualized):\n[[0.028103, 0.005677, 0.022589, -0.001336], [0.005677, 0.099436, 0.006381, -0.004119], [0.022589, 0.006381, 0.028293, -0.002159], [-0.001336, -0.004119, -0.002159, 0.014313]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_ETH-USD=0.2803, w_HAUZ=0.0000, w_GLD=0.7197", "answer_numeric": 1.9300337825155158, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_ETH-USD=0.2803, w_HAUZ=0.0000, w_GLD=0.7197\nPortfolio annualized return: 26.48%, volatility: 11.65%\nSharpe ratio: (0.2648 - 0.0400) / 0.1165 = 1.9300", "metadata": {"weights": {"XLB": 0.0, "ETH-USD": 0.2803, "HAUZ": 0.0, "GLD": 0.7197}, "sharpe_ratio": 1.93, "portfolio_return": 0.264787, "portfolio_vol": 0.116468, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240619_0073", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "ADA-USD", "VNQI", "USO"], "decision_date": "2024-06-19", "context_summary": "4-asset optimization. Max-Sharpe: 0.769. Portfolio: return=12.53%, vol=11.08%. Weights: w_VLUE=0.7243, w_ADA-USD=0.0000, w_VNQI=0.2757, w_USO=0.0000.", "question": "Assets: VLUE, ADA-USD, VNQI, USO\nAnnualized mean returns: VLUE:0.1219, ADA-USD:-1.1196, VNQI:0.1340, USO:0.0124\nCovariance matrix (annualized):\n[[0.012408, 0.011784, 0.010221, 0.006431], [0.011784, 0.2162, 0.030814, -0.006921], [0.010221, 0.030814, 0.022291, 0.003017], [0.006431, -0.006921, 0.003017, 0.054089]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.7243, w_ADA-USD=0.0000, w_VNQI=0.2757, w_USO=0.0000", "answer_numeric": 0.7693786587969448, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.7243, w_ADA-USD=0.0000, w_VNQI=0.2757, w_USO=0.0000\nPortfolio annualized return: 12.53%, volatility: 11.08%\nSharpe ratio: (0.1253 - 0.0400) / 0.1108 = 0.7694", "metadata": {"weights": {"VLUE": 0.7243, "ADA-USD": 0.0, "VNQI": 0.2757, "USO": 0.0}, "sharpe_ratio": 0.7694, "portfolio_return": 0.125278, "portfolio_vol": 0.110841, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231102_0075", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "ICSH", "TIP"], "decision_date": "2023-11-02", "context_summary": "4-asset optimization. Max-Sharpe: 3.734. Portfolio: return=5.50%, vol=0.40%. Weights: w_XLK=0.0000, w_BNB-USD=0.0027, w_ICSH=0.9973, w_TIP=0.0000.", "question": "Assets: XLK, BNB-USD, ICSH, TIP\nAnnualized mean returns: XLK:-0.3025, BNB-USD:0.1034, ICSH:0.0549, TIP:0.0318\nCovariance matrix (annualized):\n[[0.030093, -0.001248, -9.1e-05, 0.000484], [-0.001248, 0.050409, -6.7e-05, 9.7e-05], [-9.1e-05, -6.7e-05, 1.6e-05, 3.4e-05], [0.000484, 9.7e-05, 3.4e-05, 0.000603]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.0000, w_BNB-USD=0.0027, w_ICSH=0.9973, w_TIP=0.0000", "answer_numeric": 3.7335790386932954, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_BNB-USD=0.0027, w_ICSH=0.9973, w_TIP=0.0000\nPortfolio annualized return: 5.50%, volatility: 0.40%\nSharpe ratio: (0.0550 - 0.0400) / 0.0040 = 3.7336", "metadata": {"weights": {"XLK": 0.0, "BNB-USD": 0.0027, "ICSH": 0.9973, "TIP": 0.0}, "sharpe_ratio": 3.7336, "portfolio_return": 0.055043, "portfolio_vol": 0.004029, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230126_0078", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "CSHI", "SHV"], "decision_date": "2023-01-26", "context_summary": "4-asset optimization. Max-Sharpe: 3.361. Portfolio: return=6.95%, vol=0.88%. Weights: w_VEA=0.0169, w_ETH-USD=0.0106, w_CSHI=0.3195, w_SHV=0.6530.", "question": "Assets: VEA, ETH-USD, CSHI, SHV\nAnnualized mean returns: VEA:0.4461, ETH-USD:1.3721, CSHI:0.0581, SHV:0.0443\nCovariance matrix (annualized):\n[[0.025847, 0.043907, 0.000659, 4.9e-05], [0.043907, 0.220751, 0.001312, 0.000104], [0.000659, 0.001312, 7.6e-05, -1e-06], [4.9e-05, 0.000104, -1e-06, 9e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0169, w_ETH-USD=0.0106, w_CSHI=0.3195, w_SHV=0.6530", "answer_numeric": 3.3608009016948484, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0169, w_ETH-USD=0.0106, w_CSHI=0.3195, w_SHV=0.6530\nPortfolio annualized return: 6.95%, volatility: 0.88%\nSharpe ratio: (0.0695 - 0.0400) / 0.0088 = 3.3608", "metadata": {"weights": {"VEA": 0.0169, "ETH-USD": 0.0106, "CSHI": 0.3195, "SHV": 0.653}, "sharpe_ratio": 3.3608, "portfolio_return": 0.069546, "portfolio_vol": 0.008791, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230503_0080", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "DOT-USD", "SGOV", "MORT"], "decision_date": "2023-05-03", "context_summary": "4-asset optimization. Max-Sharpe: 1.948. Portfolio: return=4.52%, vol=0.27%. Weights: w_IVV=0.0031, w_DOT-USD=0.0000, w_SGOV=0.9969, w_MORT=0.0000.", "question": "Assets: IVV, DOT-USD, SGOV, MORT\nAnnualized mean returns: IVV:0.1249, DOT-USD:-0.3430, SGOV:0.0449, MORT:-0.7438\nCovariance matrix (annualized):\n[[0.023542, 0.016235, 4.4e-05, 0.035513], [0.016235, 0.331105, 0.000133, -0.013081], [4.4e-05, 0.000133, 7e-06, -5e-05], [0.035513, -0.013081, -5e-05, 0.089507]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0031, w_DOT-USD=0.0000, w_SGOV=0.9969, w_MORT=0.0000", "answer_numeric": 1.9477120562152783, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0031, w_DOT-USD=0.0000, w_SGOV=0.9969, w_MORT=0.0000\nPortfolio annualized return: 4.52%, volatility: 0.27%\nSharpe ratio: (0.0452 - 0.0400) / 0.0027 = 1.9477", "metadata": {"weights": {"IVV": 0.0031, "DOT-USD": 0.0, "SGOV": 0.9969, "MORT": 0.0}, "sharpe_ratio": 1.9477, "portfolio_return": 0.045195, "portfolio_vol": 0.002667, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230130_0082", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "BNDX", "REZ"], "decision_date": "2023-01-30", "context_summary": "4-asset optimization. Max-Sharpe: 0.516. Portfolio: return=14.96%, vol=21.25%. Weights: w_XLF=0.0000, w_BNB-USD=0.0000, w_BNDX=0.0000, w_REZ=1.0000.", "question": "Assets: XLF, BNB-USD, BNDX, REZ\nAnnualized mean returns: XLF:0.0297, BNB-USD:-0.5806, BNDX:-0.0293, REZ:0.1496\nCovariance matrix (annualized):\n[[0.027607, 0.033142, 0.001589, 0.023308], [0.033142, 0.197402, 0.000319, 0.050454], [0.001589, 0.000319, 0.003453, 0.004328], [0.023308, 0.050454, 0.004328, 0.045171]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_BNB-USD=0.0000, w_BNDX=0.0000, w_REZ=1.0000", "answer_numeric": 0.5158422278371357, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BNB-USD=0.0000, w_BNDX=0.0000, w_REZ=1.0000\nPortfolio annualized return: 14.96%, volatility: 21.25%\nSharpe ratio: (0.1496 - 0.0400) / 0.2125 = 0.5158", "metadata": {"weights": {"XLF": 0.0, "BNB-USD": 0.0, "BNDX": 0.0, "REZ": 1.0}, "sharpe_ratio": 0.5158, "portfolio_return": 0.149635, "portfolio_vol": 0.212535, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20230810_0084", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ADA-USD", "BIL", "GLD"], "decision_date": "2023-08-10", "context_summary": "4-asset optimization. Max-Sharpe: 4.906. Portfolio: return=5.21%, vol=0.25%. Weights: w_VLUE=0.0093, w_ADA-USD=0.0000, w_BIL=0.9907, w_GLD=0.0000.", "question": "Assets: VLUE, ADA-USD, BIL, GLD\nAnnualized mean returns: VLUE:0.2624, ADA-USD:0.9292, BIL:0.0501, GLD:-0.1407\nCovariance matrix (annualized):\n[[0.012541, 0.018811, -5e-06, 0.003925], [0.018811, 0.517135, 0.000418, 0.002443], [-5e-06, 0.000418, 5e-06, -6.5e-05], [0.003925, 0.002443, -6.5e-05, 0.00908]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0093, w_ADA-USD=0.0000, w_BIL=0.9907, w_GLD=0.0000", "answer_numeric": 4.905950809750415, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0093, w_ADA-USD=0.0000, w_BIL=0.9907, w_GLD=0.0000\nPortfolio annualized return: 5.21%, volatility: 0.25%\nSharpe ratio: (0.0521 - 0.0400) / 0.0025 = 4.9060", "metadata": {"weights": {"VLUE": 0.0093, "ADA-USD": 0.0, "BIL": 0.9907, "GLD": 0.0}, "sharpe_ratio": 4.906, "portfolio_return": 0.052086, "portfolio_vol": 0.002464, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231030_0086", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "MATIC-USD", "CORN", "CSHI"], "decision_date": "2023-10-30", "context_summary": "4-asset optimization. Max-Sharpe: 3.865. Portfolio: return=7.90%, vol=1.01%. Weights: w_^VIX=0.0098, w_MATIC-USD=0.0000, w_CORN=0.0000, w_CSHI=0.9902.", "question": "Assets: ^VIX, MATIC-USD, CORN, CSHI\nAnnualized mean returns: ^VIX:2.6236, MATIC-USD:-0.4830, CORN:0.0417, CSHI:0.0539\nCovariance matrix (annualized):\n[[0.980035, -0.045551, 0.003681, -0.00285], [-0.045551, 0.161832, -0.009345, 9.7e-05], [0.003681, -0.009345, 0.023144, -6e-06], [-0.00285, 9.7e-05, -6e-06, 6.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0098, w_MATIC-USD=0.0000, w_CORN=0.0000, w_CSHI=0.9902", "answer_numeric": 3.8654255598555842, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0098, w_MATIC-USD=0.0000, w_CORN=0.0000, w_CSHI=0.9902\nPortfolio annualized return: 7.90%, volatility: 1.01%\nSharpe ratio: (0.0790 - 0.0400) / 0.0101 = 3.8654", "metadata": {"weights": {"^VIX": 0.0098, "MATIC-USD": 0.0, "CORN": 0.0, "CSHI": 0.9902}, "sharpe_ratio": 3.8654, "portfolio_return": 0.078956, "portfolio_vol": 0.010078, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241129_0088", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLU", "XRP-USD", "SOYB", "SCHH"], "decision_date": "2024-11-29", "context_summary": "4-asset optimization. Max-Sharpe: 4.595. Portfolio: return=273.04%, vol=58.55%. Weights: w_XLU=0.3458, w_XRP-USD=0.6542, w_SOYB=0.0000, w_SCHH=0.0000.", "question": "Assets: XLU, XRP-USD, SOYB, SCHH\nAnnualized mean returns: XLU:0.1780, XRP-USD:4.0795, SOYB:-0.5095, SCHH:0.0740\nCovariance matrix (annualized):\n[[0.029305, 0.011389, 0.000166, 0.013748], [0.011389, 0.780779, -0.007016, -0.000223], [0.000166, -0.007016, 0.014838, 0.002125], [0.013748, -0.000223, 0.002125, 0.02177]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.3458, w_XRP-USD=0.6542, w_SOYB=0.0000, w_SCHH=0.0000", "answer_numeric": 4.594961369183884, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.3458, w_XRP-USD=0.6542, w_SOYB=0.0000, w_SCHH=0.0000\nPortfolio annualized return: 273.04%, volatility: 58.55%\nSharpe ratio: (2.7304 - 0.0400) / 0.5855 = 4.5950", "metadata": {"weights": {"XLU": 0.3458, "XRP-USD": 0.6542, "SOYB": 0.0, "SCHH": 0.0}, "sharpe_ratio": 4.595, "portfolio_return": 2.730396, "portfolio_vol": 0.58551, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230411_0090", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "SGOV", "IYR"], "decision_date": "2023-04-11", "context_summary": "4-asset optimization. Max-Sharpe: 3.115. Portfolio: return=4.77%, vol=0.25%. Weights: w_XLI=0.0000, w_BNB-USD=0.0000, w_SGOV=1.0000, w_IYR=0.0000.", "question": "Assets: XLI, BNB-USD, SGOV, IYR\nAnnualized mean returns: XLI:-0.1480, BNB-USD:-0.2464, SGOV:0.0477, IYR:-0.3986\nCovariance matrix (annualized):\n[[0.033423, 0.006346, -6.1e-05, 0.028414], [0.006346, 0.205907, 0.000216, 0.008639], [-6.1e-05, 0.000216, 6e-06, 8.7e-05], [0.028414, 0.008639, 8.7e-05, 0.05157]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_BNB-USD=0.0000, w_SGOV=1.0000, w_IYR=0.0000", "answer_numeric": 3.1152475566773603, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_BNB-USD=0.0000, w_SGOV=1.0000, w_IYR=0.0000\nPortfolio annualized return: 4.77%, volatility: 0.25%\nSharpe ratio: (0.0477 - 0.0400) / 0.0025 = 3.1152", "metadata": {"weights": {"XLI": 0.0, "BNB-USD": 0.0, "SGOV": 1.0, "IYR": 0.0}, "sharpe_ratio": 3.1152, "portfolio_return": 0.047722, "portfolio_vol": 0.002479, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231107_0092", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "LINK-USD", "CSHI", "SCHH"], "decision_date": "2023-11-07", "context_summary": "4-asset optimization. Max-Sharpe: 5.648. Portfolio: return=12.98%, vol=1.59%. Weights: w_QQQ=0.0000, w_LINK-USD=0.0251, w_CSHI=0.9749, w_SCHH=0.0000.", "question": "Assets: QQQ, LINK-USD, CSHI, SCHH\nAnnualized mean returns: QQQ:-0.0375, LINK-USD:2.5433, CSHI:0.0676, SCHH:-0.2853\nCovariance matrix (annualized):\n[[0.032657, -0.002587, 0.000503, 0.022231], [-0.002587, 0.283753, -8e-05, -0.004915], [0.000503, -8e-05, 8.2e-05, 0.000513], [0.022231, -0.004915, 0.000513, 0.051602]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0000, w_LINK-USD=0.0251, w_CSHI=0.9749, w_SCHH=0.0000", "answer_numeric": 5.648031777508437, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_LINK-USD=0.0251, w_CSHI=0.9749, w_SCHH=0.0000\nPortfolio annualized return: 12.98%, volatility: 1.59%\nSharpe ratio: (0.1298 - 0.0400) / 0.0159 = 5.6480", "metadata": {"weights": {"QQQ": 0.0, "LINK-USD": 0.0251, "CSHI": 0.9749, "SCHH": 0.0}, "sharpe_ratio": 5.648, "portfolio_return": 0.129826, "portfolio_vol": 0.015904, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240617_0094", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "DBC", "LQD"], "decision_date": "2024-06-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.091. Portfolio: return=24.27%, vol=6.56%. Weights: w_EWJ=0.0000, w_XRP-USD=0.0000, w_DBC=0.0000, w_LQD=1.0000.", "question": "Assets: EWJ, XRP-USD, DBC, LQD\nAnnualized mean returns: EWJ:0.0489, XRP-USD:0.0489, DBC:-0.0631, LQD:0.2427\nCovariance matrix (annualized):\n[[0.022647, 0.028615, 0.005733, 0.004813], [0.028615, 0.136919, 0.011481, 0.010896], [0.005733, 0.011481, 0.017252, -0.000125], [0.004813, 0.010896, -0.000125, 0.004302]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_XRP-USD=0.0000, w_DBC=0.0000, w_LQD=1.0000", "answer_numeric": 3.0908150346875174, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_XRP-USD=0.0000, w_DBC=0.0000, w_LQD=1.0000\nPortfolio annualized return: 24.27%, volatility: 6.56%\nSharpe ratio: (0.2427 - 0.0400) / 0.0656 = 3.0908", "metadata": {"weights": {"EWJ": 0.0, "XRP-USD": 0.0, "DBC": 0.0, "LQD": 1.0}, "sharpe_ratio": 3.0908, "portfolio_return": 0.242724, "portfolio_vol": 0.065589, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231201_0096", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "DOT-USD", "ITB", "SGOV"], "decision_date": "2023-12-01", "context_summary": "4-asset optimization. Max-Sharpe: 5.188. Portfolio: return=5.51%, vol=0.29%. Weights: w_XLU=0.0033, w_DOT-USD=0.0004, w_ITB=0.0031, w_SGOV=0.9933.", "question": "Assets: XLU, DOT-USD, ITB, SGOV\nAnnualized mean returns: XLU:0.3786, DOT-USD:0.1402, ITB:0.5541, SGOV:0.0524\nCovariance matrix (annualized):\n[[0.035541, -0.000482, 0.027381, -1e-05], [-0.000482, 0.331274, 0.013717, -0.000109], [0.027381, 0.013717, 0.075579, -4e-05], [-1e-05, -0.000109, -4e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0033, w_DOT-USD=0.0004, w_ITB=0.0031, w_SGOV=0.9933", "answer_numeric": 5.1878505269523245, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0033, w_DOT-USD=0.0004, w_ITB=0.0031, w_SGOV=0.9933\nPortfolio annualized return: 5.51%, volatility: 0.29%\nSharpe ratio: (0.0551 - 0.0400) / 0.0029 = 5.1879", "metadata": {"weights": {"XLU": 0.0033, "DOT-USD": 0.0004, "ITB": 0.0031, "SGOV": 0.9933}, "sharpe_ratio": 5.1879, "portfolio_return": 0.055085, "portfolio_vol": 0.002908, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231113_0098", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "SOL-USD", "ITB", "TIP"], "decision_date": "2023-11-13", "context_summary": "4-asset optimization. Max-Sharpe: 6.273. Portfolio: return=542.93%, vol=85.92%. Weights: w_XLRE=0.0000, w_SOL-USD=1.0000, w_ITB=0.0000, w_TIP=0.0000.", "question": "Assets: XLRE, SOL-USD, ITB, TIP\nAnnualized mean returns: XLRE:-0.2717, SOL-USD:5.4293, ITB:0.0148, TIP:0.0090\nCovariance matrix (annualized):\n[[0.055514, 0.015853, 0.049961, 0.002127], [0.015853, 0.738162, 0.063867, -0.001001], [0.049961, 0.063867, 0.078277, 0.003121], [0.002127, -0.001001, 0.003121, 0.000675]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_SOL-USD=1.0000, w_ITB=0.0000, w_TIP=0.0000", "answer_numeric": 6.272774481009459, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_SOL-USD=1.0000, w_ITB=0.0000, w_TIP=0.0000\nPortfolio annualized return: 542.93%, volatility: 85.92%\nSharpe ratio: (5.4293 - 0.0400) / 0.8592 = 6.2728", "metadata": {"weights": {"XLRE": 0.0, "SOL-USD": 1.0, "ITB": 0.0, "TIP": 0.0}, "sharpe_ratio": 6.2728, "portfolio_return": 5.42934, "portfolio_vol": 0.859164, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231116_0100", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "XHB", "TLH"], "decision_date": "2023-11-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.205. Portfolio: return=73.53%, vol=31.53%. Weights: w_FXI=0.0000, w_ETH-USD=0.7118, w_XHB=0.2882, w_TLH=0.0000.", "question": "Assets: FXI, ETH-USD, XHB, TLH\nAnnualized mean returns: FXI:0.0065, ETH-USD:0.9689, XHB:0.1582, TLH:-0.1480\nCovariance matrix (annualized):\n[[0.058248, 0.004138, 0.033578, 0.016474], [0.004138, 0.188532, -0.004847, -0.011428], [0.033578, -0.004847, 0.070598, 0.029756], [0.016474, -0.011428, 0.029756, 0.032776]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_ETH-USD=0.7118, w_XHB=0.2882, w_TLH=0.0000", "answer_numeric": 2.2053058727956834, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_ETH-USD=0.7118, w_XHB=0.2882, w_TLH=0.0000\nPortfolio annualized return: 73.53%, volatility: 31.53%\nSharpe ratio: (0.7353 - 0.0400) / 0.3153 = 2.2053", "metadata": {"weights": {"FXI": 0.0, "ETH-USD": 0.7118, "XHB": 0.2882, "TLH": 0.0}, "sharpe_ratio": 2.2053, "portfolio_return": 0.735295, "portfolio_vol": 0.315283, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241111_0102", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "PPLT", "SGOV"], "decision_date": "2024-11-11", "context_summary": "4-asset optimization. Max-Sharpe: 5.601. Portfolio: return=6.18%, vol=0.39%. Weights: w_XLV=0.0000, w_BTC-USD=0.0071, w_PPLT=0.0000, w_SGOV=0.9929.", "question": "Assets: XLV, BTC-USD, PPLT, SGOV\nAnnualized mean returns: XLV:-0.1780, BTC-USD:1.7158, PPLT:0.1112, SGOV:0.0499\nCovariance matrix (annualized):\n[[0.009107, 0.007764, 0.004361, 5.2e-05], [0.007764, 0.166359, 0.036517, -2.6e-05], [0.004361, 0.036517, 0.066069, 1.5e-05], [5.2e-05, -2.6e-05, 1.5e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_BTC-USD=0.0071, w_PPLT=0.0000, w_SGOV=0.9929", "answer_numeric": 5.601315406694838, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_BTC-USD=0.0071, w_PPLT=0.0000, w_SGOV=0.9929\nPortfolio annualized return: 6.18%, volatility: 0.39%\nSharpe ratio: (0.0618 - 0.0400) / 0.0039 = 5.6013", "metadata": {"weights": {"XLV": 0.0, "BTC-USD": 0.0071, "PPLT": 0.0, "SGOV": 0.9929}, "sharpe_ratio": 5.6013, "portfolio_return": 0.061769, "portfolio_vol": 0.003886, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240305_0103", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "XRP-USD", "PALL", "MORT"], "decision_date": "2024-03-05", "context_summary": "4-asset optimization. Max-Sharpe: 4.790. Portfolio: return=58.69%, vol=11.42%. Weights: w_SPY=0.9615, w_XRP-USD=0.0385, w_PALL=0.0000, w_MORT=0.0000.", "question": "Assets: SPY, XRP-USD, PALL, MORT\nAnnualized mean returns: SPY:0.5795, XRP-USD:0.7715, PALL:-0.5399, MORT:-0.1998\nCovariance matrix (annualized):\n[[0.012936, 0.010977, 0.005813, 0.016536], [0.010977, 0.178919, 0.030686, 0.038414], [0.005813, 0.030686, 0.137307, 0.038892], [0.016536, 0.038414, 0.038892, 0.061381]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.9615, w_XRP-USD=0.0385, w_PALL=0.0000, w_MORT=0.0000", "answer_numeric": 4.789596879403063, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.9615, w_XRP-USD=0.0385, w_PALL=0.0000, w_MORT=0.0000\nPortfolio annualized return: 58.69%, volatility: 11.42%\nSharpe ratio: (0.5869 - 0.0400) / 0.1142 = 4.7896", "metadata": {"weights": {"SPY": 0.9615, "XRP-USD": 0.0385, "PALL": 0.0, "MORT": 0.0}, "sharpe_ratio": 4.7896, "portfolio_return": 0.58687, "portfolio_vol": 0.114179, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241015_0107", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "CSHI", "HYG"], "decision_date": "2024-10-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.630. Portfolio: return=9.54%, vol=1.52%. Weights: w_XLV=0.0023, w_LINK-USD=0.0065, w_CSHI=0.6815, w_HYG=0.3097.", "question": "Assets: XLV, LINK-USD, CSHI, HYG\nAnnualized mean returns: XLV:0.1040, LINK-USD:1.1080, CSHI:0.0656, HYG:0.1393\nCovariance matrix (annualized):\n[[0.007178, 0.009584, -3e-05, 0.000679], [0.009584, 0.321783, 0.000736, 0.005999], [-3e-05, 0.000736, 0.000126, 5.5e-05], [0.000679, 0.005999, 5.5e-05, 0.001094]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0023, w_LINK-USD=0.0065, w_CSHI=0.6815, w_HYG=0.3097", "answer_numeric": 3.629792886701044, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0023, w_LINK-USD=0.0065, w_CSHI=0.6815, w_HYG=0.3097\nPortfolio annualized return: 9.54%, volatility: 1.52%\nSharpe ratio: (0.0954 - 0.0400) / 0.0152 = 3.6298", "metadata": {"weights": {"XLV": 0.0023, "LINK-USD": 0.0065, "CSHI": 0.6815, "HYG": 0.3097}, "sharpe_ratio": 3.6298, "portfolio_return": 0.095352, "portfolio_vol": 0.015249, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240701_0110", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "ITB", "STIP"], "decision_date": "2024-07-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.269. Portfolio: return=9.72%, vol=1.75%. Weights: w_EEM=0.0233, w_AVAX-USD=0.0000, w_ITB=0.0000, w_STIP=0.9767.", "question": "Assets: EEM, AVAX-USD, ITB, STIP\nAnnualized mean returns: EEM:0.2784, AVAX-USD:-0.1277, ITB:-0.1493, STIP:0.0928\nCovariance matrix (annualized):\n[[0.015692, 0.01472, 0.01375, 0.000932], [0.01472, 0.481991, 0.065261, 0.003717], [0.01375, 0.065261, 0.061188, 0.00173], [0.000932, 0.003717, 0.00173, 0.000267]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0233, w_AVAX-USD=0.0000, w_ITB=0.0000, w_STIP=0.9767", "answer_numeric": 3.2690977121135236, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0233, w_AVAX-USD=0.0000, w_ITB=0.0000, w_STIP=0.9767\nPortfolio annualized return: 9.72%, volatility: 1.75%\nSharpe ratio: (0.0972 - 0.0400) / 0.0175 = 3.2691", "metadata": {"weights": {"EEM": 0.0233, "AVAX-USD": 0.0, "ITB": 0.0, "STIP": 0.9767}, "sharpe_ratio": 3.2691, "portfolio_return": 0.097169, "portfolio_vol": 0.017488, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240313_0113", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "MATIC-USD", "VNQ", "SHY"], "decision_date": "2024-03-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.845. Portfolio: return=39.90%, vol=19.45%. Weights: w_XLY=0.7990, w_MATIC-USD=0.2010, w_VNQ=0.0000, w_SHY=0.0000.", "question": "Assets: XLY, MATIC-USD, VNQ, SHY\nAnnualized mean returns: XLY:0.2628, MATIC-USD:0.9404, VNQ:0.0176, SHY:-0.0065\nCovariance matrix (annualized):\n[[0.02487, 0.017978, 0.012412, 0.000447], [0.017978, 0.4008, 0.016605, 0.001428], [0.012412, 0.016605, 0.028751, 0.002043], [0.000447, 0.001428, 0.002043, 0.000345]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.7990, w_MATIC-USD=0.2010, w_VNQ=0.0000, w_SHY=0.0000", "answer_numeric": 1.8453380756971063, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.7990, w_MATIC-USD=0.2010, w_VNQ=0.0000, w_SHY=0.0000\nPortfolio annualized return: 39.90%, volatility: 19.45%\nSharpe ratio: (0.3990 - 0.0400) / 0.1945 = 1.8453", "metadata": {"weights": {"XLY": 0.799, "MATIC-USD": 0.201, "VNQ": 0.0, "SHY": 0.0}, "sharpe_ratio": 1.8453, "portfolio_return": 0.398956, "portfolio_vol": 0.194521, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230526_0116", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "CPER", "TLH"], "decision_date": "2023-05-26", "context_summary": "4-asset optimization. Max-Sharpe: 2.745. Portfolio: return=54.19%, vol=18.28%. Weights: w_XLK=0.8904, w_ADA-USD=0.1096, w_CPER=0.0000, w_TLH=0.0000.", "question": "Assets: XLK, ADA-USD, CPER, TLH\nAnnualized mean returns: XLK:0.5444, ADA-USD:0.5220, CPER:-0.6488, TLH:-0.2604\nCovariance matrix (annualized):\n[[0.036171, 0.012579, 0.015288, -0.006196], [0.012579, 0.190638, 0.006923, 0.01162], [0.015288, 0.006923, 0.039359, -0.011226], [-0.006196, 0.01162, -0.011226, 0.01699]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.8904, w_ADA-USD=0.1096, w_CPER=0.0000, w_TLH=0.0000", "answer_numeric": 2.7454268037048735, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.8904, w_ADA-USD=0.1096, w_CPER=0.0000, w_TLH=0.0000\nPortfolio annualized return: 54.19%, volatility: 18.28%\nSharpe ratio: (0.5419 - 0.0400) / 0.1828 = 2.7454", "metadata": {"weights": {"XLK": 0.8904, "ADA-USD": 0.1096, "CPER": 0.0, "TLH": 0.0}, "sharpe_ratio": 2.7454, "portfolio_return": 0.541912, "portfolio_vol": 0.182818, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230727_0118", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BNB-USD", "DBB", "IEF"], "decision_date": "2023-07-27", "context_summary": "4-asset optimization. Max-Sharpe: 2.586. Portfolio: return=39.56%, vol=13.75%. Weights: w_XLU=0.8986, w_BNB-USD=0.0000, w_DBB=0.1014, w_IEF=0.0000.", "question": "Assets: XLU, BNB-USD, DBB, IEF\nAnnualized mean returns: XLU:0.4115, BNB-USD:-0.6732, DBB:0.2546, IEF:-0.0038\nCovariance matrix (annualized):\n[[0.020897, -0.004099, 0.009638, -0.000507], [-0.004099, 0.205701, 0.011164, 0.007082], [0.009638, 0.011164, 0.027101, 0.000896], [-0.000507, 0.007082, 0.000896, 0.006634]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.8986, w_BNB-USD=0.0000, w_DBB=0.1014, w_IEF=0.0000", "answer_numeric": 2.586173232118758, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.8986, w_BNB-USD=0.0000, w_DBB=0.1014, w_IEF=0.0000\nPortfolio annualized return: 39.56%, volatility: 13.75%\nSharpe ratio: (0.3956 - 0.0400) / 0.1375 = 2.5862", "metadata": {"weights": {"XLU": 0.8986, "BNB-USD": 0.0, "DBB": 0.1014, "IEF": 0.0}, "sharpe_ratio": 2.5862, "portfolio_return": 0.395626, "portfolio_vol": 0.13751, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230627_0121", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "DBA", "CSHI"], "decision_date": "2023-06-27", "context_summary": "4-asset optimization. Max-Sharpe: 2.067. Portfolio: return=6.35%, vol=1.14%. Weights: w_XLE=0.0000, w_ADA-USD=0.0000, w_DBA=0.0450, w_CSHI=0.9550.", "question": "Assets: XLE, ADA-USD, DBA, CSHI\nAnnualized mean returns: XLE:-0.3386, ADA-USD:-1.3999, DBA:0.1664, CSHI:0.0587\nCovariance matrix (annualized):\n[[0.059069, -0.005993, 0.01299, 0.00026], [-0.005993, 0.231966, 0.013012, -0.000951], [0.01299, 0.013012, 0.018852, -0.00016], [0.00026, -0.000951, -0.00016, 0.000115]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_ADA-USD=0.0000, w_DBA=0.0450, w_CSHI=0.9550", "answer_numeric": 2.067405966611675, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_ADA-USD=0.0000, w_DBA=0.0450, w_CSHI=0.9550\nPortfolio annualized return: 6.35%, volatility: 1.14%\nSharpe ratio: (0.0635 - 0.0400) / 0.0114 = 2.0674", "metadata": {"weights": {"XLE": 0.0, "ADA-USD": 0.0, "DBA": 0.045, "CSHI": 0.955}, "sharpe_ratio": 2.0674, "portfolio_return": 0.063549, "portfolio_vol": 0.011391, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240819_0124", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "ICSH", "SHV"], "decision_date": "2024-08-19", "context_summary": "4-asset optimization. Max-Sharpe: 7.302. Portfolio: return=6.29%, vol=0.31%. Weights: w_QUAL=0.0007, w_ADA-USD=0.0008, w_ICSH=0.5444, w_SHV=0.4541.", "question": "Assets: QUAL, ADA-USD, ICSH, SHV\nAnnualized mean returns: QUAL:0.0509, ADA-USD:0.3730, ICSH:0.0701, SHV:0.0537\nCovariance matrix (annualized):\n[[0.029937, 0.042472, -9.3e-05, 0.0], [0.042472, 0.34603, -0.0005, 0.000215], [-9.3e-05, -0.0005, 2.1e-05, 5e-06], [0.0, 0.000215, 5e-06, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0007, w_ADA-USD=0.0008, w_ICSH=0.5444, w_SHV=0.4541", "answer_numeric": 7.302254892736328, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0007, w_ADA-USD=0.0008, w_ICSH=0.5444, w_SHV=0.4541\nPortfolio annualized return: 6.29%, volatility: 0.31%\nSharpe ratio: (0.0629 - 0.0400) / 0.0031 = 7.3023", "metadata": {"weights": {"QUAL": 0.0007, "ADA-USD": 0.0008, "ICSH": 0.5444, "SHV": 0.4541}, "sharpe_ratio": 7.3023, "portfolio_return": 0.062932, "portfolio_vol": 0.00314, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230102_0126", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "MORT", "PPLT"], "decision_date": "2023-01-02", "context_summary": "4-asset optimization. Max-Sharpe: 2.294. Portfolio: return=78.10%, vol=32.31%. Weights: w_XLB=0.0000, w_BNB-USD=0.0000, w_MORT=0.0000, w_PPLT=1.0000.", "question": "Assets: XLB, BNB-USD, MORT, PPLT\nAnnualized mean returns: XLB:0.3470, BNB-USD:-1.0684, MORT:0.0316, PPLT:0.7810\nCovariance matrix (annualized):\n[[0.049703, 0.099525, 0.045141, 0.043375], [0.099525, 0.651454, 0.081185, 0.112356], [0.045141, 0.081185, 0.074932, 0.053374], [0.043375, 0.112356, 0.053374, 0.104383]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_BNB-USD=0.0000, w_MORT=0.0000, w_PPLT=1.0000", "answer_numeric": 2.2936318610624076, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_BNB-USD=0.0000, w_MORT=0.0000, w_PPLT=1.0000\nPortfolio annualized return: 78.10%, volatility: 32.31%\nSharpe ratio: (0.7810 - 0.0400) / 0.3231 = 2.2936", "metadata": {"weights": {"XLB": 0.0, "BNB-USD": 0.0, "MORT": 0.0, "PPLT": 1.0}, "sharpe_ratio": 2.2936, "portfolio_return": 0.781034, "portfolio_vol": 0.323083, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240702_0129", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "BNDX", "MORT"], "decision_date": "2024-07-02", "context_summary": "4-asset optimization. Max-Sharpe: 2.903. Portfolio: return=26.20%, vol=7.65%. Weights: w_USMV=1.0000, w_XRP-USD=0.0000, w_BNDX=0.0000, w_MORT=0.0000.", "question": "Assets: USMV, XRP-USD, BNDX, MORT\nAnnualized mean returns: USMV:0.2620, XRP-USD:-0.3199, BNDX:0.0137, MORT:0.0739\nCovariance matrix (annualized):\n[[0.005848, 0.003881, 0.001139, 0.006409], [0.003881, 0.106369, 0.00336, 0.009996], [0.001139, 0.00336, 0.001717, 0.002615], [0.006409, 0.009996, 0.002615, 0.026223]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=1.0000, w_XRP-USD=0.0000, w_BNDX=0.0000, w_MORT=0.0000", "answer_numeric": 2.902599996499464, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=1.0000, w_XRP-USD=0.0000, w_BNDX=0.0000, w_MORT=0.0000\nPortfolio annualized return: 26.20%, volatility: 7.65%\nSharpe ratio: (0.2620 - 0.0400) / 0.0765 = 2.9026", "metadata": {"weights": {"USMV": 1.0, "XRP-USD": 0.0, "BNDX": 0.0, "MORT": 0.0}, "sharpe_ratio": 2.9026, "portfolio_return": 0.261964, "portfolio_vol": 0.076471, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240814_0131", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "BIL", "DBB"], "decision_date": "2024-08-14", "context_summary": "4-asset optimization. Max-Sharpe: 5.231. Portfolio: return=5.19%, vol=0.23%. Weights: w_XLB=0.0007, w_ADA-USD=0.0000, w_BIL=0.9993, w_DBB=0.0000.", "question": "Assets: XLB, ADA-USD, BIL, DBB\nAnnualized mean returns: XLB:0.0349, ADA-USD:0.0536, BIL:0.0519, DBB:-0.3772\nCovariance matrix (annualized):\n[[0.024145, 0.032212, -1.9e-05, 0.00773], [0.032212, 0.367974, 0.00018, 0.009842], [-1.9e-05, 0.00018, 5e-06, 7.7e-05], [0.00773, 0.009842, 7.7e-05, 0.024241]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0007, w_ADA-USD=0.0000, w_BIL=0.9993, w_DBB=0.0000", "answer_numeric": 5.2308368727264085, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0007, w_ADA-USD=0.0000, w_BIL=0.9993, w_DBB=0.0000\nPortfolio annualized return: 5.19%, volatility: 0.23%\nSharpe ratio: (0.0519 - 0.0400) / 0.0023 = 5.2308", "metadata": {"weights": {"XLB": 0.0007, "ADA-USD": 0.0, "BIL": 0.9993, "DBB": 0.0}, "sharpe_ratio": 5.2308, "portfolio_return": 0.05186, "portfolio_vol": 0.002267, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231121_0133", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "HYG", "ICSH"], "decision_date": "2023-11-21", "context_summary": "4-asset optimization. Max-Sharpe: 5.868. Portfolio: return=6.96%, vol=0.50%. Weights: w_EWJ=0.0000, w_AVAX-USD=0.0041, w_HYG=0.0000, w_ICSH=0.9959.", "question": "Assets: EWJ, AVAX-USD, HYG, ICSH\nAnnualized mean returns: EWJ:0.0707, AVAX-USD:2.7716, HYG:0.1456, ICSH:0.0585\nCovariance matrix (annualized):\n[[0.029284, -0.003584, 0.007626, 0.000116], [-0.003584, 0.797132, 0.010387, -0.000926], [0.007626, 0.010387, 0.00589, 0.0001], [0.000116, -0.000926, 0.0001, 2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_AVAX-USD=0.0041, w_HYG=0.0000, w_ICSH=0.9959", "answer_numeric": 5.86824227640205, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_AVAX-USD=0.0041, w_HYG=0.0000, w_ICSH=0.9959\nPortfolio annualized return: 6.96%, volatility: 0.50%\nSharpe ratio: (0.0696 - 0.0400) / 0.0050 = 5.8682", "metadata": {"weights": {"EWJ": 0.0, "AVAX-USD": 0.0041, "HYG": 0.0, "ICSH": 0.9959}, "sharpe_ratio": 5.8682, "portfolio_return": 0.069613, "portfolio_vol": 0.005046, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230110_0135", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "WEAT", "TIP"], "decision_date": "2023-01-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.714. Portfolio: return=73.58%, vol=97.48%. Weights: w_XLF=0.0000, w_SOL-USD=1.0000, w_WEAT=0.0000, w_TIP=0.0000.", "question": "Assets: XLF, SOL-USD, WEAT, TIP\nAnnualized mean returns: XLF:-0.0198, SOL-USD:0.7358, WEAT:-0.6257, TIP:0.0079\nCovariance matrix (annualized):\n[[0.027447, 0.019603, 0.008688, 0.002604], [0.019603, 0.950143, -0.020593, 0.0047], [0.008688, -0.020593, 0.052942, 0.001703], [0.002604, 0.0047, 0.001703, 0.000923]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_SOL-USD=1.0000, w_WEAT=0.0000, w_TIP=0.0000", "answer_numeric": 0.7138453970383359, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_SOL-USD=1.0000, w_WEAT=0.0000, w_TIP=0.0000\nPortfolio annualized return: 73.58%, volatility: 97.48%\nSharpe ratio: (0.7358 - 0.0400) / 0.9748 = 0.7138", "metadata": {"weights": {"XLF": 0.0, "SOL-USD": 1.0, "WEAT": 0.0, "TIP": 0.0}, "sharpe_ratio": 0.7138, "portfolio_return": 0.735823, "portfolio_vol": 0.974753, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240510_0137", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "XRP-USD", "EMB", "VNQ"], "decision_date": "2024-05-10", "context_summary": "4-asset optimization. Max-Sharpe: -0.626. Portfolio: return=-40.31%, vol=70.73%. Weights: w_XLV=0.0000, w_XRP-USD=1.0000, w_EMB=0.0000, w_VNQ=0.0000.", "question": "Assets: XLV, XRP-USD, EMB, VNQ\nAnnualized mean returns: XLV:-0.1055, XRP-USD:-0.4031, EMB:0.0309, VNQ:-0.2047\nCovariance matrix (annualized):\n[[0.010592, 0.005022, 0.003671, 0.01227], [0.005022, 0.500311, 0.008684, 0.022424], [0.003671, 0.008684, 0.006648, 0.010034], [0.01227, 0.022424, 0.010034, 0.032141]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_XRP-USD=1.0000, w_EMB=0.0000, w_VNQ=0.0000", "answer_numeric": -0.626393766884525, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_XRP-USD=1.0000, w_EMB=0.0000, w_VNQ=0.0000\nPortfolio annualized return: -40.31%, volatility: 70.73%\nSharpe ratio: (-0.4031 - 0.0400) / 0.7073 = -0.6264", "metadata": {"weights": {"XLV": 0.0, "XRP-USD": 1.0, "EMB": 0.0, "VNQ": 0.0}, "sharpe_ratio": -0.6264, "portfolio_return": -0.403065, "portfolio_vol": 0.707327, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230227_0139", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "DOT-USD", "PDBC", "ITB"], "decision_date": "2023-02-27", "context_summary": "4-asset optimization. Max-Sharpe: 3.807. Portfolio: return=130.70%, vol=33.28%. Weights: w_XLRE=0.0000, w_DOT-USD=0.3427, w_PDBC=0.0000, w_ITB=0.6573.", "question": "Assets: XLRE, DOT-USD, PDBC, ITB\nAnnualized mean returns: XLRE:0.2614, DOT-USD:2.3264, PDBC:-0.2071, ITB:0.7755\nCovariance matrix (annualized):\n[[0.049235, 0.040547, 0.008244, 0.047899], [0.040547, 0.511693, 0.014027, 0.037384], [0.008244, 0.014027, 0.035244, 0.005078], [0.047899, 0.037384, 0.005078, 0.078347]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_DOT-USD=0.3427, w_PDBC=0.0000, w_ITB=0.6573", "answer_numeric": 3.8065855609377715, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_DOT-USD=0.3427, w_PDBC=0.0000, w_ITB=0.6573\nPortfolio annualized return: 130.70%, volatility: 33.28%\nSharpe ratio: (1.3070 - 0.0400) / 0.3328 = 3.8066", "metadata": {"weights": {"XLRE": 0.0, "DOT-USD": 0.3427, "PDBC": 0.0, "ITB": 0.6573}, "sharpe_ratio": 3.8066, "portfolio_return": 1.306963, "portfolio_vol": 0.332834, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240104_0142", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD", "CSHI", "HAUZ"], "decision_date": "2024-01-04", "context_summary": "4-asset optimization. Max-Sharpe: 5.744. Portfolio: return=10.34%, vol=1.10%. Weights: w_VEA=0.0590, w_AVAX-USD=0.0056, w_CSHI=0.9354, w_HAUZ=0.0000.", "question": "Assets: VEA, AVAX-USD, CSHI, HAUZ\nAnnualized mean returns: VEA:0.4662, AVAX-USD:3.6243, CSHI:0.0594, HAUZ:0.3946\nCovariance matrix (annualized):\n[[0.015042, 0.01445, -0.00016, 0.01706], [0.01445, 1.220481, -0.000875, 0.009321], [-0.00016, -0.000875, 5.5e-05, -0.000139], [0.01706, 0.009321, -0.000139, 0.02727]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0590, w_AVAX-USD=0.0056, w_CSHI=0.9354, w_HAUZ=0.0000", "answer_numeric": 5.744239095339484, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0590, w_AVAX-USD=0.0056, w_CSHI=0.9354, w_HAUZ=0.0000\nPortfolio annualized return: 10.34%, volatility: 1.10%\nSharpe ratio: (0.1034 - 0.0400) / 0.0110 = 5.7442", "metadata": {"weights": {"VEA": 0.059, "AVAX-USD": 0.0056, "CSHI": 0.9354, "HAUZ": 0.0}, "sharpe_ratio": 5.7442, "portfolio_return": 0.103354, "portfolio_vol": 0.011029, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230807_0145", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "BIL", "SHY"], "decision_date": "2023-08-07", "context_summary": "4-asset optimization. Max-Sharpe: 5.682. Portfolio: return=5.39%, vol=0.24%. Weights: w_EEM=0.0022, w_AVAX-USD=0.0005, w_BIL=0.9973, w_SHY=0.0000.", "question": "Assets: EEM, AVAX-USD, BIL, SHY\nAnnualized mean returns: EEM:0.1797, AVAX-USD:0.4150, BIL:0.0534, SHY:0.0156\nCovariance matrix (annualized):\n[[0.029579, 0.002083, -6e-06, 0.001024], [0.002083, 0.225124, 5.5e-05, 0.000385], [-6e-06, 5.5e-05, 6e-06, 1e-06], [0.001024, 0.000385, 1e-06, 0.000451]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0022, w_AVAX-USD=0.0005, w_BIL=0.9973, w_SHY=0.0000", "answer_numeric": 5.681930783020436, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0022, w_AVAX-USD=0.0005, w_BIL=0.9973, w_SHY=0.0000\nPortfolio annualized return: 5.39%, volatility: 0.24%\nSharpe ratio: (0.0539 - 0.0400) / 0.0024 = 5.6819", "metadata": {"weights": {"EEM": 0.0022, "AVAX-USD": 0.0005, "BIL": 0.9973, "SHY": 0.0}, "sharpe_ratio": 5.6819, "portfolio_return": 0.053879, "portfolio_vol": 0.002443, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20240325_0147", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "ADA-USD", "SHV", "CPER"], "decision_date": "2024-03-25", "context_summary": "4-asset optimization. Max-Sharpe: 5.894. Portfolio: return=9.55%, vol=0.94%. Weights: w_XLE=0.0478, w_ADA-USD=0.0050, w_SHV=0.9472, w_CPER=0.0000.", "question": "Assets: XLE, ADA-USD, SHV, CPER\nAnnualized mean returns: XLE:0.7992, ADA-USD:1.9725, SHV:0.0500, CPER:0.2338\nCovariance matrix (annualized):\n[[0.022265, 0.003467, 0.000139, 0.007702], [0.003467, 0.530278, 0.000269, 0.029803], [0.000139, 0.000269, 9e-06, 1.1e-05], [0.007702, 0.029803, 1.1e-05, 0.027374]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0478, w_ADA-USD=0.0050, w_SHV=0.9472, w_CPER=0.0000", "answer_numeric": 5.894488533806144, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0478, w_ADA-USD=0.0050, w_SHV=0.9472, w_CPER=0.0000\nPortfolio annualized return: 9.55%, volatility: 0.94%\nSharpe ratio: (0.0955 - 0.0400) / 0.0094 = 5.8945", "metadata": {"weights": {"XLE": 0.0478, "ADA-USD": 0.005, "SHV": 0.9472, "CPER": 0.0}, "sharpe_ratio": 5.8945, "portfolio_return": 0.095476, "portfolio_vol": 0.009411, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240101_0149", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "SGOV", "PALL"], "decision_date": "2024-01-01", "context_summary": "4-asset optimization. Max-Sharpe: 8.793. Portfolio: return=7.35%, vol=0.38%. Weights: w_USMV=0.0277, w_BTC-USD=0.0052, w_SGOV=0.9671, w_PALL=0.0000.", "question": "Assets: USMV, BTC-USD, SGOV, PALL\nAnnualized mean returns: USMV:0.5241, BTC-USD:1.0813, SGOV:0.0551, PALL:-0.2332\nCovariance matrix (annualized):\n[[0.008525, -0.007703, 1.5e-05, 0.005298], [-0.007703, 0.180488, -0.000292, -0.062367], [1.5e-05, -0.000292, 8e-06, 0.000205], [0.005298, -0.062367, 0.000205, 0.180194]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0277, w_BTC-USD=0.0052, w_SGOV=0.9671, w_PALL=0.0000", "answer_numeric": 8.793161852170604, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0277, w_BTC-USD=0.0052, w_SGOV=0.9671, w_PALL=0.0000\nPortfolio annualized return: 7.35%, volatility: 0.38%\nSharpe ratio: (0.0735 - 0.0400) / 0.0038 = 8.7932", "metadata": {"weights": {"USMV": 0.0277, "BTC-USD": 0.0052, "SGOV": 0.9671, "PALL": 0.0}, "sharpe_ratio": 8.7932, "portfolio_return": 0.073473, "portfolio_vol": 0.003807, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230811_0152", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ETH-USD", "PPLT", "ITB"], "decision_date": "2023-08-11", "context_summary": "4-asset optimization. Max-Sharpe: 2.957. Portfolio: return=56.09%, vol=17.62%. Weights: w_VTI=0.1764, w_ETH-USD=0.0364, w_PPLT=0.0000, w_ITB=0.7872.", "question": "Assets: VTI, ETH-USD, PPLT, ITB\nAnnualized mean returns: VTI:0.2453, ETH-USD:0.4590, PPLT:-0.5986, ITB:0.6364\nCovariance matrix (annualized):\n[[0.010373, 0.007264, 0.009549, 0.012877], [0.007264, 0.128177, 0.0101, 0.024156], [0.009549, 0.0101, 0.048904, 0.016477], [0.012877, 0.024156, 0.016477, 0.041137]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.1764, w_ETH-USD=0.0364, w_PPLT=0.0000, w_ITB=0.7872", "answer_numeric": 2.9569987267793043, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.1764, w_ETH-USD=0.0364, w_PPLT=0.0000, w_ITB=0.7872\nPortfolio annualized return: 56.09%, volatility: 17.62%\nSharpe ratio: (0.5609 - 0.0400) / 0.1762 = 2.9570", "metadata": {"weights": {"VTI": 0.1764, "ETH-USD": 0.0364, "PPLT": 0.0, "ITB": 0.7872}, "sharpe_ratio": 2.957, "portfolio_return": 0.560944, "portfolio_vol": 0.176173, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241211_0155", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "XRP-USD", "IYR", "IEF"], "decision_date": "2024-12-11", "context_summary": "4-asset optimization. Max-Sharpe: 5.534. Portfolio: return=431.25%, vol=77.21%. Weights: w_XLE=0.0000, w_XRP-USD=0.6955, w_IYR=0.3045, w_IEF=0.0000.", "question": "Assets: XLE, XRP-USD, IYR, IEF\nAnnualized mean returns: XLE:-0.1719, XRP-USD:6.2149, IYR:-0.0318, IEF:-0.0304\nCovariance matrix (annualized):\n[[0.033335, 0.025274, -0.004437, -0.004677], [0.025274, 1.250292, -0.026038, 0.002578], [-0.004437, -0.026038, 0.02656, 0.006919], [-0.004677, 0.002578, 0.006919, 0.004063]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_XRP-USD=0.6955, w_IYR=0.3045, w_IEF=0.0000", "answer_numeric": 5.533537995625356, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_XRP-USD=0.6955, w_IYR=0.3045, w_IEF=0.0000\nPortfolio annualized return: 431.25%, volatility: 77.21%\nSharpe ratio: (4.3125 - 0.0400) / 0.7721 = 5.5335", "metadata": {"weights": {"XLE": 0.0, "XRP-USD": 0.6955, "IYR": 0.3045, "IEF": 0.0}, "sharpe_ratio": 5.5335, "portfolio_return": 4.3125, "portfolio_vol": 0.77211, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240222_0157", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "BIL", "PPLT"], "decision_date": "2024-02-22", "context_summary": "4-asset optimization. Max-Sharpe: 5.969. Portfolio: return=5.89%, vol=0.32%. Weights: w_XLU=0.0000, w_ETH-USD=0.0038, w_BIL=0.9962, w_PPLT=0.0000.", "question": "Assets: XLU, ETH-USD, BIL, PPLT\nAnnualized mean returns: XLU:-0.0643, ETH-USD:1.6932, BIL:0.0527, PPLT:-0.5987\nCovariance matrix (annualized):\n[[0.027743, 0.00975, 0.000103, 0.005172], [0.00975, 0.268827, -0.000149, 0.013938], [0.000103, -0.000149, 7e-06, 0.000104], [0.005172, 0.013938, 0.000104, 0.04531]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_ETH-USD=0.0038, w_BIL=0.9962, w_PPLT=0.0000", "answer_numeric": 5.969182698950704, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_ETH-USD=0.0038, w_BIL=0.9962, w_PPLT=0.0000\nPortfolio annualized return: 5.89%, volatility: 0.32%\nSharpe ratio: (0.0589 - 0.0400) / 0.0032 = 5.9692", "metadata": {"weights": {"XLU": 0.0, "ETH-USD": 0.0038, "BIL": 0.9962, "PPLT": 0.0}, "sharpe_ratio": 5.9692, "portfolio_return": 0.058936, "portfolio_vol": 0.003172, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240425_0160", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BNB-USD", "INDS", "TLH"], "decision_date": "2024-04-25", "context_summary": "4-asset optimization. Max-Sharpe: 3.338. Portfolio: return=257.58%, vol=75.98%. Weights: w_USMV=0.0000, w_BNB-USD=1.0000, w_INDS=0.0000, w_TLH=0.0000.", "question": "Assets: USMV, BNB-USD, INDS, TLH\nAnnualized mean returns: USMV:-0.0063, BNB-USD:2.5758, INDS:-0.4750, TLH:-0.2040\nCovariance matrix (annualized):\n[[0.005473, 0.005187, 0.009505, 0.00183], [0.005187, 0.577238, 0.021511, 0.000741], [0.009505, 0.021511, 0.033581, 0.009673], [0.00183, 0.000741, 0.009673, 0.011619]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_BNB-USD=1.0000, w_INDS=0.0000, w_TLH=0.0000", "answer_numeric": 3.337658097781551, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_BNB-USD=1.0000, w_INDS=0.0000, w_TLH=0.0000\nPortfolio annualized return: 257.58%, volatility: 75.98%\nSharpe ratio: (2.5758 - 0.0400) / 0.7598 = 3.3377", "metadata": {"weights": {"USMV": 0.0, "BNB-USD": 1.0, "INDS": 0.0, "TLH": 0.0}, "sharpe_ratio": 3.3377, "portfolio_return": 2.575826, "portfolio_vol": 0.759762, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240430_0163", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SOL-USD", "REZ", "DBA"], "decision_date": "2024-04-30", "context_summary": "4-asset optimization. Max-Sharpe: 4.602. Portfolio: return=67.25%, vol=13.74%. Weights: w_EFA=0.1579, w_SOL-USD=0.0000, w_REZ=0.0854, w_DBA=0.7567.", "question": "Assets: EFA, SOL-USD, REZ, DBA\nAnnualized mean returns: EFA:0.0798, SOL-USD:-0.6816, REZ:0.1798, DBA:0.8518\nCovariance matrix (annualized):\n[[0.011551, 0.033666, 0.012217, -0.002217], [0.033666, 0.748161, 0.020898, 0.023086], [0.012217, 0.020898, 0.034557, -0.000934], [-0.002217, 0.023086, -0.000934, 0.032603]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.1579, w_SOL-USD=0.0000, w_REZ=0.0854, w_DBA=0.7567", "answer_numeric": 4.602250019738589, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.1579, w_SOL-USD=0.0000, w_REZ=0.0854, w_DBA=0.7567\nPortfolio annualized return: 67.25%, volatility: 13.74%\nSharpe ratio: (0.6725 - 0.0400) / 0.1374 = 4.6023", "metadata": {"weights": {"EFA": 0.1579, "SOL-USD": 0.0, "REZ": 0.0854, "DBA": 0.7567}, "sharpe_ratio": 4.6023, "portfolio_return": 0.672484, "portfolio_vol": 0.137429, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230915_0166", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "VNQI", "CPER"], "decision_date": "2023-09-15", "context_summary": "4-asset optimization. Max-Sharpe: -0.988. Portfolio: return=-14.70%, vol=18.93%. Weights: w_XLI=0.0000, w_BNB-USD=0.0000, w_VNQI=0.0000, w_CPER=1.0000.", "question": "Assets: XLI, BNB-USD, VNQI, CPER\nAnnualized mean returns: XLI:-0.1642, BNB-USD:-0.7629, VNQI:-0.1444, CPER:-0.1470\nCovariance matrix (annualized):\n[[0.011477, 0.007466, 0.006875, 0.007267], [0.007466, 0.074698, 0.008884, -0.007539], [0.006875, 0.008884, 0.01353, 0.010604], [0.007267, -0.007539, 0.010604, 0.035833]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_BNB-USD=0.0000, w_VNQI=0.0000, w_CPER=1.0000", "answer_numeric": -0.9878763532384424, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_BNB-USD=0.0000, w_VNQI=0.0000, w_CPER=1.0000\nPortfolio annualized return: -14.70%, volatility: 18.93%\nSharpe ratio: (-0.1470 - 0.0400) / 0.1893 = -0.9879", "metadata": {"weights": {"XLI": 0.0, "BNB-USD": 0.0, "VNQI": 0.0, "CPER": 1.0}, "sharpe_ratio": -0.9879, "portfolio_return": -0.147, "portfolio_vol": 0.189295, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230912_0169", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "MORT", "SHV"], "decision_date": "2023-09-12", "context_summary": "4-asset optimization. Max-Sharpe: -3.150. Portfolio: return=-47.12%, vol=16.23%. Weights: w_XLF=0.2500, w_SOL-USD=0.2500, w_MORT=0.2500, w_SHV=0.2500.", "question": "Assets: XLF, SOL-USD, MORT, SHV\nAnnualized mean returns: XLF:-0.0036, SOL-USD:-1.8939, MORT:-0.0380, SHV:0.0506\nCovariance matrix (annualized):\n[[0.012985, 0.002578, 0.012341, -3.6e-05], [0.002578, 0.292831, 0.024437, -0.000112], [0.012341, 0.024437, 0.037444, -7.8e-05], [-3.6e-05, -0.000112, -7.8e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.2500, w_SOL-USD=0.2500, w_MORT=0.2500, w_SHV=0.2500", "answer_numeric": -3.149517963519294, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.2500, w_SOL-USD=0.2500, w_MORT=0.2500, w_SHV=0.2500\nPortfolio annualized return: -47.12%, volatility: 16.23%\nSharpe ratio: (-0.4712 - 0.0400) / 0.1623 = -3.1495", "metadata": {"weights": {"XLF": 0.25, "SOL-USD": 0.25, "MORT": 0.25, "SHV": 0.25}, "sharpe_ratio": -3.1495, "portfolio_return": -0.471206, "portfolio_vol": 0.162313, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240827_0172", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "MATIC-USD", "INDS", "PALL"], "decision_date": "2024-08-27", "context_summary": "4-asset optimization. Max-Sharpe: 4.565. Portfolio: return=58.18%, vol=11.87%. Weights: w_USMV=0.6352, w_MATIC-USD=0.0000, w_INDS=0.3648, w_PALL=0.0000.", "question": "Assets: USMV, MATIC-USD, INDS, PALL\nAnnualized mean returns: USMV:0.4422, MATIC-USD:0.3426, INDS:0.8248, PALL:0.2213\nCovariance matrix (annualized):\n[[0.00906, 0.028663, 0.012893, 0.015667], [0.028663, 0.52484, 0.037668, 0.071688], [0.012893, 0.037668, 0.033484, 0.022639], [0.015667, 0.071688, 0.022639, 0.120339]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.6352, w_MATIC-USD=0.0000, w_INDS=0.3648, w_PALL=0.0000", "answer_numeric": 4.564699293468499, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.6352, w_MATIC-USD=0.0000, w_INDS=0.3648, w_PALL=0.0000\nPortfolio annualized return: 58.18%, volatility: 11.87%\nSharpe ratio: (0.5818 - 0.0400) / 0.1187 = 4.5647", "metadata": {"weights": {"USMV": 0.6352, "MATIC-USD": 0.0, "INDS": 0.3648, "PALL": 0.0}, "sharpe_ratio": 4.5647, "portfolio_return": 0.581783, "portfolio_vol": 0.11869, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241010_0174", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "SOL-USD", "DBB", "LQD"], "decision_date": "2024-10-10", "context_summary": "4-asset optimization. Max-Sharpe: 3.046. Portfolio: return=32.40%, vol=9.32%. Weights: w_XLRE=0.5657, w_SOL-USD=0.0000, w_DBB=0.3185, w_LQD=0.1158.", "question": "Assets: XLRE, SOL-USD, DBB, LQD\nAnnualized mean returns: XLRE:0.2589, SOL-USD:-0.1809, DBB:0.5162, LQD:0.1127\nCovariance matrix (annualized):\n[[0.011196, 0.008953, 0.000323, 0.00229], [0.008953, 0.275058, 0.052279, 0.006049], [0.000323, 0.052279, 0.044537, 0.001814], [0.00229, 0.006049, 0.001814, 0.003043]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.5657, w_SOL-USD=0.0000, w_DBB=0.3185, w_LQD=0.1158", "answer_numeric": 3.045766078016297, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.5657, w_SOL-USD=0.0000, w_DBB=0.3185, w_LQD=0.1158\nPortfolio annualized return: 32.40%, volatility: 9.32%\nSharpe ratio: (0.3240 - 0.0400) / 0.0932 = 3.0458", "metadata": {"weights": {"XLRE": 0.5657, "SOL-USD": 0.0, "DBB": 0.3185, "LQD": 0.1158}, "sharpe_ratio": 3.0458, "portfolio_return": 0.323967, "portfolio_vol": 0.093233, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241209_0177", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VEA", "MATIC-USD", "IYR", "ICSH"], "decision_date": "2024-12-09", "context_summary": "4-asset optimization. Max-Sharpe: 3.419. Portfolio: return=8.77%, vol=1.40%. Weights: w_VEA=0.0000, w_MATIC-USD=0.0149, w_IYR=0.0000, w_ICSH=0.9851.", "question": "Assets: VEA, MATIC-USD, IYR, ICSH\nAnnualized mean returns: VEA:-0.1307, MATIC-USD:2.8203, IYR:0.0679, ICSH:0.0463\nCovariance matrix (annualized):\n[[0.01282, 0.020709, 0.00635, 8.2e-05], [0.020709, 0.745556, 0.019562, 0.000227], [0.00635, 0.019562, 0.026119, 0.00017], [8.2e-05, 0.000227, 0.00017, 2.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_MATIC-USD=0.0149, w_IYR=0.0000, w_ICSH=0.9851", "answer_numeric": 3.4190907815678555, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_MATIC-USD=0.0149, w_IYR=0.0000, w_ICSH=0.9851\nPortfolio annualized return: 8.77%, volatility: 1.40%\nSharpe ratio: (0.0877 - 0.0400) / 0.0140 = 3.4191", "metadata": {"weights": {"VEA": 0.0, "MATIC-USD": 0.0149, "IYR": 0.0, "ICSH": 0.9851}, "sharpe_ratio": 3.4191, "portfolio_return": 0.087743, "portfolio_vol": 0.013964, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240920_0180", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "AVAX-USD", "REZ", "BIL"], "decision_date": "2024-09-20", "context_summary": "4-asset optimization. Max-Sharpe: 5.307. Portfolio: return=6.23%, vol=0.42%. Weights: w_MTUM=0.0015, w_AVAX-USD=0.0000, w_REZ=0.0154, w_BIL=0.9831.", "question": "Assets: MTUM, AVAX-USD, REZ, BIL\nAnnualized mean returns: MTUM:0.2337, AVAX-USD:0.1106, REZ:0.6800, BIL:0.0523\nCovariance matrix (annualized):\n[[0.068397, 0.097871, 0.010719, -0.00012], [0.097871, 0.596003, 0.047186, 0.000239], [0.010719, 0.047186, 0.022697, 0.000143], [-0.00012, 0.000239, 0.000143, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0015, w_AVAX-USD=0.0000, w_REZ=0.0154, w_BIL=0.9831", "answer_numeric": 5.307093237754959, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0015, w_AVAX-USD=0.0000, w_REZ=0.0154, w_BIL=0.9831\nPortfolio annualized return: 6.23%, volatility: 0.42%\nSharpe ratio: (0.0623 - 0.0400) / 0.0042 = 5.3071", "metadata": {"weights": {"MTUM": 0.0015, "AVAX-USD": 0.0, "REZ": 0.0154, "BIL": 0.9831}, "sharpe_ratio": 5.3071, "portfolio_return": 0.062281, "portfolio_vol": 0.004198, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230120_0183", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "TLH", "VNQ"], "decision_date": "2023-01-20", "context_summary": "4-asset optimization. Max-Sharpe: 2.455. Portfolio: return=43.31%, vol=16.01%. Weights: w_XLRE=0.0000, w_LINK-USD=0.0161, w_TLH=0.9839, w_VNQ=0.0000.", "question": "Assets: XLRE, LINK-USD, TLH, VNQ\nAnnualized mean returns: XLRE:0.1620, LINK-USD:0.2841, TLH:0.4355, VNQ:0.1762\nCovariance matrix (annualized):\n[[0.055907, 0.061308, 0.012237, 0.05346], [0.061308, 0.289396, 0.011467, 0.058569], [0.012237, 0.011467, 0.02604, 0.011693], [0.05346, 0.058569, 0.011693, 0.051626]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_LINK-USD=0.0161, w_TLH=0.9839, w_VNQ=0.0000", "answer_numeric": 2.4546445271322006, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_LINK-USD=0.0161, w_TLH=0.9839, w_VNQ=0.0000\nPortfolio annualized return: 43.31%, volatility: 16.01%\nSharpe ratio: (0.4331 - 0.0400) / 0.1601 = 2.4546", "metadata": {"weights": {"XLRE": 0.0, "LINK-USD": 0.0161, "TLH": 0.9839, "VNQ": 0.0}, "sharpe_ratio": 2.4546, "portfolio_return": 0.433111, "portfolio_vol": 0.16015, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231019_0185", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BNB-USD", "MORT", "JNK"], "decision_date": "2023-10-19", "context_summary": "4-asset optimization. Max-Sharpe: -0.980. Portfolio: return=-15.92%, vol=20.33%. Weights: w_XLY=1.0000, w_BNB-USD=0.0000, w_MORT=0.0000, w_JNK=0.0000.", "question": "Assets: XLY, BNB-USD, MORT, JNK\nAnnualized mean returns: XLY:-0.1592, BNB-USD:-0.2329, MORT:-0.2945, JNK:-0.1036\nCovariance matrix (annualized):\n[[0.041346, 0.005234, 0.028466, 0.008519], [0.005234, 0.058804, 0.009638, 0.00328], [0.028466, 0.009638, 0.05851, 0.011392], [0.008519, 0.00328, 0.011392, 0.003938]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=1.0000, w_BNB-USD=0.0000, w_MORT=0.0000, w_JNK=0.0000", "answer_numeric": -0.9795865149808317, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=1.0000, w_BNB-USD=0.0000, w_MORT=0.0000, w_JNK=0.0000\nPortfolio annualized return: -15.92%, volatility: 20.33%\nSharpe ratio: (-0.1592 - 0.0400) / 0.2033 = -0.9796", "metadata": {"weights": {"XLY": 1.0, "BNB-USD": 0.0, "MORT": 0.0, "JNK": 0.0}, "sharpe_ratio": -0.9796, "portfolio_return": -0.159187, "portfolio_vol": 0.203338, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230414_0187", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "AVAX-USD", "XHB", "PPLT"], "decision_date": "2023-04-14", "context_summary": "4-asset optimization. Max-Sharpe: 2.112. Portfolio: return=65.43%, vol=29.09%. Weights: w_XLF=0.0000, w_AVAX-USD=0.0031, w_XHB=0.0000, w_PPLT=0.9969.", "question": "Assets: XLF, AVAX-USD, XHB, PPLT\nAnnualized mean returns: XLF:-0.6101, AVAX-USD:0.0798, XHB:-0.1164, PPLT:0.6561\nCovariance matrix (annualized):\n[[0.056816, 0.016439, 0.039247, -0.00507], [0.016439, 0.482495, 0.003791, 0.004013], [0.039247, 0.003791, 0.053138, -0.000882], [-0.00507, 0.004013, -0.000882, 0.085134]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_AVAX-USD=0.0031, w_XHB=0.0000, w_PPLT=0.9969", "answer_numeric": 2.1115319912162525, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_AVAX-USD=0.0031, w_XHB=0.0000, w_PPLT=0.9969\nPortfolio annualized return: 65.43%, volatility: 29.09%\nSharpe ratio: (0.6543 - 0.0400) / 0.2909 = 2.1115", "metadata": {"weights": {"XLF": 0.0, "AVAX-USD": 0.0031, "XHB": 0.0, "PPLT": 0.9969}, "sharpe_ratio": 2.1115, "portfolio_return": 0.654308, "portfolio_vol": 0.29093, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230106_0189", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "CSHI", "STIP"], "decision_date": "2023-01-06", "context_summary": "4-asset optimization. Max-Sharpe: 0.383. Portfolio: return=4.25%, vol=0.65%. Weights: w_XLY=0.0000, w_DOT-USD=0.0000, w_CSHI=1.0000, w_STIP=0.0000.", "question": "Assets: XLY, DOT-USD, CSHI, STIP\nAnnualized mean returns: XLY:-0.6001, DOT-USD:-1.9337, CSHI:0.0425, STIP:0.0132\nCovariance matrix (annualized):\n[[0.061046, 0.078443, 0.000645, 0.004646], [0.078443, 0.471721, 0.000637, 0.00587], [0.000645, 0.000637, 4.3e-05, 6.6e-05], [0.004646, 0.00587, 6.6e-05, 0.000951]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_DOT-USD=0.0000, w_CSHI=1.0000, w_STIP=0.0000", "answer_numeric": 0.38272274542322593, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_DOT-USD=0.0000, w_CSHI=1.0000, w_STIP=0.0000\nPortfolio annualized return: 4.25%, volatility: 0.65%\nSharpe ratio: (0.0425 - 0.0400) / 0.0065 = 0.3827", "metadata": {"weights": {"XLY": 0.0, "DOT-USD": 0.0, "CSHI": 1.0, "STIP": 0.0}, "sharpe_ratio": 0.3827, "portfolio_return": 0.042505, "portfolio_vol": 0.006545, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241224_0191", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "XHB", "IAU"], "decision_date": "2024-12-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.616. Portfolio: return=426.43%, vol=116.83%. Weights: w_FXI=0.0000, w_LINK-USD=1.0000, w_XHB=0.0000, w_IAU=0.0000.", "question": "Assets: FXI, LINK-USD, XHB, IAU\nAnnualized mean returns: FXI:-0.2225, LINK-USD:4.2643, XHB:-0.6236, IAU:-0.2021\nCovariance matrix (annualized):\n[[0.096722, -0.019845, 0.025735, 0.014364], [-0.019845, 1.364993, 0.051606, 0.005959], [0.025735, 0.051606, 0.055348, 0.003735], [0.014364, 0.005959, 0.003735, 0.029992]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_LINK-USD=1.0000, w_XHB=0.0000, w_IAU=0.0000", "answer_numeric": 3.61563911466025, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_LINK-USD=1.0000, w_XHB=0.0000, w_IAU=0.0000\nPortfolio annualized return: 426.43%, volatility: 116.83%\nSharpe ratio: (4.2643 - 0.0400) / 1.1683 = 3.6156", "metadata": {"weights": {"FXI": 0.0, "LINK-USD": 1.0, "XHB": 0.0, "IAU": 0.0}, "sharpe_ratio": 3.6156, "portfolio_return": 4.264256, "portfolio_vol": 1.168329, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240614_0193", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "CSHI", "IYR"], "decision_date": "2024-06-14", "context_summary": "4-asset optimization. Max-Sharpe: 3.271. Portfolio: return=7.07%, vol=0.94%. Weights: w_VTI=0.0642, w_BTC-USD=0.0000, w_CSHI=0.9358, w_IYR=0.0000.", "question": "Assets: VTI, BTC-USD, CSHI, IYR\nAnnualized mean returns: VTI:0.3132, BTC-USD:-0.0669, CSHI:0.0541, IYR:0.2071\nCovariance matrix (annualized):\n[[0.01178, 0.023189, 3e-05, 0.010827], [0.023189, 0.217508, -2.9e-05, 0.027886], [3e-05, -2.9e-05, 4.1e-05, 2.4e-05], [0.010827, 0.027886, 2.4e-05, 0.022761]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0642, w_BTC-USD=0.0000, w_CSHI=0.9358, w_IYR=0.0000", "answer_numeric": 3.2710691024580694, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0642, w_BTC-USD=0.0000, w_CSHI=0.9358, w_IYR=0.0000\nPortfolio annualized return: 7.07%, volatility: 0.94%\nSharpe ratio: (0.0707 - 0.0400) / 0.0094 = 3.2711", "metadata": {"weights": {"VTI": 0.0642, "BTC-USD": 0.0, "CSHI": 0.9358, "IYR": 0.0}, "sharpe_ratio": 3.2711, "portfolio_return": 0.070735, "portfolio_vol": 0.009396, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240725_0194", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "DOT-USD", "DBB", "CSHI"], "decision_date": "2024-07-25", "context_summary": "4-asset optimization. Max-Sharpe: 2.600. Portfolio: return=5.56%, vol=0.60%. Weights: w_FXI=0.0000, w_DOT-USD=0.0000, w_DBB=0.0000, w_CSHI=1.0000.", "question": "Assets: FXI, DOT-USD, DBB, CSHI\nAnnualized mean returns: FXI:-0.4247, DOT-USD:-1.8393, DBB:-0.7568, CSHI:0.0556\nCovariance matrix (annualized):\n[[0.039219, -0.017165, 0.012485, -0.000459], [-0.017165, 0.287923, 0.010495, 5e-06], [0.012485, 0.010495, 0.030289, -0.000284], [-0.000459, 5e-06, -0.000284, 3.6e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_DOT-USD=0.0000, w_DBB=0.0000, w_CSHI=1.0000", "answer_numeric": 2.5998510809441373, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_DOT-USD=0.0000, w_DBB=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 5.56%, volatility: 0.60%\nSharpe ratio: (0.0556 - 0.0400) / 0.0060 = 2.5999", "metadata": {"weights": {"FXI": 0.0, "DOT-USD": 0.0, "DBB": 0.0, "CSHI": 1.0}, "sharpe_ratio": 2.5999, "portfolio_return": 0.055613, "portfolio_vol": 0.006006, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9047}} +{"id": "T5_all_20240212_0197", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "AVAX-USD", "ICSH", "DBA"], "decision_date": "2024-02-12", "context_summary": "4-asset optimization. Max-Sharpe: 6.220. Portfolio: return=7.08%, vol=0.50%. Weights: w_ACWI=0.0000, w_AVAX-USD=0.0020, w_ICSH=0.9637, w_DBA=0.0343.", "question": "Assets: ACWI, AVAX-USD, ICSH, DBA\nAnnualized mean returns: ACWI:0.3287, AVAX-USD:-0.1804, ICSH:0.0590, DBA:0.4179\nCovariance matrix (annualized):\n[[0.010715, 0.014431, 0.000137, 0.002653], [0.014431, 0.717351, -0.001363, -0.008363], [0.000137, -0.001363, 2e-05, -3.2e-05], [0.002653, -0.008363, -3.2e-05, 0.01016]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_AVAX-USD=0.0020, w_ICSH=0.9637, w_DBA=0.0343", "answer_numeric": 6.220289670367493, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_AVAX-USD=0.0020, w_ICSH=0.9637, w_DBA=0.0343\nPortfolio annualized return: 7.08%, volatility: 0.50%\nSharpe ratio: (0.0708 - 0.0400) / 0.0050 = 6.2203", "metadata": {"weights": {"ACWI": 0.0, "AVAX-USD": 0.002, "ICSH": 0.9637, "DBA": 0.0343}, "sharpe_ratio": 6.2203, "portfolio_return": 0.070835, "portfolio_vol": 0.004957, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20241021_0200", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "SGOV", "ITB"], "decision_date": "2024-10-21", "context_summary": "4-asset optimization. Max-Sharpe: 4.539. Portfolio: return=5.36%, vol=0.30%. Weights: w_EEM=0.0022, w_ETH-USD=0.0000, w_SGOV=0.9938, w_ITB=0.0040.", "question": "Assets: EEM, ETH-USD, SGOV, ITB\nAnnualized mean returns: EEM:0.2734, ETH-USD:0.1512, SGOV:0.0510, ITB:0.5583\nCovariance matrix (annualized):\n[[0.040756, 0.029614, 1.4e-05, 0.012254], [0.029614, 0.246264, 0.000116, 0.052448], [1.4e-05, 0.000116, 7e-06, 0.000117], [0.012254, 0.052448, 0.000117, 0.049021]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0022, w_ETH-USD=0.0000, w_SGOV=0.9938, w_ITB=0.0040", "answer_numeric": 4.538790985236796, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0022, w_ETH-USD=0.0000, w_SGOV=0.9938, w_ITB=0.0040\nPortfolio annualized return: 5.36%, volatility: 0.30%\nSharpe ratio: (0.0536 - 0.0400) / 0.0030 = 4.5388", "metadata": {"weights": {"EEM": 0.0022, "ETH-USD": 0.0, "SGOV": 0.9938, "ITB": 0.004}, "sharpe_ratio": 4.5388, "portfolio_return": 0.053551, "portfolio_vol": 0.002985, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20230425_0203", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "BIL", "DBB"], "decision_date": "2023-04-25", "context_summary": "4-asset optimization. Max-Sharpe: -2.108. Portfolio: return=-35.61%, vol=18.79%. Weights: w_XLI=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_DBB=0.2500.", "question": "Assets: XLI, DOT-USD, BIL, DBB\nAnnualized mean returns: XLI:0.0227, DOT-USD:-1.2470, BIL:0.0461, DBB:-0.2464\nCovariance matrix (annualized):\n[[0.028057, 0.011707, -0.000138, 0.010325], [0.011707, 0.369939, -5.8e-05, 0.044595], [-0.000138, -5.8e-05, 9e-06, -5.1e-05], [0.010325, 0.044595, -5.1e-05, 0.034115]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_DBB=0.2500", "answer_numeric": -2.108193457956475, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_DBB=0.2500\nPortfolio annualized return: -35.61%, volatility: 18.79%\nSharpe ratio: (-0.3561 - 0.0400) / 0.1879 = -2.1082", "metadata": {"weights": {"XLI": 0.25, "DOT-USD": 0.25, "BIL": 0.25, "DBB": 0.25}, "sharpe_ratio": -2.1082, "portfolio_return": -0.356122, "portfolio_vol": 0.187896, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240111_0205", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "MATIC-USD", "VNQ", "VCIT"], "decision_date": "2024-01-11", "context_summary": "4-asset optimization. Max-Sharpe: 8.503. Portfolio: return=52.83%, vol=5.74%. Weights: w_XLV=0.4785, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_VCIT=0.5215.", "question": "Assets: XLV, MATIC-USD, VNQ, VCIT\nAnnualized mean returns: XLV:0.7219, MATIC-USD:-0.0324, VNQ:0.8285, VCIT:0.3507\nCovariance matrix (annualized):\n[[0.009888, 0.007085, 0.008188, -0.000241], [0.007085, 0.704117, 0.055573, 0.006998], [0.008188, 0.055573, 0.033951, 0.006452], [-0.000241, 0.006998, 0.006452, 0.004244]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.4785, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_VCIT=0.5215", "answer_numeric": 8.503255883095205, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.4785, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_VCIT=0.5215\nPortfolio annualized return: 52.83%, volatility: 5.74%\nSharpe ratio: (0.5283 - 0.0400) / 0.0574 = 8.5033", "metadata": {"weights": {"XLV": 0.4785, "MATIC-USD": 0.0, "VNQ": 0.0, "VCIT": 0.5215}, "sharpe_ratio": 8.5033, "portfolio_return": 0.528301, "portfolio_vol": 0.057425, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230711_0206", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "AVAX-USD", "XHB", "CSHI"], "decision_date": "2023-07-11", "context_summary": "4-asset optimization. Max-Sharpe: 3.983. Portfolio: return=10.88%, vol=1.73%. Weights: w_XLP=0.0000, w_AVAX-USD=0.0000, w_XHB=0.0638, w_CSHI=0.9362.", "question": "Assets: XLP, AVAX-USD, XHB, CSHI\nAnnualized mean returns: XLP:-0.2451, AVAX-USD:0.1327, XHB:0.8134, CSHI:0.0608\nCovariance matrix (annualized):\n[[0.010473, 0.002711, 0.005969, 9e-06], [0.002711, 0.227481, 0.0352, 0.000473], [0.005969, 0.0352, 0.051302, 9e-05], [9e-06, 0.000473, 9e-05, 9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_AVAX-USD=0.0000, w_XHB=0.0638, w_CSHI=0.9362", "answer_numeric": 3.9833262929940587, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_AVAX-USD=0.0000, w_XHB=0.0638, w_CSHI=0.9362\nPortfolio annualized return: 10.88%, volatility: 1.73%\nSharpe ratio: (0.1088 - 0.0400) / 0.0173 = 3.9833", "metadata": {"weights": {"XLP": 0.0, "AVAX-USD": 0.0, "XHB": 0.0638, "CSHI": 0.9362}, "sharpe_ratio": 3.9833, "portfolio_return": 0.108833, "portfolio_vol": 0.01728, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231205_0209", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "XRP-USD", "XHB", "ICSH"], "decision_date": "2023-12-05", "context_summary": "4-asset optimization. Max-Sharpe: 5.378. Portfolio: return=6.88%, vol=0.54%. Weights: w_QQQ=0.0127, w_XRP-USD=0.0025, w_XHB=0.0003, w_ICSH=0.9845.", "question": "Assets: QQQ, XRP-USD, XHB, ICSH\nAnnualized mean returns: QQQ:0.4561, XRP-USD:0.3268, XHB:0.8419, ICSH:0.0629\nCovariance matrix (annualized):\n[[0.028318, -0.001247, 0.02897, 4.9e-05], [-0.001247, 0.235847, -0.013626, -0.000285], [0.02897, -0.013626, 0.065254, 0.000452], [4.9e-05, -0.000285, 0.000452, 2.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0127, w_XRP-USD=0.0025, w_XHB=0.0003, w_ICSH=0.9845", "answer_numeric": 5.377593819980953, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0127, w_XRP-USD=0.0025, w_XHB=0.0003, w_ICSH=0.9845\nPortfolio annualized return: 6.88%, volatility: 0.54%\nSharpe ratio: (0.0688 - 0.0400) / 0.0054 = 5.3776", "metadata": {"weights": {"QQQ": 0.0127, "XRP-USD": 0.0025, "XHB": 0.0003, "ICSH": 0.9845}, "sharpe_ratio": 5.3776, "portfolio_return": 0.068811, "portfolio_vol": 0.005358, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241210_0211", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "ADA-USD", "INDS", "TLH"], "decision_date": "2024-12-10", "context_summary": "4-asset optimization. Max-Sharpe: 4.664. Portfolio: return=157.06%, vol=32.82%. Weights: w_IVV=0.7069, w_ADA-USD=0.2931, w_INDS=0.0000, w_TLH=0.0000.", "question": "Assets: IVV, ADA-USD, INDS, TLH\nAnnualized mean returns: IVV:0.2990, ADA-USD:4.6372, INDS:-0.3562, TLH:0.0061\nCovariance matrix (annualized):\n[[0.012237, 0.032644, 0.000583, -0.001557], [0.032644, 1.024617, 0.014849, 0.006001], [0.000583, 0.014849, 0.031521, 0.01179], [-0.001557, 0.006001, 0.01179, 0.01384]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.7069, w_ADA-USD=0.2931, w_INDS=0.0000, w_TLH=0.0000", "answer_numeric": 4.66438775279868, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.7069, w_ADA-USD=0.2931, w_INDS=0.0000, w_TLH=0.0000\nPortfolio annualized return: 157.06%, volatility: 32.82%\nSharpe ratio: (1.5706 - 0.0400) / 0.3282 = 4.6644", "metadata": {"weights": {"IVV": 0.7069, "ADA-USD": 0.2931, "INDS": 0.0, "TLH": 0.0}, "sharpe_ratio": 4.6644, "portfolio_return": 1.570633, "portfolio_vol": 0.328153, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230908_0214", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ETH-USD", "STIP", "BIL"], "decision_date": "2023-09-08", "context_summary": "4-asset optimization. Max-Sharpe: 4.554. Portfolio: return=5.24%, vol=0.27%. Weights: w_EFA=0.0000, w_ETH-USD=0.0000, w_STIP=0.0155, w_BIL=0.9845.", "question": "Assets: EFA, ETH-USD, STIP, BIL\nAnnualized mean returns: EFA:-0.0340, ETH-USD:-0.6485, STIP:0.0552, BIL:0.0524\nCovariance matrix (annualized):\n[[0.015633, 0.019478, 0.001957, -5.1e-05], [0.019478, 0.105779, 0.00332, -9.7e-05], [0.001957, 0.00332, 0.000702, -2e-06], [-5.1e-05, -9.7e-05, -2e-06, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_ETH-USD=0.0000, w_STIP=0.0155, w_BIL=0.9845", "answer_numeric": 4.553771786004951, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_ETH-USD=0.0000, w_STIP=0.0155, w_BIL=0.9845\nPortfolio annualized return: 5.24%, volatility: 0.27%\nSharpe ratio: (0.0524 - 0.0400) / 0.0027 = 4.5538", "metadata": {"weights": {"EFA": 0.0, "ETH-USD": 0.0, "STIP": 0.0155, "BIL": 0.9845}, "sharpe_ratio": 4.5538, "portfolio_return": 0.052437, "portfolio_vol": 0.002731, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241118_0215", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "MATIC-USD", "TLH", "CSHI"], "decision_date": "2024-11-18", "context_summary": "4-asset optimization. Max-Sharpe: 3.631. Portfolio: return=6.10%, vol=0.58%. Weights: w_XLP=0.0000, w_MATIC-USD=0.0000, w_TLH=0.0000, w_CSHI=1.0000.", "question": "Assets: XLP, MATIC-USD, TLH, CSHI\nAnnualized mean returns: XLP:-0.2022, MATIC-USD:-0.0320, TLH:-0.4241, CSHI:0.0610\nCovariance matrix (annualized):\n[[0.008873, 0.006707, 0.004946, -1.5e-05], [0.006707, 0.440376, 0.008383, 0.00062], [0.004946, 0.008383, 0.011838, -5.3e-05], [-1.5e-05, 0.00062, -5.3e-05, 3.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_MATIC-USD=0.0000, w_TLH=0.0000, w_CSHI=1.0000", "answer_numeric": 3.6311967733163515, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_MATIC-USD=0.0000, w_TLH=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 6.10%, volatility: 0.58%\nSharpe ratio: (0.0610 - 0.0400) / 0.0058 = 3.6312", "metadata": {"weights": {"XLP": 0.0, "MATIC-USD": 0.0, "TLH": 0.0, "CSHI": 1.0}, "sharpe_ratio": 3.6312, "portfolio_return": 0.061013, "portfolio_vol": 0.005787, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240802_0218", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BTC-USD", "BIL", "BNO"], "decision_date": "2024-08-02", "context_summary": "4-asset optimization. Max-Sharpe: 5.521. Portfolio: return=5.24%, vol=0.22%. Weights: w_MTUM=0.0001, w_BTC-USD=0.0000, w_BIL=0.9997, w_BNO=0.0003.", "question": "Assets: MTUM, BTC-USD, BIL, BNO\nAnnualized mean returns: MTUM:-0.0249, BTC-USD:-0.4063, BIL:0.0523, BNO:0.1050\nCovariance matrix (annualized):\n[[0.04551, 0.006703, -3.2e-05, 0.009539], [0.006703, 0.116001, 4.1e-05, -0.025773], [-3.2e-05, 4.1e-05, 5e-06, 1.3e-05], [0.009539, -0.025773, 1.3e-05, 0.050601]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0001, w_BTC-USD=0.0000, w_BIL=0.9997, w_BNO=0.0003", "answer_numeric": 5.521212601827417, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0001, w_BTC-USD=0.0000, w_BIL=0.9997, w_BNO=0.0003\nPortfolio annualized return: 5.24%, volatility: 0.22%\nSharpe ratio: (0.0524 - 0.0400) / 0.0022 = 5.5212", "metadata": {"weights": {"MTUM": 0.0001, "BTC-USD": 0.0, "BIL": 0.9997, "BNO": 0.0003}, "sharpe_ratio": 5.5212, "portfolio_return": 0.052358, "portfolio_vol": 0.002238, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230613_0220", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "HAUZ", "VCIT"], "decision_date": "2023-06-13", "context_summary": "4-asset optimization. Max-Sharpe: -1.363. Portfolio: return=-17.08%, vol=15.47%. Weights: w_MTUM=0.0000, w_ADA-USD=0.0000, w_HAUZ=1.0000, w_VCIT=0.0000.", "question": "Assets: MTUM, ADA-USD, HAUZ, VCIT\nAnnualized mean returns: MTUM:-0.1827, ADA-USD:-2.0787, HAUZ:-0.1708, VCIT:-0.0866\nCovariance matrix (annualized):\n[[0.014525, 0.006512, 0.00843, -0.000355], [0.006512, 0.236054, 0.008172, 0.009573], [0.00843, 0.008172, 0.023926, -0.001086], [-0.000355, 0.009573, -0.001086, 0.004837]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_ADA-USD=0.0000, w_HAUZ=1.0000, w_VCIT=0.0000", "answer_numeric": -1.3628953294375563, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_ADA-USD=0.0000, w_HAUZ=1.0000, w_VCIT=0.0000\nPortfolio annualized return: -17.08%, volatility: 15.47%\nSharpe ratio: (-0.1708 - 0.0400) / 0.1547 = -1.3629", "metadata": {"weights": {"MTUM": 0.0, "ADA-USD": 0.0, "HAUZ": 1.0, "VCIT": 0.0}, "sharpe_ratio": -1.3629, "portfolio_return": -0.170814, "portfolio_vol": 0.154681, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231213_0223", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "TLH", "MORT"], "decision_date": "2023-12-13", "context_summary": "4-asset optimization. Max-Sharpe: 5.001. Portfolio: return=68.09%, vol=12.81%. Weights: w_XLI=0.5592, w_DOT-USD=0.1276, w_TLH=0.3133, w_MORT=0.0000.", "question": "Assets: XLI, DOT-USD, TLH, MORT\nAnnualized mean returns: XLI:0.5071, DOT-USD:2.0685, TLH:0.4261, MORT:0.5771\nCovariance matrix (annualized):\n[[0.019608, -0.00647, 0.005834, 0.0299], [-0.00647, 0.463214, -0.01118, -0.000952], [0.005834, -0.01118, 0.025717, 0.018833], [0.0299, -0.000952, 0.018833, 0.079745]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.5592, w_DOT-USD=0.1276, w_TLH=0.3133, w_MORT=0.0000", "answer_numeric": 5.0013687898654435, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.5592, w_DOT-USD=0.1276, w_TLH=0.3133, w_MORT=0.0000\nPortfolio annualized return: 68.09%, volatility: 12.81%\nSharpe ratio: (0.6809 - 0.0400) / 0.1281 = 5.0014", "metadata": {"weights": {"XLI": 0.5592, "DOT-USD": 0.1276, "TLH": 0.3133, "MORT": 0.0}, "sharpe_ratio": 5.0014, "portfolio_return": 0.680878, "portfolio_vol": 0.128141, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241203_0225", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "MATIC-USD", "VCIT", "IYR"], "decision_date": "2024-12-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.498. Portfolio: return=214.07%, vol=84.09%. Weights: w_EEM=0.0000, w_MATIC-USD=1.0000, w_VCIT=0.0000, w_IYR=0.0000.", "question": "Assets: EEM, MATIC-USD, VCIT, IYR\nAnnualized mean returns: EEM:-0.4251, MATIC-USD:2.1407, VCIT:-0.0540, IYR:0.0754\nCovariance matrix (annualized):\n[[0.023843, 0.010044, 0.002781, 0.004554], [0.010044, 0.707074, 0.007695, 0.022549], [0.002781, 0.007695, 0.003147, 0.006221], [0.004554, 0.022549, 0.006221, 0.026484]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_MATIC-USD=1.0000, w_VCIT=0.0000, w_IYR=0.0000", "answer_numeric": 2.4981792251284802, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_MATIC-USD=1.0000, w_VCIT=0.0000, w_IYR=0.0000\nPortfolio annualized return: 214.07%, volatility: 84.09%\nSharpe ratio: (2.1407 - 0.0400) / 0.8409 = 2.4982", "metadata": {"weights": {"EEM": 0.0, "MATIC-USD": 1.0, "VCIT": 0.0, "IYR": 0.0}, "sharpe_ratio": 2.4982, "portfolio_return": 2.140661, "portfolio_vol": 0.840877, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230718_0227", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ADA-USD", "DBC", "HAUZ"], "decision_date": "2023-07-18", "context_summary": "4-asset optimization. Max-Sharpe: 2.438. Portfolio: return=36.76%, vol=13.44%. Weights: w_VLUE=0.9856, w_ADA-USD=0.0000, w_DBC=0.0144, w_HAUZ=0.0000.", "question": "Assets: VLUE, ADA-USD, DBC, HAUZ\nAnnualized mean returns: VLUE:0.3699, ADA-USD:-0.1939, DBC:0.2128, HAUZ:0.2006\nCovariance matrix (annualized):\n[[0.018317, 0.020543, 0.009244, 0.014746], [0.020543, 0.647003, 0.033739, 0.0288], [0.009244, 0.033739, 0.028859, 0.013781], [0.014746, 0.0288, 0.013781, 0.025484]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.9856, w_ADA-USD=0.0000, w_DBC=0.0144, w_HAUZ=0.0000", "answer_numeric": 2.437959670635413, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.9856, w_ADA-USD=0.0000, w_DBC=0.0144, w_HAUZ=0.0000\nPortfolio annualized return: 36.76%, volatility: 13.44%\nSharpe ratio: (0.3676 - 0.0400) / 0.1344 = 2.4380", "metadata": {"weights": {"VLUE": 0.9856, "ADA-USD": 0.0, "DBC": 0.0144, "HAUZ": 0.0}, "sharpe_ratio": 2.438, "portfolio_return": 0.367648, "portfolio_vol": 0.134394, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230721_0229", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SOL-USD", "IAU", "IYR"], "decision_date": "2023-07-21", "context_summary": "4-asset optimization. Max-Sharpe: 3.288. Portfolio: return=57.91%, vol=16.40%. Weights: w_^VIX=0.0000, w_SOL-USD=0.0893, w_IAU=0.0000, w_IYR=0.9107.", "question": "Assets: ^VIX, SOL-USD, IAU, IYR\nAnnualized mean returns: ^VIX:-1.1287, SOL-USD:1.5554, IAU:-0.0211, IYR:0.4834\nCovariance matrix (annualized):\n[[0.599195, -0.04023, -0.013129, -0.030296], [-0.04023, 0.66674, 0.009682, 0.017599], [-0.013129, 0.009682, 0.01072, -0.000314], [-0.030296, 0.017599, -0.000314, 0.022558]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0000, w_SOL-USD=0.0893, w_IAU=0.0000, w_IYR=0.9107", "answer_numeric": 3.287632967403336, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_SOL-USD=0.0893, w_IAU=0.0000, w_IYR=0.9107\nPortfolio annualized return: 57.91%, volatility: 16.40%\nSharpe ratio: (0.5791 - 0.0400) / 0.1640 = 3.2876", "metadata": {"weights": {"^VIX": 0.0, "SOL-USD": 0.0893, "IAU": 0.0, "IYR": 0.9107}, "sharpe_ratio": 3.2876, "portfolio_return": 0.579131, "portfolio_vol": 0.163987, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230822_0231", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "DBC", "EMB"], "decision_date": "2023-08-22", "context_summary": "4-asset optimization. Max-Sharpe: 1.799. Portfolio: return=21.99%, vol=10.00%. Weights: w_QUAL=0.2949, w_MATIC-USD=0.0000, w_DBC=0.7051, w_EMB=0.0000.", "question": "Assets: QUAL, MATIC-USD, DBC, EMB\nAnnualized mean returns: QUAL:0.1494, MATIC-USD:-0.3265, DBC:0.2494, EMB:-0.1053\nCovariance matrix (annualized):\n[[0.011603, 0.022717, 0.003768, 0.004003], [0.022717, 0.474834, 0.013188, 0.021387], [0.003768, 0.013188, 0.014922, 0.005453], [0.004003, 0.021387, 0.005453, 0.010184]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.2949, w_MATIC-USD=0.0000, w_DBC=0.7051, w_EMB=0.0000", "answer_numeric": 1.7994066847839776, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.2949, w_MATIC-USD=0.0000, w_DBC=0.7051, w_EMB=0.0000\nPortfolio annualized return: 21.99%, volatility: 10.00%\nSharpe ratio: (0.2199 - 0.0400) / 0.1000 = 1.7994", "metadata": {"weights": {"QUAL": 0.2949, "MATIC-USD": 0.0, "DBC": 0.7051, "EMB": 0.0}, "sharpe_ratio": 1.7994, "portfolio_return": 0.219898, "portfolio_vol": 0.099976, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231023_0233", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "TLH", "GLD"], "decision_date": "2023-10-23", "context_summary": "4-asset optimization. Max-Sharpe: 0.951. Portfolio: return=15.39%, vol=11.98%. Weights: w_EEM=0.0000, w_AVAX-USD=0.0000, w_TLH=0.0000, w_GLD=1.0000.", "question": "Assets: EEM, AVAX-USD, TLH, GLD\nAnnualized mean returns: EEM:-0.3617, AVAX-USD:-0.1254, TLH:-0.5786, GLD:0.1539\nCovariance matrix (annualized):\n[[0.018877, 0.014666, 0.003938, 0.001438], [0.014666, 0.171176, 0.002415, -0.001323], [0.003938, 0.002415, 0.021474, 0.008089], [0.001438, -0.001323, 0.008089, 0.014344]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_AVAX-USD=0.0000, w_TLH=0.0000, w_GLD=1.0000", "answer_numeric": 0.9513955193056572, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_AVAX-USD=0.0000, w_TLH=0.0000, w_GLD=1.0000\nPortfolio annualized return: 15.39%, volatility: 11.98%\nSharpe ratio: (0.1539 - 0.0400) / 0.1198 = 0.9514", "metadata": {"weights": {"EEM": 0.0, "AVAX-USD": 0.0, "TLH": 0.0, "GLD": 1.0}, "sharpe_ratio": 0.9514, "portfolio_return": 0.153947, "portfolio_vol": 0.119768, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240531_0236", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "LQD", "ICSH"], "decision_date": "2024-05-31", "context_summary": "4-asset optimization. Max-Sharpe: 2.397. Portfolio: return=4.87%, vol=0.36%. Weights: w_VEA=0.0000, w_BTC-USD=0.0000, w_LQD=0.0000, w_ICSH=1.0000.", "question": "Assets: VEA, BTC-USD, LQD, ICSH\nAnnualized mean returns: VEA:0.0128, BTC-USD:-0.3382, LQD:-0.0826, ICSH:0.0487\nCovariance matrix (annualized):\n[[0.015422, 0.024709, 0.005748, 0.000154], [0.024709, 0.259957, 0.010741, 0.000398], [0.005748, 0.010741, 0.00569, 0.000128], [0.000154, 0.000398, 0.000128, 1.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_BTC-USD=0.0000, w_LQD=0.0000, w_ICSH=1.0000", "answer_numeric": 2.3966663064328624, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_BTC-USD=0.0000, w_LQD=0.0000, w_ICSH=1.0000\nPortfolio annualized return: 4.87%, volatility: 0.36%\nSharpe ratio: (0.0487 - 0.0400) / 0.0036 = 2.3967", "metadata": {"weights": {"VEA": 0.0, "BTC-USD": 0.0, "LQD": 0.0, "ICSH": 1.0}, "sharpe_ratio": 2.3967, "portfolio_return": 0.048724, "portfolio_vol": 0.00364, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240910_0239", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNB-USD", "TLH", "XHB"], "decision_date": "2024-09-10", "context_summary": "4-asset optimization. Max-Sharpe: 3.370. Portfolio: return=35.08%, vol=9.22%. Weights: w_SPY=0.0000, w_BNB-USD=0.1032, w_TLH=0.8783, w_XHB=0.0185.", "question": "Assets: SPY, BNB-USD, TLH, XHB\nAnnualized mean returns: SPY:-0.1114, BNB-USD:0.3576, TLH:0.3514, XHB:0.2845\nCovariance matrix (annualized):\n[[0.03259, 0.044102, -0.002736, 0.04148], [0.044102, 0.243076, -0.019854, 0.056732], [-0.002736, -0.019854, 0.012054, -0.001018], [0.04148, 0.056732, -0.001018, 0.093463]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0000, w_BNB-USD=0.1032, w_TLH=0.8783, w_XHB=0.0185", "answer_numeric": 3.3699335960638557, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0000, w_BNB-USD=0.1032, w_TLH=0.8783, w_XHB=0.0185\nPortfolio annualized return: 35.08%, volatility: 9.22%\nSharpe ratio: (0.3508 - 0.0400) / 0.0922 = 3.3699", "metadata": {"weights": {"SPY": 0.0, "BNB-USD": 0.1032, "TLH": 0.8783, "XHB": 0.0185}, "sharpe_ratio": 3.3699, "portfolio_return": 0.350759, "portfolio_vol": 0.092215, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230724_0241", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "CSHI", "IYR"], "decision_date": "2023-07-24", "context_summary": "4-asset optimization. Max-Sharpe: 5.315. Portfolio: return=11.88%, vol=1.48%. Weights: w_XLU=0.0000, w_AVAX-USD=0.0037, w_CSHI=0.9019, w_IYR=0.0945.", "question": "Assets: XLU, AVAX-USD, CSHI, IYR\nAnnualized mean returns: XLU:0.3403, AVAX-USD:0.7284, CSHI:0.0556, IYR:0.6986\nCovariance matrix (annualized):\n[[0.022831, -0.003867, -0.0, 0.01176], [-0.003867, 0.27401, 0.000983, 0.000295], [-0.0, 0.000983, 4.1e-05, 3.4e-05], [0.01176, 0.000295, 3.4e-05, 0.019105]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_AVAX-USD=0.0037, w_CSHI=0.9019, w_IYR=0.0945", "answer_numeric": 5.315369390375738, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_AVAX-USD=0.0037, w_CSHI=0.9019, w_IYR=0.0945\nPortfolio annualized return: 11.88%, volatility: 1.48%\nSharpe ratio: (0.1188 - 0.0400) / 0.0148 = 5.3154", "metadata": {"weights": {"XLU": 0.0, "AVAX-USD": 0.0037, "CSHI": 0.9019, "IYR": 0.0945}, "sharpe_ratio": 5.3154, "portfolio_return": 0.118779, "portfolio_vol": 0.014821, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230424_0243", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "SGOV", "ITB"], "decision_date": "2023-04-24", "context_summary": "4-asset optimization. Max-Sharpe: 4.901. Portfolio: return=5.75%, vol=0.36%. Weights: w_VTI=0.0000, w_XRP-USD=0.0004, w_SGOV=0.9876, w_ITB=0.0120.", "question": "Assets: VTI, XRP-USD, SGOV, ITB\nAnnualized mean returns: VTI:0.1562, XRP-USD:1.0306, SGOV:0.0496, ITB:0.6743\nCovariance matrix (annualized):\n[[0.02292, 0.042177, 1.5e-05, 0.018486], [0.042177, 0.737564, 5.9e-05, 0.031342], [1.5e-05, 5.9e-05, 7e-06, 8e-06], [0.018486, 0.031342, 8e-06, 0.036846]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_XRP-USD=0.0004, w_SGOV=0.9876, w_ITB=0.0120", "answer_numeric": 4.900979977014329, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_XRP-USD=0.0004, w_SGOV=0.9876, w_ITB=0.0120\nPortfolio annualized return: 5.75%, volatility: 0.36%\nSharpe ratio: (0.0575 - 0.0400) / 0.0036 = 4.9010", "metadata": {"weights": {"VTI": 0.0, "XRP-USD": 0.0004, "SGOV": 0.9876, "ITB": 0.012}, "sharpe_ratio": 4.901, "portfolio_return": 0.057466, "portfolio_vol": 0.003564, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240219_0245", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "XRP-USD", "XHB", "IAU"], "decision_date": "2024-02-19", "context_summary": "4-asset optimization. Max-Sharpe: 1.297. Portfolio: return=33.18%, vol=22.49%. Weights: w_IWM=0.0000, w_XRP-USD=0.0000, w_XHB=1.0000, w_IAU=0.0000.", "question": "Assets: IWM, XRP-USD, XHB, IAU\nAnnualized mean returns: IWM:0.2067, XRP-USD:-0.3786, XHB:0.3318, IAU:-0.0528\nCovariance matrix (annualized):\n[[0.05308, 0.039962, 0.041048, 0.010871], [0.039962, 0.179667, 0.03521, -0.001491], [0.041048, 0.03521, 0.050602, 0.008234], [0.010871, -0.001491, 0.008234, 0.009501]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_XRP-USD=0.0000, w_XHB=1.0000, w_IAU=0.0000", "answer_numeric": 1.2971466857386624, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_XRP-USD=0.0000, w_XHB=1.0000, w_IAU=0.0000\nPortfolio annualized return: 33.18%, volatility: 22.49%\nSharpe ratio: (0.3318 - 0.0400) / 0.2249 = 1.2971", "metadata": {"weights": {"IWM": 0.0, "XRP-USD": 0.0, "XHB": 1.0, "IAU": 0.0}, "sharpe_ratio": 1.2971, "portfolio_return": 0.331791, "portfolio_vol": 0.224948, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230703_0247", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SOL-USD", "ITB", "CSHI"], "decision_date": "2023-07-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.262. Portfolio: return=12.41%, vol=1.97%. Weights: w_VEA=0.0000, w_SOL-USD=0.0000, w_ITB=0.0843, w_CSHI=0.9157.", "question": "Assets: VEA, SOL-USD, ITB, CSHI\nAnnualized mean returns: VEA:0.0935, SOL-USD:-0.4047, ITB:0.7865, CSHI:0.0631\nCovariance matrix (annualized):\n[[0.018698, 0.019019, 0.013112, -0.000132], [0.019019, 0.43031, 0.030734, -0.000139], [0.013112, 0.030734, 0.041185, -1.7e-05], [-0.000132, -0.000139, -1.7e-05, 0.000118]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_SOL-USD=0.0000, w_ITB=0.0843, w_CSHI=0.9157", "answer_numeric": 4.26203128539687, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_SOL-USD=0.0000, w_ITB=0.0843, w_CSHI=0.9157\nPortfolio annualized return: 12.41%, volatility: 1.97%\nSharpe ratio: (0.1241 - 0.0400) / 0.0197 = 4.2620", "metadata": {"weights": {"VEA": 0.0, "SOL-USD": 0.0, "ITB": 0.0843, "CSHI": 0.9157}, "sharpe_ratio": 4.262, "portfolio_return": 0.124077, "portfolio_vol": 0.019727, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230202_0250", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "BIL", "PDBC"], "decision_date": "2023-02-02", "context_summary": "4-asset optimization. Max-Sharpe: 3.598. Portfolio: return=137.39%, vol=37.07%. Weights: w_XLY=0.0000, w_BTC-USD=1.0000, w_BIL=0.0000, w_PDBC=0.0000.", "question": "Assets: XLY, BTC-USD, BIL, PDBC\nAnnualized mean returns: XLY:0.2528, BTC-USD:1.3739, BIL:0.0390, PDBC:-0.1058\nCovariance matrix (annualized):\n[[0.061366, 0.045981, -0.000114, 0.018967], [0.045981, 0.137402, 0.000249, 0.02893], [-0.000114, 0.000249, 1.2e-05, -1.9e-05], [0.018967, 0.02893, -1.9e-05, 0.039522]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_BTC-USD=1.0000, w_BIL=0.0000, w_PDBC=0.0000", "answer_numeric": 3.5984504198313925, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_BTC-USD=1.0000, w_BIL=0.0000, w_PDBC=0.0000\nPortfolio annualized return: 137.39%, volatility: 37.07%\nSharpe ratio: (1.3739 - 0.0400) / 0.3707 = 3.5985", "metadata": {"weights": {"XLY": 0.0, "BTC-USD": 1.0, "BIL": 0.0, "PDBC": 0.0}, "sharpe_ratio": 3.5985, "portfolio_return": 1.373868, "portfolio_vol": 0.370678, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240315_0252", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "INDS", "CPER"], "decision_date": "2024-03-15", "context_summary": "4-asset optimization. Max-Sharpe: 6.515. Portfolio: return=151.16%, vol=22.59%. Weights: w_FXI=0.0000, w_BTC-USD=0.4122, w_INDS=0.0000, w_CPER=0.5878.", "question": "Assets: FXI, BTC-USD, INDS, CPER\nAnnualized mean returns: FXI:0.3136, BTC-USD:2.9564, INDS:-0.2788, CPER:0.4982\nCovariance matrix (annualized):\n[[0.108208, 0.00024, 0.012329, 0.020093], [0.00024, 0.241286, 0.014394, 0.00281], [0.012329, 0.014394, 0.025089, 0.001242], [0.020093, 0.00281, 0.001242, 0.025061]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_BTC-USD=0.4122, w_INDS=0.0000, w_CPER=0.5878", "answer_numeric": 6.514826065549333, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_BTC-USD=0.4122, w_INDS=0.0000, w_CPER=0.5878\nPortfolio annualized return: 151.16%, volatility: 22.59%\nSharpe ratio: (1.5116 - 0.0400) / 0.2259 = 6.5148", "metadata": {"weights": {"FXI": 0.0, "BTC-USD": 0.4122, "INDS": 0.0, "CPER": 0.5878}, "sharpe_ratio": 6.5148, "portfolio_return": 1.511583, "portfolio_vol": 0.225882, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230313_0254", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD", "HAUZ", "SHV"], "decision_date": "2023-03-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.426. Portfolio: return=4.41%, vol=0.29%. Weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_HAUZ=0.0000, w_SHV=1.0000.", "question": "Assets: VEA, AVAX-USD, HAUZ, SHV\nAnnualized mean returns: VEA:-0.0790, AVAX-USD:-0.1332, HAUZ:-0.3917, SHV:0.0441\nCovariance matrix (annualized):\n[[0.016617, 0.024742, 0.015214, 0.000108], [0.024742, 0.756431, 0.027628, -0.000351], [0.015214, 0.027628, 0.020505, 0.000146], [0.000108, -0.000351, 0.000146, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_AVAX-USD=0.0000, w_HAUZ=0.0000, w_SHV=1.0000", "answer_numeric": 1.4257455378051394, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_HAUZ=0.0000, w_SHV=1.0000\nPortfolio annualized return: 4.41%, volatility: 0.29%\nSharpe ratio: (0.0441 - 0.0400) / 0.0029 = 1.4257", "metadata": {"weights": {"VEA": 0.0, "AVAX-USD": 0.0, "HAUZ": 0.0, "SHV": 1.0}, "sharpe_ratio": 1.4257, "portfolio_return": 0.044069, "portfolio_vol": 0.002854, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240916_0256", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "SLV", "HAUZ"], "decision_date": "2024-09-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.319. Portfolio: return=37.86%, vol=14.60%. Weights: w_QUAL=0.0000, w_SOL-USD=0.0000, w_SLV=0.0000, w_HAUZ=1.0000.", "question": "Assets: QUAL, SOL-USD, SLV, HAUZ\nAnnualized mean returns: QUAL:0.1264, SOL-USD:-0.2765, SLV:0.1261, HAUZ:0.3786\nCovariance matrix (annualized):\n[[0.03375, 0.055386, 0.03742, 0.020649], [0.055386, 0.507119, 0.069917, 0.043682], [0.03742, 0.069917, 0.098869, 0.026961], [0.020649, 0.043682, 0.026961, 0.021314]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_SOL-USD=0.0000, w_SLV=0.0000, w_HAUZ=1.0000", "answer_numeric": 2.3192284193936077, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_SOL-USD=0.0000, w_SLV=0.0000, w_HAUZ=1.0000\nPortfolio annualized return: 37.86%, volatility: 14.60%\nSharpe ratio: (0.3786 - 0.0400) / 0.1460 = 2.3192", "metadata": {"weights": {"QUAL": 0.0, "SOL-USD": 0.0, "SLV": 0.0, "HAUZ": 1.0}, "sharpe_ratio": 2.3192, "portfolio_return": 0.378594, "portfolio_vol": 0.145994, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230922_0259", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ETH-USD", "WEAT", "BIL"], "decision_date": "2023-09-22", "context_summary": "4-asset optimization. Max-Sharpe: 4.588. Portfolio: return=5.24%, vol=0.27%. Weights: w_EFA=0.0000, w_ETH-USD=0.0000, w_WEAT=0.0000, w_BIL=1.0000.", "question": "Assets: EFA, ETH-USD, WEAT, BIL\nAnnualized mean returns: EFA:-0.3375, ETH-USD:-0.8875, WEAT:-1.1520, BIL:0.0524\nCovariance matrix (annualized):\n[[0.014011, 0.010849, 0.003742, -8.7e-05], [0.010849, 0.086335, -0.000274, -0.000202], [0.003742, -0.000274, 0.077448, -3.1e-05], [-8.7e-05, -0.000202, -3.1e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_ETH-USD=0.0000, w_WEAT=0.0000, w_BIL=1.0000", "answer_numeric": 4.588030747289877, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_ETH-USD=0.0000, w_WEAT=0.0000, w_BIL=1.0000\nPortfolio annualized return: 5.24%, volatility: 0.27%\nSharpe ratio: (0.0524 - 0.0400) / 0.0027 = 4.5880", "metadata": {"weights": {"EFA": 0.0, "ETH-USD": 0.0, "WEAT": 0.0, "BIL": 1.0}, "sharpe_ratio": 4.588, "portfolio_return": 0.052389, "portfolio_vol": 0.0027, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240416_0262", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "XRP-USD", "BIL", "PDBC"], "decision_date": "2024-04-16", "context_summary": "4-asset optimization. Max-Sharpe: 6.771. Portfolio: return=6.21%, vol=0.33%. Weights: w_IWM=0.0000, w_XRP-USD=0.0000, w_BIL=0.9761, w_PDBC=0.0239.", "question": "Assets: IWM, XRP-USD, BIL, PDBC\nAnnualized mean returns: IWM:-0.2567, XRP-USD:-0.3504, BIL:0.0516, PDBC:0.4893\nCovariance matrix (annualized):\n[[0.030328, 0.032993, 8.4e-05, -9.7e-05], [0.032993, 0.588697, -5.9e-05, 0.019521], [8.4e-05, -5.9e-05, 6e-06, -1.2e-05], [-9.7e-05, 0.019521, -1.2e-05, 0.009516]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_XRP-USD=0.0000, w_BIL=0.9761, w_PDBC=0.0239", "answer_numeric": 6.770732366656685, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_XRP-USD=0.0000, w_BIL=0.9761, w_PDBC=0.0239\nPortfolio annualized return: 6.21%, volatility: 0.33%\nSharpe ratio: (0.0621 - 0.0400) / 0.0033 = 6.7707", "metadata": {"weights": {"IWM": 0.0, "XRP-USD": 0.0, "BIL": 0.9761, "PDBC": 0.0239}, "sharpe_ratio": 6.7707, "portfolio_return": 0.062051, "portfolio_vol": 0.003257, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240415_0264", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ADA-USD", "SGOV", "WEAT"], "decision_date": "2024-04-15", "context_summary": "4-asset optimization. Max-Sharpe: 6.859. Portfolio: return=5.44%, vol=0.21%. Weights: w_VTI=0.0000, w_ADA-USD=0.0000, w_SGOV=0.9987, w_WEAT=0.0013.", "question": "Assets: VTI, ADA-USD, SGOV, WEAT\nAnnualized mean returns: VTI:0.1514, ADA-USD:-1.0475, SGOV:0.0546, WEAT:-0.0787\nCovariance matrix (annualized):\n[[0.013163, 0.031321, 7.1e-05, -0.000978], [0.031321, 0.639251, 0.000265, -0.036198], [7.1e-05, 0.000265, 5e-06, -0.000107], [-0.000978, -0.036198, -0.000107, 0.054184]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_ADA-USD=0.0000, w_SGOV=0.9987, w_WEAT=0.0013", "answer_numeric": 6.8586348555782415, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_ADA-USD=0.0000, w_SGOV=0.9987, w_WEAT=0.0013\nPortfolio annualized return: 5.44%, volatility: 0.21%\nSharpe ratio: (0.0544 - 0.0400) / 0.0021 = 6.8586", "metadata": {"weights": {"VTI": 0.0, "ADA-USD": 0.0, "SGOV": 0.9987, "WEAT": 0.0013}, "sharpe_ratio": 6.8586, "portfolio_return": 0.05438, "portfolio_vol": 0.002097, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241009_0267", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SOL-USD", "SCHH", "STIP"], "decision_date": "2024-10-09", "context_summary": "4-asset optimization. Max-Sharpe: 3.423. Portfolio: return=20.73%, vol=4.89%. Weights: w_EEM=0.1776, w_SOL-USD=0.0000, w_SCHH=0.2662, w_STIP=0.5563.", "question": "Assets: EEM, SOL-USD, SCHH, STIP\nAnnualized mean returns: EEM:0.5389, SOL-USD:-0.0105, SCHH:0.2621, STIP:0.0753\nCovariance matrix (annualized):\n[[0.039039, 0.054376, -0.000472, 0.000572], [0.054376, 0.276972, 0.010442, 0.002563], [-0.000472, 0.010442, 0.010696, 0.000734], [0.000572, 0.002563, 0.000734, 0.000372]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.1776, w_SOL-USD=0.0000, w_SCHH=0.2662, w_STIP=0.5563", "answer_numeric": 3.4230641437126934, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.1776, w_SOL-USD=0.0000, w_SCHH=0.2662, w_STIP=0.5563\nPortfolio annualized return: 20.73%, volatility: 4.89%\nSharpe ratio: (0.2073 - 0.0400) / 0.0489 = 3.4231", "metadata": {"weights": {"EEM": 0.1776, "SOL-USD": 0.0, "SCHH": 0.2662, "STIP": 0.5563}, "sharpe_ratio": 3.4231, "portfolio_return": 0.207337, "portfolio_vol": 0.048885, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230525_0269", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SOL-USD", "ICSH", "EMB"], "decision_date": "2023-05-25", "context_summary": "4-asset optimization. Max-Sharpe: 1.616. Portfolio: return=7.50%, vol=2.17%. Weights: w_VEA=0.1835, w_SOL-USD=0.0014, w_ICSH=0.8151, w_EMB=0.0000.", "question": "Assets: VEA, SOL-USD, ICSH, EMB\nAnnualized mean returns: VEA:0.2262, SOL-USD:0.3188, ICSH:0.0405, EMB:-0.0381\nCovariance matrix (annualized):\n[[0.014123, 0.014455, -0.000143, 0.001145], [0.014455, 0.314791, 0.000781, 0.015982], [-0.000143, 0.000781, 4e-05, 0.000239], [0.001145, 0.015982, 0.000239, 0.004418]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.1835, w_SOL-USD=0.0014, w_ICSH=0.8151, w_EMB=0.0000", "answer_numeric": 1.6160200812530239, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.1835, w_SOL-USD=0.0014, w_ICSH=0.8151, w_EMB=0.0000\nPortfolio annualized return: 7.50%, volatility: 2.17%\nSharpe ratio: (0.0750 - 0.0400) / 0.0217 = 1.6160", "metadata": {"weights": {"VEA": 0.1835, "SOL-USD": 0.0014, "ICSH": 0.8151, "EMB": 0.0}, "sharpe_ratio": 1.616, "portfolio_return": 0.074999, "portfolio_vol": 0.021657, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240306_0271", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "WEAT", "SCHH"], "decision_date": "2024-03-06", "context_summary": "4-asset optimization. Max-Sharpe: 4.029. Portfolio: return=52.38%, vol=12.01%. Weights: w_IVV=0.9757, w_MATIC-USD=0.0243, w_WEAT=0.0000, w_SCHH=0.0000.", "question": "Assets: IVV, MATIC-USD, WEAT, SCHH\nAnnualized mean returns: IVV:0.5078, MATIC-USD:1.1665, WEAT:-0.7744, SCHH:-0.0259\nCovariance matrix (annualized):\n[[0.013728, 0.022589, 0.001134, 0.011126], [0.022589, 0.475491, -0.002095, 0.019257], [0.001134, -0.002095, 0.046725, -0.006416], [0.011126, 0.019257, -0.006416, 0.029597]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.9757, w_MATIC-USD=0.0243, w_WEAT=0.0000, w_SCHH=0.0000", "answer_numeric": 4.028607564347149, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.9757, w_MATIC-USD=0.0243, w_WEAT=0.0000, w_SCHH=0.0000\nPortfolio annualized return: 52.38%, volatility: 12.01%\nSharpe ratio: (0.5238 - 0.0400) / 0.1201 = 4.0286", "metadata": {"weights": {"IVV": 0.9757, "MATIC-USD": 0.0243, "WEAT": 0.0, "SCHH": 0.0}, "sharpe_ratio": 4.0286, "portfolio_return": 0.523756, "portfolio_vol": 0.12008, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231208_0273", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ADA-USD", "SLV", "STIP"], "decision_date": "2023-12-08", "context_summary": "4-asset optimization. Max-Sharpe: 6.216. Portfolio: return=41.65%, vol=6.06%. Weights: w_EEM=0.0000, w_ADA-USD=0.1100, w_SLV=0.1252, w_STIP=0.7648.", "question": "Assets: EEM, ADA-USD, SLV, STIP\nAnnualized mean returns: EEM:0.2055, ADA-USD:2.3103, SLV:0.6100, STIP:0.1124\nCovariance matrix (annualized):\n[[0.022751, 0.016689, 0.007262, 0.000894], [0.016689, 0.245927, -0.031187, -0.001345], [0.007262, -0.031187, 0.056254, 0.00254], [0.000894, -0.001345, 0.00254, 0.0007]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_ADA-USD=0.1100, w_SLV=0.1252, w_STIP=0.7648", "answer_numeric": 6.2157330057101206, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_ADA-USD=0.1100, w_SLV=0.1252, w_STIP=0.7648\nPortfolio annualized return: 41.65%, volatility: 6.06%\nSharpe ratio: (0.4165 - 0.0400) / 0.0606 = 6.2157", "metadata": {"weights": {"EEM": 0.0, "ADA-USD": 0.11, "SLV": 0.1252, "STIP": 0.7648}, "sharpe_ratio": 6.2157, "portfolio_return": 0.416466, "portfolio_vol": 0.060567, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240704_0276", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "DOT-USD", "IGOV", "INDS"], "decision_date": "2024-07-04", "context_summary": "4-asset optimization. Max-Sharpe: 1.693. Portfolio: return=30.75%, vol=15.80%. Weights: w_VLUE=0.0000, w_DOT-USD=0.0000, w_IGOV=0.0000, w_INDS=1.0000.", "question": "Assets: VLUE, DOT-USD, IGOV, INDS\nAnnualized mean returns: VLUE:0.1432, DOT-USD:-1.1311, IGOV:-0.0237, INDS:0.3075\nCovariance matrix (annualized):\n[[0.009261, 0.007731, 0.002475, 0.010109], [0.007731, 0.343472, 0.013313, 0.022716], [0.002475, 0.013313, 0.006272, 0.007111], [0.010109, 0.022716, 0.007111, 0.024971]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_DOT-USD=0.0000, w_IGOV=0.0000, w_INDS=1.0000", "answer_numeric": 1.6930319741767204, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_DOT-USD=0.0000, w_IGOV=0.0000, w_INDS=1.0000\nPortfolio annualized return: 30.75%, volatility: 15.80%\nSharpe ratio: (0.3075 - 0.0400) / 0.1580 = 1.6930", "metadata": {"weights": {"VLUE": 0.0, "DOT-USD": 0.0, "IGOV": 0.0, "INDS": 1.0}, "sharpe_ratio": 1.693, "portfolio_return": 0.307539, "portfolio_vol": 0.158024, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240502_0279", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "MATIC-USD", "SGOV", "ITB"], "decision_date": "2024-05-02", "context_summary": "4-asset optimization. Max-Sharpe: 5.359. Portfolio: return=5.18%, vol=0.22%. Weights: w_VEA=0.0000, w_MATIC-USD=0.0000, w_SGOV=1.0000, w_ITB=0.0000.", "question": "Assets: VEA, MATIC-USD, SGOV, ITB\nAnnualized mean returns: VEA:-0.0637, MATIC-USD:-3.1659, SGOV:0.0518, ITB:-0.2698\nCovariance matrix (annualized):\n[[0.012278, 0.033701, 7e-06, 0.020511], [0.033701, 0.551484, 0.000213, 0.031907], [7e-06, 0.000213, 5e-06, -3e-06], [0.020511, 0.031907, -3e-06, 0.058629]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_MATIC-USD=0.0000, w_SGOV=1.0000, w_ITB=0.0000", "answer_numeric": 5.359490288326557, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_MATIC-USD=0.0000, w_SGOV=1.0000, w_ITB=0.0000\nPortfolio annualized return: 5.18%, volatility: 0.22%\nSharpe ratio: (0.0518 - 0.0400) / 0.0022 = 5.3595", "metadata": {"weights": {"VEA": 0.0, "MATIC-USD": 0.0, "SGOV": 1.0, "ITB": 0.0}, "sharpe_ratio": 5.3595, "portfolio_return": 0.051833, "portfolio_vol": 0.002208, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230925_0282", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "IEF", "BIL"], "decision_date": "2023-09-25", "context_summary": "4-asset optimization. Max-Sharpe: 4.959. Portfolio: return=5.36%, vol=0.27%. Weights: w_XLF=0.0000, w_BTC-USD=0.0000, w_IEF=0.0000, w_BIL=1.0000.", "question": "Assets: XLF, BTC-USD, IEF, BIL\nAnnualized mean returns: XLF:-0.3135, BTC-USD:-0.5282, IEF:-0.2177, BIL:0.0536\nCovariance matrix (annualized):\n[[0.012793, 0.012192, 0.001968, -8.6e-05], [0.012192, 0.106565, 0.005948, -0.000311], [0.001968, 0.005948, 0.005518, -5.7e-05], [-8.6e-05, -0.000311, -5.7e-05, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_BTC-USD=0.0000, w_IEF=0.0000, w_BIL=1.0000", "answer_numeric": 4.958778916125355, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BTC-USD=0.0000, w_IEF=0.0000, w_BIL=1.0000\nPortfolio annualized return: 5.36%, volatility: 0.27%\nSharpe ratio: (0.0536 - 0.0400) / 0.0027 = 4.9588", "metadata": {"weights": {"XLF": 0.0, "BTC-USD": 0.0, "IEF": 0.0, "BIL": 1.0}, "sharpe_ratio": 4.9588, "portfolio_return": 0.053604, "portfolio_vol": 0.002743, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230113_0285", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "PALL", "ITB"], "decision_date": "2023-01-13", "context_summary": "4-asset optimization. Max-Sharpe: 2.214. Portfolio: return=58.81%, vol=24.75%. Weights: w_EWJ=0.0000, w_BNB-USD=0.0000, w_PALL=0.0000, w_ITB=1.0000.", "question": "Assets: EWJ, BNB-USD, PALL, ITB\nAnnualized mean returns: EWJ:0.1892, BNB-USD:-0.3092, PALL:-0.6637, ITB:0.5881\nCovariance matrix (annualized):\n[[0.030885, 0.034287, 0.036814, 0.023089], [0.034287, 0.289881, 0.116033, 0.04387], [0.036814, 0.116033, 0.21163, 0.038076], [0.023089, 0.04387, 0.038076, 0.061259]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_BNB-USD=0.0000, w_PALL=0.0000, w_ITB=1.0000", "answer_numeric": 2.2143831451384903, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BNB-USD=0.0000, w_PALL=0.0000, w_ITB=1.0000\nPortfolio annualized return: 58.81%, volatility: 24.75%\nSharpe ratio: (0.5881 - 0.0400) / 0.2475 = 2.2144", "metadata": {"weights": {"EWJ": 0.0, "BNB-USD": 0.0, "PALL": 0.0, "ITB": 1.0}, "sharpe_ratio": 2.2144, "portfolio_return": 0.588073, "portfolio_vol": 0.247506, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240328_0287", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "INDS", "SHY"], "decision_date": "2024-03-28", "context_summary": "4-asset optimization. Max-Sharpe: 5.392. Portfolio: return=92.29%, vol=16.38%. Weights: w_VLUE=0.7930, w_BTC-USD=0.2070, w_INDS=0.0000, w_SHY=0.0000.", "question": "Assets: VLUE, BTC-USD, INDS, SHY\nAnnualized mean returns: VLUE:0.4603, BTC-USD:2.6944, INDS:0.0140, SHY:0.0231\nCovariance matrix (annualized):\n[[0.012531, 0.01367, 0.013041, 0.001004], [0.01367, 0.337026, 0.016937, 0.000416], [0.013041, 0.016937, 0.025968, 0.001809], [0.001004, 0.000416, 0.001809, 0.000298]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.7930, w_BTC-USD=0.2070, w_INDS=0.0000, w_SHY=0.0000", "answer_numeric": 5.391578924929407, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.7930, w_BTC-USD=0.2070, w_INDS=0.0000, w_SHY=0.0000\nPortfolio annualized return: 92.29%, volatility: 16.38%\nSharpe ratio: (0.9229 - 0.0400) / 0.1638 = 5.3916", "metadata": {"weights": {"VLUE": 0.793, "BTC-USD": 0.207, "INDS": 0.0, "SHY": 0.0}, "sharpe_ratio": 5.3916, "portfolio_return": 0.92288, "portfolio_vol": 0.163752, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230223_0289", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BTC-USD", "PALL", "IEF"], "decision_date": "2023-02-23", "context_summary": "4-asset optimization. Max-Sharpe: 3.877. Portfolio: return=143.38%, vol=35.95%. Weights: w_QQQ=0.2782, w_BTC-USD=0.7218, w_PALL=0.0000, w_IEF=0.0000.", "question": "Assets: QQQ, BTC-USD, PALL, IEF\nAnnualized mean returns: QQQ:0.6112, BTC-USD:1.7508, PALL:-1.0431, IEF:-0.0809\nCovariance matrix (annualized):\n[[0.060258, 0.05013, 0.006974, 0.006521], [0.05013, 0.200394, -0.005924, 0.002779], [0.006974, -0.005924, 0.149616, 0.006671], [0.006521, 0.002779, 0.006671, 0.008644]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.2782, w_BTC-USD=0.7218, w_PALL=0.0000, w_IEF=0.0000", "answer_numeric": 3.8774341003082866, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.2782, w_BTC-USD=0.7218, w_PALL=0.0000, w_IEF=0.0000\nPortfolio annualized return: 143.38%, volatility: 35.95%\nSharpe ratio: (1.4338 - 0.0400) / 0.3595 = 3.8774", "metadata": {"weights": {"QQQ": 0.2782, "BTC-USD": 0.7218, "PALL": 0.0, "IEF": 0.0}, "sharpe_ratio": 3.8774, "portfolio_return": 1.433754, "portfolio_vol": 0.359453, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240808_0292", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "PALL", "LQD"], "decision_date": "2024-08-08", "context_summary": "4-asset optimization. Max-Sharpe: 1.800. Portfolio: return=16.79%, vol=7.11%. Weights: w_XLI=0.0000, w_DOT-USD=0.0000, w_PALL=0.0000, w_LQD=1.0000.", "question": "Assets: XLI, DOT-USD, PALL, LQD\nAnnualized mean returns: XLI:-0.0228, DOT-USD:-1.6231, PALL:-0.1017, LQD:0.1679\nCovariance matrix (annualized):\n[[0.027047, 0.021126, 0.020819, 0.002437], [0.021126, 0.352853, 0.033638, -0.004741], [0.020819, 0.033638, 0.121114, 0.000745], [0.002437, -0.004741, 0.000745, 0.005049]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_DOT-USD=0.0000, w_PALL=0.0000, w_LQD=1.0000", "answer_numeric": 1.800242312209326, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_DOT-USD=0.0000, w_PALL=0.0000, w_LQD=1.0000\nPortfolio annualized return: 16.79%, volatility: 7.11%\nSharpe ratio: (0.1679 - 0.0400) / 0.0711 = 1.8002", "metadata": {"weights": {"XLI": 0.0, "DOT-USD": 0.0, "PALL": 0.0, "LQD": 1.0}, "sharpe_ratio": 1.8002, "portfolio_return": 0.167917, "portfolio_vol": 0.071056, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230209_0295", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ETH-USD", "SCHH", "BIL"], "decision_date": "2023-02-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.381. Portfolio: return=67.49%, vol=26.67%. Weights: w_XLE=0.2710, w_ETH-USD=0.4210, w_SCHH=0.3080, w_BIL=0.0000.", "question": "Assets: XLE, ETH-USD, SCHH, BIL\nAnnualized mean returns: XLE:0.4258, ETH-USD:1.0267, SCHH:0.4132, BIL:0.0384\nCovariance matrix (annualized):\n[[0.071542, 0.044592, 0.016427, -1.4e-05], [0.044592, 0.195818, 0.051948, 4.1e-05], [0.016427, 0.051948, 0.050264, -4.6e-05], [-1.4e-05, 4.1e-05, -4.6e-05, 1.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.2710, w_ETH-USD=0.4210, w_SCHH=0.3080, w_BIL=0.0000", "answer_numeric": 2.3807655420206264, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.2710, w_ETH-USD=0.4210, w_SCHH=0.3080, w_BIL=0.0000\nPortfolio annualized return: 67.49%, volatility: 26.67%\nSharpe ratio: (0.6749 - 0.0400) / 0.2667 = 2.3808", "metadata": {"weights": {"XLE": 0.271, "ETH-USD": 0.421, "SCHH": 0.308, "BIL": 0.0}, "sharpe_ratio": 2.3808, "portfolio_return": 0.674918, "portfolio_vol": 0.266687, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231002_0296", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "HAUZ", "DBC"], "decision_date": "2023-10-02", "context_summary": "4-asset optimization. Max-Sharpe: 1.912. Portfolio: return=19.86%, vol=8.29%. Weights: w_EFA=0.0000, w_BTC-USD=0.0000, w_HAUZ=0.0000, w_DBC=1.0000.", "question": "Assets: EFA, BTC-USD, HAUZ, DBC\nAnnualized mean returns: EFA:-0.2824, BTC-USD:-0.3430, HAUZ:-0.3216, DBC:0.1986\nCovariance matrix (annualized):\n[[0.012892, 0.013137, 0.010487, 0.00316], [0.013137, 0.107946, 0.008545, -0.000756], [0.010487, 0.008545, 0.013386, 0.003316], [0.00316, -0.000756, 0.003316, 0.006878]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_BTC-USD=0.0000, w_HAUZ=0.0000, w_DBC=1.0000", "answer_numeric": 1.9120225460992435, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_BTC-USD=0.0000, w_HAUZ=0.0000, w_DBC=1.0000\nPortfolio annualized return: 19.86%, volatility: 8.29%\nSharpe ratio: (0.1986 - 0.0400) / 0.0829 = 1.9120", "metadata": {"weights": {"EFA": 0.0, "BTC-USD": 0.0, "HAUZ": 0.0, "DBC": 1.0}, "sharpe_ratio": 1.912, "portfolio_return": 0.198569, "portfolio_vol": 0.082933, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240105_0298", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "XRP-USD", "TIP", "REZ"], "decision_date": "2024-01-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.556. Portfolio: return=47.62%, vol=12.27%. Weights: w_VEA=0.9364, w_XRP-USD=0.0000, w_TIP=0.0000, w_REZ=0.0636.", "question": "Assets: VEA, XRP-USD, TIP, REZ\nAnnualized mean returns: VEA:0.4692, XRP-USD:-0.9896, TIP:0.0714, REZ:0.5783\nCovariance matrix (annualized):\n[[0.014667, 0.001857, 0.001527, 0.016872], [0.001857, 0.250262, -0.001192, 0.006094], [0.001527, -0.001192, 0.00065, 0.002854], [0.016872, 0.006094, 0.002854, 0.043567]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.9364, w_XRP-USD=0.0000, w_TIP=0.0000, w_REZ=0.0636", "answer_numeric": 3.5556419610179897, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.9364, w_XRP-USD=0.0000, w_TIP=0.0000, w_REZ=0.0636\nPortfolio annualized return: 47.62%, volatility: 12.27%\nSharpe ratio: (0.4762 - 0.0400) / 0.1227 = 3.5556", "metadata": {"weights": {"VEA": 0.9364, "XRP-USD": 0.0, "TIP": 0.0, "REZ": 0.0636}, "sharpe_ratio": 3.5556, "portfolio_return": 0.476155, "portfolio_vol": 0.122665, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231109_0300", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BNB-USD", "IYR", "TIP"], "decision_date": "2023-11-09", "context_summary": "4-asset optimization. Max-Sharpe: 0.854. Portfolio: return=26.02%, vol=25.79%. Weights: w_VTI=0.0000, w_BNB-USD=1.0000, w_IYR=0.0000, w_TIP=0.0000.", "question": "Assets: VTI, BNB-USD, IYR, TIP\nAnnualized mean returns: VTI:-0.1208, BNB-USD:0.2602, IYR:-0.3125, TIP:0.0347\nCovariance matrix (annualized):\n[[0.020045, 0.003081, 0.023605, 0.000645], [0.003081, 0.066528, 0.002229, -0.000434], [0.023605, 0.002229, 0.051191, 0.001828], [0.000645, -0.000434, 0.001828, 0.000623]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_BNB-USD=1.0000, w_IYR=0.0000, w_TIP=0.0000", "answer_numeric": 0.8536374220146912, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_BNB-USD=1.0000, w_IYR=0.0000, w_TIP=0.0000\nPortfolio annualized return: 26.02%, volatility: 25.79%\nSharpe ratio: (0.2602 - 0.0400) / 0.2579 = 0.8536", "metadata": {"weights": {"VTI": 0.0, "BNB-USD": 1.0, "IYR": 0.0, "TIP": 0.0}, "sharpe_ratio": 0.8536, "portfolio_return": 0.260178, "portfolio_vol": 0.25793, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230329_0303", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD", "BIL", "HYG"], "decision_date": "2023-03-29", "context_summary": "4-asset optimization. Max-Sharpe: 2.630. Portfolio: return=4.64%, vol=0.24%. Weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_HYG=0.0000.", "question": "Assets: VEA, AVAX-USD, BIL, HYG\nAnnualized mean returns: VEA:-0.2275, AVAX-USD:-1.5659, BIL:0.0464, HYG:-0.1459\nCovariance matrix (annualized):\n[[0.024756, 0.026367, -5.2e-05, 0.010229], [0.026367, 0.616806, -0.000348, 0.019537], [-5.2e-05, -0.000348, 6e-06, 1.2e-05], [0.010229, 0.019537, 1.2e-05, 0.00975]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_HYG=0.0000", "answer_numeric": 2.6298069364799925, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_HYG=0.0000\nPortfolio annualized return: 4.64%, volatility: 0.24%\nSharpe ratio: (0.0464 - 0.0400) / 0.0024 = 2.6298", "metadata": {"weights": {"VEA": 0.0, "AVAX-USD": 0.0, "BIL": 1.0, "HYG": 0.0}, "sharpe_ratio": 2.6298, "portfolio_return": 0.046371, "portfolio_vol": 0.002423, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231026_0305", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "XRP-USD", "PALL", "INDS"], "decision_date": "2023-10-26", "context_summary": "4-asset optimization. Max-Sharpe: 1.412. Portfolio: return=55.52%, vol=36.48%. Weights: w_IVV=0.0000, w_XRP-USD=1.0000, w_PALL=0.0000, w_INDS=0.0000.", "question": "Assets: IVV, XRP-USD, PALL, INDS\nAnnualized mean returns: IVV:-0.2915, XRP-USD:0.5552, PALL:-0.5135, INDS:-0.9050\nCovariance matrix (annualized):\n[[0.015752, -0.003456, 0.006842, 0.01829], [-0.003456, 0.13307, 0.00294, -0.001759], [0.006842, 0.00294, 0.057829, 0.012391], [0.01829, -0.001759, 0.012391, 0.037862]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_XRP-USD=1.0000, w_PALL=0.0000, w_INDS=0.0000", "answer_numeric": 1.4123467706741892, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_XRP-USD=1.0000, w_PALL=0.0000, w_INDS=0.0000\nPortfolio annualized return: 55.52%, volatility: 36.48%\nSharpe ratio: (0.5552 - 0.0400) / 0.3648 = 1.4123", "metadata": {"weights": {"IVV": 0.0, "XRP-USD": 1.0, "PALL": 0.0, "INDS": 0.0}, "sharpe_ratio": 1.4123, "portfolio_return": 0.555206, "portfolio_vol": 0.364787, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230314_0308", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ETH-USD", "ITB", "BIL"], "decision_date": "2023-03-14", "context_summary": "4-asset optimization. Max-Sharpe: 1.183. Portfolio: return=4.27%, vol=0.23%. Weights: w_XLB=0.0000, w_ETH-USD=0.0000, w_ITB=0.0000, w_BIL=1.0000.", "question": "Assets: XLB, ETH-USD, ITB, BIL\nAnnualized mean returns: XLB:-0.4629, ETH-USD:-0.0723, ITB:0.0674, BIL:0.0427\nCovariance matrix (annualized):\n[[0.03366, 0.032292, 0.035082, -4e-06], [0.032292, 0.265575, 0.022808, -9.7e-05], [0.035082, 0.022808, 0.072291, 8.3e-05], [-4e-06, -9.7e-05, 8.3e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_ETH-USD=0.0000, w_ITB=0.0000, w_BIL=1.0000", "answer_numeric": 1.183100037146429, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_ETH-USD=0.0000, w_ITB=0.0000, w_BIL=1.0000\nPortfolio annualized return: 4.27%, volatility: 0.23%\nSharpe ratio: (0.0427 - 0.0400) / 0.0023 = 1.1831", "metadata": {"weights": {"XLB": 0.0, "ETH-USD": 0.0, "ITB": 0.0, "BIL": 1.0}, "sharpe_ratio": 1.1831, "portfolio_return": 0.042732, "portfolio_vol": 0.002309, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240311_0311", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ETH-USD", "CPER", "SCHH"], "decision_date": "2024-03-11", "context_summary": "4-asset optimization. Max-Sharpe: 5.313. Portfolio: return=90.11%, vol=16.21%. Weights: w_IVV=0.7141, w_ETH-USD=0.2859, w_CPER=0.0000, w_SCHH=0.0000.", "question": "Assets: IVV, ETH-USD, CPER, SCHH\nAnnualized mean returns: IVV:0.4503, ETH-USD:2.0270, CPER:0.1950, SCHH:0.0110\nCovariance matrix (annualized):\n[[0.013596, 0.00983, 0.003457, 0.009444], [0.00983, 0.187514, 0.012393, 0.018356], [0.003457, 0.012393, 0.021402, 0.001223], [0.009444, 0.018356, 0.001223, 0.02873]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.7141, w_ETH-USD=0.2859, w_CPER=0.0000, w_SCHH=0.0000", "answer_numeric": 5.31254027360695, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.7141, w_ETH-USD=0.2859, w_CPER=0.0000, w_SCHH=0.0000\nPortfolio annualized return: 90.11%, volatility: 16.21%\nSharpe ratio: (0.9011 - 0.0400) / 0.1621 = 5.3125", "metadata": {"weights": {"IVV": 0.7141, "ETH-USD": 0.2859, "CPER": 0.0, "SCHH": 0.0}, "sharpe_ratio": 5.3125, "portfolio_return": 0.901073, "portfolio_vol": 0.162083, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230321_0313", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "CSHI", "SCHH"], "decision_date": "2023-03-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.131. Portfolio: return=7.01%, vol=1.41%. Weights: w_FXI=0.0000, w_ETH-USD=0.0000, w_CSHI=1.0000, w_SCHH=0.0000.", "question": "Assets: FXI, ETH-USD, CSHI, SCHH\nAnnualized mean returns: FXI:-0.8535, ETH-USD:0.1150, CSHI:0.0701, SCHH:-0.3462\nCovariance matrix (annualized):\n[[0.074412, 0.053068, 0.000356, 0.016899], [0.053068, 0.286185, 0.0009, 0.013926], [0.000356, 0.0009, 0.000199, 0.000843], [0.016899, 0.013926, 0.000843, 0.041812]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_ETH-USD=0.0000, w_CSHI=1.0000, w_SCHH=0.0000", "answer_numeric": 2.1305300651667927, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_ETH-USD=0.0000, w_CSHI=1.0000, w_SCHH=0.0000\nPortfolio annualized return: 7.01%, volatility: 1.41%\nSharpe ratio: (0.0701 - 0.0400) / 0.0141 = 2.1305", "metadata": {"weights": {"FXI": 0.0, "ETH-USD": 0.0, "CSHI": 1.0, "SCHH": 0.0}, "sharpe_ratio": 2.1305, "portfolio_return": 0.070068, "portfolio_vol": 0.014113, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230804_0315", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "XRP-USD", "HYG", "DBB"], "decision_date": "2023-08-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.306. Portfolio: return=39.23%, vol=15.28%. Weights: w_IWM=0.8166, w_XRP-USD=0.0000, w_HYG=0.0000, w_DBB=0.1834.", "question": "Assets: IWM, XRP-USD, HYG, DBB\nAnnualized mean returns: IWM:0.4163, XRP-USD:0.1264, HYG:0.0330, DBB:0.2853\nCovariance matrix (annualized):\n[[0.027838, 0.050623, 0.006309, 0.012051], [0.050623, 0.912151, 0.022005, 0.036656], [0.006309, 0.022005, 0.00422, 0.005739], [0.012051, 0.036656, 0.005739, 0.035005]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.8166, w_XRP-USD=0.0000, w_HYG=0.0000, w_DBB=0.1834", "answer_numeric": 2.3055869513709806, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.8166, w_XRP-USD=0.0000, w_HYG=0.0000, w_DBB=0.1834\nPortfolio annualized return: 39.23%, volatility: 15.28%\nSharpe ratio: (0.3923 - 0.0400) / 0.1528 = 2.3056", "metadata": {"weights": {"IWM": 0.8166, "XRP-USD": 0.0, "HYG": 0.0, "DBB": 0.1834}, "sharpe_ratio": 2.3056, "portfolio_return": 0.392313, "portfolio_vol": 0.152808, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230828_0317", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "LINK-USD", "TIP", "USO"], "decision_date": "2023-08-28", "context_summary": "4-asset optimization. Max-Sharpe: 4.485. Portfolio: return=93.06%, vol=19.86%. Weights: w_VLUE=0.0000, w_LINK-USD=0.0603, w_TIP=0.0000, w_USO=0.9397.", "question": "Assets: VLUE, LINK-USD, TIP, USO\nAnnualized mean returns: VLUE:-0.0246, LINK-USD:0.9730, TIP:0.0059, USO:0.9278\nCovariance matrix (annualized):\n[[0.011476, 0.027925, 0.001468, 0.009352], [0.027925, 0.584586, 0.006284, 0.006431], [0.001468, 0.006284, 0.000796, 0.001119], [0.009352, 0.006431, 0.001119, 0.041427]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_LINK-USD=0.0603, w_TIP=0.0000, w_USO=0.9397", "answer_numeric": 4.484553403947352, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_LINK-USD=0.0603, w_TIP=0.0000, w_USO=0.9397\nPortfolio annualized return: 93.06%, volatility: 19.86%\nSharpe ratio: (0.9306 - 0.0400) / 0.1986 = 4.4846", "metadata": {"weights": {"VLUE": 0.0, "LINK-USD": 0.0603, "TIP": 0.0, "USO": 0.9397}, "sharpe_ratio": 4.4846, "portfolio_return": 0.930568, "portfolio_vol": 0.198586, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230123_0320", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "AVAX-USD", "HAUZ", "SHY"], "decision_date": "2023-01-23", "context_summary": "4-asset optimization. Max-Sharpe: 3.167. Portfolio: return=30.83%, vol=8.47%. Weights: w_VLUE=0.0000, w_AVAX-USD=0.0280, w_HAUZ=0.3883, w_SHY=0.5836.", "question": "Assets: VLUE, AVAX-USD, HAUZ, SHY\nAnnualized mean returns: VLUE:-0.1109, AVAX-USD:1.7499, HAUZ:0.5573, SHY:0.0734\nCovariance matrix (annualized):\n[[0.03377, 0.071994, 0.023074, 0.001149], [0.071994, 0.78071, 0.060735, 0.000449], [0.023074, 0.060735, 0.028882, 0.001569], [0.001149, 0.000449, 0.001569, 0.000464]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_AVAX-USD=0.0280, w_HAUZ=0.3883, w_SHY=0.5836", "answer_numeric": 3.167152414511733, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_AVAX-USD=0.0280, w_HAUZ=0.3883, w_SHY=0.5836\nPortfolio annualized return: 30.83%, volatility: 8.47%\nSharpe ratio: (0.3083 - 0.0400) / 0.0847 = 3.1672", "metadata": {"weights": {"VLUE": 0.0, "AVAX-USD": 0.028, "HAUZ": 0.3883, "SHY": 0.5836}, "sharpe_ratio": 3.1672, "portfolio_return": 0.308269, "portfolio_vol": 0.084704, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231120_0323", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "MORT", "LQD"], "decision_date": "2023-11-20", "context_summary": "4-asset optimization. Max-Sharpe: 1.337. Portfolio: return=75.52%, vol=53.49%. Weights: w_IWM=0.0000, w_MATIC-USD=1.0000, w_MORT=0.0000, w_LQD=0.0000.", "question": "Assets: IWM, MATIC-USD, MORT, LQD\nAnnualized mean returns: IWM:-0.1357, MATIC-USD:0.7552, MORT:-0.3228, LQD:0.0320\nCovariance matrix (annualized):\n[[0.047138, 0.002358, 0.057973, 0.011885], [0.002358, 0.286083, 0.009905, -0.003003], [0.057973, 0.009905, 0.102161, 0.023073], [0.011885, -0.003003, 0.023073, 0.013749]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_MATIC-USD=1.0000, w_MORT=0.0000, w_LQD=0.0000", "answer_numeric": 1.3372013292046065, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_MATIC-USD=1.0000, w_MORT=0.0000, w_LQD=0.0000\nPortfolio annualized return: 75.52%, volatility: 53.49%\nSharpe ratio: (0.7552 - 0.0400) / 0.5349 = 1.3372", "metadata": {"weights": {"IWM": 0.0, "MATIC-USD": 1.0, "MORT": 0.0, "LQD": 0.0}, "sharpe_ratio": 1.3372, "portfolio_return": 0.755225, "portfolio_vol": 0.534867, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240205_0325", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "ITB", "DBC"], "decision_date": "2024-02-05", "context_summary": "4-asset optimization. Max-Sharpe: 2.548. Portfolio: return=68.65%, vol=25.37%. Weights: w_EEM=0.0000, w_AVAX-USD=0.0475, w_ITB=0.9525, w_DBC=0.0000.", "question": "Assets: EEM, AVAX-USD, ITB, DBC\nAnnualized mean returns: EEM:0.0645, AVAX-USD:0.6683, ITB:0.6874, DBC:0.0147\nCovariance matrix (annualized):\n[[0.021566, -0.00289, 0.01305, 0.00581], [-0.00289, 0.871819, 0.022214, -0.032274], [0.01305, 0.022214, 0.06655, 0.004295], [0.00581, -0.032274, 0.004295, 0.017454]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_AVAX-USD=0.0475, w_ITB=0.9525, w_DBC=0.0000", "answer_numeric": 2.5484584650617665, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_AVAX-USD=0.0475, w_ITB=0.9525, w_DBC=0.0000\nPortfolio annualized return: 68.65%, volatility: 25.37%\nSharpe ratio: (0.6865 - 0.0400) / 0.2537 = 2.5485", "metadata": {"weights": {"EEM": 0.0, "AVAX-USD": 0.0475, "ITB": 0.9525, "DBC": 0.0}, "sharpe_ratio": 2.5485, "portfolio_return": 0.686501, "portfolio_vol": 0.253683, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240513_0328", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "ADA-USD", "BIL", "SCHP"], "decision_date": "2024-05-13", "context_summary": "4-asset optimization. Max-Sharpe: 4.580. Portfolio: return=5.25%, vol=0.27%. Weights: w_XLV=0.0000, w_ADA-USD=0.0000, w_BIL=1.0000, w_SCHP=0.0000.", "question": "Assets: XLV, ADA-USD, BIL, SCHP\nAnnualized mean returns: XLV:-0.0995, ADA-USD:-2.9342, BIL:0.0525, SCHP:-0.0072\nCovariance matrix (annualized):\n[[0.010922, 0.010803, -3e-06, 0.001189], [0.010803, 0.398011, 0.000308, 0.001598], [-3e-06, 0.000308, 8e-06, 2e-06], [0.001189, 0.001598, 2e-06, 0.002515]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_ADA-USD=0.0000, w_BIL=1.0000, w_SCHP=0.0000", "answer_numeric": 4.579512754752388, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_ADA-USD=0.0000, w_BIL=1.0000, w_SCHP=0.0000\nPortfolio annualized return: 5.25%, volatility: 0.27%\nSharpe ratio: (0.0525 - 0.0400) / 0.0027 = 4.5795", "metadata": {"weights": {"XLV": 0.0, "ADA-USD": 0.0, "BIL": 1.0, "SCHP": 0.0}, "sharpe_ratio": 4.5795, "portfolio_return": 0.052549, "portfolio_vol": 0.00274, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231129_0331", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "ICSH", "JNK"], "decision_date": "2023-11-29", "context_summary": "4-asset optimization. Max-Sharpe: 6.233. Portfolio: return=6.99%, vol=0.48%. Weights: w_EWJ=0.0001, w_AVAX-USD=0.0031, w_ICSH=0.9968, w_JNK=0.0000.", "question": "Assets: EWJ, AVAX-USD, ICSH, JNK\nAnnualized mean returns: EWJ:0.2262, AVAX-USD:2.5058, ICSH:0.0623, JNK:0.2037\nCovariance matrix (annualized):\n[[0.027236, 0.001256, 0.000138, 0.007519], [0.001256, 0.920855, -0.000953, 0.011351], [0.000138, -0.000953, 2e-05, 0.0001], [0.007519, 0.011351, 0.0001, 0.005942]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0001, w_AVAX-USD=0.0031, w_ICSH=0.9968, w_JNK=0.0000", "answer_numeric": 6.232637053265782, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0001, w_AVAX-USD=0.0031, w_ICSH=0.9968, w_JNK=0.0000\nPortfolio annualized return: 6.99%, volatility: 0.48%\nSharpe ratio: (0.0699 - 0.0400) / 0.0048 = 6.2326", "metadata": {"weights": {"EWJ": 0.0001, "AVAX-USD": 0.0031, "ICSH": 0.9968, "JNK": 0.0}, "sharpe_ratio": 6.2326, "portfolio_return": 0.0699, "portfolio_vol": 0.004797, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240527_0333", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "XRP-USD", "WEAT", "ICSH"], "decision_date": "2024-05-27", "context_summary": "4-asset optimization. Max-Sharpe: 5.135. Portfolio: return=7.54%, vol=0.69%. Weights: w_QQQ=0.0000, w_XRP-USD=0.0000, w_WEAT=0.0222, w_ICSH=0.9778.", "question": "Assets: QQQ, XRP-USD, WEAT, ICSH\nAnnualized mean returns: QQQ:0.1787, XRP-USD:-0.1567, WEAT:1.2007, ICSH:0.0499\nCovariance matrix (annualized):\n[[0.025808, 0.021617, 0.010016, 0.000105], [0.021617, 0.205891, 0.030223, 0.000599], [0.010016, 0.030223, 0.070417, -4e-06], [0.000105, 0.000599, -4e-06, 1.4e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0000, w_XRP-USD=0.0000, w_WEAT=0.0222, w_ICSH=0.9778", "answer_numeric": 5.135063708674952, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_XRP-USD=0.0000, w_WEAT=0.0222, w_ICSH=0.9778\nPortfolio annualized return: 7.54%, volatility: 0.69%\nSharpe ratio: (0.0754 - 0.0400) / 0.0069 = 5.1351", "metadata": {"weights": {"QQQ": 0.0, "XRP-USD": 0.0, "WEAT": 0.0222, "ICSH": 0.9778}, "sharpe_ratio": 5.1351, "portfolio_return": 0.075434, "portfolio_vol": 0.0069, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230808_0336", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "PPLT", "MORT"], "decision_date": "2023-08-08", "context_summary": "4-asset optimization. Max-Sharpe: 3.480. Portfolio: return=58.58%, vol=15.69%. Weights: w_XLY=0.5882, w_BTC-USD=0.3169, w_PPLT=0.0000, w_MORT=0.0949.", "question": "Assets: XLY, BTC-USD, PPLT, MORT\nAnnualized mean returns: XLY:0.5015, BTC-USD:0.7841, PPLT:-0.5570, MORT:0.4458\nCovariance matrix (annualized):\n[[0.030754, 0.002767, 0.011803, 0.019367], [0.002767, 0.098609, -0.00198, 0.007009], [0.011803, -0.00198, 0.045192, 0.020033], [0.019367, 0.007009, 0.020033, 0.049312]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.5882, w_BTC-USD=0.3169, w_PPLT=0.0000, w_MORT=0.0949", "answer_numeric": 3.4795578911778944, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.5882, w_BTC-USD=0.3169, w_PPLT=0.0000, w_MORT=0.0949\nPortfolio annualized return: 58.58%, volatility: 15.69%\nSharpe ratio: (0.5858 - 0.0400) / 0.1569 = 3.4796", "metadata": {"weights": {"XLY": 0.5882, "BTC-USD": 0.3169, "PPLT": 0.0, "MORT": 0.0949}, "sharpe_ratio": 3.4796, "portfolio_return": 0.585771, "portfolio_vol": 0.156851, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240206_0339", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XRP-USD", "JNK", "UNG"], "decision_date": "2024-02-06", "context_summary": "4-asset optimization. Max-Sharpe: 1.722. Portfolio: return=14.97%, vol=6.37%. Weights: w_XLY=0.0000, w_XRP-USD=0.0000, w_JNK=0.9696, w_UNG=0.0304.", "question": "Assets: XLY, XRP-USD, JNK, UNG\nAnnualized mean returns: XLY:0.1016, XRP-USD:-1.1788, JNK:0.1430, UNG:0.3634\nCovariance matrix (annualized):\n[[0.027259, 0.029743, 0.005072, -0.015964], [0.029743, 0.198996, 0.005762, -0.032032], [0.005072, 0.005762, 0.003968, -0.001158], [-0.015964, -0.032032, -0.001158, 0.430794]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_XRP-USD=0.0000, w_JNK=0.9696, w_UNG=0.0304", "answer_numeric": 1.72233119281714, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_XRP-USD=0.0000, w_JNK=0.9696, w_UNG=0.0304\nPortfolio annualized return: 14.97%, volatility: 6.37%\nSharpe ratio: (0.1497 - 0.0400) / 0.0637 = 1.7223", "metadata": {"weights": {"XLY": 0.0, "XRP-USD": 0.0, "JNK": 0.9696, "UNG": 0.0304}, "sharpe_ratio": 1.7223, "portfolio_return": 0.149741, "portfolio_vol": 0.063717, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240124_0342", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "XRP-USD", "CSHI", "CPER"], "decision_date": "2024-01-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.967. Portfolio: return=9.58%, vol=1.41%. Weights: w_XLK=0.0870, w_XRP-USD=0.0000, w_CSHI=0.9130, w_CPER=0.0000.", "question": "Assets: XLK, XRP-USD, CSHI, CPER\nAnnualized mean returns: XLK:0.5984, XRP-USD:-1.0702, CSHI:0.0479, CPER:0.0064\nCovariance matrix (annualized):\n[[0.023086, 0.006635, -3.2e-05, 0.011095], [0.006635, 0.182559, 4.2e-05, 0.023757], [-3.2e-05, 4.2e-05, 3.4e-05, -0.000333], [0.011095, 0.023757, -0.000333, 0.029851]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.0870, w_XRP-USD=0.0000, w_CSHI=0.9130, w_CPER=0.0000", "answer_numeric": 3.967332373164199, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0870, w_XRP-USD=0.0000, w_CSHI=0.9130, w_CPER=0.0000\nPortfolio annualized return: 9.58%, volatility: 1.41%\nSharpe ratio: (0.0958 - 0.0400) / 0.0141 = 3.9673", "metadata": {"weights": {"XLK": 0.087, "XRP-USD": 0.0, "CSHI": 0.913, "CPER": 0.0}, "sharpe_ratio": 3.9673, "portfolio_return": 0.095772, "portfolio_vol": 0.014058, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240418_0345", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "MATIC-USD", "BIL", "PALL"], "decision_date": "2024-04-18", "context_summary": "4-asset optimization. Max-Sharpe: -2.510. Portfolio: return=-62.06%, vol=26.32%. Weights: w_QQQ=0.2500, w_MATIC-USD=0.2500, w_BIL=0.2500, w_PALL=0.2500.", "question": "Assets: QQQ, MATIC-USD, BIL, PALL\nAnnualized mean returns: QQQ:-0.0598, MATIC-USD:-2.8193, BIL:0.0503, PALL:0.3464\nCovariance matrix (annualized):\n[[0.026898, 0.040782, 0.000173, 0.007377], [0.040782, 0.602578, -5e-06, 0.127976], [0.000173, -5e-06, 6e-06, -1.6e-05], [0.007377, 0.127976, -1.6e-05, 0.126024]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.2500, w_MATIC-USD=0.2500, w_BIL=0.2500, w_PALL=0.2500", "answer_numeric": -2.510120738507237, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.2500, w_MATIC-USD=0.2500, w_BIL=0.2500, w_PALL=0.2500\nPortfolio annualized return: -62.06%, volatility: 26.32%\nSharpe ratio: (-0.6206 - 0.0400) / 0.2632 = -2.5101", "metadata": {"weights": {"QQQ": 0.25, "MATIC-USD": 0.25, "BIL": 0.25, "PALL": 0.25}, "sharpe_ratio": -2.5101, "portfolio_return": -0.620572, "portfolio_vol": 0.263164, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230719_0348", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SOL-USD", "VNQ", "JNK"], "decision_date": "2023-07-19", "context_summary": "4-asset optimization. Max-Sharpe: 3.235. Portfolio: return=39.25%, vol=10.90%. Weights: w_^VIX=0.0000, w_SOL-USD=0.0655, w_VNQ=0.4134, w_JNK=0.5210.", "question": "Assets: ^VIX, SOL-USD, VNQ, JNK\nAnnualized mean returns: ^VIX:-1.5134, SOL-USD:1.6701, VNQ:0.4523, JNK:0.1843\nCovariance matrix (annualized):\n[[0.617369, -0.042722, -0.033913, -0.026505], [-0.042722, 0.684383, 0.014917, 0.007481], [-0.033913, 0.014917, 0.02524, 0.004751], [-0.026505, 0.007481, 0.004751, 0.004619]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0000, w_SOL-USD=0.0655, w_VNQ=0.4134, w_JNK=0.5210", "answer_numeric": 3.234814116635385, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_SOL-USD=0.0655, w_VNQ=0.4134, w_JNK=0.5210\nPortfolio annualized return: 39.25%, volatility: 10.90%\nSharpe ratio: (0.3925 - 0.0400) / 0.1090 = 3.2348", "metadata": {"weights": {"^VIX": 0.0, "SOL-USD": 0.0655, "VNQ": 0.4134, "JNK": 0.521}, "sharpe_ratio": 3.2348, "portfolio_return": 0.392461, "portfolio_vol": 0.108959, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230816_0351", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "WEAT", "HAUZ"], "decision_date": "2023-08-16", "context_summary": "4-asset optimization. Max-Sharpe: 0.926. Portfolio: return=41.96%, vol=40.99%. Weights: w_XLP=0.0000, w_DOT-USD=1.0000, w_WEAT=0.0000, w_HAUZ=0.0000.", "question": "Assets: XLP, DOT-USD, WEAT, HAUZ\nAnnualized mean returns: XLP:-0.0438, DOT-USD:0.4196, WEAT:-0.8678, HAUZ:-0.2374\nCovariance matrix (annualized):\n[[0.009013, 0.003254, 0.009039, 0.004208], [0.003254, 0.168055, 0.008192, 0.00155], [0.009039, 0.008192, 0.142396, 0.003986], [0.004208, 0.00155, 0.003986, 0.022163]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_DOT-USD=1.0000, w_WEAT=0.0000, w_HAUZ=0.0000", "answer_numeric": 0.9260679956465689, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_DOT-USD=1.0000, w_WEAT=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: 41.96%, volatility: 40.99%\nSharpe ratio: (0.4196 - 0.0400) / 0.4099 = 0.9261", "metadata": {"weights": {"XLP": 0.0, "DOT-USD": 1.0, "WEAT": 0.0, "HAUZ": 0.0}, "sharpe_ratio": 0.9261, "portfolio_return": 0.419638, "portfolio_vol": 0.409946, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230116_0353", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "IEF", "REZ"], "decision_date": "2023-01-16", "context_summary": "4-asset optimization. Max-Sharpe: 3.531. Portfolio: return=105.09%, vol=28.63%. Weights: w_XLF=0.0000, w_BTC-USD=0.8471, w_IEF=0.1529, w_REZ=0.0000.", "question": "Assets: XLF, BTC-USD, IEF, REZ\nAnnualized mean returns: XLF:0.1943, BTC-USD:1.2148, IEF:0.1433, REZ:0.1824\nCovariance matrix (annualized):\n[[0.026491, 0.025131, 0.004808, 0.028182], [0.025131, 0.110993, 0.008166, 0.034419], [0.004808, 0.008166, 0.009552, 0.008978], [0.028182, 0.034419, 0.008978, 0.053339]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_BTC-USD=0.8471, w_IEF=0.1529, w_REZ=0.0000", "answer_numeric": 3.5307027062072165, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BTC-USD=0.8471, w_IEF=0.1529, w_REZ=0.0000\nPortfolio annualized return: 105.09%, volatility: 28.63%\nSharpe ratio: (1.0509 - 0.0400) / 0.2863 = 3.5307", "metadata": {"weights": {"XLF": 0.0, "BTC-USD": 0.8471, "IEF": 0.1529, "REZ": 0.0}, "sharpe_ratio": 3.5307, "portfolio_return": 1.05094, "portfolio_vol": 0.286328, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241023_0355", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "UNG", "SCHP"], "decision_date": "2024-10-23", "context_summary": "4-asset optimization. Max-Sharpe: 2.397. Portfolio: return=86.35%, vol=34.36%. Weights: w_FXI=0.9251, w_ADA-USD=0.0000, w_UNG=0.0749, w_SCHP=0.0000.", "question": "Assets: FXI, ADA-USD, UNG, SCHP\nAnnualized mean returns: FXI:0.9325, ADA-USD:-0.3046, UNG:0.0108, SCHP:-0.0249\nCovariance matrix (annualized):\n[[0.14016, 0.058467, -0.02283, 0.00069], [0.058467, 0.221562, -0.027639, -0.001423], [-0.02283, -0.027639, 0.226196, 0.005429], [0.00069, -0.001423, 0.005429, 0.002049]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.9251, w_ADA-USD=0.0000, w_UNG=0.0749, w_SCHP=0.0000", "answer_numeric": 2.396748707993701, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.9251, w_ADA-USD=0.0000, w_UNG=0.0749, w_SCHP=0.0000\nPortfolio annualized return: 86.35%, volatility: 34.36%\nSharpe ratio: (0.8635 - 0.0400) / 0.3436 = 2.3967", "metadata": {"weights": {"FXI": 0.9251, "ADA-USD": 0.0, "UNG": 0.0749, "SCHP": 0.0}, "sharpe_ratio": 2.3967, "portfolio_return": 0.863544, "portfolio_vol": 0.343609, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20230405_0357", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "EMB", "VNQ"], "decision_date": "2023-04-05", "context_summary": "4-asset optimization. Max-Sharpe: -1.717. Portfolio: return=-78.50%, vol=48.06%. Weights: w_XLB=0.0000, w_BNB-USD=1.0000, w_EMB=0.0000, w_VNQ=0.0000.", "question": "Assets: XLB, BNB-USD, EMB, VNQ\nAnnualized mean returns: XLB:-0.2299, BNB-USD:-0.7850, EMB:-0.0792, VNQ:-0.5743\nCovariance matrix (annualized):\n[[0.043832, 0.010818, 0.003362, 0.029625], [0.010818, 0.230959, -0.002001, 0.011242], [0.003362, -0.002001, 0.011191, 0.003878], [0.029625, 0.011242, 0.003878, 0.049969]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_BNB-USD=1.0000, w_EMB=0.0000, w_VNQ=0.0000", "answer_numeric": -1.7166125141577413, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_BNB-USD=1.0000, w_EMB=0.0000, w_VNQ=0.0000\nPortfolio annualized return: -78.50%, volatility: 48.06%\nSharpe ratio: (-0.7850 - 0.0400) / 0.4806 = -1.7166", "metadata": {"weights": {"XLB": 0.0, "BNB-USD": 1.0, "EMB": 0.0, "VNQ": 0.0}, "sharpe_ratio": -1.7166, "portfolio_return": -0.784974, "portfolio_vol": 0.480582, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241127_0359", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "MATIC-USD", "IYR", "SGOV"], "decision_date": "2024-11-27", "context_summary": "4-asset optimization. Max-Sharpe: 2.224. Portfolio: return=4.65%, vol=0.29%. Weights: w_XLK=0.0096, w_MATIC-USD=0.0000, w_IYR=0.0005, w_SGOV=0.9900.", "question": "Assets: XLK, MATIC-USD, IYR, SGOV\nAnnualized mean returns: XLK:0.2521, MATIC-USD:0.1407, IYR:0.0674, SGOV:0.0445\nCovariance matrix (annualized):\n[[0.036752, 0.040199, -0.000913, -7.3e-05], [0.040199, 0.638043, 0.024691, 0.000176], [-0.000913, 0.024691, 0.025395, 3.3e-05], [-7.3e-05, 0.000176, 3.3e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.0096, w_MATIC-USD=0.0000, w_IYR=0.0005, w_SGOV=0.9900", "answer_numeric": 2.2240480129294133, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0096, w_MATIC-USD=0.0000, w_IYR=0.0005, w_SGOV=0.9900\nPortfolio annualized return: 4.65%, volatility: 0.29%\nSharpe ratio: (0.0465 - 0.0400) / 0.0029 = 2.2240", "metadata": {"weights": {"XLK": 0.0096, "MATIC-USD": 0.0, "IYR": 0.0005, "SGOV": 0.99}, "sharpe_ratio": 2.224, "portfolio_return": 0.046491, "portfolio_vol": 0.002919, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240805_0362", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "XRP-USD", "BIL", "ITB"], "decision_date": "2024-08-05", "context_summary": "4-asset optimization. Max-Sharpe: 6.954. Portfolio: return=5.69%, vol=0.24%. Weights: w_XLE=0.0000, w_XRP-USD=0.0000, w_BIL=0.9964, w_ITB=0.0036.", "question": "Assets: XLE, XRP-USD, BIL, ITB\nAnnualized mean returns: XLE:-0.0542, XRP-USD:0.1049, BIL:0.0553, ITB:0.4996\nCovariance matrix (annualized):\n[[0.031244, 0.029398, -7.6e-05, 0.012325], [0.029398, 0.294511, -8.6e-05, 0.041968], [-7.6e-05, -8.6e-05, 6e-06, -0.000148], [0.012325, 0.041968, -0.000148, 0.086699]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_XRP-USD=0.0000, w_BIL=0.9964, w_ITB=0.0036", "answer_numeric": 6.954442421187647, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_XRP-USD=0.0000, w_BIL=0.9964, w_ITB=0.0036\nPortfolio annualized return: 5.69%, volatility: 0.24%\nSharpe ratio: (0.0569 - 0.0400) / 0.0024 = 6.9544", "metadata": {"weights": {"XLE": 0.0, "XRP-USD": 0.0, "BIL": 0.9964, "ITB": 0.0036}, "sharpe_ratio": 6.9544, "portfolio_return": 0.056894, "portfolio_vol": 0.002429, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240904_0365", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "XRP-USD", "CSHI", "PPLT"], "decision_date": "2024-09-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.692. Portfolio: return=57.94%, vol=20.04%. Weights: w_ACWI=0.0000, w_XRP-USD=0.2677, w_CSHI=0.7323, w_PPLT=0.0000.", "question": "Assets: ACWI, XRP-USD, CSHI, PPLT\nAnnualized mean returns: ACWI:0.0043, XRP-USD:2.0281, CSHI:0.0498, PPLT:-0.7299\nCovariance matrix (annualized):\n[[0.02915, 0.032447, 0.00125, 0.024739], [0.032447, 0.548253, 0.001661, 0.059958], [0.00125, 0.001661, 0.000385, 0.001764], [0.024739, 0.059958, 0.001764, 0.05993]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_XRP-USD=0.2677, w_CSHI=0.7323, w_PPLT=0.0000", "answer_numeric": 2.6918036890842836, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_XRP-USD=0.2677, w_CSHI=0.7323, w_PPLT=0.0000\nPortfolio annualized return: 57.94%, volatility: 20.04%\nSharpe ratio: (0.5794 - 0.0400) / 0.2004 = 2.6918", "metadata": {"weights": {"ACWI": 0.0, "XRP-USD": 0.2677, "CSHI": 0.7323, "PPLT": 0.0}, "sharpe_ratio": 2.6918, "portfolio_return": 0.579377, "portfolio_vol": 0.200378, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241004_0368", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "CSHI", "SCHH"], "decision_date": "2024-10-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.748. Portfolio: return=35.74%, vol=11.55%. Weights: w_ACWI=0.6025, w_ADA-USD=0.0000, w_CSHI=0.1022, w_SCHH=0.2953.", "question": "Assets: ACWI, ADA-USD, CSHI, SCHH\nAnnualized mean returns: ACWI:0.4283, ADA-USD:0.7777, CSHI:0.0674, SCHH:0.3129\nCovariance matrix (annualized):\n[[0.021907, 0.050599, 0.001302, 0.01011], [0.050599, 0.347641, 0.005886, 0.028825], [0.001302, 0.005886, 0.000393, 0.001114], [0.01011, 0.028825, 0.001114, 0.017826]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.6025, w_ADA-USD=0.0000, w_CSHI=0.1022, w_SCHH=0.2953", "answer_numeric": 2.7480121753628173, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.6025, w_ADA-USD=0.0000, w_CSHI=0.1022, w_SCHH=0.2953\nPortfolio annualized return: 35.74%, volatility: 11.55%\nSharpe ratio: (0.3574 - 0.0400) / 0.1155 = 2.7480", "metadata": {"weights": {"ACWI": 0.6025, "ADA-USD": 0.0, "CSHI": 0.1022, "SCHH": 0.2953}, "sharpe_ratio": 2.748, "portfolio_return": 0.357353, "portfolio_vol": 0.115484, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241230_0371", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "LQD", "SOYB"], "decision_date": "2024-12-30", "context_summary": "4-asset optimization. Max-Sharpe: 5.349. Portfolio: return=630.46%, vol=117.11%. Weights: w_USMV=0.0000, w_XRP-USD=1.0000, w_LQD=0.0000, w_SOYB=0.0000.", "question": "Assets: USMV, XRP-USD, LQD, SOYB\nAnnualized mean returns: USMV:-0.0389, XRP-USD:6.3046, LQD:-0.0796, SOYB:-0.1091\nCovariance matrix (annualized):\n[[0.012378, 0.022212, 0.002388, 0.005885], [0.022212, 1.371565, 0.012999, -0.010209], [0.002388, 0.012999, 0.006828, 0.005468], [0.005885, -0.010209, 0.005468, 0.019884]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_XRP-USD=1.0000, w_LQD=0.0000, w_SOYB=0.0000", "answer_numeric": 5.349193054928013, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_XRP-USD=1.0000, w_LQD=0.0000, w_SOYB=0.0000\nPortfolio annualized return: 630.46%, volatility: 117.11%\nSharpe ratio: (6.3046 - 0.0400) / 1.1711 = 5.3492", "metadata": {"weights": {"USMV": 0.0, "XRP-USD": 1.0, "LQD": 0.0, "SOYB": 0.0}, "sharpe_ratio": 5.3492, "portfolio_return": 6.304646, "portfolio_vol": 1.171139, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230621_0373", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "MORT", "CSHI"], "decision_date": "2023-06-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.192. Portfolio: return=7.40%, vol=1.55%. Weights: w_USMV=0.0000, w_ADA-USD=0.0000, w_MORT=0.0450, w_CSHI=0.9550.", "question": "Assets: USMV, ADA-USD, MORT, CSHI\nAnnualized mean returns: USMV:-0.0140, ADA-USD:-1.4030, MORT:0.4886, CSHI:0.0544\nCovariance matrix (annualized):\n[[0.010032, 0.002643, 0.01766, -0.000259], [0.002643, 0.203739, 0.024538, -0.000954], [0.01766, 0.024538, 0.073603, -0.000147], [-0.000259, -0.000954, -0.000147, 0.000114]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_ADA-USD=0.0000, w_MORT=0.0450, w_CSHI=0.9550", "answer_numeric": 2.1920510716533608, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_ADA-USD=0.0000, w_MORT=0.0450, w_CSHI=0.9550\nPortfolio annualized return: 7.40%, volatility: 1.55%\nSharpe ratio: (0.0740 - 0.0400) / 0.0155 = 2.1921", "metadata": {"weights": {"USMV": 0.0, "ADA-USD": 0.0, "MORT": 0.045, "CSHI": 0.955}, "sharpe_ratio": 2.1921, "portfolio_return": 0.07396, "portfolio_vol": 0.015492, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240116_0375", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "INDS", "EMB"], "decision_date": "2024-01-16", "context_summary": "4-asset optimization. Max-Sharpe: 5.417. Portfolio: return=53.70%, vol=9.18%. Weights: w_QUAL=0.4649, w_ADA-USD=0.0051, w_INDS=0.2242, w_EMB=0.3058.", "question": "Assets: QUAL, ADA-USD, INDS, EMB\nAnnualized mean returns: QUAL:0.4195, ADA-USD:2.4749, INDS:0.9114, EMB:0.4089\nCovariance matrix (annualized):\n[[0.007742, 0.036456, 0.007597, 0.003072], [0.036456, 0.938442, 0.04826, 0.028395], [0.007597, 0.04826, 0.036304, 0.009295], [0.003072, 0.028395, 0.009295, 0.008473]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.4649, w_ADA-USD=0.0051, w_INDS=0.2242, w_EMB=0.3058", "answer_numeric": 5.4170336943060855, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.4649, w_ADA-USD=0.0051, w_INDS=0.2242, w_EMB=0.3058\nPortfolio annualized return: 53.70%, volatility: 9.18%\nSharpe ratio: (0.5370 - 0.0400) / 0.0918 = 5.4170", "metadata": {"weights": {"QUAL": 0.4649, "ADA-USD": 0.0051, "INDS": 0.2242, "EMB": 0.3058}, "sharpe_ratio": 5.417, "portfolio_return": 0.537013, "portfolio_vol": 0.09175, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240723_0378", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "SGOV", "BNO"], "decision_date": "2024-07-23", "context_summary": "4-asset optimization. Max-Sharpe: 6.113. Portfolio: return=5.32%, vol=0.22%. Weights: w_XLE=0.0000, w_ADA-USD=0.0000, w_SGOV=0.9967, w_BNO=0.0033.", "question": "Assets: XLE, ADA-USD, SGOV, BNO\nAnnualized mean returns: XLE:0.0905, ADA-USD:-0.2929, SGOV:0.0527, BNO:0.2250\nCovariance matrix (annualized):\n[[0.028983, 0.000285, -4e-05, 0.018237], [0.000285, 0.207467, -0.0, -0.024401], [-4e-05, -0.0, 5e-06, -9.4e-05], [0.018237, -0.024401, -9.4e-05, 0.048144]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_ADA-USD=0.0000, w_SGOV=0.9967, w_BNO=0.0033", "answer_numeric": 6.11310497954331, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_ADA-USD=0.0000, w_SGOV=0.9967, w_BNO=0.0033\nPortfolio annualized return: 5.32%, volatility: 0.22%\nSharpe ratio: (0.0532 - 0.0400) / 0.0022 = 6.1131", "metadata": {"weights": {"XLE": 0.0, "ADA-USD": 0.0, "SGOV": 0.9967, "BNO": 0.0033}, "sharpe_ratio": 6.1131, "portfolio_return": 0.053233, "portfolio_vol": 0.002165, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240221_0380", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LINK-USD", "CPER", "IYR"], "decision_date": "2024-02-21", "context_summary": "4-asset optimization. Max-Sharpe: 3.202. Portfolio: return=38.32%, vol=10.72%. Weights: w_XLF=0.9887, w_LINK-USD=0.0113, w_CPER=0.0000, w_IYR=0.0000.", "question": "Assets: XLF, LINK-USD, CPER, IYR\nAnnualized mean returns: XLF:0.3763, LINK-USD:0.9903, CPER:-0.0020, IYR:-0.2692\nCovariance matrix (annualized):\n[[0.011095, 0.025371, 0.004649, 0.011524], [0.025371, 0.596565, 0.019792, 0.024674], [0.004649, 0.019792, 0.024251, 0.001132], [0.011524, 0.024674, 0.001132, 0.032282]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.9887, w_LINK-USD=0.0113, w_CPER=0.0000, w_IYR=0.0000", "answer_numeric": 3.2021887629271344, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.9887, w_LINK-USD=0.0113, w_CPER=0.0000, w_IYR=0.0000\nPortfolio annualized return: 38.32%, volatility: 10.72%\nSharpe ratio: (0.3832 - 0.0400) / 0.1072 = 3.2022", "metadata": {"weights": {"XLF": 0.9887, "LINK-USD": 0.0113, "CPER": 0.0, "IYR": 0.0}, "sharpe_ratio": 3.2022, "portfolio_return": 0.383205, "portfolio_vol": 0.107178, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20231130_0383", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "DBC", "TLT"], "decision_date": "2023-11-30", "context_summary": "4-asset optimization. Max-Sharpe: 3.202. Portfolio: return=71.64%, vol=21.12%. Weights: w_EFA=0.5433, w_AVAX-USD=0.1759, w_DBC=0.0000, w_TLT=0.2808.", "question": "Assets: EFA, AVAX-USD, DBC, TLT\nAnnualized mean returns: EFA:0.3022, AVAX-USD:2.5718, DBC:-0.1395, TLT:0.3554\nCovariance matrix (annualized):\n[[0.020579, 0.01669, -0.001087, 0.011316], [0.01669, 0.899123, -0.056074, -0.000877], [-0.001087, -0.056074, 0.033334, -0.002417], [0.011316, -0.000877, -0.002417, 0.052743]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.5433, w_AVAX-USD=0.1759, w_DBC=0.0000, w_TLT=0.2808", "answer_numeric": 3.2022683785797845, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.5433, w_AVAX-USD=0.1759, w_DBC=0.0000, w_TLT=0.2808\nPortfolio annualized return: 71.64%, volatility: 21.12%\nSharpe ratio: (0.7164 - 0.0400) / 0.2112 = 3.2023", "metadata": {"weights": {"EFA": 0.5433, "AVAX-USD": 0.1759, "DBC": 0.0, "TLT": 0.2808}, "sharpe_ratio": 3.2023, "portfolio_return": 0.716403, "portfolio_vol": 0.211226, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241014_0386", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "SOL-USD", "IGOV", "REZ"], "decision_date": "2024-10-14", "context_summary": "4-asset optimization. Max-Sharpe: 3.137. Portfolio: return=36.03%, vol=10.21%. Weights: w_SPY=0.7402, w_SOL-USD=0.0000, w_IGOV=0.0000, w_REZ=0.2598.", "question": "Assets: SPY, SOL-USD, IGOV, REZ\nAnnualized mean returns: SPY:0.4110, SOL-USD:-0.0248, IGOV:-0.0405, REZ:0.2156\nCovariance matrix (annualized):\n[[0.01542, 0.032548, 0.001709, 0.002533], [0.032548, 0.285962, 0.020217, 0.004841], [0.001709, 0.020217, 0.006619, 0.001624], [0.002533, 0.004841, 0.001624, 0.014771]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.7402, w_SOL-USD=0.0000, w_IGOV=0.0000, w_REZ=0.2598", "answer_numeric": 3.1373828092251403, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.7402, w_SOL-USD=0.0000, w_IGOV=0.0000, w_REZ=0.2598\nPortfolio annualized return: 36.03%, volatility: 10.21%\nSharpe ratio: (0.3603 - 0.0400) / 0.1021 = 3.1374", "metadata": {"weights": {"SPY": 0.7402, "SOL-USD": 0.0, "IGOV": 0.0, "REZ": 0.2598}, "sharpe_ratio": 3.1374, "portfolio_return": 0.360264, "portfolio_vol": 0.10208, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230829_0388", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "LQD", "PALL"], "decision_date": "2023-08-29", "context_summary": "4-asset optimization. Max-Sharpe: 0.336. Portfolio: return=13.63%, vol=28.69%. Weights: w_XLP=0.0000, w_XRP-USD=0.0000, w_LQD=0.0000, w_PALL=1.0000.", "question": "Assets: XLP, XRP-USD, LQD, PALL\nAnnualized mean returns: XLP:-0.0655, XRP-USD:-0.7831, LQD:-0.0823, PALL:0.1363\nCovariance matrix (annualized):\n[[0.00969, 0.021597, 0.002871, 0.005211], [0.021597, 1.014289, 0.035009, 0.027986], [0.002871, 0.035009, 0.009259, 0.011529], [0.005211, 0.027986, 0.011529, 0.082284]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_XRP-USD=0.0000, w_LQD=0.0000, w_PALL=1.0000", "answer_numeric": 0.3356876690541344, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_XRP-USD=0.0000, w_LQD=0.0000, w_PALL=1.0000\nPortfolio annualized return: 13.63%, volatility: 28.69%\nSharpe ratio: (0.1363 - 0.0400) / 0.2869 = 0.3357", "metadata": {"weights": {"XLP": 0.0, "XRP-USD": 0.0, "LQD": 0.0, "PALL": 1.0}, "sharpe_ratio": 0.3357, "portfolio_return": 0.136293, "portfolio_vol": 0.286852, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230413_0391", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "UNG", "IEF"], "decision_date": "2023-04-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.675. Portfolio: return=28.33%, vol=14.53%. Weights: w_XLI=0.0000, w_ADA-USD=0.1795, w_UNG=0.0000, w_IEF=0.8205.", "question": "Assets: XLI, ADA-USD, UNG, IEF\nAnnualized mean returns: XLI:-0.1308, ADA-USD:0.9343, UNG:-1.1793, IEF:0.1409\nCovariance matrix (annualized):\n[[0.032583, 0.026413, 0.039629, -0.008578], [0.026413, 0.429994, 0.06761, 0.000498], [0.039629, 0.06761, 0.544479, -0.006956], [-0.008578, 0.000498, -0.006956, 0.010562]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_ADA-USD=0.1795, w_UNG=0.0000, w_IEF=0.8205", "answer_numeric": 1.6745510136381805, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_ADA-USD=0.1795, w_UNG=0.0000, w_IEF=0.8205\nPortfolio annualized return: 28.33%, volatility: 14.53%\nSharpe ratio: (0.2833 - 0.0400) / 0.1453 = 1.6746", "metadata": {"weights": {"XLI": 0.0, "ADA-USD": 0.1795, "UNG": 0.0, "IEF": 0.8205}, "sharpe_ratio": 1.6746, "portfolio_return": 0.283333, "portfolio_vol": 0.145312, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240816_0393", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "LINK-USD", "VNQI", "BNO"], "decision_date": "2024-08-16", "context_summary": "4-asset optimization. Max-Sharpe: 1.966. Portfolio: return=31.99%, vol=14.24%. Weights: w_VTI=0.0000, w_LINK-USD=0.0000, w_VNQI=1.0000, w_BNO=0.0000.", "question": "Assets: VTI, LINK-USD, VNQI, BNO\nAnnualized mean returns: VTI:0.1510, LINK-USD:-1.3558, VNQI:0.3199, BNO:0.0685\nCovariance matrix (annualized):\n[[0.028213, 0.06327, 0.015587, 0.007152], [0.06327, 0.533903, 0.022832, -0.007434], [0.015587, 0.022832, 0.020275, 0.002851], [0.007152, -0.007434, 0.002851, 0.053514]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_LINK-USD=0.0000, w_VNQI=1.0000, w_BNO=0.0000", "answer_numeric": 1.965787993507831, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_LINK-USD=0.0000, w_VNQI=1.0000, w_BNO=0.0000\nPortfolio annualized return: 31.99%, volatility: 14.24%\nSharpe ratio: (0.3199 - 0.0400) / 0.1424 = 1.9658", "metadata": {"weights": {"VTI": 0.0, "LINK-USD": 0.0, "VNQI": 1.0, "BNO": 0.0}, "sharpe_ratio": 1.9658, "portfolio_return": 0.319908, "portfolio_vol": 0.142389, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230622_0395", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "XRP-USD", "ICSH", "VNQI"], "decision_date": "2023-06-22", "context_summary": "4-asset optimization. Max-Sharpe: 2.176. Portfolio: return=6.37%, vol=1.09%. Weights: w_XLI=0.0473, w_XRP-USD=0.0129, w_ICSH=0.9399, w_VNQI=0.0000.", "question": "Assets: XLI, XRP-USD, ICSH, VNQI\nAnnualized mean returns: XLI:0.2771, XRP-USD:0.6071, ICSH:0.0456, VNQI:-0.1363\nCovariance matrix (annualized):\n[[0.029478, 0.016097, -0.000439, 0.01416], [0.016097, 0.160666, 1.5e-05, 0.006913], [-0.000439, 1.5e-05, 5.1e-05, -0.000199], [0.01416, 0.006913, -0.000199, 0.02528]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0473, w_XRP-USD=0.0129, w_ICSH=0.9399, w_VNQI=0.0000", "answer_numeric": 2.1759514634246564, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0473, w_XRP-USD=0.0129, w_ICSH=0.9399, w_VNQI=0.0000\nPortfolio annualized return: 6.37%, volatility: 1.09%\nSharpe ratio: (0.0637 - 0.0400) / 0.0109 = 2.1760", "metadata": {"weights": {"XLI": 0.0473, "XRP-USD": 0.0129, "ICSH": 0.9399, "VNQI": 0.0}, "sharpe_ratio": 2.176, "portfolio_return": 0.063713, "portfolio_vol": 0.010898, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240813_0398", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "SOL-USD", "PDBC", "LQD"], "decision_date": "2024-08-13", "context_summary": "4-asset optimization. Max-Sharpe: 2.155. Portfolio: return=20.59%, vol=7.70%. Weights: w_MTUM=0.0000, w_SOL-USD=0.0736, w_PDBC=0.0000, w_LQD=0.9264.", "question": "Assets: MTUM, SOL-USD, PDBC, LQD\nAnnualized mean returns: MTUM:-0.3571, SOL-USD:1.0635, PDBC:-0.1701, LQD:0.1378\nCovariance matrix (annualized):\n[[0.062657, 0.068558, 0.010396, 0.001251], [0.068558, 0.673546, -0.011546, -0.014012], [0.010396, -0.011546, 0.016692, 0.000661], [0.001251, -0.014012, 0.000661, 0.004882]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_SOL-USD=0.0736, w_PDBC=0.0000, w_LQD=0.9264", "answer_numeric": 2.154825212351121, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_SOL-USD=0.0736, w_PDBC=0.0000, w_LQD=0.9264\nPortfolio annualized return: 20.59%, volatility: 7.70%\nSharpe ratio: (0.2059 - 0.0400) / 0.0770 = 2.1548", "metadata": {"weights": {"MTUM": 0.0, "SOL-USD": 0.0736, "PDBC": 0.0, "LQD": 0.9264}, "sharpe_ratio": 2.1548, "portfolio_return": 0.205857, "portfolio_vol": 0.07697, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230104_0400", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "AVAX-USD", "DBB", "CSHI"], "decision_date": "2023-01-04", "context_summary": "4-asset optimization. Max-Sharpe: 0.121. Portfolio: return=4.08%, vol=0.67%. Weights: w_XLRE=0.0000, w_AVAX-USD=0.0000, w_DBB=0.0000, w_CSHI=1.0000.", "question": "Assets: XLRE, AVAX-USD, DBB, CSHI\nAnnualized mean returns: XLRE:-0.0464, AVAX-USD:-1.7974, DBB:0.0066, CSHI:0.0408\nCovariance matrix (annualized):\n[[0.048743, 0.104113, 0.018101, 0.000542], [0.104113, 0.870891, 0.072538, 0.000574], [0.018101, 0.072538, 0.042138, 0.000255], [0.000542, 0.000574, 0.000255, 4.4e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_AVAX-USD=0.0000, w_DBB=0.0000, w_CSHI=1.0000", "answer_numeric": 0.1214527770046649, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_AVAX-USD=0.0000, w_DBB=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 4.08%, volatility: 0.67%\nSharpe ratio: (0.0408 - 0.0400) / 0.0067 = 0.1215", "metadata": {"weights": {"XLRE": 0.0, "AVAX-USD": 0.0, "DBB": 0.0, "CSHI": 1.0}, "sharpe_ratio": 0.1215, "portfolio_return": 0.040809, "portfolio_vol": 0.006657, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241217_0403", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "DOT-USD", "CPER", "CSHI"], "decision_date": "2024-12-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.709. Portfolio: return=5.89%, vol=0.51%. Weights: w_VTI=0.0117, w_DOT-USD=0.0008, w_CPER=0.0000, w_CSHI=0.9875.", "question": "Assets: VTI, DOT-USD, CPER, CSHI\nAnnualized mean returns: VTI:0.2724, DOT-USD:1.2428, CPER:-0.2166, CSHI:0.0555\nCovariance matrix (annualized):\n[[0.01297, 0.044133, -0.003606, 0.000135], [0.044133, 0.816786, -0.032967, 0.000503], [-0.003606, -0.032967, 0.041718, -0.000157], [0.000135, 0.000503, -0.000157, 2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0117, w_DOT-USD=0.0008, w_CPER=0.0000, w_CSHI=0.9875", "answer_numeric": 3.7087523065275314, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0117, w_DOT-USD=0.0008, w_CPER=0.0000, w_CSHI=0.9875\nPortfolio annualized return: 5.89%, volatility: 0.51%\nSharpe ratio: (0.0589 - 0.0400) / 0.0051 = 3.7088", "metadata": {"weights": {"VTI": 0.0117, "DOT-USD": 0.0008, "CPER": 0.0, "CSHI": 0.9875}, "sharpe_ratio": 3.7088, "portfolio_return": 0.058937, "portfolio_vol": 0.005106, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230821_0404", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MATIC-USD", "SGOV", "INDS"], "decision_date": "2023-08-21", "context_summary": "4-asset optimization. Max-Sharpe: 6.307. Portfolio: return=5.24%, vol=0.20%. Weights: w_FXI=0.0000, w_MATIC-USD=0.0000, w_SGOV=0.9993, w_INDS=0.0007.", "question": "Assets: FXI, MATIC-USD, SGOV, INDS\nAnnualized mean returns: FXI:-0.3388, MATIC-USD:-0.2092, SGOV:0.0526, INDS:-0.2021\nCovariance matrix (annualized):\n[[0.090251, 0.043787, 4e-06, 0.024003], [0.043787, 0.468166, 0.000139, 0.028807], [4e-06, 0.000139, 4e-06, -9.7e-05], [0.024003, 0.028807, -9.7e-05, 0.029152]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_MATIC-USD=0.0000, w_SGOV=0.9993, w_INDS=0.0007", "answer_numeric": 6.307279255938064, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_MATIC-USD=0.0000, w_SGOV=0.9993, w_INDS=0.0007\nPortfolio annualized return: 5.24%, volatility: 0.20%\nSharpe ratio: (0.0524 - 0.0400) / 0.0020 = 6.3073", "metadata": {"weights": {"FXI": 0.0, "MATIC-USD": 0.0, "SGOV": 0.9993, "INDS": 0.0007}, "sharpe_ratio": 6.3073, "portfolio_return": 0.052404, "portfolio_vol": 0.001967, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230713_0407", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "CSHI", "INDS"], "decision_date": "2023-07-13", "context_summary": "4-asset optimization. Max-Sharpe: 2.927. Portfolio: return=7.80%, vol=1.30%. Weights: w_XLB=0.0535, w_BNB-USD=0.0000, w_CSHI=0.9465, w_INDS=0.0000.", "question": "Assets: XLB, BNB-USD, CSHI, INDS\nAnnualized mean returns: XLB:0.4199, BNB-USD:-0.7838, CSHI:0.0587, INDS:0.0399\nCovariance matrix (annualized):\n[[0.031989, 0.013612, -2.7e-05, 0.019262], [0.013612, 0.185418, 0.000616, 0.011497], [-2.7e-05, 0.000616, 8.9e-05, -2.2e-05], [0.019262, 0.011497, -2.2e-05, 0.029677]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0535, w_BNB-USD=0.0000, w_CSHI=0.9465, w_INDS=0.0000", "answer_numeric": 2.9274460401219966, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0535, w_BNB-USD=0.0000, w_CSHI=0.9465, w_INDS=0.0000\nPortfolio annualized return: 7.80%, volatility: 1.30%\nSharpe ratio: (0.0780 - 0.0400) / 0.0130 = 2.9274", "metadata": {"weights": {"XLB": 0.0535, "BNB-USD": 0.0, "CSHI": 0.9465, "INDS": 0.0}, "sharpe_ratio": 2.9274, "portfolio_return": 0.078003, "portfolio_vol": 0.012982, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230619_0409", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "XRP-USD", "DBA", "ITB"], "decision_date": "2023-06-19", "context_summary": "4-asset optimization. Max-Sharpe: 3.205. Portfolio: return=44.43%, vol=12.61%. Weights: w_IVV=0.3338, w_XRP-USD=0.0000, w_DBA=0.3070, w_ITB=0.3592.", "question": "Assets: IVV, XRP-USD, DBA, ITB\nAnnualized mean returns: IVV:0.3868, XRP-USD:-0.0229, DBA:0.2586, ITB:0.6563\nCovariance matrix (annualized):\n[[0.016813, 0.013079, 0.00557, 0.0176], [0.013079, 0.185987, 0.007132, 0.026313], [0.00557, 0.007132, 0.015292, 0.005698], [0.0176, 0.026313, 0.005698, 0.04628]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.3338, w_XRP-USD=0.0000, w_DBA=0.3070, w_ITB=0.3592", "answer_numeric": 3.2054183816325805, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.3338, w_XRP-USD=0.0000, w_DBA=0.3070, w_ITB=0.3592\nPortfolio annualized return: 44.43%, volatility: 12.61%\nSharpe ratio: (0.4443 - 0.0400) / 0.1261 = 3.2054", "metadata": {"weights": {"IVV": 0.3338, "XRP-USD": 0.0, "DBA": 0.307, "ITB": 0.3592}, "sharpe_ratio": 3.2054, "portfolio_return": 0.444263, "portfolio_vol": 0.126119, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230720_0411", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "SGOV", "HAUZ"], "decision_date": "2023-07-20", "context_summary": "4-asset optimization. Max-Sharpe: 6.361. Portfolio: return=6.58%, vol=0.41%. Weights: w_QUAL=0.0180, w_LINK-USD=0.0014, w_SGOV=0.9806, w_HAUZ=0.0000.", "question": "Assets: QUAL, LINK-USD, SGOV, HAUZ\nAnnualized mean returns: QUAL:0.5928, LINK-USD:1.6230, SGOV:0.0539, HAUZ:0.2587\nCovariance matrix (annualized):\n[[0.013375, 0.021344, 8.4e-05, 0.010806], [0.021344, 0.393812, 7.1e-05, 0.016504], [8.4e-05, 7.1e-05, 7e-06, 7e-06], [0.010806, 0.016504, 7e-06, 0.025695]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0180, w_LINK-USD=0.0014, w_SGOV=0.9806, w_HAUZ=0.0000", "answer_numeric": 6.360954257406088, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0180, w_LINK-USD=0.0014, w_SGOV=0.9806, w_HAUZ=0.0000\nPortfolio annualized return: 6.58%, volatility: 0.41%\nSharpe ratio: (0.0658 - 0.0400) / 0.0041 = 6.3610", "metadata": {"weights": {"QUAL": 0.018, "LINK-USD": 0.0014, "SGOV": 0.9806, "HAUZ": 0.0}, "sharpe_ratio": 6.361, "portfolio_return": 0.06581, "portfolio_vol": 0.004058, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231222_0414", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "DOT-USD", "VNQ", "CSHI"], "decision_date": "2023-12-22", "context_summary": "4-asset optimization. Max-Sharpe: 6.965. Portfolio: return=14.88%, vol=1.56%. Weights: w_EEM=0.0000, w_DOT-USD=0.0106, w_VNQ=0.0509, w_CSHI=0.9385.", "question": "Assets: EEM, DOT-USD, VNQ, CSHI\nAnnualized mean returns: EEM:0.5367, DOT-USD:3.2443, VNQ:1.0282, CSHI:0.0662\nCovariance matrix (annualized):\n[[0.023324, 0.015706, 0.021416, 4e-06], [0.015706, 0.731058, -0.001188, -0.000543], [0.021416, -0.001188, 0.046328, -0.000136], [4e-06, -0.000543, -0.000136, 7.6e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_DOT-USD=0.0106, w_VNQ=0.0509, w_CSHI=0.9385", "answer_numeric": 6.965132057364239, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_DOT-USD=0.0106, w_VNQ=0.0509, w_CSHI=0.9385\nPortfolio annualized return: 14.88%, volatility: 1.56%\nSharpe ratio: (0.1488 - 0.0400) / 0.0156 = 6.9651", "metadata": {"weights": {"EEM": 0.0, "DOT-USD": 0.0106, "VNQ": 0.0509, "CSHI": 0.9385}, "sharpe_ratio": 6.9651, "portfolio_return": 0.148832, "portfolio_vol": 0.015625, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230815_0417", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "USO", "VCIT"], "decision_date": "2023-08-15", "context_summary": "4-asset optimization. Max-Sharpe: 4.835. Portfolio: return=97.32%, vol=19.30%. Weights: w_FXI=0.0000, w_BTC-USD=0.3460, w_USO=0.6540, w_VCIT=0.0000.", "question": "Assets: FXI, BTC-USD, USO, VCIT\nAnnualized mean returns: FXI:-0.3552, BTC-USD:0.9508, USO:0.9851, VCIT:-0.0703\nCovariance matrix (annualized):\n[[0.096519, -0.004572, 0.019599, 0.007551], [-0.004572, 0.092409, 0.006702, 0.004402], [0.019599, 0.006702, 0.054148, 0.003817], [0.007551, 0.004402, 0.003817, 0.005303]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_BTC-USD=0.3460, w_USO=0.6540, w_VCIT=0.0000", "answer_numeric": 4.834993456691139, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_BTC-USD=0.3460, w_USO=0.6540, w_VCIT=0.0000\nPortfolio annualized return: 97.32%, volatility: 19.30%\nSharpe ratio: (0.9732 - 0.0400) / 0.1930 = 4.8350", "metadata": {"weights": {"FXI": 0.0, "BTC-USD": 0.346, "USO": 0.654, "VCIT": 0.0}, "sharpe_ratio": 4.835, "portfolio_return": 0.973239, "portfolio_vol": 0.193018, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240326_0420", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "MATIC-USD", "GLD", "SGOV"], "decision_date": "2024-03-26", "context_summary": "4-asset optimization. Max-Sharpe: 6.042. Portfolio: return=5.66%, vol=0.27%. Weights: w_USMV=0.0000, w_MATIC-USD=0.0004, w_GLD=0.0123, w_SGOV=0.9873.", "question": "Assets: USMV, MATIC-USD, GLD, SGOV\nAnnualized mean returns: USMV:0.2168, MATIC-USD:1.3244, GLD:0.4448, SGOV:0.0513\nCovariance matrix (annualized):\n[[0.00515, 0.011156, 0.003005, 7.6e-05], [0.011156, 0.546992, 0.031347, 1e-06], [0.003005, 0.031347, 0.011371, 3.3e-05], [7.6e-05, 1e-06, 3.3e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_MATIC-USD=0.0004, w_GLD=0.0123, w_SGOV=0.9873", "answer_numeric": 6.042123583203571, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_MATIC-USD=0.0004, w_GLD=0.0123, w_SGOV=0.9873\nPortfolio annualized return: 5.66%, volatility: 0.27%\nSharpe ratio: (0.0566 - 0.0400) / 0.0027 = 6.0421", "metadata": {"weights": {"USMV": 0.0, "MATIC-USD": 0.0004, "GLD": 0.0123, "SGOV": 0.9873}, "sharpe_ratio": 6.0421, "portfolio_return": 0.056577, "portfolio_vol": 0.002744, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241227_0422", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "SGOV", "JNK"], "decision_date": "2024-12-27", "context_summary": "4-asset optimization. Max-Sharpe: 4.450. Portfolio: return=6.01%, vol=0.45%. Weights: w_EEM=0.0000, w_BTC-USD=0.0073, w_SGOV=0.9927, w_JNK=0.0000.", "question": "Assets: EEM, BTC-USD, SGOV, JNK\nAnnualized mean returns: EEM:-0.2599, BTC-USD:2.0242, SGOV:0.0457, JNK:0.0562\nCovariance matrix (annualized):\n[[0.022816, -0.000806, -1.8e-05, 0.002953], [-0.000806, 0.283682, -5e-05, 0.00828], [-1.8e-05, -5e-05, 6e-06, 3e-06], [0.002953, 0.00828, 3e-06, 0.001995]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_BTC-USD=0.0073, w_SGOV=0.9927, w_JNK=0.0000", "answer_numeric": 4.449803629858448, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_BTC-USD=0.0073, w_SGOV=0.9927, w_JNK=0.0000\nPortfolio annualized return: 6.01%, volatility: 0.45%\nSharpe ratio: (0.0601 - 0.0400) / 0.0045 = 4.4498", "metadata": {"weights": {"EEM": 0.0, "BTC-USD": 0.0073, "SGOV": 0.9927, "JNK": 0.0}, "sharpe_ratio": 4.4498, "portfolio_return": 0.060127, "portfolio_vol": 0.004523, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240118_0424", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "XRP-USD", "PPLT", "XHB"], "decision_date": "2024-01-18", "context_summary": "4-asset optimization. Max-Sharpe: 3.686. Portfolio: return=65.82%, vol=16.77%. Weights: w_XLK=0.2493, w_XRP-USD=0.0000, w_PPLT=0.0000, w_XHB=0.7507.", "question": "Assets: XLK, XRP-USD, PPLT, XHB\nAnnualized mean returns: XLK:0.3238, XRP-USD:-0.5836, PPLT:-0.0852, XHB:0.7692\nCovariance matrix (annualized):\n[[0.019733, 0.014325, 0.004852, 0.010641], [0.014325, 0.210594, 0.001294, 0.042891], [0.004852, 0.001294, 0.044262, 0.011561], [0.010641, 0.042891, 0.011561, 0.040652]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.2493, w_XRP-USD=0.0000, w_PPLT=0.0000, w_XHB=0.7507", "answer_numeric": 3.686451099749396, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.2493, w_XRP-USD=0.0000, w_PPLT=0.0000, w_XHB=0.7507\nPortfolio annualized return: 65.82%, volatility: 16.77%\nSharpe ratio: (0.6582 - 0.0400) / 0.1677 = 3.6865", "metadata": {"weights": {"XLK": 0.2493, "XRP-USD": 0.0, "PPLT": 0.0, "XHB": 0.7507}, "sharpe_ratio": 3.6865, "portfolio_return": 0.658162, "portfolio_vol": 0.167685, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240726_0425", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "SOYB", "XHB"], "decision_date": "2024-07-26", "context_summary": "4-asset optimization. Max-Sharpe: 1.004. Portfolio: return=32.27%, vol=28.15%. Weights: w_XLB=0.0000, w_LINK-USD=0.0000, w_SOYB=0.0000, w_XHB=1.0000.", "question": "Assets: XLB, LINK-USD, SOYB, XHB\nAnnualized mean returns: XLB:-0.0725, LINK-USD:-2.4242, SOYB:-0.6479, XHB:0.3227\nCovariance matrix (annualized):\n[[0.017175, -0.001133, 0.006615, 0.029929], [-0.001133, 0.30837, -0.036727, 0.019624], [0.006615, -0.036727, 0.029085, 0.013162], [0.029929, 0.019624, 0.013162, 0.079268]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_LINK-USD=0.0000, w_SOYB=0.0000, w_XHB=1.0000", "answer_numeric": 1.0042393604202413, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_LINK-USD=0.0000, w_SOYB=0.0000, w_XHB=1.0000\nPortfolio annualized return: 32.27%, volatility: 28.15%\nSharpe ratio: (0.3227 - 0.0400) / 0.2815 = 1.0042", "metadata": {"weights": {"XLB": 0.0, "LINK-USD": 0.0, "SOYB": 0.0, "XHB": 1.0}, "sharpe_ratio": 1.0042, "portfolio_return": 0.32274, "portfolio_vol": 0.281546, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230522_0428", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "XHB", "SGOV"], "decision_date": "2023-05-22", "context_summary": "4-asset optimization. Max-Sharpe: 3.918. Portfolio: return=5.52%, vol=0.39%. Weights: w_IWM=0.0000, w_AVAX-USD=0.0000, w_XHB=0.0163, w_SGOV=0.9837.", "question": "Assets: IWM, AVAX-USD, XHB, SGOV\nAnnualized mean returns: IWM:0.1807, AVAX-USD:-0.1463, XHB:0.6007, SGOV:0.0462\nCovariance matrix (annualized):\n[[0.030876, 0.003771, 0.025795, -0.000104], [0.003771, 0.267007, 0.013363, -0.000116], [0.025795, 0.013363, 0.039412, -8.9e-05], [-0.000104, -0.000116, -8.9e-05, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_AVAX-USD=0.0000, w_XHB=0.0163, w_SGOV=0.9837", "answer_numeric": 3.9182817477649956, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_AVAX-USD=0.0000, w_XHB=0.0163, w_SGOV=0.9837\nPortfolio annualized return: 5.52%, volatility: 0.39%\nSharpe ratio: (0.0552 - 0.0400) / 0.0039 = 3.9183", "metadata": {"weights": {"IWM": 0.0, "AVAX-USD": 0.0, "XHB": 0.0163, "SGOV": 0.9837}, "sharpe_ratio": 3.9183, "portfolio_return": 0.055235, "portfolio_vol": 0.003888, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240624_0430", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "XRP-USD", "TLH", "BIL"], "decision_date": "2024-06-24", "context_summary": "4-asset optimization. Max-Sharpe: 9.027. Portfolio: return=6.86%, vol=0.32%. Weights: w_QUAL=0.0276, w_XRP-USD=0.0000, w_TLH=0.0018, w_BIL=0.9706.", "question": "Assets: QUAL, XRP-USD, TLH, BIL\nAnnualized mean returns: QUAL:0.5672, XRP-USD:-0.1339, TLH:0.3765, BIL:0.0539\nCovariance matrix (annualized):\n[[0.009203, 0.012048, 0.004553, -8e-05], [0.012048, 0.117511, 0.009486, -1.8e-05], [0.004553, 0.009486, 0.01265, -3.1e-05], [-8e-05, -1.8e-05, -3.1e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0276, w_XRP-USD=0.0000, w_TLH=0.0018, w_BIL=0.9706", "answer_numeric": 9.027382224718876, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0276, w_XRP-USD=0.0000, w_TLH=0.0018, w_BIL=0.9706\nPortfolio annualized return: 6.86%, volatility: 0.32%\nSharpe ratio: (0.0686 - 0.0400) / 0.0032 = 9.0274", "metadata": {"weights": {"QUAL": 0.0276, "XRP-USD": 0.0, "TLH": 0.0018, "BIL": 0.9706}, "sharpe_ratio": 9.0274, "portfolio_return": 0.068612, "portfolio_vol": 0.003169, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231220_0432", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "PDBC", "VCIT"], "decision_date": "2023-12-20", "context_summary": "4-asset optimization. Max-Sharpe: 8.336. Portfolio: return=65.98%, vol=7.43%. Weights: w_QQQ=0.2308, w_ETH-USD=0.0702, w_PDBC=0.0000, w_VCIT=0.6990.", "question": "Assets: QQQ, ETH-USD, PDBC, VCIT\nAnnualized mean returns: QQQ:0.8919, ETH-USD:1.3062, PDBC:-0.3596, VCIT:0.5182\nCovariance matrix (annualized):\n[[0.022499, -0.011894, 0.002139, 0.004636], [-0.011894, 0.275948, 0.003988, -0.00763], [0.002139, 0.003988, 0.031187, -0.000359], [0.004636, -0.00763, -0.000359, 0.005337]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.2308, w_ETH-USD=0.0702, w_PDBC=0.0000, w_VCIT=0.6990", "answer_numeric": 8.335657052598554, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.2308, w_ETH-USD=0.0702, w_PDBC=0.0000, w_VCIT=0.6990\nPortfolio annualized return: 65.98%, volatility: 7.43%\nSharpe ratio: (0.6598 - 0.0400) / 0.0743 = 8.3357", "metadata": {"weights": {"QQQ": 0.2308, "ETH-USD": 0.0702, "PDBC": 0.0, "VCIT": 0.699}, "sharpe_ratio": 8.3357, "portfolio_return": 0.659754, "portfolio_vol": 0.07435, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241226_0434", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "AVAX-USD", "ICSH", "TLH"], "decision_date": "2024-12-26", "context_summary": "4-asset optimization. Max-Sharpe: 3.365. Portfolio: return=28.19%, vol=7.19%. Weights: w_XLV=0.0000, w_AVAX-USD=0.0640, w_ICSH=0.9360, w_TLH=0.0000.", "question": "Assets: XLV, AVAX-USD, ICSH, TLH\nAnnualized mean returns: XLV:-0.3682, AVAX-USD:3.7771, ICSH:0.0431, TLH:-0.1717\nCovariance matrix (annualized):\n[[0.016062, 0.029768, 2.4e-05, 0.003645], [0.029768, 1.239514, 0.000577, 0.005896], [2.4e-05, 0.000577, 3.1e-05, 0.000316], [0.003645, 0.005896, 0.000316, 0.013586]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_AVAX-USD=0.0640, w_ICSH=0.9360, w_TLH=0.0000", "answer_numeric": 3.36531768618153, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_AVAX-USD=0.0640, w_ICSH=0.9360, w_TLH=0.0000\nPortfolio annualized return: 28.19%, volatility: 7.19%\nSharpe ratio: (0.2819 - 0.0400) / 0.0719 = 3.3653", "metadata": {"weights": {"XLV": 0.0, "AVAX-USD": 0.064, "ICSH": 0.936, "TLH": 0.0}, "sharpe_ratio": 3.3653, "portfolio_return": 0.281898, "portfolio_vol": 0.07188, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231127_0436", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "ICSH", "BNDX"], "decision_date": "2023-11-27", "context_summary": "4-asset optimization. Max-Sharpe: 8.009. Portfolio: return=7.75%, vol=0.47%. Weights: w_FXI=0.0000, w_BTC-USD=0.0085, w_ICSH=0.9915, w_BNDX=0.0000.", "question": "Assets: FXI, BTC-USD, ICSH, BNDX\nAnnualized mean returns: FXI:-0.0116, BTC-USD:1.6954, ICSH:0.0636, BNDX:0.1344\nCovariance matrix (annualized):\n[[0.063793, 0.022424, 7.5e-05, 0.002945], [0.022424, 0.186928, -0.000632, -0.004583], [7.5e-05, -0.000632, 1.9e-05, 0.000103], [0.002945, -0.004583, 0.000103, 0.003215]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_BTC-USD=0.0085, w_ICSH=0.9915, w_BNDX=0.0000", "answer_numeric": 8.008894183617976, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_BTC-USD=0.0085, w_ICSH=0.9915, w_BNDX=0.0000\nPortfolio annualized return: 7.75%, volatility: 0.47%\nSharpe ratio: (0.0775 - 0.0400) / 0.0047 = 8.0089", "metadata": {"weights": {"FXI": 0.0, "BTC-USD": 0.0085, "ICSH": 0.9915, "BNDX": 0.0}, "sharpe_ratio": 8.0089, "portfolio_return": 0.077474, "portfolio_vol": 0.004679, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230203_0439", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BNB-USD", "DBB", "TLT"], "decision_date": "2023-02-03", "context_summary": "4-asset optimization. Max-Sharpe: 1.655. Portfolio: return=27.81%, vol=14.38%. Weights: w_ACWI=0.4780, w_BNB-USD=0.0000, w_DBB=0.4688, w_TLT=0.0532.", "question": "Assets: ACWI, BNB-USD, DBB, TLT\nAnnualized mean returns: ACWI:0.2634, BNB-USD:-0.2833, DBB:0.3088, TLT:0.1385\nCovariance matrix (annualized):\n[[0.026399, 0.037461, 0.01375, 0.006546], [0.037461, 0.195288, 0.028177, 0.001604], [0.01375, 0.028177, 0.035028, 0.006923], [0.006546, 0.001604, 0.006923, 0.041124]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.4780, w_BNB-USD=0.0000, w_DBB=0.4688, w_TLT=0.0532", "answer_numeric": 1.6551185376585678, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.4780, w_BNB-USD=0.0000, w_DBB=0.4688, w_TLT=0.0532\nPortfolio annualized return: 27.81%, volatility: 14.38%\nSharpe ratio: (0.2781 - 0.0400) / 0.1438 = 1.6551", "metadata": {"weights": {"ACWI": 0.478, "BNB-USD": 0.0, "DBB": 0.4688, "TLT": 0.0532}, "sharpe_ratio": 1.6551, "portfolio_return": 0.278056, "portfolio_vol": 0.14383, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241206_0441", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "BIL", "INDS"], "decision_date": "2024-12-06", "context_summary": "4-asset optimization. Max-Sharpe: 4.359. Portfolio: return=7.47%, vol=0.80%. Weights: w_MTUM=0.0246, w_LINK-USD=0.0065, w_BIL=0.9689, w_INDS=0.0000.", "question": "Assets: MTUM, LINK-USD, BIL, INDS\nAnnualized mean returns: MTUM:0.3579, LINK-USD:3.5041, BIL:0.0444, INDS:-0.5244\nCovariance matrix (annualized):\n[[0.015407, 0.0333, -1.6e-05, 0.004612], [0.0333, 0.784846, 0.000396, 0.025762], [-1.6e-05, 0.000396, 6e-06, -5e-06], [0.004612, 0.025762, -5e-06, 0.030015]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0246, w_LINK-USD=0.0065, w_BIL=0.9689, w_INDS=0.0000", "answer_numeric": 4.358749286881015, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0246, w_LINK-USD=0.0065, w_BIL=0.9689, w_INDS=0.0000\nPortfolio annualized return: 7.47%, volatility: 0.80%\nSharpe ratio: (0.0747 - 0.0400) / 0.0080 = 4.3587", "metadata": {"weights": {"MTUM": 0.0246, "LINK-USD": 0.0065, "BIL": 0.9689, "INDS": 0.0}, "sharpe_ratio": 4.3587, "portfolio_return": 0.074694, "portfolio_vol": 0.00796, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230629_0444", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "REZ", "TIP"], "decision_date": "2023-06-29", "context_summary": "4-asset optimization. Max-Sharpe: 1.503. Portfolio: return=21.72%, vol=11.79%. Weights: w_ACWI=0.8781, w_BTC-USD=0.1219, w_REZ=0.0000, w_TIP=0.0000.", "question": "Assets: ACWI, BTC-USD, REZ, TIP\nAnnualized mean returns: ACWI:0.2029, BTC-USD:0.3204, REZ:0.0304, TIP:-0.0417\nCovariance matrix (annualized):\n[[0.013982, 0.004158, 0.010743, -0.000292], [0.004158, 0.150533, 0.003955, 0.001682], [0.010743, 0.003955, 0.03113, -0.000268], [-0.000292, 0.001682, -0.000268, 0.000676]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.8781, w_BTC-USD=0.1219, w_REZ=0.0000, w_TIP=0.0000", "answer_numeric": 1.5025811310016275, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.8781, w_BTC-USD=0.1219, w_REZ=0.0000, w_TIP=0.0000\nPortfolio annualized return: 21.72%, volatility: 11.79%\nSharpe ratio: (0.2172 - 0.0400) / 0.1179 = 1.5026", "metadata": {"weights": {"ACWI": 0.8781, "BTC-USD": 0.1219, "REZ": 0.0, "TIP": 0.0}, "sharpe_ratio": 1.5026, "portfolio_return": 0.217209, "portfolio_vol": 0.117936, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240919_0446", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "DOT-USD", "SCHH", "TLT"], "decision_date": "2024-09-19", "context_summary": "4-asset optimization. Max-Sharpe: 4.831. Portfolio: return=52.71%, vol=10.08%. Weights: w_XLV=0.0000, w_DOT-USD=0.0000, w_SCHH=0.5750, w_TLT=0.4250.", "question": "Assets: XLV, DOT-USD, SCHH, TLT\nAnnualized mean returns: XLV:0.2965, DOT-USD:-1.5944, SCHH:0.6055, TLT:0.4211\nCovariance matrix (annualized):\n[[0.014695, 0.029569, 0.011324, -0.002061], [0.029569, 0.273652, 0.041882, -0.021295], [0.011324, 0.041882, 0.020371, 0.00021], [-0.002061, -0.021295, 0.00021, 0.018434]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_DOT-USD=0.0000, w_SCHH=0.5750, w_TLT=0.4250", "answer_numeric": 4.831012868945791, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_DOT-USD=0.0000, w_SCHH=0.5750, w_TLT=0.4250\nPortfolio annualized return: 52.71%, volatility: 10.08%\nSharpe ratio: (0.5271 - 0.0400) / 0.1008 = 4.8310", "metadata": {"weights": {"XLV": 0.0, "DOT-USD": 0.0, "SCHH": 0.575, "TLT": 0.425}, "sharpe_ratio": 4.831, "portfolio_return": 0.527123, "portfolio_vol": 0.100833, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240715_0449", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "SOL-USD", "REZ", "TLH"], "decision_date": "2024-07-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.397. Portfolio: return=40.29%, vol=10.68%. Weights: w_XLY=0.6761, w_SOL-USD=0.0000, w_REZ=0.3239, w_TLH=0.0000.", "question": "Assets: XLY, SOL-USD, REZ, TLH\nAnnualized mean returns: XLY:0.4515, SOL-USD:-0.0971, REZ:0.3013, TLH:0.1578\nCovariance matrix (annualized):\n[[0.017262, 0.012942, 0.003922, 0.001852], [0.012942, 0.459475, 0.00287, 0.003535], [0.003922, 0.00287, 0.017185, 0.009197], [0.001852, 0.003535, 0.009197, 0.015656]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.6761, w_SOL-USD=0.0000, w_REZ=0.3239, w_TLH=0.0000", "answer_numeric": 3.3968274610893534, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.6761, w_SOL-USD=0.0000, w_REZ=0.3239, w_TLH=0.0000\nPortfolio annualized return: 40.29%, volatility: 10.68%\nSharpe ratio: (0.4029 - 0.0400) / 0.1068 = 3.3968", "metadata": {"weights": {"XLY": 0.6761, "SOL-USD": 0.0, "REZ": 0.3239, "TLH": 0.0}, "sharpe_ratio": 3.3968, "portfolio_return": 0.402867, "portfolio_vol": 0.106825, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240514_0451", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "ETH-USD", "IYR", "BIL"], "decision_date": "2024-05-14", "context_summary": "4-asset optimization. Max-Sharpe: -3.164. Portfolio: return=-53.13%, vol=18.06%. Weights: w_XLE=0.2500, w_ETH-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500.", "question": "Assets: XLE, ETH-USD, IYR, BIL\nAnnualized mean returns: XLE:0.2018, ETH-USD:-2.3246, IYR:-0.0534, BIL:0.0512\nCovariance matrix (annualized):\n[[0.020637, 0.010295, 0.009557, 0.000101], [0.010295, 0.368759, 0.030275, 0.000172], [0.009557, 0.030275, 0.031238, 0.0001], [0.000101, 0.000172, 0.0001, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.2500, w_ETH-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500", "answer_numeric": -3.163791804593793, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.2500, w_ETH-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500\nPortfolio annualized return: -53.13%, volatility: 18.06%\nSharpe ratio: (-0.5313 - 0.0400) / 0.1806 = -3.1638", "metadata": {"weights": {"XLE": 0.25, "ETH-USD": 0.25, "IYR": 0.25, "BIL": 0.25}, "sharpe_ratio": -3.1638, "portfolio_return": -0.53126, "portfolio_vol": 0.180562, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230217_0453", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SOL-USD", "CPER", "HYG"], "decision_date": "2023-02-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.460. Portfolio: return=54.82%, vol=14.69%. Weights: w_VTI=0.4097, w_SOL-USD=0.0246, w_CPER=0.5657, w_HYG=0.0000.", "question": "Assets: VTI, SOL-USD, CPER, HYG\nAnnualized mean returns: VTI:0.4305, SOL-USD:1.4818, CPER:0.5928, HYG:0.0067\nCovariance matrix (annualized):\n[[0.02891, 0.069648, 0.005329, 0.01368], [0.069648, 1.154582, 0.007495, 0.034603], [0.005329, 0.007495, 0.037288, 0.003395], [0.01368, 0.034603, 0.003395, 0.010654]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.4097, w_SOL-USD=0.0246, w_CPER=0.5657, w_HYG=0.0000", "answer_numeric": 3.460473653951888, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.4097, w_SOL-USD=0.0246, w_CPER=0.5657, w_HYG=0.0000\nPortfolio annualized return: 54.82%, volatility: 14.69%\nSharpe ratio: (0.5482 - 0.0400) / 0.1469 = 3.4605", "metadata": {"weights": {"VTI": 0.4097, "SOL-USD": 0.0246, "CPER": 0.5657, "HYG": 0.0}, "sharpe_ratio": 3.4605, "portfolio_return": 0.548196, "portfolio_vol": 0.146857, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230510_0455", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "MORT", "SHV"], "decision_date": "2023-05-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.695. Portfolio: return=46.25%, vol=60.82%. Weights: w_XLB=0.0000, w_LINK-USD=1.0000, w_MORT=0.0000, w_SHV=0.0000.", "question": "Assets: XLB, LINK-USD, MORT, SHV\nAnnualized mean returns: XLB:0.0659, LINK-USD:0.4625, MORT:-0.1219, SHV:0.0384\nCovariance matrix (annualized):\n[[0.034691, 0.025625, 0.037857, -0.000375], [0.025625, 0.369924, -0.011174, 3.5e-05], [0.037857, -0.011174, 0.079101, -0.000505], [-0.000375, 3.5e-05, -0.000505, 1.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_LINK-USD=1.0000, w_MORT=0.0000, w_SHV=0.0000", "answer_numeric": 0.6946382790727248, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_LINK-USD=1.0000, w_MORT=0.0000, w_SHV=0.0000\nPortfolio annualized return: 46.25%, volatility: 60.82%\nSharpe ratio: (0.4625 - 0.0400) / 0.6082 = 0.6946", "metadata": {"weights": {"XLB": 0.0, "LINK-USD": 1.0, "MORT": 0.0, "SHV": 0.0}, "sharpe_ratio": 0.6946, "portfolio_return": 0.462488, "portfolio_vol": 0.608213, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241119_0458", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SOL-USD", "IGOV", "CSHI"], "decision_date": "2024-11-19", "context_summary": "4-asset optimization. Max-Sharpe: 4.158. Portfolio: return=6.95%, vol=0.71%. Weights: w_EEM=0.0000, w_SOL-USD=0.0062, w_IGOV=0.0000, w_CSHI=0.9938.", "question": "Assets: EEM, SOL-USD, IGOV, CSHI\nAnnualized mean returns: EEM:-0.0827, SOL-USD:1.5594, IGOV:-0.3030, CSHI:0.0602\nCovariance matrix (annualized):\n[[0.042326, 0.034969, 0.007505, 2.1e-05], [0.034969, 0.383817, 0.008906, 0.000203], [0.007505, 0.008906, 0.007396, -5.7e-05], [2.1e-05, 0.000203, -5.7e-05, 3.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_SOL-USD=0.0062, w_IGOV=0.0000, w_CSHI=0.9938", "answer_numeric": 4.158108050163586, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_SOL-USD=0.0062, w_IGOV=0.0000, w_CSHI=0.9938\nPortfolio annualized return: 6.95%, volatility: 0.71%\nSharpe ratio: (0.0695 - 0.0400) / 0.0071 = 4.1581", "metadata": {"weights": {"EEM": 0.0, "SOL-USD": 0.0062, "IGOV": 0.0, "CSHI": 0.9938}, "sharpe_ratio": 4.1581, "portfolio_return": 0.06951, "portfolio_vol": 0.007097, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230926_0461", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "BNDX", "UNG"], "decision_date": "2023-09-26", "context_summary": "4-asset optimization. Max-Sharpe: 0.577. Portfolio: return=33.83%, vol=51.72%. Weights: w_XLB=0.0000, w_LINK-USD=1.0000, w_BNDX=0.0000, w_UNG=0.0000.", "question": "Assets: XLB, LINK-USD, BNDX, UNG\nAnnualized mean returns: XLB:-0.3980, LINK-USD:0.3383, BNDX:-0.0733, UNG:-0.1303\nCovariance matrix (annualized):\n[[0.016012, 0.014879, 0.000922, 0.020311], [0.014879, 0.267477, 0.001491, 0.036163], [0.000922, 0.001491, 0.00191, 0.000843], [0.020311, 0.036163, 0.000843, 0.209837]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_LINK-USD=1.0000, w_BNDX=0.0000, w_UNG=0.0000", "answer_numeric": 0.5768560131709248, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_LINK-USD=1.0000, w_BNDX=0.0000, w_UNG=0.0000\nPortfolio annualized return: 33.83%, volatility: 51.72%\nSharpe ratio: (0.3383 - 0.0400) / 0.5172 = 0.5769", "metadata": {"weights": {"XLB": 0.0, "LINK-USD": 1.0, "BNDX": 0.0, "UNG": 0.0}, "sharpe_ratio": 0.5769, "portfolio_return": 0.33834, "portfolio_vol": 0.517182, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230208_0463", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "PDBC", "ICSH"], "decision_date": "2023-02-08", "context_summary": "4-asset optimization. Max-Sharpe: 3.697. Portfolio: return=5.90%, vol=0.51%. Weights: w_QUAL=0.0055, w_ADA-USD=0.0012, w_PDBC=0.0000, w_ICSH=0.9933.", "question": "Assets: QUAL, ADA-USD, PDBC, ICSH\nAnnualized mean returns: QUAL:0.4629, ADA-USD:0.8731, PDBC:0.1412, ICSH:0.0557\nCovariance matrix (annualized):\n[[0.038367, 0.056924, 0.017027, 0.000308], [0.056924, 0.391602, 0.041276, 0.000372], [0.017027, 0.041276, 0.041129, 0.000123], [0.000308, 0.000372, 0.000123, 2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0055, w_ADA-USD=0.0012, w_PDBC=0.0000, w_ICSH=0.9933", "answer_numeric": 3.6972736568708053, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0055, w_ADA-USD=0.0012, w_PDBC=0.0000, w_ICSH=0.9933\nPortfolio annualized return: 5.90%, volatility: 0.51%\nSharpe ratio: (0.0590 - 0.0400) / 0.0051 = 3.6973", "metadata": {"weights": {"QUAL": 0.0055, "ADA-USD": 0.0012, "PDBC": 0.0, "ICSH": 0.9933}, "sharpe_ratio": 3.6973, "portfolio_return": 0.058954, "portfolio_vol": 0.005127, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240731_0465", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "CSHI", "ITB"], "decision_date": "2024-07-31", "context_summary": "4-asset optimization. Max-Sharpe: 3.881. Portfolio: return=7.08%, vol=0.79%. Weights: w_IVV=0.0052, w_ADA-USD=0.0000, w_CSHI=0.9730, w_ITB=0.0218.", "question": "Assets: IVV, ADA-USD, CSHI, ITB\nAnnualized mean returns: IVV:0.1931, ADA-USD:-0.1286, CSHI:0.0556, ITB:0.7168\nCovariance matrix (annualized):\n[[0.011639, 0.007937, 2.8e-05, 0.010294], [0.007937, 0.234647, 0.000943, 0.020329], [2.8e-05, 0.000943, 4.5e-05, -0.00055], [0.010294, 0.020329, -0.00055, 0.085429]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0052, w_ADA-USD=0.0000, w_CSHI=0.9730, w_ITB=0.0218", "answer_numeric": 3.880825531802794, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0052, w_ADA-USD=0.0000, w_CSHI=0.9730, w_ITB=0.0218\nPortfolio annualized return: 7.08%, volatility: 0.79%\nSharpe ratio: (0.0708 - 0.0400) / 0.0079 = 3.8808", "metadata": {"weights": {"IVV": 0.0052, "ADA-USD": 0.0, "CSHI": 0.973, "ITB": 0.0218}, "sharpe_ratio": 3.8808, "portfolio_return": 0.070758, "portfolio_vol": 0.007926, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240612_0468", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "MATIC-USD", "ICSH", "VNQ"], "decision_date": "2024-06-12", "context_summary": "4-asset optimization. Max-Sharpe: 4.594. Portfolio: return=5.59%, vol=0.35%. Weights: w_XLB=0.0000, w_MATIC-USD=0.0000, w_ICSH=1.0000, w_VNQ=0.0000.", "question": "Assets: XLB, MATIC-USD, ICSH, VNQ\nAnnualized mean returns: XLB:-0.0171, MATIC-USD:-1.0041, ICSH:0.0559, VNQ:0.1032\nCovariance matrix (annualized):\n[[0.014233, 0.010733, 9.1e-05, 0.010523], [0.010733, 0.28085, 0.001281, 0.017412], [9.1e-05, 0.001281, 1.2e-05, 0.000132], [0.010523, 0.017412, 0.000132, 0.023353]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_MATIC-USD=0.0000, w_ICSH=1.0000, w_VNQ=0.0000", "answer_numeric": 4.594123001280084, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_MATIC-USD=0.0000, w_ICSH=1.0000, w_VNQ=0.0000\nPortfolio annualized return: 5.59%, volatility: 0.35%\nSharpe ratio: (0.0559 - 0.0400) / 0.0035 = 4.5941", "metadata": {"weights": {"XLB": 0.0, "MATIC-USD": 0.0, "ICSH": 1.0, "VNQ": 0.0}, "sharpe_ratio": 4.5941, "portfolio_return": 0.055851, "portfolio_vol": 0.00345, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230710_0470", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "IAU", "IYR"], "decision_date": "2023-07-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.737. Portfolio: return=16.20%, vol=16.55%. Weights: w_XLU=0.0000, w_AVAX-USD=0.0000, w_IAU=0.0000, w_IYR=1.0000.", "question": "Assets: XLU, AVAX-USD, IAU, IYR\nAnnualized mean returns: XLU:-0.3291, AVAX-USD:0.0020, IAU:-0.3475, IYR:0.1620\nCovariance matrix (annualized):\n[[0.020376, 0.002521, 0.002977, 0.015049], [0.002521, 0.23457, 0.005701, 0.011137], [0.002977, 0.005701, 0.011758, 0.001852], [0.015049, 0.011137, 0.001852, 0.027405]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_AVAX-USD=0.0000, w_IAU=0.0000, w_IYR=1.0000", "answer_numeric": 0.7368479657288097, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_AVAX-USD=0.0000, w_IAU=0.0000, w_IYR=1.0000\nPortfolio annualized return: 16.20%, volatility: 16.55%\nSharpe ratio: (0.1620 - 0.0400) / 0.1655 = 0.7368", "metadata": {"weights": {"XLU": 0.0, "AVAX-USD": 0.0, "IAU": 0.0, "IYR": 1.0}, "sharpe_ratio": 0.7368, "portfolio_return": 0.161981, "portfolio_vol": 0.165545, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231204_0472", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "IYR", "BIL"], "decision_date": "2023-12-04", "context_summary": "4-asset optimization. Max-Sharpe: 7.098. Portfolio: return=5.92%, vol=0.27%. Weights: w_XLI=0.0112, w_BNB-USD=0.0002, w_IYR=0.0010, w_BIL=0.9877.", "question": "Assets: XLI, BNB-USD, IYR, BIL\nAnnualized mean returns: XLI:0.5144, BNB-USD:-0.0008, IYR:0.6741, BIL:0.0535\nCovariance matrix (annualized):\n[[0.022645, 0.004465, 0.025135, -9.9e-05], [0.004465, 0.178089, 0.004258, -0.000107], [0.025135, 0.004258, 0.046387, -8.6e-05], [-9.9e-05, -0.000107, -8.6e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0112, w_BNB-USD=0.0002, w_IYR=0.0010, w_BIL=0.9877", "answer_numeric": 7.097683148078809, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0112, w_BNB-USD=0.0002, w_IYR=0.0010, w_BIL=0.9877\nPortfolio annualized return: 5.92%, volatility: 0.27%\nSharpe ratio: (0.0592 - 0.0400) / 0.0027 = 7.0977", "metadata": {"weights": {"XLI": 0.0112, "BNB-USD": 0.0002, "IYR": 0.001, "BIL": 0.9877}, "sharpe_ratio": 7.0977, "portfolio_return": 0.059211, "portfolio_vol": 0.002707, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231218_0474", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "AVAX-USD", "ICSH", "MORT"], "decision_date": "2023-12-18", "context_summary": "4-asset optimization. Max-Sharpe: 9.979. Portfolio: return=9.82%, vol=0.58%. Weights: w_XLV=0.0000, w_AVAX-USD=0.0043, w_ICSH=0.9957, w_MORT=0.0000.", "question": "Assets: XLV, AVAX-USD, ICSH, MORT\nAnnualized mean returns: XLV:0.2007, AVAX-USD:5.6353, ICSH:0.0743, MORT:0.9722\nCovariance matrix (annualized):\n[[0.015319, 0.003479, 8e-05, 0.01905], [0.003479, 0.992841, -0.001008, 0.018902], [8e-05, -0.001008, 2.4e-05, 0.000564], [0.01905, 0.018902, 0.000564, 0.086796]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_AVAX-USD=0.0043, w_ICSH=0.9957, w_MORT=0.0000", "answer_numeric": 9.978615043292073, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_AVAX-USD=0.0043, w_ICSH=0.9957, w_MORT=0.0000\nPortfolio annualized return: 9.82%, volatility: 0.58%\nSharpe ratio: (0.0982 - 0.0400) / 0.0058 = 9.9786", "metadata": {"weights": {"XLV": 0.0, "AVAX-USD": 0.0043, "ICSH": 0.9957, "MORT": 0.0}, "sharpe_ratio": 9.9786, "portfolio_return": 0.098226, "portfolio_vol": 0.005835, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240404_0477", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "XRP-USD", "CSHI", "SCHP"], "decision_date": "2024-04-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.041. Portfolio: return=5.64%, vol=0.80%. Weights: w_QQQ=0.0172, w_XRP-USD=0.0033, w_CSHI=0.9795, w_SCHP=0.0000.", "question": "Assets: QQQ, XRP-USD, CSHI, SCHP\nAnnualized mean returns: QQQ:0.1929, XRP-USD:0.7608, CSHI:0.0516, SCHP:-0.0138\nCovariance matrix (annualized):\n[[0.022233, 0.025373, 0.000138, 0.00082], [0.025373, 0.516667, 0.000723, -0.002077], [0.000138, 0.000723, 4.2e-05, -0.000108], [0.00082, -0.002077, -0.000108, 0.001927]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0172, w_XRP-USD=0.0033, w_CSHI=0.9795, w_SCHP=0.0000", "answer_numeric": 2.0409852704967615, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0172, w_XRP-USD=0.0033, w_CSHI=0.9795, w_SCHP=0.0000\nPortfolio annualized return: 5.64%, volatility: 0.80%\nSharpe ratio: (0.0564 - 0.0400) / 0.0080 = 2.0410", "metadata": {"weights": {"QQQ": 0.0172, "XRP-USD": 0.0033, "CSHI": 0.9795, "SCHP": 0.0}, "sharpe_ratio": 2.041, "portfolio_return": 0.056399, "portfolio_vol": 0.008035, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241002_0480", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD", "STIP", "SCHH"], "decision_date": "2024-10-02", "context_summary": "4-asset optimization. Max-Sharpe: 4.055. Portfolio: return=12.45%, vol=2.08%. Weights: w_QQQ=0.0231, w_BNB-USD=0.0000, w_STIP=0.9034, w_SCHH=0.0735.", "question": "Assets: QQQ, BNB-USD, STIP, SCHH\nAnnualized mean returns: QQQ:0.4386, BNB-USD:0.6691, STIP:0.0940, SCHH:0.4005\nCovariance matrix (annualized):\n[[0.048001, 0.058686, -3.5e-05, 0.013218], [0.058686, 0.222736, 5.1e-05, 0.027118], [-3.5e-05, 5.1e-05, 0.000288, 0.000247], [0.013218, 0.027118, 0.000247, 0.018017]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0231, w_BNB-USD=0.0000, w_STIP=0.9034, w_SCHH=0.0735", "answer_numeric": 4.054765534940782, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0231, w_BNB-USD=0.0000, w_STIP=0.9034, w_SCHH=0.0735\nPortfolio annualized return: 12.45%, volatility: 2.08%\nSharpe ratio: (0.1245 - 0.0400) / 0.0208 = 4.0548", "metadata": {"weights": {"QQQ": 0.0231, "BNB-USD": 0.0, "STIP": 0.9034, "SCHH": 0.0735}, "sharpe_ratio": 4.0548, "portfolio_return": 0.124506, "portfolio_vol": 0.020841, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230913_0483", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "TLH", "REZ"], "decision_date": "2023-09-13", "context_summary": "4-asset optimization. Max-Sharpe: -2.805. Portfolio: return=-31.98%, vol=12.83%. Weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_TLH=1.0000, w_REZ=0.0000.", "question": "Assets: VEA, ADA-USD, TLH, REZ\nAnnualized mean returns: VEA:-0.2525, ADA-USD:-1.6271, TLH:-0.3198, REZ:-0.4684\nCovariance matrix (annualized):\n[[0.012761, 0.011028, 0.005541, 0.005801], [0.011028, 0.133305, 0.020273, 0.009212], [0.005541, 0.020273, 0.016462, 0.003628], [0.005801, 0.009212, 0.003628, 0.020302]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_ADA-USD=0.0000, w_TLH=1.0000, w_REZ=0.0000", "answer_numeric": -2.80463712797285, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_TLH=1.0000, w_REZ=0.0000\nPortfolio annualized return: -31.98%, volatility: 12.83%\nSharpe ratio: (-0.3198 - 0.0400) / 0.1283 = -2.8046", "metadata": {"weights": {"VEA": 0.0, "ADA-USD": 0.0, "TLH": 1.0, "REZ": 0.0}, "sharpe_ratio": -2.8046, "portfolio_return": -0.319846, "portfolio_vol": 0.128304, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240801_0485", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "REZ", "SGOV"], "decision_date": "2024-08-01", "context_summary": "4-asset optimization. Max-Sharpe: 6.398. Portfolio: return=5.62%, vol=0.25%. Weights: w_QUAL=0.0010, w_MATIC-USD=0.0000, w_REZ=0.0095, w_SGOV=0.9896.", "question": "Assets: QUAL, MATIC-USD, REZ, SGOV\nAnnualized mean returns: QUAL:0.2326, MATIC-USD:-2.3419, REZ:0.4798, SGOV:0.0519\nCovariance matrix (annualized):\n[[0.01548, 0.006493, 0.003674, 2.7e-05], [0.006493, 0.268, 0.012628, -0.000151], [0.003674, 0.012628, 0.015608, 2.2e-05], [2.7e-05, -0.000151, 2.2e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0010, w_MATIC-USD=0.0000, w_REZ=0.0095, w_SGOV=0.9896", "answer_numeric": 6.398419773703526, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0010, w_MATIC-USD=0.0000, w_REZ=0.0095, w_SGOV=0.9896\nPortfolio annualized return: 5.62%, volatility: 0.25%\nSharpe ratio: (0.0562 - 0.0400) / 0.0025 = 6.3984", "metadata": {"weights": {"QUAL": 0.001, "MATIC-USD": 0.0, "REZ": 0.0095, "SGOV": 0.9896}, "sharpe_ratio": 6.3984, "portfolio_return": 0.05616, "portfolio_vol": 0.002526, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20230630_0487", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SOL-USD", "CPER", "IGOV"], "decision_date": "2023-06-30", "context_summary": "4-asset optimization. Max-Sharpe: 1.743. Portfolio: return=38.36%, vol=19.71%. Weights: w_IWM=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_IGOV=0.0000.", "question": "Assets: IWM, SOL-USD, CPER, IGOV\nAnnualized mean returns: IWM:0.3836, SOL-USD:-0.8538, CPER:-0.2635, IGOV:-0.1514\nCovariance matrix (annualized):\n[[0.038851, 0.032554, 0.014613, -0.003484], [0.032554, 0.400079, 0.009944, 0.004329], [0.014613, 0.009944, 0.040064, 0.000221], [-0.003484, 0.004329, 0.000221, 0.010236]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_IGOV=0.0000", "answer_numeric": 1.74313234110693, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_IGOV=0.0000\nPortfolio annualized return: 38.36%, volatility: 19.71%\nSharpe ratio: (0.3836 - 0.0400) / 0.1971 = 1.7431", "metadata": {"weights": {"IWM": 1.0, "SOL-USD": 0.0, "CPER": 0.0, "IGOV": 0.0}, "sharpe_ratio": 1.7431, "portfolio_return": 0.383583, "portfolio_vol": 0.197107, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230731_0490", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "REZ", "EMB"], "decision_date": "2023-07-31", "context_summary": "4-asset optimization. Max-Sharpe: 4.689. Portfolio: return=50.97%, vol=10.02%. Weights: w_XLP=0.4316, w_LINK-USD=0.0822, w_REZ=0.1093, w_EMB=0.3769.", "question": "Assets: XLP, LINK-USD, REZ, EMB\nAnnualized mean returns: XLP:0.3351, LINK-USD:2.7725, REZ:0.3619, EMB:0.2588\nCovariance matrix (annualized):\n[[0.008584, 0.01225, 0.006947, 0.002208], [0.01225, 0.613029, 0.000189, 0.00705], [0.006947, 0.000189, 0.030207, 0.001485], [0.002208, 0.00705, 0.001485, 0.007903]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.4316, w_LINK-USD=0.0822, w_REZ=0.1093, w_EMB=0.3769", "answer_numeric": 4.689032232232089, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.4316, w_LINK-USD=0.0822, w_REZ=0.1093, w_EMB=0.3769\nPortfolio annualized return: 50.97%, volatility: 10.02%\nSharpe ratio: (0.5097 - 0.0400) / 0.1002 = 4.6890", "metadata": {"weights": {"XLP": 0.4316, "LINK-USD": 0.0822, "REZ": 0.1093, "EMB": 0.3769}, "sharpe_ratio": 4.689, "portfolio_return": 0.509662, "portfolio_vol": 0.100162, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230818_0492", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "SOL-USD", "ICSH", "DBA"], "decision_date": "2023-08-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.981. Portfolio: return=6.89%, vol=0.58%. Weights: w_XLU=0.0000, w_SOL-USD=0.0044, w_ICSH=0.9956, w_DBA=0.0000.", "question": "Assets: XLU, SOL-USD, ICSH, DBA\nAnnualized mean returns: XLU:-0.3329, SOL-USD:2.2126, ICSH:0.0594, DBA:-0.2178\nCovariance matrix (annualized):\n[[0.024964, 0.012398, 3.7e-05, 0.007867], [0.012398, 0.598598, -0.000117, 0.003308], [3.7e-05, -0.000117, 2.3e-05, 4e-06], [0.007867, 0.003308, 4e-06, 0.014869]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_SOL-USD=0.0044, w_ICSH=0.9956, w_DBA=0.0000", "answer_numeric": 4.9805430351973285, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_SOL-USD=0.0044, w_ICSH=0.9956, w_DBA=0.0000\nPortfolio annualized return: 6.89%, volatility: 0.58%\nSharpe ratio: (0.0689 - 0.0400) / 0.0058 = 4.9805", "metadata": {"weights": {"XLU": 0.0, "SOL-USD": 0.0044, "ICSH": 0.9956, "DBA": 0.0}, "sharpe_ratio": 4.9805, "portfolio_return": 0.068922, "portfolio_vol": 0.005807, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240925_0494", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "ICSH", "MORT"], "decision_date": "2024-09-25", "context_summary": "4-asset optimization. Max-Sharpe: 7.838. Portfolio: return=7.36%, vol=0.43%. Weights: w_MTUM=0.0056, w_ADA-USD=0.0014, w_ICSH=0.9908, w_MORT=0.0022.", "question": "Assets: MTUM, ADA-USD, ICSH, MORT\nAnnualized mean returns: MTUM:0.4258, ADA-USD:0.7491, ICSH:0.0702, MORT:0.2348\nCovariance matrix (annualized):\n[[0.059605, 0.066256, -0.000262, 0.018507], [0.066256, 0.339665, -0.00057, 0.04077], [-0.000262, -0.00057, 1.9e-05, -0.000115], [0.018507, 0.04077, -0.000115, 0.026168]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0056, w_ADA-USD=0.0014, w_ICSH=0.9908, w_MORT=0.0022", "answer_numeric": 7.837736819738517, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0056, w_ADA-USD=0.0014, w_ICSH=0.9908, w_MORT=0.0022\nPortfolio annualized return: 7.36%, volatility: 0.43%\nSharpe ratio: (0.0736 - 0.0400) / 0.0043 = 7.8377", "metadata": {"weights": {"MTUM": 0.0056, "ADA-USD": 0.0014, "ICSH": 0.9908, "MORT": 0.0022}, "sharpe_ratio": 7.8377, "portfolio_return": 0.073585, "portfolio_vol": 0.004285, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241016_0496", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "CSHI", "STIP"], "decision_date": "2024-10-16", "context_summary": "4-asset optimization. Max-Sharpe: 3.502. Portfolio: return=9.97%, vol=1.70%. Weights: w_XLRE=0.1128, w_XRP-USD=0.0000, w_CSHI=0.6063, w_STIP=0.2809.", "question": "Assets: XLRE, XRP-USD, CSHI, STIP\nAnnualized mean returns: XLRE:0.3884, XRP-USD:-0.5910, CSHI:0.0570, STIP:0.0759\nCovariance matrix (annualized):\n[[0.012851, 0.012453, 0.000137, 0.000579], [0.012453, 0.181848, 0.0001, 0.000834], [0.000137, 0.0001, 0.000111, 0.0], [0.000579, 0.000834, 0.0, 0.000388]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.1128, w_XRP-USD=0.0000, w_CSHI=0.6063, w_STIP=0.2809", "answer_numeric": 3.5021742270395766, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.1128, w_XRP-USD=0.0000, w_CSHI=0.6063, w_STIP=0.2809\nPortfolio annualized return: 9.97%, volatility: 1.70%\nSharpe ratio: (0.0997 - 0.0400) / 0.0170 = 3.5022", "metadata": {"weights": {"XLRE": 0.1128, "XRP-USD": 0.0, "CSHI": 0.6063, "STIP": 0.2809}, "sharpe_ratio": 3.5022, "portfolio_return": 0.099681, "portfolio_vol": 0.017041, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240229_0498", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BNB-USD", "IAU", "SGOV"], "decision_date": "2024-02-29", "context_summary": "4-asset optimization. Max-Sharpe: 6.296. Portfolio: return=5.93%, vol=0.31%. Weights: w_XLU=0.0000, w_BNB-USD=0.0038, w_IAU=0.0000, w_SGOV=0.9962.", "question": "Assets: XLU, BNB-USD, IAU, SGOV\nAnnualized mean returns: XLU:-0.1256, BNB-USD:1.4968, IAU:-0.0852, SGOV:0.0538\nCovariance matrix (annualized):\n[[0.032014, 0.011915, 0.007729, 4.8e-05], [0.011915, 0.153325, 0.0051, 0.000128], [0.007729, 0.0051, 0.008548, 8.5e-05], [4.8e-05, 0.000128, 8.5e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_BNB-USD=0.0038, w_IAU=0.0000, w_SGOV=0.9962", "answer_numeric": 6.295974441955785, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_BNB-USD=0.0038, w_IAU=0.0000, w_SGOV=0.9962\nPortfolio annualized return: 5.93%, volatility: 0.31%\nSharpe ratio: (0.0593 - 0.0400) / 0.0031 = 6.2960", "metadata": {"weights": {"XLU": 0.0, "BNB-USD": 0.0038, "IAU": 0.0, "SGOV": 0.9962}, "sharpe_ratio": 6.296, "portfolio_return": 0.059277, "portfolio_vol": 0.003062, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240417_0499", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "AVAX-USD", "INDS", "LQD"], "decision_date": "2024-04-17", "context_summary": "4-asset optimization. Max-Sharpe: -0.102. Portfolio: return=3.16%, vol=8.29%. Weights: w_XLP=1.0000, w_AVAX-USD=0.0000, w_INDS=0.0000, w_LQD=0.0000.", "question": "Assets: XLP, AVAX-USD, INDS, LQD\nAnnualized mean returns: XLP:0.0316, AVAX-USD:-0.8461, INDS:-0.4238, LQD:-0.1198\nCovariance matrix (annualized):\n[[0.006865, 0.022901, 0.006524, 0.002358], [0.022901, 0.906873, 0.025855, -0.005048], [0.006524, 0.025855, 0.031153, 0.00826], [0.002358, -0.005048, 0.00826, 0.004741]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=1.0000, w_AVAX-USD=0.0000, w_INDS=0.0000, w_LQD=0.0000", "answer_numeric": -0.10162365580312381, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=1.0000, w_AVAX-USD=0.0000, w_INDS=0.0000, w_LQD=0.0000\nPortfolio annualized return: 3.16%, volatility: 8.29%\nSharpe ratio: (0.0316 - 0.0400) / 0.0829 = -0.1016", "metadata": {"weights": {"XLP": 1.0, "AVAX-USD": 0.0, "INDS": 0.0, "LQD": 0.0}, "sharpe_ratio": -0.1016, "portfolio_return": 0.03158, "portfolio_vol": 0.082856, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241017_0501", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "EMB", "MORT"], "decision_date": "2024-10-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.493. Portfolio: return=25.55%, vol=8.65%. Weights: w_IVV=0.4107, w_BNB-USD=0.0919, w_EMB=0.4975, w_MORT=0.0000.", "question": "Assets: IVV, BNB-USD, EMB, MORT\nAnnualized mean returns: IVV:0.3138, BNB-USD:0.6832, EMB:0.1284, MORT:0.2315\nCovariance matrix (annualized):\n[[0.014605, 0.020289, 0.003284, 0.008668], [0.020289, 0.139327, 0.00236, 0.018911], [0.003284, 0.00236, 0.003017, 0.004015], [0.008668, 0.018911, 0.004015, 0.020854]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.4107, w_BNB-USD=0.0919, w_EMB=0.4975, w_MORT=0.0000", "answer_numeric": 2.4927597537341786, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.4107, w_BNB-USD=0.0919, w_EMB=0.4975, w_MORT=0.0000\nPortfolio annualized return: 25.55%, volatility: 8.65%\nSharpe ratio: (0.2555 - 0.0400) / 0.0865 = 2.4928", "metadata": {"weights": {"IVV": 0.4107, "BNB-USD": 0.0919, "EMB": 0.4975, "MORT": 0.0}, "sharpe_ratio": 2.4928, "portfolio_return": 0.255507, "portfolio_vol": 0.086453, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241204_0504", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "SOL-USD", "EMB", "CSHI"], "decision_date": "2024-12-04", "context_summary": "4-asset optimization. Max-Sharpe: 3.942. Portfolio: return=6.54%, vol=0.64%. Weights: w_XLI=0.0000, w_SOL-USD=0.0065, w_EMB=0.0000, w_CSHI=0.9935.", "question": "Assets: XLI, SOL-USD, EMB, CSHI\nAnnualized mean returns: XLI:0.2391, SOL-USD:1.7830, EMB:0.0012, CSHI:0.0542\nCovariance matrix (annualized):\n[[0.020613, 0.048306, 0.001504, 0.000265], [0.048306, 0.425468, 0.006704, 0.0001], [0.001504, 0.006704, 0.004169, 1.8e-05], [0.000265, 0.0001, 1.8e-05, 2.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_SOL-USD=0.0065, w_EMB=0.0000, w_CSHI=0.9935", "answer_numeric": 3.9421615137773913, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_SOL-USD=0.0065, w_EMB=0.0000, w_CSHI=0.9935\nPortfolio annualized return: 6.54%, volatility: 0.64%\nSharpe ratio: (0.0654 - 0.0400) / 0.0064 = 3.9422", "metadata": {"weights": {"XLI": 0.0, "SOL-USD": 0.0065, "EMB": 0.0, "CSHI": 0.9935}, "sharpe_ratio": 3.9422, "portfolio_return": 0.065408, "portfolio_vol": 0.006445, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230216_0507", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "XHB", "PDBC"], "decision_date": "2023-02-16", "context_summary": "4-asset optimization. Max-Sharpe: 3.492. Portfolio: return=90.70%, vol=24.83%. Weights: w_FXI=0.0000, w_LINK-USD=0.1384, w_XHB=0.8616, w_PDBC=0.0000.", "question": "Assets: FXI, LINK-USD, XHB, PDBC\nAnnualized mean returns: FXI:0.3839, LINK-USD:1.0442, XHB:0.8850, PDBC:0.0525\nCovariance matrix (annualized):\n[[0.108426, 0.046849, 0.03979, -0.000527], [0.046849, 0.273308, 0.038945, 0.015519], [0.03979, 0.038945, 0.06346, 0.004447], [-0.000527, 0.015519, 0.004447, 0.037635]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_LINK-USD=0.1384, w_XHB=0.8616, w_PDBC=0.0000", "answer_numeric": 3.4923660740201865, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_LINK-USD=0.1384, w_XHB=0.8616, w_PDBC=0.0000\nPortfolio annualized return: 90.70%, volatility: 24.83%\nSharpe ratio: (0.9070 - 0.0400) / 0.2483 = 3.4924", "metadata": {"weights": {"FXI": 0.0, "LINK-USD": 0.1384, "XHB": 0.8616, "PDBC": 0.0}, "sharpe_ratio": 3.4924, "portfolio_return": 0.907013, "portfolio_vol": 0.24826, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240125_0509", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "SCHH", "CSHI"], "decision_date": "2024-01-25", "context_summary": "4-asset optimization. Max-Sharpe: 3.115. Portfolio: return=6.30%, vol=0.74%. Weights: w_XLP=0.0199, w_DOT-USD=0.0011, w_SCHH=0.0180, w_CSHI=0.9611.", "question": "Assets: XLP, DOT-USD, SCHH, CSHI\nAnnualized mean returns: XLP:0.1523, DOT-USD:0.6999, SCHH:0.3928, CSHI:0.0543\nCovariance matrix (annualized):\n[[0.014375, 0.011273, 0.008245, -0.000187], [0.011273, 0.903531, 0.037173, -0.000306], [0.008245, 0.037173, 0.034912, 6e-06], [-0.000187, -0.000306, 6e-06, 3.9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0199, w_DOT-USD=0.0011, w_SCHH=0.0180, w_CSHI=0.9611", "answer_numeric": 3.1149674803722363, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0199, w_DOT-USD=0.0011, w_SCHH=0.0180, w_CSHI=0.9611\nPortfolio annualized return: 6.30%, volatility: 0.74%\nSharpe ratio: (0.0630 - 0.0400) / 0.0074 = 3.1150", "metadata": {"weights": {"XLP": 0.0199, "DOT-USD": 0.0011, "SCHH": 0.018, "CSHI": 0.9611}, "sharpe_ratio": 3.115, "portfolio_return": 0.062989, "portfolio_vol": 0.00738, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240403_0510", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "SGOV", "JNK"], "decision_date": "2024-04-03", "context_summary": "4-asset optimization. Max-Sharpe: 8.238. Portfolio: return=5.74%, vol=0.21%. Weights: w_FXI=0.0031, w_ETH-USD=0.0013, w_SGOV=0.9956, w_JNK=0.0000.", "question": "Assets: FXI, ETH-USD, SGOV, JNK\nAnnualized mean returns: FXI:0.8251, ETH-USD:1.3933, SGOV:0.0533, JNK:0.0427\nCovariance matrix (annualized):\n[[0.075817, 0.034289, -7.9e-05, 0.003037], [0.034289, 0.388157, -0.000253, 0.005756], [-7.9e-05, -0.000253, 4e-06, 2.1e-05], [0.003037, 0.005756, 2.1e-05, 0.002122]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0031, w_ETH-USD=0.0013, w_SGOV=0.9956, w_JNK=0.0000", "answer_numeric": 8.238438588645069, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0031, w_ETH-USD=0.0013, w_SGOV=0.9956, w_JNK=0.0000\nPortfolio annualized return: 5.74%, volatility: 0.21%\nSharpe ratio: (0.0574 - 0.0400) / 0.0021 = 8.2384", "metadata": {"weights": {"FXI": 0.0031, "ETH-USD": 0.0013, "SGOV": 0.9956, "JNK": 0.0}, "sharpe_ratio": 8.2384, "portfolio_return": 0.057397, "portfolio_vol": 0.002112, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240112_0513", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ETH-USD", "VNQI", "WEAT"], "decision_date": "2024-01-12", "context_summary": "4-asset optimization. Max-Sharpe: 7.150. Portfolio: return=67.01%, vol=8.81%. Weights: w_XLV=0.8068, w_ETH-USD=0.0332, w_VNQI=0.0955, w_WEAT=0.0645.", "question": "Assets: XLV, ETH-USD, VNQI, WEAT\nAnnualized mean returns: XLV:0.7000, ETH-USD:1.4744, VNQI:0.5401, WEAT:0.0760\nCovariance matrix (annualized):\n[[0.009719, 0.006561, 0.004137, -0.00495], [0.006561, 0.297476, 0.022222, 0.006237], [0.004137, 0.022222, 0.023218, -0.001996], [-0.00495, 0.006237, -0.001996, 0.068518]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.8068, w_ETH-USD=0.0332, w_VNQI=0.0955, w_WEAT=0.0645", "answer_numeric": 7.149702024718172, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.8068, w_ETH-USD=0.0332, w_VNQI=0.0955, w_WEAT=0.0645\nPortfolio annualized return: 67.01%, volatility: 8.81%\nSharpe ratio: (0.6701 - 0.0400) / 0.0881 = 7.1497", "metadata": {"weights": {"XLV": 0.8068, "ETH-USD": 0.0332, "VNQI": 0.0955, "WEAT": 0.0645}, "sharpe_ratio": 7.1497, "portfolio_return": 0.6701, "portfolio_vol": 0.08813, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240208_0515", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "DOT-USD", "IEF", "BIL"], "decision_date": "2024-02-08", "context_summary": "4-asset optimization. Max-Sharpe: 4.531. Portfolio: return=5.30%, vol=0.29%. Weights: w_EEM=0.0000, w_DOT-USD=0.0000, w_IEF=0.0031, w_BIL=0.9969.", "question": "Assets: EEM, DOT-USD, IEF, BIL\nAnnualized mean returns: EEM:0.2174, DOT-USD:-0.2898, IEF:0.1006, BIL:0.0528\nCovariance matrix (annualized):\n[[0.02385, 0.036581, 0.003511, 0.000128], [0.036581, 0.818591, 0.001613, 0.000415], [0.003511, 0.001613, 0.006082, 1.9e-05], [0.000128, 0.000415, 1.9e-05, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_DOT-USD=0.0000, w_IEF=0.0031, w_BIL=0.9969", "answer_numeric": 4.530894343803099, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_DOT-USD=0.0000, w_IEF=0.0031, w_BIL=0.9969\nPortfolio annualized return: 5.30%, volatility: 0.29%\nSharpe ratio: (0.0530 - 0.0400) / 0.0029 = 4.5309", "metadata": {"weights": {"EEM": 0.0, "DOT-USD": 0.0, "IEF": 0.0031, "BIL": 0.9969}, "sharpe_ratio": 4.5309, "portfolio_return": 0.052972, "portfolio_vol": 0.002863, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240730_0517", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "XHB", "SHY"], "decision_date": "2024-07-30", "context_summary": "4-asset optimization. Max-Sharpe: 4.349. Portfolio: return=10.66%, vol=1.53%. Weights: w_QUAL=0.0000, w_MATIC-USD=0.0000, w_XHB=0.0080, w_SHY=0.9919.", "question": "Assets: QUAL, MATIC-USD, XHB, SHY\nAnnualized mean returns: QUAL:0.1883, MATIC-USD:-2.2312, XHB:0.6408, SHY:0.1023\nCovariance matrix (annualized):\n[[0.013926, 0.007936, 0.014134, 0.000412], [0.007936, 0.27452, 0.024268, 0.000886], [0.014134, 0.024268, 0.08287, 0.001461], [0.000412, 0.000886, 0.001461, 0.000209]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_MATIC-USD=0.0000, w_XHB=0.0080, w_SHY=0.9919", "answer_numeric": 4.349265026772843, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_MATIC-USD=0.0000, w_XHB=0.0080, w_SHY=0.9919\nPortfolio annualized return: 10.66%, volatility: 1.53%\nSharpe ratio: (0.1066 - 0.0400) / 0.0153 = 4.3493", "metadata": {"weights": {"QUAL": 0.0, "MATIC-USD": 0.0, "XHB": 0.008, "SHY": 0.9919}, "sharpe_ratio": 4.3493, "portfolio_return": 0.106627, "portfolio_vol": 0.015319, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20240710_0519", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLU", "SOL-USD", "ICSH", "MORT"], "decision_date": "2024-07-10", "context_summary": "4-asset optimization. Max-Sharpe: 5.668. Portfolio: return=6.13%, vol=0.38%. Weights: w_XLU=0.0000, w_SOL-USD=0.0000, w_ICSH=1.0000, w_MORT=0.0000.", "question": "Assets: XLU, SOL-USD, ICSH, MORT\nAnnualized mean returns: XLU:-0.1741, SOL-USD:0.6522, ICSH:0.0613, MORT:0.0549\nCovariance matrix (annualized):\n[[0.019245, 0.014822, 5.4e-05, 0.010607], [0.014822, 0.539471, 0.001012, -2.6e-05], [5.4e-05, 0.001012, 1.4e-05, 8.9e-05], [0.010607, -2.6e-05, 8.9e-05, 0.026419]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_SOL-USD=0.0000, w_ICSH=1.0000, w_MORT=0.0000", "answer_numeric": 5.668437940989784, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_SOL-USD=0.0000, w_ICSH=1.0000, w_MORT=0.0000\nPortfolio annualized return: 6.13%, volatility: 0.38%\nSharpe ratio: (0.0613 - 0.0400) / 0.0038 = 5.6684", "metadata": {"weights": {"XLU": 0.0, "SOL-USD": 0.0, "ICSH": 1.0, "MORT": 0.0}, "sharpe_ratio": 5.6684, "portfolio_return": 0.061262, "portfolio_vol": 0.003751, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241022_0521", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "WEAT", "HYG"], "decision_date": "2024-10-22", "context_summary": "4-asset optimization. Max-Sharpe: 4.417. Portfolio: return=42.73%, vol=8.77%. Weights: w_XLI=0.6328, w_BNB-USD=0.0000, w_WEAT=0.2083, w_HYG=0.1589.", "question": "Assets: XLI, BNB-USD, WEAT, HYG\nAnnualized mean returns: XLI:0.5169, BNB-USD:0.0395, WEAT:0.4057, HYG:0.0988\nCovariance matrix (annualized):\n[[0.015676, 0.018596, -0.003747, 0.002061], [0.018596, 0.12499, -0.015343, 0.004447], [-0.003747, -0.015343, 0.047413, -0.001553], [0.002061, 0.004447, -0.001553, 0.001176]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.6328, w_BNB-USD=0.0000, w_WEAT=0.2083, w_HYG=0.1589", "answer_numeric": 4.417331869722428, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.6328, w_BNB-USD=0.0000, w_WEAT=0.2083, w_HYG=0.1589\nPortfolio annualized return: 42.73%, volatility: 8.77%\nSharpe ratio: (0.4273 - 0.0400) / 0.0877 = 4.4173", "metadata": {"weights": {"XLI": 0.6328, "BNB-USD": 0.0, "WEAT": 0.2083, "HYG": 0.1589}, "sharpe_ratio": 4.4173, "portfolio_return": 0.427307, "portfolio_vol": 0.087679, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20240320_0524", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "DOT-USD", "REZ", "BNO"], "decision_date": "2024-03-20", "context_summary": "4-asset optimization. Max-Sharpe: 4.801. Portfolio: return=74.99%, vol=14.79%. Weights: w_MTUM=0.4425, w_DOT-USD=0.0378, w_REZ=0.0000, w_BNO=0.5197.", "question": "Assets: MTUM, DOT-USD, REZ, BNO\nAnnualized mean returns: MTUM:0.6631, DOT-USD:1.2634, REZ:-0.0754, BNO:0.7865\nCovariance matrix (annualized):\n[[0.040144, 0.027813, 0.005529, 0.000723], [0.027813, 0.426503, 0.012781, 0.017821], [0.005529, 0.012781, 0.026709, -0.001431], [0.000723, 0.017821, -0.001431, 0.042327]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.4425, w_DOT-USD=0.0378, w_REZ=0.0000, w_BNO=0.5197", "answer_numeric": 4.800753844992878, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.4425, w_DOT-USD=0.0378, w_REZ=0.0000, w_BNO=0.5197\nPortfolio annualized return: 74.99%, volatility: 14.79%\nSharpe ratio: (0.7499 - 0.0400) / 0.1479 = 4.8008", "metadata": {"weights": {"MTUM": 0.4425, "DOT-USD": 0.0378, "REZ": 0.0, "BNO": 0.5197}, "sharpe_ratio": 4.8008, "portfolio_return": 0.749865, "portfolio_vol": 0.147865, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230328_0527", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "XRP-USD", "HAUZ", "ICSH"], "decision_date": "2023-03-28", "context_summary": "4-asset optimization. Max-Sharpe: 1.441. Portfolio: return=13.33%, vol=6.48%. Weights: w_XLB=0.0000, w_XRP-USD=0.0806, w_HAUZ=0.0000, w_ICSH=0.9194.", "question": "Assets: XLB, XRP-USD, HAUZ, ICSH\nAnnualized mean returns: XLB:-0.4537, XRP-USD:1.2057, HAUZ:-0.6630, ICSH:0.0394\nCovariance matrix (annualized):\n[[0.044115, 0.055294, 0.020192, -0.000522], [0.055294, 0.659783, 0.017246, -0.000829], [0.020192, 0.017246, 0.022574, -0.000171], [-0.000522, -0.000829, -0.000171, 4.2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_XRP-USD=0.0806, w_HAUZ=0.0000, w_ICSH=0.9194", "answer_numeric": 1.441071825804412, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_XRP-USD=0.0806, w_HAUZ=0.0000, w_ICSH=0.9194\nPortfolio annualized return: 13.33%, volatility: 6.48%\nSharpe ratio: (0.1333 - 0.0400) / 0.0648 = 1.4411", "metadata": {"weights": {"XLB": 0.0, "XRP-USD": 0.0806, "HAUZ": 0.0, "ICSH": 0.9194}, "sharpe_ratio": 1.4411, "portfolio_return": 0.133346, "portfolio_vol": 0.064775, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230606_0529", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "AVAX-USD", "JNK", "IAU"], "decision_date": "2023-06-06", "context_summary": "4-asset optimization. Max-Sharpe: -0.169. Portfolio: return=2.97%, vol=6.06%. Weights: w_FXI=0.0000, w_AVAX-USD=0.0000, w_JNK=1.0000, w_IAU=0.0000.", "question": "Assets: FXI, AVAX-USD, JNK, IAU\nAnnualized mean returns: FXI:-0.4225, AVAX-USD:-1.0763, JNK:0.0297, IAU:-0.1405\nCovariance matrix (annualized):\n[[0.086443, 0.016208, 0.006603, 7.8e-05], [0.016208, 0.263606, 0.011583, 0.009916], [0.006603, 0.011583, 0.003671, 0.00161], [7.8e-05, 0.009916, 0.00161, 0.017585]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_AVAX-USD=0.0000, w_JNK=1.0000, w_IAU=0.0000", "answer_numeric": -0.16942478589830026, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_AVAX-USD=0.0000, w_JNK=1.0000, w_IAU=0.0000\nPortfolio annualized return: 2.97%, volatility: 6.06%\nSharpe ratio: (0.0297 - 0.0400) / 0.0606 = -0.1694", "metadata": {"weights": {"FXI": 0.0, "AVAX-USD": 0.0, "JNK": 1.0, "IAU": 0.0}, "sharpe_ratio": -0.1694, "portfolio_return": 0.029735, "portfolio_vol": 0.060588, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240227_0531", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "SCHH", "IGOV"], "decision_date": "2024-02-27", "context_summary": "4-asset optimization. Max-Sharpe: -0.082. Portfolio: return=-2.48%, vol=79.46%. Weights: w_IWM=0.0000, w_AVAX-USD=1.0000, w_SCHH=0.0000, w_IGOV=0.0000.", "question": "Assets: IWM, AVAX-USD, SCHH, IGOV\nAnnualized mean returns: IWM:-0.0602, AVAX-USD:-0.0248, SCHH:-0.3984, IGOV:-0.2954\nCovariance matrix (annualized):\n[[0.051595, 0.054787, 0.029609, 0.011282], [0.054787, 0.631407, 0.00743, 0.002715], [0.029609, 0.00743, 0.031179, 0.007931], [0.011282, 0.002715, 0.007931, 0.008145]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_AVAX-USD=1.0000, w_SCHH=0.0000, w_IGOV=0.0000", "answer_numeric": -0.08160536049909721, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_AVAX-USD=1.0000, w_SCHH=0.0000, w_IGOV=0.0000\nPortfolio annualized return: -2.48%, volatility: 79.46%\nSharpe ratio: (-0.0248 - 0.0400) / 0.7946 = -0.0816", "metadata": {"weights": {"IWM": 0.0, "AVAX-USD": 1.0, "SCHH": 0.0, "IGOV": 0.0}, "sharpe_ratio": -0.0816, "portfolio_return": -0.024845, "portfolio_vol": 0.794612, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240312_0534", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BTC-USD", "STIP", "BIL"], "decision_date": "2024-03-12", "context_summary": "4-asset optimization. Max-Sharpe: 7.105. Portfolio: return=6.44%, vol=0.34%. Weights: w_QQQ=0.0000, w_BTC-USD=0.0051, w_STIP=0.0000, w_BIL=0.9949.", "question": "Assets: QQQ, BTC-USD, STIP, BIL\nAnnualized mean returns: QQQ:0.4174, BTC-USD:2.6869, STIP:0.0327, BIL:0.0510\nCovariance matrix (annualized):\n[[0.027853, 0.004713, -0.000224, 0.000219], [0.004713, 0.291566, -0.00113, -0.000208], [-0.000224, -0.00113, 0.000507, 1.4e-05], [0.000219, -0.000208, 1.4e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0000, w_BTC-USD=0.0051, w_STIP=0.0000, w_BIL=0.9949", "answer_numeric": 7.104751049256371, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_BTC-USD=0.0051, w_STIP=0.0000, w_BIL=0.9949\nPortfolio annualized return: 6.44%, volatility: 0.34%\nSharpe ratio: (0.0644 - 0.0400) / 0.0034 = 7.1048", "metadata": {"weights": {"QQQ": 0.0, "BTC-USD": 0.0051, "STIP": 0.0, "BIL": 0.9949}, "sharpe_ratio": 7.1048, "portfolio_return": 0.064434, "portfolio_vol": 0.003439, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241007_0536", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ETH-USD", "WEAT", "ICSH"], "decision_date": "2024-10-07", "context_summary": "4-asset optimization. Max-Sharpe: 4.709. Portfolio: return=6.18%, vol=0.46%. Weights: w_XLV=0.0203, w_ETH-USD=0.0016, w_WEAT=0.0072, w_ICSH=0.9709.", "question": "Assets: XLV, ETH-USD, WEAT, ICSH\nAnnualized mean returns: XLV:0.2554, ETH-USD:0.6031, WEAT:0.3437, ICSH:0.0548\nCovariance matrix (annualized):\n[[0.009884, 0.024871, -0.002713, -1e-05], [0.024871, 0.397352, -0.03662, -0.000347], [-0.002713, -0.03662, 0.047923, 7.2e-05], [-1e-05, -0.000347, 7.2e-05, 1.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0203, w_ETH-USD=0.0016, w_WEAT=0.0072, w_ICSH=0.9709", "answer_numeric": 4.7094214621499235, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0203, w_ETH-USD=0.0016, w_WEAT=0.0072, w_ICSH=0.9709\nPortfolio annualized return: 6.18%, volatility: 0.46%\nSharpe ratio: (0.0618 - 0.0400) / 0.0046 = 4.7094", "metadata": {"weights": {"XLV": 0.0203, "ETH-USD": 0.0016, "WEAT": 0.0072, "ICSH": 0.9709}, "sharpe_ratio": 4.7094, "portfolio_return": 0.061816, "portfolio_vol": 0.004632, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240109_0538", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "LINK-USD", "XHB", "ICSH"], "decision_date": "2024-01-09", "context_summary": "4-asset optimization. Max-Sharpe: 7.212. Portfolio: return=8.78%, vol=0.66%. Weights: w_EEM=0.0000, w_LINK-USD=0.0000, w_XHB=0.0124, w_ICSH=0.9876.", "question": "Assets: EEM, LINK-USD, XHB, ICSH\nAnnualized mean returns: EEM:0.3658, LINK-USD:-0.4359, XHB:1.2550, ICSH:0.0731\nCovariance matrix (annualized):\n[[0.019015, 0.023681, 0.019557, 0.000308], [0.023681, 0.650897, 0.063925, -0.000236], [0.019557, 0.063925, 0.051262, 0.000484], [0.000308, -0.000236, 0.000484, 2.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_LINK-USD=0.0000, w_XHB=0.0124, w_ICSH=0.9876", "answer_numeric": 7.212027044250586, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_LINK-USD=0.0000, w_XHB=0.0124, w_ICSH=0.9876\nPortfolio annualized return: 8.78%, volatility: 0.66%\nSharpe ratio: (0.0878 - 0.0400) / 0.0066 = 7.2120", "metadata": {"weights": {"EEM": 0.0, "LINK-USD": 0.0, "XHB": 0.0124, "ICSH": 0.9876}, "sharpe_ratio": 7.212, "portfolio_return": 0.087774, "portfolio_vol": 0.006624, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231011_0540", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "BIL", "SCHP"], "decision_date": "2023-10-11", "context_summary": "4-asset optimization. Max-Sharpe: 3.750. Portfolio: return=5.02%, vol=0.27%. Weights: w_ACWI=0.0000, w_ADA-USD=0.0000, w_BIL=1.0000, w_SCHP=0.0000.", "question": "Assets: ACWI, ADA-USD, BIL, SCHP\nAnnualized mean returns: ACWI:-0.1633, ADA-USD:-1.0402, BIL:0.0502, SCHP:-0.1240\nCovariance matrix (annualized):\n[[0.014309, 0.013108, -0.0001, 0.003362], [0.013108, 0.105951, -0.00021, 0.00376], [-0.0001, -0.00021, 7e-06, -8e-06], [0.003362, 0.00376, -8e-06, 0.003647]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_ADA-USD=0.0000, w_BIL=1.0000, w_SCHP=0.0000", "answer_numeric": 3.7500074236349383, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_ADA-USD=0.0000, w_BIL=1.0000, w_SCHP=0.0000\nPortfolio annualized return: 5.02%, volatility: 0.27%\nSharpe ratio: (0.0502 - 0.0400) / 0.0027 = 3.7500", "metadata": {"weights": {"ACWI": 0.0, "ADA-USD": 0.0, "BIL": 1.0, "SCHP": 0.0}, "sharpe_ratio": 3.75, "portfolio_return": 0.050241, "portfolio_vol": 0.002731, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240628_0543", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "LQD", "BNO"], "decision_date": "2024-06-28", "context_summary": "4-asset optimization. Max-Sharpe: 2.428. Portfolio: return=19.38%, vol=6.33%. Weights: w_XLP=0.1208, w_ADA-USD=0.0000, w_LQD=0.8791, w_BNO=0.0001.", "question": "Assets: XLP, ADA-USD, LQD, BNO\nAnnualized mean returns: XLP:0.1498, ADA-USD:-0.6056, LQD:0.1998, BNO:-0.0577\nCovariance matrix (annualized):\n[[0.01049, -0.0048, 0.001817, 0.001369], [-0.0048, 0.197472, 0.00934, -0.004398], [0.001817, 0.00934, 0.004495, -0.003094], [0.001369, -0.004398, -0.003094, 0.047996]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.1208, w_ADA-USD=0.0000, w_LQD=0.8791, w_BNO=0.0001", "answer_numeric": 2.4276803063924177, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.1208, w_ADA-USD=0.0000, w_LQD=0.8791, w_BNO=0.0001\nPortfolio annualized return: 19.38%, volatility: 6.33%\nSharpe ratio: (0.1938 - 0.0400) / 0.0633 = 2.4277", "metadata": {"weights": {"XLP": 0.1208, "ADA-USD": 0.0, "LQD": 0.8791, "BNO": 0.0001}, "sharpe_ratio": 2.4277, "portfolio_return": 0.193771, "portfolio_vol": 0.063341, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230316_0545", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "ITB", "CORN"], "decision_date": "2023-03-16", "context_summary": "4-asset optimization. Max-Sharpe: 0.072. Portfolio: return=5.94%, vol=26.99%. Weights: w_VEA=0.0000, w_ETH-USD=0.0000, w_ITB=1.0000, w_CORN=0.0000.", "question": "Assets: VEA, ETH-USD, ITB, CORN\nAnnualized mean returns: VEA:-0.3303, ETH-USD:-0.3024, ITB:0.0594, CORN:-0.4830\nCovariance matrix (annualized):\n[[0.020197, 0.021951, 0.023428, 0.002904], [0.021951, 0.261094, 0.025019, 0.002379], [0.023428, 0.025019, 0.072854, -0.003992], [0.002904, 0.002379, -0.003992, 0.018094]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_ETH-USD=0.0000, w_ITB=1.0000, w_CORN=0.0000", "answer_numeric": 0.07198869118824239, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_ETH-USD=0.0000, w_ITB=1.0000, w_CORN=0.0000\nPortfolio annualized return: 5.94%, volatility: 26.99%\nSharpe ratio: (0.0594 - 0.0400) / 0.2699 = 0.0720", "metadata": {"weights": {"VEA": 0.0, "ETH-USD": 0.0, "ITB": 1.0, "CORN": 0.0}, "sharpe_ratio": 0.072, "portfolio_return": 0.059431, "portfolio_vol": 0.269915, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240523_0547", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "ADA-USD", "PPLT", "SGOV"], "decision_date": "2024-05-23", "context_summary": "4-asset optimization. Max-Sharpe: 6.461. Portfolio: return=5.72%, vol=0.27%. Weights: w_XLF=0.0000, w_ADA-USD=0.0000, w_PPLT=0.0070, w_SGOV=0.9930.", "question": "Assets: XLF, ADA-USD, PPLT, SGOV\nAnnualized mean returns: XLF:0.0749, ADA-USD:-1.1904, PPLT:0.9136, SGOV:0.0512\nCovariance matrix (annualized):\n[[0.013866, 0.020427, 0.006968, -1e-06], [0.020427, 0.346293, 0.007864, 0.000238], [0.006968, 0.007864, 0.062345, -7.3e-05], [-1e-06, 0.000238, -7.3e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_ADA-USD=0.0000, w_PPLT=0.0070, w_SGOV=0.9930", "answer_numeric": 6.461370351413435, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_ADA-USD=0.0000, w_PPLT=0.0070, w_SGOV=0.9930\nPortfolio annualized return: 5.72%, volatility: 0.27%\nSharpe ratio: (0.0572 - 0.0400) / 0.0027 = 6.4614", "metadata": {"weights": {"XLF": 0.0, "ADA-USD": 0.0, "PPLT": 0.007, "SGOV": 0.993}, "sharpe_ratio": 6.4614, "portfolio_return": 0.057236, "portfolio_vol": 0.002668, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241008_0549", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SOL-USD", "ICSH", "DBC"], "decision_date": "2024-10-08", "context_summary": "4-asset optimization. Max-Sharpe: 0.808. Portfolio: return=17.67%, vol=16.92%. Weights: w_VLUE=0.2500, w_SOL-USD=0.2500, w_ICSH=0.2500, w_DBC=0.2500.", "question": "Assets: VLUE, SOL-USD, ICSH, DBC\nAnnualized mean returns: VLUE:0.4688, SOL-USD:-0.2292, ICSH:0.0548, DBC:0.4122\nCovariance matrix (annualized):\n[[0.015847, 0.034022, 4.5e-05, 0.005496], [0.034022, 0.286596, 0.000217, 0.024575], [4.5e-05, 0.000217, 1.5e-05, -7.9e-05], [0.005496, 0.024575, -7.9e-05, 0.026998]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.2500, w_SOL-USD=0.2500, w_ICSH=0.2500, w_DBC=0.2500", "answer_numeric": 0.8077882763429476, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.2500, w_SOL-USD=0.2500, w_ICSH=0.2500, w_DBC=0.2500\nPortfolio annualized return: 17.67%, volatility: 16.92%\nSharpe ratio: (0.1767 - 0.0400) / 0.1692 = 0.8078", "metadata": {"weights": {"VLUE": 0.25, "SOL-USD": 0.25, "ICSH": 0.25, "DBC": 0.25}, "sharpe_ratio": 0.8078, "portfolio_return": 0.17667, "portfolio_vol": 0.169191, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240401_0552", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "BTC-USD", "IAU", "HYG"], "decision_date": "2024-04-01", "context_summary": "4-asset optimization. Max-Sharpe: 5.874. Portfolio: return=93.18%, vol=15.18%. Weights: w_IWM=0.0630, w_BTC-USD=0.1613, w_IAU=0.7756, w_HYG=0.0000.", "question": "Assets: IWM, BTC-USD, IAU, HYG\nAnnualized mean returns: IWM:0.5919, BTC-USD:2.8614, IAU:0.5580, HYG:0.0885\nCovariance matrix (annualized):\n[[0.041574, 0.028937, 0.008991, 0.006694], [0.028937, 0.34763, 0.019349, 0.00116], [0.008991, 0.019349, 0.012505, 0.002767], [0.006694, 0.00116, 0.002767, 0.00233]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0630, w_BTC-USD=0.1613, w_IAU=0.7756, w_HYG=0.0000", "answer_numeric": 5.874098300649528, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0630, w_BTC-USD=0.1613, w_IAU=0.7756, w_HYG=0.0000\nPortfolio annualized return: 93.18%, volatility: 15.18%\nSharpe ratio: (0.9318 - 0.0400) / 0.1518 = 5.8741", "metadata": {"weights": {"IWM": 0.063, "BTC-USD": 0.1613, "IAU": 0.7756, "HYG": 0.0}, "sharpe_ratio": 5.8741, "portfolio_return": 0.931776, "portfolio_vol": 0.151815, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230427_0554", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "IGOV", "SGOV"], "decision_date": "2023-04-27", "context_summary": "4-asset optimization. Max-Sharpe: 3.239. Portfolio: return=5.11%, vol=0.34%. Weights: w_XLY=0.0024, w_DOT-USD=0.0000, w_IGOV=0.0269, w_SGOV=0.9707.", "question": "Assets: XLY, DOT-USD, IGOV, SGOV\nAnnualized mean returns: XLY:0.0112, DOT-USD:-0.8521, IGOV:0.2391, SGOV:0.0460\nCovariance matrix (annualized):\n[[0.042976, 0.021615, -0.005819, 2.2e-05], [0.021615, 0.342442, 0.010082, 4.3e-05], [-0.005819, 0.010082, 0.008919, -1.5e-05], [2.2e-05, 4.3e-05, -1.5e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0024, w_DOT-USD=0.0000, w_IGOV=0.0269, w_SGOV=0.9707", "answer_numeric": 3.2390236385067177, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0024, w_DOT-USD=0.0000, w_IGOV=0.0269, w_SGOV=0.9707\nPortfolio annualized return: 5.11%, volatility: 0.34%\nSharpe ratio: (0.0511 - 0.0400) / 0.0034 = 3.2390", "metadata": {"weights": {"XLY": 0.0024, "DOT-USD": 0.0, "IGOV": 0.0269, "SGOV": 0.9707}, "sharpe_ratio": 3.239, "portfolio_return": 0.051144, "portfolio_vol": 0.003441, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240207_0556", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "VNQ", "CSHI"], "decision_date": "2024-02-07", "context_summary": "4-asset optimization. Max-Sharpe: 5.833. Portfolio: return=12.01%, vol=1.37%. Weights: w_MTUM=0.0770, w_LINK-USD=0.0000, w_VNQ=0.0000, w_CSHI=0.9230.", "question": "Assets: MTUM, LINK-USD, VNQ, CSHI\nAnnualized mean returns: MTUM:0.8857, LINK-USD:1.1278, VNQ:0.0642, CSHI:0.0563\nCovariance matrix (annualized):\n[[0.02559, 0.04311, 0.007355, 2.5e-05], [0.04311, 0.715325, 0.03786, 2.6e-05], [0.007355, 0.03786, 0.039918, -0.00011], [2.5e-05, 2.6e-05, -0.00011, 4e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0770, w_LINK-USD=0.0000, w_VNQ=0.0000, w_CSHI=0.9230", "answer_numeric": 5.832551108525416, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0770, w_LINK-USD=0.0000, w_VNQ=0.0000, w_CSHI=0.9230\nPortfolio annualized return: 12.01%, volatility: 1.37%\nSharpe ratio: (0.1201 - 0.0400) / 0.0137 = 5.8326", "metadata": {"weights": {"MTUM": 0.077, "LINK-USD": 0.0, "VNQ": 0.0, "CSHI": 0.923}, "sharpe_ratio": 5.8326, "portfolio_return": 0.120148, "portfolio_vol": 0.013741, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230907_0559", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "SOL-USD", "CPER", "TLH"], "decision_date": "2023-09-07", "context_summary": "4-asset optimization. Max-Sharpe: 0.501. Portfolio: return=7.64%, vol=7.27%. Weights: w_USMV=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_TLH=0.0000.", "question": "Assets: USMV, SOL-USD, CPER, TLH\nAnnualized mean returns: USMV:0.0764, SOL-USD:-0.3928, CPER:0.0265, TLH:-0.1907\nCovariance matrix (annualized):\n[[0.005288, 0.010537, 0.004686, 0.002911], [0.010537, 0.508936, 0.022075, 0.035362], [0.004686, 0.022075, 0.038561, 0.007408], [0.002911, 0.035362, 0.007408, 0.017881]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_TLH=0.0000", "answer_numeric": 0.5011939778653707, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_TLH=0.0000\nPortfolio annualized return: 7.64%, volatility: 7.27%\nSharpe ratio: (0.0764 - 0.0400) / 0.0727 = 0.5012", "metadata": {"weights": {"USMV": 1.0, "SOL-USD": 0.0, "CPER": 0.0, "TLH": 0.0}, "sharpe_ratio": 0.5012, "portfolio_return": 0.076445, "portfolio_vol": 0.072715, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241218_0561", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VEA", "DOT-USD", "LQD", "ITB"], "decision_date": "2024-12-18", "context_summary": "4-asset optimization. Max-Sharpe: 0.925. Portfolio: return=87.78%, vol=90.62%. Weights: w_VEA=0.0000, w_DOT-USD=1.0000, w_LQD=0.0000, w_ITB=0.0000.", "question": "Assets: VEA, DOT-USD, LQD, ITB\nAnnualized mean returns: VEA:-0.2641, DOT-USD:0.8778, LQD:-0.0592, ITB:-0.9397\nCovariance matrix (annualized):\n[[0.0123, 0.030737, 0.005573, 0.015339], [0.030737, 0.821182, 0.011873, 0.000474], [0.005573, 0.011873, 0.006031, 0.01194], [0.015339, 0.000474, 0.01194, 0.064287]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_DOT-USD=1.0000, w_LQD=0.0000, w_ITB=0.0000", "answer_numeric": 0.9245139021437744, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_DOT-USD=1.0000, w_LQD=0.0000, w_ITB=0.0000\nPortfolio annualized return: 87.78%, volatility: 90.62%\nSharpe ratio: (0.8778 - 0.0400) / 0.9062 = 0.9245", "metadata": {"weights": {"VEA": 0.0, "DOT-USD": 1.0, "LQD": 0.0, "ITB": 0.0}, "sharpe_ratio": 0.9245, "portfolio_return": 0.877786, "portfolio_vol": 0.906191, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240402_0564", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "BNB-USD", "SOYB", "CSHI"], "decision_date": "2024-04-02", "context_summary": "4-asset optimization. Max-Sharpe: 5.739. Portfolio: return=15.26%, vol=1.96%. Weights: w_USMV=0.1056, w_BNB-USD=0.0207, w_SOYB=0.0000, w_CSHI=0.8737.", "question": "Assets: USMV, BNB-USD, SOYB, CSHI\nAnnualized mean returns: USMV:0.2311, BNB-USD:3.9365, SOYB:-0.0735, CSHI:0.0534\nCovariance matrix (annualized):\n[[0.004704, 0.008384, -0.000722, -2e-05], [0.008384, 0.576441, 0.031847, 0.000576], [-0.000722, 0.031847, 0.018336, 4e-05], [-2e-05, 0.000576, 4e-05, 4.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.1056, w_BNB-USD=0.0207, w_SOYB=0.0000, w_CSHI=0.8737", "answer_numeric": 5.7385656724359055, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.1056, w_BNB-USD=0.0207, w_SOYB=0.0000, w_CSHI=0.8737\nPortfolio annualized return: 15.26%, volatility: 1.96%\nSharpe ratio: (0.1526 - 0.0400) / 0.0196 = 5.7386", "metadata": {"weights": {"USMV": 0.1056, "BNB-USD": 0.0207, "SOYB": 0.0, "CSHI": 0.8737}, "sharpe_ratio": 5.7386, "portfolio_return": 0.152583, "portfolio_vol": 0.019619, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241223_0567", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "SOL-USD", "CPER", "SCHP"], "decision_date": "2024-12-23", "context_summary": "4-asset optimization. Max-Sharpe: 1.782. Portfolio: return=37.00%, vol=18.52%. Weights: w_QQQ=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_SCHP=0.0000.", "question": "Assets: QQQ, SOL-USD, CPER, SCHP\nAnnualized mean returns: QQQ:0.3700, SOL-USD:0.3149, CPER:-0.3452, SCHP:-0.0800\nCovariance matrix (annualized):\n[[0.034284, 0.053376, 0.001525, 0.002424], [0.053376, 0.518609, -0.029157, 0.00603], [0.001525, -0.029157, 0.04015, 0.003651], [0.002424, 0.00603, 0.003651, 0.001683]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_SCHP=0.0000", "answer_numeric": 1.7821567962727567, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=1.0000, w_SOL-USD=0.0000, w_CPER=0.0000, w_SCHP=0.0000\nPortfolio annualized return: 37.00%, volatility: 18.52%\nSharpe ratio: (0.3700 - 0.0400) / 0.1852 = 1.7822", "metadata": {"weights": {"QQQ": 1.0, "SOL-USD": 0.0, "CPER": 0.0, "SCHP": 0.0}, "sharpe_ratio": 1.7822, "portfolio_return": 0.369984, "portfolio_vol": 0.18516, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241105_0569", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "DOT-USD", "XHB", "STIP"], "decision_date": "2024-11-05", "context_summary": "4-asset optimization. Max-Sharpe: 1.256. Portfolio: return=20.31%, vol=12.99%. Weights: w_XLF=0.7697, w_DOT-USD=0.0000, w_XHB=0.2303, w_STIP=0.0000.", "question": "Assets: XLF, DOT-USD, XHB, STIP\nAnnualized mean returns: XLF:0.1967, DOT-USD:-0.7490, XHB:0.2248, STIP:0.0205\nCovariance matrix (annualized):\n[[0.017771, 0.017579, 0.010959, -0.000308], [0.017579, 0.212553, 0.034945, 0.001472], [0.010959, 0.034945, 0.046332, 0.001398], [-0.000308, 0.001472, 0.001398, 0.000372]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.7697, w_DOT-USD=0.0000, w_XHB=0.2303, w_STIP=0.0000", "answer_numeric": 1.2560292736643077, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.7697, w_DOT-USD=0.0000, w_XHB=0.2303, w_STIP=0.0000\nPortfolio annualized return: 20.31%, volatility: 12.99%\nSharpe ratio: (0.2031 - 0.0400) / 0.1299 = 1.2560", "metadata": {"weights": {"XLF": 0.7697, "DOT-USD": 0.0, "XHB": 0.2303, "STIP": 0.0}, "sharpe_ratio": 1.256, "portfolio_return": 0.203144, "portfolio_vol": 0.129888, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240913_0571", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "XRP-USD", "PPLT", "MORT"], "decision_date": "2024-09-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.558. Portfolio: return=118.16%, vol=73.28%. Weights: w_EFA=0.0000, w_XRP-USD=1.0000, w_PPLT=0.0000, w_MORT=0.0000.", "question": "Assets: EFA, XRP-USD, PPLT, MORT\nAnnualized mean returns: EFA:-0.0173, XRP-USD:1.1816, PPLT:-0.0823, MORT:0.0770\nCovariance matrix (annualized):\n[[0.028715, 0.049349, 0.025371, 0.020534], [0.049349, 0.537021, 0.064778, 0.04977], [0.025371, 0.064778, 0.063553, 0.017996], [0.020534, 0.04977, 0.017996, 0.034733]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_XRP-USD=1.0000, w_PPLT=0.0000, w_MORT=0.0000", "answer_numeric": 1.5578720073849093, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_XRP-USD=1.0000, w_PPLT=0.0000, w_MORT=0.0000\nPortfolio annualized return: 118.16%, volatility: 73.28%\nSharpe ratio: (1.1816 - 0.0400) / 0.7328 = 1.5579", "metadata": {"weights": {"EFA": 0.0, "XRP-USD": 1.0, "PPLT": 0.0, "MORT": 0.0}, "sharpe_ratio": 1.5579, "portfolio_return": 1.181635, "portfolio_vol": 0.732817, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240917_0574", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "XHB", "PPLT"], "decision_date": "2024-09-17", "context_summary": "4-asset optimization. Max-Sharpe: 4.180. Portfolio: return=44.73%, vol=9.74%. Weights: w_XLP=0.9780, w_DOT-USD=0.0000, w_XHB=0.0220, w_PPLT=0.0000.", "question": "Assets: XLP, DOT-USD, XHB, PPLT\nAnnualized mean returns: XLP:0.4470, DOT-USD:-1.3357, XHB:0.4607, PPLT:0.1448\nCovariance matrix (annualized):\n[[0.009516, 0.022148, 0.008097, 0.007012], [0.022148, 0.293962, 0.077861, 0.071539], [0.008097, 0.077861, 0.085808, 0.034452], [0.007012, 0.071539, 0.034452, 0.065014]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.9780, w_DOT-USD=0.0000, w_XHB=0.0220, w_PPLT=0.0000", "answer_numeric": 4.180398320701202, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.9780, w_DOT-USD=0.0000, w_XHB=0.0220, w_PPLT=0.0000\nPortfolio annualized return: 44.73%, volatility: 9.74%\nSharpe ratio: (0.4473 - 0.0400) / 0.0974 = 4.1804", "metadata": {"weights": {"XLP": 0.978, "DOT-USD": 0.0, "XHB": 0.022, "PPLT": 0.0}, "sharpe_ratio": 4.1804, "portfolio_return": 0.447273, "portfolio_vol": 0.097424, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241120_0575", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "INDS", "SHV"], "decision_date": "2024-11-20", "context_summary": "4-asset optimization. Max-Sharpe: 0.122. Portfolio: return=4.03%, vol=0.24%. Weights: w_EWJ=0.0000, w_BNB-USD=0.0000, w_INDS=0.0000, w_SHV=1.0000.", "question": "Assets: EWJ, BNB-USD, INDS, SHV\nAnnualized mean returns: EWJ:-0.3134, BNB-USD:-0.0332, INDS:-0.6285, SHV:0.0403\nCovariance matrix (annualized):\n[[0.026775, 0.021208, 0.004603, 3.4e-05], [0.021208, 0.138704, 0.011829, 3.1e-05], [0.004603, 0.011829, 0.028436, 0.000126], [3.4e-05, 3.1e-05, 0.000126, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_BNB-USD=0.0000, w_INDS=0.0000, w_SHV=1.0000", "answer_numeric": 0.12175430879729583, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BNB-USD=0.0000, w_INDS=0.0000, w_SHV=1.0000\nPortfolio annualized return: 4.03%, volatility: 0.24%\nSharpe ratio: (0.0403 - 0.0400) / 0.0024 = 0.1218", "metadata": {"weights": {"EWJ": 0.0, "BNB-USD": 0.0, "INDS": 0.0, "SHV": 1.0}, "sharpe_ratio": 0.1218, "portfolio_return": 0.040297, "portfolio_vol": 0.002443, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231016_0577", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "XRP-USD", "TIP", "SGOV"], "decision_date": "2023-10-16", "context_summary": "4-asset optimization. Max-Sharpe: -2.363. Portfolio: return=-25.72%, vol=12.58%. Weights: w_QQQ=0.2500, w_XRP-USD=0.2500, w_TIP=0.2500, w_SGOV=0.2500.", "question": "Assets: QQQ, XRP-USD, TIP, SGOV\nAnnualized mean returns: QQQ:0.0552, XRP-USD:-1.1818, TIP:0.0451, SGOV:0.0528\nCovariance matrix (annualized):\n[[0.028359, 0.004214, 0.001371, -6.1e-05], [0.004214, 0.215498, -0.000932, -0.000239], [0.001371, -0.000932, 0.000559, 7e-06], [-6.1e-05, -0.000239, 7e-06, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.2500, w_XRP-USD=0.2500, w_TIP=0.2500, w_SGOV=0.2500", "answer_numeric": -2.3626788332797495, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.2500, w_XRP-USD=0.2500, w_TIP=0.2500, w_SGOV=0.2500\nPortfolio annualized return: -25.72%, volatility: 12.58%\nSharpe ratio: (-0.2572 - 0.0400) / 0.1258 = -2.3627", "metadata": {"weights": {"QQQ": 0.25, "XRP-USD": 0.25, "TIP": 0.25, "SGOV": 0.25}, "sharpe_ratio": -2.3627, "portfolio_return": -0.257184, "portfolio_vol": 0.125783, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241202_0578", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "ETH-USD", "SCHP", "BIL"], "decision_date": "2024-12-02", "context_summary": "4-asset optimization. Max-Sharpe: 3.847. Portfolio: return=5.74%, vol=0.45%. Weights: w_XLE=0.0046, w_ETH-USD=0.0057, w_SCHP=0.0000, w_BIL=0.9897.", "question": "Assets: XLE, ETH-USD, SCHP, BIL\nAnnualized mean returns: XLE:0.3175, ETH-USD:2.0172, SCHP:-0.0961, BIL:0.0449\nCovariance matrix (annualized):\n[[0.03403, 0.028108, -0.001692, 1.1e-05], [0.028108, 0.399004, 0.006352, -8.4e-05], [-0.001692, 0.006352, 0.001921, 4e-06], [1.1e-05, -8.4e-05, 4e-06, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0046, w_ETH-USD=0.0057, w_SCHP=0.0000, w_BIL=0.9897", "answer_numeric": 3.8469289600913457, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0046, w_ETH-USD=0.0057, w_SCHP=0.0000, w_BIL=0.9897\nPortfolio annualized return: 5.74%, volatility: 0.45%\nSharpe ratio: (0.0574 - 0.0400) / 0.0045 = 3.8469", "metadata": {"weights": {"XLE": 0.0046, "ETH-USD": 0.0057, "SCHP": 0.0, "BIL": 0.9897}, "sharpe_ratio": 3.8469, "portfolio_return": 0.057396, "portfolio_vol": 0.004522, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230220_0581", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "AVAX-USD", "SCHH", "UNG"], "decision_date": "2023-02-20", "context_summary": "4-asset optimization. Max-Sharpe: 3.934. Portfolio: return=157.90%, vol=39.12%. Weights: w_XLY=0.7462, w_AVAX-USD=0.2538, w_SCHH=0.0000, w_UNG=0.0000.", "question": "Assets: XLY, AVAX-USD, SCHH, UNG\nAnnualized mean returns: XLY:0.8534, AVAX-USD:3.7117, SCHH:0.4849, UNG:-4.5348\nCovariance matrix (annualized):\n[[0.063563, 0.131767, 0.040037, 0.042837], [0.131767, 1.050797, 0.106784, 0.169231], [0.040037, 0.106784, 0.044005, 0.04922], [0.042837, 0.169231, 0.04922, 0.576004]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.7462, w_AVAX-USD=0.2538, w_SCHH=0.0000, w_UNG=0.0000", "answer_numeric": 3.9343432095645077, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.7462, w_AVAX-USD=0.2538, w_SCHH=0.0000, w_UNG=0.0000\nPortfolio annualized return: 157.90%, volatility: 39.12%\nSharpe ratio: (1.5790 - 0.0400) / 0.3912 = 3.9343", "metadata": {"weights": {"XLY": 0.7462, "AVAX-USD": 0.2538, "SCHH": 0.0, "UNG": 0.0}, "sharpe_ratio": 3.9343, "portfolio_return": 1.578973, "portfolio_vol": 0.391164, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240329_0583", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "LINK-USD", "VNQI", "SLV"], "decision_date": "2024-03-29", "context_summary": "4-asset optimization. Max-Sharpe: 3.677. Portfolio: return=45.10%, vol=11.18%. Weights: w_SPY=0.8160, w_LINK-USD=0.0000, w_VNQI=0.0000, w_SLV=0.1840.", "question": "Assets: SPY, LINK-USD, VNQI, SLV\nAnnualized mean returns: SPY:0.4320, LINK-USD:0.3755, VNQI:0.2318, SLV:0.5354\nCovariance matrix (annualized):\n[[0.013221, 0.021252, 0.006382, 0.006123], [0.021252, 0.393433, 0.005618, 0.025609], [0.006382, 0.005618, 0.014228, 0.014567], [0.006123, 0.025609, 0.014567, 0.054701]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.8160, w_LINK-USD=0.0000, w_VNQI=0.0000, w_SLV=0.1840", "answer_numeric": 3.677213519607724, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.8160, w_LINK-USD=0.0000, w_VNQI=0.0000, w_SLV=0.1840\nPortfolio annualized return: 45.10%, volatility: 11.18%\nSharpe ratio: (0.4510 - 0.0400) / 0.1118 = 3.6772", "metadata": {"weights": {"SPY": 0.816, "LINK-USD": 0.0, "VNQI": 0.0, "SLV": 0.184}, "sharpe_ratio": 3.6772, "portfolio_return": 0.45102, "portfolio_vol": 0.111775, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240703_0586", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "DOT-USD", "SGOV", "XHB"], "decision_date": "2024-07-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.884. Portfolio: return=5.19%, vol=0.24%. Weights: w_XLU=0.0027, w_DOT-USD=0.0000, w_SGOV=0.9973, w_XHB=0.0000.", "question": "Assets: XLU, DOT-USD, SGOV, XHB\nAnnualized mean returns: XLU:0.0146, DOT-USD:-0.7286, SGOV:0.0520, XHB:-0.3839\nCovariance matrix (annualized):\n[[0.021733, 0.018348, -7.1e-05, 0.016298], [0.018348, 0.325242, -0.000204, 0.030207], [-7.1e-05, -0.000204, 6e-06, -8.4e-05], [0.016298, 0.030207, -8.4e-05, 0.05549]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0027, w_DOT-USD=0.0000, w_SGOV=0.9973, w_XHB=0.0000", "answer_numeric": 4.883727001870344, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0027, w_DOT-USD=0.0000, w_SGOV=0.9973, w_XHB=0.0000\nPortfolio annualized return: 5.19%, volatility: 0.24%\nSharpe ratio: (0.0519 - 0.0400) / 0.0024 = 4.8837", "metadata": {"weights": {"XLU": 0.0027, "DOT-USD": 0.0, "SGOV": 0.9973, "XHB": 0.0}, "sharpe_ratio": 4.8837, "portfolio_return": 0.051864, "portfolio_vol": 0.002429, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240522_0588", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "DOT-USD", "DBC", "CSHI"], "decision_date": "2024-05-22", "context_summary": "4-asset optimization. Max-Sharpe: 2.927. Portfolio: return=7.70%, vol=1.26%. Weights: w_MTUM=0.0000, w_DOT-USD=0.0000, w_DBC=0.0925, w_CSHI=0.9075.", "question": "Assets: MTUM, DOT-USD, DBC, CSHI\nAnnualized mean returns: MTUM:0.0166, DOT-USD:-1.1155, DBC:0.2988, CSHI:0.0544\nCovariance matrix (annualized):\n[[0.032414, 0.031673, 0.005531, 9.5e-05], [0.031673, 0.419527, 0.002453, 0.001287], [0.005531, 0.002453, 0.010829, 0.000128], [9.5e-05, 0.001287, 0.000128, 5.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_DOT-USD=0.0000, w_DBC=0.0925, w_CSHI=0.9075", "answer_numeric": 2.926807026513251, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_DOT-USD=0.0000, w_DBC=0.0925, w_CSHI=0.9075\nPortfolio annualized return: 7.70%, volatility: 1.26%\nSharpe ratio: (0.0770 - 0.0400) / 0.0126 = 2.9268", "metadata": {"weights": {"MTUM": 0.0, "DOT-USD": 0.0, "DBC": 0.0925, "CSHI": 0.9075}, "sharpe_ratio": 2.9268, "portfolio_return": 0.076986, "portfolio_vol": 0.012637, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240508_0590", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "MATIC-USD", "VNQ", "PALL"], "decision_date": "2024-05-08", "context_summary": "4-asset optimization. Max-Sharpe: 2.382. Portfolio: return=39.11%, vol=14.74%. Weights: w_XLE=1.0000, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_PALL=0.0000.", "question": "Assets: XLE, MATIC-USD, VNQ, PALL\nAnnualized mean returns: XLE:0.3911, MATIC-USD:-3.5076, VNQ:-0.2891, PALL:-0.2566\nCovariance matrix (annualized):\n[[0.021734, 0.013123, 0.006433, 0.008837], [0.013123, 0.444898, 0.024843, 0.055752], [0.006433, 0.024843, 0.030494, 0.021956], [0.008837, 0.055752, 0.021956, 0.107508]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=1.0000, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_PALL=0.0000", "answer_numeric": 2.381768148508351, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=1.0000, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_PALL=0.0000\nPortfolio annualized return: 39.11%, volatility: 14.74%\nSharpe ratio: (0.3911 - 0.0400) / 0.1474 = 2.3818", "metadata": {"weights": {"XLE": 1.0, "MATIC-USD": 0.0, "VNQ": 0.0, "PALL": 0.0}, "sharpe_ratio": 2.3818, "portfolio_return": 0.391135, "portfolio_vol": 0.147426, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230614_0592", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "SOL-USD", "VNQI", "DBB"], "decision_date": "2023-06-14", "context_summary": "4-asset optimization. Max-Sharpe: -1.047. Portfolio: return=-12.16%, vol=15.43%. Weights: w_USMV=0.0000, w_SOL-USD=0.0000, w_VNQI=1.0000, w_DBB=0.0000.", "question": "Assets: USMV, SOL-USD, VNQI, DBB\nAnnualized mean returns: USMV:-0.0381, SOL-USD:-2.3299, VNQI:-0.1216, DBB:-0.5554\nCovariance matrix (annualized):\n[[0.008467, 0.014071, 0.007858, 0.008369], [0.014071, 0.328225, 0.030913, 0.018597], [0.007858, 0.030913, 0.023814, 0.014794], [0.008369, 0.018597, 0.014794, 0.034637]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_SOL-USD=0.0000, w_VNQI=1.0000, w_DBB=0.0000", "answer_numeric": -1.0473329953300008, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_SOL-USD=0.0000, w_VNQI=1.0000, w_DBB=0.0000\nPortfolio annualized return: -12.16%, volatility: 15.43%\nSharpe ratio: (-0.1216 - 0.0400) / 0.1543 = -1.0473", "metadata": {"weights": {"USMV": 0.0, "SOL-USD": 0.0, "VNQI": 1.0, "DBB": 0.0}, "sharpe_ratio": -1.0473, "portfolio_return": -0.121623, "portfolio_vol": 0.154319, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230904_0595", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "IAU", "IYR"], "decision_date": "2023-09-04", "context_summary": "4-asset optimization. Max-Sharpe: 0.718. Portfolio: return=10.40%, vol=8.92%. Weights: w_XLI=0.7067, w_DOT-USD=0.0000, w_IAU=0.2933, w_IYR=0.0000.", "question": "Assets: XLI, DOT-USD, IAU, IYR\nAnnualized mean returns: XLI:0.1136, DOT-USD:-0.8624, IAU:0.0811, IYR:-0.1439\nCovariance matrix (annualized):\n[[0.0113, 0.017965, 0.003942, 0.00936], [0.017965, 0.150792, 0.002727, 0.019824], [0.003942, 0.002727, 0.007904, 0.00528], [0.00936, 0.019824, 0.00528, 0.016345]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.7067, w_DOT-USD=0.0000, w_IAU=0.2933, w_IYR=0.0000", "answer_numeric": 0.7178722924666777, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.7067, w_DOT-USD=0.0000, w_IAU=0.2933, w_IYR=0.0000\nPortfolio annualized return: 10.40%, volatility: 8.92%\nSharpe ratio: (0.1040 - 0.0400) / 0.0892 = 0.7179", "metadata": {"weights": {"XLI": 0.7067, "DOT-USD": 0.0, "IAU": 0.2933, "IYR": 0.0}, "sharpe_ratio": 0.7179, "portfolio_return": 0.104038, "portfolio_vol": 0.089205, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241101_0597", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "DBC", "MORT"], "decision_date": "2024-11-01", "context_summary": "4-asset optimization. Max-Sharpe: 0.575. Portfolio: return=11.78%, vol=13.52%. Weights: w_IVV=0.3449, w_MATIC-USD=0.0000, w_DBC=0.6551, w_MORT=0.0000.", "question": "Assets: IVV, MATIC-USD, DBC, MORT\nAnnualized mean returns: IVV:0.0690, MATIC-USD:-1.6559, DBC:0.1434, MORT:-0.2140\nCovariance matrix (annualized):\n[[0.0152, 0.022581, 0.002412, 0.008984], [0.022581, 0.17358, -0.001248, 0.030177], [0.002412, -0.001248, 0.035853, -0.001851], [0.008984, 0.030177, -0.001851, 0.02366]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.3449, w_MATIC-USD=0.0000, w_DBC=0.6551, w_MORT=0.0000", "answer_numeric": 0.5751829376468695, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.3449, w_MATIC-USD=0.0000, w_DBC=0.6551, w_MORT=0.0000\nPortfolio annualized return: 11.78%, volatility: 13.52%\nSharpe ratio: (0.1178 - 0.0400) / 0.1352 = 0.5752", "metadata": {"weights": {"IVV": 0.3449, "MATIC-USD": 0.0, "DBC": 0.6551, "MORT": 0.0}, "sharpe_ratio": 0.5752, "portfolio_return": 0.117776, "portfolio_vol": 0.135219, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240820_0600", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "SOL-USD", "CSHI", "IGOV"], "decision_date": "2024-08-20", "context_summary": "4-asset optimization. Max-Sharpe: 5.299. Portfolio: return=43.22%, vol=7.40%. Weights: w_EEM=0.0000, w_SOL-USD=0.0760, w_CSHI=0.0000, w_IGOV=0.9240.", "question": "Assets: EEM, SOL-USD, CSHI, IGOV\nAnnualized mean returns: EEM:0.1433, SOL-USD:1.6498, CSHI:0.0557, IGOV:0.3321\nCovariance matrix (annualized):\n[[0.027721, 0.024683, 0.001127, 0.000382], [0.024683, 0.623504, 0.008132, -0.02694], [0.001127, 0.008132, 0.000355, -0.000313], [0.000382, -0.02694, -0.000313, 0.006632]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_SOL-USD=0.0760, w_CSHI=0.0000, w_IGOV=0.9240", "answer_numeric": 5.298635782855058, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_SOL-USD=0.0760, w_CSHI=0.0000, w_IGOV=0.9240\nPortfolio annualized return: 43.22%, volatility: 7.40%\nSharpe ratio: (0.4322 - 0.0400) / 0.0740 = 5.2986", "metadata": {"weights": {"EEM": 0.0, "SOL-USD": 0.076, "CSHI": 0.0, "IGOV": 0.924}, "sharpe_ratio": 5.2986, "portfolio_return": 0.432237, "portfolio_vol": 0.074026, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231128_0605", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "DOT-USD", "PDBC", "JNK"], "decision_date": "2023-11-28", "context_summary": "4-asset optimization. Max-Sharpe: 1.783. Portfolio: return=17.69%, vol=7.68%. Weights: w_VLUE=0.0000, w_DOT-USD=0.0000, w_PDBC=0.0000, w_JNK=1.0000.", "question": "Assets: VLUE, DOT-USD, PDBC, JNK\nAnnualized mean returns: VLUE:0.1702, DOT-USD:-0.2135, PDBC:-0.3264, JNK:0.1769\nCovariance matrix (annualized):\n[[0.023339, 0.000755, 0.001024, 0.008496], [0.000755, 0.321627, -0.016529, 0.001254], [0.001024, -0.016529, 0.032868, -0.000333], [0.008496, 0.001254, -0.000333, 0.0059]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_DOT-USD=0.0000, w_PDBC=0.0000, w_JNK=1.0000", "answer_numeric": 1.7826664525560239, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_DOT-USD=0.0000, w_PDBC=0.0000, w_JNK=1.0000\nPortfolio annualized return: 17.69%, volatility: 7.68%\nSharpe ratio: (0.1769 - 0.0400) / 0.0768 = 1.7827", "metadata": {"weights": {"VLUE": 0.0, "DOT-USD": 0.0, "PDBC": 0.0, "JNK": 1.0}, "sharpe_ratio": 1.7827, "portfolio_return": 0.176927, "portfolio_vol": 0.07681, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231214_0608", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "MATIC-USD", "WEAT", "SGOV"], "decision_date": "2023-12-14", "context_summary": "4-asset optimization. Max-Sharpe: 5.966. Portfolio: return=6.09%, vol=0.35%. Weights: w_XLI=0.0134, w_MATIC-USD=0.0015, w_WEAT=0.0000, w_SGOV=0.9851.", "question": "Assets: XLI, MATIC-USD, WEAT, SGOV\nAnnualized mean returns: XLI:0.5614, MATIC-USD:1.4879, WEAT:-0.0025, SGOV:0.0519\nCovariance matrix (annualized):\n[[0.019622, 0.003086, -0.00601, 3.8e-05], [0.003086, 0.423984, 0.040953, 0.000193], [-0.00601, 0.040953, 0.058596, 0.000148], [3.8e-05, 0.000193, 0.000148, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0134, w_MATIC-USD=0.0015, w_WEAT=0.0000, w_SGOV=0.9851", "answer_numeric": 5.966267744002748, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0134, w_MATIC-USD=0.0015, w_WEAT=0.0000, w_SGOV=0.9851\nPortfolio annualized return: 6.09%, volatility: 0.35%\nSharpe ratio: (0.0609 - 0.0400) / 0.0035 = 5.9663", "metadata": {"weights": {"XLI": 0.0134, "MATIC-USD": 0.0015, "WEAT": 0.0, "SGOV": 0.9851}, "sharpe_ratio": 5.9663, "portfolio_return": 0.060882, "portfolio_vol": 0.0035, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230502_0610", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ETH-USD", "SGOV", "SLV"], "decision_date": "2023-05-02", "context_summary": "4-asset optimization. Max-Sharpe: 4.368. Portfolio: return=8.18%, vol=0.96%. Weights: w_XLV=0.0238, w_ETH-USD=0.0000, w_SGOV=0.9452, w_SLV=0.0310.", "question": "Assets: XLV, ETH-USD, SGOV, SLV\nAnnualized mean returns: XLV:0.3281, ETH-USD:0.1818, SGOV:0.0443, SLV:1.0362\nCovariance matrix (annualized):\n[[0.018977, -0.002431, 8.1e-05, 0.003342], [-0.002431, 0.274025, 0.000309, 0.033739], [8.1e-05, 0.000309, 7e-06, 4e-05], [0.003342, 0.033739, 4e-05, 0.066681]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0238, w_ETH-USD=0.0000, w_SGOV=0.9452, w_SLV=0.0310", "answer_numeric": 4.36751285889726, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0238, w_ETH-USD=0.0000, w_SGOV=0.9452, w_SLV=0.0310\nPortfolio annualized return: 8.18%, volatility: 0.96%\nSharpe ratio: (0.0818 - 0.0400) / 0.0096 = 4.3675", "metadata": {"weights": {"XLV": 0.0238, "ETH-USD": 0.0, "SGOV": 0.9452, "SLV": 0.031}, "sharpe_ratio": 4.3675, "portfolio_return": 0.081849, "portfolio_vol": 0.009582, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230704_0611", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "XRP-USD", "TLT", "SGOV"], "decision_date": "2023-07-04", "context_summary": "4-asset optimization. Max-Sharpe: 6.150. Portfolio: return=6.69%, vol=0.44%. Weights: w_QUAL=0.0230, w_XRP-USD=0.0000, w_TLT=0.0000, w_SGOV=0.9770.", "question": "Assets: QUAL, XRP-USD, TLT, SGOV\nAnnualized mean returns: QUAL:0.6174, XRP-USD:0.3678, TLT:-0.1499, SGOV:0.0539\nCovariance matrix (annualized):\n[[0.015015, 0.011717, -0.000302, 6.6e-05], [0.011717, 0.171094, -0.000109, -2.4e-05], [-0.000302, -0.000109, 0.017038, 8.8e-05], [6.6e-05, -2.4e-05, 8.8e-05, 9e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0230, w_XRP-USD=0.0000, w_TLT=0.0000, w_SGOV=0.9770", "answer_numeric": 6.150442288893731, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0230, w_XRP-USD=0.0000, w_TLT=0.0000, w_SGOV=0.9770\nPortfolio annualized return: 6.69%, volatility: 0.44%\nSharpe ratio: (0.0669 - 0.0400) / 0.0044 = 6.1504", "metadata": {"weights": {"QUAL": 0.023, "XRP-USD": 0.0, "TLT": 0.0, "SGOV": 0.977}, "sharpe_ratio": 6.1504, "portfolio_return": 0.066895, "portfolio_vol": 0.004373, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230213_0613", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "XRP-USD", "BIL", "REZ"], "decision_date": "2023-02-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.310. Portfolio: return=31.97%, vol=21.35%. Weights: w_ACWI=0.1636, w_XRP-USD=0.0000, w_BIL=0.0000, w_REZ=0.8364.", "question": "Assets: ACWI, XRP-USD, BIL, REZ\nAnnualized mean returns: ACWI:0.2090, XRP-USD:0.1722, BIL:0.0393, REZ:0.3413\nCovariance matrix (annualized):\n[[0.026155, 0.037826, -6.6e-05, 0.027808], [0.037826, 0.223794, -0.000263, 0.051923], [-6.6e-05, -0.000263, 1.1e-05, -4.5e-05], [0.027808, 0.051923, -4.5e-05, 0.053259]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.1636, w_XRP-USD=0.0000, w_BIL=0.0000, w_REZ=0.8364", "answer_numeric": 1.3100913616609562, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.1636, w_XRP-USD=0.0000, w_BIL=0.0000, w_REZ=0.8364\nPortfolio annualized return: 31.97%, volatility: 21.35%\nSharpe ratio: (0.3197 - 0.0400) / 0.2135 = 1.3101", "metadata": {"weights": {"ACWI": 0.1636, "XRP-USD": 0.0, "BIL": 0.0, "REZ": 0.8364}, "sharpe_ratio": 1.3101, "portfolio_return": 0.319666, "portfolio_vol": 0.21347, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230523_0615", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "SOYB", "CSHI"], "decision_date": "2023-05-23", "context_summary": "4-asset optimization. Max-Sharpe: 1.789. Portfolio: return=6.35%, vol=1.31%. Weights: w_^VIX=0.0000, w_ADA-USD=0.0240, w_SOYB=0.0000, w_CSHI=0.9760.", "question": "Assets: ^VIX, ADA-USD, SOYB, CSHI\nAnnualized mean returns: ^VIX:-1.6773, ADA-USD:0.5102, SOYB:-0.2124, CSHI:0.0525\nCovariance matrix (annualized):\n[[0.662705, -0.03796, -0.029677, 0.000156], [-0.03796, 0.203098, 0.007473, -0.001451], [-0.029677, 0.007473, 0.01904, -0.000243], [0.000156, -0.001451, -0.000243, 0.00013]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0000, w_ADA-USD=0.0240, w_SOYB=0.0000, w_CSHI=0.9760", "answer_numeric": 1.789279877661785, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_ADA-USD=0.0240, w_SOYB=0.0000, w_CSHI=0.9760\nPortfolio annualized return: 6.35%, volatility: 1.31%\nSharpe ratio: (0.0635 - 0.0400) / 0.0131 = 1.7893", "metadata": {"weights": {"^VIX": 0.0, "ADA-USD": 0.024, "SOYB": 0.0, "CSHI": 0.976}, "sharpe_ratio": 1.7893, "portfolio_return": 0.063479, "portfolio_vol": 0.013122, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240604_0617", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "IYR", "PALL"], "decision_date": "2024-06-04", "context_summary": "4-asset optimization. Max-Sharpe: -0.050. Portfolio: return=3.11%, vol=17.93%. Weights: w_XLE=0.0000, w_LINK-USD=0.0000, w_IYR=1.0000, w_PALL=0.0000.", "question": "Assets: XLE, LINK-USD, IYR, PALL\nAnnualized mean returns: XLE:-0.4112, LINK-USD:-0.4471, IYR:0.0311, PALL:-0.5576\nCovariance matrix (annualized):\n[[0.030438, 0.044206, 0.016362, 0.008759], [0.044206, 0.439928, 0.028919, 0.02105], [0.016362, 0.028919, 0.032138, 0.025398], [0.008759, 0.02105, 0.025398, 0.111076]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_LINK-USD=0.0000, w_IYR=1.0000, w_PALL=0.0000", "answer_numeric": -0.04967232034420203, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_LINK-USD=0.0000, w_IYR=1.0000, w_PALL=0.0000\nPortfolio annualized return: 3.11%, volatility: 17.93%\nSharpe ratio: (0.0311 - 0.0400) / 0.1793 = -0.0497", "metadata": {"weights": {"XLE": 0.0, "LINK-USD": 0.0, "IYR": 1.0, "PALL": 0.0}, "sharpe_ratio": -0.0497, "portfolio_return": 0.031095, "portfolio_vol": 0.179269, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230615_0618", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "IAU", "VCIT"], "decision_date": "2023-06-15", "context_summary": "4-asset optimization. Max-Sharpe: -0.217. Portfolio: return=-2.15%, vol=28.34%. Weights: w_FXI=1.0000, w_ETH-USD=0.0000, w_IAU=0.0000, w_VCIT=0.0000.", "question": "Assets: FXI, ETH-USD, IAU, VCIT\nAnnualized mean returns: FXI:-0.0215, ETH-USD:-0.8470, IAU:-0.1768, VCIT:-0.0863\nCovariance matrix (annualized):\n[[0.08034, 0.015111, -0.000828, -0.003248], [0.015111, 0.156035, 0.006003, 0.004853], [-0.000828, 0.006003, 0.015285, 0.005401], [-0.003248, 0.004853, 0.005401, 0.004795]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=1.0000, w_ETH-USD=0.0000, w_IAU=0.0000, w_VCIT=0.0000", "answer_numeric": -0.21690616327395226, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=1.0000, w_ETH-USD=0.0000, w_IAU=0.0000, w_VCIT=0.0000\nPortfolio annualized return: -2.15%, volatility: 28.34%\nSharpe ratio: (-0.0215 - 0.0400) / 0.2834 = -0.2169", "metadata": {"weights": {"FXI": 1.0, "ETH-USD": 0.0, "IAU": 0.0, "VCIT": 0.0}, "sharpe_ratio": -0.2169, "portfolio_return": -0.02148, "portfolio_vol": 0.283443, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230306_0620", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "MATIC-USD", "BIL", "SCHH"], "decision_date": "2023-03-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.855. Portfolio: return=6.61%, vol=0.91%. Weights: w_EEM=0.0000, w_MATIC-USD=0.0108, w_BIL=0.9881, w_SCHH=0.0011.", "question": "Assets: EEM, MATIC-USD, BIL, SCHH\nAnnualized mean returns: EEM:0.0271, MATIC-USD:2.1391, BIL:0.0434, SCHH:0.1727\nCovariance matrix (annualized):\n[[0.026107, 0.037556, 2.7e-05, 0.014626], [0.037556, 0.601585, 0.000217, 0.034329], [2.7e-05, 0.000217, 9e-06, 8e-06], [0.014626, 0.034329, 8e-06, 0.042653]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_MATIC-USD=0.0108, w_BIL=0.9881, w_SCHH=0.0011", "answer_numeric": 2.8548254852597967, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_MATIC-USD=0.0108, w_BIL=0.9881, w_SCHH=0.0011\nPortfolio annualized return: 6.61%, volatility: 0.91%\nSharpe ratio: (0.0661 - 0.0400) / 0.0091 = 2.8548", "metadata": {"weights": {"EEM": 0.0, "MATIC-USD": 0.0108, "BIL": 0.9881, "SCHH": 0.0011}, "sharpe_ratio": 2.8548, "portfolio_return": 0.066106, "portfolio_vol": 0.009144, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240327_0622", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "SOL-USD", "UNG", "SCHP"], "decision_date": "2024-03-27", "context_summary": "4-asset optimization. Max-Sharpe: 4.570. Portfolio: return=221.75%, vol=47.65%. Weights: w_XLRE=0.0000, w_SOL-USD=0.6072, w_UNG=0.0000, w_SCHP=0.3928.", "question": "Assets: XLRE, SOL-USD, UNG, SCHP\nAnnualized mean returns: XLRE:0.0129, SOL-USD:3.6375, UNG:-1.9026, SCHP:0.0222\nCovariance matrix (annualized):\n[[0.024382, 0.009185, -0.006362, 0.003733], [0.009185, 0.620737, -0.100687, -0.004638], [-0.006362, -0.100687, 0.272348, -0.004569], [0.003733, -0.004638, -0.004569, 0.002431]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_SOL-USD=0.6072, w_UNG=0.0000, w_SCHP=0.3928", "answer_numeric": 4.569869613920094, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_SOL-USD=0.6072, w_UNG=0.0000, w_SCHP=0.3928\nPortfolio annualized return: 221.75%, volatility: 47.65%\nSharpe ratio: (2.2175 - 0.0400) / 0.4765 = 4.5699", "metadata": {"weights": {"XLRE": 0.0, "SOL-USD": 0.6072, "UNG": 0.0, "SCHP": 0.3928}, "sharpe_ratio": 4.5699, "portfolio_return": 2.217541, "portfolio_vol": 0.4765, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240822_0624", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "ETH-USD", "SOYB", "BIL"], "decision_date": "2024-08-22", "context_summary": "4-asset optimization. Max-Sharpe: -1.061. Portfolio: return=-15.09%, vol=17.99%. Weights: w_IWM=0.2500, w_ETH-USD=0.2500, w_SOYB=0.2500, w_BIL=0.2500.", "question": "Assets: IWM, ETH-USD, SOYB, BIL\nAnnualized mean returns: IWM:0.4339, ETH-USD:-0.4788, SOYB:-0.6102, BIL:0.0514\nCovariance matrix (annualized):\n[[0.066878, 0.069228, -0.003397, -0.000132], [0.069228, 0.404884, -0.062143, 3e-06], [-0.003397, -0.062143, 0.039076, -6.2e-05], [-0.000132, 3e-06, -6.2e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.2500, w_ETH-USD=0.2500, w_SOYB=0.2500, w_BIL=0.2500", "answer_numeric": -1.0611688171138338, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.2500, w_ETH-USD=0.2500, w_SOYB=0.2500, w_BIL=0.2500\nPortfolio annualized return: -15.09%, volatility: 17.99%\nSharpe ratio: (-0.1509 - 0.0400) / 0.1799 = -1.0612", "metadata": {"weights": {"IWM": 0.25, "ETH-USD": 0.25, "SOYB": 0.25, "BIL": 0.25}, "sharpe_ratio": -1.0612, "portfolio_return": -0.150907, "portfolio_vol": 0.179902, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240724_0625", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "BIL", "PPLT"], "decision_date": "2024-07-24", "context_summary": "4-asset optimization. Max-Sharpe: 5.436. Portfolio: return=5.21%, vol=0.22%. Weights: w_ACWI=0.0102, w_ETH-USD=0.0000, w_BIL=0.9898, w_PPLT=0.0000.", "question": "Assets: ACWI, ETH-USD, BIL, PPLT\nAnnualized mean returns: ACWI:0.2010, ETH-USD:-0.7454, BIL:0.0506, PPLT:-0.5019\nCovariance matrix (annualized):\n[[0.008069, 0.00056, -1.6e-05, 0.007906], [0.00056, 0.125866, -2.4e-05, -0.011632], [-1.6e-05, -2.4e-05, 5e-06, -9.2e-05], [0.007906, -0.011632, -9.2e-05, 0.067483]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0102, w_ETH-USD=0.0000, w_BIL=0.9898, w_PPLT=0.0000", "answer_numeric": 5.436342165011066, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0102, w_ETH-USD=0.0000, w_BIL=0.9898, w_PPLT=0.0000\nPortfolio annualized return: 5.21%, volatility: 0.22%\nSharpe ratio: (0.0521 - 0.0400) / 0.0022 = 5.4363", "metadata": {"weights": {"ACWI": 0.0102, "ETH-USD": 0.0, "BIL": 0.9898, "PPLT": 0.0}, "sharpe_ratio": 5.4363, "portfolio_return": 0.052128, "portfolio_vol": 0.002231, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230602_0626", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "DBA", "XHB"], "decision_date": "2023-06-02", "context_summary": "4-asset optimization. Max-Sharpe: 1.410. Portfolio: return=33.37%, vol=20.83%. Weights: w_VEA=0.0000, w_ETH-USD=0.4302, w_DBA=0.0526, w_XHB=0.5171.", "question": "Assets: VEA, ETH-USD, DBA, XHB\nAnnualized mean returns: VEA:0.0199, ETH-USD:0.5205, DBA:0.1024, XHB:0.2018\nCovariance matrix (annualized):\n[[0.015054, 0.012051, 0.007127, 0.01338], [0.012051, 0.157373, 0.014143, 0.004958], [0.007127, 0.014143, 0.012727, 0.00476], [0.01338, 0.004958, 0.00476, 0.041622]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_ETH-USD=0.4302, w_DBA=0.0526, w_XHB=0.5171", "answer_numeric": 1.4096383401423378, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_ETH-USD=0.4302, w_DBA=0.0526, w_XHB=0.5171\nPortfolio annualized return: 33.37%, volatility: 20.83%\nSharpe ratio: (0.3337 - 0.0400) / 0.2083 = 1.4096", "metadata": {"weights": {"VEA": 0.0, "ETH-USD": 0.4302, "DBA": 0.0526, "XHB": 0.5171}, "sharpe_ratio": 1.4096, "portfolio_return": 0.333667, "portfolio_vol": 0.208328, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240826_0628", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "SCHP", "IAU"], "decision_date": "2024-08-26", "context_summary": "4-asset optimization. Max-Sharpe: 5.886. Portfolio: return=43.65%, vol=6.74%. Weights: w_XLRE=0.3481, w_ETH-USD=0.0000, w_SCHP=0.5863, w_IAU=0.0657.", "question": "Assets: XLRE, ETH-USD, SCHP, IAU\nAnnualized mean returns: XLRE:0.8514, ETH-USD:-0.0916, SCHP:0.1775, IAU:0.5500\nCovariance matrix (annualized):\n[[0.024164, 0.041292, 0.000726, 0.006871], [0.041292, 0.430325, -0.003267, 0.032691], [0.000726, -0.003267, 0.001909, 0.003081], [0.006871, 0.032691, 0.003081, 0.024969]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.3481, w_ETH-USD=0.0000, w_SCHP=0.5863, w_IAU=0.0657", "answer_numeric": 5.885745978513337, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.3481, w_ETH-USD=0.0000, w_SCHP=0.5863, w_IAU=0.0657\nPortfolio annualized return: 43.65%, volatility: 6.74%\nSharpe ratio: (0.4365 - 0.0400) / 0.0674 = 5.8857", "metadata": {"weights": {"XLRE": 0.3481, "ETH-USD": 0.0, "SCHP": 0.5863, "IAU": 0.0657}, "sharpe_ratio": 5.8857, "portfolio_return": 0.436543, "portfolio_vol": 0.067373, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240108_0630", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "DOT-USD", "WEAT", "IYR"], "decision_date": "2024-01-08", "context_summary": "4-asset optimization. Max-Sharpe: 4.785. Portfolio: return=59.80%, vol=11.66%. Weights: w_XLV=0.7207, w_DOT-USD=0.0000, w_WEAT=0.0101, w_IYR=0.2691.", "question": "Assets: XLV, DOT-USD, WEAT, IYR\nAnnualized mean returns: XLV:0.5586, DOT-USD:0.5544, WEAT:0.0003, IYR:0.7261\nCovariance matrix (annualized):\n[[0.013533, 0.01962, -0.002569, 0.010823], [0.01962, 0.834146, 0.012611, 0.037856], [-0.002569, 0.012611, 0.068047, 0.00072], [0.010823, 0.037856, 0.00072, 0.033127]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.7207, w_DOT-USD=0.0000, w_WEAT=0.0101, w_IYR=0.2691", "answer_numeric": 4.784517749495509, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.7207, w_DOT-USD=0.0000, w_WEAT=0.0101, w_IYR=0.2691\nPortfolio annualized return: 59.80%, volatility: 11.66%\nSharpe ratio: (0.5980 - 0.0400) / 0.1166 = 4.7845", "metadata": {"weights": {"XLV": 0.7207, "DOT-USD": 0.0, "WEAT": 0.0101, "IYR": 0.2691}, "sharpe_ratio": 4.7845, "portfolio_return": 0.597996, "portfolio_vol": 0.116625, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240812_0632", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "GLD", "VNQ"], "decision_date": "2024-08-12", "context_summary": "4-asset optimization. Max-Sharpe: 3.739. Portfolio: return=60.90%, vol=15.22%. Weights: w_EEM=0.0000, w_BNB-USD=0.0000, w_GLD=0.0486, w_VNQ=0.9514.", "question": "Assets: EEM, BNB-USD, GLD, VNQ\nAnnualized mean returns: EEM:-0.0329, BNB-USD:-0.4660, GLD:0.2943, VNQ:0.6251\nCovariance matrix (annualized):\n[[0.026074, 0.018012, 0.014061, 0.010507], [0.018012, 0.236495, 0.002749, 0.02808], [0.014061, 0.002749, 0.024349, 0.009636], [0.010507, 0.02808, 0.009636, 0.02454]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_BNB-USD=0.0000, w_GLD=0.0486, w_VNQ=0.9514", "answer_numeric": 3.738832106168765, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_BNB-USD=0.0000, w_GLD=0.0486, w_VNQ=0.9514\nPortfolio annualized return: 60.90%, volatility: 15.22%\nSharpe ratio: (0.6090 - 0.0400) / 0.1522 = 3.7388", "metadata": {"weights": {"EEM": 0.0, "BNB-USD": 0.0, "GLD": 0.0486, "VNQ": 0.9514}, "sharpe_ratio": 3.7388, "portfolio_return": 0.609009, "portfolio_vol": 0.152189, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231103_0633", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "HYG", "ICSH"], "decision_date": "2023-11-03", "context_summary": "4-asset optimization. Max-Sharpe: 6.068. Portfolio: return=7.38%, vol=0.56%. Weights: w_XLV=0.0000, w_LINK-USD=0.0088, w_HYG=0.0000, w_ICSH=0.9912.", "question": "Assets: XLV, LINK-USD, HYG, ICSH\nAnnualized mean returns: XLV:-0.2818, LINK-USD:2.2107, HYG:-0.0442, ICSH:0.0548\nCovariance matrix (annualized):\n[[0.012038, -0.00744, 0.004681, -2.6e-05], [-0.00744, 0.254682, -0.000287, -0.000252], [0.004681, -0.000287, 0.004944, 5.3e-05], [-2.6e-05, -0.000252, 5.3e-05, 1.6e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_LINK-USD=0.0088, w_HYG=0.0000, w_ICSH=0.9912", "answer_numeric": 6.068489783344578, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_LINK-USD=0.0088, w_HYG=0.0000, w_ICSH=0.9912\nPortfolio annualized return: 7.38%, volatility: 0.56%\nSharpe ratio: (0.0738 - 0.0400) / 0.0056 = 6.0685", "metadata": {"weights": {"XLV": 0.0, "LINK-USD": 0.0088, "HYG": 0.0, "ICSH": 0.9912}, "sharpe_ratio": 6.0685, "portfolio_return": 0.073768, "portfolio_vol": 0.005564, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231215_0634", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "MATIC-USD", "UNG", "BIL"], "decision_date": "2023-12-15", "context_summary": "4-asset optimization. Max-Sharpe: -1.120. Portfolio: return=-17.03%, vol=18.79%. Weights: w_USMV=0.2500, w_MATIC-USD=0.2500, w_UNG=0.2500, w_BIL=0.2500.", "question": "Assets: USMV, MATIC-USD, UNG, BIL\nAnnualized mean returns: USMV:0.3810, MATIC-USD:1.4298, UNG:-2.5438, BIL:0.0516\nCovariance matrix (annualized):\n[[0.010729, -0.003141, 0.000386, -6.6e-05], [-0.003141, 0.414464, -0.03719, 6.1e-05], [0.000386, -0.03719, 0.219316, 3.8e-05], [-6.6e-05, 6.1e-05, 3.8e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.2500, w_MATIC-USD=0.2500, w_UNG=0.2500, w_BIL=0.2500", "answer_numeric": -1.1195124949691049, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.2500, w_MATIC-USD=0.2500, w_UNG=0.2500, w_BIL=0.2500\nPortfolio annualized return: -17.03%, volatility: 18.79%\nSharpe ratio: (-0.1703 - 0.0400) / 0.1879 = -1.1195", "metadata": {"weights": {"USMV": 0.25, "MATIC-USD": 0.25, "UNG": 0.25, "BIL": 0.25}, "sharpe_ratio": -1.1195, "portfolio_return": -0.170317, "portfolio_vol": 0.187865, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240722_0635", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "ICSH", "DBA"], "decision_date": "2024-07-22", "context_summary": "4-asset optimization. Max-Sharpe: 6.292. Portfolio: return=6.38%, vol=0.38%. Weights: w_XLU=0.0000, w_LINK-USD=0.0000, w_ICSH=1.0000, w_DBA=0.0000.", "question": "Assets: XLU, LINK-USD, ICSH, DBA\nAnnualized mean returns: XLU:-0.1190, LINK-USD:-1.3494, ICSH:0.0638, DBA:-0.1155\nCovariance matrix (annualized):\n[[0.023766, -0.004103, 0.000146, -0.006403], [-0.004103, 0.313748, 0.00026, -0.016266], [0.000146, 0.00026, 1.4e-05, 0.000105], [-0.006403, -0.016266, 0.000105, 0.033202]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_LINK-USD=0.0000, w_ICSH=1.0000, w_DBA=0.0000", "answer_numeric": 6.29195000054748, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_LINK-USD=0.0000, w_ICSH=1.0000, w_DBA=0.0000\nPortfolio annualized return: 6.38%, volatility: 0.38%\nSharpe ratio: (0.0638 - 0.0400) / 0.0038 = 6.2920", "metadata": {"weights": {"XLU": 0.0, "LINK-USD": 0.0, "ICSH": 1.0, "DBA": 0.0}, "sharpe_ratio": 6.292, "portfolio_return": 0.063816, "portfolio_vol": 0.003785, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240130_0637", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD", "EMB", "DBA"], "decision_date": "2024-01-30", "context_summary": "4-asset optimization. Max-Sharpe: 2.915. Portfolio: return=40.34%, vol=12.47%. Weights: w_VEA=0.6732, w_AVAX-USD=0.0782, w_EMB=0.1843, w_DBA=0.0642.", "question": "Assets: VEA, AVAX-USD, EMB, DBA\nAnnualized mean returns: VEA:0.3257, AVAX-USD:1.8441, EMB:0.2097, DBA:0.0199\nCovariance matrix (annualized):\n[[0.014816, 0.01163, 0.007184, 0.000122], [0.01163, 0.870497, 0.012759, -0.017622], [0.007184, 0.012759, 0.008512, -0.002325], [0.000122, -0.017622, -0.002325, 0.013494]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.6732, w_AVAX-USD=0.0782, w_EMB=0.1843, w_DBA=0.0642", "answer_numeric": 2.9153916701136593, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.6732, w_AVAX-USD=0.0782, w_EMB=0.1843, w_DBA=0.0642\nPortfolio annualized return: 40.34%, volatility: 12.47%\nSharpe ratio: (0.4034 - 0.0400) / 0.1247 = 2.9154", "metadata": {"weights": {"VEA": 0.6732, "AVAX-USD": 0.0782, "EMB": 0.1843, "DBA": 0.0642}, "sharpe_ratio": 2.9154, "portfolio_return": 0.403447, "portfolio_vol": 0.124665, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240213_0639", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "XRP-USD", "SGOV", "LQD"], "decision_date": "2024-02-13", "context_summary": "4-asset optimization. Max-Sharpe: 4.970. Portfolio: return=5.40%, vol=0.28%. Weights: w_EEM=0.0000, w_XRP-USD=0.0000, w_SGOV=1.0000, w_LQD=0.0000.", "question": "Assets: EEM, XRP-USD, SGOV, LQD\nAnnualized mean returns: EEM:0.0678, XRP-USD:-0.8762, SGOV:0.0540, LQD:-0.1132\nCovariance matrix (annualized):\n[[0.023111, 0.006182, 0.000147, 0.003785], [0.006182, 0.166122, 0.000131, 0.000897], [0.000147, 0.000131, 8e-06, 4e-05], [0.003785, 0.000897, 4e-05, 0.0057]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_XRP-USD=0.0000, w_SGOV=1.0000, w_LQD=0.0000", "answer_numeric": 4.9704011597832185, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_XRP-USD=0.0000, w_SGOV=1.0000, w_LQD=0.0000\nPortfolio annualized return: 5.40%, volatility: 0.28%\nSharpe ratio: (0.0540 - 0.0400) / 0.0028 = 4.9704", "metadata": {"weights": {"EEM": 0.0, "XRP-USD": 0.0, "SGOV": 1.0, "LQD": 0.0}, "sharpe_ratio": 4.9704, "portfolio_return": 0.053955, "portfolio_vol": 0.002808, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240718_0640", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "IYR", "ICSH"], "decision_date": "2024-07-18", "context_summary": "4-asset optimization. Max-Sharpe: 6.833. Portfolio: return=7.20%, vol=0.47%. Weights: w_IVV=0.0237, w_BTC-USD=0.0000, w_IYR=0.0054, w_ICSH=0.9708.", "question": "Assets: IVV, BTC-USD, IYR, ICSH\nAnnualized mean returns: IVV:0.3408, BTC-USD:-0.3375, IYR:0.4276, ICSH:0.0635\nCovariance matrix (annualized):\n[[0.007227, 0.005794, 0.000698, 3.2e-05], [0.005794, 0.140071, -0.000267, 0.000164], [0.000698, -0.000267, 0.019885, 0.000146], [3.2e-05, 0.000164, 0.000146, 1.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0237, w_BTC-USD=0.0000, w_IYR=0.0054, w_ICSH=0.9708", "answer_numeric": 6.832835938550794, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0237, w_BTC-USD=0.0000, w_IYR=0.0054, w_ICSH=0.9708\nPortfolio annualized return: 7.20%, volatility: 0.47%\nSharpe ratio: (0.0720 - 0.0400) / 0.0047 = 6.8328", "metadata": {"weights": {"IVV": 0.0237, "BTC-USD": 0.0, "IYR": 0.0054, "ICSH": 0.9708}, "sharpe_ratio": 6.8328, "portfolio_return": 0.072031, "portfolio_vol": 0.004688, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231115_0641", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ETH-USD", "CSHI", "EMB"], "decision_date": "2023-11-15", "context_summary": "4-asset optimization. Max-Sharpe: 2.561. Portfolio: return=6.86%, vol=1.11%. Weights: w_XLI=0.0000, w_ETH-USD=0.0161, w_CSHI=0.9839, w_EMB=0.0000.", "question": "Assets: XLI, ETH-USD, CSHI, EMB\nAnnualized mean returns: XLI:0.0072, ETH-USD:0.7454, CSHI:0.0574, EMB:0.0056\nCovariance matrix (annualized):\n[[0.025325, -0.004715, 0.000458, 0.010272], [-0.004715, 0.184393, 9.5e-05, -0.00261], [0.000458, 9.5e-05, 7.6e-05, 3.1e-05], [0.010272, -0.00261, 3.1e-05, 0.0117]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_ETH-USD=0.0161, w_CSHI=0.9839, w_EMB=0.0000", "answer_numeric": 2.561137076449091, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_ETH-USD=0.0161, w_CSHI=0.9839, w_EMB=0.0000\nPortfolio annualized return: 6.86%, volatility: 1.11%\nSharpe ratio: (0.0686 - 0.0400) / 0.0111 = 2.5611", "metadata": {"weights": {"XLI": 0.0, "ETH-USD": 0.0161, "CSHI": 0.9839, "EMB": 0.0}, "sharpe_ratio": 2.5611, "portfolio_return": 0.068554, "portfolio_vol": 0.011149, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230725_0642", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ETH-USD", "SOYB", "CSHI"], "decision_date": "2023-07-25", "context_summary": "4-asset optimization. Max-Sharpe: 3.895. Portfolio: return=100.55%, vol=24.79%. Weights: w_^VIX=0.0000, w_ETH-USD=0.0000, w_SOYB=1.0000, w_CSHI=0.0000.", "question": "Assets: ^VIX, ETH-USD, SOYB, CSHI\nAnnualized mean returns: ^VIX:-2.0623, ETH-USD:0.4144, SOYB:1.0055, CSHI:0.0459\nCovariance matrix (annualized):\n[[0.533768, -0.05933, 0.005293, -0.000245], [-0.05933, 0.167293, 0.037695, 0.001137], [0.005293, 0.037695, 0.061456, 0.000524], [-0.000245, 0.001137, 0.000524, 5.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0000, w_ETH-USD=0.0000, w_SOYB=1.0000, w_CSHI=0.0000", "answer_numeric": 3.894758430345955, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_ETH-USD=0.0000, w_SOYB=1.0000, w_CSHI=0.0000\nPortfolio annualized return: 100.55%, volatility: 24.79%\nSharpe ratio: (1.0055 - 0.0400) / 0.2479 = 3.8948", "metadata": {"weights": {"^VIX": 0.0, "ETH-USD": 0.0, "SOYB": 1.0, "CSHI": 0.0}, "sharpe_ratio": 3.8948, "portfolio_return": 1.005521, "portfolio_vol": 0.247903, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230418_0643", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "ICSH", "ITB"], "decision_date": "2023-04-18", "context_summary": "4-asset optimization. Max-Sharpe: 2.942. Portfolio: return=7.53%, vol=1.20%. Weights: w_USMV=0.0370, w_XRP-USD=0.0126, w_ICSH=0.9504, w_ITB=0.0000.", "question": "Assets: USMV, XRP-USD, ICSH, ITB\nAnnualized mean returns: USMV:0.1588, XRP-USD:1.9499, ICSH:0.0471, ITB:0.1496\nCovariance matrix (annualized):\n[[0.013614, 0.009476, -0.000147, 0.014801], [0.009476, 0.67743, -0.001165, 0.0337], [-0.000147, -0.001165, 5.2e-05, -0.000393], [0.014801, 0.0337, -0.000393, 0.046823]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0370, w_XRP-USD=0.0126, w_ICSH=0.9504, w_ITB=0.0000", "answer_numeric": 2.9420713766491255, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0370, w_XRP-USD=0.0126, w_ICSH=0.9504, w_ITB=0.0000\nPortfolio annualized return: 7.53%, volatility: 1.20%\nSharpe ratio: (0.0753 - 0.0400) / 0.0120 = 2.9421", "metadata": {"weights": {"USMV": 0.037, "XRP-USD": 0.0126, "ICSH": 0.9504, "ITB": 0.0}, "sharpe_ratio": 2.9421, "portfolio_return": 0.075256, "portfolio_vol": 0.011983, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231207_0645", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "AVAX-USD", "ICSH", "TLT"], "decision_date": "2023-12-07", "context_summary": "4-asset optimization. Max-Sharpe: 7.418. Portfolio: return=8.09%, vol=0.55%. Weights: w_XLB=0.0000, w_AVAX-USD=0.0034, w_ICSH=0.9935, w_TLT=0.0031.", "question": "Assets: XLB, AVAX-USD, ICSH, TLT\nAnnualized mean returns: XLB:0.2331, AVAX-USD:3.3185, ICSH:0.0674, TLT:0.8315\nCovariance matrix (annualized):\n[[0.029549, 0.013031, 0.00027, 0.01091], [0.013031, 0.901974, -0.000678, 0.00338], [0.00027, -0.000678, 2.2e-05, 0.000425], [0.01091, 0.00338, 0.000425, 0.050626]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_AVAX-USD=0.0034, w_ICSH=0.9935, w_TLT=0.0031", "answer_numeric": 7.418232690639321, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_AVAX-USD=0.0034, w_ICSH=0.9935, w_TLT=0.0031\nPortfolio annualized return: 8.09%, volatility: 0.55%\nSharpe ratio: (0.0809 - 0.0400) / 0.0055 = 7.4182", "metadata": {"weights": {"XLB": 0.0, "AVAX-USD": 0.0034, "ICSH": 0.9935, "TLT": 0.0031}, "sharpe_ratio": 7.4182, "portfolio_return": 0.080898, "portfolio_vol": 0.005513, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230530_0647", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "DOT-USD", "XHB", "IAU"], "decision_date": "2023-05-30", "context_summary": "4-asset optimization. Max-Sharpe: 3.026. Portfolio: return=60.69%, vol=18.73%. Weights: w_XLK=0.8743, w_DOT-USD=0.0000, w_XHB=0.1257, w_IAU=0.0000.", "question": "Assets: XLK, DOT-USD, XHB, IAU\nAnnualized mean returns: XLK:0.6368, DOT-USD:-0.5159, XHB:0.3985, IAU:-0.1009\nCovariance matrix (annualized):\n[[0.039493, 0.015246, 0.019164, -0.008573], [0.015246, 0.173943, 0.020844, 0.011986], [0.019164, 0.020844, 0.043259, -0.006998], [-0.008573, 0.011986, -0.006998, 0.018469]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.8743, w_DOT-USD=0.0000, w_XHB=0.1257, w_IAU=0.0000", "answer_numeric": 3.0263446033299486, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.8743, w_DOT-USD=0.0000, w_XHB=0.1257, w_IAU=0.0000\nPortfolio annualized return: 60.69%, volatility: 18.73%\nSharpe ratio: (0.6069 - 0.0400) / 0.1873 = 3.0263", "metadata": {"weights": {"XLK": 0.8743, "DOT-USD": 0.0, "XHB": 0.1257, "IAU": 0.0}, "sharpe_ratio": 3.0263, "portfolio_return": 0.606863, "portfolio_vol": 0.18731, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230109_0648", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ADA-USD", "SGOV", "PDBC"], "decision_date": "2023-01-09", "context_summary": "4-asset optimization. Max-Sharpe: -0.416. Portfolio: return=-21.32%, vol=60.80%. Weights: w_IWM=0.0000, w_ADA-USD=0.9631, w_SGOV=0.0369, w_PDBC=0.0000.", "question": "Assets: IWM, ADA-USD, SGOV, PDBC\nAnnualized mean returns: IWM:-0.0223, ADA-USD:-0.2229, SGOV:0.0400, PDBC:-0.4194\nCovariance matrix (annualized):\n[[0.05313, 0.081838, -9.3e-05, 0.027433], [0.081838, 0.398579, -4.6e-05, 0.026354], [-9.3e-05, -4.6e-05, 8e-06, -0.000139], [0.027433, 0.026354, -0.000139, 0.04113]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_ADA-USD=0.9631, w_SGOV=0.0369, w_PDBC=0.0000", "answer_numeric": -0.41644317117984336, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_ADA-USD=0.9631, w_SGOV=0.0369, w_PDBC=0.0000\nPortfolio annualized return: -21.32%, volatility: 60.80%\nSharpe ratio: (-0.2132 - 0.0400) / 0.6080 = -0.4164", "metadata": {"weights": {"IWM": 0.0, "ADA-USD": 0.9631, "SGOV": 0.0369, "PDBC": 0.0}, "sharpe_ratio": -0.4164, "portfolio_return": -0.213218, "portfolio_vol": 0.608049, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230609_0650", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "AVAX-USD", "USO", "ICSH"], "decision_date": "2023-06-09", "context_summary": "4-asset optimization. Max-Sharpe: 1.735. Portfolio: return=7.02%, vol=1.74%. Weights: w_QUAL=0.1347, w_AVAX-USD=0.0000, w_USO=0.0000, w_ICSH=0.8653.", "question": "Assets: QUAL, AVAX-USD, USO, ICSH\nAnnualized mean returns: QUAL:0.2720, AVAX-USD:-0.9738, USO:-0.5393, ICSH:0.0388\nCovariance matrix (annualized):\n[[0.019918, 0.018594, 0.019058, -0.000413], [0.018594, 0.27246, 0.014333, -0.0001], [0.019058, 0.014333, 0.115151, -0.000907], [-0.000413, -0.0001, -0.000907, 5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.1347, w_AVAX-USD=0.0000, w_USO=0.0000, w_ICSH=0.8653", "answer_numeric": 1.7351475797991993, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.1347, w_AVAX-USD=0.0000, w_USO=0.0000, w_ICSH=0.8653\nPortfolio annualized return: 7.02%, volatility: 1.74%\nSharpe ratio: (0.0702 - 0.0400) / 0.0174 = 1.7351", "metadata": {"weights": {"QUAL": 0.1347, "AVAX-USD": 0.0, "USO": 0.0, "ICSH": 0.8653}, "sharpe_ratio": 1.7351, "portfolio_return": 0.070176, "portfolio_vol": 0.017391, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240906_0651", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNB-USD", "VNQI", "ICSH"], "decision_date": "2024-09-06", "context_summary": "4-asset optimization. Max-Sharpe: 7.837. Portfolio: return=7.52%, vol=0.45%. Weights: w_SPY=0.0000, w_BNB-USD=0.0037, w_VNQI=0.0079, w_ICSH=0.9885.", "question": "Assets: SPY, BNB-USD, VNQI, ICSH\nAnnualized mean returns: SPY:-0.0526, BNB-USD:0.7412, VNQI:0.5045, ICSH:0.0694\nCovariance matrix (annualized):\n[[0.029648, 0.038063, 0.017556, -0.000106], [0.038063, 0.230775, 0.015909, -0.000577], [0.017556, 0.015909, 0.022085, 3.5e-05], [-0.000106, -0.000577, 3.5e-05, 1.9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0000, w_BNB-USD=0.0037, w_VNQI=0.0079, w_ICSH=0.9885", "answer_numeric": 7.837452238079987, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0000, w_BNB-USD=0.0037, w_VNQI=0.0079, w_ICSH=0.9885\nPortfolio annualized return: 7.52%, volatility: 0.45%\nSharpe ratio: (0.0752 - 0.0400) / 0.0045 = 7.8375", "metadata": {"weights": {"SPY": 0.0, "BNB-USD": 0.0037, "VNQI": 0.0079, "ICSH": 0.9885}, "sharpe_ratio": 7.8375, "portfolio_return": 0.075246, "portfolio_vol": 0.004497, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230412_0652", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "MATIC-USD", "DBC", "IYR"], "decision_date": "2023-04-12", "context_summary": "4-asset optimization. Max-Sharpe: 0.654. Portfolio: return=14.50%, vol=16.06%. Weights: w_EFA=1.0000, w_MATIC-USD=0.0000, w_DBC=0.0000, w_IYR=0.0000.", "question": "Assets: EFA, MATIC-USD, DBC, IYR\nAnnualized mean returns: EFA:0.1450, MATIC-USD:-0.2348, DBC:-0.0099, IYR:-0.3852\nCovariance matrix (annualized):\n[[0.025783, 0.006016, 0.011962, 0.019064], [0.006016, 0.502232, -0.003288, -0.02386], [0.011962, -0.003288, 0.022275, 0.00295], [0.019064, -0.02386, 0.00295, 0.05173]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=1.0000, w_MATIC-USD=0.0000, w_DBC=0.0000, w_IYR=0.0000", "answer_numeric": 0.6537462669659339, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=1.0000, w_MATIC-USD=0.0000, w_DBC=0.0000, w_IYR=0.0000\nPortfolio annualized return: 14.50%, volatility: 16.06%\nSharpe ratio: (0.1450 - 0.0400) / 0.1606 = 0.6537", "metadata": {"weights": {"EFA": 1.0, "MATIC-USD": 0.0, "DBC": 0.0, "IYR": 0.0}, "sharpe_ratio": 0.6537, "portfolio_return": 0.144973, "portfolio_vol": 0.160572, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230831_0654", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "SLV", "BIL"], "decision_date": "2023-08-31", "context_summary": "4-asset optimization. Max-Sharpe: 4.908. Portfolio: return=5.18%, vol=0.24%. Weights: w_XLV=0.0084, w_LINK-USD=0.0000, w_SLV=0.0056, w_BIL=0.9860.", "question": "Assets: XLV, LINK-USD, SLV, BIL\nAnnualized mean returns: XLV:0.0937, LINK-USD:0.3767, SLV:0.4955, BIL:0.0489\nCovariance matrix (annualized):\n[[0.011246, 0.024383, -0.000821, -6.5e-05], [0.024383, 0.561699, 0.011991, 0.000424], [-0.000821, 0.011991, 0.063808, -0.000129], [-6.5e-05, 0.000424, -0.000129, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0084, w_LINK-USD=0.0000, w_SLV=0.0056, w_BIL=0.9860", "answer_numeric": 4.907929735505234, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0084, w_LINK-USD=0.0000, w_SLV=0.0056, w_BIL=0.9860\nPortfolio annualized return: 5.18%, volatility: 0.24%\nSharpe ratio: (0.0518 - 0.0400) / 0.0024 = 4.9079", "metadata": {"weights": {"XLV": 0.0084, "LINK-USD": 0.0, "SLV": 0.0056, "BIL": 0.986}, "sharpe_ratio": 4.9079, "portfolio_return": 0.051809, "portfolio_vol": 0.002406, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231212_0655", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "DBC", "SGOV"], "decision_date": "2023-12-12", "context_summary": "4-asset optimization. Max-Sharpe: 5.985. Portfolio: return=5.97%, vol=0.33%. Weights: w_XLI=0.0084, w_DOT-USD=0.0027, w_DBC=0.0000, w_SGOV=0.9889.", "question": "Assets: XLI, DOT-USD, DBC, SGOV\nAnnualized mean returns: XLI:0.4245, DOT-USD:1.7659, DBC:-0.3208, SGOV:0.0520\nCovariance matrix (annualized):\n[[0.020291, -0.007756, -0.005196, 6.1e-05], [-0.007756, 0.444626, -0.022227, -0.000168], [-0.005196, -0.022227, 0.031753, -7.1e-05], [6.1e-05, -0.000168, -7.1e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0084, w_DOT-USD=0.0027, w_DBC=0.0000, w_SGOV=0.9889", "answer_numeric": 5.98530948227782, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0084, w_DOT-USD=0.0027, w_DBC=0.0000, w_SGOV=0.9889\nPortfolio annualized return: 5.97%, volatility: 0.33%\nSharpe ratio: (0.0597 - 0.0400) / 0.0033 = 5.9853", "metadata": {"weights": {"XLI": 0.0084, "DOT-USD": 0.0027, "DBC": 0.0, "SGOV": 0.9889}, "sharpe_ratio": 5.9853, "portfolio_return": 0.059678, "portfolio_vol": 0.003288, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230222_0657", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "CSHI", "HAUZ"], "decision_date": "2023-02-22", "context_summary": "4-asset optimization. Max-Sharpe: 2.802. Portfolio: return=8.07%, vol=1.45%. Weights: w_IVV=0.0000, w_BNB-USD=0.0211, w_CSHI=0.9672, w_HAUZ=0.0117.", "question": "Assets: IVV, BNB-USD, CSHI, HAUZ\nAnnualized mean returns: IVV:0.2776, BNB-USD:0.9819, CSHI:0.0594, HAUZ:0.2169\nCovariance matrix (annualized):\n[[0.028698, 0.033037, 0.000573, 0.018735], [0.033037, 0.194289, 0.000583, 0.018192], [0.000573, 0.000583, 8.8e-05, 0.000247], [0.018735, 0.018192, 0.000247, 0.025172]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_BNB-USD=0.0211, w_CSHI=0.9672, w_HAUZ=0.0117", "answer_numeric": 2.802340186487596, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_BNB-USD=0.0211, w_CSHI=0.9672, w_HAUZ=0.0117\nPortfolio annualized return: 8.07%, volatility: 1.45%\nSharpe ratio: (0.0807 - 0.0400) / 0.0145 = 2.8023", "metadata": {"weights": {"IVV": 0.0, "BNB-USD": 0.0211, "CSHI": 0.9672, "HAUZ": 0.0117}, "sharpe_ratio": 2.8023, "portfolio_return": 0.080724, "portfolio_vol": 0.014532, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20241107_0659", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SOL-USD", "ICSH", "DBB"], "decision_date": "2024-11-07", "context_summary": "4-asset optimization. Max-Sharpe: 4.076. Portfolio: return=47.66%, vol=10.71%. Weights: w_VLUE=0.7265, w_SOL-USD=0.0149, w_ICSH=0.0908, w_DBB=0.1678.", "question": "Assets: VLUE, SOL-USD, ICSH, DBB\nAnnualized mean returns: VLUE:0.5161, SOL-USD:1.7428, ICSH:0.0386, DBB:0.4303\nCovariance matrix (annualized):\n[[0.015485, 0.049897, -9.1e-05, 0.00313], [0.049897, 0.353029, -0.000506, 0.019533], [-9.1e-05, -0.000506, 1.6e-05, 0.000207], [0.00313, 0.019533, 0.000207, 0.04574]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.7265, w_SOL-USD=0.0149, w_ICSH=0.0908, w_DBB=0.1678", "answer_numeric": 4.075913279606925, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.7265, w_SOL-USD=0.0149, w_ICSH=0.0908, w_DBB=0.1678\nPortfolio annualized return: 47.66%, volatility: 10.71%\nSharpe ratio: (0.4766 - 0.0400) / 0.1071 = 4.0759", "metadata": {"weights": {"VLUE": 0.7265, "SOL-USD": 0.0149, "ICSH": 0.0908, "DBB": 0.1678}, "sharpe_ratio": 4.0759, "portfolio_return": 0.476615, "portfolio_vol": 0.107121, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241213_0661", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "SOL-USD", "HAUZ", "SLV"], "decision_date": "2024-12-13", "context_summary": "4-asset optimization. Max-Sharpe: 5.537. Portfolio: return=103.52%, vol=17.97%. Weights: w_XLY=1.0000, w_SOL-USD=0.0000, w_HAUZ=0.0000, w_SLV=0.0000.", "question": "Assets: XLY, SOL-USD, HAUZ, SLV\nAnnualized mean returns: XLY:1.0352, SOL-USD:1.5963, HAUZ:-0.5202, SLV:-0.1429\nCovariance matrix (annualized):\n[[0.032303, 0.051533, 0.002294, -0.003026], [0.051533, 0.459901, 0.003805, -0.019762], [0.002294, 0.003805, 0.018993, 0.012622], [-0.003026, -0.019762, 0.012622, 0.089601]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=1.0000, w_SOL-USD=0.0000, w_HAUZ=0.0000, w_SLV=0.0000", "answer_numeric": 5.537195784024117, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=1.0000, w_SOL-USD=0.0000, w_HAUZ=0.0000, w_SLV=0.0000\nPortfolio annualized return: 103.52%, volatility: 17.97%\nSharpe ratio: (1.0352 - 0.0400) / 0.1797 = 5.5372", "metadata": {"weights": {"XLY": 1.0, "SOL-USD": 0.0, "HAUZ": 0.0, "SLV": 0.0}, "sharpe_ratio": 5.5372, "portfolio_return": 1.035204, "portfolio_vol": 0.179731, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230307_0662", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "JNK", "BIL"], "decision_date": "2023-03-07", "context_summary": "4-asset optimization. Max-Sharpe: 2.862. Portfolio: return=8.09%, vol=1.43%. Weights: w_EWJ=0.0826, w_ADA-USD=0.0062, w_JNK=0.0000, w_BIL=0.9112.", "question": "Assets: EWJ, ADA-USD, JNK, BIL\nAnnualized mean returns: EWJ:0.4493, ADA-USD:0.8832, JNK:0.1190, BIL:0.0420\nCovariance matrix (annualized):\n[[0.022686, 0.021158, 0.009438, 4.2e-05], [0.021158, 0.424099, 0.020686, -0.000179], [0.009438, 0.020686, 0.009774, 1.2e-05], [4.2e-05, -0.000179, 1.2e-05, 9e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0826, w_ADA-USD=0.0062, w_JNK=0.0000, w_BIL=0.9112", "answer_numeric": 2.8620890400423145, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0826, w_ADA-USD=0.0062, w_JNK=0.0000, w_BIL=0.9112\nPortfolio annualized return: 8.09%, volatility: 1.43%\nSharpe ratio: (0.0809 - 0.0400) / 0.0143 = 2.8621", "metadata": {"weights": {"EWJ": 0.0826, "ADA-USD": 0.0062, "JNK": 0.0, "BIL": 0.9112}, "sharpe_ratio": 2.8621, "portfolio_return": 0.080911, "portfolio_vol": 0.014294, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230201_0664", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ETH-USD", "BNO", "SGOV"], "decision_date": "2023-02-01", "context_summary": "4-asset optimization. Max-Sharpe: 1.311. Portfolio: return=5.60%, vol=1.22%. Weights: w_VTI=0.0000, w_ETH-USD=0.0263, w_BNO=0.0000, w_SGOV=0.9737.", "question": "Assets: VTI, ETH-USD, BNO, SGOV\nAnnualized mean returns: VTI:0.0450, ETH-USD:0.5867, BNO:0.0351, SGOV:0.0417\nCovariance matrix (annualized):\n[[0.035111, 0.049325, 0.027856, -0.000117], [0.049325, 0.205341, 0.056093, -1.2e-05], [0.027856, 0.056093, 0.127589, -0.00022], [-0.000117, -1.2e-05, -0.00022, 9e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_ETH-USD=0.0263, w_BNO=0.0000, w_SGOV=0.9737", "answer_numeric": 1.3112701446289186, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_ETH-USD=0.0263, w_BNO=0.0000, w_SGOV=0.9737\nPortfolio annualized return: 5.60%, volatility: 1.22%\nSharpe ratio: (0.0560 - 0.0400) / 0.0122 = 1.3113", "metadata": {"weights": {"VTI": 0.0, "ETH-USD": 0.0263, "BNO": 0.0, "SGOV": 0.9737}, "sharpe_ratio": 1.3113, "portfolio_return": 0.056039, "portfolio_vol": 0.012232, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230620_0666", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "DOT-USD", "WEAT", "ICSH"], "decision_date": "2023-06-20", "context_summary": "4-asset optimization. Max-Sharpe: 5.692. Portfolio: return=13.65%, vol=1.70%. Weights: w_QQQ=0.1028, w_DOT-USD=0.0000, w_WEAT=0.0000, w_ICSH=0.8972.", "question": "Assets: QQQ, DOT-USD, WEAT, ICSH\nAnnualized mean returns: QQQ:0.9530, DOT-USD:-1.3503, WEAT:0.0795, ICSH:0.0429\nCovariance matrix (annualized):\n[[0.029525, 0.009447, 0.004995, -0.000352], [0.009447, 0.122631, 0.019194, -6.7e-05], [0.004995, 0.019194, 0.108386, -0.00032], [-0.000352, -6.7e-05, -0.00032, 5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.1028, w_DOT-USD=0.0000, w_WEAT=0.0000, w_ICSH=0.8972", "answer_numeric": 5.691516835696922, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.1028, w_DOT-USD=0.0000, w_WEAT=0.0000, w_ICSH=0.8972\nPortfolio annualized return: 13.65%, volatility: 1.70%\nSharpe ratio: (0.1365 - 0.0400) / 0.0170 = 5.6915", "metadata": {"weights": {"QQQ": 0.1028, "DOT-USD": 0.0, "WEAT": 0.0, "ICSH": 0.8972}, "sharpe_ratio": 5.6915, "portfolio_return": 0.136505, "portfolio_vol": 0.016956, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240319_0668", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "SOYB", "XHB"], "decision_date": "2024-03-19", "context_summary": "4-asset optimization. Max-Sharpe: 6.390. Portfolio: return=159.42%, vol=24.32%. Weights: w_^VIX=0.0786, w_BTC-USD=0.4287, w_SOYB=0.0000, w_XHB=0.4927.", "question": "Assets: ^VIX, BTC-USD, SOYB, XHB\nAnnualized mean returns: ^VIX:0.0864, BTC-USD:2.9600, SOYB:-0.0975, XHB:0.6466\nCovariance matrix (annualized):\n[[0.541391, -0.004282, 0.007931, -0.079078], [-0.004282, 0.244388, 0.002383, 0.01366], [0.007931, 0.002383, 0.018947, -0.006405], [-0.079078, 0.01366, -0.006405, 0.047599]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0786, w_BTC-USD=0.4287, w_SOYB=0.0000, w_XHB=0.4927", "answer_numeric": 6.389587970187969, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0786, w_BTC-USD=0.4287, w_SOYB=0.0000, w_XHB=0.4927\nPortfolio annualized return: 159.42%, volatility: 24.32%\nSharpe ratio: (1.5942 - 0.0400) / 0.2432 = 6.3896", "metadata": {"weights": {"^VIX": 0.0786, "BTC-USD": 0.4287, "SOYB": 0.0, "XHB": 0.4927}, "sharpe_ratio": 6.3896, "portfolio_return": 1.594248, "portfolio_vol": 0.243247, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230623_0670", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "LINK-USD", "SCHP", "HAUZ"], "decision_date": "2023-06-23", "context_summary": "4-asset optimization. Max-Sharpe: -1.666. Portfolio: return=-156.95%, vol=96.59%. Weights: w_^VIX=1.0000, w_LINK-USD=0.0000, w_SCHP=0.0000, w_HAUZ=0.0000.", "question": "Assets: ^VIX, LINK-USD, SCHP, HAUZ\nAnnualized mean returns: ^VIX:-1.5695, LINK-USD:-0.0990, SCHP:-0.0645, HAUZ:-0.2110\nCovariance matrix (annualized):\n[[0.932913, -0.056685, 0.013018, -0.071441], [-0.056685, 0.167786, 0.00428, 0.008814], [0.013018, 0.00428, 0.003242, -0.00104], [-0.071441, 0.008814, -0.00104, 0.025204]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=1.0000, w_LINK-USD=0.0000, w_SCHP=0.0000, w_HAUZ=0.0000", "answer_numeric": -1.6664041795578466, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=1.0000, w_LINK-USD=0.0000, w_SCHP=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: -156.95%, volatility: 96.59%\nSharpe ratio: (-1.5695 - 0.0400) / 0.9659 = -1.6664", "metadata": {"weights": {"^VIX": 1.0, "LINK-USD": 0.0, "SCHP": 0.0, "HAUZ": 0.0}, "sharpe_ratio": -1.6664, "portfolio_return": -1.569536, "portfolio_vol": 0.965874, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230419_0671", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BNB-USD", "CPER", "XHB"], "decision_date": "2023-04-19", "context_summary": "4-asset optimization. Max-Sharpe: 0.979. Portfolio: return=19.72%, vol=16.07%. Weights: w_VEA=1.0000, w_BNB-USD=0.0000, w_CPER=0.0000, w_XHB=0.0000.", "question": "Assets: VEA, BNB-USD, CPER, XHB\nAnnualized mean returns: VEA:0.1972, BNB-USD:-0.1662, CPER:0.0209, XHB:0.0433\nCovariance matrix (annualized):\n[[0.025815, 0.003956, 0.014241, 0.024284], [0.003956, 0.145347, 0.007925, 0.012046], [0.014241, 0.007925, 0.047706, 0.00309], [0.024284, 0.012046, 0.00309, 0.052514]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=1.0000, w_BNB-USD=0.0000, w_CPER=0.0000, w_XHB=0.0000", "answer_numeric": 0.9785042764584352, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=1.0000, w_BNB-USD=0.0000, w_CPER=0.0000, w_XHB=0.0000\nPortfolio annualized return: 19.72%, volatility: 16.07%\nSharpe ratio: (0.1972 - 0.0400) / 0.1607 = 0.9785", "metadata": {"weights": {"VEA": 1.0, "BNB-USD": 0.0, "CPER": 0.0, "XHB": 0.0}, "sharpe_ratio": 0.9785, "portfolio_return": 0.197217, "portfolio_vol": 0.16067, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240924_0673", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "AVAX-USD", "SLV", "CSHI"], "decision_date": "2024-09-24", "context_summary": "4-asset optimization. Max-Sharpe: 2.303. Portfolio: return=63.29%, vol=25.75%. Weights: w_XLE=0.0000, w_AVAX-USD=0.1918, w_SLV=0.5328, w_CSHI=0.2754.", "question": "Assets: XLE, AVAX-USD, SLV, CSHI\nAnnualized mean returns: XLE:-0.1382, AVAX-USD:1.4236, SLV:0.6402, CSHI:0.0680\nCovariance matrix (annualized):\n[[0.04172, 0.058548, 0.030022, 0.001028], [0.058548, 0.572079, 0.079791, 0.008864], [0.030022, 0.079791, 0.095934, 0.002479], [0.001028, 0.008864, 0.002479, 0.000407]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_AVAX-USD=0.1918, w_SLV=0.5328, w_CSHI=0.2754", "answer_numeric": 2.3028970224187453, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_AVAX-USD=0.1918, w_SLV=0.5328, w_CSHI=0.2754\nPortfolio annualized return: 63.29%, volatility: 25.75%\nSharpe ratio: (0.6329 - 0.0400) / 0.2575 = 2.3029", "metadata": {"weights": {"XLE": 0.0, "AVAX-USD": 0.1918, "SLV": 0.5328, "CSHI": 0.2754}, "sharpe_ratio": 2.3029, "portfolio_return": 0.632904, "portfolio_vol": 0.25746, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240123_0674", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "MATIC-USD", "PALL", "SGOV"], "decision_date": "2024-01-23", "context_summary": "4-asset optimization. Max-Sharpe: -0.840. Portfolio: return=-15.29%, vol=22.97%. Weights: w_XLI=0.2500, w_MATIC-USD=0.2500, w_PALL=0.2500, w_SGOV=0.2500.", "question": "Assets: XLI, MATIC-USD, PALL, SGOV\nAnnualized mean returns: XLI:0.4619, MATIC-USD:-0.1748, PALL:-0.9539, SGOV:0.0553\nCovariance matrix (annualized):\n[[0.014195, 0.029601, 0.021942, 0.000113], [0.029601, 0.642572, -0.041226, 0.000337], [0.021942, -0.041226, 0.16537, 0.000255], [0.000113, 0.000337, 0.000255, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.2500, w_MATIC-USD=0.2500, w_PALL=0.2500, w_SGOV=0.2500", "answer_numeric": -0.8397543805617024, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.2500, w_MATIC-USD=0.2500, w_PALL=0.2500, w_SGOV=0.2500\nPortfolio annualized return: -15.29%, volatility: 22.97%\nSharpe ratio: (-0.1529 - 0.0400) / 0.2297 = -0.8398", "metadata": {"weights": {"XLI": 0.25, "MATIC-USD": 0.25, "PALL": 0.25, "SGOV": 0.25}, "sharpe_ratio": -0.8398, "portfolio_return": -0.152891, "portfolio_vol": 0.229699, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230406_0675", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "AVAX-USD", "BIL", "XHB"], "decision_date": "2023-04-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.130. Portfolio: return=4.57%, vol=0.27%. Weights: w_VTI=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_XHB=0.0000.", "question": "Assets: VTI, AVAX-USD, BIL, XHB\nAnnualized mean returns: VTI:-0.1312, AVAX-USD:-1.0294, BIL:0.0457, XHB:-0.5114\nCovariance matrix (annualized):\n[[0.028229, 0.034535, -6.3e-05, 0.032711], [0.034535, 0.582276, -0.00047, 0.009392], [-6.3e-05, -0.00047, 7e-06, -5.6e-05], [0.032711, 0.009392, -5.6e-05, 0.051496]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_XHB=0.0000", "answer_numeric": 2.1301807536960893, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_XHB=0.0000\nPortfolio annualized return: 4.57%, volatility: 0.27%\nSharpe ratio: (0.0457 - 0.0400) / 0.0027 = 2.1302", "metadata": {"weights": {"VTI": 0.0, "AVAX-USD": 0.0, "BIL": 1.0, "XHB": 0.0}, "sharpe_ratio": 2.1302, "portfolio_return": 0.045661, "portfolio_vol": 0.002658, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240621_0677", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BNB-USD", "BNDX", "HAUZ"], "decision_date": "2024-06-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.456. Portfolio: return=38.73%, vol=14.14%. Weights: w_XLY=1.0000, w_BNB-USD=0.0000, w_BNDX=0.0000, w_HAUZ=0.0000.", "question": "Assets: XLY, BNB-USD, BNDX, HAUZ\nAnnualized mean returns: XLY:0.3873, BNB-USD:-0.1188, BNDX:0.0595, HAUZ:0.0851\nCovariance matrix (annualized):\n[[0.019991, 0.012328, 0.001461, 0.012771], [0.012328, 0.228821, 0.006424, 0.021844], [0.001461, 0.006424, 0.001721, 0.00359], [0.012771, 0.021844, 0.00359, 0.025432]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=1.0000, w_BNB-USD=0.0000, w_BNDX=0.0000, w_HAUZ=0.0000", "answer_numeric": 2.456484626078424, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=1.0000, w_BNB-USD=0.0000, w_BNDX=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: 38.73%, volatility: 14.14%\nSharpe ratio: (0.3873 - 0.0400) / 0.1414 = 2.4565", "metadata": {"weights": {"XLY": 1.0, "BNB-USD": 0.0, "BNDX": 0.0, "HAUZ": 0.0}, "sharpe_ratio": 2.4565, "portfolio_return": 0.387319, "portfolio_vol": 0.141389, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240530_0678", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "SHV", "CSHI"], "decision_date": "2024-05-30", "context_summary": "4-asset optimization. Max-Sharpe: 3.308. Portfolio: return=4.79%, vol=0.24%. Weights: w_EEM=0.0000, w_BNB-USD=0.0000, w_SHV=0.7541, w_CSHI=0.2459.", "question": "Assets: EEM, BNB-USD, SHV, CSHI\nAnnualized mean returns: EEM:0.1784, BNB-USD:-0.1815, SHV:0.0455, CSHI:0.0554\nCovariance matrix (annualized):\n[[0.018964, 0.005142, 9.2e-05, 0.000199], [0.005142, 0.168157, 9.8e-05, 6e-06], [9.2e-05, 9.8e-05, 5e-06, 0.0], [0.000199, 6e-06, 0.0, 4.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_BNB-USD=0.0000, w_SHV=0.7541, w_CSHI=0.2459", "answer_numeric": 3.3078018151066275, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_BNB-USD=0.0000, w_SHV=0.7541, w_CSHI=0.2459\nPortfolio annualized return: 4.79%, volatility: 0.24%\nSharpe ratio: (0.0479 - 0.0400) / 0.0024 = 3.3078", "metadata": {"weights": {"EEM": 0.0, "BNB-USD": 0.0, "SHV": 0.7541, "CSHI": 0.2459}, "sharpe_ratio": 3.3078, "portfolio_return": 0.047935, "portfolio_vol": 0.002399, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230814_0679", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "PALL", "ITB"], "decision_date": "2023-08-14", "context_summary": "4-asset optimization. Max-Sharpe: 2.949. Portfolio: return=62.11%, vol=19.70%. Weights: w_XLU=0.0000, w_AVAX-USD=0.0718, w_PALL=0.0000, w_ITB=0.9282.", "question": "Assets: XLU, AVAX-USD, PALL, ITB\nAnnualized mean returns: XLU:-0.1085, AVAX-USD:0.5794, PALL:-0.3711, ITB:0.6243\nCovariance matrix (annualized):\n[[0.025315, 0.006114, 0.012838, 0.004198], [0.006114, 0.215517, -0.019244, 0.022159], [0.012838, -0.019244, 0.087756, 0.003784], [0.004198, 0.022159, 0.003784, 0.040343]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_AVAX-USD=0.0718, w_PALL=0.0000, w_ITB=0.9282", "answer_numeric": 2.948981426884568, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_AVAX-USD=0.0718, w_PALL=0.0000, w_ITB=0.9282\nPortfolio annualized return: 62.11%, volatility: 19.70%\nSharpe ratio: (0.6211 - 0.0400) / 0.1970 = 2.9490", "metadata": {"weights": {"XLU": 0.0, "AVAX-USD": 0.0718, "PALL": 0.0, "ITB": 0.9282}, "sharpe_ratio": 2.949, "portfolio_return": 0.621052, "portfolio_vol": 0.197035, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230824_0681", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "AVAX-USD", "SLV", "BIL"], "decision_date": "2023-08-24", "context_summary": "4-asset optimization. Max-Sharpe: -1.614. Portfolio: return=-20.63%, vol=15.26%. Weights: w_XLRE=0.2500, w_AVAX-USD=0.2500, w_SLV=0.2500, w_BIL=0.2500.", "question": "Assets: XLRE, AVAX-USD, SLV, BIL\nAnnualized mean returns: XLRE:0.1094, AVAX-USD:-1.4947, SLV:0.5097, BIL:0.0502\nCovariance matrix (annualized):\n[[0.019662, 0.013783, 0.012067, -9.2e-05], [0.013783, 0.20314, 0.017948, 0.00014], [0.012067, 0.017948, 0.062442, -8.6e-05], [-9.2e-05, 0.00014, -8.6e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.2500, w_AVAX-USD=0.2500, w_SLV=0.2500, w_BIL=0.2500", "answer_numeric": -1.6138956947230538, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.2500, w_AVAX-USD=0.2500, w_SLV=0.2500, w_BIL=0.2500\nPortfolio annualized return: -20.63%, volatility: 15.26%\nSharpe ratio: (-0.2063 - 0.0400) / 0.1526 = -1.6139", "metadata": {"weights": {"XLRE": 0.25, "AVAX-USD": 0.25, "SLV": 0.25, "BIL": 0.25}, "sharpe_ratio": -1.6139, "portfolio_return": -0.206341, "portfolio_vol": 0.152637, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230324_0682", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ADA-USD", "CPER", "ITB"], "decision_date": "2023-03-24", "context_summary": "4-asset optimization. Max-Sharpe: 0.679. Portfolio: return=21.67%, vol=26.04%. Weights: w_VTI=0.0000, w_ADA-USD=0.0000, w_CPER=0.0000, w_ITB=1.0000.", "question": "Assets: VTI, ADA-USD, CPER, ITB\nAnnualized mean returns: VTI:-0.0674, ADA-USD:-0.0492, CPER:-0.1984, ITB:0.2167\nCovariance matrix (annualized):\n[[0.031328, 0.040937, 0.000736, 0.038373], [0.040937, 0.456838, 0.017983, 0.034458], [0.000736, 0.017983, 0.050848, -0.003099], [0.038373, 0.034458, -0.003099, 0.067796]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_ADA-USD=0.0000, w_CPER=0.0000, w_ITB=1.0000", "answer_numeric": 0.678584298814757, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_ADA-USD=0.0000, w_CPER=0.0000, w_ITB=1.0000\nPortfolio annualized return: 21.67%, volatility: 26.04%\nSharpe ratio: (0.2167 - 0.0400) / 0.2604 = 0.6786", "metadata": {"weights": {"VTI": 0.0, "ADA-USD": 0.0, "CPER": 0.0, "ITB": 1.0}, "sharpe_ratio": 0.6786, "portfolio_return": 0.216687, "portfolio_vol": 0.260376, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240318_0683", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "ICSH", "VNQI"], "decision_date": "2024-03-18", "context_summary": "4-asset optimization. Max-Sharpe: 5.321. Portfolio: return=12.23%, vol=1.55%. Weights: w_ACWI=0.0800, w_ETH-USD=0.0222, w_ICSH=0.8978, w_VNQI=0.0000.", "question": "Assets: ACWI, ETH-USD, ICSH, VNQI\nAnnualized mean returns: ACWI:0.4757, ETH-USD:1.8459, ICSH:0.0482, VNQI:0.1445\nCovariance matrix (annualized):\n[[0.011627, 0.011521, 9e-05, 0.007927], [0.011521, 0.199064, -9.6e-05, 0.0131], [9e-05, -9.6e-05, 2.1e-05, 0.000196], [0.007927, 0.0131, 0.000196, 0.013898]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0800, w_ETH-USD=0.0222, w_ICSH=0.8978, w_VNQI=0.0000", "answer_numeric": 5.321175322987015, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0800, w_ETH-USD=0.0222, w_ICSH=0.8978, w_VNQI=0.0000\nPortfolio annualized return: 12.23%, volatility: 1.55%\nSharpe ratio: (0.1223 - 0.0400) / 0.0155 = 5.3212", "metadata": {"weights": {"ACWI": 0.08, "ETH-USD": 0.0222, "ICSH": 0.8978, "VNQI": 0.0}, "sharpe_ratio": 5.3212, "portfolio_return": 0.12232, "portfolio_vol": 0.01547, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240520_0684", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "XRP-USD", "INDS", "JNK"], "decision_date": "2024-05-20", "context_summary": "4-asset optimization. Max-Sharpe: -0.004. Portfolio: return=3.95%, vol=12.15%. Weights: w_XLB=1.0000, w_XRP-USD=0.0000, w_INDS=0.0000, w_JNK=0.0000.", "question": "Assets: XLB, XRP-USD, INDS, JNK\nAnnualized mean returns: XLB:0.0395, XRP-USD:-0.6759, INDS:-0.0445, JNK:0.0207\nCovariance matrix (annualized):\n[[0.014751, 0.018617, 0.014401, 0.003301], [0.018617, 0.217788, 0.031196, 0.008487], [0.014401, 0.031196, 0.039659, 0.008518], [0.003301, 0.008487, 0.008518, 0.002895]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=1.0000, w_XRP-USD=0.0000, w_INDS=0.0000, w_JNK=0.0000", "answer_numeric": -0.004279938346516536, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=1.0000, w_XRP-USD=0.0000, w_INDS=0.0000, w_JNK=0.0000\nPortfolio annualized return: 3.95%, volatility: 12.15%\nSharpe ratio: (0.0395 - 0.0400) / 0.1215 = -0.0043", "metadata": {"weights": {"XLB": 1.0, "XRP-USD": 0.0, "INDS": 0.0, "JNK": 0.0}, "sharpe_ratio": -0.0043, "portfolio_return": 0.03948, "portfolio_vol": 0.121453, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230111_0686", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "SCHP", "VNQ"], "decision_date": "2023-01-11", "context_summary": "4-asset optimization. Max-Sharpe: 0.987. Portfolio: return=28.06%, vol=24.37%. Weights: w_USMV=0.2319, w_XRP-USD=0.4986, w_SCHP=0.2695, w_VNQ=0.0000.", "question": "Assets: USMV, XRP-USD, SCHP, VNQ\nAnnualized mean returns: USMV:0.1107, XRP-USD:0.4832, SCHP:0.0519, VNQ:-0.0657\nCovariance matrix (annualized):\n[[0.02067, 0.021916, 0.006387, 0.025518], [0.021916, 0.209466, -0.000516, 0.027446], [0.006387, -0.000516, 0.006318, 0.008624], [0.025518, 0.027446, 0.008624, 0.049891]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.2319, w_XRP-USD=0.4986, w_SCHP=0.2695, w_VNQ=0.0000", "answer_numeric": 0.9872352991770992, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.2319, w_XRP-USD=0.4986, w_SCHP=0.2695, w_VNQ=0.0000\nPortfolio annualized return: 28.06%, volatility: 24.37%\nSharpe ratio: (0.2806 - 0.0400) / 0.2437 = 0.9872", "metadata": {"weights": {"USMV": 0.2319, "XRP-USD": 0.4986, "SCHP": 0.2695, "VNQ": 0.0}, "sharpe_ratio": 0.9872, "portfolio_return": 0.280562, "portfolio_vol": 0.243672, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241113_0688", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "IYR", "DBB"], "decision_date": "2024-11-13", "context_summary": "4-asset optimization. Max-Sharpe: 2.887. Portfolio: return=106.61%, vol=35.54%. Weights: w_FXI=0.5022, w_ETH-USD=0.4978, w_IYR=0.0000, w_DBB=0.0000.", "question": "Assets: FXI, ETH-USD, IYR, DBB\nAnnualized mean returns: FXI:0.7915, ETH-USD:1.3431, IYR:-0.2601, DBB:-0.0065\nCovariance matrix (annualized):\n[[0.177558, 0.006674, 0.006158, 0.084717], [0.006674, 0.315446, 0.002822, -0.010345], [0.006158, 0.002822, 0.023664, 0.007721], [0.084717, -0.010345, 0.007721, 0.052034]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.5022, w_ETH-USD=0.4978, w_IYR=0.0000, w_DBB=0.0000", "answer_numeric": 2.88745877828595, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.5022, w_ETH-USD=0.4978, w_IYR=0.0000, w_DBB=0.0000\nPortfolio annualized return: 106.61%, volatility: 35.54%\nSharpe ratio: (1.0661 - 0.0400) / 0.3554 = 2.8875", "metadata": {"weights": {"FXI": 0.5022, "ETH-USD": 0.4978, "IYR": 0.0, "DBB": 0.0}, "sharpe_ratio": 2.8875, "portfolio_return": 1.066115, "portfolio_vol": 0.35537, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240716_0689", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "MATIC-USD", "ICSH", "HAUZ"], "decision_date": "2024-07-16", "context_summary": "4-asset optimization. Max-Sharpe: -2.112. Portfolio: return=-31.00%, vol=16.57%. Weights: w_XLRE=0.2500, w_MATIC-USD=0.2500, w_ICSH=0.2500, w_HAUZ=0.2500.", "question": "Assets: XLRE, MATIC-USD, ICSH, HAUZ\nAnnualized mean returns: XLRE:0.2946, MATIC-USD:-1.5821, ICSH:0.0613, HAUZ:-0.0138\nCovariance matrix (annualized):\n[[0.01929, -0.001784, 0.000119, 0.01513], [-0.001784, 0.333866, 0.000725, 0.016101], [0.000119, 0.000725, 1.5e-05, 0.000224], [0.01513, 0.016101, 0.000224, 0.025135]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.2500, w_MATIC-USD=0.2500, w_ICSH=0.2500, w_HAUZ=0.2500", "answer_numeric": -2.1123012082834136, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.2500, w_MATIC-USD=0.2500, w_ICSH=0.2500, w_HAUZ=0.2500\nPortfolio annualized return: -31.00%, volatility: 16.57%\nSharpe ratio: (-0.3100 - 0.0400) / 0.1657 = -2.1123", "metadata": {"weights": {"XLRE": 0.25, "MATIC-USD": 0.25, "ICSH": 0.25, "HAUZ": 0.25}, "sharpe_ratio": -2.1123, "portfolio_return": -0.310022, "portfolio_vol": 0.165706, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241104_0691", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "HYG", "HAUZ"], "decision_date": "2024-11-04", "context_summary": "4-asset optimization. Max-Sharpe: 0.912. Portfolio: return=18.68%, vol=16.11%. Weights: w_IWM=1.0000, w_AVAX-USD=0.0000, w_HYG=0.0000, w_HAUZ=0.0000.", "question": "Assets: IWM, AVAX-USD, HYG, HAUZ\nAnnualized mean returns: IWM:0.1868, AVAX-USD:0.0607, HYG:0.0430, HAUZ:-0.1415\nCovariance matrix (annualized):\n[[0.025954, 0.058108, 0.003242, 0.013151], [0.058108, 0.347913, 0.009667, 0.043534], [0.003242, 0.009667, 0.00104, 0.002489], [0.013151, 0.043534, 0.002489, 0.019066]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=1.0000, w_AVAX-USD=0.0000, w_HYG=0.0000, w_HAUZ=0.0000", "answer_numeric": 0.9115363160196537, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=1.0000, w_AVAX-USD=0.0000, w_HYG=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: 18.68%, volatility: 16.11%\nSharpe ratio: (0.1868 - 0.0400) / 0.1611 = 0.9115", "metadata": {"weights": {"IWM": 1.0, "AVAX-USD": 0.0, "HYG": 0.0, "HAUZ": 0.0}, "sharpe_ratio": 0.9115, "portfolio_return": 0.186849, "portfolio_vol": 0.161101, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230524_0692", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BTC-USD", "ICSH", "GLD"], "decision_date": "2023-05-24", "context_summary": "4-asset optimization. Max-Sharpe: 1.226. Portfolio: return=5.43%, vol=1.17%. Weights: w_MTUM=0.0864, w_BTC-USD=0.0000, w_ICSH=0.9136, w_GLD=0.0000.", "question": "Assets: MTUM, BTC-USD, ICSH, GLD\nAnnualized mean returns: MTUM:0.1763, BTC-USD:0.0962, ICSH:0.0428, GLD:0.0016\nCovariance matrix (annualized):\n[[0.016242, 0.004373, -0.000118, -0.002136], [0.004373, 0.121687, 0.000384, 0.010152], [-0.000118, 0.000384, 4e-05, 0.000392], [-0.002136, 0.010152, 0.000392, 0.018414]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0864, w_BTC-USD=0.0000, w_ICSH=0.9136, w_GLD=0.0000", "answer_numeric": 1.2258671282985196, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0864, w_BTC-USD=0.0000, w_ICSH=0.9136, w_GLD=0.0000\nPortfolio annualized return: 5.43%, volatility: 1.17%\nSharpe ratio: (0.0543 - 0.0400) / 0.0117 = 1.2259", "metadata": {"weights": {"MTUM": 0.0864, "BTC-USD": 0.0, "ICSH": 0.9136, "GLD": 0.0}, "sharpe_ratio": 1.2259, "portfolio_return": 0.054296, "portfolio_vol": 0.011662, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240807_0693", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "LINK-USD", "ITB", "CSHI"], "decision_date": "2024-08-07", "context_summary": "4-asset optimization. Max-Sharpe: 1.615. Portfolio: return=29.56%, vol=15.83%. Weights: w_VLUE=0.0000, w_LINK-USD=0.0000, w_ITB=0.5284, w_CSHI=0.4716.", "question": "Assets: VLUE, LINK-USD, ITB, CSHI\nAnnualized mean returns: VLUE:-0.1705, LINK-USD:-2.5193, ITB:0.5211, CSHI:0.0431\nCovariance matrix (annualized):\n[[0.024914, 0.042995, 0.028895, 0.000871], [0.042995, 0.46203, 0.052583, 0.006003], [0.028895, 0.052583, 0.088916, 0.000376], [0.000871, 0.006003, 0.000376, 0.000214]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_LINK-USD=0.0000, w_ITB=0.5284, w_CSHI=0.4716", "answer_numeric": 1.6149438368618718, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_LINK-USD=0.0000, w_ITB=0.5284, w_CSHI=0.4716\nPortfolio annualized return: 29.56%, volatility: 15.83%\nSharpe ratio: (0.2956 - 0.0400) / 0.1583 = 1.6149", "metadata": {"weights": {"VLUE": 0.0, "LINK-USD": 0.0, "ITB": 0.5284, "CSHI": 0.4716}, "sharpe_ratio": 1.6149, "portfolio_return": 0.295643, "portfolio_vol": 0.158298, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241018_0695", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "TLH", "BIL"], "decision_date": "2024-10-18", "context_summary": "4-asset optimization. Max-Sharpe: 3.561. Portfolio: return=5.02%, vol=0.29%. Weights: w_^VIX=0.0004, w_ADA-USD=0.0028, w_TLH=0.0000, w_BIL=0.9967.", "question": "Assets: ^VIX, ADA-USD, TLH, BIL\nAnnualized mean returns: ^VIX:1.0745, ADA-USD:0.5335, TLH:-0.1045, BIL:0.0484\nCovariance matrix (annualized):\n[[1.506865, -0.213697, 0.027192, 0.000835], [-0.213697, 0.253579, -0.002129, -0.000238], [0.027192, -0.002129, 0.00834, 4.3e-05], [0.000835, -0.000238, 4.3e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0004, w_ADA-USD=0.0028, w_TLH=0.0000, w_BIL=0.9967", "answer_numeric": 3.561153251729994, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0004, w_ADA-USD=0.0028, w_TLH=0.0000, w_BIL=0.9967\nPortfolio annualized return: 5.02%, volatility: 0.29%\nSharpe ratio: (0.0502 - 0.0400) / 0.0029 = 3.5612", "metadata": {"weights": {"^VIX": 0.0004, "ADA-USD": 0.0028, "TLH": 0.0, "BIL": 0.9967}, "sharpe_ratio": 3.5612, "portfolio_return": 0.050224, "portfolio_vol": 0.002871, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240209_0696", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SOL-USD", "INDS", "PALL"], "decision_date": "2024-02-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.055. Portfolio: return=76.66%, vol=35.35%. Weights: w_^VIX=0.0330, w_SOL-USD=0.3588, w_INDS=0.6082, w_PALL=0.0000.", "question": "Assets: ^VIX, SOL-USD, INDS, PALL\nAnnualized mean returns: ^VIX:0.2152, SOL-USD:1.7355, INDS:0.2249, PALL:-0.5447\nCovariance matrix (annualized):\n[[0.387122, 0.095463, -0.027779, -0.03489], [0.095463, 0.774742, 0.017296, -0.014704], [-0.027779, 0.017296, 0.043598, 0.023178], [-0.03489, -0.014704, 0.023178, 0.163033]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0330, w_SOL-USD=0.3588, w_INDS=0.6082, w_PALL=0.0000", "answer_numeric": 2.055211184589858, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0330, w_SOL-USD=0.3588, w_INDS=0.6082, w_PALL=0.0000\nPortfolio annualized return: 76.66%, volatility: 35.35%\nSharpe ratio: (0.7666 - 0.0400) / 0.3535 = 2.0552", "metadata": {"weights": {"^VIX": 0.033, "SOL-USD": 0.3588, "INDS": 0.6082, "PALL": 0.0}, "sharpe_ratio": 2.0552, "portfolio_return": 0.766572, "portfolio_vol": 0.353527, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240705_0697", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "ITB", "DBB"], "decision_date": "2024-07-05", "context_summary": "4-asset optimization. Max-Sharpe: 0.454. Portfolio: return=12.71%, vol=19.19%. Weights: w_XLE=0.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_DBB=1.0000.", "question": "Assets: XLE, LINK-USD, ITB, DBB\nAnnualized mean returns: XLE:-0.0203, LINK-USD:-0.9224, ITB:-0.5166, DBB:0.1271\nCovariance matrix (annualized):\n[[0.02745, 0.020146, 0.011577, 0.007979], [0.020146, 0.391625, 0.023145, 0.032381], [0.011577, 0.023145, 0.059735, 0.010214], [0.007979, 0.032381, 0.010214, 0.036821]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_DBB=1.0000", "answer_numeric": 0.45385097714129274, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_DBB=1.0000\nPortfolio annualized return: 12.71%, volatility: 19.19%\nSharpe ratio: (0.1271 - 0.0400) / 0.1919 = 0.4539", "metadata": {"weights": {"XLE": 0.0, "LINK-USD": 0.0, "ITB": 0.0, "DBB": 1.0}, "sharpe_ratio": 0.4539, "portfolio_return": 0.127088, "portfolio_vol": 0.191888, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240405_0698", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "SLV", "IYR"], "decision_date": "2024-04-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.836. Portfolio: return=102.30%, vol=25.62%. Weights: w_XLP=0.0000, w_DOT-USD=0.0183, w_SLV=0.9817, w_IYR=0.0000.", "question": "Assets: XLP, DOT-USD, SLV, IYR\nAnnualized mean returns: XLP:0.0472, DOT-USD:0.7284, SLV:1.0285, IYR:0.0153\nCovariance matrix (annualized):\n[[0.007614, 0.00415, 0.001028, 0.006848], [0.00415, 0.47119, 0.038049, 0.017802], [0.001028, 0.038049, 0.066548, 0.012463], [0.006848, 0.017802, 0.012463, 0.027008]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_DOT-USD=0.0183, w_SLV=0.9817, w_IYR=0.0000", "answer_numeric": 3.8362624108671173, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_DOT-USD=0.0183, w_SLV=0.9817, w_IYR=0.0000\nPortfolio annualized return: 102.30%, volatility: 25.62%\nSharpe ratio: (1.0230 - 0.0400) / 0.2562 = 3.8363", "metadata": {"weights": {"XLP": 0.0, "DOT-USD": 0.0183, "SLV": 0.9817, "IYR": 0.0}, "sharpe_ratio": 3.8363, "portfolio_return": 1.023003, "portfolio_vol": 0.25624, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240719_0699", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "MATIC-USD", "BIL", "GLD"], "decision_date": "2024-07-19", "context_summary": "4-asset optimization. Max-Sharpe: -3.132. Portfolio: return=-44.86%, vol=15.60%. Weights: w_XLV=0.2500, w_MATIC-USD=0.2500, w_BIL=0.2500, w_GLD=0.2500.", "question": "Assets: XLV, MATIC-USD, BIL, GLD\nAnnualized mean returns: XLV:0.0580, MATIC-USD:-2.0503, BIL:0.0528, GLD:0.1451\nCovariance matrix (annualized):\n[[0.011935, 0.00668, -4e-06, 0.004862], [0.00668, 0.317839, 3e-05, 0.005049], [-4e-06, 3e-05, 5e-06, -0.00011], [0.004862, 0.005049, -0.00011, 0.02648]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.2500, w_MATIC-USD=0.2500, w_BIL=0.2500, w_GLD=0.2500", "answer_numeric": -3.1324046884498076, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.2500, w_MATIC-USD=0.2500, w_BIL=0.2500, w_GLD=0.2500\nPortfolio annualized return: -44.86%, volatility: 15.60%\nSharpe ratio: (-0.4486 - 0.0400) / 0.1560 = -3.1324", "metadata": {"weights": {"XLV": 0.25, "MATIC-USD": 0.25, "BIL": 0.25, "GLD": 0.25}, "sharpe_ratio": -3.1324, "portfolio_return": -0.448592, "portfolio_vol": 0.15598, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230105_0700", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "DOT-USD", "CSHI", "SHV"], "decision_date": "2023-01-05", "context_summary": "4-asset optimization. Max-Sharpe: 2.635. Portfolio: return=7.79%, vol=1.44%. Weights: w_EEM=0.0643, w_DOT-USD=0.0000, w_CSHI=0.0000, w_SHV=0.9357.", "question": "Assets: EEM, DOT-USD, CSHI, SHV\nAnnualized mean returns: EEM:0.5997, DOT-USD:-1.9650, CSHI:0.0429, SHV:0.0420\nCovariance matrix (annualized):\n[[0.046851, 0.060789, 0.00033, 4.4e-05], [0.060789, 0.483653, 0.000656, 0.000245], [0.00033, 0.000656, 4.4e-05, -3e-06], [4.4e-05, 0.000245, -3e-06, 9e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0643, w_DOT-USD=0.0000, w_CSHI=0.0000, w_SHV=0.9357", "answer_numeric": 2.6348715935457006, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0643, w_DOT-USD=0.0000, w_CSHI=0.0000, w_SHV=0.9357\nPortfolio annualized return: 7.79%, volatility: 1.44%\nSharpe ratio: (0.0779 - 0.0400) / 0.0144 = 2.6349", "metadata": {"weights": {"EEM": 0.0643, "DOT-USD": 0.0, "CSHI": 0.0, "SHV": 0.9357}, "sharpe_ratio": 2.6349, "portfolio_return": 0.077896, "portfolio_vol": 0.014383, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230628_0701", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "SGOV", "USO"], "decision_date": "2023-06-28", "context_summary": "4-asset optimization. Max-Sharpe: 4.218. Portfolio: return=5.26%, vol=0.30%. Weights: w_EFA=0.0000, w_BTC-USD=0.0022, w_SGOV=0.9978, w_USO=0.0000.", "question": "Assets: EFA, BTC-USD, SGOV, USO\nAnnualized mean returns: EFA:-0.0547, BTC-USD:0.4520, SGOV:0.0517, USO:-0.5411\nCovariance matrix (annualized):\n[[0.017845, 0.008515, 3.9e-05, 0.017789], [0.008515, 0.151504, -4.6e-05, 0.012518], [3.9e-05, -4.6e-05, 8e-06, -0.000106], [0.017789, 0.012518, -0.000106, 0.132634]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_BTC-USD=0.0022, w_SGOV=0.9978, w_USO=0.0000", "answer_numeric": 4.2178811741617634, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_BTC-USD=0.0022, w_SGOV=0.9978, w_USO=0.0000\nPortfolio annualized return: 5.26%, volatility: 0.30%\nSharpe ratio: (0.0526 - 0.0400) / 0.0030 = 4.2179", "metadata": {"weights": {"EFA": 0.0, "BTC-USD": 0.0022, "SGOV": 0.9978, "USO": 0.0}, "sharpe_ratio": 4.2179, "portfolio_return": 0.052624, "portfolio_vol": 0.002993, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230421_0703", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "UNG", "BIL"], "decision_date": "2023-04-21", "context_summary": "4-asset optimization. Max-Sharpe: -0.920. Portfolio: return=-19.97%, vol=26.05%. Weights: w_EWJ=0.2500, w_AVAX-USD=0.2500, w_UNG=0.2500, w_BIL=0.2500.", "question": "Assets: EWJ, AVAX-USD, UNG, BIL\nAnnualized mean returns: EWJ:0.1722, AVAX-USD:-0.9342, UNG:-0.0858, BIL:0.0489\nCovariance matrix (annualized):\n[[0.022325, 0.007726, 0.01979, -8e-06], [0.007726, 0.461561, 0.012062, -0.000284], [0.01979, 0.012062, 0.523683, -0.000144], [-8e-06, -0.000284, -0.000144, 9e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.2500, w_AVAX-USD=0.2500, w_UNG=0.2500, w_BIL=0.2500", "answer_numeric": -0.9202604254381068, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.2500, w_AVAX-USD=0.2500, w_UNG=0.2500, w_BIL=0.2500\nPortfolio annualized return: -19.97%, volatility: 26.05%\nSharpe ratio: (-0.1997 - 0.0400) / 0.2605 = -0.9203", "metadata": {"weights": {"EWJ": 0.25, "AVAX-USD": 0.25, "UNG": 0.25, "BIL": 0.25}, "sharpe_ratio": -0.9203, "portfolio_return": -0.199739, "portfolio_vol": 0.260512, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231009_0705", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "AVAX-USD", "ICSH", "ITB"], "decision_date": "2023-10-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.232. Portfolio: return=4.98%, vol=0.44%. Weights: w_ACWI=0.0000, w_AVAX-USD=0.0000, w_ICSH=1.0000, w_ITB=0.0000.", "question": "Assets: ACWI, AVAX-USD, ICSH, ITB\nAnnualized mean returns: ACWI:-0.2501, AVAX-USD:-0.7278, ICSH:0.0498, ITB:-0.8431\nCovariance matrix (annualized):\n[[0.013745, 0.022461, -5.4e-05, 0.019088], [0.022461, 0.199247, 2.7e-05, 0.043517], [-5.4e-05, 2.7e-05, 1.9e-05, -0.000169], [0.019088, 0.043517, -0.000169, 0.06572]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_AVAX-USD=0.0000, w_ICSH=1.0000, w_ITB=0.0000", "answer_numeric": 2.2323673684145704, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_AVAX-USD=0.0000, w_ICSH=1.0000, w_ITB=0.0000\nPortfolio annualized return: 4.98%, volatility: 0.44%\nSharpe ratio: (0.0498 - 0.0400) / 0.0044 = 2.2324", "metadata": {"weights": {"ACWI": 0.0, "AVAX-USD": 0.0, "ICSH": 1.0, "ITB": 0.0}, "sharpe_ratio": 2.2324, "portfolio_return": 0.049767, "portfolio_vol": 0.004375, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231117_0706", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "SGOV", "ITB"], "decision_date": "2023-11-17", "context_summary": "4-asset optimization. Max-Sharpe: 6.845. Portfolio: return=5.97%, vol=0.29%. Weights: w_FXI=0.0000, w_LINK-USD=0.0031, w_SGOV=0.9957, w_ITB=0.0012.", "question": "Assets: FXI, LINK-USD, SGOV, ITB\nAnnualized mean returns: FXI:-0.2322, LINK-USD:2.5217, SGOV:0.0518, ITB:0.2944\nCovariance matrix (annualized):\n[[0.066841, 0.018625, -0.000128, 0.033218], [0.018625, 0.52183, -0.000589, 0.018529], [-0.000128, -0.000589, 7e-06, -5.2e-05], [0.033218, 0.018529, -5.2e-05, 0.081641]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_LINK-USD=0.0031, w_SGOV=0.9957, w_ITB=0.0012", "answer_numeric": 6.8453324168806144, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_LINK-USD=0.0031, w_SGOV=0.9957, w_ITB=0.0012\nPortfolio annualized return: 5.97%, volatility: 0.29%\nSharpe ratio: (0.0597 - 0.0400) / 0.0029 = 6.8453", "metadata": {"weights": {"FXI": 0.0, "LINK-USD": 0.0031, "SGOV": 0.9957, "ITB": 0.0012}, "sharpe_ratio": 6.8453, "portfolio_return": 0.059736, "portfolio_vol": 0.002883, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230404_0707", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "TLT", "CPER"], "decision_date": "2023-04-04", "context_summary": "4-asset optimization. Max-Sharpe: 0.531. Portfolio: return=33.59%, vol=55.71%. Weights: w_XLU=0.0000, w_BTC-USD=1.0000, w_TLT=0.0000, w_CPER=0.0000.", "question": "Assets: XLU, BTC-USD, TLT, CPER\nAnnualized mean returns: XLU:-0.1693, BTC-USD:0.3359, TLT:-0.1143, CPER:0.0113\nCovariance matrix (annualized):\n[[0.042468, 0.015332, 0.001338, -0.01211], [0.015332, 0.310341, -0.00102, 0.009915], [0.001338, -0.00102, 0.033041, -0.007284], [-0.01211, 0.009915, -0.007284, 0.048272]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_BTC-USD=1.0000, w_TLT=0.0000, w_CPER=0.0000", "answer_numeric": 0.5311243186947652, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_BTC-USD=1.0000, w_TLT=0.0000, w_CPER=0.0000\nPortfolio annualized return: 33.59%, volatility: 55.71%\nSharpe ratio: (0.3359 - 0.0400) / 0.5571 = 0.5311", "metadata": {"weights": {"XLU": 0.0, "BTC-USD": 1.0, "TLT": 0.0, "CPER": 0.0}, "sharpe_ratio": 0.5311, "portfolio_return": 0.33588, "portfolio_vol": 0.557083, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230607_0709", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SOL-USD", "ICSH", "PPLT"], "decision_date": "2023-06-07", "context_summary": "4-asset optimization. Max-Sharpe: 0.521. Portfolio: return=16.37%, vol=23.73%. Weights: w_FXI=0.0000, w_SOL-USD=0.0803, w_ICSH=0.0000, w_PPLT=0.9197.", "question": "Assets: FXI, SOL-USD, ICSH, PPLT\nAnnualized mean returns: FXI:-0.2790, SOL-USD:0.0870, ICSH:0.0382, PPLT:0.1704\nCovariance matrix (annualized):\n[[0.087632, -0.007376, -0.000445, 0.012707], [-0.007376, 0.341919, 0.000157, -0.00661], [-0.000445, 0.000157, 5.2e-05, 0.000229], [0.012707, -0.00661, 0.000229, 0.065106]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_SOL-USD=0.0803, w_ICSH=0.0000, w_PPLT=0.9197", "answer_numeric": 0.5213139214585015, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_SOL-USD=0.0803, w_ICSH=0.0000, w_PPLT=0.9197\nPortfolio annualized return: 16.37%, volatility: 23.73%\nSharpe ratio: (0.1637 - 0.0400) / 0.2373 = 0.5213", "metadata": {"weights": {"FXI": 0.0, "SOL-USD": 0.0803, "ICSH": 0.0, "PPLT": 0.9197}, "sharpe_ratio": 0.5213, "portfolio_return": 0.163696, "portfolio_vol": 0.237277, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230707_0710", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "AVAX-USD", "ICSH", "MORT"], "decision_date": "2023-07-07", "context_summary": "4-asset optimization. Max-Sharpe: 2.358. Portfolio: return=60.74%, vol=24.06%. Weights: w_XLB=0.0000, w_AVAX-USD=0.0000, w_ICSH=0.0000, w_MORT=1.0000.", "question": "Assets: XLB, AVAX-USD, ICSH, MORT\nAnnualized mean returns: XLB:0.0958, AVAX-USD:-0.4983, ICSH:0.0362, MORT:0.6074\nCovariance matrix (annualized):\n[[0.030918, 0.024772, -0.000252, 0.028488], [0.024772, 0.243117, 0.00031, 0.028603], [-0.000252, 0.00031, 4.4e-05, -0.0], [0.028488, 0.028603, -0.0, 0.057892]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_AVAX-USD=0.0000, w_ICSH=0.0000, w_MORT=1.0000", "answer_numeric": 2.3581176638879158, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_AVAX-USD=0.0000, w_ICSH=0.0000, w_MORT=1.0000\nPortfolio annualized return: 60.74%, volatility: 24.06%\nSharpe ratio: (0.6074 - 0.0400) / 0.2406 = 2.3581", "metadata": {"weights": {"XLB": 0.0, "AVAX-USD": 0.0, "ICSH": 0.0, "MORT": 1.0}, "sharpe_ratio": 2.3581, "portfolio_return": 0.607382, "portfolio_vol": 0.240608, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240507_0712", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "SLV", "EMB"], "decision_date": "2024-05-07", "context_summary": "4-asset optimization. Max-Sharpe: 2.589. Portfolio: return=80.03%, vol=29.37%. Weights: w_XLY=0.0000, w_LINK-USD=0.0000, w_SLV=1.0000, w_EMB=0.0000.", "question": "Assets: XLY, LINK-USD, SLV, EMB\nAnnualized mean returns: XLY:-0.0265, LINK-USD:-2.2379, SLV:0.8003, EMB:0.0365\nCovariance matrix (annualized):\n[[0.026856, 0.034647, 0.003245, 0.007849], [0.034647, 0.389665, 0.016028, 0.013923], [0.003245, 0.016028, 0.08626, 0.001416], [0.007849, 0.013923, 0.001416, 0.006824]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_LINK-USD=0.0000, w_SLV=1.0000, w_EMB=0.0000", "answer_numeric": 2.58852936914645, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_LINK-USD=0.0000, w_SLV=1.0000, w_EMB=0.0000\nPortfolio annualized return: 80.03%, volatility: 29.37%\nSharpe ratio: (0.8003 - 0.0400) / 0.2937 = 2.5885", "metadata": {"weights": {"XLY": 0.0, "LINK-USD": 0.0, "SLV": 1.0, "EMB": 0.0}, "sharpe_ratio": 2.5885, "portfolio_return": 0.800253, "portfolio_vol": 0.293701, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241030_0714", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "CPER", "IYR"], "decision_date": "2024-10-30", "context_summary": "4-asset optimization. Max-Sharpe: 1.949. Portfolio: return=30.66%, vol=13.68%. Weights: w_XLU=0.6672, w_LINK-USD=0.0913, w_CPER=0.2414, w_IYR=0.0000.", "question": "Assets: XLU, LINK-USD, CPER, IYR\nAnnualized mean returns: XLU:0.2778, LINK-USD:0.6347, CPER:0.2622, IYR:0.0500\nCovariance matrix (annualized):\n[[0.025088, 0.003974, -0.001734, 0.011172], [0.003974, 0.302645, 0.047316, 0.012109], [-0.001734, 0.047316, 0.051453, -0.001138], [0.011172, 0.012109, -0.001138, 0.015088]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.6672, w_LINK-USD=0.0913, w_CPER=0.2414, w_IYR=0.0000", "answer_numeric": 1.949485271616029, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.6672, w_LINK-USD=0.0913, w_CPER=0.2414, w_IYR=0.0000\nPortfolio annualized return: 30.66%, volatility: 13.68%\nSharpe ratio: (0.3066 - 0.0400) / 0.1368 = 1.9495", "metadata": {"weights": {"XLU": 0.6672, "LINK-USD": 0.0913, "CPER": 0.2414, "IYR": 0.0}, "sharpe_ratio": 1.9495, "portfolio_return": 0.306632, "portfolio_vol": 0.136771, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20230322_0715", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SOL-USD", "XHB", "BIL"], "decision_date": "2023-03-22", "context_summary": "4-asset optimization. Max-Sharpe: -2.330. Portfolio: return=-50.01%, vol=23.18%. Weights: w_EFA=0.2500, w_SOL-USD=0.2500, w_XHB=0.2500, w_BIL=0.2500.", "question": "Assets: EFA, SOL-USD, XHB, BIL\nAnnualized mean returns: EFA:-0.1376, SOL-USD:-2.0565, XHB:0.1481, BIL:0.0457\nCovariance matrix (annualized):\n[[0.025065, 0.029383, 0.028067, -5.2e-05], [0.029383, 0.601283, 0.028611, -0.000449], [0.028067, 0.028611, 0.062077, 3.2e-05], [-5.2e-05, -0.000449, 3.2e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.2500, w_SOL-USD=0.2500, w_XHB=0.2500, w_BIL=0.2500", "answer_numeric": -2.3300841693403624, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.2500, w_SOL-USD=0.2500, w_XHB=0.2500, w_BIL=0.2500\nPortfolio annualized return: -50.01%, volatility: 23.18%\nSharpe ratio: (-0.5001 - 0.0400) / 0.2318 = -2.3301", "metadata": {"weights": {"EFA": 0.25, "SOL-USD": 0.25, "XHB": 0.25, "BIL": 0.25}, "sharpe_ratio": -2.3301, "portfolio_return": -0.500087, "portfolio_vol": 0.231788, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231228_0716", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "SOL-USD", "BIL", "ITB"], "decision_date": "2023-12-28", "context_summary": "4-asset optimization. Max-Sharpe: 9.845. Portfolio: return=9.25%, vol=0.53%. Weights: w_XLY=0.0124, w_SOL-USD=0.0010, w_BIL=0.9761, w_ITB=0.0105.", "question": "Assets: XLY, SOL-USD, BIL, ITB\nAnnualized mean returns: XLY:1.1777, SOL-USD:6.0071, BIL:0.0516, ITB:2.0580\nCovariance matrix (annualized):\n[[0.023814, 0.040106, -3.2e-05, 0.029829], [0.040106, 1.420277, 0.000557, 0.072659], [-3.2e-05, 0.000557, 6e-06, -1.9e-05], [0.029829, 0.072659, -1.9e-05, 0.063969]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0124, w_SOL-USD=0.0010, w_BIL=0.9761, w_ITB=0.0105", "answer_numeric": 9.844770053234305, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0124, w_SOL-USD=0.0010, w_BIL=0.9761, w_ITB=0.0105\nPortfolio annualized return: 9.25%, volatility: 0.53%\nSharpe ratio: (0.0925 - 0.0400) / 0.0053 = 9.8448", "metadata": {"weights": {"XLY": 0.0124, "SOL-USD": 0.001, "BIL": 0.9761, "ITB": 0.0105}, "sharpe_ratio": 9.8448, "portfolio_return": 0.092539, "portfolio_vol": 0.005337, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231227_0717", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BTC-USD", "TLT", "SLV"], "decision_date": "2023-12-27", "context_summary": "4-asset optimization. Max-Sharpe: 10.261. Portfolio: return=101.08%, vol=9.46%. Weights: w_MTUM=0.6126, w_BTC-USD=0.1360, w_TLT=0.2241, w_SLV=0.0272.", "question": "Assets: MTUM, BTC-USD, TLT, SLV\nAnnualized mean returns: MTUM:0.9574, BTC-USD:1.3043, TLT:1.0613, SLV:0.3290\nCovariance matrix (annualized):\n[[0.016299, -0.016681, 0.003138, 0.001445], [-0.016681, 0.175353, -0.006751, -0.017133], [0.003138, -0.006751, 0.036296, 0.010213], [0.001445, -0.017133, 0.010213, 0.066852]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.6126, w_BTC-USD=0.1360, w_TLT=0.2241, w_SLV=0.0272", "answer_numeric": 10.261499130709119, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.6126, w_BTC-USD=0.1360, w_TLT=0.2241, w_SLV=0.0272\nPortfolio annualized return: 101.08%, volatility: 9.46%\nSharpe ratio: (1.0108 - 0.0400) / 0.0946 = 10.2615", "metadata": {"weights": {"MTUM": 0.6126, "BTC-USD": 0.136, "TLT": 0.2241, "SLV": 0.0272}, "sharpe_ratio": 10.2615, "portfolio_return": 1.010793, "portfolio_vol": 0.094605, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240102_0718", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "DOT-USD", "PALL", "VNQI"], "decision_date": "2024-01-02", "context_summary": "4-asset optimization. Max-Sharpe: 5.070. Portfolio: return=62.43%, vol=11.52%. Weights: w_XLV=0.5690, w_DOT-USD=0.0283, w_PALL=0.0000, w_VNQI=0.4027.", "question": "Assets: XLV, DOT-USD, PALL, VNQI\nAnnualized mean returns: XLV:0.5005, DOT-USD:1.7897, PALL:-0.2708, VNQI:0.7173\nCovariance matrix (annualized):\n[[0.012051, 0.018779, 0.012123, 0.007647], [0.018779, 0.75239, -0.052408, 0.01939], [0.012123, -0.052408, 0.184705, 0.031163], [0.007647, 0.01939, 0.031163, 0.026064]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.5690, w_DOT-USD=0.0283, w_PALL=0.0000, w_VNQI=0.4027", "answer_numeric": 5.069703111103416, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.5690, w_DOT-USD=0.0283, w_PALL=0.0000, w_VNQI=0.4027\nPortfolio annualized return: 62.43%, volatility: 11.52%\nSharpe ratio: (0.6243 - 0.0400) / 0.1152 = 5.0697", "metadata": {"weights": {"XLV": 0.569, "DOT-USD": 0.0283, "PALL": 0.0, "VNQI": 0.4027}, "sharpe_ratio": 5.0697, "portfolio_return": 0.624254, "portfolio_vol": 0.115244, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240314_0720", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "LINK-USD", "SCHH", "SHV"], "decision_date": "2024-03-14", "context_summary": "4-asset optimization. Max-Sharpe: 2.563. Portfolio: return=6.09%, vol=0.82%. Weights: w_VEA=0.0511, w_LINK-USD=0.0029, w_SCHH=0.0000, w_SHV=0.9460.", "question": "Assets: VEA, LINK-USD, SCHH, SHV\nAnnualized mean returns: VEA:0.3197, LINK-USD:0.4928, SCHH:-0.0469, SHV:0.0456\nCovariance matrix (annualized):\n[[0.013435, 0.00647, 0.010368, 0.000195], [0.00647, 0.384926, 0.010496, -9e-06], [0.010368, 0.010496, 0.027179, 0.000301], [0.000195, -9e-06, 0.000301, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0511, w_LINK-USD=0.0029, w_SCHH=0.0000, w_SHV=0.9460", "answer_numeric": 2.5628316090808427, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0511, w_LINK-USD=0.0029, w_SCHH=0.0000, w_SHV=0.9460\nPortfolio annualized return: 6.09%, volatility: 0.82%\nSharpe ratio: (0.0609 - 0.0400) / 0.0082 = 2.5628", "metadata": {"weights": {"VEA": 0.0511, "LINK-USD": 0.0029, "SCHH": 0.0, "SHV": 0.946}, "sharpe_ratio": 2.5628, "portfolio_return": 0.06089, "portfolio_vol": 0.008151, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240126_0722", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "XRP-USD", "USO", "BNDX"], "decision_date": "2024-01-26", "context_summary": "4-asset optimization. Max-Sharpe: 2.596. Portfolio: return=18.11%, vol=5.43%. Weights: w_FXI=0.0000, w_XRP-USD=0.0000, w_USO=0.0151, w_BNDX=0.9849.", "question": "Assets: FXI, XRP-USD, USO, BNDX\nAnnualized mean returns: FXI:-0.7491, XRP-USD:-1.0670, USO:0.1672, BNDX:0.1813\nCovariance matrix (annualized):\n[[0.085991, -0.016309, 0.009207, -7.9e-05], [-0.016309, 0.173684, -0.050082, 0.000622], [0.009207, -0.050082, 0.093842, 0.001266], [-7.9e-05, 0.000622, 0.001266, 0.002982]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_XRP-USD=0.0000, w_USO=0.0151, w_BNDX=0.9849", "answer_numeric": 2.596420397073732, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_XRP-USD=0.0000, w_USO=0.0151, w_BNDX=0.9849\nPortfolio annualized return: 18.11%, volatility: 5.43%\nSharpe ratio: (0.1811 - 0.0400) / 0.0543 = 2.5964", "metadata": {"weights": {"FXI": 0.0, "XRP-USD": 0.0, "USO": 0.0151, "BNDX": 0.9849}, "sharpe_ratio": 2.5964, "portfolio_return": 0.181055, "portfolio_vol": 0.054327, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230118_0724", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "CSHI", "VNQ"], "decision_date": "2023-01-18", "context_summary": "4-asset optimization. Max-Sharpe: 2.184. Portfolio: return=7.51%, vol=1.61%. Weights: w_XLF=0.0000, w_SOL-USD=0.0127, w_CSHI=0.9732, w_VNQ=0.0140.", "question": "Assets: XLF, SOL-USD, CSHI, VNQ\nAnnualized mean returns: XLF:0.1364, SOL-USD:1.7974, CSHI:0.0491, VNQ:0.3188\nCovariance matrix (annualized):\n[[0.026931, 0.03615, 0.000595, 0.029549], [0.03615, 0.952028, 2.6e-05, 0.055591], [0.000595, 2.6e-05, 5.9e-05, 0.000626], [0.029549, 0.055591, 0.000626, 0.05248]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_SOL-USD=0.0127, w_CSHI=0.9732, w_VNQ=0.0140", "answer_numeric": 2.18396189103095, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_SOL-USD=0.0127, w_CSHI=0.9732, w_VNQ=0.0140\nPortfolio annualized return: 7.51%, volatility: 1.61%\nSharpe ratio: (0.0751 - 0.0400) / 0.0161 = 2.1840", "metadata": {"weights": {"XLF": 0.0, "SOL-USD": 0.0127, "CSHI": 0.9732, "VNQ": 0.014}, "sharpe_ratio": 2.184, "portfolio_return": 0.075124, "portfolio_vol": 0.016083, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230119_0725", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "BIL", "DBB"], "decision_date": "2023-01-19", "context_summary": "4-asset optimization. Max-Sharpe: 2.928. Portfolio: return=62.67%, vol=20.04%. Weights: w_XLP=0.0000, w_DOT-USD=0.0000, w_BIL=0.0000, w_DBB=1.0000.", "question": "Assets: XLP, DOT-USD, BIL, DBB\nAnnualized mean returns: XLP:-0.1398, DOT-USD:-0.2729, BIL:0.0382, DBB:0.6267\nCovariance matrix (annualized):\n[[0.020454, 0.022362, -0.000108, 0.009738], [0.022362, 0.240995, 0.000273, 0.045209], [-0.000108, 0.000273, 1.1e-05, -6.7e-05], [0.009738, 0.045209, -6.7e-05, 0.040157]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_DOT-USD=0.0000, w_BIL=0.0000, w_DBB=1.0000", "answer_numeric": 2.928002819929775, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_DOT-USD=0.0000, w_BIL=0.0000, w_DBB=1.0000\nPortfolio annualized return: 62.67%, volatility: 20.04%\nSharpe ratio: (0.6267 - 0.0400) / 0.2004 = 2.9280", "metadata": {"weights": {"XLP": 0.0, "DOT-USD": 0.0, "BIL": 0.0, "DBB": 1.0}, "sharpe_ratio": 2.928, "portfolio_return": 0.626746, "portfolio_vol": 0.200391, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241121_0726", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "TIP", "ICSH"], "decision_date": "2024-11-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.895. Portfolio: return=100.00%, vol=33.17%. Weights: w_USMV=0.5442, w_XRP-USD=0.4558, w_TIP=0.0000, w_ICSH=0.0000.", "question": "Assets: USMV, XRP-USD, TIP, ICSH\nAnnualized mean returns: USMV:0.0697, XRP-USD:2.1108, TIP:-0.0142, ICSH:0.0340\nCovariance matrix (annualized):\n[[0.008893, -0.003154, 0.000208, -8.1e-05], [-0.003154, 0.524312, 0.000403, -0.000183], [0.000208, 0.000403, 0.000368, 3.1e-05], [-8.1e-05, -0.000183, 3.1e-05, 1.8e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.5442, w_XRP-USD=0.4558, w_TIP=0.0000, w_ICSH=0.0000", "answer_numeric": 2.894593042751866, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.5442, w_XRP-USD=0.4558, w_TIP=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 100.00%, volatility: 33.17%\nSharpe ratio: (1.0000 - 0.0400) / 0.3317 = 2.8946", "metadata": {"weights": {"USMV": 0.5442, "XRP-USD": 0.4558, "TIP": 0.0, "ICSH": 0.0}, "sharpe_ratio": 2.8946, "portfolio_return": 1.000014, "portfolio_vol": 0.331658, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240429_0728", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "DOT-USD", "GLD", "BIL"], "decision_date": "2024-04-29", "context_summary": "4-asset optimization. Max-Sharpe: -1.067. Portfolio: return=-19.25%, vol=21.79%. Weights: w_EFA=0.2500, w_DOT-USD=0.2500, w_GLD=0.2500, w_BIL=0.2500.", "question": "Assets: EFA, DOT-USD, GLD, BIL\nAnnualized mean returns: EFA:0.0722, DOT-USD:-1.7710, GLD:0.8767, BIL:0.0523\nCovariance matrix (annualized):\n[[0.011506, 0.032009, 0.002317, 6e-06], [0.032009, 0.606405, 0.025496, 6.3e-05], [0.002317, 0.025496, 0.022066, -4e-06], [6e-06, 6.3e-05, -4e-06, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.2500, w_DOT-USD=0.2500, w_GLD=0.2500, w_BIL=0.2500", "answer_numeric": -1.0667776834536589, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.2500, w_DOT-USD=0.2500, w_GLD=0.2500, w_BIL=0.2500\nPortfolio annualized return: -19.25%, volatility: 21.79%\nSharpe ratio: (-0.1925 - 0.0400) / 0.2179 = -1.0668", "metadata": {"weights": {"EFA": 0.25, "DOT-USD": 0.25, "GLD": 0.25, "BIL": 0.25}, "sharpe_ratio": -1.0668, "portfolio_return": -0.192462, "portfolio_vol": 0.21791, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231226_0730", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "INDS", "TLH"], "decision_date": "2023-12-26", "context_summary": "4-asset optimization. Max-Sharpe: 8.248. Portfolio: return=106.61%, vol=12.44%. Weights: w_USMV=0.3627, w_ADA-USD=0.0698, w_INDS=0.1897, w_TLH=0.3777.", "question": "Assets: USMV, ADA-USD, INDS, TLH\nAnnualized mean returns: USMV:0.5430, ADA-USD:4.0000, INDS:1.4835, TLH:0.8166\nCovariance matrix (annualized):\n[[0.010465, 0.015544, 0.011276, 0.001503], [0.015544, 0.732192, 0.026769, -0.00554], [0.011276, 0.026769, 0.04816, 0.01768], [0.001503, -0.00554, 0.01768, 0.021712]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.3627, w_ADA-USD=0.0698, w_INDS=0.1897, w_TLH=0.3777", "answer_numeric": 8.247768976123512, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.3627, w_ADA-USD=0.0698, w_INDS=0.1897, w_TLH=0.3777\nPortfolio annualized return: 106.61%, volatility: 12.44%\nSharpe ratio: (1.0661 - 0.0400) / 0.1244 = 8.2478", "metadata": {"weights": {"USMV": 0.3627, "ADA-USD": 0.0698, "INDS": 0.1897, "TLH": 0.3777}, "sharpe_ratio": 8.2478, "portfolio_return": 1.066118, "portfolio_vol": 0.124412, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240927_0732", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "LINK-USD", "SOYB", "SHV"], "decision_date": "2024-09-27", "context_summary": "4-asset optimization. Max-Sharpe: 6.266. Portfolio: return=5.53%, vol=0.24%. Weights: w_VTI=0.0064, w_LINK-USD=0.0000, w_SOYB=0.0023, w_SHV=0.9913.", "question": "Assets: VTI, LINK-USD, SOYB, SHV\nAnnualized mean returns: VTI:0.2865, LINK-USD:1.0016, SOYB:0.0551, SHV:0.0538\nCovariance matrix (annualized):\n[[0.029795, 0.076981, -0.002672, -9.1e-05], [0.076981, 0.523328, -0.025418, 7e-06], [-0.002672, -0.025418, 0.033357, -5.4e-05], [-9.1e-05, 7e-06, -5.4e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0064, w_LINK-USD=0.0000, w_SOYB=0.0023, w_SHV=0.9913", "answer_numeric": 6.265632318021488, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0064, w_LINK-USD=0.0000, w_SOYB=0.0023, w_SHV=0.9913\nPortfolio annualized return: 5.53%, volatility: 0.24%\nSharpe ratio: (0.0553 - 0.0400) / 0.0024 = 6.2656", "metadata": {"weights": {"VTI": 0.0064, "LINK-USD": 0.0, "SOYB": 0.0023, "SHV": 0.9913}, "sharpe_ratio": 6.2656, "portfolio_return": 0.055307, "portfolio_vol": 0.002443, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241003_0734", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "SHV", "CSHI"], "decision_date": "2024-10-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.874. Portfolio: return=5.23%, vol=0.25%. Weights: w_IWM=0.0014, w_MATIC-USD=0.0000, w_SHV=0.9736, w_CSHI=0.0250.", "question": "Assets: IWM, MATIC-USD, SHV, CSHI\nAnnualized mean returns: IWM:0.2644, MATIC-USD:0.0191, SHV:0.0516, CSHI:0.0666\nCovariance matrix (annualized):\n[[0.047984, 0.061278, 1.2e-05, 0.001495], [0.061278, 0.506421, 7.6e-05, 0.006695], [1.2e-05, 7.6e-05, 6e-06, 2e-06], [0.001495, 0.006695, 2e-06, 0.000403]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0014, w_MATIC-USD=0.0000, w_SHV=0.9736, w_CSHI=0.0250", "answer_numeric": 4.873759917540766, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0014, w_MATIC-USD=0.0000, w_SHV=0.9736, w_CSHI=0.0250\nPortfolio annualized return: 5.23%, volatility: 0.25%\nSharpe ratio: (0.0523 - 0.0400) / 0.0025 = 4.8738", "metadata": {"weights": {"IWM": 0.0014, "MATIC-USD": 0.0, "SHV": 0.9736, "CSHI": 0.025}, "sharpe_ratio": 4.8738, "portfolio_return": 0.052268, "portfolio_vol": 0.002517, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230612_0735", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "XRP-USD", "SHV", "REZ"], "decision_date": "2023-06-12", "context_summary": "4-asset optimization. Max-Sharpe: 1.236. Portfolio: return=4.55%, vol=0.44%. Weights: w_VEA=0.0000, w_XRP-USD=0.0064, w_SHV=0.9834, w_REZ=0.0102.", "question": "Assets: VEA, XRP-USD, SHV, REZ\nAnnualized mean returns: VEA:0.0374, XRP-USD:0.3973, SHV:0.0423, REZ:0.1329\nCovariance matrix (annualized):\n[[0.01756, 0.01006, 7.4e-05, 0.009968], [0.01006, 0.200608, -9.2e-05, 0.008176], [7.4e-05, -9.2e-05, 9e-06, -2.7e-05], [0.009968, 0.008176, -2.7e-05, 0.030105]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_XRP-USD=0.0064, w_SHV=0.9834, w_REZ=0.0102", "answer_numeric": 1.2364979737513728, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_XRP-USD=0.0064, w_SHV=0.9834, w_REZ=0.0102\nPortfolio annualized return: 4.55%, volatility: 0.44%\nSharpe ratio: (0.0455 - 0.0400) / 0.0044 = 1.2365", "metadata": {"weights": {"VEA": 0.0, "XRP-USD": 0.0064, "SHV": 0.9834, "REZ": 0.0102}, "sharpe_ratio": 1.2365, "portfolio_return": 0.045469, "portfolio_vol": 0.004423, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231006_0736", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "XHB", "HYG"], "decision_date": "2023-10-06", "context_summary": "4-asset optimization. Max-Sharpe: -0.581. Portfolio: return=-7.27%, vol=19.40%. Weights: w_XLE=1.0000, w_ADA-USD=0.0000, w_XHB=0.0000, w_HYG=0.0000.", "question": "Assets: XLE, ADA-USD, XHB, HYG\nAnnualized mean returns: XLE:-0.0727, ADA-USD:-0.8953, XHB:-0.6681, HYG:-0.1042\nCovariance matrix (annualized):\n[[0.037642, 0.014846, 0.003677, 0.001379], [0.014846, 0.104112, 0.025172, 0.007089], [0.003677, 0.025172, 0.049791, 0.010189], [0.001379, 0.007089, 0.010189, 0.003472]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=1.0000, w_ADA-USD=0.0000, w_XHB=0.0000, w_HYG=0.0000", "answer_numeric": -0.5807238364128288, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=1.0000, w_ADA-USD=0.0000, w_XHB=0.0000, w_HYG=0.0000\nPortfolio annualized return: -7.27%, volatility: 19.40%\nSharpe ratio: (-0.0727 - 0.0400) / 0.1940 = -0.5807", "metadata": {"weights": {"XLE": 1.0, "ADA-USD": 0.0, "XHB": 0.0, "HYG": 0.0}, "sharpe_ratio": -0.5807, "portfolio_return": -0.072669, "portfolio_vol": 0.194014, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231003_0737", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "PDBC", "IEF"], "decision_date": "2023-10-03", "context_summary": "4-asset optimization. Max-Sharpe: 0.725. Portfolio: return=9.92%, vol=8.17%. Weights: w_VTI=0.0000, w_BTC-USD=0.0000, w_PDBC=1.0000, w_IEF=0.0000.", "question": "Assets: VTI, BTC-USD, PDBC, IEF\nAnnualized mean returns: VTI:-0.3080, BTC-USD:-0.4482, PDBC:0.0992, IEF:-0.1947\nCovariance matrix (annualized):\n[[0.013044, 0.013668, 0.003112, 0.002102], [0.013668, 0.109253, 0.000123, 0.007105], [0.003112, 0.000123, 0.00668, 0.001365], [0.002102, 0.007105, 0.001365, 0.005153]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_BTC-USD=0.0000, w_PDBC=1.0000, w_IEF=0.0000", "answer_numeric": 0.7245627202808288, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_BTC-USD=0.0000, w_PDBC=1.0000, w_IEF=0.0000\nPortfolio annualized return: 9.92%, volatility: 8.17%\nSharpe ratio: (0.0992 - 0.0400) / 0.0817 = 0.7246", "metadata": {"weights": {"VTI": 0.0, "BTC-USD": 0.0, "PDBC": 1.0, "IEF": 0.0}, "sharpe_ratio": 0.7246, "portfolio_return": 0.099217, "portfolio_vol": 0.081729, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230605_0738", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD", "VNQI", "ICSH"], "decision_date": "2023-06-05", "context_summary": "4-asset optimization. Max-Sharpe: 0.563. Portfolio: return=11.19%, vol=12.79%. Weights: w_VEA=1.0000, w_AVAX-USD=0.0000, w_VNQI=0.0000, w_ICSH=0.0000.", "question": "Assets: VEA, AVAX-USD, VNQI, ICSH\nAnnualized mean returns: VEA:0.1119, AVAX-USD:-0.6947, VNQI:-0.0272, ICSH:0.0329\nCovariance matrix (annualized):\n[[0.016353, 0.016743, 0.016106, -0.000348], [0.016743, 0.243188, 0.024204, -0.000133], [0.016106, 0.024204, 0.024719, -0.000206], [-0.000348, -0.000133, -0.000206, 5.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=1.0000, w_AVAX-USD=0.0000, w_VNQI=0.0000, w_ICSH=0.0000", "answer_numeric": 0.5626212383117128, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=1.0000, w_AVAX-USD=0.0000, w_VNQI=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 11.19%, volatility: 12.79%\nSharpe ratio: (0.1119 - 0.0400) / 0.1279 = 0.5626", "metadata": {"weights": {"VEA": 1.0, "AVAX-USD": 0.0, "VNQI": 0.0, "ICSH": 0.0}, "sharpe_ratio": 0.5626, "portfolio_return": 0.111947, "portfolio_vol": 0.127879, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240515_0739", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "DBC", "INDS"], "decision_date": "2024-05-15", "context_summary": "4-asset optimization. Max-Sharpe: 1.138. Portfolio: return=15.73%, vol=10.30%. Weights: w_EWJ=0.0000, w_AVAX-USD=0.0000, w_DBC=1.0000, w_INDS=0.0000.", "question": "Assets: EWJ, AVAX-USD, DBC, INDS\nAnnualized mean returns: EWJ:-0.1213, AVAX-USD:-4.3635, DBC:0.1573, INDS:-0.1235\nCovariance matrix (annualized):\n[[0.021469, 0.03408, 0.000991, 0.018098], [0.03408, 0.54029, 0.012077, 0.041965], [0.000991, 0.012077, 0.010612, 0.001234], [0.018098, 0.041965, 0.001234, 0.03811]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_AVAX-USD=0.0000, w_DBC=1.0000, w_INDS=0.0000", "answer_numeric": 1.1383086776846838, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_AVAX-USD=0.0000, w_DBC=1.0000, w_INDS=0.0000\nPortfolio annualized return: 15.73%, volatility: 10.30%\nSharpe ratio: (0.1573 - 0.0400) / 0.1030 = 1.1383", "metadata": {"weights": {"EWJ": 0.0, "AVAX-USD": 0.0, "DBC": 1.0, "INDS": 0.0}, "sharpe_ratio": 1.1383, "portfolio_return": 0.157264, "portfolio_vol": 0.103016, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230905_0740", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "MATIC-USD", "PALL", "SCHH"], "decision_date": "2023-09-05", "context_summary": "4-asset optimization. Max-Sharpe: -1.220. Portfolio: return=-75.05%, vol=64.81%. Weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_PALL=0.0000, w_SCHH=0.0000.", "question": "Assets: XLU, MATIC-USD, PALL, SCHH\nAnnualized mean returns: XLU:-0.3090, MATIC-USD:-0.7505, PALL:-0.0740, SCHH:-0.1278\nCovariance matrix (annualized):\n[[0.019876, 0.023611, 0.009761, 0.010791], [0.023611, 0.420038, 0.00516, 0.030078], [0.009761, 0.00516, 0.078987, 0.008887], [0.010791, 0.030078, 0.008887, 0.016708]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_MATIC-USD=1.0000, w_PALL=0.0000, w_SCHH=0.0000", "answer_numeric": -1.219755662585702, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_PALL=0.0000, w_SCHH=0.0000\nPortfolio annualized return: -75.05%, volatility: 64.81%\nSharpe ratio: (-0.7505 - 0.0400) / 0.6481 = -1.2198", "metadata": {"weights": {"XLU": 0.0, "MATIC-USD": 1.0, "PALL": 0.0, "SCHH": 0.0}, "sharpe_ratio": -1.2198, "portfolio_return": -0.750527, "portfolio_vol": 0.648103, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230803_0742", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "BNDX", "CSHI"], "decision_date": "2023-08-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.152. Portfolio: return=9.00%, vol=1.21%. Weights: w_XLF=0.0960, w_XRP-USD=0.0000, w_BNDX=0.0000, w_CSHI=0.9040.", "question": "Assets: XLF, XRP-USD, BNDX, CSHI\nAnnualized mean returns: XLF:0.4318, XRP-USD:0.3184, BNDX:-0.0118, CSHI:0.0538\nCovariance matrix (annualized):\n[[0.01249, 0.025807, 0.000519, -6.8e-05], [0.025807, 0.928657, 0.016949, 0.002796], [0.000519, 0.016949, 0.001917, 8.5e-05], [-6.8e-05, 0.002796, 8.5e-05, 5.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0960, w_XRP-USD=0.0000, w_BNDX=0.0000, w_CSHI=0.9040", "answer_numeric": 4.151751946847445, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0960, w_XRP-USD=0.0000, w_BNDX=0.0000, w_CSHI=0.9040\nPortfolio annualized return: 9.00%, volatility: 1.21%\nSharpe ratio: (0.0900 - 0.0400) / 0.0121 = 4.1518", "metadata": {"weights": {"XLF": 0.096, "XRP-USD": 0.0, "BNDX": 0.0, "CSHI": 0.904}, "sharpe_ratio": 4.1518, "portfolio_return": 0.090048, "portfolio_vol": 0.012055, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230616_0744", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BNB-USD", "DBC", "BIL"], "decision_date": "2023-06-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.805. Portfolio: return=6.44%, vol=0.87%. Weights: w_QUAL=0.0470, w_BNB-USD=0.0000, w_DBC=0.0000, w_BIL=0.9530.", "question": "Assets: QUAL, BNB-USD, DBC, BIL\nAnnualized mean returns: QUAL:0.4170, BNB-USD:-1.9528, DBC:-0.3011, BIL:0.0470\nCovariance matrix (annualized):\n[[0.020429, 0.011789, 0.012192, 0.000218], [0.011789, 0.160987, 0.018248, 7.3e-05], [0.012192, 0.018248, 0.03284, 5.1e-05], [0.000218, 7.3e-05, 5.1e-05, 1.2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0470, w_BNB-USD=0.0000, w_DBC=0.0000, w_BIL=0.9530", "answer_numeric": 2.804891961082098, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0470, w_BNB-USD=0.0000, w_DBC=0.0000, w_BIL=0.9530\nPortfolio annualized return: 6.44%, volatility: 0.87%\nSharpe ratio: (0.0644 - 0.0400) / 0.0087 = 2.8049", "metadata": {"weights": {"QUAL": 0.047, "BNB-USD": 0.0, "DBC": 0.0, "BIL": 0.953}, "sharpe_ratio": 2.8049, "portfolio_return": 0.064362, "portfolio_vol": 0.008686, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240424_0745", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "DOT-USD", "STIP", "BIL"], "decision_date": "2024-04-24", "context_summary": "4-asset optimization. Max-Sharpe: 4.581. Portfolio: return=5.10%, vol=0.24%. Weights: w_EWJ=0.0000, w_DOT-USD=0.0000, w_STIP=0.0200, w_BIL=0.9800.", "question": "Assets: EWJ, DOT-USD, STIP, BIL\nAnnualized mean returns: EWJ:-0.1524, DOT-USD:-1.0288, STIP:0.0526, BIL:0.0510\nCovariance matrix (annualized):\n[[0.021025, 0.015202, 0.001143, 3.6e-05], [0.015202, 0.611154, -0.001456, -2.4e-05], [0.001143, -0.001456, 0.000335, -0.0], [3.6e-05, -2.4e-05, -0.0, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_DOT-USD=0.0000, w_STIP=0.0200, w_BIL=0.9800", "answer_numeric": 4.581267206570382, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_DOT-USD=0.0000, w_STIP=0.0200, w_BIL=0.9800\nPortfolio annualized return: 5.10%, volatility: 0.24%\nSharpe ratio: (0.0510 - 0.0400) / 0.0024 = 4.5813", "metadata": {"weights": {"EWJ": 0.0, "DOT-USD": 0.0, "STIP": 0.02, "BIL": 0.98}, "sharpe_ratio": 4.5813, "portfolio_return": 0.051035, "portfolio_vol": 0.002409, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240521_0746", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "BNB-USD", "INDS", "TLH"], "decision_date": "2024-05-21", "context_summary": "4-asset optimization. Max-Sharpe: 0.940. Portfolio: return=14.39%, vol=11.05%. Weights: w_EFA=1.0000, w_BNB-USD=0.0000, w_INDS=0.0000, w_TLH=0.0000.", "question": "Assets: EFA, BNB-USD, INDS, TLH\nAnnualized mean returns: EFA:0.1439, BNB-USD:0.0524, INDS:-0.1123, TLH:-0.0336\nCovariance matrix (annualized):\n[[0.012212, 0.006904, 0.01653, 0.005222], [0.006904, 0.172081, 0.001252, 0.00179], [0.01653, 0.001252, 0.039542, 0.013829], [0.005222, 0.00179, 0.013829, 0.012244]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=1.0000, w_BNB-USD=0.0000, w_INDS=0.0000, w_TLH=0.0000", "answer_numeric": 0.9398068398069632, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=1.0000, w_BNB-USD=0.0000, w_INDS=0.0000, w_TLH=0.0000\nPortfolio annualized return: 14.39%, volatility: 11.05%\nSharpe ratio: (0.1439 - 0.0400) / 0.1105 = 0.9398", "metadata": {"weights": {"EFA": 1.0, "BNB-USD": 0.0, "INDS": 0.0, "TLH": 0.0}, "sharpe_ratio": 0.9398, "portfolio_return": 0.143857, "portfolio_vol": 0.110509, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230509_0749", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "JNK", "PPLT"], "decision_date": "2023-05-09", "context_summary": "4-asset optimization. Max-Sharpe: 6.401. Portfolio: return=59.30%, vol=8.64%. Weights: w_XLP=0.7711, w_ADA-USD=0.0742, w_JNK=0.0000, w_PPLT=0.1547.", "question": "Assets: XLP, ADA-USD, JNK, PPLT\nAnnualized mean returns: XLP:0.4844, ADA-USD:1.3191, JNK:0.1619, PPLT:0.7862\nCovariance matrix (annualized):\n[[0.009168, -0.012292, 0.002031, -0.001023], [-0.012292, 0.354187, 0.015337, 0.00301], [0.002031, 0.015337, 0.005901, 0.001628], [-0.001023, 0.00301, 0.001628, 0.068754]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.7711, w_ADA-USD=0.0742, w_JNK=0.0000, w_PPLT=0.1547", "answer_numeric": 6.400825654974554, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.7711, w_ADA-USD=0.0742, w_JNK=0.0000, w_PPLT=0.1547\nPortfolio annualized return: 59.30%, volatility: 8.64%\nSharpe ratio: (0.5930 - 0.0400) / 0.0864 = 6.4008", "metadata": {"weights": {"XLP": 0.7711, "ADA-USD": 0.0742, "JNK": 0.0, "PPLT": 0.1547}, "sharpe_ratio": 6.4008, "portfolio_return": 0.593027, "portfolio_vol": 0.086399, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240122_0750", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "DOT-USD", "LQD", "REZ"], "decision_date": "2024-01-22", "context_summary": "4-asset optimization. Max-Sharpe: 3.732. Portfolio: return=39.92%, vol=9.63%. Weights: w_VLUE=0.5559, w_DOT-USD=0.0167, w_LQD=0.4274, w_REZ=0.0000.", "question": "Assets: VLUE, DOT-USD, LQD, REZ\nAnnualized mean returns: VLUE:0.4846, DOT-USD:1.2081, LQD:0.2565, REZ:0.5107\nCovariance matrix (annualized):\n[[0.017257, 0.02088, 0.003571, 0.020575], [0.02088, 0.916605, 0.007543, 0.051122], [0.003571, 0.007543, 0.008127, 0.007419], [0.020575, 0.051122, 0.007419, 0.03877]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.5559, w_DOT-USD=0.0167, w_LQD=0.4274, w_REZ=0.0000", "answer_numeric": 3.7315399725587306, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.5559, w_DOT-USD=0.0167, w_LQD=0.4274, w_REZ=0.0000\nPortfolio annualized return: 39.92%, volatility: 9.63%\nSharpe ratio: (0.3992 - 0.0400) / 0.0963 = 3.7315", "metadata": {"weights": {"VLUE": 0.5559, "DOT-USD": 0.0167, "LQD": 0.4274, "REZ": 0.0}, "sharpe_ratio": 3.7315, "portfolio_return": 0.399173, "portfolio_vol": 0.096253, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240829_0751", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "LINK-USD", "IEF", "BIL"], "decision_date": "2024-08-29", "context_summary": "4-asset optimization. Max-Sharpe: 5.180. Portfolio: return=5.63%, vol=0.32%. Weights: w_IVV=0.0026, w_LINK-USD=0.0000, w_IEF=0.0224, w_BIL=0.9750.", "question": "Assets: IVV, LINK-USD, IEF, BIL\nAnnualized mean returns: IVV:0.1530, LINK-USD:-0.3484, IEF:0.2610, BIL:0.0514\nCovariance matrix (annualized):\n[[0.028832, 0.066379, -0.000508, 6e-06], [0.066379, 0.576097, -0.011847, 0.0002], [-0.000508, -0.011847, 0.004285, 4.1e-05], [6e-06, 0.0002, 4.1e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0026, w_LINK-USD=0.0000, w_IEF=0.0224, w_BIL=0.9750", "answer_numeric": 5.17960392326753, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0026, w_LINK-USD=0.0000, w_IEF=0.0224, w_BIL=0.9750\nPortfolio annualized return: 5.63%, volatility: 0.32%\nSharpe ratio: (0.0563 - 0.0400) / 0.0032 = 5.1796", "metadata": {"weights": {"IVV": 0.0026, "LINK-USD": 0.0, "IEF": 0.0224, "BIL": 0.975}, "sharpe_ratio": 5.1796, "portfolio_return": 0.056323, "portfolio_vol": 0.003151, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230207_0752", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "XHB", "CSHI"], "decision_date": "2023-02-07", "context_summary": "4-asset optimization. Max-Sharpe: 3.939. Portfolio: return=11.89%, vol=2.00%. Weights: w_VTI=0.0000, w_BTC-USD=0.0254, w_XHB=0.0336, w_CSHI=0.9410.", "question": "Assets: VTI, BTC-USD, XHB, CSHI\nAnnualized mean returns: VTI:0.2841, BTC-USD:1.2378, XHB:0.8234, CSHI:0.0635\nCovariance matrix (annualized):\n[[0.033674, 0.037465, 0.039253, 0.000557], [0.037465, 0.138256, 0.041942, 0.00124], [0.039253, 0.041942, 0.065139, 0.000777], [0.000557, 0.00124, 0.000777, 6.6e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_BTC-USD=0.0254, w_XHB=0.0336, w_CSHI=0.9410", "answer_numeric": 3.9392317424831167, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_BTC-USD=0.0254, w_XHB=0.0336, w_CSHI=0.9410\nPortfolio annualized return: 11.89%, volatility: 2.00%\nSharpe ratio: (0.1189 - 0.0400) / 0.0200 = 3.9392", "metadata": {"weights": {"VTI": 0.0, "BTC-USD": 0.0254, "XHB": 0.0336, "CSHI": 0.941}, "sharpe_ratio": 3.9392, "portfolio_return": 0.118938, "portfolio_vol": 0.020039, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230906_0753", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "SLV", "SCHP"], "decision_date": "2023-09-06", "context_summary": "4-asset optimization. Max-Sharpe: 0.929. Portfolio: return=19.54%, vol=16.72%. Weights: w_QQQ=1.0000, w_ADA-USD=0.0000, w_SLV=0.0000, w_SCHP=0.0000.", "question": "Assets: QQQ, ADA-USD, SLV, SCHP\nAnnualized mean returns: QQQ:0.1954, ADA-USD:-0.5192, SLV:0.1504, SCHP:-0.0138\nCovariance matrix (annualized):\n[[0.027964, 0.039586, 0.024378, 0.004273], [0.039586, 0.488131, 0.046957, 0.016438], [0.024378, 0.046957, 0.067076, 0.010026], [0.004273, 0.016438, 0.010026, 0.003981]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=1.0000, w_ADA-USD=0.0000, w_SLV=0.0000, w_SCHP=0.0000", "answer_numeric": 0.9292576956279616, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=1.0000, w_ADA-USD=0.0000, w_SLV=0.0000, w_SCHP=0.0000\nPortfolio annualized return: 19.54%, volatility: 16.72%\nSharpe ratio: (0.1954 - 0.0400) / 0.1672 = 0.9293", "metadata": {"weights": {"QQQ": 1.0, "ADA-USD": 0.0, "SLV": 0.0, "SCHP": 0.0}, "sharpe_ratio": 0.9293, "portfolio_return": 0.195395, "portfolio_vol": 0.167225, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231012_0755", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "DOT-USD", "XHB", "CSHI"], "decision_date": "2023-10-12", "context_summary": "4-asset optimization. Max-Sharpe: 1.226. Portfolio: return=5.14%, vol=0.93%. Weights: w_EWJ=0.0000, w_DOT-USD=0.0000, w_XHB=0.0000, w_CSHI=1.0000.", "question": "Assets: EWJ, DOT-USD, XHB, CSHI\nAnnualized mean returns: EWJ:-0.1175, DOT-USD:-1.6393, XHB:-0.3845, CSHI:0.0514\nCovariance matrix (annualized):\n[[0.022515, 0.011157, 0.018503, 0.000414], [0.011157, 0.105009, 0.01901, 0.000314], [0.018503, 0.01901, 0.053457, 0.000494], [0.000414, 0.000314, 0.000494, 8.7e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_DOT-USD=0.0000, w_XHB=0.0000, w_CSHI=1.0000", "answer_numeric": 1.2264396499341184, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_DOT-USD=0.0000, w_XHB=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 5.14%, volatility: 0.93%\nSharpe ratio: (0.0514 - 0.0400) / 0.0093 = 1.2264", "metadata": {"weights": {"EWJ": 0.0, "DOT-USD": 0.0, "XHB": 0.0, "CSHI": 1.0}, "sharpe_ratio": 1.2264, "portfolio_return": 0.051437, "portfolio_vol": 0.009325, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230823_0756", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "BNO", "SCHP"], "decision_date": "2023-08-23", "context_summary": "4-asset optimization. Max-Sharpe: 3.792. Portfolio: return=76.21%, vol=19.04%. Weights: w_XLF=0.1300, w_XRP-USD=0.0000, w_BNO=0.8700, w_SCHP=0.0000.", "question": "Assets: XLF, XRP-USD, BNO, SCHP\nAnnualized mean returns: XLF:0.1630, XRP-USD:-1.0320, BNO:0.8517, SCHP:-0.1259\nCovariance matrix (annualized):\n[[0.014732, 0.029337, 0.004898, 0.001655], [0.029337, 1.021827, 0.04342, 0.015384], [0.004898, 0.04342, 0.046108, 0.002887], [0.001655, 0.015384, 0.002887, 0.003663]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.1300, w_XRP-USD=0.0000, w_BNO=0.8700, w_SCHP=0.0000", "answer_numeric": 3.792491457178497, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.1300, w_XRP-USD=0.0000, w_BNO=0.8700, w_SCHP=0.0000\nPortfolio annualized return: 76.21%, volatility: 19.04%\nSharpe ratio: (0.7621 - 0.0400) / 0.1904 = 3.7925", "metadata": {"weights": {"XLF": 0.13, "XRP-USD": 0.0, "BNO": 0.87, "SCHP": 0.0}, "sharpe_ratio": 3.7925, "portfolio_return": 0.762137, "portfolio_vol": 0.190412, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231020_0757", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "VCIT", "SGOV"], "decision_date": "2023-10-20", "context_summary": "4-asset optimization. Max-Sharpe: 5.728. Portfolio: return=5.33%, vol=0.23%. Weights: w_USMV=0.0000, w_XRP-USD=0.0000, w_VCIT=0.0000, w_SGOV=1.0000.", "question": "Assets: USMV, XRP-USD, VCIT, SGOV\nAnnualized mean returns: USMV:-0.1104, XRP-USD:0.0832, VCIT:-0.2384, SGOV:0.0533\nCovariance matrix (annualized):\n[[0.008403, 0.000411, 0.003653, -3.5e-05], [0.000411, 0.125621, 0.000678, 2e-05], [0.003653, 0.000678, 0.005195, 5e-06], [-3.5e-05, 2e-05, 5e-06, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_XRP-USD=0.0000, w_VCIT=0.0000, w_SGOV=1.0000", "answer_numeric": 5.727998306957948, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_XRP-USD=0.0000, w_VCIT=0.0000, w_SGOV=1.0000\nPortfolio annualized return: 5.33%, volatility: 0.23%\nSharpe ratio: (0.0533 - 0.0400) / 0.0023 = 5.7280", "metadata": {"weights": {"USMV": 0.0, "XRP-USD": 0.0, "VCIT": 0.0, "SGOV": 1.0}, "sharpe_ratio": 5.728, "portfolio_return": 0.053268, "portfolio_vol": 0.002316, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240909_0758", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "TLH", "REZ"], "decision_date": "2024-09-09", "context_summary": "4-asset optimization. Max-Sharpe: 5.629. Portfolio: return=60.94%, vol=10.11%. Weights: w_XLY=0.0000, w_DOT-USD=0.0000, w_TLH=0.4427, w_REZ=0.5573.", "question": "Assets: XLY, DOT-USD, TLH, REZ\nAnnualized mean returns: XLY:-0.2796, DOT-USD:-1.6526, TLH:0.3917, REZ:0.7823\nCovariance matrix (annualized):\n[[0.070194, 0.058849, -0.002485, 0.011895], [0.058849, 0.286701, -0.018749, 0.032963], [-0.002485, -0.018749, 0.012429, 0.001467], [0.011895, 0.032963, 0.001467, 0.022766]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_DOT-USD=0.0000, w_TLH=0.4427, w_REZ=0.5573", "answer_numeric": 5.6290984200256835, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_DOT-USD=0.0000, w_TLH=0.4427, w_REZ=0.5573\nPortfolio annualized return: 60.94%, volatility: 10.11%\nSharpe ratio: (0.6094 - 0.0400) / 0.1011 = 5.6291", "metadata": {"weights": {"XLY": 0.0, "DOT-USD": 0.0, "TLH": 0.4427, "REZ": 0.5573}, "sharpe_ratio": 5.6291, "portfolio_return": 0.609366, "portfolio_vol": 0.101147, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240301_0760", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ETH-USD", "DBB", "ICSH"], "decision_date": "2024-03-01", "context_summary": "4-asset optimization. Max-Sharpe: 4.624. Portfolio: return=8.27%, vol=0.92%. Weights: w_XLK=0.0117, w_ETH-USD=0.0150, w_DBB=0.0000, w_ICSH=0.9733.", "question": "Assets: XLK, ETH-USD, DBB, ICSH\nAnnualized mean returns: XLK:0.4464, ETH-USD:1.8642, DBB:-0.3214, ICSH:0.0508\nCovariance matrix (annualized):\n[[0.036422, 0.014389, 0.002201, 0.000174], [0.014389, 0.239502, 0.007479, -0.000131], [0.002201, 0.007479, 0.019733, 1.5e-05], [0.000174, -0.000131, 1.5e-05, 2.2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.0117, w_ETH-USD=0.0150, w_DBB=0.0000, w_ICSH=0.9733", "answer_numeric": 4.623505404966515, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0117, w_ETH-USD=0.0150, w_DBB=0.0000, w_ICSH=0.9733\nPortfolio annualized return: 8.27%, volatility: 0.92%\nSharpe ratio: (0.0827 - 0.0400) / 0.0092 = 4.6235", "metadata": {"weights": {"XLK": 0.0117, "ETH-USD": 0.015, "DBB": 0.0, "ICSH": 0.9733}, "sharpe_ratio": 4.6235, "portfolio_return": 0.082703, "portfolio_vol": 0.009236, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230706_0761", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "CORN", "IGOV"], "decision_date": "2023-07-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.058. Portfolio: return=31.39%, vol=13.31%. Weights: w_XLF=1.0000, w_SOL-USD=0.0000, w_CORN=0.0000, w_IGOV=0.0000.", "question": "Assets: XLF, SOL-USD, CORN, IGOV\nAnnualized mean returns: XLF:0.3139, SOL-USD:-0.7026, CORN:-0.2098, IGOV:-0.1899\nCovariance matrix (annualized):\n[[0.017722, 0.029116, 0.004333, -0.000355], [0.029116, 0.410599, 0.016091, 0.005022], [0.004333, 0.016091, 0.088735, 0.007974], [-0.000355, 0.005022, 0.007974, 0.008966]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=1.0000, w_SOL-USD=0.0000, w_CORN=0.0000, w_IGOV=0.0000", "answer_numeric": 2.057660149614416, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=1.0000, w_SOL-USD=0.0000, w_CORN=0.0000, w_IGOV=0.0000\nPortfolio annualized return: 31.39%, volatility: 13.31%\nSharpe ratio: (0.3139 - 0.0400) / 0.1331 = 2.0577", "metadata": {"weights": {"XLF": 1.0, "SOL-USD": 0.0, "CORN": 0.0, "IGOV": 0.0}, "sharpe_ratio": 2.0577, "portfolio_return": 0.313924, "portfolio_vol": 0.133124, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231017_0762", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD", "DBA", "CSHI"], "decision_date": "2023-10-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.390. Portfolio: return=10.87%, vol=2.03%. Weights: w_EFA=0.0000, w_LINK-USD=0.0339, w_DBA=0.0692, w_CSHI=0.8970.", "question": "Assets: EFA, LINK-USD, DBA, CSHI\nAnnualized mean returns: EFA:-0.0806, LINK-USD:1.3656, DBA:0.1628, CSHI:0.0571\nCovariance matrix (annualized):\n[[0.016414, 0.017983, 0.003897, 0.000407], [0.017983, 0.247761, -0.007717, 8e-05], [0.003897, -0.007717, 0.010633, 0.000291], [0.000407, 8e-05, 0.000291, 8.9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_LINK-USD=0.0339, w_DBA=0.0692, w_CSHI=0.8970", "answer_numeric": 3.3899758200683436, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_LINK-USD=0.0339, w_DBA=0.0692, w_CSHI=0.8970\nPortfolio annualized return: 10.87%, volatility: 2.03%\nSharpe ratio: (0.1087 - 0.0400) / 0.0203 = 3.3900", "metadata": {"weights": {"EFA": 0.0, "LINK-USD": 0.0339, "DBA": 0.0692, "CSHI": 0.897}, "sharpe_ratio": 3.39, "portfolio_return": 0.108749, "portfolio_vol": 0.02028, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241106_0763", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "DBC", "MORT"], "decision_date": "2024-11-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.888. Portfolio: return=46.18%, vol=14.61%. Weights: w_EWJ=0.0000, w_BNB-USD=0.2795, w_DBC=0.7205, w_MORT=0.0000.", "question": "Assets: EWJ, BNB-USD, DBC, MORT\nAnnualized mean returns: EWJ:0.0736, BNB-USD:0.4855, DBC:0.4525, MORT:-0.0921\nCovariance matrix (annualized):\n[[0.032273, 0.01505, 0.000638, 0.006664], [0.01505, 0.11918, -0.014959, 0.023971], [0.000638, -0.014959, 0.034769, -0.003208], [0.006664, 0.023971, -0.003208, 0.022821]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_BNB-USD=0.2795, w_DBC=0.7205, w_MORT=0.0000", "answer_numeric": 2.8875519183568947, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BNB-USD=0.2795, w_DBC=0.7205, w_MORT=0.0000\nPortfolio annualized return: 46.18%, volatility: 14.61%\nSharpe ratio: (0.4618 - 0.0400) / 0.1461 = 2.8876", "metadata": {"weights": {"EWJ": 0.0, "BNB-USD": 0.2795, "DBC": 0.7205, "MORT": 0.0}, "sharpe_ratio": 2.8876, "portfolio_return": 0.46177, "portfolio_vol": 0.146065, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240506_0764", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "TLH", "WEAT"], "decision_date": "2024-05-06", "context_summary": "4-asset optimization. Max-Sharpe: 4.289. Portfolio: return=71.10%, vol=15.65%. Weights: w_XLE=0.4423, w_DOT-USD=0.0000, w_TLH=0.0000, w_WEAT=0.5577.", "question": "Assets: XLE, DOT-USD, TLH, WEAT\nAnnualized mean returns: XLE:0.4224, DOT-USD:-2.0135, TLH:-0.2350, WEAT:0.9399\nCovariance matrix (annualized):\n[[0.021765, 0.008194, -0.001232, 0.007752], [0.008194, 0.522456, -3e-06, 0.00303], [-0.001232, -3e-06, 0.011817, 0.003234], [0.007752, 0.00303, 0.003234, 0.052717]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.4423, w_DOT-USD=0.0000, w_TLH=0.0000, w_WEAT=0.5577", "answer_numeric": 4.288794679605162, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.4423, w_DOT-USD=0.0000, w_TLH=0.0000, w_WEAT=0.5577\nPortfolio annualized return: 71.10%, volatility: 15.65%\nSharpe ratio: (0.7110 - 0.0400) / 0.1565 = 4.2888", "metadata": {"weights": {"XLE": 0.4423, "DOT-USD": 0.0, "TLH": 0.0, "WEAT": 0.5577}, "sharpe_ratio": 4.2888, "portfolio_return": 0.710998, "portfolio_vol": 0.156454, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230519_0765", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "XRP-USD", "DBB", "BIL"], "decision_date": "2023-05-19", "context_summary": "4-asset optimization. Max-Sharpe: 3.529. Portfolio: return=17.78%, vol=3.91%. Weights: w_QQQ=0.2219, w_XRP-USD=0.0102, w_DBB=0.0000, w_BIL=0.7679.", "question": "Assets: QQQ, XRP-USD, DBB, BIL\nAnnualized mean returns: QQQ:0.5916, XRP-USD:1.4079, DBB:-0.3365, BIL:0.0419\nCovariance matrix (annualized):\n[[0.025493, 0.037973, 0.009864, 7.7e-05], [0.037973, 0.693903, 0.021415, -0.00048], [0.009864, 0.021415, 0.028481, 1.8e-05], [7.7e-05, -0.00048, 1.8e-05, 1.2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.2219, w_XRP-USD=0.0102, w_DBB=0.0000, w_BIL=0.7679", "answer_numeric": 3.5290233073402377, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.2219, w_XRP-USD=0.0102, w_DBB=0.0000, w_BIL=0.7679\nPortfolio annualized return: 17.78%, volatility: 3.91%\nSharpe ratio: (0.1778 - 0.0400) / 0.0391 = 3.5290", "metadata": {"weights": {"QQQ": 0.2219, "XRP-USD": 0.0102, "DBB": 0.0, "BIL": 0.7679}, "sharpe_ratio": 3.529, "portfolio_return": 0.177824, "portfolio_vol": 0.039054, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241001_0767", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MATIC-USD", "ICSH", "IYR"], "decision_date": "2024-10-01", "context_summary": "4-asset optimization. Max-Sharpe: 6.623. Portfolio: return=7.99%, vol=0.60%. Weights: w_FXI=0.0116, w_MATIC-USD=0.0000, w_ICSH=0.9752, w_IYR=0.0132.", "question": "Assets: FXI, MATIC-USD, ICSH, IYR\nAnnualized mean returns: FXI:0.9341, MATIC-USD:0.0441, ICSH:0.0648, IYR:0.4478\nCovariance matrix (annualized):\n[[0.069414, 0.047225, 2e-06, 0.000356], [0.047225, 0.518682, -0.0, 0.033289], [2e-06, -0.0, 2.1e-05, 0.000121], [0.000356, 0.033289, 0.000121, 0.018925]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0116, w_MATIC-USD=0.0000, w_ICSH=0.9752, w_IYR=0.0132", "answer_numeric": 6.622972414370315, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0116, w_MATIC-USD=0.0000, w_ICSH=0.9752, w_IYR=0.0132\nPortfolio annualized return: 7.99%, volatility: 0.60%\nSharpe ratio: (0.0799 - 0.0400) / 0.0060 = 6.6230", "metadata": {"weights": {"FXI": 0.0116, "MATIC-USD": 0.0, "ICSH": 0.9752, "IYR": 0.0132}, "sharpe_ratio": 6.623, "portfolio_return": 0.079919, "portfolio_vol": 0.006027, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230529_0768", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "SHV", "HAUZ"], "decision_date": "2023-05-29", "context_summary": "4-asset optimization. Max-Sharpe: -0.901. Portfolio: return=-38.24%, vol=46.89%. Weights: w_XLRE=0.0000, w_LINK-USD=1.0000, w_SHV=0.0000, w_HAUZ=0.0000.", "question": "Assets: XLRE, LINK-USD, SHV, HAUZ\nAnnualized mean returns: XLRE:-0.0702, LINK-USD:-0.3824, SHV:0.0390, HAUZ:-0.0847\nCovariance matrix (annualized):\n[[0.034597, 0.016196, 1.6e-05, 0.015767], [0.016196, 0.21988, -0.000113, 0.00534], [1.6e-05, -0.000113, 9e-06, -6e-06], [0.015767, 0.00534, -6e-06, 0.022549]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_LINK-USD=1.0000, w_SHV=0.0000, w_HAUZ=0.0000", "answer_numeric": -0.9007287352242311, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_LINK-USD=1.0000, w_SHV=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: -38.24%, volatility: 46.89%\nSharpe ratio: (-0.3824 - 0.0400) / 0.4689 = -0.9007", "metadata": {"weights": {"XLRE": 0.0, "LINK-USD": 1.0, "SHV": 0.0, "HAUZ": 0.0}, "sharpe_ratio": -0.9007, "portfolio_return": -0.382364, "portfolio_vol": 0.468914, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240627_0769", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "LINK-USD", "IEF", "SGOV"], "decision_date": "2024-06-27", "context_summary": "4-asset optimization. Max-Sharpe: 5.143. Portfolio: return=5.42%, vol=0.28%. Weights: w_IWM=0.0000, w_LINK-USD=0.0000, w_IEF=0.0196, w_SGOV=0.9804.", "question": "Assets: IWM, LINK-USD, IEF, SGOV\nAnnualized mean returns: IWM:0.0687, LINK-USD:-0.4407, IEF:0.2025, SGOV:0.0513\nCovariance matrix (annualized):\n[[0.023923, 0.036532, 0.004861, -6.8e-05], [0.036532, 0.398993, 0.008421, 0.000285], [0.004861, 0.008421, 0.004489, -1e-06], [-6.8e-05, 0.000285, -1e-06, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_LINK-USD=0.0000, w_IEF=0.0196, w_SGOV=0.9804", "answer_numeric": 5.142996052856046, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_LINK-USD=0.0000, w_IEF=0.0196, w_SGOV=0.9804\nPortfolio annualized return: 5.42%, volatility: 0.28%\nSharpe ratio: (0.0542 - 0.0400) / 0.0028 = 5.1430", "metadata": {"weights": {"IWM": 0.0, "LINK-USD": 0.0, "IEF": 0.0196, "SGOV": 0.9804}, "sharpe_ratio": 5.143, "portfolio_return": 0.054219, "portfolio_vol": 0.002765, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230308_0771", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "UNG", "ICSH"], "decision_date": "2023-03-08", "context_summary": "4-asset optimization. Max-Sharpe: 3.040. Portfolio: return=8.95%, vol=1.63%. Weights: w_VTI=0.0000, w_XRP-USD=0.0372, w_UNG=0.0000, w_ICSH=0.9628.", "question": "Assets: VTI, XRP-USD, UNG, ICSH\nAnnualized mean returns: VTI:0.1991, XRP-USD:1.3325, UNG:-1.2932, ICSH:0.0416\nCovariance matrix (annualized):\n[[0.025927, 0.034911, 0.030626, 9.3e-05], [0.034911, 0.190452, 0.055268, -0.000153], [0.030626, 0.055268, 0.672062, -0.000785], [9.3e-05, -0.000153, -0.000785, 1.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_XRP-USD=0.0372, w_UNG=0.0000, w_ICSH=0.9628", "answer_numeric": 3.040040255871541, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_XRP-USD=0.0372, w_UNG=0.0000, w_ICSH=0.9628\nPortfolio annualized return: 8.95%, volatility: 1.63%\nSharpe ratio: (0.0895 - 0.0400) / 0.0163 = 3.0400", "metadata": {"weights": {"VTI": 0.0, "XRP-USD": 0.0372, "UNG": 0.0, "ICSH": 0.9628}, "sharpe_ratio": 3.04, "portfolio_return": 0.089537, "portfolio_vol": 0.016295, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230125_0773", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ADA-USD", "VNQ", "BNO"], "decision_date": "2023-01-25", "context_summary": "4-asset optimization. Max-Sharpe: 0.701. Portfolio: return=19.37%, vol=21.93%. Weights: w_VTI=0.0000, w_ADA-USD=0.0000, w_VNQ=0.7344, w_BNO=0.2656.", "question": "Assets: VTI, ADA-USD, VNQ, BNO\nAnnualized mean returns: VTI:-0.0132, ADA-USD:0.0092, VNQ:0.1875, BNO:0.2108\nCovariance matrix (annualized):\n[[0.037868, 0.053114, 0.037401, 0.029989], [0.053114, 0.336862, 0.065267, 0.053982], [0.037401, 0.065267, 0.053433, 0.026055], [0.029989, 0.053982, 0.026055, 0.129229]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_ADA-USD=0.0000, w_VNQ=0.7344, w_BNO=0.2656", "answer_numeric": 0.7007853485825493, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_ADA-USD=0.0000, w_VNQ=0.7344, w_BNO=0.2656\nPortfolio annualized return: 19.37%, volatility: 21.93%\nSharpe ratio: (0.1937 - 0.0400) / 0.2193 = 0.7008", "metadata": {"weights": {"VTI": 0.0, "ADA-USD": 0.0, "VNQ": 0.7344, "BNO": 0.2656}, "sharpe_ratio": 0.7008, "portfolio_return": 0.193693, "portfolio_vol": 0.219315, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240524_0774", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "INDS", "SGOV"], "decision_date": "2024-05-24", "context_summary": "4-asset optimization. Max-Sharpe: 5.548. Portfolio: return=5.41%, vol=0.25%. Weights: w_EWJ=0.0000, w_BNB-USD=0.0001, w_INDS=0.0000, w_SGOV=0.9999.", "question": "Assets: EWJ, BNB-USD, INDS, SGOV\nAnnualized mean returns: EWJ:-0.3445, BNB-USD:0.0511, INDS:-0.2928, SGOV:0.0541\nCovariance matrix (annualized):\n[[0.021074, 0.008261, 0.018404, -6.1e-05], [0.008261, 0.173403, 0.004579, -7e-06], [0.018404, 0.004579, 0.041811, -4.9e-05], [-6.1e-05, -7e-06, -4.9e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_BNB-USD=0.0001, w_INDS=0.0000, w_SGOV=0.9999", "answer_numeric": 5.548342871477398, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BNB-USD=0.0001, w_INDS=0.0000, w_SGOV=0.9999\nPortfolio annualized return: 5.41%, volatility: 0.25%\nSharpe ratio: (0.0541 - 0.0400) / 0.0025 = 5.5483", "metadata": {"weights": {"EWJ": 0.0, "BNB-USD": 0.0001, "INDS": 0.0, "SGOV": 0.9999}, "sharpe_ratio": 5.5483, "portfolio_return": 0.054126, "portfolio_vol": 0.002546, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240729_0775", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "SHV", "DBC"], "decision_date": "2024-07-29", "context_summary": "4-asset optimization. Max-Sharpe: 7.233. Portfolio: return=5.71%, vol=0.24%. Weights: w_QUAL=0.0005, w_ADA-USD=0.0000, w_SHV=0.9995, w_DBC=0.0000.", "question": "Assets: QUAL, ADA-USD, SHV, DBC\nAnnualized mean returns: QUAL:0.1543, ADA-USD:-0.0893, SHV:0.0570, DBC:-0.3902\nCovariance matrix (annualized):\n[[0.01417, 0.005488, 3e-05, 0.00133], [0.005488, 0.234667, 0.000354, -0.016357], [3e-05, 0.000354, 6e-06, -8.4e-05], [0.00133, -0.016357, -8.4e-05, 0.015189]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0005, w_ADA-USD=0.0000, w_SHV=0.9995, w_DBC=0.0000", "answer_numeric": 7.233166264977225, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0005, w_ADA-USD=0.0000, w_SHV=0.9995, w_DBC=0.0000\nPortfolio annualized return: 5.71%, volatility: 0.24%\nSharpe ratio: (0.0571 - 0.0400) / 0.0024 = 7.2332", "metadata": {"weights": {"QUAL": 0.0005, "ADA-USD": 0.0, "SHV": 0.9995, "DBC": 0.0}, "sharpe_ratio": 7.2332, "portfolio_return": 0.057073, "portfolio_vol": 0.00236, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231004_0776", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ETH-USD", "PALL", "SCHP"], "decision_date": "2023-10-04", "context_summary": "4-asset optimization. Max-Sharpe: -1.489. Portfolio: return=-37.47%, vol=27.85%. Weights: w_XLY=0.0000, w_ETH-USD=0.0000, w_PALL=1.0000, w_SCHP=0.0000.", "question": "Assets: XLY, ETH-USD, PALL, SCHP\nAnnualized mean returns: XLY:-0.5264, ETH-USD:-0.6798, PALL:-0.3747, SCHP:-0.2202\nCovariance matrix (annualized):\n[[0.036472, 0.014082, 0.015496, 0.004154], [0.014082, 0.104726, 0.015452, 0.006876], [0.015496, 0.015452, 0.07755, 0.0061], [0.004154, 0.006876, 0.0061, 0.002852]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_ETH-USD=0.0000, w_PALL=1.0000, w_SCHP=0.0000", "answer_numeric": -1.4890235709035025, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_ETH-USD=0.0000, w_PALL=1.0000, w_SCHP=0.0000\nPortfolio annualized return: -37.47%, volatility: 27.85%\nSharpe ratio: (-0.3747 - 0.0400) / 0.2785 = -1.4890", "metadata": {"weights": {"XLY": 0.0, "ETH-USD": 0.0, "PALL": 1.0, "SCHP": 0.0}, "sharpe_ratio": -1.489, "portfolio_return": -0.374661, "portfolio_vol": 0.278479, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230901_0777", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ETH-USD", "IYR", "UNG"], "decision_date": "2023-09-01", "context_summary": "4-asset optimization. Max-Sharpe: -0.434. Portfolio: return=-15.33%, vol=44.59%. Weights: w_EFA=0.0000, w_ETH-USD=0.0000, w_IYR=0.0000, w_UNG=1.0000.", "question": "Assets: EFA, ETH-USD, IYR, UNG\nAnnualized mean returns: EFA:-0.0789, ETH-USD:-0.7968, IYR:-0.0737, UNG:-0.1533\nCovariance matrix (annualized):\n[[0.018, 0.024358, 0.008862, 0.006251], [0.024358, 0.112443, 0.015901, -0.010777], [0.008862, 0.015901, 0.016524, 0.007482], [0.006251, -0.010777, 0.007482, 0.198787]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_ETH-USD=0.0000, w_IYR=0.0000, w_UNG=1.0000", "answer_numeric": -0.43359827052711203, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_ETH-USD=0.0000, w_IYR=0.0000, w_UNG=1.0000\nPortfolio annualized return: -15.33%, volatility: 44.59%\nSharpe ratio: (-0.1533 - 0.0400) / 0.4459 = -0.4336", "metadata": {"weights": {"EFA": 0.0, "ETH-USD": 0.0, "IYR": 0.0, "UNG": 1.0}, "sharpe_ratio": -0.4336, "portfolio_return": -0.153322, "portfolio_vol": 0.445856, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231123_0778", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "BNDX", "IAU"], "decision_date": "2023-11-23", "context_summary": "4-asset optimization. Max-Sharpe: 4.363. Portfolio: return=42.51%, vol=8.83%. Weights: w_XLV=0.0104, w_BTC-USD=0.2083, w_BNDX=0.5273, w_IAU=0.2540.", "question": "Assets: XLV, BTC-USD, BNDX, IAU\nAnnualized mean returns: XLV:0.0126, BTC-USD:1.5703, BNDX:0.1118, IAU:0.1532\nCovariance matrix (annualized):\n[[0.014625, -0.00646, 0.00151, -0.000621], [-0.00646, 0.178575, -0.003994, -0.016025], [0.00151, -0.003994, 0.0031, 0.002496], [-0.000621, -0.016025, 0.002496, 0.017001]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0104, w_BTC-USD=0.2083, w_BNDX=0.5273, w_IAU=0.2540", "answer_numeric": 4.3634575953332115, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0104, w_BTC-USD=0.2083, w_BNDX=0.5273, w_IAU=0.2540\nPortfolio annualized return: 42.51%, volatility: 8.83%\nSharpe ratio: (0.4251 - 0.0400) / 0.0883 = 4.3635", "metadata": {"weights": {"XLV": 0.0104, "BTC-USD": 0.2083, "BNDX": 0.5273, "IAU": 0.254}, "sharpe_ratio": 4.3635, "portfolio_return": 0.425083, "portfolio_vol": 0.088252, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240517_0780", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VEA", "ETH-USD", "TLH", "SGOV"], "decision_date": "2024-05-17", "context_summary": "4-asset optimization. Max-Sharpe: 5.851. Portfolio: return=5.35%, vol=0.23%. Weights: w_VEA=0.0049, w_ETH-USD=0.0000, w_TLH=0.0000, w_SGOV=0.9951.", "question": "Assets: VEA, ETH-USD, TLH, SGOV\nAnnualized mean returns: VEA:0.1717, ETH-USD:-1.9891, TLH:0.0370, SGOV:0.0530\nCovariance matrix (annualized):\n[[0.012913, 0.031417, 0.005315, -1.2e-05], [0.031417, 0.373625, 0.002122, 6e-06], [0.005315, 0.002122, 0.011606, 3e-06], [-1.2e-05, 6e-06, 3e-06, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0049, w_ETH-USD=0.0000, w_TLH=0.0000, w_SGOV=0.9951", "answer_numeric": 5.850546101447891, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0049, w_ETH-USD=0.0000, w_TLH=0.0000, w_SGOV=0.9951\nPortfolio annualized return: 5.35%, volatility: 0.23%\nSharpe ratio: (0.0535 - 0.0400) / 0.0023 = 5.8505", "metadata": {"weights": {"VEA": 0.0049, "ETH-USD": 0.0, "TLH": 0.0, "SGOV": 0.9951}, "sharpe_ratio": 5.8505, "portfolio_return": 0.053548, "portfolio_vol": 0.002316, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230705_0781", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "CSHI", "LQD"], "decision_date": "2023-07-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.111. Portfolio: return=7.47%, vol=1.12%. Weights: w_XLP=0.0000, w_LINK-USD=0.0083, w_CSHI=0.9917, w_LQD=0.0000.", "question": "Assets: XLP, LINK-USD, CSHI, LQD\nAnnualized mean returns: XLP:-0.1610, LINK-USD:0.5894, CSHI:0.0704, LQD:-0.0183\nCovariance matrix (annualized):\n[[0.009607, 0.011633, -1.2e-05, 0.000691], [0.011633, 0.258253, -0.00017, 0.007531], [-1.2e-05, -0.00017, 0.000111, -1.6e-05], [0.000691, 0.007531, -1.6e-05, 0.005441]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_LINK-USD=0.0083, w_CSHI=0.9917, w_LQD=0.0000", "answer_numeric": 3.111126532314407, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_LINK-USD=0.0083, w_CSHI=0.9917, w_LQD=0.0000\nPortfolio annualized return: 7.47%, volatility: 1.12%\nSharpe ratio: (0.0747 - 0.0400) / 0.0112 = 3.1111", "metadata": {"weights": {"XLP": 0.0, "LINK-USD": 0.0083, "CSHI": 0.9917, "LQD": 0.0}, "sharpe_ratio": 3.1111, "portfolio_return": 0.074692, "portfolio_vol": 0.011151, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231225_0782", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "BIL", "PPLT"], "decision_date": "2023-12-25", "context_summary": "4-asset optimization. Max-Sharpe: 10.753. Portfolio: return=7.88%, vol=0.36%. Weights: w_VTI=0.0233, w_BTC-USD=0.0038, w_BIL=0.9725, w_PPLT=0.0004.", "question": "Assets: VTI, BTC-USD, BIL, PPLT\nAnnualized mean returns: VTI:0.8676, BTC-USD:1.3204, BIL:0.0549, PPLT:0.4677\nCovariance matrix (annualized):\n[[0.014203, -0.004206, -4.2e-05, 0.008955], [-0.004206, 0.167637, -0.000107, -0.016622], [-4.2e-05, -0.000107, 7e-06, -2.6e-05], [0.008955, -0.016622, -2.6e-05, 0.059104]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0233, w_BTC-USD=0.0038, w_BIL=0.9725, w_PPLT=0.0004", "answer_numeric": 10.752757614238458, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0233, w_BTC-USD=0.0038, w_BIL=0.9725, w_PPLT=0.0004\nPortfolio annualized return: 7.88%, volatility: 0.36%\nSharpe ratio: (0.0788 - 0.0400) / 0.0036 = 10.7528", "metadata": {"weights": {"VTI": 0.0233, "BTC-USD": 0.0038, "BIL": 0.9725, "PPLT": 0.0004}, "sharpe_ratio": 10.7528, "portfolio_return": 0.078842, "portfolio_vol": 0.003612, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240117_0783", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "AVAX-USD", "IYR", "USO"], "decision_date": "2024-01-17", "context_summary": "4-asset optimization. Max-Sharpe: 4.167. Portfolio: return=57.01%, vol=12.72%. Weights: w_XLP=0.4323, w_AVAX-USD=0.0612, w_IYR=0.5065, w_USO=0.0000.", "question": "Assets: XLP, AVAX-USD, IYR, USO\nAnnualized mean returns: XLP:0.3221, AVAX-USD:1.8081, IYR:0.6321, USO:-0.2884\nCovariance matrix (annualized):\n[[0.013266, -0.015057, 0.0075, -0.006227], [-0.015057, 0.926494, 0.007446, -0.081093], [0.0075, 0.007446, 0.028382, -0.001456], [-0.006227, -0.081093, -0.001456, 0.097762]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.4323, w_AVAX-USD=0.0612, w_IYR=0.5065, w_USO=0.0000", "answer_numeric": 4.167133902362521, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.4323, w_AVAX-USD=0.0612, w_IYR=0.5065, w_USO=0.0000\nPortfolio annualized return: 57.01%, volatility: 12.72%\nSharpe ratio: (0.5701 - 0.0400) / 0.1272 = 4.1671", "metadata": {"weights": {"XLP": 0.4323, "AVAX-USD": 0.0612, "IYR": 0.5065, "USO": 0.0}, "sharpe_ratio": 4.1671, "portfolio_return": 0.570053, "portfolio_vol": 0.127198, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240529_0784", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "MATIC-USD", "SHY", "BIL"], "decision_date": "2024-05-29", "context_summary": "4-asset optimization. Max-Sharpe: 3.769. Portfolio: return=5.05%, vol=0.28%. Weights: w_XLF=0.0000, w_MATIC-USD=0.0000, w_SHY=0.0000, w_BIL=1.0000.", "question": "Assets: XLF, MATIC-USD, SHY, BIL\nAnnualized mean returns: XLF:-0.1432, MATIC-USD:-1.8995, SHY:0.0141, BIL:0.0505\nCovariance matrix (annualized):\n[[0.015154, 0.010094, 0.000507, -6.4e-05], [0.010094, 0.36906, 0.001462, 0.00063], [0.000507, 0.001462, 0.000257, -0.0], [-6.4e-05, 0.00063, -0.0, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_MATIC-USD=0.0000, w_SHY=0.0000, w_BIL=1.0000", "answer_numeric": 3.768515357908457, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_MATIC-USD=0.0000, w_SHY=0.0000, w_BIL=1.0000\nPortfolio annualized return: 5.05%, volatility: 0.28%\nSharpe ratio: (0.0505 - 0.0400) / 0.0028 = 3.7685", "metadata": {"weights": {"XLF": 0.0, "MATIC-USD": 0.0, "SHY": 0.0, "BIL": 1.0}, "sharpe_ratio": 3.7685, "portfolio_return": 0.050544, "portfolio_vol": 0.002798, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230327_0786", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SOL-USD", "ICSH", "USO"], "decision_date": "2023-03-27", "context_summary": "4-asset optimization. Max-Sharpe: 0.915. Portfolio: return=4.55%, vol=0.60%. Weights: w_VEA=0.0000, w_SOL-USD=0.0000, w_ICSH=1.0000, w_USO=0.0000.", "question": "Assets: VEA, SOL-USD, ICSH, USO\nAnnualized mean returns: VEA:-0.2773, SOL-USD:-2.6968, ICSH:0.0455, USO:-0.8432\nCovariance matrix (annualized):\n[[0.024231, 0.02843, -0.000194, 0.01929], [0.02843, 0.578126, 0.001033, 0.019203], [-0.000194, 0.001033, 3.6e-05, -0.000112], [0.01929, 0.019203, -0.000112, 0.101328]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_SOL-USD=0.0000, w_ICSH=1.0000, w_USO=0.0000", "answer_numeric": 0.9153869252202025, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_SOL-USD=0.0000, w_ICSH=1.0000, w_USO=0.0000\nPortfolio annualized return: 4.55%, volatility: 0.60%\nSharpe ratio: (0.0455 - 0.0400) / 0.0060 = 0.9154", "metadata": {"weights": {"VEA": 0.0, "SOL-USD": 0.0, "ICSH": 1.0, "USO": 0.0}, "sharpe_ratio": 0.9154, "portfolio_return": 0.045479, "portfolio_vol": 0.005986, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230830_0788", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "REZ", "SGOV"], "decision_date": "2023-08-30", "context_summary": "4-asset optimization. Max-Sharpe: 7.013. Portfolio: return=5.23%, vol=0.18%. Weights: w_MTUM=0.0061, w_LINK-USD=0.0000, w_REZ=0.0000, w_SGOV=0.9939.", "question": "Assets: MTUM, LINK-USD, REZ, SGOV\nAnnualized mean returns: MTUM:0.1069, LINK-USD:0.6387, REZ:-0.1674, SGOV:0.0520\nCovariance matrix (annualized):\n[[0.017227, 0.02053, 0.004062, -9e-05], [0.02053, 0.56401, 0.030458, 0.000368], [0.004062, 0.030458, 0.021359, -1e-05], [-9e-05, 0.000368, -1e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0061, w_LINK-USD=0.0000, w_REZ=0.0000, w_SGOV=0.9939", "answer_numeric": 7.013262220965752, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0061, w_LINK-USD=0.0000, w_REZ=0.0000, w_SGOV=0.9939\nPortfolio annualized return: 5.23%, volatility: 0.18%\nSharpe ratio: (0.0523 - 0.0400) / 0.0018 = 7.0133", "metadata": {"weights": {"MTUM": 0.0061, "LINK-USD": 0.0, "REZ": 0.0, "SGOV": 0.9939}, "sharpe_ratio": 7.0133, "portfolio_return": 0.052315, "portfolio_vol": 0.001756, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230112_0789", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "DOT-USD", "BIL", "TLT"], "decision_date": "2023-01-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.209. Portfolio: return=50.55%, vol=21.07%. Weights: w_IWM=0.0000, w_DOT-USD=0.0000, w_BIL=0.0000, w_TLT=1.0000.", "question": "Assets: IWM, DOT-USD, BIL, TLT\nAnnualized mean returns: IWM:-0.1121, DOT-USD:-0.5433, BIL:0.0352, TLT:0.5055\nCovariance matrix (annualized):\n[[0.045806, 0.045672, -0.000113, 0.011435], [0.045672, 0.214104, 0.000195, 0.026428], [-0.000113, 0.000195, 9e-06, 7.1e-05], [0.011435, 0.026428, 7.1e-05, 0.044397]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_DOT-USD=0.0000, w_BIL=0.0000, w_TLT=1.0000", "answer_numeric": 2.209160764853627, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_DOT-USD=0.0000, w_BIL=0.0000, w_TLT=1.0000\nPortfolio annualized return: 50.55%, volatility: 21.07%\nSharpe ratio: (0.5055 - 0.0400) / 0.2107 = 2.2092", "metadata": {"weights": {"IWM": 0.0, "DOT-USD": 0.0, "BIL": 0.0, "TLT": 1.0}, "sharpe_ratio": 2.2092, "portfolio_return": 0.505486, "portfolio_vol": 0.210707, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240611_0791", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "XRP-USD", "ICSH", "PALL"], "decision_date": "2024-06-11", "context_summary": "4-asset optimization. Max-Sharpe: 4.246. Portfolio: return=5.54%, vol=0.36%. Weights: w_IVV=0.0054, w_XRP-USD=0.0000, w_ICSH=0.9946, w_PALL=0.0000.", "question": "Assets: IVV, XRP-USD, ICSH, PALL\nAnnualized mean returns: IVV:0.2060, XRP-USD:-0.4016, ICSH:0.0546, PALL:-0.8701\nCovariance matrix (annualized):\n[[0.013013, 0.02318, 7.3e-05, 0.012644], [0.02318, 0.183627, 0.00086, 0.036753], [7.3e-05, 0.00086, 1.2e-05, 3.8e-05], [0.012644, 0.036753, 3.8e-05, 0.083779]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0054, w_XRP-USD=0.0000, w_ICSH=0.9946, w_PALL=0.0000", "answer_numeric": 4.246484889300739, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0054, w_XRP-USD=0.0000, w_ICSH=0.9946, w_PALL=0.0000\nPortfolio annualized return: 5.54%, volatility: 0.36%\nSharpe ratio: (0.0554 - 0.0400) / 0.0036 = 4.2465", "metadata": {"weights": {"IVV": 0.0054, "XRP-USD": 0.0, "ICSH": 0.9946, "PALL": 0.0}, "sharpe_ratio": 4.2465, "portfolio_return": 0.055441, "portfolio_vol": 0.003636, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240912_0793", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "DOT-USD", "BIL", "HAUZ"], "decision_date": "2024-09-12", "context_summary": "4-asset optimization. Max-Sharpe: -2.502. Portfolio: return=-39.30%, vol=17.31%. Weights: w_FXI=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_HAUZ=0.2500.", "question": "Assets: FXI, DOT-USD, BIL, HAUZ\nAnnualized mean returns: FXI:-0.3401, DOT-USD:-1.5769, BIL:0.0510, HAUZ:0.2940\nCovariance matrix (annualized):\n[[0.038916, 0.02054, 2.7e-05, 0.013906], [0.02054, 0.274536, 0.000219, 0.03802], [2.7e-05, 0.000219, 8e-06, 1e-06], [0.013906, 0.03802, 1e-06, 0.020495]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_HAUZ=0.2500", "answer_numeric": -2.501675773812147, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_HAUZ=0.2500\nPortfolio annualized return: -39.30%, volatility: 17.31%\nSharpe ratio: (-0.3930 - 0.0400) / 0.1731 = -2.5017", "metadata": {"weights": {"FXI": 0.25, "DOT-USD": 0.25, "BIL": 0.25, "HAUZ": 0.25}, "sharpe_ratio": -2.5017, "portfolio_return": -0.393023, "portfolio_vol": 0.173093, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241126_0795", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BTC-USD", "IGOV", "CSHI"], "decision_date": "2024-11-26", "context_summary": "4-asset optimization. Max-Sharpe: 4.656. Portfolio: return=8.16%, vol=0.89%. Weights: w_XLI=0.0000, w_BTC-USD=0.0130, w_IGOV=0.0000, w_CSHI=0.9870.", "question": "Assets: XLI, BTC-USD, IGOV, CSHI\nAnnualized mean returns: XLI:0.3355, BTC-USD:1.9067, IGOV:-0.2849, CSHI:0.0575\nCovariance matrix (annualized):\n[[0.019629, 0.03395, -0.002807, 0.000202], [0.03395, 0.249335, -0.0032, 0.000342], [-0.002807, -0.0032, 0.00774, 2.1e-05], [0.000202, 0.000342, 2.1e-05, 3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_BTC-USD=0.0130, w_IGOV=0.0000, w_CSHI=0.9870", "answer_numeric": 4.655597134750582, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_BTC-USD=0.0130, w_IGOV=0.0000, w_CSHI=0.9870\nPortfolio annualized return: 8.16%, volatility: 0.89%\nSharpe ratio: (0.0816 - 0.0400) / 0.0089 = 4.6556", "metadata": {"weights": {"XLI": 0.0, "BTC-USD": 0.013, "IGOV": 0.0, "CSHI": 0.987}, "sharpe_ratio": 4.6556, "portfolio_return": 0.081573, "portfolio_vol": 0.00893, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20241128_0796", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "BNB-USD", "IYR", "SOYB"], "decision_date": "2024-11-28", "context_summary": "4-asset optimization. Max-Sharpe: 0.449. Portfolio: return=11.11%, vol=15.85%. Weights: w_XLV=0.0000, w_BNB-USD=0.0000, w_IYR=1.0000, w_SOYB=0.0000.", "question": "Assets: XLV, BNB-USD, IYR, SOYB\nAnnualized mean returns: XLV:-0.2372, BNB-USD:-0.1879, IYR:0.1111, SOYB:-0.5095\nCovariance matrix (annualized):\n[[0.014068, 0.009417, 0.008465, 0.000595], [0.009417, 0.1601, 0.007242, -0.009123], [0.008465, 0.007242, 0.025117, 0.002571], [0.000595, -0.009123, 0.002571, 0.014838]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_BNB-USD=0.0000, w_IYR=1.0000, w_SOYB=0.0000", "answer_numeric": 0.448889815870077, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_BNB-USD=0.0000, w_IYR=1.0000, w_SOYB=0.0000\nPortfolio annualized return: 11.11%, volatility: 15.85%\nSharpe ratio: (0.1111 - 0.0400) / 0.1585 = 0.4489", "metadata": {"weights": {"XLV": 0.0, "BNB-USD": 0.0, "IYR": 1.0, "SOYB": 0.0}, "sharpe_ratio": 0.4489, "portfolio_return": 0.111142, "portfolio_vol": 0.158485, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230103_0798", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "SOL-USD", "DBA", "BNDX"], "decision_date": "2023-01-03", "context_summary": "4-asset optimization. Max-Sharpe: 1.811. Portfolio: return=25.01%, vol=11.60%. Weights: w_XLV=0.6741, w_SOL-USD=0.0000, w_DBA=0.3259, w_BNDX=0.0000.", "question": "Assets: XLV, SOL-USD, DBA, BNDX\nAnnualized mean returns: XLV:0.3056, SOL-USD:-2.4684, DBA:0.1352, BNDX:-0.0319\nCovariance matrix (annualized):\n[[0.022571, 0.089884, 0.005518, 0.003248], [0.089884, 1.796099, 0.028186, 0.012553], [0.005518, 0.028186, 0.007303, -0.000628], [0.003248, 0.012553, -0.000628, 0.003544]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.6741, w_SOL-USD=0.0000, w_DBA=0.3259, w_BNDX=0.0000", "answer_numeric": 1.8112103896684526, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.6741, w_SOL-USD=0.0000, w_DBA=0.3259, w_BNDX=0.0000\nPortfolio annualized return: 25.01%, volatility: 11.60%\nSharpe ratio: (0.2501 - 0.0400) / 0.1160 = 1.8112", "metadata": {"weights": {"XLV": 0.6741, "SOL-USD": 0.0, "DBA": 0.3259, "BNDX": 0.0}, "sharpe_ratio": 1.8112, "portfolio_return": 0.250108, "portfolio_vol": 0.116004, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230417_0800", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ETH-USD", "CSHI", "INDS"], "decision_date": "2023-04-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.852. Portfolio: return=9.59%, vol=1.96%. Weights: w_XLP=0.0569, w_ETH-USD=0.0243, w_CSHI=0.9187, w_INDS=0.0000.", "question": "Assets: XLP, ETH-USD, CSHI, INDS\nAnnualized mean returns: XLP:0.1923, ETH-USD:0.8193, CSHI:0.0708, INDS:-0.1521\nCovariance matrix (annualized):\n[[0.011996, 1.7e-05, 0.000396, 0.015509], [1.7e-05, 0.239268, -0.000508, 0.000216], [0.000396, -0.000508, 0.000219, 0.000925], [0.015509, 0.000216, 0.000925, 0.04405]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0569, w_ETH-USD=0.0243, w_CSHI=0.9187, w_INDS=0.0000", "answer_numeric": 2.851940532509018, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0569, w_ETH-USD=0.0243, w_CSHI=0.9187, w_INDS=0.0000\nPortfolio annualized return: 9.59%, volatility: 1.96%\nSharpe ratio: (0.0959 - 0.0400) / 0.0196 = 2.8519", "metadata": {"weights": {"XLP": 0.0569, "ETH-USD": 0.0243, "CSHI": 0.9187, "INDS": 0.0}, "sharpe_ratio": 2.8519, "portfolio_return": 0.095908, "portfolio_vol": 0.019603, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241219_0802", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ADA-USD", "SCHH", "TLT"], "decision_date": "2024-12-19", "context_summary": "4-asset optimization. Max-Sharpe: 3.985. Portfolio: return=415.08%, vol=103.16%. Weights: w_XLV=0.0000, w_ADA-USD=1.0000, w_SCHH=0.0000, w_TLT=0.0000.", "question": "Assets: XLV, ADA-USD, SCHH, TLT\nAnnualized mean returns: XLV:-0.6538, ADA-USD:4.1508, SCHH:-0.5108, TLT:-0.2175\nCovariance matrix (annualized):\n[[0.013901, 0.019537, 0.008885, 0.005074], [0.019537, 1.064231, 0.035061, 0.009137], [0.008885, 0.035061, 0.026641, 0.014369], [0.005074, 0.009137, 0.014369, 0.022429]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_ADA-USD=1.0000, w_SCHH=0.0000, w_TLT=0.0000", "answer_numeric": 3.984771729033398, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_ADA-USD=1.0000, w_SCHH=0.0000, w_TLT=0.0000\nPortfolio annualized return: 415.08%, volatility: 103.16%\nSharpe ratio: (4.1508 - 0.0400) / 1.0316 = 3.9848", "metadata": {"weights": {"XLV": 0.0, "ADA-USD": 1.0, "SCHH": 0.0, "TLT": 0.0}, "sharpe_ratio": 3.9848, "portfolio_return": 4.150753, "portfolio_vol": 1.031616, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240226_0804", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "PPLT", "IEF"], "decision_date": "2024-02-26", "context_summary": "4-asset optimization. Max-Sharpe: 2.436. Portfolio: return=33.76%, vol=12.22%. Weights: w_XLI=1.0000, w_DOT-USD=0.0000, w_PPLT=0.0000, w_IEF=0.0000.", "question": "Assets: XLI, DOT-USD, PPLT, IEF\nAnnualized mean returns: XLI:0.3376, DOT-USD:-0.4562, PPLT:-0.6438, IEF:-0.1598\nCovariance matrix (annualized):\n[[0.014928, 0.025367, 0.006609, 0.003171], [0.025367, 0.421966, 0.008821, -0.000561], [0.006609, 0.008821, 0.045184, 0.003082], [0.003171, -0.000561, 0.003082, 0.005486]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=1.0000, w_DOT-USD=0.0000, w_PPLT=0.0000, w_IEF=0.0000", "answer_numeric": 2.435797032959048, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=1.0000, w_DOT-USD=0.0000, w_PPLT=0.0000, w_IEF=0.0000\nPortfolio annualized return: 33.76%, volatility: 12.22%\nSharpe ratio: (0.3376 - 0.0400) / 0.1222 = 2.4358", "metadata": {"weights": {"XLI": 1.0, "DOT-USD": 0.0, "PPLT": 0.0, "IEF": 0.0}, "sharpe_ratio": 2.4358, "portfolio_return": 0.337603, "portfolio_vol": 0.122179, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231114_0805", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SOL-USD", "USO", "INDS"], "decision_date": "2023-11-14", "context_summary": "4-asset optimization. Max-Sharpe: 5.377. Portfolio: return=483.36%, vol=89.15%. Weights: w_VTI=0.0000, w_SOL-USD=1.0000, w_USO=0.0000, w_INDS=0.0000.", "question": "Assets: VTI, SOL-USD, USO, INDS\nAnnualized mean returns: VTI:-0.1503, SOL-USD:4.8336, USO:-0.5880, INDS:-0.6068\nCovariance matrix (annualized):\n[[0.021464, 0.024669, -0.008701, 0.025683], [0.024669, 0.794734, 0.005096, 0.00995], [-0.008701, 0.005096, 0.103478, -0.020409], [0.025683, 0.00995, -0.020409, 0.05108]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_SOL-USD=1.0000, w_USO=0.0000, w_INDS=0.0000", "answer_numeric": 5.377158931043022, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_SOL-USD=1.0000, w_USO=0.0000, w_INDS=0.0000\nPortfolio annualized return: 483.36%, volatility: 89.15%\nSharpe ratio: (4.8336 - 0.0400) / 0.8915 = 5.3772", "metadata": {"weights": {"VTI": 0.0, "SOL-USD": 1.0, "USO": 0.0, "INDS": 0.0}, "sharpe_ratio": 5.3772, "portfolio_return": 4.833623, "portfolio_vol": 0.891479, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231101_0806", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "IAU", "ICSH"], "decision_date": "2023-11-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.849. Portfolio: return=6.14%, vol=0.56%. Weights: w_^VIX=0.0025, w_ADA-USD=0.0091, w_IAU=0.0000, w_ICSH=0.9885.", "question": "Assets: ^VIX, ADA-USD, IAU, ICSH\nAnnualized mean returns: ^VIX:2.0054, ADA-USD:0.4805, IAU:0.0958, ICSH:0.0527\nCovariance matrix (annualized):\n[[1.060477, -0.059077, 0.036198, 0.00076], [-0.059077, 0.077177, -0.00168, 8.4e-05], [0.036198, -0.00168, 0.014972, 6.4e-05], [0.00076, 8.4e-05, 6.4e-05, 1.6e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0025, w_ADA-USD=0.0091, w_IAU=0.0000, w_ICSH=0.9885", "answer_numeric": 3.84947482987913, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0025, w_ADA-USD=0.0091, w_IAU=0.0000, w_ICSH=0.9885\nPortfolio annualized return: 6.14%, volatility: 0.56%\nSharpe ratio: (0.0614 - 0.0400) / 0.0056 = 3.8495", "metadata": {"weights": {"^VIX": 0.0025, "ADA-USD": 0.0091, "IAU": 0.0, "ICSH": 0.9885}, "sharpe_ratio": 3.8495, "portfolio_return": 0.061409, "portfolio_vol": 0.005562, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240119_0808", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "IYR", "BIL"], "decision_date": "2024-01-19", "context_summary": "4-asset optimization. Max-Sharpe: 6.744. Portfolio: return=6.29%, vol=0.34%. Weights: w_QUAL=0.0171, w_LINK-USD=0.0000, w_IYR=0.0030, w_BIL=0.9799.", "question": "Assets: QUAL, LINK-USD, IYR, BIL\nAnnualized mean returns: QUAL:0.4064, LINK-USD:-0.0677, IYR:0.4456, BIL:0.0558\nCovariance matrix (annualized):\n[[0.00824, 0.015124, 0.007506, 2.2e-05], [0.015124, 0.594214, 0.042869, 6.2e-05], [0.007506, 0.042869, 0.030017, -1.5e-05], [2.2e-05, 6.2e-05, -1.5e-05, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0171, w_LINK-USD=0.0000, w_IYR=0.0030, w_BIL=0.9799", "answer_numeric": 6.744297532637299, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0171, w_LINK-USD=0.0000, w_IYR=0.0030, w_BIL=0.9799\nPortfolio annualized return: 6.29%, volatility: 0.34%\nSharpe ratio: (0.0629 - 0.0400) / 0.0034 = 6.7443", "metadata": {"weights": {"QUAL": 0.0171, "LINK-USD": 0.0, "IYR": 0.003, "BIL": 0.9799}, "sharpe_ratio": 6.7443, "portfolio_return": 0.062945, "portfolio_vol": 0.003402, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240509_0810", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "MATIC-USD", "CPER", "SCHH"], "decision_date": "2024-05-09", "context_summary": "4-asset optimization. Max-Sharpe: 4.458. Portfolio: return=92.85%, vol=19.93%. Weights: w_MTUM=0.0287, w_MATIC-USD=0.0000, w_CPER=0.9713, w_SCHH=0.0000.", "question": "Assets: MTUM, MATIC-USD, CPER, SCHH\nAnnualized mean returns: MTUM:-0.0516, MATIC-USD:-3.5280, CPER:0.9575, SCHH:-0.3135\nCovariance matrix (annualized):\n[[0.034159, 0.015238, -0.005227, 0.01035], [0.015238, 0.434116, 0.035699, 0.023376], [-0.005227, 0.035699, 0.042378, 0.003718], [0.01035, 0.023376, 0.003718, 0.029579]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0287, w_MATIC-USD=0.0000, w_CPER=0.9713, w_SCHH=0.0000", "answer_numeric": 4.458479259083575, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0287, w_MATIC-USD=0.0000, w_CPER=0.9713, w_SCHH=0.0000\nPortfolio annualized return: 92.85%, volatility: 19.93%\nSharpe ratio: (0.9285 - 0.0400) / 0.1993 = 4.4585", "metadata": {"weights": {"MTUM": 0.0287, "MATIC-USD": 0.0, "CPER": 0.9713, "SCHH": 0.0}, "sharpe_ratio": 4.4585, "portfolio_return": 0.928492, "portfolio_vol": 0.199281, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230320_0811", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ETH-USD", "WEAT", "MORT"], "decision_date": "2023-03-20", "context_summary": "4-asset optimization. Max-Sharpe: 0.747. Portfolio: return=43.83%, vol=53.31%. Weights: w_IVV=0.0000, w_ETH-USD=1.0000, w_WEAT=0.0000, w_MORT=0.0000.", "question": "Assets: IVV, ETH-USD, WEAT, MORT\nAnnualized mean returns: IVV:-0.0025, ETH-USD:0.4383, WEAT:-0.2728, MORT:-1.2851\nCovariance matrix (annualized):\n[[0.02929, 0.028126, 0.006816, 0.038732], [0.028126, 0.284233, 0.016942, 0.042759], [0.006816, 0.016942, 0.053719, 0.010052], [0.038732, 0.042759, 0.010052, 0.077195]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_ETH-USD=1.0000, w_WEAT=0.0000, w_MORT=0.0000", "answer_numeric": 0.7470596740786954, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_ETH-USD=1.0000, w_WEAT=0.0000, w_MORT=0.0000\nPortfolio annualized return: 43.83%, volatility: 53.31%\nSharpe ratio: (0.4383 - 0.0400) / 0.5331 = 0.7471", "metadata": {"weights": {"IVV": 0.0, "ETH-USD": 1.0, "WEAT": 0.0, "MORT": 0.0}, "sharpe_ratio": 0.7471, "portfolio_return": 0.438283, "portfolio_vol": 0.533135, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230809_0813", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "DOT-USD", "HAUZ", "CORN"], "decision_date": "2023-08-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.834. Portfolio: return=32.99%, vol=10.23%. Weights: w_VTI=0.8945, w_DOT-USD=0.1055, w_HAUZ=0.0000, w_CORN=0.0000.", "question": "Assets: VTI, DOT-USD, HAUZ, CORN\nAnnualized mean returns: VTI:0.3017, DOT-USD:0.5697, HAUZ:-0.0123, CORN:-0.1167\nCovariance matrix (annualized):\n[[0.010458, 0.00084, 0.008761, 0.000182], [0.00084, 0.174045, -0.004778, -0.016409], [0.008761, -0.004778, 0.021607, -0.000357], [0.000182, -0.016409, -0.000357, 0.122788]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.8945, w_DOT-USD=0.1055, w_HAUZ=0.0000, w_CORN=0.0000", "answer_numeric": 2.8344498678701147, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.8945, w_DOT-USD=0.1055, w_HAUZ=0.0000, w_CORN=0.0000\nPortfolio annualized return: 32.99%, volatility: 10.23%\nSharpe ratio: (0.3299 - 0.0400) / 0.1023 = 2.8344", "metadata": {"weights": {"VTI": 0.8945, "DOT-USD": 0.1055, "HAUZ": 0.0, "CORN": 0.0}, "sharpe_ratio": 2.8344, "portfolio_return": 0.329948, "portfolio_vol": 0.102294, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240215_0815", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "HAUZ", "SGOV"], "decision_date": "2024-02-15", "context_summary": "4-asset optimization. Max-Sharpe: 5.953. Portfolio: return=5.94%, vol=0.33%. Weights: w_USMV=0.0043, w_BTC-USD=0.0033, w_HAUZ=0.0000, w_SGOV=0.9924.", "question": "Assets: USMV, BTC-USD, HAUZ, SGOV\nAnnualized mean returns: USMV:0.2525, BTC-USD:1.2706, HAUZ:-0.1671, SGOV:0.0545\nCovariance matrix (annualized):\n[[0.006172, 0.001737, 0.007079, 8.5e-05], [0.001737, 0.198158, 0.007884, 6e-06], [0.007079, 0.007884, 0.029123, 9.4e-05], [8.5e-05, 6e-06, 9.4e-05, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0043, w_BTC-USD=0.0033, w_HAUZ=0.0000, w_SGOV=0.9924", "answer_numeric": 5.952586661055899, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0043, w_BTC-USD=0.0033, w_HAUZ=0.0000, w_SGOV=0.9924\nPortfolio annualized return: 5.94%, volatility: 0.33%\nSharpe ratio: (0.0594 - 0.0400) / 0.0033 = 5.9526", "metadata": {"weights": {"USMV": 0.0043, "BTC-USD": 0.0033, "HAUZ": 0.0, "SGOV": 0.9924}, "sharpe_ratio": 5.9526, "portfolio_return": 0.059378, "portfolio_vol": 0.003255, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20241122_0817", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "AVAX-USD", "ICSH", "BNO"], "decision_date": "2024-11-22", "context_summary": "4-asset optimization. Max-Sharpe: 1.253. Portfolio: return=47.85%, vol=35.00%. Weights: w_^VIX=0.2453, w_AVAX-USD=0.4844, w_ICSH=0.0000, w_BNO=0.2704.", "question": "Assets: ^VIX, AVAX-USD, ICSH, BNO\nAnnualized mean returns: ^VIX:0.5255, AVAX-USD:0.6412, ICSH:0.0343, BNO:0.1445\nCovariance matrix (annualized):\n[[1.065536, -0.331477, 0.000977, 0.128766], [-0.331477, 0.554511, -0.000441, -0.07172], [0.000977, -0.000441, 1.7e-05, 8.5e-05], [0.128766, -0.07172, 8.5e-05, 0.119641]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.2453, w_AVAX-USD=0.4844, w_ICSH=0.0000, w_BNO=0.2704", "answer_numeric": 1.253108805385423, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.2453, w_AVAX-USD=0.4844, w_ICSH=0.0000, w_BNO=0.2704\nPortfolio annualized return: 47.85%, volatility: 35.00%\nSharpe ratio: (0.4785 - 0.0400) / 0.3500 = 1.2531", "metadata": {"weights": {"^VIX": 0.2453, "AVAX-USD": 0.4844, "ICSH": 0.0, "BNO": 0.2704}, "sharpe_ratio": 1.2531, "portfolio_return": 0.478539, "portfolio_vol": 0.349961, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240607_0818", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DOT-USD", "SHY", "ICSH"], "decision_date": "2024-06-07", "context_summary": "4-asset optimization. Max-Sharpe: -1.820. Portfolio: return=-26.42%, vol=16.71%. Weights: w_XLB=0.2500, w_DOT-USD=0.2500, w_SHY=0.2500, w_ICSH=0.2500.", "question": "Assets: XLB, DOT-USD, SHY, ICSH\nAnnualized mean returns: XLB:-0.1322, DOT-USD:-1.0310, SHY:0.0532, ICSH:0.0533\nCovariance matrix (annualized):\n[[0.016302, 0.023521, 0.000762, 0.000148], [0.023521, 0.374523, 0.002218, 0.00122], [0.000762, 0.002218, 0.000221, 2.8e-05], [0.000148, 0.00122, 2.8e-05, 1.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.2500, w_DOT-USD=0.2500, w_SHY=0.2500, w_ICSH=0.2500", "answer_numeric": -1.8202279466131417, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.2500, w_DOT-USD=0.2500, w_SHY=0.2500, w_ICSH=0.2500\nPortfolio annualized return: -26.42%, volatility: 16.71%\nSharpe ratio: (-0.2642 - 0.0400) / 0.1671 = -1.8202", "metadata": {"weights": {"XLB": 0.25, "DOT-USD": 0.25, "SHY": 0.25, "ICSH": 0.25}, "sharpe_ratio": -1.8202, "portfolio_return": -0.264192, "portfolio_vol": 0.167117, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240918_0819", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "VNQI", "DBC"], "decision_date": "2024-09-18", "context_summary": "4-asset optimization. Max-Sharpe: 3.885. Portfolio: return=42.09%, vol=9.80%. Weights: w_XLP=0.7354, w_ADA-USD=0.0000, w_VNQI=0.2646, w_DBC=0.0000.", "question": "Assets: XLP, ADA-USD, VNQI, DBC\nAnnualized mean returns: XLP:0.4088, ADA-USD:-0.5750, VNQI:0.4546, DBC:-0.1552\nCovariance matrix (annualized):\n[[0.010152, 0.014991, 0.00696, -0.003091], [0.014991, 0.346804, 0.032935, 0.016997], [0.00696, 0.032935, 0.020201, 0.006769], [-0.003091, 0.016997, 0.006769, 0.026892]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.7354, w_ADA-USD=0.0000, w_VNQI=0.2646, w_DBC=0.0000", "answer_numeric": 3.8846822105525787, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.7354, w_ADA-USD=0.0000, w_VNQI=0.2646, w_DBC=0.0000\nPortfolio annualized return: 42.09%, volatility: 9.80%\nSharpe ratio: (0.4209 - 0.0400) / 0.0980 = 3.8847", "metadata": {"weights": {"XLP": 0.7354, "ADA-USD": 0.0, "VNQI": 0.2646, "DBC": 0.0}, "sharpe_ratio": 3.8847, "portfolio_return": 0.420885, "portfolio_vol": 0.098048, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230303_0821", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "DBA", "VNQI"], "decision_date": "2023-03-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.205. Portfolio: return=147.69%, vol=65.18%. Weights: w_MTUM=0.0000, w_ADA-USD=1.0000, w_DBA=0.0000, w_VNQI=0.0000.", "question": "Assets: MTUM, ADA-USD, DBA, VNQI\nAnnualized mean returns: MTUM:-0.2278, ADA-USD:1.4769, DBA:0.0210, VNQI:0.0403\nCovariance matrix (annualized):\n[[0.018688, 0.020829, 0.003988, 0.003329], [0.020829, 0.424781, 0.006645, 0.031109], [0.003988, 0.006645, 0.011798, -0.000239], [0.003329, 0.031109, -0.000239, 0.021869]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_ADA-USD=1.0000, w_DBA=0.0000, w_VNQI=0.0000", "answer_numeric": 2.204596286880686, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_ADA-USD=1.0000, w_DBA=0.0000, w_VNQI=0.0000\nPortfolio annualized return: 147.69%, volatility: 65.18%\nSharpe ratio: (1.4769 - 0.0400) / 0.6518 = 2.2046", "metadata": {"weights": {"MTUM": 0.0, "ADA-USD": 1.0, "DBA": 0.0, "VNQI": 0.0}, "sharpe_ratio": 2.2046, "portfolio_return": 1.47685, "portfolio_vol": 0.651752, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240408_0823", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "DOT-USD", "CORN", "EMB"], "decision_date": "2024-04-08", "context_summary": "4-asset optimization. Max-Sharpe: 2.458. Portfolio: return=19.66%, vol=6.37%. Weights: w_FXI=0.1385, w_DOT-USD=0.0000, w_CORN=0.0541, w_EMB=0.8074.", "question": "Assets: FXI, DOT-USD, CORN, EMB\nAnnualized mean returns: FXI:0.4228, DOT-USD:0.4348, CORN:-0.0615, EMB:0.1751\nCovariance matrix (annualized):\n[[0.05755, 0.05107, -0.009828, 0.003072], [0.05107, 0.493864, 0.011756, 0.004721], [-0.009828, 0.011756, 0.028698, -0.003497], [0.003072, 0.004721, -0.003497, 0.004043]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.1385, w_DOT-USD=0.0000, w_CORN=0.0541, w_EMB=0.8074", "answer_numeric": 2.4584219950325013, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.1385, w_DOT-USD=0.0000, w_CORN=0.0541, w_EMB=0.8074\nPortfolio annualized return: 19.66%, volatility: 6.37%\nSharpe ratio: (0.1966 - 0.0400) / 0.0637 = 2.4584", "metadata": {"weights": {"FXI": 0.1385, "DOT-USD": 0.0, "CORN": 0.0541, "EMB": 0.8074}, "sharpe_ratio": 2.4584, "portfolio_return": 0.196603, "portfolio_vol": 0.063701, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241114_0825", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "ICSH", "CORN"], "decision_date": "2024-11-14", "context_summary": "4-asset optimization. Max-Sharpe: 2.227. Portfolio: return=159.66%, vol=69.91%. Weights: w_XLRE=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_CORN=0.0000.", "question": "Assets: XLRE, LINK-USD, ICSH, CORN\nAnnualized mean returns: XLRE:-0.2093, LINK-USD:1.5966, ICSH:0.0363, CORN:-0.0004\nCovariance matrix (annualized):\n[[0.024626, 0.008116, 0.000162, -0.000278], [0.008116, 0.488779, -0.000779, -0.002196], [0.000162, -0.000779, 1.8e-05, -4.7e-05], [-0.000278, -0.002196, -4.7e-05, 0.018974]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_CORN=0.0000", "answer_numeric": 2.2265361099998775, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_CORN=0.0000\nPortfolio annualized return: 159.66%, volatility: 69.91%\nSharpe ratio: (1.5966 - 0.0400) / 0.6991 = 2.2265", "metadata": {"weights": {"XLRE": 0.0, "LINK-USD": 1.0, "ICSH": 0.0, "CORN": 0.0}, "sharpe_ratio": 2.2265, "portfolio_return": 1.596633, "portfolio_vol": 0.699127, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230914_0827", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "ICSH", "XHB"], "decision_date": "2023-09-14", "context_summary": "4-asset optimization. Max-Sharpe: 3.762. Portfolio: return=5.65%, vol=0.44%. Weights: w_USMV=0.0021, w_XRP-USD=0.0000, w_ICSH=0.9979, w_XHB=0.0000.", "question": "Assets: USMV, XRP-USD, ICSH, XHB\nAnnualized mean returns: USMV:0.0426, XRP-USD:-2.3557, ICSH:0.0565, XHB:-0.2563\nCovariance matrix (annualized):\n[[0.005205, 0.014144, -8e-06, 0.007276], [0.014144, 0.254386, -4e-06, 0.042163], [-8e-06, -4e-06, 1.9e-05, 7.2e-05], [0.007276, 0.042163, 7.2e-05, 0.040512]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0021, w_XRP-USD=0.0000, w_ICSH=0.9979, w_XHB=0.0000", "answer_numeric": 3.762051224608457, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0021, w_XRP-USD=0.0000, w_ICSH=0.9979, w_XHB=0.0000\nPortfolio annualized return: 5.65%, volatility: 0.44%\nSharpe ratio: (0.0565 - 0.0400) / 0.0044 = 3.7621", "metadata": {"weights": {"USMV": 0.0021, "XRP-USD": 0.0, "ICSH": 0.9979, "XHB": 0.0}, "sharpe_ratio": 3.7621, "portfolio_return": 0.056453, "portfolio_vol": 0.004373, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230301_0828", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "TIP", "SCHH"], "decision_date": "2023-03-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.102. Portfolio: return=88.08%, vol=27.11%. Weights: w_XLY=0.8236, w_LINK-USD=0.1764, w_TIP=0.0000, w_SCHH=0.0000.", "question": "Assets: XLY, LINK-USD, TIP, SCHH\nAnnualized mean returns: XLY:0.7715, LINK-USD:1.3910, TIP:0.0312, SCHH:0.2261\nCovariance matrix (annualized):\n[[0.06323, 0.067186, 0.001507, 0.040815], [0.067186, 0.355597, 0.002017, 0.043699], [0.001507, 0.002017, 0.000805, 0.002107], [0.040815, 0.043699, 0.002107, 0.043225]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.8236, w_LINK-USD=0.1764, w_TIP=0.0000, w_SCHH=0.0000", "answer_numeric": 3.101754427818268, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.8236, w_LINK-USD=0.1764, w_TIP=0.0000, w_SCHH=0.0000\nPortfolio annualized return: 88.08%, volatility: 27.11%\nSharpe ratio: (0.8808 - 0.0400) / 0.2711 = 3.1018", "metadata": {"weights": {"XLY": 0.8236, "LINK-USD": 0.1764, "TIP": 0.0, "SCHH": 0.0}, "sharpe_ratio": 3.1018, "portfolio_return": 0.8808, "portfolio_vol": 0.271072, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240709_0830", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "SGOV", "VNQI"], "decision_date": "2024-07-09", "context_summary": "4-asset optimization. Max-Sharpe: 5.894. Portfolio: return=5.46%, vol=0.25%. Weights: w_XLB=0.0000, w_ADA-USD=0.0000, w_SGOV=1.0000, w_VNQI=0.0000.", "question": "Assets: XLB, ADA-USD, SGOV, VNQI\nAnnualized mean returns: XLB:-0.2258, ADA-USD:-0.4944, SGOV:0.0546, VNQI:-0.1609\nCovariance matrix (annualized):\n[[0.011696, 0.000822, -6.3e-05, 0.006651], [0.000822, 0.239598, -0.000235, 0.018095], [-6.3e-05, -0.000235, 6e-06, -1.3e-05], [0.006651, 0.018095, -1.3e-05, 0.01617]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_ADA-USD=0.0000, w_SGOV=1.0000, w_VNQI=0.0000", "answer_numeric": 5.894381409488973, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_ADA-USD=0.0000, w_SGOV=1.0000, w_VNQI=0.0000\nPortfolio annualized return: 5.46%, volatility: 0.25%\nSharpe ratio: (0.0546 - 0.0400) / 0.0025 = 5.8944", "metadata": {"weights": {"XLB": 0.0, "ADA-USD": 0.0, "SGOV": 1.0, "VNQI": 0.0}, "sharpe_ratio": 5.8944, "portfolio_return": 0.054562, "portfolio_vol": 0.002471, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240307_0832", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "ICSH", "TLT"], "decision_date": "2024-03-07", "context_summary": "4-asset optimization. Max-Sharpe: 4.928. Portfolio: return=7.41%, vol=0.69%. Weights: w_FXI=0.0000, w_ADA-USD=0.0078, w_ICSH=0.9922, w_TLT=0.0000.", "question": "Assets: FXI, ADA-USD, ICSH, TLT\nAnnualized mean returns: FXI:0.0302, ADA-USD:2.6046, ICSH:0.0543, TLT:0.0310\nCovariance matrix (annualized):\n[[0.106528, 0.023232, 0.000125, 0.004033], [0.023232, 0.520106, -0.000435, 0.009892], [0.000125, -0.000435, 2.4e-05, 0.000389], [0.004033, 0.009892, 0.000389, 0.022729]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_ADA-USD=0.0078, w_ICSH=0.9922, w_TLT=0.0000", "answer_numeric": 4.927961026218666, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_ADA-USD=0.0078, w_ICSH=0.9922, w_TLT=0.0000\nPortfolio annualized return: 7.41%, volatility: 0.69%\nSharpe ratio: (0.0741 - 0.0400) / 0.0069 = 4.9280", "metadata": {"weights": {"FXI": 0.0, "ADA-USD": 0.0078, "ICSH": 0.9922, "TLT": 0.0}, "sharpe_ratio": 4.928, "portfolio_return": 0.074131, "portfolio_vol": 0.006926, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231025_0834", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "SGOV", "DBA"], "decision_date": "2023-10-25", "context_summary": "4-asset optimization. Max-Sharpe: 5.858. Portfolio: return=5.39%, vol=0.24%. Weights: w_VTI=0.0000, w_XRP-USD=0.0017, w_SGOV=0.9949, w_DBA=0.0034.", "question": "Assets: VTI, XRP-USD, SGOV, DBA\nAnnualized mean returns: VTI:-0.2395, XRP-USD:0.6042, SGOV:0.0528, DBA:0.0864\nCovariance matrix (annualized):\n[[0.015924, -0.004672, -2.4e-05, 0.002954], [-0.004672, 0.135986, 6e-06, -0.004539], [-2.4e-05, 6e-06, 5e-06, -4e-06], [0.002954, -0.004539, -4e-06, 0.009189]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_XRP-USD=0.0017, w_SGOV=0.9949, w_DBA=0.0034", "answer_numeric": 5.857888608767484, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_XRP-USD=0.0017, w_SGOV=0.9949, w_DBA=0.0034\nPortfolio annualized return: 5.39%, volatility: 0.24%\nSharpe ratio: (0.0539 - 0.0400) / 0.0024 = 5.8579", "metadata": {"weights": {"VTI": 0.0, "XRP-USD": 0.0017, "SGOV": 0.9949, "DBA": 0.0034}, "sharpe_ratio": 5.8579, "portfolio_return": 0.053881, "portfolio_vol": 0.00237, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231206_0835", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ETH-USD", "SHV", "SOYB"], "decision_date": "2023-12-06", "context_summary": "4-asset optimization. Max-Sharpe: 6.926. Portfolio: return=6.12%, vol=0.31%. Weights: w_EFA=0.0078, w_ETH-USD=0.0036, w_SHV=0.9837, w_SOYB=0.0049.", "question": "Assets: EFA, ETH-USD, SHV, SOYB\nAnnualized mean returns: EFA:0.3343, ETH-USD:1.3896, SHV:0.0537, SOYB:0.1753\nCovariance matrix (annualized):\n[[0.018539, -0.006165, 5e-06, 0.000578], [-0.006165, 0.229839, -7.6e-05, -0.020336], [5e-06, -7.6e-05, 6e-06, -3e-06], [0.000578, -0.020336, -3e-06, 0.026726]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0078, w_ETH-USD=0.0036, w_SHV=0.9837, w_SOYB=0.0049", "answer_numeric": 6.92601074675142, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0078, w_ETH-USD=0.0036, w_SHV=0.9837, w_SOYB=0.0049\nPortfolio annualized return: 6.12%, volatility: 0.31%\nSharpe ratio: (0.0612 - 0.0400) / 0.0031 = 6.9260", "metadata": {"weights": {"EFA": 0.0078, "ETH-USD": 0.0036, "SHV": 0.9837, "SOYB": 0.0049}, "sharpe_ratio": 6.926, "portfolio_return": 0.061226, "portfolio_vol": 0.003065, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230131_0836", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "VNQ", "PALL"], "decision_date": "2023-01-31", "context_summary": "4-asset optimization. Max-Sharpe: 0.676. Portfolio: return=18.52%, vol=21.47%. Weights: w_XLI=0.0000, w_DOT-USD=0.0000, w_VNQ=1.0000, w_PALL=0.0000.", "question": "Assets: XLI, DOT-USD, VNQ, PALL\nAnnualized mean returns: XLI:-0.0716, DOT-USD:0.2196, VNQ:0.1852, PALL:-1.0241\nCovariance matrix (annualized):\n[[0.032533, 0.031248, 0.02927, 0.024824], [0.031248, 0.336313, 0.064884, 0.034659], [0.02927, 0.064884, 0.046111, 0.042098], [0.024824, 0.034659, 0.042098, 0.196758]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_DOT-USD=0.0000, w_VNQ=1.0000, w_PALL=0.0000", "answer_numeric": 0.6761889669102508, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_DOT-USD=0.0000, w_VNQ=1.0000, w_PALL=0.0000\nPortfolio annualized return: 18.52%, volatility: 21.47%\nSharpe ratio: (0.1852 - 0.0400) / 0.2147 = 0.6762", "metadata": {"weights": {"XLI": 0.0, "DOT-USD": 0.0, "VNQ": 1.0, "PALL": 0.0}, "sharpe_ratio": 0.6762, "portfolio_return": 0.185201, "portfolio_vol": 0.214734, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241205_0838", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "DOT-USD", "DBA", "SGOV"], "decision_date": "2024-12-05", "context_summary": "4-asset optimization. Max-Sharpe: 4.342. Portfolio: return=5.83%, vol=0.42%. Weights: w_QUAL=0.0126, w_DOT-USD=0.0028, w_DBA=0.0206, w_SGOV=0.9640.", "question": "Assets: QUAL, DOT-USD, DBA, SGOV\nAnnualized mean returns: QUAL:0.2505, DOT-USD:2.0137, DBA:0.2697, SGOV:0.0456\nCovariance matrix (annualized):\n[[0.012805, 0.023186, -0.00039, -1.5e-05], [0.023186, 0.573066, -0.008672, 0.000188], [-0.00039, -0.008672, 0.013849, -3.3e-05], [-1.5e-05, 0.000188, -3.3e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0126, w_DOT-USD=0.0028, w_DBA=0.0206, w_SGOV=0.9640", "answer_numeric": 4.3424456636909765, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0126, w_DOT-USD=0.0028, w_DBA=0.0206, w_SGOV=0.9640\nPortfolio annualized return: 5.83%, volatility: 0.42%\nSharpe ratio: (0.0583 - 0.0400) / 0.0042 = 4.3424", "metadata": {"weights": {"QUAL": 0.0126, "DOT-USD": 0.0028, "DBA": 0.0206, "SGOV": 0.964}, "sharpe_ratio": 4.3424, "portfolio_return": 0.05833, "portfolio_vol": 0.004221, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20240528_0839", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "AVAX-USD", "IYR", "BIL"], "decision_date": "2024-05-28", "context_summary": "4-asset optimization. Max-Sharpe: -2.970. Portfolio: return=-66.25%, vol=23.66%. Weights: w_IVV=0.2500, w_AVAX-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500.", "question": "Assets: IVV, AVAX-USD, IYR, BIL\nAnnualized mean returns: IVV:0.0765, AVAX-USD:-2.4911, IYR:-0.2877, BIL:0.0525\nCovariance matrix (annualized):\n[[0.014363, 0.042805, 0.01479, -5.6e-05], [0.042805, 0.640491, 0.046923, 0.00031], [0.01479, 0.046923, 0.030996, -5.2e-05], [-5.6e-05, 0.00031, -5.2e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.2500, w_AVAX-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500", "answer_numeric": -2.969599545779533, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.2500, w_AVAX-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500\nPortfolio annualized return: -66.25%, volatility: 23.66%\nSharpe ratio: (-0.6625 - 0.0400) / 0.2366 = -2.9696", "metadata": {"weights": {"IVV": 0.25, "AVAX-USD": 0.25, "IYR": 0.25, "BIL": 0.25}, "sharpe_ratio": -2.9696, "portfolio_return": -0.662461, "portfolio_vol": 0.236551, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230918_0840", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ETH-USD", "USO", "SGOV"], "decision_date": "2023-09-18", "context_summary": "4-asset optimization. Max-Sharpe: 9.131. Portfolio: return=6.45%, vol=0.27%. Weights: w_VLUE=0.0000, w_ETH-USD=0.0000, w_USO=0.0101, w_SGOV=0.9899.", "question": "Assets: VLUE, ETH-USD, USO, SGOV\nAnnualized mean returns: VLUE:-0.1389, ETH-USD:-0.7754, USO:1.1436, SGOV:0.0534\nCovariance matrix (annualized):\n[[0.010081, 0.00925, 0.00748, -3.1e-05], [0.00925, 0.086429, -0.001466, -7.2e-05], [0.00748, -0.001466, 0.03243, -4e-06], [-3.1e-05, -7.2e-05, -4e-06, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_ETH-USD=0.0000, w_USO=0.0101, w_SGOV=0.9899", "answer_numeric": 9.131258093102774, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_ETH-USD=0.0000, w_USO=0.0101, w_SGOV=0.9899\nPortfolio annualized return: 6.45%, volatility: 0.27%\nSharpe ratio: (0.0645 - 0.0400) / 0.0027 = 9.1313", "metadata": {"weights": {"VLUE": 0.0, "ETH-USD": 0.0, "USO": 0.0101, "SGOV": 0.9899}, "sharpe_ratio": 9.1313, "portfolio_return": 0.064473, "portfolio_vol": 0.00268, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240606_0841", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "XRP-USD", "CSHI", "PPLT"], "decision_date": "2024-06-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.715. Portfolio: return=6.07%, vol=0.76%. Weights: w_XLB=0.0000, w_XRP-USD=0.0000, w_CSHI=0.9853, w_PPLT=0.0147.", "question": "Assets: XLB, XRP-USD, CSHI, PPLT\nAnnualized mean returns: XLB:-0.1420, XRP-USD:0.0832, CSHI:0.0548, PPLT:0.4563\nCovariance matrix (annualized):\n[[0.016683, 0.020925, 0.00021, 0.018195], [0.020925, 0.176619, 0.000959, 0.003074], [0.00021, 0.000959, 4.1e-05, 4.9e-05], [0.018195, 0.003074, 4.9e-05, 0.076072]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_XRP-USD=0.0000, w_CSHI=0.9853, w_PPLT=0.0147", "answer_numeric": 2.7151179019981284, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_XRP-USD=0.0000, w_CSHI=0.9853, w_PPLT=0.0147\nPortfolio annualized return: 6.07%, volatility: 0.76%\nSharpe ratio: (0.0607 - 0.0400) / 0.0076 = 2.7151", "metadata": {"weights": {"XLB": 0.0, "XRP-USD": 0.0, "CSHI": 0.9853, "PPLT": 0.0147}, "sharpe_ratio": 2.7151, "portfolio_return": 0.06069, "portfolio_vol": 0.00762, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240711_0842", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "AVAX-USD", "STIP", "SGOV"], "decision_date": "2024-07-11", "context_summary": "4-asset optimization. Max-Sharpe: 8.493. Portfolio: return=6.80%, vol=0.33%. Weights: w_SPY=0.0332, w_AVAX-USD=0.0000, w_STIP=0.0262, w_SGOV=0.9406.", "question": "Assets: SPY, AVAX-USD, STIP, SGOV\nAnnualized mean returns: SPY:0.4918, AVAX-USD:-0.3498, STIP:0.0837, SGOV:0.0526\nCovariance matrix (annualized):\n[[0.005622, 0.010007, 0.000459, -2.5e-05], [0.010007, 0.483684, 0.002279, -0.000359], [0.000459, 0.002279, 0.000249, -5e-06], [-2.5e-05, -0.000359, -5e-06, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0332, w_AVAX-USD=0.0000, w_STIP=0.0262, w_SGOV=0.9406", "answer_numeric": 8.49269715264418, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0332, w_AVAX-USD=0.0000, w_STIP=0.0262, w_SGOV=0.9406\nPortfolio annualized return: 6.80%, volatility: 0.33%\nSharpe ratio: (0.0680 - 0.0400) / 0.0033 = 8.4927", "metadata": {"weights": {"SPY": 0.0332, "AVAX-USD": 0.0, "STIP": 0.0262, "SGOV": 0.9406}, "sharpe_ratio": 8.4927, "portfolio_return": 0.067997, "portfolio_vol": 0.003297, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241115_0844", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SOL-USD", "JNK", "SGOV"], "decision_date": "2024-11-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.378. Portfolio: return=5.39%, vol=0.41%. Weights: w_VEA=0.0000, w_SOL-USD=0.0053, w_JNK=0.0000, w_SGOV=0.9947.", "question": "Assets: VEA, SOL-USD, JNK, SGOV\nAnnualized mean returns: VEA:-0.2606, SOL-USD:1.6786, JNK:0.0254, SGOV:0.0453\nCovariance matrix (annualized):\n[[0.017681, 0.032005, 0.002186, 1e-05], [0.032005, 0.380466, 0.010985, -6e-06], [0.002186, 0.010985, 0.001224, 2.3e-05], [1e-05, -6e-06, 2.3e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_SOL-USD=0.0053, w_JNK=0.0000, w_SGOV=0.9947", "answer_numeric": 3.378472472913323, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_SOL-USD=0.0053, w_JNK=0.0000, w_SGOV=0.9947\nPortfolio annualized return: 5.39%, volatility: 0.41%\nSharpe ratio: (0.0539 - 0.0400) / 0.0041 = 3.3785", "metadata": {"weights": {"VEA": 0.0, "SOL-USD": 0.0053, "JNK": 0.0, "SGOV": 0.9947}, "sharpe_ratio": 3.3785, "portfolio_return": 0.053913, "portfolio_vol": 0.004118, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230802_0846", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "LINK-USD", "JNK", "PPLT"], "decision_date": "2023-08-02", "context_summary": "4-asset optimization. Max-Sharpe: 5.343. Portfolio: return=77.49%, vol=13.75%. Weights: w_VLUE=0.8774, w_LINK-USD=0.1226, w_JNK=0.0000, w_PPLT=0.0000.", "question": "Assets: VLUE, LINK-USD, JNK, PPLT\nAnnualized mean returns: VLUE:0.4844, LINK-USD:2.8533, JNK:0.0941, PPLT:-0.4414\nCovariance matrix (annualized):\n[[0.013367, -0.002362, 0.003646, 0.005278], [-0.002362, 0.607295, 0.00315, -0.011528], [0.003646, 0.00315, 0.004257, 0.008384], [0.005278, -0.011528, 0.008384, 0.049939]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.8774, w_LINK-USD=0.1226, w_JNK=0.0000, w_PPLT=0.0000", "answer_numeric": 5.343474511378792, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.8774, w_LINK-USD=0.1226, w_JNK=0.0000, w_PPLT=0.0000\nPortfolio annualized return: 77.49%, volatility: 13.75%\nSharpe ratio: (0.7749 - 0.0400) / 0.1375 = 5.3435", "metadata": {"weights": {"VLUE": 0.8774, "LINK-USD": 0.1226, "JNK": 0.0, "PPLT": 0.0}, "sharpe_ratio": 5.3435, "portfolio_return": 0.774919, "portfolio_vol": 0.137536, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230323_0848", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ADA-USD", "PDBC", "CSHI"], "decision_date": "2023-03-23", "context_summary": "4-asset optimization. Max-Sharpe: 1.707. Portfolio: return=6.38%, vol=1.40%. Weights: w_IWM=0.0000, w_ADA-USD=0.0000, w_PDBC=0.0000, w_CSHI=1.0000.", "question": "Assets: IWM, ADA-USD, PDBC, CSHI\nAnnualized mean returns: IWM:-0.4510, ADA-USD:-0.2406, PDBC:-0.5461, CSHI:0.0638\nCovariance matrix (annualized):\n[[0.05521, 0.048243, 0.00764, 0.000904], [0.048243, 0.461579, 0.019159, 0.000503], [0.00764, 0.019159, 0.031792, -6.2e-05], [0.000904, 0.000503, -6.2e-05, 0.000195]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_ADA-USD=0.0000, w_PDBC=0.0000, w_CSHI=1.0000", "answer_numeric": 1.7074772697114213, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_ADA-USD=0.0000, w_PDBC=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 6.38%, volatility: 1.40%\nSharpe ratio: (0.0638 - 0.0400) / 0.0140 = 1.7075", "metadata": {"weights": {"IWM": 0.0, "ADA-USD": 0.0, "PDBC": 0.0, "CSHI": 1.0}, "sharpe_ratio": 1.7075, "portfolio_return": 0.063833, "portfolio_vol": 0.013958, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240419_0850", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "CSHI", "SCHH"], "decision_date": "2024-04-19", "context_summary": "4-asset optimization. Max-Sharpe: 1.613. Portfolio: return=5.10%, vol=0.68%. Weights: w_VLUE=0.0000, w_XRP-USD=0.0000, w_CSHI=1.0000, w_SCHH=0.0000.", "question": "Assets: VLUE, XRP-USD, CSHI, SCHH\nAnnualized mean returns: VLUE:-0.0049, XRP-USD:-0.2934, CSHI:0.0510, SCHH:-0.2980\nCovariance matrix (annualized):\n[[0.013613, 0.030444, 0.000135, 0.015705], [0.030444, 0.561787, 0.001439, 0.023324], [0.000135, 0.001439, 4.7e-05, -2.7e-05], [0.015705, 0.023324, -2.7e-05, 0.028691]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_XRP-USD=0.0000, w_CSHI=1.0000, w_SCHH=0.0000", "answer_numeric": 1.61279366937111, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_XRP-USD=0.0000, w_CSHI=1.0000, w_SCHH=0.0000\nPortfolio annualized return: 5.10%, volatility: 0.68%\nSharpe ratio: (0.0510 - 0.0400) / 0.0068 = 1.6128", "metadata": {"weights": {"VLUE": 0.0, "XRP-USD": 0.0, "CSHI": 1.0, "SCHH": 0.0}, "sharpe_ratio": 1.6128, "portfolio_return": 0.051035, "portfolio_vol": 0.006842, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240131_0851", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "HYG", "MORT"], "decision_date": "2024-01-31", "context_summary": "4-asset optimization. Max-Sharpe: 5.504. Portfolio: return=67.04%, vol=11.45%. Weights: w_XLF=0.9447, w_SOL-USD=0.0553, w_HYG=0.0000, w_MORT=0.0000.", "question": "Assets: XLF, SOL-USD, HYG, MORT\nAnnualized mean returns: XLF:0.5583, SOL-USD:2.5850, HYG:0.1698, MORT:0.2102\nCovariance matrix (annualized):\n[[0.011248, 0.002881, 0.002885, 0.015978], [0.002881, 0.908697, 0.003374, 0.040433], [0.002885, 0.003374, 0.003428, 0.009811], [0.015978, 0.040433, 0.009811, 0.053869]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.9447, w_SOL-USD=0.0553, w_HYG=0.0000, w_MORT=0.0000", "answer_numeric": 5.50385179929641, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.9447, w_SOL-USD=0.0553, w_HYG=0.0000, w_MORT=0.0000\nPortfolio annualized return: 67.04%, volatility: 11.45%\nSharpe ratio: (0.6704 - 0.0400) / 0.1145 = 5.5039", "metadata": {"weights": {"XLF": 0.9447, "SOL-USD": 0.0553, "HYG": 0.0, "MORT": 0.0}, "sharpe_ratio": 5.5039, "portfolio_return": 0.670351, "portfolio_vol": 0.114529, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230221_0852", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "CSHI", "SCHP"], "decision_date": "2023-02-21", "context_summary": "4-asset optimization. Max-Sharpe: 3.652. Portfolio: return=8.21%, vol=1.15%. Weights: w_MTUM=0.0000, w_LINK-USD=0.0088, w_CSHI=0.9912, w_SCHP=0.0000.", "question": "Assets: MTUM, LINK-USD, CSHI, SCHP\nAnnualized mean returns: MTUM:-0.1227, LINK-USD:1.4289, CSHI:0.0701, SCHP:0.0253\nCovariance matrix (annualized):\n[[0.020462, 0.018168, 0.000422, -0.000263], [0.018168, 0.331499, 0.00147, 0.001615], [0.000422, 0.00147, 8.3e-05, 4.3e-05], [-0.000263, 0.001615, 4.3e-05, 0.004978]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_LINK-USD=0.0088, w_CSHI=0.9912, w_SCHP=0.0000", "answer_numeric": 3.6524538677189624, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_LINK-USD=0.0088, w_CSHI=0.9912, w_SCHP=0.0000\nPortfolio annualized return: 8.21%, volatility: 1.15%\nSharpe ratio: (0.0821 - 0.0400) / 0.0115 = 3.6525", "metadata": {"weights": {"MTUM": 0.0, "LINK-USD": 0.0088, "CSHI": 0.9912, "SCHP": 0.0}, "sharpe_ratio": 3.6525, "portfolio_return": 0.082109, "portfolio_vol": 0.011529, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240308_0853", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNB-USD", "GLD", "ICSH"], "decision_date": "2024-03-08", "context_summary": "4-asset optimization. Max-Sharpe: 6.150. Portfolio: return=9.50%, vol=0.89%. Weights: w_SPY=0.0395, w_BNB-USD=0.0091, w_GLD=0.0000, w_ICSH=0.9513.", "question": "Assets: SPY, BNB-USD, GLD, ICSH\nAnnualized mean returns: SPY:0.5730, BNB-USD:2.1421, GLD:0.3325, ICSH:0.0554\nCovariance matrix (annualized):\n[[0.013636, 0.018803, 0.003104, 6.7e-05], [0.018803, 0.280285, 0.010088, -0.000265], [0.003104, 0.010088, 0.011889, 0.000305], [6.7e-05, -0.000265, 0.000305, 2.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0395, w_BNB-USD=0.0091, w_GLD=0.0000, w_ICSH=0.9513", "answer_numeric": 6.1496816493630355, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0395, w_BNB-USD=0.0091, w_GLD=0.0000, w_ICSH=0.9513\nPortfolio annualized return: 9.50%, volatility: 0.89%\nSharpe ratio: (0.0950 - 0.0400) / 0.0089 = 6.1497", "metadata": {"weights": {"SPY": 0.0395, "BNB-USD": 0.0091, "GLD": 0.0, "ICSH": 0.9513}, "sharpe_ratio": 6.1497, "portfolio_return": 0.094979, "portfolio_vol": 0.00894, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240426_0854", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "SLV", "CSHI"], "decision_date": "2024-04-26", "context_summary": "4-asset optimization. Max-Sharpe: 4.090. Portfolio: return=11.21%, vol=1.76%. Weights: w_IVV=0.0000, w_SOL-USD=0.0013, w_SLV=0.0557, w_CSHI=0.9430.", "question": "Assets: IVV, SOL-USD, SLV, CSHI\nAnnualized mean returns: IVV:-0.0335, SOL-USD:0.7750, SLV:1.0997, CSHI:0.0529\nCovariance matrix (annualized):\n[[0.012124, 0.024711, 0.000787, 0.000222], [0.024711, 0.799869, 0.022523, 0.00094], [0.000787, 0.022523, 0.079815, 9.9e-05], [0.000222, 0.00094, 9.9e-05, 5.2e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_SOL-USD=0.0013, w_SLV=0.0557, w_CSHI=0.9430", "answer_numeric": 4.0903910930338965, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_SOL-USD=0.0013, w_SLV=0.0557, w_CSHI=0.9430\nPortfolio annualized return: 11.21%, volatility: 1.76%\nSharpe ratio: (0.1121 - 0.0400) / 0.0176 = 4.0904", "metadata": {"weights": {"IVV": 0.0, "SOL-USD": 0.0013, "SLV": 0.0557, "CSHI": 0.943}, "sharpe_ratio": 4.0904, "portfolio_return": 0.112095, "portfolio_vol": 0.017625, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241028_0855", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "TLT", "USO"], "decision_date": "2024-10-28", "context_summary": "4-asset optimization. Max-Sharpe: 1.682. Portfolio: return=65.91%, vol=36.80%. Weights: w_XLV=0.0000, w_BTC-USD=1.0000, w_TLT=0.0000, w_USO=0.0000.", "question": "Assets: XLV, BTC-USD, TLT, USO\nAnnualized mean returns: XLV:-0.2680, BTC-USD:0.6591, TLT:-0.3224, USO:-0.0387\nCovariance matrix (annualized):\n[[0.009289, 0.009565, 0.001115, -0.006499], [0.009565, 0.135402, 0.001984, -0.011426], [0.001115, 0.001984, 0.014657, -0.014581], [-0.006499, -0.011426, -0.014581, 0.130596]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_BTC-USD=1.0000, w_TLT=0.0000, w_USO=0.0000", "answer_numeric": 1.6824822225154772, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_BTC-USD=1.0000, w_TLT=0.0000, w_USO=0.0000\nPortfolio annualized return: 65.91%, volatility: 36.80%\nSharpe ratio: (0.6591 - 0.0400) / 0.3680 = 1.6825", "metadata": {"weights": {"XLV": 0.0, "BTC-USD": 1.0, "TLT": 0.0, "USO": 0.0}, "sharpe_ratio": 1.6825, "portfolio_return": 0.659102, "portfolio_vol": 0.36797, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20240605_0856", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD", "DBB", "REZ"], "decision_date": "2024-06-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.304. Portfolio: return=46.13%, vol=12.75%. Weights: w_ACWI=0.0000, w_DOT-USD=0.0000, w_DBB=0.5399, w_REZ=0.4601.", "question": "Assets: ACWI, DOT-USD, DBB, REZ\nAnnualized mean returns: ACWI:0.1071, DOT-USD:-1.0432, DBB:0.5069, REZ:0.4077\nCovariance matrix (annualized):\n[[0.012563, 0.030825, 0.000851, 0.013771], [0.030825, 0.391532, 0.014444, 0.037791], [0.000851, 0.014444, 0.034217, -0.000996], [0.013771, 0.037791, -0.000996, 0.032001]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_DOT-USD=0.0000, w_DBB=0.5399, w_REZ=0.4601", "answer_numeric": 3.3043094386824836, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_DOT-USD=0.0000, w_DBB=0.5399, w_REZ=0.4601\nPortfolio annualized return: 46.13%, volatility: 12.75%\nSharpe ratio: (0.4613 - 0.0400) / 0.1275 = 3.3043", "metadata": {"weights": {"ACWI": 0.0, "DOT-USD": 0.0, "DBB": 0.5399, "REZ": 0.4601}, "sharpe_ratio": 3.3043, "portfolio_return": 0.461263, "portfolio_vol": 0.127489, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230921_0858", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "LINK-USD", "ICSH", "SHY"], "decision_date": "2023-09-21", "context_summary": "4-asset optimization. Max-Sharpe: 3.910. Portfolio: return=5.65%, vol=0.42%. Weights: w_USMV=0.0000, w_LINK-USD=0.0000, w_ICSH=1.0000, w_SHY=0.0000.", "question": "Assets: USMV, LINK-USD, ICSH, SHY\nAnnualized mean returns: USMV:-0.0605, LINK-USD:-0.0411, ICSH:0.0565, SHY:0.0044\nCovariance matrix (annualized):\n[[0.005317, 0.008094, -7e-06, 0.000221], [0.008094, 0.247085, 7.6e-05, -7.4e-05], [-7e-06, 7.6e-05, 1.8e-05, 3.6e-05], [0.000221, -7.4e-05, 3.6e-05, 0.000228]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_LINK-USD=0.0000, w_ICSH=1.0000, w_SHY=0.0000", "answer_numeric": 3.9104916867379425, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_LINK-USD=0.0000, w_ICSH=1.0000, w_SHY=0.0000\nPortfolio annualized return: 5.65%, volatility: 0.42%\nSharpe ratio: (0.0565 - 0.0400) / 0.0042 = 3.9105", "metadata": {"weights": {"USMV": 0.0, "LINK-USD": 0.0, "ICSH": 1.0, "SHY": 0.0}, "sharpe_ratio": 3.9105, "portfolio_return": 0.056477, "portfolio_vol": 0.004214, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230712_0859", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "PALL", "BIL"], "decision_date": "2023-07-12", "context_summary": "4-asset optimization. Max-Sharpe: 3.877. Portfolio: return=5.14%, vol=0.29%. Weights: w_XLRE=0.0044, w_ADA-USD=0.0000, w_PALL=0.0000, w_BIL=0.9956.", "question": "Assets: XLRE, ADA-USD, PALL, BIL\nAnnualized mean returns: XLRE:0.2777, ADA-USD:-0.9384, PALL:-1.1713, BIL:0.0504\nCovariance matrix (annualized):\n[[0.028035, -0.003213, 0.019938, 5.6e-05], [-0.003213, 0.278112, 0.00094, 9.5e-05], [0.019938, 0.00094, 0.078011, -1.9e-05], [5.6e-05, 9.5e-05, -1.9e-05, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0044, w_ADA-USD=0.0000, w_PALL=0.0000, w_BIL=0.9956", "answer_numeric": 3.8767963710155935, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0044, w_ADA-USD=0.0000, w_PALL=0.0000, w_BIL=0.9956\nPortfolio annualized return: 5.14%, volatility: 0.29%\nSharpe ratio: (0.0514 - 0.0400) / 0.0029 = 3.8768", "metadata": {"weights": {"XLRE": 0.0044, "ADA-USD": 0.0, "PALL": 0.0, "BIL": 0.9956}, "sharpe_ratio": 3.8768, "portfolio_return": 0.051378, "portfolio_vol": 0.002935, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240228_0861", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BNB-USD", "SGOV", "REZ"], "decision_date": "2024-02-28", "context_summary": "4-asset optimization. Max-Sharpe: 6.603. Portfolio: return=6.43%, vol=0.37%. Weights: w_MTUM=0.0078, w_BNB-USD=0.0031, w_SGOV=0.9892, w_REZ=0.0000.", "question": "Assets: MTUM, BNB-USD, SGOV, REZ\nAnnualized mean returns: MTUM:0.8647, BNB-USD:1.1953, SGOV:0.0545, REZ:-0.3952\nCovariance matrix (annualized):\n[[0.0351, 0.005381, 0.000173, 0.006051], [0.005381, 0.142553, 0.000167, 0.018085], [0.000173, 0.000167, 6e-06, 0.000105], [0.006051, 0.018085, 0.000105, 0.031431]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0078, w_BNB-USD=0.0031, w_SGOV=0.9892, w_REZ=0.0000", "answer_numeric": 6.603442502460363, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0078, w_BNB-USD=0.0031, w_SGOV=0.9892, w_REZ=0.0000\nPortfolio annualized return: 6.43%, volatility: 0.37%\nSharpe ratio: (0.0643 - 0.0400) / 0.0037 = 6.6034", "metadata": {"weights": {"MTUM": 0.0078, "BNB-USD": 0.0031, "SGOV": 0.9892, "REZ": 0.0}, "sharpe_ratio": 6.6034, "portfolio_return": 0.064344, "portfolio_vol": 0.003687, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241031_0863", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD", "CORN", "SGOV"], "decision_date": "2024-10-31", "context_summary": "4-asset optimization. Max-Sharpe: 3.378. Portfolio: return=4.86%, vol=0.25%. Weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_CORN=0.0000, w_SGOV=1.0000.", "question": "Assets: VEA, AVAX-USD, CORN, SGOV\nAnnualized mean returns: VEA:-0.2088, AVAX-USD:0.2661, CORN:0.0608, SGOV:0.0486\nCovariance matrix (annualized):\n[[0.01794, 0.046117, -0.002549, -4.7e-05], [0.046117, 0.350146, -0.015052, 0.000322], [-0.002549, -0.015052, 0.020795, 1.5e-05], [-4.7e-05, 0.000322, 1.5e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_AVAX-USD=0.0000, w_CORN=0.0000, w_SGOV=1.0000", "answer_numeric": 3.377767185481004, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_CORN=0.0000, w_SGOV=1.0000\nPortfolio annualized return: 4.86%, volatility: 0.25%\nSharpe ratio: (0.0486 - 0.0400) / 0.0025 = 3.3778", "metadata": {"weights": {"VEA": 0.0, "AVAX-USD": 0.0, "CORN": 0.0, "SGOV": 1.0}, "sharpe_ratio": 3.3778, "portfolio_return": 0.048606, "portfolio_vol": 0.002548, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9047}} +{"id": "T5_all_20230817_0865", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ADA-USD", "CSHI", "JNK"], "decision_date": "2023-08-17", "context_summary": "4-asset optimization. Max-Sharpe: 1.651. Portfolio: return=5.49%, vol=0.90%. Weights: w_XLU=0.0000, w_ADA-USD=0.0021, w_CSHI=0.9979, w_JNK=0.0000.", "question": "Assets: XLU, ADA-USD, CSHI, JNK\nAnnualized mean returns: XLU:-0.3274, ADA-USD:0.6599, CSHI:0.0537, JNK:0.0240\nCovariance matrix (annualized):\n[[0.025583, 0.018734, 0.000354, 0.003112], [0.018734, 0.518898, 0.002315, 0.012858], [0.000354, 0.002315, 7e-05, 8.6e-05], [0.003112, 0.012858, 8.6e-05, 0.004066]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_ADA-USD=0.0021, w_CSHI=0.9979, w_JNK=0.0000", "answer_numeric": 1.650683065768251, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_ADA-USD=0.0021, w_CSHI=0.9979, w_JNK=0.0000\nPortfolio annualized return: 5.49%, volatility: 0.90%\nSharpe ratio: (0.0549 - 0.0400) / 0.0090 = 1.6507", "metadata": {"weights": {"XLU": 0.0, "ADA-USD": 0.0021, "CSHI": 0.9979, "JNK": 0.0}, "sharpe_ratio": 1.6507, "portfolio_return": 0.054932, "portfolio_vol": 0.009046, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240712_0866", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "UNG", "SCHH"], "decision_date": "2024-07-12", "context_summary": "4-asset optimization. Max-Sharpe: 4.783. Portfolio: return=38.96%, vol=7.31%. Weights: w_QUAL=0.7292, w_ETH-USD=0.0000, w_UNG=0.0000, w_SCHH=0.2708.", "question": "Assets: QUAL, ETH-USD, UNG, SCHH\nAnnualized mean returns: QUAL:0.3826, ETH-USD:0.2476, UNG:-0.3338, SCHH:0.4086\nCovariance matrix (annualized):\n[[0.006979, 0.007898, 0.005892, 0.000544], [0.007898, 0.280033, 0.043483, 0.001556], [0.005892, 0.043483, 0.349623, -0.006192], [0.000544, 0.001556, -0.006192, 0.019342]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.7292, w_ETH-USD=0.0000, w_UNG=0.0000, w_SCHH=0.2708", "answer_numeric": 4.782778546440399, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.7292, w_ETH-USD=0.0000, w_UNG=0.0000, w_SCHH=0.2708\nPortfolio annualized return: 38.96%, volatility: 7.31%\nSharpe ratio: (0.3896 - 0.0400) / 0.0731 = 4.7828", "metadata": {"weights": {"QUAL": 0.7292, "ETH-USD": 0.0, "UNG": 0.0, "SCHH": 0.2708}, "sharpe_ratio": 4.7828, "portfolio_return": 0.38963, "portfolio_vol": 0.073102, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230228_0867", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "MATIC-USD", "SOYB", "EMB"], "decision_date": "2023-02-28", "context_summary": "4-asset optimization. Max-Sharpe: 3.368. Portfolio: return=261.12%, vol=76.33%. Weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_SOYB=0.0000, w_EMB=0.0000.", "question": "Assets: XLU, MATIC-USD, SOYB, EMB\nAnnualized mean returns: XLU:-0.4726, MATIC-USD:2.6112, SOYB:-0.0803, EMB:0.0533\nCovariance matrix (annualized):\n[[0.02795, 0.037088, 0.002469, 0.00603], [0.037088, 0.582641, 0.003459, 0.018321], [0.002469, 0.003459, 0.013849, -0.002126], [0.00603, 0.018321, -0.002126, 0.017504]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_MATIC-USD=1.0000, w_SOYB=0.0000, w_EMB=0.0000", "answer_numeric": 3.3684575072371223, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_SOYB=0.0000, w_EMB=0.0000\nPortfolio annualized return: 261.12%, volatility: 76.33%\nSharpe ratio: (2.6112 - 0.0400) / 0.7633 = 3.3685", "metadata": {"weights": {"XLU": 0.0, "MATIC-USD": 1.0, "SOYB": 0.0, "EMB": 0.0}, "sharpe_ratio": 3.3685, "portfolio_return": 2.611175, "portfolio_vol": 0.763309, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240830_0869", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "ADA-USD", "SGOV", "VCIT"], "decision_date": "2024-08-30", "context_summary": "4-asset optimization. Max-Sharpe: 5.593. Portfolio: return=5.75%, vol=0.31%. Weights: w_XLK=0.0000, w_ADA-USD=0.0008, w_SGOV=0.9702, w_VCIT=0.0290.", "question": "Assets: XLK, ADA-USD, SGOV, VCIT\nAnnualized mean returns: XLK:-0.2570, ADA-USD:0.9003, SGOV:0.0509, VCIT:0.2566\nCovariance matrix (annualized):\n[[0.098053, 0.056794, 0.0001, 0.002563], [0.056794, 0.385869, 0.000218, -0.00183], [0.0001, 0.000218, 5e-06, 5e-05], [0.002563, -0.00183, 5e-05, 0.002572]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.0000, w_ADA-USD=0.0008, w_SGOV=0.9702, w_VCIT=0.0290", "answer_numeric": 5.59333656420441, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_ADA-USD=0.0008, w_SGOV=0.9702, w_VCIT=0.0290\nPortfolio annualized return: 5.75%, volatility: 0.31%\nSharpe ratio: (0.0575 - 0.0400) / 0.0031 = 5.5933", "metadata": {"weights": {"XLK": 0.0, "ADA-USD": 0.0008, "SGOV": 0.9702, "VCIT": 0.029}, "sharpe_ratio": 5.5933, "portfolio_return": 0.05754, "portfolio_vol": 0.003136, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230331_0871", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "XRP-USD", "BIL", "SHV"], "decision_date": "2023-03-31", "context_summary": "4-asset optimization. Max-Sharpe: 3.722. Portfolio: return=5.03%, vol=0.28%. Weights: w_XLU=0.0000, w_XRP-USD=0.0028, w_BIL=0.9972, w_SHV=0.0000.", "question": "Assets: XLU, XRP-USD, BIL, SHV\nAnnualized mean returns: XLU:-0.1242, XRP-USD:1.7633, BIL:0.0455, SHV:0.0410\nCovariance matrix (annualized):\n[[0.040396, -0.018107, 7.1e-05, -1.1e-05], [-0.018107, 0.673293, -0.000606, -0.001086], [7.1e-05, -0.000606, 6e-06, 5e-06], [-1.1e-05, -0.001086, 5e-06, 1.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_XRP-USD=0.0028, w_BIL=0.9972, w_SHV=0.0000", "answer_numeric": 3.721617132244519, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_XRP-USD=0.0028, w_BIL=0.9972, w_SHV=0.0000\nPortfolio annualized return: 5.03%, volatility: 0.28%\nSharpe ratio: (0.0503 - 0.0400) / 0.0028 = 3.7216", "metadata": {"weights": {"XLU": 0.0, "XRP-USD": 0.0028, "BIL": 0.9972, "SHV": 0.0}, "sharpe_ratio": 3.7216, "portfolio_return": 0.050302, "portfolio_vol": 0.002768, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230501_0873", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SOL-USD", "SGOV", "TIP"], "decision_date": "2023-05-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.887. Portfolio: return=5.52%, vol=0.39%. Weights: w_VEA=0.0179, w_SOL-USD=0.0000, w_SGOV=0.9150, w_TIP=0.0671.", "question": "Assets: VEA, SOL-USD, SGOV, TIP\nAnnualized mean returns: VEA:0.2981, SOL-USD:-0.1497, SGOV:0.0467, TIP:0.1070\nCovariance matrix (annualized):\n[[0.023364, 0.020174, -3.3e-05, -0.001915], [0.020174, 0.499613, -0.000137, 0.002893], [-3.3e-05, -0.000137, 7e-06, 9e-06], [-0.001915, 0.002893, 9e-06, 0.001392]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0179, w_SOL-USD=0.0000, w_SGOV=0.9150, w_TIP=0.0671", "answer_numeric": 3.8872746624270587, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0179, w_SOL-USD=0.0000, w_SGOV=0.9150, w_TIP=0.0671\nPortfolio annualized return: 5.52%, volatility: 0.39%\nSharpe ratio: (0.0552 - 0.0400) / 0.0039 = 3.8873", "metadata": {"weights": {"VEA": 0.0179, "SOL-USD": 0.0, "SGOV": 0.915, "TIP": 0.0671}, "sharpe_ratio": 3.8873, "portfolio_return": 0.055215, "portfolio_vol": 0.003914, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231110_0875", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "MORT", "SLV"], "decision_date": "2023-11-10", "context_summary": "4-asset optimization. Max-Sharpe: 5.894. Portfolio: return=382.39%, vol=64.20%. Weights: w_QUAL=0.0000, w_SOL-USD=1.0000, w_MORT=0.0000, w_SLV=0.0000.", "question": "Assets: QUAL, SOL-USD, MORT, SLV\nAnnualized mean returns: QUAL:-0.0548, SOL-USD:3.8239, MORT:-0.5078, SLV:-0.0633\nCovariance matrix (annualized):\n[[0.021005, 0.00063, 0.028147, -0.002602], [0.00063, 0.412143, 0.006943, -0.004366], [0.028147, 0.006943, 0.085614, 0.005005], [-0.002602, -0.004366, 0.005005, 0.05018]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_SOL-USD=1.0000, w_MORT=0.0000, w_SLV=0.0000", "answer_numeric": 5.894108413613668, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_SOL-USD=1.0000, w_MORT=0.0000, w_SLV=0.0000\nPortfolio annualized return: 382.39%, volatility: 64.20%\nSharpe ratio: (3.8239 - 0.0400) / 0.6420 = 5.8941", "metadata": {"weights": {"QUAL": 0.0, "SOL-USD": 1.0, "MORT": 0.0, "SLV": 0.0}, "sharpe_ratio": 5.8941, "portfolio_return": 3.823919, "portfolio_vol": 0.641983, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240516_0876", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "ADA-USD", "REZ", "IEF"], "decision_date": "2024-05-16", "context_summary": "4-asset optimization. Max-Sharpe: 4.153. Portfolio: return=85.53%, vol=19.63%. Weights: w_FXI=0.8061, w_ADA-USD=0.0000, w_REZ=0.1939, w_IEF=0.0000.", "question": "Assets: FXI, ADA-USD, REZ, IEF\nAnnualized mean returns: FXI:0.9495, ADA-USD:-2.3439, REZ:0.4636, IEF:0.0509\nCovariance matrix (annualized):\n[[0.049268, 0.060815, 0.016962, 0.000709], [0.060815, 0.414922, 0.034774, 0.002929], [0.016962, 0.034774, 0.032787, 0.006447], [0.000709, 0.002929, 0.006447, 0.004327]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.8061, w_ADA-USD=0.0000, w_REZ=0.1939, w_IEF=0.0000", "answer_numeric": 4.152588214375112, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.8061, w_ADA-USD=0.0000, w_REZ=0.1939, w_IEF=0.0000\nPortfolio annualized return: 85.53%, volatility: 19.63%\nSharpe ratio: (0.8553 - 0.0400) / 0.1963 = 4.1526", "metadata": {"weights": {"FXI": 0.8061, "ADA-USD": 0.0, "REZ": 0.1939, "IEF": 0.0}, "sharpe_ratio": 4.1526, "portfolio_return": 0.855329, "portfolio_vol": 0.196342, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240422_0877", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "BIL", "ITB"], "decision_date": "2024-04-22", "context_summary": "4-asset optimization. Max-Sharpe: 5.056. Portfolio: return=5.30%, vol=0.26%. Weights: w_EFA=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_ITB=0.0000.", "question": "Assets: EFA, AVAX-USD, BIL, ITB\nAnnualized mean returns: EFA:-0.0258, AVAX-USD:-0.5338, BIL:0.0530, ITB:-0.0024\nCovariance matrix (annualized):\n[[0.010442, 0.028429, 5.9e-05, 0.01796], [0.028429, 0.896193, 0.000143, 0.026794], [5.9e-05, 0.000143, 7e-06, 9e-05], [0.01796, 0.026794, 9e-05, 0.056015]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_ITB=0.0000", "answer_numeric": 5.056253750636657, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_AVAX-USD=0.0000, w_BIL=1.0000, w_ITB=0.0000\nPortfolio annualized return: 5.30%, volatility: 0.26%\nSharpe ratio: (0.0530 - 0.0400) / 0.0026 = 5.0563", "metadata": {"weights": {"EFA": 0.0, "AVAX-USD": 0.0, "BIL": 1.0, "ITB": 0.0}, "sharpe_ratio": 5.0563, "portfolio_return": 0.053017, "portfolio_vol": 0.002574, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240115_0879", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD", "VNQ", "ICSH"], "decision_date": "2024-01-15", "context_summary": "4-asset optimization. Max-Sharpe: 8.779. Portfolio: return=8.15%, vol=0.47%. Weights: w_QUAL=0.0115, w_BTC-USD=0.0019, w_VNQ=0.0000, w_ICSH=0.9866.", "question": "Assets: QUAL, BTC-USD, VNQ, ICSH\nAnnualized mean returns: QUAL:0.4051, BTC-USD:0.5546, VNQ:0.6559, ICSH:0.0769\nCovariance matrix (annualized):\n[[0.007571, 0.004671, 0.007132, 0.000102], [0.004671, 0.2395, 0.026073, -0.000224], [0.007132, 0.026073, 0.029391, 0.000365], [0.000102, -0.000224, 0.000365, 1.9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0115, w_BTC-USD=0.0019, w_VNQ=0.0000, w_ICSH=0.9866", "answer_numeric": 8.778944720842128, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0115, w_BTC-USD=0.0019, w_VNQ=0.0000, w_ICSH=0.9866\nPortfolio annualized return: 8.15%, volatility: 0.47%\nSharpe ratio: (0.0815 - 0.0400) / 0.0047 = 8.7789", "metadata": {"weights": {"QUAL": 0.0115, "BTC-USD": 0.0019, "VNQ": 0.0, "ICSH": 0.9866}, "sharpe_ratio": 8.7789, "portfolio_return": 0.08155, "portfolio_vol": 0.004733, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240923_0880", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "DOT-USD", "SHV", "XHB"], "decision_date": "2024-09-23", "context_summary": "4-asset optimization. Max-Sharpe: 0.030. Portfolio: return=4.63%, vol=21.26%. Weights: w_EEM=0.2500, w_DOT-USD=0.2500, w_SHV=0.2500, w_XHB=0.2500.", "question": "Assets: EEM, DOT-USD, SHV, XHB\nAnnualized mean returns: EEM:0.2279, DOT-USD:-0.7218, SHV:0.0570, XHB:0.6224\nCovariance matrix (annualized):\n[[0.032206, 0.053862, -3.2e-05, 0.034937], [0.053862, 0.267854, 0.000155, 0.079399], [-3.2e-05, 0.000155, 7e-06, 5.5e-05], [0.034937, 0.079399, 5.5e-05, 0.086384]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.2500, w_DOT-USD=0.2500, w_SHV=0.2500, w_XHB=0.2500", "answer_numeric": 0.029854599862850294, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.2500, w_DOT-USD=0.2500, w_SHV=0.2500, w_XHB=0.2500\nPortfolio annualized return: 4.63%, volatility: 21.26%\nSharpe ratio: (0.0463 - 0.0400) / 0.2126 = 0.0299", "metadata": {"weights": {"EEM": 0.25, "DOT-USD": 0.25, "SHV": 0.25, "XHB": 0.25}, "sharpe_ratio": 0.0299, "portfolio_return": 0.046347, "portfolio_vol": 0.212604, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230825_0881", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ETH-USD", "DBA", "TLH"], "decision_date": "2023-08-25", "context_summary": "4-asset optimization. Max-Sharpe: 0.853. Portfolio: return=13.30%, vol=10.89%. Weights: w_XLI=1.0000, w_ETH-USD=0.0000, w_DBA=0.0000, w_TLH=0.0000.", "question": "Assets: XLI, ETH-USD, DBA, TLH\nAnnualized mean returns: XLI:0.1330, ETH-USD:-0.6292, DBA:0.0145, TLH:-0.3520\nCovariance matrix (annualized):\n[[0.011868, 0.015918, 0.002265, 0.003808], [0.015918, 0.114933, 0.003519, 0.013499], [0.002265, 0.003519, 0.013078, 0.00306], [0.003808, 0.013499, 0.00306, 0.018424]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=1.0000, w_ETH-USD=0.0000, w_DBA=0.0000, w_TLH=0.0000", "answer_numeric": 0.853314647812356, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=1.0000, w_ETH-USD=0.0000, w_DBA=0.0000, w_TLH=0.0000\nPortfolio annualized return: 13.30%, volatility: 10.89%\nSharpe ratio: (0.1330 - 0.0400) / 0.1089 = 0.8533", "metadata": {"weights": {"XLI": 1.0, "ETH-USD": 0.0, "DBA": 0.0, "TLH": 0.0}, "sharpe_ratio": 0.8533, "portfolio_return": 0.132962, "portfolio_vol": 0.108942, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240603_0883", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "USO", "VNQI"], "decision_date": "2024-06-03", "context_summary": "4-asset optimization. Max-Sharpe: 0.219. Portfolio: return=7.10%, vol=14.18%. Weights: w_EEM=1.0000, w_ETH-USD=0.0000, w_USO=0.0000, w_VNQI=0.0000.", "question": "Assets: EEM, ETH-USD, USO, VNQI\nAnnualized mean returns: EEM:0.0710, ETH-USD:-0.0716, USO:-0.4883, VNQI:0.0016\nCovariance matrix (annualized):\n[[0.020117, 0.02136, 0.002989, 0.017923], [0.02136, 0.373749, 0.024463, 0.021095], [0.002989, 0.024463, 0.036679, 0.000248], [0.017923, 0.021095, 0.000248, 0.024767]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=1.0000, w_ETH-USD=0.0000, w_USO=0.0000, w_VNQI=0.0000", "answer_numeric": 0.21860125818577456, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=1.0000, w_ETH-USD=0.0000, w_USO=0.0000, w_VNQI=0.0000\nPortfolio annualized return: 7.10%, volatility: 14.18%\nSharpe ratio: (0.0710 - 0.0400) / 0.1418 = 0.2186", "metadata": {"weights": {"EEM": 1.0, "ETH-USD": 0.0, "USO": 0.0, "VNQI": 0.0}, "sharpe_ratio": 0.2186, "portfolio_return": 0.071005, "portfolio_vol": 0.141835, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240409_0885", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "DOT-USD", "PALL", "ITB"], "decision_date": "2024-04-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.481. Portfolio: return=61.65%, vol=23.23%. Weights: w_XLV=0.0000, w_DOT-USD=0.0000, w_PALL=0.3456, w_ITB=0.6544.", "question": "Assets: XLV, DOT-USD, PALL, ITB\nAnnualized mean returns: XLV:-0.0370, DOT-USD:0.6115, PALL:0.7881, ITB:0.5259\nCovariance matrix (annualized):\n[[0.01095, 0.011167, 0.006986, 0.015517], [0.011167, 0.502095, 0.149597, 0.016587], [0.006986, 0.149597, 0.148741, 0.028483], [0.015517, 0.016587, 0.028483, 0.054462]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_DOT-USD=0.0000, w_PALL=0.3456, w_ITB=0.6544", "answer_numeric": 2.481481716380845, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_DOT-USD=0.0000, w_PALL=0.3456, w_ITB=0.6544\nPortfolio annualized return: 61.65%, volatility: 23.23%\nSharpe ratio: (0.6165 - 0.0400) / 0.2323 = 2.4815", "metadata": {"weights": {"XLV": 0.0, "DOT-USD": 0.0, "PALL": 0.3456, "ITB": 0.6544}, "sharpe_ratio": 2.4815, "portfolio_return": 0.616484, "portfolio_vol": 0.232315, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240717_0887", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "MATIC-USD", "SCHH", "DBC"], "decision_date": "2024-07-17", "context_summary": "4-asset optimization. Max-Sharpe: 4.307. Portfolio: return=51.88%, vol=11.12%. Weights: w_XLY=0.6512, w_MATIC-USD=0.0000, w_SCHH=0.3488, w_DBC=0.0000.", "question": "Assets: XLY, MATIC-USD, SCHH, DBC\nAnnualized mean returns: XLY:0.5680, MATIC-USD:-1.8355, SCHH:0.4270, DBC:-0.1705\nCovariance matrix (annualized):\n[[0.018429, -0.003577, 0.004656, 0.003486], [-0.003577, 0.325978, 0.000701, -0.002055], [0.004656, 0.000701, 0.019939, 0.000755], [0.003486, -0.002055, 0.000755, 0.018493]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.6512, w_MATIC-USD=0.0000, w_SCHH=0.3488, w_DBC=0.0000", "answer_numeric": 4.3073835744308795, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.6512, w_MATIC-USD=0.0000, w_SCHH=0.3488, w_DBC=0.0000\nPortfolio annualized return: 51.88%, volatility: 11.12%\nSharpe ratio: (0.5188 - 0.0400) / 0.1112 = 4.3074", "metadata": {"weights": {"XLY": 0.6512, "MATIC-USD": 0.0, "SCHH": 0.3488, "DBC": 0.0}, "sharpe_ratio": 4.3074, "portfolio_return": 0.518801, "portfolio_vol": 0.111158, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231124_0888", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "IYR", "PALL"], "decision_date": "2023-11-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.734. Portfolio: return=98.36%, vol=25.27%. Weights: w_EFA=0.4203, w_BTC-USD=0.5797, w_IYR=0.0000, w_PALL=0.0000.", "question": "Assets: EFA, BTC-USD, IYR, PALL\nAnnualized mean returns: EFA:0.1743, BTC-USD:1.5703, IYR:0.0987, PALL:-0.9337\nCovariance matrix (annualized):\n[[0.021487, 9.9e-05, 0.024081, 0.021642], [9.9e-05, 0.178575, -0.010027, 0.004453], [0.024081, -0.010027, 0.049612, 0.028195], [0.021642, 0.004453, 0.028195, 0.097307]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.4203, w_BTC-USD=0.5797, w_IYR=0.0000, w_PALL=0.0000", "answer_numeric": 3.733989055862328, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.4203, w_BTC-USD=0.5797, w_IYR=0.0000, w_PALL=0.0000\nPortfolio annualized return: 98.36%, volatility: 25.27%\nSharpe ratio: (0.9836 - 0.0400) / 0.2527 = 3.7340", "metadata": {"weights": {"EFA": 0.4203, "BTC-USD": 0.5797, "IYR": 0.0, "PALL": 0.0}, "sharpe_ratio": 3.734, "portfolio_return": 0.983604, "portfolio_vol": 0.252707, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240321_0889", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "DOT-USD", "SLV", "MORT"], "decision_date": "2024-03-21", "context_summary": "4-asset optimization. Max-Sharpe: 3.485. Portfolio: return=68.54%, vol=18.52%. Weights: w_XLY=0.3610, w_DOT-USD=0.1057, w_SLV=0.5333, w_MORT=0.0000.", "question": "Assets: XLY, DOT-USD, SLV, MORT\nAnnualized mean returns: XLY:0.2935, DOT-USD:1.7314, SLV:0.7434, MORT:-0.0556\nCovariance matrix (annualized):\n[[0.025376, 0.019281, 0.004265, 0.017146], [0.019281, 0.452598, 0.065793, 0.030158], [0.004265, 0.065793, 0.054168, 0.029963], [0.017146, 0.030158, 0.029963, 0.057039]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.3610, w_DOT-USD=0.1057, w_SLV=0.5333, w_MORT=0.0000", "answer_numeric": 3.4850119637173127, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.3610, w_DOT-USD=0.1057, w_SLV=0.5333, w_MORT=0.0000\nPortfolio annualized return: 68.54%, volatility: 18.52%\nSharpe ratio: (0.6854 - 0.0400) / 0.1852 = 3.4850", "metadata": {"weights": {"XLY": 0.361, "DOT-USD": 0.1057, "SLV": 0.5333, "MORT": 0.0}, "sharpe_ratio": 3.485, "portfolio_return": 0.685416, "portfolio_vol": 0.185198, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240828_0891", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "BTC-USD", "STIP", "GLD"], "decision_date": "2024-08-28", "context_summary": "4-asset optimization. Max-Sharpe: 4.279. Portfolio: return=13.73%, vol=2.27%. Weights: w_XLV=0.0833, w_BTC-USD=0.0000, w_STIP=0.8790, w_GLD=0.0377.", "question": "Assets: XLV, BTC-USD, STIP, GLD\nAnnualized mean returns: XLV:0.4023, BTC-USD:0.3352, STIP:0.0959, GLD:0.5166\nCovariance matrix (annualized):\n[[0.018778, 0.035458, 0.000137, 0.006404], [0.035458, 0.296769, -0.000325, 0.014817], [0.000137, -0.000325, 0.000273, 0.001218], [0.006404, 0.014817, 0.001218, 0.024629]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0833, w_BTC-USD=0.0000, w_STIP=0.8790, w_GLD=0.0377", "answer_numeric": 4.279302152101487, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0833, w_BTC-USD=0.0000, w_STIP=0.8790, w_GLD=0.0377\nPortfolio annualized return: 13.73%, volatility: 2.27%\nSharpe ratio: (0.1373 - 0.0400) / 0.0227 = 4.2793", "metadata": {"weights": {"XLV": 0.0833, "BTC-USD": 0.0, "STIP": 0.879, "GLD": 0.0377}, "sharpe_ratio": 4.2793, "portfolio_return": 0.137323, "portfolio_vol": 0.022743, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230309_0892", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "DOT-USD", "HAUZ", "UNG"], "decision_date": "2023-03-09", "context_summary": "4-asset optimization. Max-Sharpe: 1.122. Portfolio: return=86.99%, vol=73.99%. Weights: w_XLRE=0.0000, w_DOT-USD=1.0000, w_HAUZ=0.0000, w_UNG=0.0000.", "question": "Assets: XLRE, DOT-USD, HAUZ, UNG\nAnnualized mean returns: XLRE:0.0187, DOT-USD:0.8699, HAUZ:-0.1245, UNG:-1.3948\nCovariance matrix (annualized):\n[[0.039157, 0.021031, 0.020562, 0.017607], [0.021031, 0.547407, 0.020596, -0.016749], [0.020562, 0.020596, 0.019206, 0.014366], [0.017607, -0.016749, 0.014366, 0.656941]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_DOT-USD=1.0000, w_HAUZ=0.0000, w_UNG=0.0000", "answer_numeric": 1.1216990506522024, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_DOT-USD=1.0000, w_HAUZ=0.0000, w_UNG=0.0000\nPortfolio annualized return: 86.99%, volatility: 73.99%\nSharpe ratio: (0.8699 - 0.0400) / 0.7399 = 1.1217", "metadata": {"weights": {"XLRE": 0.0, "DOT-USD": 1.0, "HAUZ": 0.0, "UNG": 0.0}, "sharpe_ratio": 1.1217, "portfolio_return": 0.869911, "portfolio_vol": 0.73987, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241025_0893", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "SGOV", "BNDX"], "decision_date": "2024-10-25", "context_summary": "4-asset optimization. Max-Sharpe: 3.892. Portfolio: return=4.98%, vol=0.25%. Weights: w_XLP=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_BNDX=0.0000.", "question": "Assets: XLP, DOT-USD, SGOV, BNDX\nAnnualized mean returns: XLP:0.0239, DOT-USD:-1.0138, SGOV:0.0498, BNDX:0.0307\nCovariance matrix (annualized):\n[[0.007892, 0.010015, 9.1e-05, 0.000971], [0.010015, 0.211001, 0.000186, 0.002033], [9.1e-05, 0.000186, 6e-06, 2.1e-05], [0.000971, 0.002033, 2.1e-05, 0.000997]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_BNDX=0.0000", "answer_numeric": 3.8923569252882486, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_BNDX=0.0000\nPortfolio annualized return: 4.98%, volatility: 0.25%\nSharpe ratio: (0.0498 - 0.0400) / 0.0025 = 3.8924", "metadata": {"weights": {"XLP": 0.0, "DOT-USD": 0.0, "SGOV": 1.0, "BNDX": 0.0}, "sharpe_ratio": 3.8924, "portfolio_return": 0.049804, "portfolio_vol": 0.002519, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20240501_0894", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LINK-USD", "ITB", "PALL"], "decision_date": "2024-05-01", "context_summary": "4-asset optimization. Max-Sharpe: -0.054. Portfolio: return=3.38%, vol=11.64%. Weights: w_XLF=1.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_PALL=0.0000.", "question": "Assets: XLF, LINK-USD, ITB, PALL\nAnnualized mean returns: XLF:0.0338, LINK-USD:-2.8300, ITB:-0.2894, PALL:-0.1255\nCovariance matrix (annualized):\n[[0.013557, 0.02329, 0.017946, 0.009399], [0.02329, 0.415176, 0.018503, 0.077377], [0.017946, 0.018503, 0.06003, 0.023811], [0.009399, 0.077377, 0.023811, 0.12399]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=1.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_PALL=0.0000", "answer_numeric": -0.05351294408624355, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=1.0000, w_LINK-USD=0.0000, w_ITB=0.0000, w_PALL=0.0000\nPortfolio annualized return: 3.38%, volatility: 11.64%\nSharpe ratio: (0.0338 - 0.0400) / 0.1164 = -0.0535", "metadata": {"weights": {"XLF": 1.0, "LINK-USD": 0.0, "ITB": 0.0, "PALL": 0.0}, "sharpe_ratio": -0.0535, "portfolio_return": 0.033769, "portfolio_vol": 0.116435, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240410_0895", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "MATIC-USD", "SOYB", "CSHI"], "decision_date": "2024-04-10", "context_summary": "4-asset optimization. Max-Sharpe: 2.875. Portfolio: return=6.29%, vol=0.80%. Weights: w_SPY=0.0437, w_MATIC-USD=0.0000, w_SOYB=0.0012, w_CSHI=0.9551.", "question": "Assets: SPY, MATIC-USD, SOYB, CSHI\nAnnualized mean returns: SPY:0.2433, MATIC-USD:-0.6941, SOYB:0.0407, CSHI:0.0547\nCovariance matrix (annualized):\n[[0.012029, 0.015785, 0.000481, 4e-05], [0.015785, 0.596982, 0.032121, 0.000307], [0.000481, 0.032121, 0.016067, -4e-05], [4e-05, 0.000307, -4e-05, 4.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0437, w_MATIC-USD=0.0000, w_SOYB=0.0012, w_CSHI=0.9551", "answer_numeric": 2.8751516900386775, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0437, w_MATIC-USD=0.0000, w_SOYB=0.0012, w_CSHI=0.9551\nPortfolio annualized return: 6.29%, volatility: 0.80%\nSharpe ratio: (0.0629 - 0.0400) / 0.0080 = 2.8752", "metadata": {"weights": {"SPY": 0.0437, "MATIC-USD": 0.0, "SOYB": 0.0012, "CSHI": 0.9551}, "sharpe_ratio": 2.8752, "portfolio_return": 0.062934, "portfolio_vol": 0.007977, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240412_0896", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ADA-USD", "SGOV", "SCHH"], "decision_date": "2024-04-12", "context_summary": "4-asset optimization. Max-Sharpe: 6.706. Portfolio: return=5.48%, vol=0.22%. Weights: w_XLF=0.0055, w_ADA-USD=0.0000, w_SGOV=0.9945, w_SCHH=0.0000.", "question": "Assets: XLF, ADA-USD, SGOV, SCHH\nAnnualized mean returns: XLF:0.2515, ADA-USD:0.2490, SGOV:0.0537, SCHH:-0.0280\nCovariance matrix (annualized):\n[[0.013226, 0.019096, -3e-06, 0.014118], [0.019096, 0.523275, 0.000102, 0.038306], [-3e-06, 0.000102, 5e-06, 5.4e-05], [0.014118, 0.038306, 5.4e-05, 0.030974]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0055, w_ADA-USD=0.0000, w_SGOV=0.9945, w_SCHH=0.0000", "answer_numeric": 6.705607610929181, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0055, w_ADA-USD=0.0000, w_SGOV=0.9945, w_SCHH=0.0000\nPortfolio annualized return: 5.48%, volatility: 0.22%\nSharpe ratio: (0.0548 - 0.0400) / 0.0022 = 6.7056", "metadata": {"weights": {"XLF": 0.0055, "ADA-USD": 0.0, "SGOV": 0.9945, "SCHH": 0.0}, "sharpe_ratio": 6.7056, "portfolio_return": 0.054832, "portfolio_vol": 0.002212, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240223_0898", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "SGOV", "MORT"], "decision_date": "2024-02-23", "context_summary": "4-asset optimization. Max-Sharpe: 5.854. Portfolio: return=5.66%, vol=0.28%. Weights: w_VLUE=0.0000, w_BTC-USD=0.0019, w_SGOV=0.9981, w_MORT=0.0000.", "question": "Assets: VLUE, BTC-USD, SGOV, MORT\nAnnualized mean returns: VLUE:0.1064, BTC-USD:0.8587, SGOV:0.0551, MORT:-0.5246\nCovariance matrix (annualized):\n[[0.014035, 0.011106, 9.9e-05, 0.021551], [0.011106, 0.190101, 4e-05, 0.031582], [9.9e-05, 4e-05, 7e-06, 0.00017], [0.021551, 0.031582, 0.00017, 0.061586]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_BTC-USD=0.0019, w_SGOV=0.9981, w_MORT=0.0000", "answer_numeric": 5.853642273209954, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_BTC-USD=0.0019, w_SGOV=0.9981, w_MORT=0.0000\nPortfolio annualized return: 5.66%, volatility: 0.28%\nSharpe ratio: (0.0566 - 0.0400) / 0.0028 = 5.8536", "metadata": {"weights": {"VLUE": 0.0, "BTC-USD": 0.0019, "SGOV": 0.9981, "MORT": 0.0}, "sharpe_ratio": 5.8536, "portfolio_return": 0.05659, "portfolio_vol": 0.002834, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240806_0900", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "LQD", "SOYB"], "decision_date": "2024-08-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.003. Portfolio: return=18.54%, vol=7.26%. Weights: w_XLF=0.0000, w_XRP-USD=0.0000, w_LQD=1.0000, w_SOYB=0.0000.", "question": "Assets: XLF, XRP-USD, LQD, SOYB\nAnnualized mean returns: XLF:-0.0441, XRP-USD:-0.2540, LQD:0.1854, SOYB:-0.5761\nCovariance matrix (annualized):\n[[0.024633, 0.051191, 0.000164, -0.006431], [0.051191, 0.321048, 0.000222, -0.030024], [0.000164, 0.000222, 0.005268, 0.003819], [-0.006431, -0.030024, 0.003819, 0.03409]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_XRP-USD=0.0000, w_LQD=1.0000, w_SOYB=0.0000", "answer_numeric": 2.0025546935503837, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_XRP-USD=0.0000, w_LQD=1.0000, w_SOYB=0.0000\nPortfolio annualized return: 18.54%, volatility: 7.26%\nSharpe ratio: (0.1854 - 0.0400) / 0.0726 = 2.0026", "metadata": {"weights": {"XLF": 0.0, "XRP-USD": 0.0, "LQD": 1.0, "SOYB": 0.0}, "sharpe_ratio": 2.0026, "portfolio_return": 0.185352, "portfolio_vol": 0.072583, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240905_0901", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "BTC-USD", "CSHI", "STIP"], "decision_date": "2024-09-05", "context_summary": "4-asset optimization. Max-Sharpe: 2.514. Portfolio: return=7.40%, vol=1.35%. Weights: w_SPY=0.0000, w_BTC-USD=0.0041, w_CSHI=0.1677, w_STIP=0.8283.", "question": "Assets: SPY, BTC-USD, CSHI, STIP\nAnnualized mean returns: SPY:-0.0393, BTC-USD:0.4490, CSHI:0.0546, STIP:0.0761\nCovariance matrix (annualized):\n[[0.03034, 0.047399, 0.001382, 0.000124], [0.047399, 0.288637, 0.005823, 5.6e-05], [0.001382, 0.005823, 0.000379, -1.1e-05], [0.000124, 5.6e-05, -1.1e-05, 0.000236]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0000, w_BTC-USD=0.0041, w_CSHI=0.1677, w_STIP=0.8283", "answer_numeric": 2.5136856599564013, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0000, w_BTC-USD=0.0041, w_CSHI=0.1677, w_STIP=0.8283\nPortfolio annualized return: 7.40%, volatility: 1.35%\nSharpe ratio: (0.0740 - 0.0400) / 0.0135 = 2.5137", "metadata": {"weights": {"SPY": 0.0, "BTC-USD": 0.0041, "CSHI": 0.1677, "STIP": 0.8283}, "sharpe_ratio": 2.5137, "portfolio_return": 0.074015, "portfolio_vol": 0.013532, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230315_0903", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MATIC-USD", "ICSH", "PALL"], "decision_date": "2023-03-15", "context_summary": "4-asset optimization. Max-Sharpe: 1.766. Portfolio: return=6.04%, vol=1.15%. Weights: w_FXI=0.0000, w_MATIC-USD=0.0124, w_ICSH=0.9876, w_PALL=0.0000.", "question": "Assets: FXI, MATIC-USD, ICSH, PALL\nAnnualized mean returns: FXI:-0.9223, MATIC-USD:1.3591, ICSH:0.0441, PALL:-1.1400\nCovariance matrix (annualized):\n[[0.079809, 0.069956, -2.2e-05, 0.038184], [0.069956, 0.664538, 0.000403, -0.017054], [-2.2e-05, 0.000403, 2.2e-05, 0.000417], [0.038184, -0.017054, 0.000417, 0.129475]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_MATIC-USD=0.0124, w_ICSH=0.9876, w_PALL=0.0000", "answer_numeric": 1.7657660531358117, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_MATIC-USD=0.0124, w_ICSH=0.9876, w_PALL=0.0000\nPortfolio annualized return: 6.04%, volatility: 1.15%\nSharpe ratio: (0.0604 - 0.0400) / 0.0115 = 1.7658", "metadata": {"weights": {"FXI": 0.0, "MATIC-USD": 0.0124, "ICSH": 0.9876, "PALL": 0.0}, "sharpe_ratio": 1.7658, "portfolio_return": 0.060359, "portfolio_vol": 0.01153, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241220_0904", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "ICSH", "USO"], "decision_date": "2024-12-20", "context_summary": "4-asset optimization. Max-Sharpe: 3.520. Portfolio: return=12.46%, vol=2.40%. Weights: w_IWM=0.0000, w_BTC-USD=0.0460, w_ICSH=0.9245, w_USO=0.0295.", "question": "Assets: IWM, BTC-USD, ICSH, USO\nAnnualized mean returns: IWM:-0.2122, BTC-USD:1.7486, ICSH:0.0434, USO:0.1390\nCovariance matrix (annualized):\n[[0.039649, 0.061006, 0.000225, -0.009586], [0.061006, 0.274029, 2.4e-05, -0.032432], [0.000225, 2.4e-05, 3e-05, -0.000186], [-0.009586, -0.032432, -0.000186, 0.079347]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_BTC-USD=0.0460, w_ICSH=0.9245, w_USO=0.0295", "answer_numeric": 3.5198629739848633, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_BTC-USD=0.0460, w_ICSH=0.9245, w_USO=0.0295\nPortfolio annualized return: 12.46%, volatility: 2.40%\nSharpe ratio: (0.1246 - 0.0400) / 0.0240 = 3.5199", "metadata": {"weights": {"IWM": 0.0, "BTC-USD": 0.046, "ICSH": 0.9245, "USO": 0.0295}, "sharpe_ratio": 3.5199, "portfolio_return": 0.124639, "portfolio_vol": 0.024046, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240110_0906", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "LINK-USD", "IYR", "BIL"], "decision_date": "2024-01-10", "context_summary": "4-asset optimization. Max-Sharpe: -0.102. Portfolio: return=1.63%, vol=23.29%. Weights: w_EEM=0.2500, w_LINK-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500.", "question": "Assets: EEM, LINK-USD, IYR, BIL\nAnnualized mean returns: EEM:0.2280, LINK-USD:-1.0275, IYR:0.8119, BIL:0.0530\nCovariance matrix (annualized):\n[[0.020365, 0.024202, 0.016533, 5.7e-05], [0.024202, 0.630469, 0.051565, 0.000143], [0.016533, 0.051565, 0.031976, -1e-06], [5.7e-05, 0.000143, -1e-06, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.2500, w_LINK-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500", "answer_numeric": -0.10165802495625709, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.2500, w_LINK-USD=0.2500, w_IYR=0.2500, w_BIL=0.2500\nPortfolio annualized return: 1.63%, volatility: 23.29%\nSharpe ratio: (0.0163 - 0.0400) / 0.2329 = -0.1017", "metadata": {"weights": {"EEM": 0.25, "LINK-USD": 0.25, "IYR": 0.25, "BIL": 0.25}, "sharpe_ratio": -0.1017, "portfolio_return": 0.016325, "portfolio_vol": 0.232891, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241231_0907", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "STIP", "ICSH"], "decision_date": "2024-12-31", "context_summary": "4-asset optimization. Max-Sharpe: 5.458. Portfolio: return=25.84%, vol=4.00%. Weights: w_EWJ=0.0000, w_XRP-USD=0.0333, w_STIP=0.0000, w_ICSH=0.9667.", "question": "Assets: EWJ, XRP-USD, STIP, ICSH\nAnnualized mean returns: EWJ:0.0129, XRP-USD:6.3630, STIP:0.0183, ICSH:0.0479\nCovariance matrix (annualized):\n[[0.023403, 0.056304, 0.001037, 0.000135], [0.056304, 1.365971, 0.002305, 0.000852], [0.001037, 0.002305, 0.000241, 3.2e-05], [0.000135, 0.000852, 3.2e-05, 3.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_XRP-USD=0.0333, w_STIP=0.0000, w_ICSH=0.9667", "answer_numeric": 5.458122716928763, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_XRP-USD=0.0333, w_STIP=0.0000, w_ICSH=0.9667\nPortfolio annualized return: 25.84%, volatility: 4.00%\nSharpe ratio: (0.2584 - 0.0400) / 0.0400 = 5.4581", "metadata": {"weights": {"EWJ": 0.0, "XRP-USD": 0.0333, "STIP": 0.0, "ICSH": 0.9667}, "sharpe_ratio": 5.4581, "portfolio_return": 0.258354, "portfolio_vol": 0.040005, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240930_0909", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SOL-USD", "LQD", "ITB"], "decision_date": "2024-09-30", "context_summary": "4-asset optimization. Max-Sharpe: 4.035. Portfolio: return=27.30%, vol=5.77%. Weights: w_IWM=0.0000, w_SOL-USD=0.0355, w_LQD=0.9645, w_ITB=0.0000.", "question": "Assets: IWM, SOL-USD, LQD, ITB\nAnnualized mean returns: IWM:-0.0768, SOL-USD:0.8895, LQD:0.2503, ITB:0.3461\nCovariance matrix (annualized):\n[[0.063275, 0.112217, -0.000419, 0.056096], [0.112217, 0.486237, -0.005291, 0.090344], [-0.000419, -0.005291, 0.003316, 0.003001], [0.056096, 0.090344, 0.003001, 0.067707]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_SOL-USD=0.0355, w_LQD=0.9645, w_ITB=0.0000", "answer_numeric": 4.0351776906848755, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_SOL-USD=0.0355, w_LQD=0.9645, w_ITB=0.0000\nPortfolio annualized return: 27.30%, volatility: 5.77%\nSharpe ratio: (0.2730 - 0.0400) / 0.0577 = 4.0352", "metadata": {"weights": {"IWM": 0.0, "SOL-USD": 0.0355, "LQD": 0.9645, "ITB": 0.0}, "sharpe_ratio": 4.0352, "portfolio_return": 0.273026, "portfolio_vol": 0.057749, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230717_0911", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "WEAT", "TLT"], "decision_date": "2023-07-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.937. Portfolio: return=52.55%, vol=16.53%. Weights: w_IWM=0.8332, w_AVAX-USD=0.0000, w_WEAT=0.1668, w_TLT=0.0000.", "question": "Assets: IWM, AVAX-USD, WEAT, TLT\nAnnualized mean returns: IWM:0.5554, AVAX-USD:0.5848, WEAT:0.3762, TLT:-0.0386\nCovariance matrix (annualized):\n[[0.035325, 0.023978, -0.002529, -0.001501], [0.023978, 0.278945, 0.071154, 0.01277], [-0.002529, 0.071154, 0.126077, 0.002661], [-0.001501, 0.01277, 0.002661, 0.017593]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.8332, w_AVAX-USD=0.0000, w_WEAT=0.1668, w_TLT=0.0000", "answer_numeric": 2.936768168508803, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.8332, w_AVAX-USD=0.0000, w_WEAT=0.1668, w_TLT=0.0000\nPortfolio annualized return: 52.55%, volatility: 16.53%\nSharpe ratio: (0.5255 - 0.0400) / 0.1653 = 2.9368", "metadata": {"weights": {"IWM": 0.8332, "AVAX-USD": 0.0, "WEAT": 0.1668, "TLT": 0.0}, "sharpe_ratio": 2.9368, "portfolio_return": 0.525481, "portfolio_vol": 0.165311, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230801_0913", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ETH-USD", "XHB", "BIL"], "decision_date": "2023-08-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.769. Portfolio: return=64.30%, vol=16.00%. Weights: w_IWM=0.2500, w_ETH-USD=0.2500, w_XHB=0.2500, w_BIL=0.2500.", "question": "Assets: IWM, ETH-USD, XHB, BIL\nAnnualized mean returns: IWM:0.7902, ETH-USD:0.4933, XHB:1.2387, BIL:0.0497\nCovariance matrix (annualized):\n[[0.033949, 0.025006, 0.030843, -7e-05], [0.025006, 0.161203, 0.030723, 0.000177], [0.030843, 0.030723, 0.04111, -8.7e-05], [-7e-05, 0.000177, -8.7e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.2500, w_ETH-USD=0.2500, w_XHB=0.2500, w_BIL=0.2500", "answer_numeric": 3.7692371427465208, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.2500, w_ETH-USD=0.2500, w_XHB=0.2500, w_BIL=0.2500\nPortfolio annualized return: 64.30%, volatility: 16.00%\nSharpe ratio: (0.6430 - 0.0400) / 0.1600 = 3.7692", "metadata": {"weights": {"IWM": 0.25, "ETH-USD": 0.25, "XHB": 0.25, "BIL": 0.25}, "sharpe_ratio": 3.7692, "portfolio_return": 0.642969, "portfolio_vol": 0.159971, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230428_0915", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "CPER", "VNQI"], "decision_date": "2023-04-28", "context_summary": "4-asset optimization. Max-Sharpe: 0.970. Portfolio: return=62.22%, vol=60.05%. Weights: w_XLB=0.0000, w_ADA-USD=1.0000, w_CPER=0.0000, w_VNQI=0.0000.", "question": "Assets: XLB, ADA-USD, CPER, VNQI\nAnnualized mean returns: XLB:-0.0890, ADA-USD:0.6222, CPER:-0.0363, VNQI:0.0390\nCovariance matrix (annualized):\n[[0.041917, 0.016141, 0.01795, 0.017811], [0.016141, 0.360547, 0.024603, 0.00123], [0.01795, 0.024603, 0.040631, 0.00959], [0.017811, 0.00123, 0.00959, 0.016531]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_ADA-USD=1.0000, w_CPER=0.0000, w_VNQI=0.0000", "answer_numeric": 0.9695984969041452, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_ADA-USD=1.0000, w_CPER=0.0000, w_VNQI=0.0000\nPortfolio annualized return: 62.22%, volatility: 60.05%\nSharpe ratio: (0.6222 - 0.0400) / 0.6005 = 0.9696", "metadata": {"weights": {"XLB": 0.0, "ADA-USD": 1.0, "CPER": 0.0, "VNQI": 0.0}, "sharpe_ratio": 0.9696, "portfolio_return": 0.622201, "portfolio_vol": 0.600456, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240823_0916", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "MATIC-USD", "PALL", "VNQI"], "decision_date": "2024-08-23", "context_summary": "4-asset optimization. Max-Sharpe: 3.002. Portfolio: return=41.37%, vol=12.45%. Weights: w_XLV=0.3014, w_MATIC-USD=0.0000, w_PALL=0.0000, w_VNQI=0.6986.", "question": "Assets: XLV, MATIC-USD, PALL, VNQI\nAnnualized mean returns: XLV:0.3327, MATIC-USD:0.5518, PALL:-0.1107, VNQI:0.4486\nCovariance matrix (annualized):\n[[0.018291, 0.037457, 0.017192, 0.009479], [0.037457, 0.498536, 0.068905, 0.016629], [0.017192, 0.068905, 0.11952, 0.024861], [0.009479, 0.016629, 0.024861, 0.020154]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.3014, w_MATIC-USD=0.0000, w_PALL=0.0000, w_VNQI=0.6986", "answer_numeric": 3.0023934778036665, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.3014, w_MATIC-USD=0.0000, w_PALL=0.0000, w_VNQI=0.6986\nPortfolio annualized return: 41.37%, volatility: 12.45%\nSharpe ratio: (0.4137 - 0.0400) / 0.1245 = 3.0024", "metadata": {"weights": {"XLV": 0.3014, "MATIC-USD": 0.0, "PALL": 0.0, "VNQI": 0.6986}, "sharpe_ratio": 3.0024, "portfolio_return": 0.413666, "portfolio_vol": 0.124456, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241029_0918", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "BTC-USD", "VNQ", "SCHP"], "decision_date": "2024-10-29", "context_summary": "4-asset optimization. Max-Sharpe: 2.176. Portfolio: return=45.70%, vol=19.16%. Weights: w_XLRE=0.5673, w_BTC-USD=0.4327, w_VNQ=0.0000, w_SCHP=0.0000.", "question": "Assets: XLRE, BTC-USD, VNQ, SCHP\nAnnualized mean returns: XLRE:0.1949, BTC-USD:0.8006, VNQ:0.1764, SCHP:-0.0529\nCovariance matrix (annualized):\n[[0.015275, 0.011503, 0.014735, 0.002394], [0.011503, 0.139671, 0.015312, 0.000519], [0.014735, 0.015312, 0.014733, 0.00217], [0.002394, 0.000519, 0.00217, 0.00215]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.5673, w_BTC-USD=0.4327, w_VNQ=0.0000, w_SCHP=0.0000", "answer_numeric": 2.1763210962703354, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.5673, w_BTC-USD=0.4327, w_VNQ=0.0000, w_SCHP=0.0000\nPortfolio annualized return: 45.70%, volatility: 19.16%\nSharpe ratio: (0.4570 - 0.0400) / 0.1916 = 2.1763", "metadata": {"weights": {"XLRE": 0.5673, "BTC-USD": 0.4327, "VNQ": 0.0, "SCHP": 0.0}, "sharpe_ratio": 2.1763, "portfolio_return": 0.457029, "portfolio_vol": 0.191621, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20230515_0920", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "CSHI", "PALL"], "decision_date": "2023-05-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.363. Portfolio: return=9.78%, vol=1.72%. Weights: w_XLB=0.0224, w_ADA-USD=0.0223, w_CSHI=0.9517, w_PALL=0.0036.", "question": "Assets: XLB, ADA-USD, CSHI, PALL\nAnnualized mean returns: XLB:0.2080, ADA-USD:1.4040, CSHI:0.0641, PALL:0.2253\nCovariance matrix (annualized):\n[[0.02664, 0.011504, -2.2e-05, 0.007208], [0.011504, 0.332588, -0.000695, -0.009289], [-2.2e-05, -0.000695, 0.000144, 0.000559], [0.007208, -0.009289, 0.000559, 0.127869]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0224, w_ADA-USD=0.0223, w_CSHI=0.9517, w_PALL=0.0036", "answer_numeric": 3.3634242130683063, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0224, w_ADA-USD=0.0223, w_CSHI=0.9517, w_PALL=0.0036\nPortfolio annualized return: 9.78%, volatility: 1.72%\nSharpe ratio: (0.0978 - 0.0400) / 0.0172 = 3.3634", "metadata": {"weights": {"XLB": 0.0224, "ADA-USD": 0.0223, "CSHI": 0.9517, "PALL": 0.0036}, "sharpe_ratio": 3.3634, "portfolio_return": 0.097763, "portfolio_vol": 0.017174, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230214_0921", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DOT-USD", "CSHI", "UNG"], "decision_date": "2023-02-14", "context_summary": "4-asset optimization. Max-Sharpe: 2.621. Portfolio: return=6.41%, vol=0.92%. Weights: w_XLB=0.0000, w_DOT-USD=0.0000, w_CSHI=1.0000, w_UNG=0.0000.", "question": "Assets: XLB, DOT-USD, CSHI, UNG\nAnnualized mean returns: XLB:0.2774, DOT-USD:0.5710, CSHI:0.0641, UNG:-5.3234\nCovariance matrix (annualized):\n[[0.034423, 0.04945, 0.000856, 0.041264], [0.04945, 0.423489, 0.001894, 0.132237], [0.000856, 0.001894, 8.4e-05, -0.000143], [0.041264, 0.132237, -0.000143, 0.576055]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_DOT-USD=0.0000, w_CSHI=1.0000, w_UNG=0.0000", "answer_numeric": 2.6210384111656366, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_DOT-USD=0.0000, w_CSHI=1.0000, w_UNG=0.0000\nPortfolio annualized return: 6.41%, volatility: 0.92%\nSharpe ratio: (0.0641 - 0.0400) / 0.0092 = 2.6210", "metadata": {"weights": {"XLB": 0.0, "DOT-USD": 0.0, "CSHI": 1.0, "UNG": 0.0}, "sharpe_ratio": 2.621, "portfolio_return": 0.064071, "portfolio_vol": 0.009184, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240220_0922", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "AVAX-USD", "IGOV", "HAUZ"], "decision_date": "2024-02-20", "context_summary": "4-asset optimization. Max-Sharpe: 4.772. Portfolio: return=84.20%, vol=16.81%. Weights: w_MTUM=1.0000, w_AVAX-USD=0.0000, w_IGOV=0.0000, w_HAUZ=0.0000.", "question": "Assets: MTUM, AVAX-USD, IGOV, HAUZ\nAnnualized mean returns: MTUM:0.8420, AVAX-USD:-1.0457, IGOV:-0.2978, HAUZ:-0.2067\nCovariance matrix (annualized):\n[[0.028245, 0.060992, 0.005392, 0.010449], [0.060992, 0.695295, 0.002262, 0.014148], [0.005392, 0.002262, 0.008908, 0.010591], [0.010449, 0.014148, 0.010591, 0.027718]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=1.0000, w_AVAX-USD=0.0000, w_IGOV=0.0000, w_HAUZ=0.0000", "answer_numeric": 4.771897509435785, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=1.0000, w_AVAX-USD=0.0000, w_IGOV=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: 84.20%, volatility: 16.81%\nSharpe ratio: (0.8420 - 0.0400) / 0.1681 = 4.7719", "metadata": {"weights": {"MTUM": 1.0, "AVAX-USD": 0.0, "IGOV": 0.0, "HAUZ": 0.0}, "sharpe_ratio": 4.7719, "portfolio_return": 0.841979, "portfolio_vol": 0.168063, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230206_0923", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "MATIC-USD", "SOYB", "LQD"], "decision_date": "2023-02-06", "context_summary": "4-asset optimization. Max-Sharpe: 3.015. Portfolio: return=52.00%, vol=15.92%. Weights: w_VEA=0.9526, w_MATIC-USD=0.0474, w_SOYB=0.0000, w_LQD=0.0000.", "question": "Assets: VEA, MATIC-USD, SOYB, LQD\nAnnualized mean returns: VEA:0.4858, MATIC-USD:1.2074, SOYB:0.0935, LQD:0.0513\nCovariance matrix (annualized):\n[[0.022594, 0.0424, 0.003254, 0.007722], [0.0424, 0.44776, 0.003353, 0.006165], [0.003254, 0.003353, 0.016674, 0.00011], [0.007722, 0.006165, 0.00011, 0.011618]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.9526, w_MATIC-USD=0.0474, w_SOYB=0.0000, w_LQD=0.0000", "answer_numeric": 3.0152814907077286, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.9526, w_MATIC-USD=0.0474, w_SOYB=0.0000, w_LQD=0.0000\nPortfolio annualized return: 52.00%, volatility: 15.92%\nSharpe ratio: (0.5200 - 0.0400) / 0.1592 = 3.0153", "metadata": {"weights": {"VEA": 0.9526, "MATIC-USD": 0.0474, "SOYB": 0.0, "LQD": 0.0}, "sharpe_ratio": 3.0153, "portfolio_return": 0.520008, "portfolio_vol": 0.159192, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230215_0925", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "XHB", "VCIT"], "decision_date": "2023-02-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.384. Portfolio: return=82.29%, vol=23.14%. Weights: w_XLK=0.4162, w_BNB-USD=0.0235, w_XHB=0.5603, w_VCIT=0.0000.", "question": "Assets: XLK, BNB-USD, XHB, VCIT\nAnnualized mean returns: XLK:0.7798, BNB-USD:0.5315, XHB:0.8671, VCIT:-0.0184\nCovariance matrix (annualized):\n[[0.056989, 0.031654, 0.046622, 0.007656], [0.031654, 0.170953, 0.029304, 0.000223], [0.046622, 0.029304, 0.065078, 0.011987], [0.007656, 0.000223, 0.011987, 0.007158]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.4162, w_BNB-USD=0.0235, w_XHB=0.5603, w_VCIT=0.0000", "answer_numeric": 3.3838114525178944, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.4162, w_BNB-USD=0.0235, w_XHB=0.5603, w_VCIT=0.0000\nPortfolio annualized return: 82.29%, volatility: 23.14%\nSharpe ratio: (0.8229 - 0.0400) / 0.2314 = 3.3838", "metadata": {"weights": {"XLK": 0.4162, "BNB-USD": 0.0235, "XHB": 0.5603, "VCIT": 0.0}, "sharpe_ratio": 3.3838, "portfolio_return": 0.82292, "portfolio_vol": 0.231372, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241125_0926", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "MATIC-USD", "MORT", "CORN"], "decision_date": "2024-11-25", "context_summary": "4-asset optimization. Max-Sharpe: 1.166. Portfolio: return=96.18%, vol=79.09%. Weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_MORT=0.0000, w_CORN=0.0000.", "question": "Assets: XLU, MATIC-USD, MORT, CORN\nAnnualized mean returns: XLU:0.0943, MATIC-USD:0.9618, MORT:-0.1360, CORN:-0.0446\nCovariance matrix (annualized):\n[[0.029449, 0.039075, 0.009422, -0.000295], [0.039075, 0.625502, 0.049979, 0.018333], [0.009422, 0.049979, 0.021299, -0.004844], [-0.000295, 0.018333, -0.004844, 0.017021]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_MATIC-USD=1.0000, w_MORT=0.0000, w_CORN=0.0000", "answer_numeric": 1.1655447765074465, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_MORT=0.0000, w_CORN=0.0000\nPortfolio annualized return: 96.18%, volatility: 79.09%\nSharpe ratio: (0.9618 - 0.0400) / 0.7909 = 1.1655", "metadata": {"weights": {"XLU": 0.0, "MATIC-USD": 1.0, "MORT": 0.0, "CORN": 0.0}, "sharpe_ratio": 1.1655, "portfolio_return": 0.961814, "portfolio_vol": 0.790887, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230511_0928", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "CSHI", "MORT"], "decision_date": "2023-05-11", "context_summary": "4-asset optimization. Max-Sharpe: 4.487. Portfolio: return=10.93%, vol=1.54%. Weights: w_XLF=0.0000, w_BTC-USD=0.0263, w_CSHI=0.9684, w_MORT=0.0053.", "question": "Assets: XLF, BTC-USD, CSHI, MORT\nAnnualized mean returns: XLF:-0.1088, BTC-USD:1.3977, CSHI:0.0754, MORT:-0.1017\nCovariance matrix (annualized):\n[[0.052932, -0.023076, -3.6e-05, 0.048293], [-0.023076, 0.239478, -0.001542, -0.025167], [-3.6e-05, -0.001542, 0.000169, -0.000242], [0.048293, -0.025167, -0.000242, 0.07724]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_BTC-USD=0.0263, w_CSHI=0.9684, w_MORT=0.0053", "answer_numeric": 4.487356023772808, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BTC-USD=0.0263, w_CSHI=0.9684, w_MORT=0.0053\nPortfolio annualized return: 10.93%, volatility: 1.54%\nSharpe ratio: (0.1093 - 0.0400) / 0.0154 = 4.4874", "metadata": {"weights": {"XLF": 0.0, "BTC-USD": 0.0263, "CSHI": 0.9684, "MORT": 0.0053}, "sharpe_ratio": 4.4874, "portfolio_return": 0.109277, "portfolio_vol": 0.015438, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240216_0929", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "DOT-USD", "SGOV", "SCHH"], "decision_date": "2024-02-16", "context_summary": "4-asset optimization. Max-Sharpe: 6.323. Portfolio: return=5.74%, vol=0.27%. Weights: w_^VIX=0.0015, w_DOT-USD=0.0000, w_SGOV=0.9985, w_SCHH=0.0000.", "question": "Assets: ^VIX, DOT-USD, SGOV, SCHH\nAnnualized mean returns: ^VIX:0.8101, DOT-USD:0.7745, SGOV:0.0562, SCHH:-0.1400\nCovariance matrix (annualized):\n[[0.567485, -0.018828, -0.000541, -0.057825], [-0.018828, 0.683104, 0.000763, 0.027605], [-0.000541, 0.000763, 8e-06, 0.000187], [-0.057825, 0.027605, 0.000187, 0.031111]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0015, w_DOT-USD=0.0000, w_SGOV=0.9985, w_SCHH=0.0000", "answer_numeric": 6.322941407340442, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0015, w_DOT-USD=0.0000, w_SGOV=0.9985, w_SCHH=0.0000\nPortfolio annualized return: 5.74%, volatility: 0.27%\nSharpe ratio: (0.0574 - 0.0400) / 0.0027 = 6.3229", "metadata": {"weights": {"^VIX": 0.0015, "DOT-USD": 0.0, "SGOV": 0.9985, "SCHH": 0.0}, "sharpe_ratio": 6.3229, "portfolio_return": 0.057379, "portfolio_vol": 0.002749, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230714_0930", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "REZ", "SHY"], "decision_date": "2023-07-14", "context_summary": "4-asset optimization. Max-Sharpe: 4.667. Portfolio: return=60.80%, vol=12.17%. Weights: w_QUAL=1.0000, w_ADA-USD=0.0000, w_REZ=0.0000, w_SHY=0.0000.", "question": "Assets: QUAL, ADA-USD, REZ, SHY\nAnnualized mean returns: QUAL:0.6080, ADA-USD:0.3818, REZ:0.2927, SHY:-0.0265\nCovariance matrix (annualized):\n[[0.014808, 0.025351, 0.006598, -0.000127], [0.025351, 0.576514, 0.005853, 0.003585], [0.006598, 0.005853, 0.0295, -8.4e-05], [-0.000127, 0.003585, -8.4e-05, 0.000487]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=1.0000, w_ADA-USD=0.0000, w_REZ=0.0000, w_SHY=0.0000", "answer_numeric": 4.667392684398051, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=1.0000, w_ADA-USD=0.0000, w_REZ=0.0000, w_SHY=0.0000\nPortfolio annualized return: 60.80%, volatility: 12.17%\nSharpe ratio: (0.6080 - 0.0400) / 0.1217 = 4.6674", "metadata": {"weights": {"QUAL": 1.0, "ADA-USD": 0.0, "REZ": 0.0, "SHY": 0.0}, "sharpe_ratio": 4.6674, "portfolio_return": 0.607973, "portfolio_vol": 0.12169, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231229_0931", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BNB-USD", "HAUZ", "TLH"], "decision_date": "2023-12-29", "context_summary": "4-asset optimization. Max-Sharpe: 8.655. Portfolio: return=85.12%, vol=9.37%. Weights: w_XLP=0.3824, w_BNB-USD=0.0827, w_HAUZ=0.0496, w_TLH=0.4854.", "question": "Assets: XLP, BNB-USD, HAUZ, TLH\nAnnualized mean returns: XLP:0.5049, BNB-USD:2.2814, HAUZ:0.9945, TLH:0.8659\nCovariance matrix (annualized):\n[[0.014648, 0.008334, 0.006273, -0.003227], [0.008334, 0.307934, 0.017431, -0.010779], [0.006273, 0.017431, 0.028365, 0.010488], [-0.003227, -0.010779, 0.010488, 0.021731]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.3824, w_BNB-USD=0.0827, w_HAUZ=0.0496, w_TLH=0.4854", "answer_numeric": 8.655343798271144, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.3824, w_BNB-USD=0.0827, w_HAUZ=0.0496, w_TLH=0.4854\nPortfolio annualized return: 85.12%, volatility: 9.37%\nSharpe ratio: (0.8512 - 0.0400) / 0.0937 = 8.6553", "metadata": {"weights": {"XLP": 0.3824, "BNB-USD": 0.0827, "HAUZ": 0.0496, "TLH": 0.4854}, "sharpe_ratio": 8.6553, "portfolio_return": 0.851238, "portfolio_vol": 0.093727, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240304_0932", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "DOT-USD", "IYR", "SGOV"], "decision_date": "2024-03-04", "context_summary": "4-asset optimization. Max-Sharpe: 1.785. Portfolio: return=35.32%, vol=17.54%. Weights: w_VLUE=0.2500, w_DOT-USD=0.2500, w_IYR=0.2500, w_SGOV=0.2500.", "question": "Assets: VLUE, DOT-USD, IYR, SGOV\nAnnualized mean returns: VLUE:0.2222, DOT-USD:1.1533, IYR:-0.0185, SGOV:0.0557\nCovariance matrix (annualized):\n[[0.013692, 0.009352, 0.014942, 0.000109], [0.009352, 0.369427, 0.0157, 0.000285], [0.014942, 0.0157, 0.028263, 0.000147], [0.000109, 0.000285, 0.000147, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.2500, w_DOT-USD=0.2500, w_IYR=0.2500, w_SGOV=0.2500", "answer_numeric": 1.7851210260053851, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.2500, w_DOT-USD=0.2500, w_IYR=0.2500, w_SGOV=0.2500\nPortfolio annualized return: 35.32%, volatility: 17.54%\nSharpe ratio: (0.3532 - 0.0400) / 0.1754 = 1.7851", "metadata": {"weights": {"VLUE": 0.25, "DOT-USD": 0.25, "IYR": 0.25, "SGOV": 0.25}, "sharpe_ratio": 1.7851, "portfolio_return": 0.353178, "portfolio_vol": 0.175438, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20231005_0933", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "PPLT", "ICSH"], "decision_date": "2023-10-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.116. Portfolio: return=5.34%, vol=0.43%. Weights: w_EEM=0.0000, w_ETH-USD=0.0000, w_PPLT=0.0000, w_ICSH=1.0000.", "question": "Assets: EEM, ETH-USD, PPLT, ICSH\nAnnualized mean returns: EEM:-0.5240, ETH-USD:-0.6957, PPLT:-0.3328, ICSH:0.0534\nCovariance matrix (annualized):\n[[0.016704, 0.007808, 0.011899, -4.8e-05], [0.007808, 0.102214, 0.012029, 0.000131], [0.011899, 0.012029, 0.047529, 9e-06], [-4.8e-05, 0.000131, 9e-06, 1.8e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_ETH-USD=0.0000, w_PPLT=0.0000, w_ICSH=1.0000", "answer_numeric": 3.115510656999764, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_ETH-USD=0.0000, w_PPLT=0.0000, w_ICSH=1.0000\nPortfolio annualized return: 5.34%, volatility: 0.43%\nSharpe ratio: (0.0534 - 0.0400) / 0.0043 = 3.1155", "metadata": {"weights": {"EEM": 0.0, "ETH-USD": 0.0, "PPLT": 0.0, "ICSH": 1.0}, "sharpe_ratio": 3.1155, "portfolio_return": 0.053361, "portfolio_vol": 0.004289, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240708_0935", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DOT-USD", "SCHH", "SLV"], "decision_date": "2024-07-08", "context_summary": "4-asset optimization. Max-Sharpe: 2.818. Portfolio: return=50.27%, vol=16.42%. Weights: w_XLB=0.0000, w_DOT-USD=0.0000, w_SCHH=0.6805, w_SLV=0.3195.", "question": "Assets: XLB, DOT-USD, SCHH, SLV\nAnnualized mean returns: XLB:-0.1733, DOT-USD:-0.7820, SCHH:0.2956, SLV:0.9439\nCovariance matrix (annualized):\n[[0.012536, 0.003755, 0.008904, 0.014192], [0.003755, 0.360684, 0.021775, 0.046102], [0.008904, 0.021775, 0.0179, 0.008498], [0.014192, 0.046102, 0.008498, 0.146801]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_DOT-USD=0.0000, w_SCHH=0.6805, w_SLV=0.3195", "answer_numeric": 2.817644236846643, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_DOT-USD=0.0000, w_SCHH=0.6805, w_SLV=0.3195\nPortfolio annualized return: 50.27%, volatility: 16.42%\nSharpe ratio: (0.5027 - 0.0400) / 0.1642 = 2.8176", "metadata": {"weights": {"XLB": 0.0, "DOT-USD": 0.0, "SCHH": 0.6805, "SLV": 0.3195}, "sharpe_ratio": 2.8176, "portfolio_return": 0.502699, "portfolio_vol": 0.164215, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230403_0936", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "PALL", "ITB"], "decision_date": "2023-04-03", "context_summary": "4-asset optimization. Max-Sharpe: -0.250. Portfolio: return=-2.01%, vol=23.98%. Weights: w_XLB=0.0000, w_BNB-USD=0.0000, w_PALL=0.0000, w_ITB=1.0000.", "question": "Assets: XLB, BNB-USD, PALL, ITB\nAnnualized mean returns: XLB:-0.3106, BNB-USD:-0.4450, PALL:-0.8781, ITB:-0.0201\nCovariance matrix (annualized):\n[[0.044221, 0.00886, 0.005522, 0.033538], [0.00886, 0.23738, -0.017577, 0.014339], [0.005522, -0.017577, 0.114024, 0.001135], [0.033538, 0.014339, 0.001135, 0.057497]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_BNB-USD=0.0000, w_PALL=0.0000, w_ITB=1.0000", "answer_numeric": -0.25047013247661676, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_BNB-USD=0.0000, w_PALL=0.0000, w_ITB=1.0000\nPortfolio annualized return: -2.01%, volatility: 23.98%\nSharpe ratio: (-0.0201 - 0.0400) / 0.2398 = -0.2505", "metadata": {"weights": {"XLB": 0.0, "BNB-USD": 0.0, "PALL": 0.0, "ITB": 1.0}, "sharpe_ratio": -0.2505, "portfolio_return": -0.020059, "portfolio_vol": 0.239786, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231221_0938", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "SOYB", "SGOV"], "decision_date": "2023-12-21", "context_summary": "4-asset optimization. Max-Sharpe: 8.107. Portfolio: return=7.08%, vol=0.38%. Weights: w_XLU=0.0018, w_AVAX-USD=0.0034, w_SOYB=0.0102, w_SGOV=0.9846.", "question": "Assets: XLU, AVAX-USD, SOYB, SGOV\nAnnualized mean returns: XLU:0.3497, AVAX-USD:5.7177, SOYB:-0.0137, SGOV:0.0517\nCovariance matrix (annualized):\n[[0.03225, 0.015825, -0.001734, 5.2e-05], [0.015825, 1.014753, -0.06117, -0.00019], [-0.001734, -0.06117, 0.025804, -8e-05], [5.2e-05, -0.00019, -8e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0018, w_AVAX-USD=0.0034, w_SOYB=0.0102, w_SGOV=0.9846", "answer_numeric": 8.106639419571941, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0018, w_AVAX-USD=0.0034, w_SOYB=0.0102, w_SGOV=0.9846\nPortfolio annualized return: 7.08%, volatility: 0.38%\nSharpe ratio: (0.0708 - 0.0400) / 0.0038 = 8.1066", "metadata": {"weights": {"XLU": 0.0018, "AVAX-USD": 0.0034, "SOYB": 0.0102, "SGOV": 0.9846}, "sharpe_ratio": 8.1066, "portfolio_return": 0.070775, "portfolio_vol": 0.003796, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240821_0939", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "XHB", "UNG"], "decision_date": "2024-08-21", "context_summary": "4-asset optimization. Max-Sharpe: 1.111. Portfolio: return=37.82%, vol=30.46%. Weights: w_QUAL=0.0000, w_MATIC-USD=0.0000, w_XHB=1.0000, w_UNG=0.0000.", "question": "Assets: QUAL, MATIC-USD, XHB, UNG\nAnnualized mean returns: QUAL:0.1350, MATIC-USD:-0.3406, XHB:0.3782, UNG:-1.4717\nCovariance matrix (annualized):\n[[0.030055, 0.045636, 0.029712, 0.017373], [0.045636, 0.404917, 0.042705, 0.055729], [0.029712, 0.042705, 0.092759, 0.045144], [0.017373, 0.055729, 0.045144, 0.220733]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_MATIC-USD=0.0000, w_XHB=1.0000, w_UNG=0.0000", "answer_numeric": 1.110528404956377, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_MATIC-USD=0.0000, w_XHB=1.0000, w_UNG=0.0000\nPortfolio annualized return: 37.82%, volatility: 30.46%\nSharpe ratio: (0.3782 - 0.0400) / 0.3046 = 1.1105", "metadata": {"weights": {"QUAL": 0.0, "MATIC-USD": 0.0, "XHB": 1.0, "UNG": 0.0}, "sharpe_ratio": 1.1105, "portfolio_return": 0.378227, "portfolio_vol": 0.304564, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240103_0940", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "REZ", "LQD"], "decision_date": "2024-01-03", "context_summary": "4-asset optimization. Max-Sharpe: 6.187. Portfolio: return=46.80%, vol=6.92%. Weights: w_XLP=0.3700, w_XRP-USD=0.0000, w_REZ=0.0000, w_LQD=0.6300.", "question": "Assets: XLP, XRP-USD, REZ, LQD\nAnnualized mean returns: XLP:0.4222, XRP-USD:-0.6609, REZ:0.7818, LQD:0.4949\nCovariance matrix (annualized):\n[[0.014259, -0.001489, 0.007718, -0.001592], [-0.001489, 0.234187, -0.005212, -0.008231], [0.007718, -0.005212, 0.040597, 0.00915], [-0.001592, -0.008231, 0.00915, 0.009006]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.3700, w_XRP-USD=0.0000, w_REZ=0.0000, w_LQD=0.6300", "answer_numeric": 6.187431719041904, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.3700, w_XRP-USD=0.0000, w_REZ=0.0000, w_LQD=0.6300\nPortfolio annualized return: 46.80%, volatility: 6.92%\nSharpe ratio: (0.4680 - 0.0400) / 0.0692 = 6.1874", "metadata": {"weights": {"XLP": 0.37, "XRP-USD": 0.0, "REZ": 0.0, "LQD": 0.63}, "sharpe_ratio": 6.1874, "portfolio_return": 0.467987, "portfolio_vol": 0.06917, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230426_0941", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ADA-USD", "LQD", "BNO"], "decision_date": "2023-04-26", "context_summary": "4-asset optimization. Max-Sharpe: 2.957. Portfolio: return=25.11%, vol=7.14%. Weights: w_VTI=0.0943, w_ADA-USD=0.0000, w_LQD=0.9057, w_BNO=0.0000.", "question": "Assets: VTI, ADA-USD, LQD, BNO\nAnnualized mean returns: VTI:0.0915, ADA-USD:0.4224, LQD:0.2677, BNO:-0.0901\nCovariance matrix (annualized):\n[[0.023797, 0.012488, -0.001104, 0.012076], [0.012488, 0.37503, 0.010874, 0.018134], [-0.001104, 0.010874, 0.006186, -0.00013], [0.012076, 0.018134, -0.00013, 0.105863]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0943, w_ADA-USD=0.0000, w_LQD=0.9057, w_BNO=0.0000", "answer_numeric": 2.956672341872929, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0943, w_ADA-USD=0.0000, w_LQD=0.9057, w_BNO=0.0000\nPortfolio annualized return: 25.11%, volatility: 7.14%\nSharpe ratio: (0.2511 - 0.0400) / 0.0714 = 2.9567", "metadata": {"weights": {"VTI": 0.0943, "ADA-USD": 0.0, "LQD": 0.9057, "BNO": 0.0}, "sharpe_ratio": 2.9567, "portfolio_return": 0.251091, "portfolio_vol": 0.071395, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230310_0943", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "AVAX-USD", "UNG", "BNDX"], "decision_date": "2023-03-10", "context_summary": "4-asset optimization. Max-Sharpe: 1.411. Portfolio: return=152.02%, vol=104.93%. Weights: w_MTUM=0.0000, w_AVAX-USD=1.0000, w_UNG=0.0000, w_BNDX=0.0000.", "question": "Assets: MTUM, AVAX-USD, UNG, BNDX\nAnnualized mean returns: MTUM:-0.3531, AVAX-USD:1.5202, UNG:-1.5994, BNDX:-0.0493\nCovariance matrix (annualized):\n[[0.017876, 0.024665, 0.026828, -0.00096], [0.024665, 1.100962, 0.001278, 0.001429], [0.026828, 0.001278, 0.647891, -0.002412], [-0.00096, 0.001429, -0.002412, 0.002829]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_AVAX-USD=1.0000, w_UNG=0.0000, w_BNDX=0.0000", "answer_numeric": 1.4107133473639895, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_AVAX-USD=1.0000, w_UNG=0.0000, w_BNDX=0.0000\nPortfolio annualized return: 152.02%, volatility: 104.93%\nSharpe ratio: (1.5202 - 0.0400) / 1.0493 = 1.4107", "metadata": {"weights": {"MTUM": 0.0, "AVAX-USD": 1.0, "UNG": 0.0, "BNDX": 0.0}, "sharpe_ratio": 1.4107, "portfolio_return": 1.520215, "portfolio_vol": 1.049267, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230420_0944", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "SHV", "PDBC"], "decision_date": "2023-04-20", "context_summary": "4-asset optimization. Max-Sharpe: 0.399. Portfolio: return=4.20%, vol=0.51%. Weights: w_VTI=0.0103, w_MATIC-USD=0.0000, w_SHV=0.9649, w_PDBC=0.0248.", "question": "Assets: VTI, MATIC-USD, SHV, PDBC\nAnnualized mean returns: VTI:0.0552, MATIC-USD:-1.8242, SHV:0.0408, PDBC:0.0841\nCovariance matrix (annualized):\n[[0.025525, 0.013366, -0.000234, 0.006344], [0.013366, 0.383478, 0.000185, 0.012444], [-0.000234, 0.000185, 1.5e-05, -8.3e-05], [0.006344, 0.012444, -8.3e-05, 0.02319]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0103, w_MATIC-USD=0.0000, w_SHV=0.9649, w_PDBC=0.0248", "answer_numeric": 0.3989914406733045, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0103, w_MATIC-USD=0.0000, w_SHV=0.9649, w_PDBC=0.0248\nPortfolio annualized return: 4.20%, volatility: 0.51%\nSharpe ratio: (0.0420 - 0.0400) / 0.0051 = 0.3990", "metadata": {"weights": {"VTI": 0.0103, "MATIC-USD": 0.0, "SHV": 0.9649, "PDBC": 0.0248}, "sharpe_ratio": 0.399, "portfolio_return": 0.042023, "portfolio_vol": 0.00507, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230927_0946", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "MATIC-USD", "BIL", "VCIT"], "decision_date": "2023-09-27", "context_summary": "4-asset optimization. Max-Sharpe: 4.168. Portfolio: return=5.09%, vol=0.26%. Weights: w_XLRE=0.0000, w_MATIC-USD=0.0000, w_BIL=1.0000, w_VCIT=0.0000.", "question": "Assets: XLRE, MATIC-USD, BIL, VCIT\nAnnualized mean returns: XLRE:-0.6351, MATIC-USD:-1.6468, BIL:0.0509, VCIT:-0.1751\nCovariance matrix (annualized):\n[[0.022853, 0.024523, -0.000107, 0.004181], [0.024523, 0.167628, -0.000362, 0.008329], [-0.000107, -0.000362, 7e-06, -2.9e-05], [0.004181, 0.008329, -2.9e-05, 0.00387]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_MATIC-USD=0.0000, w_BIL=1.0000, w_VCIT=0.0000", "answer_numeric": 4.168073899011144, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_MATIC-USD=0.0000, w_BIL=1.0000, w_VCIT=0.0000\nPortfolio annualized return: 5.09%, volatility: 0.26%\nSharpe ratio: (0.0509 - 0.0400) / 0.0026 = 4.1681", "metadata": {"weights": {"XLRE": 0.0, "MATIC-USD": 0.0, "BIL": 1.0, "VCIT": 0.0}, "sharpe_ratio": 4.1681, "portfolio_return": 0.050924, "portfolio_vol": 0.002621, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230330_0947", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "AVAX-USD", "HAUZ", "IEF"], "decision_date": "2023-03-30", "context_summary": "4-asset optimization. Max-Sharpe: -1.746. Portfolio: return=-132.50%, vol=78.19%. Weights: w_XLE=0.0000, w_AVAX-USD=1.0000, w_HAUZ=0.0000, w_IEF=0.0000.", "question": "Assets: XLE, AVAX-USD, HAUZ, IEF\nAnnualized mean returns: XLE:-0.5425, AVAX-USD:-1.3250, HAUZ:-0.6380, IEF:-0.0642\nCovariance matrix (annualized):\n[[0.085861, 0.035231, 0.016149, -0.01593], [0.035231, 0.611435, 0.017985, -0.000278], [0.016149, 0.017985, 0.022948, -0.001337], [-0.01593, -0.000278, -0.001337, 0.011055]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_AVAX-USD=1.0000, w_HAUZ=0.0000, w_IEF=0.0000", "answer_numeric": -1.7456585666617692, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_AVAX-USD=1.0000, w_HAUZ=0.0000, w_IEF=0.0000\nPortfolio annualized return: -132.50%, volatility: 78.19%\nSharpe ratio: (-1.3250 - 0.0400) / 0.7819 = -1.7457", "metadata": {"weights": {"XLE": 0.0, "AVAX-USD": 1.0, "HAUZ": 0.0, "IEF": 0.0}, "sharpe_ratio": -1.7457, "portfolio_return": -1.325006, "portfolio_vol": 0.781943, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240809_0948", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "DOT-USD", "VNQ", "CSHI"], "decision_date": "2024-08-09", "context_summary": "4-asset optimization. Max-Sharpe: 6.420. Portfolio: return=52.14%, vol=7.50%. Weights: w_^VIX=0.0541, w_DOT-USD=0.0000, w_VNQ=0.5123, w_CSHI=0.4335.", "question": "Assets: ^VIX, DOT-USD, VNQ, CSHI\nAnnualized mean returns: ^VIX:3.3903, DOT-USD:-1.1772, VNQ:0.6197, CSHI:0.0471\nCovariance matrix (annualized):\n[[1.874518, -0.435513, -0.110685, -0.012912], [-0.435513, 0.377382, 0.035495, 0.005153], [-0.110685, 0.035495, 0.023802, 0.001305], [-0.012912, 0.005153, 0.001305, 0.000259]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0541, w_DOT-USD=0.0000, w_VNQ=0.5123, w_CSHI=0.4335", "answer_numeric": 6.419578175496088, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0541, w_DOT-USD=0.0000, w_VNQ=0.5123, w_CSHI=0.4335\nPortfolio annualized return: 52.14%, volatility: 7.50%\nSharpe ratio: (0.5214 - 0.0400) / 0.0750 = 6.4196", "metadata": {"weights": {"^VIX": 0.0541, "DOT-USD": 0.0, "VNQ": 0.5123, "CSHI": 0.4335}, "sharpe_ratio": 6.4196, "portfolio_return": 0.521362, "portfolio_vol": 0.074983, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230317_0950", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "AVAX-USD", "SHY", "DBA"], "decision_date": "2023-03-17", "context_summary": "4-asset optimization. Max-Sharpe: 0.605. Portfolio: return=10.28%, vol=10.37%. Weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_SHY=0.0000, w_DBA=1.0000.", "question": "Assets: VEA, AVAX-USD, SHY, DBA\nAnnualized mean returns: VEA:-0.2301, AVAX-USD:-0.2583, SHY:-0.0098, DBA:0.1028\nCovariance matrix (annualized):\n[[0.021378, 0.044828, -0.000271, 0.00592], [0.044828, 0.774716, -0.002231, 0.023057], [-0.000271, -0.002231, 0.000601, -0.000384], [0.00592, 0.023057, -0.000384, 0.010762]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_AVAX-USD=0.0000, w_SHY=0.0000, w_DBA=1.0000", "answer_numeric": 0.6052152513777118, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_AVAX-USD=0.0000, w_SHY=0.0000, w_DBA=1.0000\nPortfolio annualized return: 10.28%, volatility: 10.37%\nSharpe ratio: (0.1028 - 0.0400) / 0.1037 = 0.6052", "metadata": {"weights": {"VEA": 0.0, "AVAX-USD": 0.0, "SHY": 0.0, "DBA": 1.0}, "sharpe_ratio": 0.6052, "portfolio_return": 0.102785, "portfolio_vol": 0.103739, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240902_0952", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "DOT-USD", "BIL", "GLD"], "decision_date": "2024-09-02", "context_summary": "4-asset optimization. Max-Sharpe: -0.657. Portfolio: return=-7.00%, vol=16.74%. Weights: w_EFA=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_GLD=0.2500.", "question": "Assets: EFA, DOT-USD, BIL, GLD\nAnnualized mean returns: EFA:0.2587, DOT-USD:-0.9662, BIL:0.0511, GLD:0.3765\nCovariance matrix (annualized):\n[[0.026997, 0.032954, 4.8e-05, 0.012599], [0.032954, 0.288816, 0.000361, 0.007713], [4.8e-05, 0.000361, 7e-06, 7.2e-05], [0.012599, 0.007713, 7.2e-05, 0.025095]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_GLD=0.2500", "answer_numeric": -0.6569128075104516, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.2500, w_DOT-USD=0.2500, w_BIL=0.2500, w_GLD=0.2500\nPortfolio annualized return: -7.00%, volatility: 16.74%\nSharpe ratio: (-0.0700 - 0.0400) / 0.1674 = -0.6569", "metadata": {"weights": {"EFA": 0.25, "DOT-USD": 0.25, "BIL": 0.25, "GLD": 0.25}, "sharpe_ratio": -0.6569, "portfolio_return": -0.069973, "portfolio_vol": 0.167408, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230210_0953", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "BIL", "WEAT"], "decision_date": "2023-02-10", "context_summary": "4-asset optimization. Max-Sharpe: 2.536. Portfolio: return=66.14%, vol=24.50%. Weights: w_XLU=0.0000, w_BTC-USD=0.5863, w_BIL=0.0000, w_WEAT=0.4137.", "question": "Assets: XLU, BTC-USD, BIL, WEAT\nAnnualized mean returns: XLU:-0.3478, BTC-USD:0.9633, BIL:0.0394, WEAT:0.2336\nCovariance matrix (annualized):\n[[0.029406, 0.019509, -0.000126, 0.004352], [0.019509, 0.15263, 7.3e-05, -0.000704], [-0.000126, 7.3e-05, 1.1e-05, 3.7e-05], [0.004352, -0.000704, 3.7e-05, 0.046197]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_BTC-USD=0.5863, w_BIL=0.0000, w_WEAT=0.4137", "answer_numeric": 2.536241231578521, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_BTC-USD=0.5863, w_BIL=0.0000, w_WEAT=0.4137\nPortfolio annualized return: 66.14%, volatility: 24.50%\nSharpe ratio: (0.6614 - 0.0400) / 0.2450 = 2.5362", "metadata": {"weights": {"XLU": 0.0, "BTC-USD": 0.5863, "BIL": 0.0, "WEAT": 0.4137}, "sharpe_ratio": 2.5362, "portfolio_return": 0.661407, "portfolio_vol": 0.245011, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20230508_0954", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "AVAX-USD", "SGOV", "PPLT"], "decision_date": "2023-05-08", "context_summary": "4-asset optimization. Max-Sharpe: 4.224. Portfolio: return=6.06%, vol=0.49%. Weights: w_USMV=0.0177, w_AVAX-USD=0.0016, w_SGOV=0.9685, w_PPLT=0.0122.", "question": "Assets: USMV, AVAX-USD, SGOV, PPLT\nAnnualized mean returns: USMV:0.2744, AVAX-USD:0.6657, SGOV:0.0468, PPLT:0.7714\nCovariance matrix (annualized):\n[[0.01347, 0.003698, 4.7e-05, -0.001517], [0.003698, 0.432011, -7.8e-05, 0.002038], [4.7e-05, -7.8e-05, 7e-06, 3.7e-05], [-0.001517, 0.002038, 3.7e-05, 0.068526]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0177, w_AVAX-USD=0.0016, w_SGOV=0.9685, w_PPLT=0.0122", "answer_numeric": 4.223905193040075, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0177, w_AVAX-USD=0.0016, w_SGOV=0.9685, w_PPLT=0.0122\nPortfolio annualized return: 6.06%, volatility: 0.49%\nSharpe ratio: (0.0606 - 0.0400) / 0.0049 = 4.2239", "metadata": {"weights": {"USMV": 0.0177, "AVAX-USD": 0.0016, "SGOV": 0.9685, "PPLT": 0.0122}, "sharpe_ratio": 4.2239, "portfolio_return": 0.060646, "portfolio_vol": 0.004888, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231010_0956", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "AVAX-USD", "PALL", "ICSH"], "decision_date": "2023-10-10", "context_summary": "4-asset optimization. Max-Sharpe: 3.396. Portfolio: return=5.46%, vol=0.43%. Weights: w_XLK=0.0035, w_AVAX-USD=0.0000, w_PALL=0.0000, w_ICSH=0.9965.", "question": "Assets: XLK, AVAX-USD, PALL, ICSH\nAnnualized mean returns: XLK:0.0477, AVAX-USD:-0.9993, PALL:-0.7232, ICSH:0.0547\nCovariance matrix (annualized):\n[[0.03435, 0.022157, 0.008177, -0.000112], [0.022157, 0.215821, 0.042446, -0.00012], [0.008177, 0.042446, 0.06703, 9.1e-05], [-0.000112, -0.00012, 9.1e-05, 1.9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.0035, w_AVAX-USD=0.0000, w_PALL=0.0000, w_ICSH=0.9965", "answer_numeric": 3.3961073703859572, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0035, w_AVAX-USD=0.0000, w_PALL=0.0000, w_ICSH=0.9965\nPortfolio annualized return: 5.46%, volatility: 0.43%\nSharpe ratio: (0.0546 - 0.0400) / 0.0043 = 3.3961", "metadata": {"weights": {"XLK": 0.0035, "AVAX-USD": 0.0, "PALL": 0.0, "ICSH": 0.9965}, "sharpe_ratio": 3.3961, "portfolio_return": 0.054635, "portfolio_vol": 0.004309, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20231108_0957", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BNB-USD", "TLH", "ICSH"], "decision_date": "2023-11-08", "context_summary": "4-asset optimization. Max-Sharpe: 3.516. Portfolio: return=5.37%, vol=0.39%. Weights: w_XLP=0.0000, w_BNB-USD=0.0059, w_TLH=0.0000, w_ICSH=0.9941.", "question": "Assets: XLP, BNB-USD, TLH, ICSH\nAnnualized mean returns: XLP:-0.1872, BNB-USD:0.2486, TLH:-0.2240, ICSH:0.0525\nCovariance matrix (annualized):\n[[0.015699, 0.001419, 0.00451, -4.5e-05], [0.001419, 0.068127, 0.001369, -0.00017], [0.00451, 0.001369, 0.028419, 0.000211], [-4.5e-05, -0.00017, 0.000211, 1.5e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_BNB-USD=0.0059, w_TLH=0.0000, w_ICSH=0.9941", "answer_numeric": 3.516276483639536, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_BNB-USD=0.0059, w_TLH=0.0000, w_ICSH=0.9941\nPortfolio annualized return: 5.37%, volatility: 0.39%\nSharpe ratio: (0.0537 - 0.0400) / 0.0039 = 3.5163", "metadata": {"weights": {"XLP": 0.0, "BNB-USD": 0.0059, "TLH": 0.0, "ICSH": 0.9941}, "sharpe_ratio": 3.5163, "portfolio_return": 0.053667, "portfolio_vol": 0.003887, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241112_0959", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "PALL", "EMB"], "decision_date": "2024-11-12", "context_summary": "4-asset optimization. Max-Sharpe: 3.842. Portfolio: return=83.10%, vol=20.59%. Weights: w_IVV=0.7799, w_SOL-USD=0.2201, w_PALL=0.0000, w_EMB=0.0000.", "question": "Assets: IVV, SOL-USD, PALL, EMB\nAnnualized mean returns: IVV:0.4299, SOL-USD:2.2523, PALL:-0.4764, EMB:-0.0146\nCovariance matrix (annualized):\n[[0.013679, 0.046458, 0.006273, 0.002263], [0.046458, 0.373956, -0.001353, 0.008775], [0.006273, -0.001353, 0.170788, 0.00498], [0.002263, 0.008775, 0.00498, 0.003782]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.7799, w_SOL-USD=0.2201, w_PALL=0.0000, w_EMB=0.0000", "answer_numeric": 3.8423183798080567, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.7799, w_SOL-USD=0.2201, w_PALL=0.0000, w_EMB=0.0000\nPortfolio annualized return: 83.10%, volatility: 20.59%\nSharpe ratio: (0.8310 - 0.0400) / 0.2059 = 3.8423", "metadata": {"weights": {"IVV": 0.7799, "SOL-USD": 0.2201, "PALL": 0.0, "EMB": 0.0}, "sharpe_ratio": 3.8423, "portfolio_return": 0.83102, "portfolio_vol": 0.20587, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240625_0960", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "USO", "BIL"], "decision_date": "2024-06-25", "context_summary": "4-asset optimization. Max-Sharpe: 7.570. Portfolio: return=6.39%, vol=0.32%. Weights: w_IVV=0.0272, w_BTC-USD=0.0000, w_USO=0.0000, w_BIL=0.9728.", "question": "Assets: IVV, BTC-USD, USO, BIL\nAnnualized mean returns: IVV:0.4959, BTC-USD:-0.4496, USO:-0.0311, BIL:0.0518\nCovariance matrix (annualized):\n[[0.008984, 0.020623, 0.006349, -5.6e-05], [0.020623, 0.211638, 0.009015, 6.4e-05], [0.006349, 0.009015, 0.055515, -5.7e-05], [-5.6e-05, 6.4e-05, -5.7e-05, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0272, w_BTC-USD=0.0000, w_USO=0.0000, w_BIL=0.9728", "answer_numeric": 7.570100893544173, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0272, w_BTC-USD=0.0000, w_USO=0.0000, w_BIL=0.9728\nPortfolio annualized return: 6.39%, volatility: 0.32%\nSharpe ratio: (0.0639 - 0.0400) / 0.0032 = 7.5701", "metadata": {"weights": {"IVV": 0.0272, "BTC-USD": 0.0, "USO": 0.0, "BIL": 0.9728}, "sharpe_ratio": 7.5701, "portfolio_return": 0.063863, "portfolio_vol": 0.003152, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240926_0961", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNB-USD", "DBB", "IYR"], "decision_date": "2024-09-26", "context_summary": "4-asset optimization. Max-Sharpe: 4.200. Portfolio: return=55.96%, vol=12.37%. Weights: w_SPY=0.0000, w_BNB-USD=0.0000, w_DBB=0.2364, w_IYR=0.7636.", "question": "Assets: SPY, BNB-USD, DBB, IYR\nAnnualized mean returns: SPY:0.2949, BNB-USD:0.5170, DBB:0.5237, IYR:0.5707\nCovariance matrix (annualized):\n[[0.027621, 0.044772, 0.02292, 0.010344], [0.044772, 0.218887, 0.031013, 0.030167], [0.02292, 0.031013, 0.039478, 0.006432], [0.010344, 0.030167, 0.006432, 0.018477]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0000, w_BNB-USD=0.0000, w_DBB=0.2364, w_IYR=0.7636", "answer_numeric": 4.200404559445559, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0000, w_BNB-USD=0.0000, w_DBB=0.2364, w_IYR=0.7636\nPortfolio annualized return: 55.96%, volatility: 12.37%\nSharpe ratio: (0.5596 - 0.0400) / 0.1237 = 4.2004", "metadata": {"weights": {"SPY": 0.0, "BNB-USD": 0.0, "DBB": 0.2364, "IYR": 0.7636}, "sharpe_ratio": 4.2004, "portfolio_return": 0.55959, "portfolio_vol": 0.1237, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240129_0962", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "INDS", "SGOV"], "decision_date": "2024-01-29", "context_summary": "4-asset optimization. Max-Sharpe: 6.163. Portfolio: return=5.94%, vol=0.31%. Weights: w_^VIX=0.0010, w_ADA-USD=0.0012, w_INDS=0.0018, w_SGOV=0.9961.", "question": "Assets: ^VIX, ADA-USD, INDS, SGOV\nAnnualized mean returns: ^VIX:0.1379, ADA-USD:2.1320, INDS:0.5440, SGOV:0.0559\nCovariance matrix (annualized):\n[[0.373638, -0.103624, -0.024501, -0.000143], [-0.103624, 0.910746, 0.050705, -2.6e-05], [-0.024501, 0.050705, 0.041766, 0.000146], [-0.000143, -2.6e-05, 0.000146, 8e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0010, w_ADA-USD=0.0012, w_INDS=0.0018, w_SGOV=0.9961", "answer_numeric": 6.163115808762474, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0010, w_ADA-USD=0.0012, w_INDS=0.0018, w_SGOV=0.9961\nPortfolio annualized return: 5.94%, volatility: 0.31%\nSharpe ratio: (0.0594 - 0.0400) / 0.0031 = 6.1631", "metadata": {"weights": {"^VIX": 0.001, "ADA-USD": 0.0012, "INDS": 0.0018, "SGOV": 0.9961}, "sharpe_ratio": 6.1631, "portfolio_return": 0.05935, "portfolio_vol": 0.00314, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241108_0963", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BTC-USD", "TLT", "GLD"], "decision_date": "2024-11-08", "context_summary": "4-asset optimization. Max-Sharpe: 5.496. Portfolio: return=92.54%, vol=16.11%. Weights: w_XLP=0.0000, w_BTC-USD=0.3144, w_TLT=0.0000, w_GLD=0.6856.", "question": "Assets: XLP, BTC-USD, TLT, GLD\nAnnualized mean returns: XLP:-0.1905, BTC-USD:1.8498, TLT:-0.4203, GLD:0.5014\nCovariance matrix (annualized):\n[[0.009077, -0.000652, 0.006348, 0.004267], [-0.000652, 0.165842, -0.004857, 0.001331], [0.006348, -0.004857, 0.016657, 0.006779], [0.004267, 0.001331, 0.006779, 0.01912]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_BTC-USD=0.3144, w_TLT=0.0000, w_GLD=0.6856", "answer_numeric": 5.49554626271745, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_BTC-USD=0.3144, w_TLT=0.0000, w_GLD=0.6856\nPortfolio annualized return: 92.54%, volatility: 16.11%\nSharpe ratio: (0.9254 - 0.0400) / 0.1611 = 5.4955", "metadata": {"weights": {"XLP": 0.0, "BTC-USD": 0.3144, "TLT": 0.0, "GLD": 0.6856}, "sharpe_ratio": 5.4955, "portfolio_return": 0.925374, "portfolio_vol": 0.161108, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240903_0964", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "DOT-USD", "SGOV", "UNG"], "decision_date": "2024-09-03", "context_summary": "4-asset optimization. Max-Sharpe: 5.154. Portfolio: return=5.16%, vol=0.22%. Weights: w_MTUM=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_UNG=0.0000.", "question": "Assets: MTUM, DOT-USD, SGOV, UNG\nAnnualized mean returns: MTUM:-0.0642, DOT-USD:-0.9662, SGOV:0.0516, UNG:-1.1345\nCovariance matrix (annualized):\n[[0.067854, 0.053475, 4.7e-05, 0.034123], [0.053475, 0.288816, 0.000283, 0.022726], [4.7e-05, 0.000283, 5e-06, 5.3e-05], [0.034123, 0.022726, 5.3e-05, 0.201597]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_UNG=0.0000", "answer_numeric": 5.153934109202483, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_UNG=0.0000\nPortfolio annualized return: 5.16%, volatility: 0.22%\nSharpe ratio: (0.0516 - 0.0400) / 0.0022 = 5.1539", "metadata": {"weights": {"MTUM": 0.0, "DOT-USD": 0.0, "SGOV": 1.0, "UNG": 0.0}, "sharpe_ratio": 5.1539, "portfolio_return": 0.051556, "portfolio_vol": 0.002242, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240322_0965", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "XHB", "GLD"], "decision_date": "2024-03-22", "context_summary": "4-asset optimization. Max-Sharpe: 5.837. Portfolio: return=77.92%, vol=12.66%. Weights: w_XLU=0.0000, w_AVAX-USD=0.0833, w_XHB=0.2838, w_GLD=0.6330.", "question": "Assets: XLU, AVAX-USD, XHB, GLD\nAnnualized mean returns: XLU:0.3104, AVAX-USD:3.0071, XHB:0.9086, GLD:0.4280\nCovariance matrix (annualized):\n[[0.025767, -0.007592, 0.014187, 0.009048], [-0.007592, 0.782277, 0.007298, -0.004485], [0.014187, 0.007298, 0.050307, 0.006261], [0.009048, -0.004485, 0.006261, 0.011083]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_AVAX-USD=0.0833, w_XHB=0.2838, w_GLD=0.6330", "answer_numeric": 5.836676310019109, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_AVAX-USD=0.0833, w_XHB=0.2838, w_GLD=0.6330\nPortfolio annualized return: 77.92%, volatility: 12.66%\nSharpe ratio: (0.7792 - 0.0400) / 0.1266 = 5.8367", "metadata": {"weights": {"XLU": 0.0, "AVAX-USD": 0.0833, "XHB": 0.2838, "GLD": 0.633}, "sharpe_ratio": 5.8367, "portfolio_return": 0.779156, "portfolio_vol": 0.12664, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240618_0967", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BTC-USD", "PPLT", "REZ"], "decision_date": "2024-06-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.503. Portfolio: return=62.69%, vol=13.03%. Weights: w_XLP=0.0417, w_BTC-USD=0.0000, w_PPLT=0.0000, w_REZ=0.9583.", "question": "Assets: XLP, BTC-USD, PPLT, REZ\nAnnualized mean returns: XLP:0.3216, BTC-USD:0.0462, PPLT:0.2249, REZ:0.6402\nCovariance matrix (annualized):\n[[0.010902, 0.002226, 0.004862, 0.008031], [0.002226, 0.202849, 0.001698, 0.019996], [0.004862, 0.001698, 0.076743, 0.010793], [0.008031, 0.019996, 0.010793, 0.017778]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0417, w_BTC-USD=0.0000, w_PPLT=0.0000, w_REZ=0.9583", "answer_numeric": 4.502950544524178, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0417, w_BTC-USD=0.0000, w_PPLT=0.0000, w_REZ=0.9583\nPortfolio annualized return: 62.69%, volatility: 13.03%\nSharpe ratio: (0.6269 - 0.0400) / 0.1303 = 4.5030", "metadata": {"weights": {"XLP": 0.0417, "BTC-USD": 0.0, "PPLT": 0.0, "REZ": 0.9583}, "sharpe_ratio": 4.503, "portfolio_return": 0.626903, "portfolio_vol": 0.130338, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20240911_0969", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "AVAX-USD", "SOYB", "SCHH"], "decision_date": "2024-09-11", "context_summary": "4-asset optimization. Max-Sharpe: 4.280. Portfolio: return=66.63%, vol=14.63%. Weights: w_IVV=0.0000, w_AVAX-USD=0.0000, w_SOYB=0.0000, w_SCHH=1.0000.", "question": "Assets: IVV, AVAX-USD, SOYB, SCHH\nAnnualized mean returns: IVV:-0.1273, AVAX-USD:-0.3300, SOYB:-0.2852, SCHH:0.6663\nCovariance matrix (annualized):\n[[0.033565, 0.071303, -0.001294, 0.01484], [0.071303, 0.579873, -0.065419, 0.054415], [-0.001294, -0.065419, 0.044056, -0.005085], [0.01484, 0.054415, -0.005085, 0.021407]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_AVAX-USD=0.0000, w_SOYB=0.0000, w_SCHH=1.0000", "answer_numeric": 4.28041548850663, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_AVAX-USD=0.0000, w_SOYB=0.0000, w_SCHH=1.0000\nPortfolio annualized return: 66.63%, volatility: 14.63%\nSharpe ratio: (0.6663 - 0.0400) / 0.1463 = 4.2804", "metadata": {"weights": {"IVV": 0.0, "AVAX-USD": 0.0, "SOYB": 0.0, "SCHH": 1.0}, "sharpe_ratio": 4.2804, "portfolio_return": 0.666271, "portfolio_vol": 0.146311, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230127_0970", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "XRP-USD", "SHV", "PDBC"], "decision_date": "2023-01-27", "context_summary": "4-asset optimization. Max-Sharpe: 2.022. Portfolio: return=4.65%, vol=0.32%. Weights: w_QUAL=0.0000, w_XRP-USD=0.0030, w_SHV=0.9933, w_PDBC=0.0037.", "question": "Assets: QUAL, XRP-USD, SHV, PDBC\nAnnualized mean returns: QUAL:0.1120, XRP-USD:0.4395, SHV:0.0449, PDBC:0.1625\nCovariance matrix (annualized):\n[[0.038459, 0.040761, -1.8e-05, 0.022248], [0.040761, 0.202404, -0.000125, 0.041658], [-1.8e-05, -0.000125, 8e-06, -6.9e-05], [0.022248, 0.041658, -6.9e-05, 0.037315]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_XRP-USD=0.0030, w_SHV=0.9933, w_PDBC=0.0037", "answer_numeric": 2.0222009765001574, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_XRP-USD=0.0030, w_SHV=0.9933, w_PDBC=0.0037\nPortfolio annualized return: 4.65%, volatility: 0.32%\nSharpe ratio: (0.0465 - 0.0400) / 0.0032 = 2.0222", "metadata": {"weights": {"QUAL": 0.0, "XRP-USD": 0.003, "SHV": 0.9933, "PDBC": 0.0037}, "sharpe_ratio": 2.0222, "portfolio_return": 0.046491, "portfolio_vol": 0.00321, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20241216_0972", "template": "T5", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VEA", "LINK-USD", "CSHI", "TLT"], "decision_date": "2024-12-16", "context_summary": "4-asset optimization. Max-Sharpe: 3.784. Portfolio: return=111.22%, vol=28.34%. Weights: w_VEA=0.2500, w_LINK-USD=0.2500, w_CSHI=0.2500, w_TLT=0.2500.", "question": "Assets: VEA, LINK-USD, CSHI, TLT\nAnnualized mean returns: VEA:-0.1913, LINK-USD:4.8567, CSHI:0.0555, TLT:-0.2721\nCovariance matrix (annualized):\n[[0.012486, 0.014253, -9e-05, 0.00809], [0.014253, 1.19252, 0.000764, 0.005076], [-9e-05, 0.000764, 2e-05, 4e-06], [0.00809, 0.005076, 4e-06, 0.023391]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.2500, w_LINK-USD=0.2500, w_CSHI=0.2500, w_TLT=0.2500", "answer_numeric": 3.7839111819505784, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.2500, w_LINK-USD=0.2500, w_CSHI=0.2500, w_TLT=0.2500\nPortfolio annualized return: 111.22%, volatility: 28.34%\nSharpe ratio: (1.1122 - 0.0400) / 0.2834 = 3.7839", "metadata": {"weights": {"VEA": 0.25, "LINK-USD": 0.25, "CSHI": 0.25, "TLT": 0.25}, "sharpe_ratio": 3.7839, "portfolio_return": 1.112178, "portfolio_vol": 0.283352, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241011_0974", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "SOL-USD", "BIL", "SHY"], "decision_date": "2024-10-11", "context_summary": "4-asset optimization. Max-Sharpe: 3.894. Portfolio: return=5.05%, vol=0.27%. Weights: w_XLRE=0.0054, w_SOL-USD=0.0000, w_BIL=0.9946, w_SHY=0.0000.", "question": "Assets: XLRE, SOL-USD, BIL, SHY\nAnnualized mean returns: XLRE:0.2040, SOL-USD:-0.1946, BIL:0.0497, SHY:0.0447\nCovariance matrix (annualized):\n[[0.011444, 0.008868, 5.2e-05, 0.00081], [0.008868, 0.268541, -3.2e-05, 0.001655], [5.2e-05, -3.2e-05, 7e-06, 2e-05], [0.00081, 0.001655, 2e-05, 0.00033]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0054, w_SOL-USD=0.0000, w_BIL=0.9946, w_SHY=0.0000", "answer_numeric": 3.8938272005864376, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0054, w_SOL-USD=0.0000, w_BIL=0.9946, w_SHY=0.0000\nPortfolio annualized return: 5.05%, volatility: 0.27%\nSharpe ratio: (0.0505 - 0.0400) / 0.0027 = 3.8938", "metadata": {"weights": {"XLRE": 0.0054, "SOL-USD": 0.0, "BIL": 0.9946, "SHY": 0.0}, "sharpe_ratio": 3.8938, "portfolio_return": 0.050543, "portfolio_vol": 0.002708, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20230518_0975", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ADA-USD", "PPLT", "ICSH"], "decision_date": "2023-05-18", "context_summary": "4-asset optimization. Max-Sharpe: 3.132. Portfolio: return=19.28%, vol=4.88%. Weights: w_XLU=0.0231, w_ADA-USD=0.0596, w_PPLT=0.1598, w_ICSH=0.7575.", "question": "Assets: XLU, ADA-USD, PPLT, ICSH\nAnnualized mean returns: XLU:-0.0285, ADA-USD:0.9697, PPLT:0.6345, ICSH:0.0453\nCovariance matrix (annualized):\n[[0.030294, -0.020473, -0.002998, -9.1e-05], [-0.020473, 0.294857, -0.017402, 0.000236], [-0.002998, -0.017402, 0.063785, 0.000234], [-9.1e-05, 0.000236, 0.000234, 4.4e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0231, w_ADA-USD=0.0596, w_PPLT=0.1598, w_ICSH=0.7575", "answer_numeric": 3.1316381960301873, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0231, w_ADA-USD=0.0596, w_PPLT=0.1598, w_ICSH=0.7575\nPortfolio annualized return: 19.28%, volatility: 4.88%\nSharpe ratio: (0.1928 - 0.0400) / 0.0488 = 3.1316", "metadata": {"weights": {"XLU": 0.0231, "ADA-USD": 0.0596, "PPLT": 0.1598, "ICSH": 0.7575}, "sharpe_ratio": 3.1316, "portfolio_return": 0.192822, "portfolio_vol": 0.048799, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240613_0976", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "XRP-USD", "MORT", "EMB"], "decision_date": "2024-06-13", "context_summary": "4-asset optimization. Max-Sharpe: 2.984. Portfolio: return=51.47%, vol=15.91%. Weights: w_XLU=1.0000, w_XRP-USD=0.0000, w_MORT=0.0000, w_EMB=0.0000.", "question": "Assets: XLU, XRP-USD, MORT, EMB\nAnnualized mean returns: XLU:0.5147, XRP-USD:0.1469, MORT:0.2697, EMB:0.1340\nCovariance matrix (annualized):\n[[0.025302, 0.013718, 0.015842, 0.007103], [0.013718, 0.129068, 0.020599, 0.01528], [0.015842, 0.020599, 0.033362, 0.010507], [0.007103, 0.01528, 0.010507, 0.006552]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=1.0000, w_XRP-USD=0.0000, w_MORT=0.0000, w_EMB=0.0000", "answer_numeric": 2.984089896052951, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=1.0000, w_XRP-USD=0.0000, w_MORT=0.0000, w_EMB=0.0000\nPortfolio annualized return: 51.47%, volatility: 15.91%\nSharpe ratio: (0.5147 - 0.0400) / 0.1591 = 2.9841", "metadata": {"weights": {"XLU": 1.0, "XRP-USD": 0.0, "MORT": 0.0, "EMB": 0.0}, "sharpe_ratio": 2.9841, "portfolio_return": 0.514665, "portfolio_vol": 0.159065, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20241024_0977", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ETH-USD", "IGOV", "SGOV"], "decision_date": "2024-10-24", "context_summary": "4-asset optimization. Max-Sharpe: 4.377. Portfolio: return=5.33%, vol=0.30%. Weights: w_XLI=0.0133, w_ETH-USD=0.0000, w_IGOV=0.0000, w_SGOV=0.9867.", "question": "Assets: XLI, ETH-USD, IGOV, SGOV\nAnnualized mean returns: XLI:0.3543, ETH-USD:-0.6899, IGOV:-0.2446, SGOV:0.0492\nCovariance matrix (annualized):\n[[0.016199, 0.031559, 0.000843, 2e-06], [0.031559, 0.238607, 0.010314, 0.000103], [0.000843, 0.010314, 0.004951, 2e-05], [2e-06, 0.000103, 2e-05, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0133, w_ETH-USD=0.0000, w_IGOV=0.0000, w_SGOV=0.9867", "answer_numeric": 4.377467201523116, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0133, w_ETH-USD=0.0000, w_IGOV=0.0000, w_SGOV=0.9867\nPortfolio annualized return: 5.33%, volatility: 0.30%\nSharpe ratio: (0.0533 - 0.0400) / 0.0030 = 4.3775", "metadata": {"weights": {"XLI": 0.0133, "ETH-USD": 0.0, "IGOV": 0.0, "SGOV": 0.9867}, "sharpe_ratio": 4.3775, "portfolio_return": 0.05327, "portfolio_vol": 0.003031, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20230726_0978", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "SHV", "SGOV"], "decision_date": "2023-07-26", "context_summary": "4-asset optimization. Max-Sharpe: 5.392. Portfolio: return=5.51%, vol=0.28%. Weights: w_XLP=0.0117, w_DOT-USD=0.0004, w_SHV=0.0000, w_SGOV=0.9880.", "question": "Assets: XLP, DOT-USD, SHV, SGOV\nAnnualized mean returns: XLP:0.2595, DOT-USD:0.0749, SHV:0.0482, SGOV:0.0527\nCovariance matrix (annualized):\n[[0.008657, 0.002512, 9.7e-05, 1.2e-05], [0.002512, 0.201255, 0.0001, -8.6e-05], [9.7e-05, 0.0001, 8e-06, 4e-06], [1.2e-05, -8.6e-05, 4e-06, 7e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0117, w_DOT-USD=0.0004, w_SHV=0.0000, w_SGOV=0.9880", "answer_numeric": 5.392062194730492, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0117, w_DOT-USD=0.0004, w_SHV=0.0000, w_SGOV=0.9880\nPortfolio annualized return: 5.51%, volatility: 0.28%\nSharpe ratio: (0.0551 - 0.0400) / 0.0028 = 5.3921", "metadata": {"weights": {"XLP": 0.0117, "DOT-USD": 0.0004, "SHV": 0.0, "SGOV": 0.988}, "sharpe_ratio": 5.3921, "portfolio_return": 0.055142, "portfolio_vol": 0.002808, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20240214_0980", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SOL-USD", "IAU", "ICSH"], "decision_date": "2024-02-14", "context_summary": "4-asset optimization. Max-Sharpe: 5.020. Portfolio: return=6.64%, vol=0.53%. Weights: w_XLI=0.0000, w_SOL-USD=0.0052, w_IAU=0.0000, w_ICSH=0.9948.", "question": "Assets: XLI, SOL-USD, IAU, ICSH\nAnnualized mean returns: XLI:0.1990, SOL-USD:2.5572, IAU:-0.0787, ICSH:0.0535\nCovariance matrix (annualized):\n[[0.014792, -0.003877, 0.007404, 0.000204], [-0.003877, 0.747093, -0.016482, -0.001235], [0.007404, -0.016482, 0.0097, 0.000323], [0.000204, -0.001235, 0.000323, 2.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_SOL-USD=0.0052, w_IAU=0.0000, w_ICSH=0.9948", "answer_numeric": 5.020237530266215, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_SOL-USD=0.0052, w_IAU=0.0000, w_ICSH=0.9948\nPortfolio annualized return: 6.64%, volatility: 0.53%\nSharpe ratio: (0.0664 - 0.0400) / 0.0053 = 5.0202", "metadata": {"weights": {"XLI": 0.0, "SOL-USD": 0.0052, "IAU": 0.0, "ICSH": 0.9948}, "sharpe_ratio": 5.0202, "portfolio_return": 0.066434, "portfolio_vol": 0.005265, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20230224_0982", "template": "T5", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "VNQI", "DBA"], "decision_date": "2023-02-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.955. Portfolio: return=155.28%, vol=38.25%. Weights: w_VTI=0.0414, w_MATIC-USD=0.5127, w_VNQI=0.0000, w_DBA=0.4458.", "question": "Assets: VTI, MATIC-USD, VNQI, DBA\nAnnualized mean returns: VTI:0.3305, MATIC-USD:2.9005, VNQI:0.1684, DBA:0.1165\nCovariance matrix (annualized):\n[[0.029397, 0.052722, 0.020062, -0.000353], [0.052722, 0.530776, 0.029616, 0.005133], [0.020062, 0.029616, 0.025723, -0.002883], [-0.000353, 0.005133, -0.002883, 0.010732]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0414, w_MATIC-USD=0.5127, w_VNQI=0.0000, w_DBA=0.4458", "answer_numeric": 3.955199424330556, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0414, w_MATIC-USD=0.5127, w_VNQI=0.0000, w_DBA=0.4458\nPortfolio annualized return: 155.28%, volatility: 38.25%\nSharpe ratio: (1.5528 - 0.0400) / 0.3825 = 3.9552", "metadata": {"weights": {"VTI": 0.0414, "MATIC-USD": 0.5127, "VNQI": 0.0, "DBA": 0.4458}, "sharpe_ratio": 3.9552, "portfolio_return": 1.552801, "portfolio_vol": 0.382484, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T6_all_20231219_0000", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "SGOV", "PDBC"], "decision_date": "2023-12-19", "context_summary": "Max weight deviation: 0.0224, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.1850, target=0.2500\n BNB-USD: current=0.2938, target=0.2500\n SGOV: current=0.2636, target=0.2500\n PDBC: current=0.2575, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of IVV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0224.\nRebalancing threshold: 0.0500.\n0.0224 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0448, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.185, "BNB-USD": 0.2938, "SGOV": 0.2636, "PDBC": 0.2575}, "target_weights": {"IVV": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "PDBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.044754, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IVV", "primary_trade": -0.065}} +{"id": "T6_all_20230517_0003", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "ICSH", "GLD"], "decision_date": "2023-05-17", "context_summary": "Max weight deviation: 0.0320, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2633, target=0.2500\n ADA-USD: current=0.2794, target=0.2500\n ICSH: current=0.2180, target=0.2500\n GLD: current=0.2392, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0320.\nRebalancing threshold: 0.0500.\n0.0320 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0855, transaction cost = 0.000086 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2633, "ADA-USD": 0.2794, "ICSH": 0.218, "GLD": 0.2392}, "target_weights": {"XLY": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "GLD": 0.25}, "max_deviation": 0.032, "total_turnover": 0.085538, "transaction_cost": 8.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.032}} +{"id": "T6_all_20230919_0005", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SOL-USD", "TLH", "SGOV"], "decision_date": "2023-09-19", "context_summary": "Max weight deviation: 0.0207, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2321, target=0.2500\n SOL-USD: current=0.2502, target=0.2500\n TLH: current=0.2707, target=0.2500\n SGOV: current=0.2470, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0207.\nRebalancing threshold: 0.0500.\n0.0207 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0418, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2321, "SOL-USD": 0.2502, "TLH": 0.2707, "SGOV": 0.247}, "target_weights": {"VTI": 0.25, "SOL-USD": 0.25, "TLH": 0.25, "SGOV": 0.25}, "max_deviation": 0.0207, "total_turnover": 0.041824, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": 0.0207}} +{"id": "T6_all_20240423_0008", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "SOL-USD", "ITB", "DBB"], "decision_date": "2024-04-23", "context_summary": "Max weight deviation: 0.0293, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2831, target=0.2500\n SOL-USD: current=0.2788, target=0.2500\n ITB: current=0.1850, target=0.2500\n DBB: current=0.2531, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of ITB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0293.\nRebalancing threshold: 0.0500.\n0.0293 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0586, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2831, "SOL-USD": 0.2788, "ITB": 0.185, "DBB": 0.2531}, "target_weights": {"QQQ": 0.25, "SOL-USD": 0.25, "ITB": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.058634, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "ITB", "primary_trade": -0.065}} +{"id": "T6_all_20230728_0011", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "SCHP", "HAUZ"], "decision_date": "2023-07-28", "context_summary": "Max weight deviation: 0.0183, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2616, target=0.2500\n BTC-USD: current=0.2354, target=0.2500\n SCHP: current=0.2347, target=0.2500\n HAUZ: current=0.2683, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0183.\nRebalancing threshold: 0.0500.\n0.0183 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0599, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2616, "BTC-USD": 0.2354, "SCHP": 0.2347, "HAUZ": 0.2683}, "target_weights": {"EFA": 0.25, "BTC-USD": 0.25, "SCHP": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0183, "total_turnover": 0.059859, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "HAUZ", "primary_trade": 0.0183}} +{"id": "T6_all_20231013_0012", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "BIL", "LQD"], "decision_date": "2023-10-13", "context_summary": "Max weight deviation: 0.0275, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.1952, target=0.2500\n AVAX-USD: current=0.2826, target=0.2500\n BIL: current=0.2072, target=0.2500\n LQD: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of LQD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0275.\nRebalancing threshold: 0.0500.\n0.0275 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0825, transaction cost = 0.000083 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.1952, "AVAX-USD": 0.2826, "BIL": 0.2072, "LQD": 0.315}, "target_weights": {"EWJ": 0.25, "AVAX-USD": 0.25, "BIL": 0.25, "LQD": 0.25}, "max_deviation": 0.065, "total_turnover": 0.082533, "transaction_cost": 8.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LQD", "primary_trade": 0.065}} +{"id": "T6_all_20231024_0015", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "LINK-USD", "SGOV", "INDS"], "decision_date": "2023-10-24", "context_summary": "Max weight deviation: 0.0385, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2467, target=0.2500\n LINK-USD: current=0.2269, target=0.2500\n SGOV: current=0.2885, target=0.2500\n INDS: current=0.2378, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0385.\nRebalancing threshold: 0.0500.\n0.0385 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0770, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2467, "LINK-USD": 0.2269, "SGOV": 0.2885, "INDS": 0.2378}, "target_weights": {"VTI": 0.25, "LINK-USD": 0.25, "SGOV": 0.25, "INDS": 0.25}, "max_deviation": 0.0385, "total_turnover": 0.076994, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0385}} +{"id": "T6_all_20230626_0017", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "AVAX-USD", "DBB", "CSHI"], "decision_date": "2023-06-26", "context_summary": "Max weight deviation: 0.0454, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2630, target=0.2500\n AVAX-USD: current=0.2785, target=0.2500\n DBB: current=0.2046, target=0.2500\n CSHI: current=0.2540, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0454.\nRebalancing threshold: 0.0500.\n0.0454 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0908, transaction cost = 0.000091 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.263, "AVAX-USD": 0.2785, "DBB": 0.2046, "CSHI": 0.254}, "target_weights": {"XLY": 0.25, "AVAX-USD": 0.25, "DBB": 0.25, "CSHI": 0.25}, "max_deviation": 0.0454, "total_turnover": 0.090788, "transaction_cost": 9.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": -0.0454}} +{"id": "T6_all_20230928_0018", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "MATIC-USD", "TLT", "CSHI"], "decision_date": "2023-09-28", "context_summary": "Max weight deviation: 0.0214, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2268, target=0.2500\n MATIC-USD: current=0.2542, target=0.2500\n TLT: current=0.2041, target=0.2500\n CSHI: current=0.3149, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of CSHI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0214.\nRebalancing threshold: 0.0500.\n0.0214 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0455, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2268, "MATIC-USD": 0.2542, "TLT": 0.2041, "CSHI": 0.3149}, "target_weights": {"XLE": 0.25, "MATIC-USD": 0.25, "TLT": 0.25, "CSHI": 0.25}, "max_deviation": 0.064904, "total_turnover": 0.045534, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "CSHI", "primary_trade": 0.0649}} +{"id": "T6_all_20241212_0022", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX", "MATIC-USD", "SGOV", "IGOV"], "decision_date": "2024-12-12", "context_summary": "Max weight deviation: 0.0108, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.1922, target=0.2500\n MATIC-USD: current=0.3150, target=0.2500\n SGOV: current=0.3030, target=0.2500\n IGOV: current=0.1898, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of MATIC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0108.\nRebalancing threshold: 0.0500.\n0.0108 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0392, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.1922, "MATIC-USD": 0.315, "SGOV": 0.303, "IGOV": 0.1898}, "target_weights": {"^VIX": 0.25, "MATIC-USD": 0.25, "SGOV": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.039167, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "MATIC-USD", "primary_trade": 0.065}} +{"id": "T6_all_20230117_0024", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "XHB", "SGOV"], "decision_date": "2023-01-17", "context_summary": "Max weight deviation: 0.0313, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.3149, target=0.2500\n DOT-USD: current=0.2174, target=0.2500\n XHB: current=0.2101, target=0.2500\n SGOV: current=0.2576, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of XLY", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0313.\nRebalancing threshold: 0.0500.\n0.0313 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0699, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.3149, "DOT-USD": 0.2174, "XHB": 0.2101, "SGOV": 0.2576}, "target_weights": {"XLY": 0.25, "DOT-USD": 0.25, "XHB": 0.25, "SGOV": 0.25}, "max_deviation": 0.064935, "total_turnover": 0.069921, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLY", "primary_trade": 0.0649}} +{"id": "T6_all_20240610_0025", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "SHV", "SGOV"], "decision_date": "2024-06-10", "context_summary": "Max weight deviation: 0.0210, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2379, target=0.2500\n XRP-USD: current=0.2710, target=0.2500\n SHV: current=0.2567, target=0.2500\n SGOV: current=0.2345, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0210.\nRebalancing threshold: 0.0500.\n0.0210 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0553, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2379, "XRP-USD": 0.271, "SHV": 0.2567, "SGOV": 0.2345}, "target_weights": {"XLF": 0.25, "XRP-USD": 0.25, "SHV": 0.25, "SGOV": 0.25}, "max_deviation": 0.021, "total_turnover": 0.055293, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XRP-USD", "primary_trade": 0.021}} +{"id": "T6_all_20230920_0029", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "DOT-USD", "TLT", "MORT"], "decision_date": "2023-09-20", "context_summary": "Max weight deviation: 0.0166, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2437, target=0.2500\n DOT-USD: current=0.2441, target=0.2500\n TLT: current=0.2666, target=0.2500\n MORT: current=0.2456, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0166.\nRebalancing threshold: 0.0500.\n0.0166 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0332, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2437, "DOT-USD": 0.2441, "TLT": 0.2666, "MORT": 0.2456}, "target_weights": {"VTI": 0.25, "DOT-USD": 0.25, "TLT": 0.25, "MORT": 0.25}, "max_deviation": 0.0166, "total_turnover": 0.033211, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLT", "primary_trade": 0.0166}} +{"id": "T6_all_20230512_0031", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "XRP-USD", "HAUZ", "SGOV"], "decision_date": "2023-05-12", "context_summary": "Max weight deviation: 0.0168, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2636, target=0.2500\n XRP-USD: current=0.2332, target=0.2500\n HAUZ: current=0.2530, target=0.2500\n SGOV: current=0.2502, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0168.\nRebalancing threshold: 0.0500.\n0.0168 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0336, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2636, "XRP-USD": 0.2332, "HAUZ": 0.253, "SGOV": 0.2502}, "target_weights": {"EFA": 0.25, "XRP-USD": 0.25, "HAUZ": 0.25, "SGOV": 0.25}, "max_deviation": 0.0168, "total_turnover": 0.033641, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.0168}} +{"id": "T6_all_20240620_0033", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "BIL", "IEF"], "decision_date": "2024-06-20", "context_summary": "Max weight deviation: 0.0225, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2484, target=0.2500\n XRP-USD: current=0.2725, target=0.2500\n BIL: current=0.2431, target=0.2500\n IEF: current=0.2360, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0225.\nRebalancing threshold: 0.0500.\n0.0225 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0450, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2484, "XRP-USD": 0.2725, "BIL": 0.2431, "IEF": 0.236}, "target_weights": {"EWJ": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "IEF": 0.25}, "max_deviation": 0.0225, "total_turnover": 0.045009, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XRP-USD", "primary_trade": 0.0225}} +{"id": "T6_all_20240503_0035", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "SCHP", "PPLT"], "decision_date": "2024-05-03", "context_summary": "Max weight deviation: 0.0273, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2258, target=0.2500\n ADA-USD: current=0.2528, target=0.2500\n SCHP: current=0.2773, target=0.2500\n PPLT: current=0.2441, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0273.\nRebalancing threshold: 0.0500.\n0.0273 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0602, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2258, "ADA-USD": 0.2528, "SCHP": 0.2773, "PPLT": 0.2441}, "target_weights": {"QUAL": 0.25, "ADA-USD": 0.25, "SCHP": 0.25, "PPLT": 0.25}, "max_deviation": 0.0273, "total_turnover": 0.060248, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SCHP", "primary_trade": 0.0273}} +{"id": "T6_all_20230911_0038", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "DOT-USD", "TIP", "XHB"], "decision_date": "2023-09-11", "context_summary": "Max weight deviation: 0.0152, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.1850, target=0.2500\n DOT-USD: current=0.2338, target=0.2500\n TIP: current=0.2791, target=0.2500\n XHB: current=0.3022, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of USMV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0152.\nRebalancing threshold: 0.0500.\n0.0152 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0380, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.185, "DOT-USD": 0.2338, "TIP": 0.2791, "XHB": 0.3022}, "target_weights": {"USMV": 0.25, "DOT-USD": 0.25, "TIP": 0.25, "XHB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.038015, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": -0.065}} +{"id": "T6_all_20230929_0039", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "DBC", "SGOV"], "decision_date": "2023-09-29", "context_summary": "Max weight deviation: 0.0261, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2291, target=0.2500\n DOT-USD: current=0.2604, target=0.2500\n DBC: current=0.2761, target=0.2500\n SGOV: current=0.2344, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0261.\nRebalancing threshold: 0.0500.\n0.0261 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0730, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2291, "DOT-USD": 0.2604, "DBC": 0.2761, "SGOV": 0.2344}, "target_weights": {"XLE": 0.25, "DOT-USD": 0.25, "DBC": 0.25, "SGOV": 0.25}, "max_deviation": 0.0261, "total_turnover": 0.072997, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBC", "primary_trade": 0.0261}} +{"id": "T6_all_20231106_0040", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "CSHI", "JNK"], "decision_date": "2023-11-06", "context_summary": "Max weight deviation: 0.0310, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.1923, target=0.2500\n MATIC-USD: current=0.2773, target=0.2500\n CSHI: current=0.3150, target=0.2500\n JNK: current=0.2154, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of CSHI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0310.\nRebalancing threshold: 0.0500.\n0.0310 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0880, transaction cost = 0.000088 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.1923, "MATIC-USD": 0.2773, "CSHI": 0.315, "JNK": 0.2154}, "target_weights": {"VTI": 0.25, "MATIC-USD": 0.25, "CSHI": 0.25, "JNK": 0.25}, "max_deviation": 0.065, "total_turnover": 0.087997, "transaction_cost": 8.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "CSHI", "primary_trade": 0.065}} +{"id": "T6_all_20240619_0042", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "ICSH", "IGOV"], "decision_date": "2024-06-19", "context_summary": "Max weight deviation: 0.0204, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.1850, target=0.2500\n XRP-USD: current=0.2828, target=0.2500\n ICSH: current=0.2541, target=0.2500\n IGOV: current=0.2780, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of VLUE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0204.\nRebalancing threshold: 0.0500.\n0.0204 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0407, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.185, "XRP-USD": 0.2828, "ICSH": 0.2541, "IGOV": 0.278}, "target_weights": {"VLUE": 0.25, "XRP-USD": 0.25, "ICSH": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.040733, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "VLUE", "primary_trade": -0.065}} +{"id": "T6_all_20231102_0043", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ADA-USD", "PPLT", "ICSH"], "decision_date": "2023-11-02", "context_summary": "Max weight deviation: 0.0148, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2470, target=0.2500\n ADA-USD: current=0.2372, target=0.2500\n PPLT: current=0.2648, target=0.2500\n ICSH: current=0.2510, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0148.\nRebalancing threshold: 0.0500.\n0.0148 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0316, transaction cost = 0.000032 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.247, "ADA-USD": 0.2372, "PPLT": 0.2648, "ICSH": 0.251}, "target_weights": {"EEM": 0.25, "ADA-USD": 0.25, "PPLT": 0.25, "ICSH": 0.25}, "max_deviation": 0.0148, "total_turnover": 0.031634, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "PPLT", "primary_trade": 0.0148}} +{"id": "T6_all_20230810_0047", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ETH-USD", "BIL", "IGOV"], "decision_date": "2023-08-10", "context_summary": "Max weight deviation: 0.0109, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2525, target=0.2500\n ETH-USD: current=0.2582, target=0.2500\n BIL: current=0.2502, target=0.2500\n IGOV: current=0.2391, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0109.\nRebalancing threshold: 0.0500.\n0.0109 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0219, transaction cost = 0.000022 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2525, "ETH-USD": 0.2582, "BIL": 0.2502, "IGOV": 0.2391}, "target_weights": {"EWJ": 0.25, "ETH-USD": 0.25, "BIL": 0.25, "IGOV": 0.25}, "max_deviation": 0.0109, "total_turnover": 0.02185, "transaction_cost": 2.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IGOV", "primary_trade": -0.0109}} +{"id": "T6_all_20230411_0050", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "SCHP", "UNG"], "decision_date": "2023-04-11", "context_summary": "Max weight deviation: 0.0270, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2854, target=0.2500\n ADA-USD: current=0.1850, target=0.2500\n SCHP: current=0.2356, target=0.2500\n UNG: current=0.2941, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of ADA-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0270.\nRebalancing threshold: 0.0500.\n0.0270 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0661, transaction cost = 0.000066 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2854, "ADA-USD": 0.185, "SCHP": 0.2356, "UNG": 0.2941}, "target_weights": {"EFA": 0.25, "ADA-USD": 0.25, "SCHP": 0.25, "UNG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.066062, "transaction_cost": 6.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": -0.065}} +{"id": "T6_all_20231107_0052", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "BIL", "BNDX"], "decision_date": "2023-11-07", "context_summary": "Max weight deviation: 0.0257, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.3150, target=0.2500\n BTC-USD: current=0.1850, target=0.2500\n BIL: current=0.2510, target=0.2500\n BNDX: current=0.2490, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of USMV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0257.\nRebalancing threshold: 0.0500.\n0.0257 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0522, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.315, "BTC-USD": 0.185, "BIL": 0.251, "BNDX": 0.249}, "target_weights": {"USMV": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "BNDX": 0.25}, "max_deviation": 0.065, "total_turnover": 0.052196, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": 0.065}} +{"id": "T6_all_20231113_0055", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "ICSH", "PDBC"], "decision_date": "2023-11-13", "context_summary": "Max weight deviation: 0.0250, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2250, target=0.2500\n DOT-USD: current=0.2542, target=0.2500\n ICSH: current=0.2521, target=0.2500\n PDBC: current=0.2687, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0250.\nRebalancing threshold: 0.0500.\n0.0250 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0500, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.225, "DOT-USD": 0.2542, "ICSH": 0.2521, "PDBC": 0.2687}, "target_weights": {"XLP": 0.25, "DOT-USD": 0.25, "ICSH": 0.25, "PDBC": 0.25}, "max_deviation": 0.025, "total_turnover": 0.050046, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLP", "primary_trade": -0.025}} +{"id": "T6_all_20240305_0058", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "SGOV", "SCHP"], "decision_date": "2024-03-05", "context_summary": "Max weight deviation: 0.0256, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.1913, target=0.2500\n BNB-USD: current=0.3149, target=0.2500\n SGOV: current=0.2053, target=0.2500\n SCHP: current=0.2885, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of BNB-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0256.\nRebalancing threshold: 0.0500.\n0.0256 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0814, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.1913, "BNB-USD": 0.3149, "SGOV": 0.2053, "SCHP": 0.2885}, "target_weights": {"XLF": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "SCHP": 0.25}, "max_deviation": 0.06492, "total_turnover": 0.081449, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "BNB-USD", "primary_trade": 0.0649}} +{"id": "T6_all_20230302_0059", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "XRP-USD", "USO", "IYR"], "decision_date": "2023-03-02", "context_summary": "Max weight deviation: 0.0227, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.2448, target=0.2500\n XRP-USD: current=0.2409, target=0.2500\n USO: current=0.2727, target=0.2500\n IYR: current=0.2416, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0227.\nRebalancing threshold: 0.0500.\n0.0227 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0454, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2448, "XRP-USD": 0.2409, "USO": 0.2727, "IYR": 0.2416}, "target_weights": {"XLI": 0.25, "XRP-USD": 0.25, "USO": 0.25, "IYR": 0.25}, "max_deviation": 0.0227, "total_turnover": 0.045387, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "USO", "primary_trade": 0.0227}} +{"id": "T6_all_20241015_0060", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "LINK-USD", "SHV", "BNO"], "decision_date": "2024-10-15", "context_summary": "Max weight deviation: 0.0173, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2437, target=0.2500\n LINK-USD: current=0.1851, target=0.2500\n SHV: current=0.2866, target=0.2500\n BNO: current=0.2847, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0649 of LINK-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0173.\nRebalancing threshold: 0.0500.\n0.0173 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0379, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2437, "LINK-USD": 0.1851, "SHV": 0.2866, "BNO": 0.2847}, "target_weights": {"QQQ": 0.25, "LINK-USD": 0.25, "SHV": 0.25, "BNO": 0.25}, "max_deviation": 0.06493, "total_turnover": 0.037935, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "LINK-USD", "primary_trade": -0.0649}} +{"id": "T6_all_20240313_0064", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "SOL-USD", "LQD", "UNG"], "decision_date": "2024-03-13", "context_summary": "Max weight deviation: 0.0303, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.3015, target=0.2500\n SOL-USD: current=0.2047, target=0.2500\n LQD: current=0.3088, target=0.2500\n UNG: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of UNG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0303.\nRebalancing threshold: 0.0500.\n0.0303 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1028, transaction cost = 0.000103 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3015, "SOL-USD": 0.2047, "LQD": 0.3088, "UNG": 0.185}, "target_weights": {"XLRE": 0.25, "SOL-USD": 0.25, "LQD": 0.25, "UNG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.102799, "transaction_cost": 0.000103, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "UNG", "primary_trade": -0.065}} +{"id": "T6_all_20230627_0066", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "IYR", "SHV"], "decision_date": "2023-06-27", "context_summary": "Max weight deviation: 0.0084, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.1859, target=0.2500\n ADA-USD: current=0.3152, target=0.2500\n IYR: current=0.2378, target=0.2500\n SHV: current=0.2610, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0652 of ADA-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0084.\nRebalancing threshold: 0.0500.\n0.0084 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0196, transaction cost = 0.000020 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.1859, "ADA-USD": 0.3152, "IYR": 0.2378, "SHV": 0.261}, "target_weights": {"VEA": 0.25, "ADA-USD": 0.25, "IYR": 0.25, "SHV": 0.25}, "max_deviation": 0.065244, "total_turnover": 0.019607, "transaction_cost": 2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.0652}} +{"id": "T6_all_20240819_0067", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "DOT-USD", "VNQ", "CORN"], "decision_date": "2024-08-19", "context_summary": "Max weight deviation: 0.0263, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2539, target=0.2500\n DOT-USD: current=0.2381, target=0.2500\n VNQ: current=0.2763, target=0.2500\n CORN: current=0.2317, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0263.\nRebalancing threshold: 0.0500.\n0.0263 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0604, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2539, "DOT-USD": 0.2381, "VNQ": 0.2763, "CORN": 0.2317}, "target_weights": {"USMV": 0.25, "DOT-USD": 0.25, "VNQ": 0.25, "CORN": 0.25}, "max_deviation": 0.0263, "total_turnover": 0.060427, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "VNQ", "primary_trade": 0.0263}} +{"id": "T6_all_20231121_0070", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ADA-USD", "CORN", "IYR"], "decision_date": "2023-11-21", "context_summary": "Max weight deviation: 0.0118, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2401, target=0.2500\n ADA-USD: current=0.1993, target=0.2500\n CORN: current=0.2456, target=0.2500\n IYR: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of IYR", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0118.\nRebalancing threshold: 0.0500.\n0.0118 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0235, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2401, "ADA-USD": 0.1993, "CORN": 0.2456, "IYR": 0.315}, "target_weights": {"XLU": 0.25, "ADA-USD": 0.25, "CORN": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.023527, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IYR", "primary_trade": 0.065}} +{"id": "T6_all_20230110_0072", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "SGOV", "REZ"], "decision_date": "2023-01-10", "context_summary": "Max weight deviation: 0.0240, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.3150, target=0.2500\n BNB-USD: current=0.2562, target=0.2500\n SGOV: current=0.2069, target=0.2500\n REZ: current=0.2218, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0240.\nRebalancing threshold: 0.0500.\n0.0240 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0527, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.315, "BNB-USD": 0.2562, "SGOV": 0.2069, "REZ": 0.2218}, "target_weights": {"XLB": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "REZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.05268, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLB", "primary_trade": 0.065}} +{"id": "T6_all_20240101_0080", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "IAU", "VCIT"], "decision_date": "2024-01-01", "context_summary": "Max weight deviation: 0.0344, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.3150, target=0.2500\n BNB-USD: current=0.2196, target=0.2500\n IAU: current=0.2390, target=0.2500\n VCIT: current=0.2264, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of EEM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0344.\nRebalancing threshold: 0.0500.\n0.0344 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0689, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.315, "BNB-USD": 0.2196, "IAU": 0.239, "VCIT": 0.2264}, "target_weights": {"EEM": 0.25, "BNB-USD": 0.25, "IAU": 0.25, "VCIT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.068857, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": 0.065}} +{"id": "T6_all_20241211_0083", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "ETH-USD", "BIL", "JNK"], "decision_date": "2024-12-11", "context_summary": "Max weight deviation: 0.0282, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2731, target=0.2500\n ETH-USD: current=0.2386, target=0.2500\n BIL: current=0.2665, target=0.2500\n JNK: current=0.2218, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0282.\nRebalancing threshold: 0.0500.\n0.0282 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0793, transaction cost = 0.000079 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2731, "ETH-USD": 0.2386, "BIL": 0.2665, "JNK": 0.2218}, "target_weights": {"USMV": 0.25, "ETH-USD": 0.25, "BIL": 0.25, "JNK": 0.25}, "max_deviation": 0.0282, "total_turnover": 0.07933, "transaction_cost": 7.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "JNK", "primary_trade": -0.0282}} +{"id": "T6_all_20240222_0084", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "AVAX-USD", "HYG", "MORT"], "decision_date": "2024-02-22", "context_summary": "Max weight deviation: 0.0393, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2703, target=0.2500\n AVAX-USD: current=0.1850, target=0.2500\n HYG: current=0.2497, target=0.2500\n MORT: current=0.2950, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of AVAX-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0393.\nRebalancing threshold: 0.0500.\n0.0393 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0790, transaction cost = 0.000079 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2703, "AVAX-USD": 0.185, "HYG": 0.2497, "MORT": 0.295}, "target_weights": {"FXI": 0.25, "AVAX-USD": 0.25, "HYG": 0.25, "MORT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.078959, "transaction_cost": 7.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "AVAX-USD", "primary_trade": -0.065}} +{"id": "T6_all_20230915_0087", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "PPLT", "SGOV"], "decision_date": "2023-09-15", "context_summary": "Max weight deviation: 0.0190, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.2378, target=0.2500\n BNB-USD: current=0.2359, target=0.2500\n PPLT: current=0.2573, target=0.2500\n SGOV: current=0.2690, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0190.\nRebalancing threshold: 0.0500.\n0.0190 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0525, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2378, "BNB-USD": 0.2359, "PPLT": 0.2573, "SGOV": 0.269}, "target_weights": {"XLI": 0.25, "BNB-USD": 0.25, "PPLT": 0.25, "SGOV": 0.25}, "max_deviation": 0.019, "total_turnover": 0.052542, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.019}} +{"id": "T6_all_20230912_0088", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "SCHP", "INDS"], "decision_date": "2023-09-12", "context_summary": "Max weight deviation: 0.0057, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2568, target=0.2500\n LINK-USD: current=0.3150, target=0.2500\n SCHP: current=0.2272, target=0.2500\n INDS: current=0.2010, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of LINK-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0057.\nRebalancing threshold: 0.0500.\n0.0057 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0127, transaction cost = 0.000013 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2568, "LINK-USD": 0.315, "SCHP": 0.2272, "INDS": 0.201}, "target_weights": {"XLV": 0.25, "LINK-USD": 0.25, "SCHP": 0.25, "INDS": 0.25}, "max_deviation": 0.065, "total_turnover": 0.012671, "transaction_cost": 1.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": 0.065}} +{"id": "T6_all_20241010_0090", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "AVAX-USD", "PPLT", "SCHH"], "decision_date": "2024-10-10", "context_summary": "Max weight deviation: 0.0275, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.2953, target=0.2500\n AVAX-USD: current=0.1850, target=0.2500\n PPLT: current=0.2544, target=0.2500\n SCHH: current=0.2653, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of AVAX-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0275.\nRebalancing threshold: 0.0500.\n0.0275 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0551, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2953, "AVAX-USD": 0.185, "PPLT": 0.2544, "SCHH": 0.2653}, "target_weights": {"XLB": 0.25, "AVAX-USD": 0.25, "PPLT": 0.25, "SCHH": 0.25}, "max_deviation": 0.065044, "total_turnover": 0.055074, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "AVAX-USD", "primary_trade": -0.065}} +{"id": "T6_all_20241209_0091", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "SOL-USD", "CSHI", "HAUZ"], "decision_date": "2024-12-09", "context_summary": "Max weight deviation: 0.0227, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2672, target=0.2500\n SOL-USD: current=0.2415, target=0.2500\n CSHI: current=0.2273, target=0.2500\n HAUZ: current=0.2640, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0227.\nRebalancing threshold: 0.0500.\n0.0227 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0624, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2672, "SOL-USD": 0.2415, "CSHI": 0.2273, "HAUZ": 0.264}, "target_weights": {"XLRE": 0.25, "SOL-USD": 0.25, "CSHI": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0227, "total_turnover": 0.062411, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "CSHI", "primary_trade": -0.0227}} +{"id": "T6_all_20240920_0093", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LINK-USD", "IGOV", "CSHI"], "decision_date": "2024-09-20", "context_summary": "Max weight deviation: 0.0332, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2541, target=0.2500\n LINK-USD: current=0.2521, target=0.2500\n IGOV: current=0.2770, target=0.2500\n CSHI: current=0.2168, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0332.\nRebalancing threshold: 0.0500.\n0.0332 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0664, transaction cost = 0.000066 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2541, "LINK-USD": 0.2521, "IGOV": 0.277, "CSHI": 0.2168}, "target_weights": {"XLF": 0.25, "LINK-USD": 0.25, "IGOV": 0.25, "CSHI": 0.25}, "max_deviation": 0.0332, "total_turnover": 0.066412, "transaction_cost": 6.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "CSHI", "primary_trade": -0.0332}} +{"id": "T6_all_20231019_0096", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "IGOV", "SLV"], "decision_date": "2023-10-19", "context_summary": "Max weight deviation: 0.0442, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.2522, target=0.2500\n BTC-USD: current=0.2844, target=0.2500\n IGOV: current=0.2784, target=0.2500\n SLV: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SLV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0442.\nRebalancing threshold: 0.0500.\n0.0442 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0884, transaction cost = 0.000088 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2522, "BTC-USD": 0.2844, "IGOV": 0.2784, "SLV": 0.185}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "IGOV": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.088371, "transaction_cost": 8.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SLV", "primary_trade": -0.065}} +{"id": "T6_all_20240614_0099", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "XRP-USD", "UNG", "SHV"], "decision_date": "2024-06-14", "context_summary": "Max weight deviation: 0.0160, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2437, target=0.2500\n XRP-USD: current=0.2660, target=0.2500\n UNG: current=0.2374, target=0.2500\n SHV: current=0.2529, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0160.\nRebalancing threshold: 0.0500.\n0.0160 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0378, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2437, "XRP-USD": 0.266, "UNG": 0.2374, "SHV": 0.2529}, "target_weights": {"^VIX": 0.25, "XRP-USD": 0.25, "UNG": 0.25, "SHV": 0.25}, "max_deviation": 0.016, "total_turnover": 0.03783, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XRP-USD", "primary_trade": 0.016}} +{"id": "T6_all_20241021_0104", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "IAU", "ITB"], "decision_date": "2024-10-21", "context_summary": "Max weight deviation: 0.0142, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2482, target=0.2500\n BNB-USD: current=0.1932, target=0.2500\n IAU: current=0.3150, target=0.2500\n ITB: current=0.2436, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of IAU", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0142.\nRebalancing threshold: 0.0500.\n0.0142 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0284, transaction cost = 0.000028 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2482, "BNB-USD": 0.1932, "IAU": 0.315, "ITB": 0.2436}, "target_weights": {"XLF": 0.25, "BNB-USD": 0.25, "IAU": 0.25, "ITB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.0284, "transaction_cost": 2.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "IAU", "primary_trade": 0.065}} +{"id": "T6_all_20230425_0105", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "DOT-USD", "LQD", "VNQI"], "decision_date": "2023-04-25", "context_summary": "Max weight deviation: 0.0189, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2679, target=0.2500\n DOT-USD: current=0.2428, target=0.2500\n LQD: current=0.2581, target=0.2500\n VNQI: current=0.2311, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0189.\nRebalancing threshold: 0.0500.\n0.0189 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0521, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2679, "DOT-USD": 0.2428, "LQD": 0.2581, "VNQI": 0.2311}, "target_weights": {"VTI": 0.25, "DOT-USD": 0.25, "LQD": 0.25, "VNQI": 0.25}, "max_deviation": 0.0189, "total_turnover": 0.052083, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VNQI", "primary_trade": -0.0189}} +{"id": "T6_all_20241118_0109", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "EMB", "IAU"], "decision_date": "2024-11-18", "context_summary": "Max weight deviation: 0.0400, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2443, target=0.2500\n BNB-USD: current=0.2900, target=0.2500\n EMB: current=0.2202, target=0.2500\n IAU: current=0.2455, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0400.\nRebalancing threshold: 0.0500.\n0.0400 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0800, transaction cost = 0.000080 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2443, "BNB-USD": 0.29, "EMB": 0.2202, "IAU": 0.2455}, "target_weights": {"XLK": 0.25, "BNB-USD": 0.25, "EMB": 0.25, "IAU": 0.25}, "max_deviation": 0.04, "total_turnover": 0.080023, "transaction_cost": 8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "BNB-USD", "primary_trade": 0.04}} +{"id": "T6_all_20240802_0111", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "LINK-USD", "BIL", "STIP"], "decision_date": "2024-08-02", "context_summary": "Max weight deviation: 0.0194, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2663, target=0.2500\n LINK-USD: current=0.2306, target=0.2500\n BIL: current=0.2359, target=0.2500\n STIP: current=0.2672, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0194.\nRebalancing threshold: 0.0500.\n0.0194 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0670, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2663, "LINK-USD": 0.2306, "BIL": 0.2359, "STIP": 0.2672}, "target_weights": {"SPY": 0.25, "LINK-USD": 0.25, "BIL": 0.25, "STIP": 0.25}, "max_deviation": 0.0194, "total_turnover": 0.066983, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "LINK-USD", "primary_trade": -0.0194}} +{"id": "T6_all_20231213_0112", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD", "ICSH", "DBB"], "decision_date": "2023-12-13", "context_summary": "Max weight deviation: 0.0350, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2642, target=0.2500\n BTC-USD: current=0.1850, target=0.2500\n ICSH: current=0.2891, target=0.2500\n DBB: current=0.2617, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0350.\nRebalancing threshold: 0.0500.\n0.0350 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0699, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2642, "BTC-USD": 0.185, "ICSH": 0.2891, "DBB": 0.2617}, "target_weights": {"QUAL": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "DBB": 0.25}, "max_deviation": 0.064966, "total_turnover": 0.069936, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.065}} +{"id": "T6_all_20230721_0113", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "SGOV", "HAUZ"], "decision_date": "2023-07-21", "context_summary": "Max weight deviation: 0.0179, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2671, target=0.2500\n LINK-USD: current=0.2517, target=0.2500\n SGOV: current=0.2321, target=0.2500\n HAUZ: current=0.2491, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0179.\nRebalancing threshold: 0.0500.\n0.0179 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0376, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2671, "LINK-USD": 0.2517, "SGOV": 0.2321, "HAUZ": 0.2491}, "target_weights": {"QUAL": 0.25, "LINK-USD": 0.25, "SGOV": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0179, "total_turnover": 0.037595, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": -0.0179}} +{"id": "T6_all_20231023_0115", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "REZ", "BNO"], "decision_date": "2023-10-23", "context_summary": "Max weight deviation: 0.0178, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2520, target=0.2500\n ADA-USD: current=0.2592, target=0.2500\n REZ: current=0.2565, target=0.2500\n BNO: current=0.2322, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0178.\nRebalancing threshold: 0.0500.\n0.0178 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0355, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.252, "ADA-USD": 0.2592, "REZ": 0.2565, "BNO": 0.2322}, "target_weights": {"EFA": 0.25, "ADA-USD": 0.25, "REZ": 0.25, "BNO": 0.25}, "max_deviation": 0.0178, "total_turnover": 0.035533, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": -0.0178}} +{"id": "T6_all_20240531_0116", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BTC-USD", "IYR", "IGOV"], "decision_date": "2024-05-31", "context_summary": "Max weight deviation: 0.0122, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.1850, target=0.2500\n BTC-USD: current=0.2964, target=0.2500\n IYR: current=0.2804, target=0.2500\n IGOV: current=0.2383, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of EWJ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0122.\nRebalancing threshold: 0.0500.\n0.0122 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0287, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.185, "BTC-USD": 0.2964, "IYR": 0.2804, "IGOV": 0.2383}, "target_weights": {"EWJ": 0.25, "BTC-USD": 0.25, "IYR": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.028677, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "EWJ", "primary_trade": -0.065}} +{"id": "T6_all_20240910_0117", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "MATIC-USD", "IAU", "CSHI"], "decision_date": "2024-09-10", "context_summary": "Max weight deviation: 0.0119, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2428, target=0.2500\n MATIC-USD: current=0.2548, target=0.2500\n IAU: current=0.2619, target=0.2500\n CSHI: current=0.2406, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0119.\nRebalancing threshold: 0.0500.\n0.0119 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0332, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2428, "MATIC-USD": 0.2548, "IAU": 0.2619, "CSHI": 0.2406}, "target_weights": {"EWJ": 0.25, "MATIC-USD": 0.25, "IAU": 0.25, "CSHI": 0.25}, "max_deviation": 0.0119, "total_turnover": 0.033221, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "IAU", "primary_trade": 0.0119}} +{"id": "T6_all_20230724_0120", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "ICSH", "ITB"], "decision_date": "2023-07-24", "context_summary": "Max weight deviation: 0.0540, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2197, target=0.2500\n LINK-USD: current=0.2215, target=0.2500\n ICSH: current=0.3040, target=0.2500\n ITB: current=0.2547, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0540 of ICSH", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0540.\nRebalancing threshold: 0.0500.\n0.0540 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1175, transaction cost = 0.000118 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2197, "LINK-USD": 0.2215, "ICSH": 0.304, "ITB": 0.2547}, "target_weights": {"XLV": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "ITB": 0.25}, "max_deviation": 0.054, "total_turnover": 0.117506, "transaction_cost": 0.000118, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": 0.054}} +{"id": "T6_all_20230703_0123", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "AVAX-USD", "CSHI", "IGOV"], "decision_date": "2023-07-03", "context_summary": "Max weight deviation: 0.0208, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.2708, target=0.2500\n AVAX-USD: current=0.2465, target=0.2500\n CSHI: current=0.2414, target=0.2500\n IGOV: current=0.2413, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0208.\nRebalancing threshold: 0.0500.\n0.0208 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0417, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2708, "AVAX-USD": 0.2465, "CSHI": 0.2414, "IGOV": 0.2413}, "target_weights": {"XLB": 0.25, "AVAX-USD": 0.25, "CSHI": 0.25, "IGOV": 0.25}, "max_deviation": 0.0208, "total_turnover": 0.041663, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLB", "primary_trade": 0.0208}} +{"id": "T6_all_20240916_0127", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SOL-USD", "HYG", "PALL"], "decision_date": "2024-09-16", "context_summary": "Max weight deviation: 0.0295, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2408, target=0.2500\n SOL-USD: current=0.2519, target=0.2500\n HYG: current=0.2277, target=0.2500\n PALL: current=0.2795, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0295.\nRebalancing threshold: 0.0500.\n0.0295 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0630, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2408, "SOL-USD": 0.2519, "HYG": 0.2277, "PALL": 0.2795}, "target_weights": {"FXI": 0.25, "SOL-USD": 0.25, "HYG": 0.25, "PALL": 0.25}, "max_deviation": 0.0295, "total_turnover": 0.062977, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "PALL", "primary_trade": 0.0295}} +{"id": "T6_all_20230922_0130", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "BIL", "VNQI"], "decision_date": "2023-09-22", "context_summary": "Max weight deviation: 0.0174, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2115, target=0.2500\n ADA-USD: current=0.2168, target=0.2500\n BIL: current=0.2567, target=0.2500\n VNQI: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of VNQI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0174.\nRebalancing threshold: 0.0500.\n0.0174 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0384, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2115, "ADA-USD": 0.2168, "BIL": 0.2567, "VNQI": 0.315}, "target_weights": {"XLK": 0.25, "ADA-USD": 0.25, "BIL": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.038427, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQI", "primary_trade": 0.065}} +{"id": "T6_all_20240416_0131", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "SOL-USD", "BNDX", "BIL"], "decision_date": "2024-04-16", "context_summary": "Max weight deviation: 0.0278, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2222, target=0.2500\n SOL-USD: current=0.2515, target=0.2500\n BNDX: current=0.2537, target=0.2500\n BIL: current=0.2726, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0278.\nRebalancing threshold: 0.0500.\n0.0278 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0555, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2222, "SOL-USD": 0.2515, "BNDX": 0.2537, "BIL": 0.2726}, "target_weights": {"MTUM": 0.25, "SOL-USD": 0.25, "BNDX": 0.25, "BIL": 0.25}, "max_deviation": 0.0278, "total_turnover": 0.055526, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "MTUM", "primary_trade": -0.0278}} +{"id": "T6_all_20241009_0133", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "DOT-USD", "MORT", "BIL"], "decision_date": "2024-10-09", "context_summary": "Max weight deviation: 0.0250, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2558, target=0.2500\n DOT-USD: current=0.2686, target=0.2500\n MORT: current=0.2505, target=0.2500\n BIL: current=0.2250, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0250.\nRebalancing threshold: 0.0500.\n0.0250 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0500, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2558, "DOT-USD": 0.2686, "MORT": 0.2505, "BIL": 0.225}, "target_weights": {"IVV": 0.25, "DOT-USD": 0.25, "MORT": 0.25, "BIL": 0.25}, "max_deviation": 0.025, "total_turnover": 0.04999, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "BIL", "primary_trade": -0.025}} +{"id": "T6_all_20240306_0136", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "SOL-USD", "IGOV", "INDS"], "decision_date": "2024-03-06", "context_summary": "Max weight deviation: 0.0328, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.1850, target=0.2500\n SOL-USD: current=0.2274, target=0.2500\n IGOV: current=0.3045, target=0.2500\n INDS: current=0.2831, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XLV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0328.\nRebalancing threshold: 0.0500.\n0.0328 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0884, transaction cost = 0.000088 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.185, "SOL-USD": 0.2274, "IGOV": 0.3045, "INDS": 0.2831}, "target_weights": {"XLV": 0.25, "SOL-USD": 0.25, "IGOV": 0.25, "INDS": 0.25}, "max_deviation": 0.065, "total_turnover": 0.0884, "transaction_cost": 8.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XLV", "primary_trade": -0.065}} +{"id": "T6_all_20240502_0138", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "STIP", "BIL"], "decision_date": "2024-05-02", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.3100, target=0.2500\n ADA-USD: current=0.2786, target=0.2500\n STIP: current=0.1849, target=0.2500\n BIL: current=0.2264, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0651 of STIP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0213.\nRebalancing threshold: 0.0500.\n0.0213 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0582, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.31, "ADA-USD": 0.2786, "STIP": 0.1849, "BIL": 0.2264}, "target_weights": {"XLRE": 0.25, "ADA-USD": 0.25, "STIP": 0.25, "BIL": 0.25}, "max_deviation": 0.065056, "total_turnover": 0.058154, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "STIP", "primary_trade": -0.0651}} +{"id": "T6_all_20230223_0141", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "TIP", "IYR"], "decision_date": "2023-02-23", "context_summary": "Max weight deviation: 0.0288, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2393, target=0.2500\n AVAX-USD: current=0.2266, target=0.2500\n TIP: current=0.2552, target=0.2500\n IYR: current=0.2788, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0288.\nRebalancing threshold: 0.0500.\n0.0288 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0681, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2393, "AVAX-USD": 0.2266, "TIP": 0.2552, "IYR": 0.2788}, "target_weights": {"XLU": 0.25, "AVAX-USD": 0.25, "TIP": 0.25, "IYR": 0.25}, "max_deviation": 0.0288, "total_turnover": 0.068107, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "IYR", "primary_trade": 0.0288}} +{"id": "T6_all_20230209_0143", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "TIP", "DBC"], "decision_date": "2023-02-09", "context_summary": "Max weight deviation: 0.0153, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2526, target=0.2500\n XRP-USD: current=0.2584, target=0.2500\n TIP: current=0.2347, target=0.2500\n DBC: current=0.2544, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0153.\nRebalancing threshold: 0.0500.\n0.0153 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0306, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2526, "XRP-USD": 0.2584, "TIP": 0.2347, "DBC": 0.2544}, "target_weights": {"USMV": 0.25, "XRP-USD": 0.25, "TIP": 0.25, "DBC": 0.25}, "max_deviation": 0.0153, "total_turnover": 0.030646, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TIP", "primary_trade": -0.0153}} +{"id": "T6_all_20230321_0149", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "ICSH", "PALL"], "decision_date": "2023-03-21", "context_summary": "Max weight deviation: 0.0200, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.2700, target=0.2500\n LINK-USD: current=0.2383, target=0.2500\n ICSH: current=0.2599, target=0.2500\n PALL: current=0.2318, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0200.\nRebalancing threshold: 0.0500.\n0.0200 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0598, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.27, "LINK-USD": 0.2383, "ICSH": 0.2599, "PALL": 0.2318}, "target_weights": {"XLI": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "PALL": 0.25}, "max_deviation": 0.02, "total_turnover": 0.05982, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLI", "primary_trade": 0.02}} +{"id": "T6_all_20230804_0152", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "CSHI", "HYG"], "decision_date": "2023-08-04", "context_summary": "Max weight deviation: 0.0122, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.3148, target=0.2500\n LINK-USD: current=0.2307, target=0.2500\n CSHI: current=0.2376, target=0.2500\n HYG: current=0.2169, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0648 of XLB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0122.\nRebalancing threshold: 0.0500.\n0.0122 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0243, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.3148, "LINK-USD": 0.2307, "CSHI": 0.2376, "HYG": 0.2169}, "target_weights": {"XLB": 0.25, "LINK-USD": 0.25, "CSHI": 0.25, "HYG": 0.25}, "max_deviation": 0.064832, "total_turnover": 0.024307, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLB", "primary_trade": 0.0648}} +{"id": "T6_all_20230828_0154", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "VNQI", "GLD"], "decision_date": "2023-08-28", "context_summary": "Max weight deviation: 0.0160, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2580, target=0.2500\n MATIC-USD: current=0.2966, target=0.2500\n VNQI: current=0.2605, target=0.2500\n GLD: current=0.1849, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0651 of GLD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0160.\nRebalancing threshold: 0.0500.\n0.0160 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0321, transaction cost = 0.000032 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.258, "MATIC-USD": 0.2966, "VNQI": 0.2605, "GLD": 0.1849}, "target_weights": {"IVV": 0.25, "MATIC-USD": 0.25, "VNQI": 0.25, "GLD": 0.25}, "max_deviation": 0.065075, "total_turnover": 0.032072, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "GLD", "primary_trade": -0.0651}} +{"id": "T6_all_20230123_0156", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "AVAX-USD", "HYG", "REZ"], "decision_date": "2023-01-23", "context_summary": "Max weight deviation: 0.0119, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2693, target=0.2500\n AVAX-USD: current=0.1851, target=0.2500\n HYG: current=0.2818, target=0.2500\n REZ: current=0.2638, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0649 of AVAX-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0119.\nRebalancing threshold: 0.0500.\n0.0119 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0237, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2693, "AVAX-USD": 0.1851, "HYG": 0.2818, "REZ": 0.2638}, "target_weights": {"MTUM": 0.25, "AVAX-USD": 0.25, "HYG": 0.25, "REZ": 0.25}, "max_deviation": 0.064899, "total_turnover": 0.023745, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": -0.0649}} +{"id": "T6_all_20240513_0159", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "DOT-USD", "PDBC", "STIP"], "decision_date": "2024-05-13", "context_summary": "Max weight deviation: 0.0155, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2375, target=0.2500\n DOT-USD: current=0.2655, target=0.2500\n PDBC: current=0.2565, target=0.2500\n STIP: current=0.2406, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0155.\nRebalancing threshold: 0.0500.\n0.0155 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0439, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2375, "DOT-USD": 0.2655, "PDBC": 0.2565, "STIP": 0.2406}, "target_weights": {"IWM": 0.25, "DOT-USD": 0.25, "PDBC": 0.25, "STIP": 0.25}, "max_deviation": 0.0155, "total_turnover": 0.043856, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "DOT-USD", "primary_trade": 0.0155}} +{"id": "T6_all_20230808_0163", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "XRP-USD", "VNQI", "HYG"], "decision_date": "2023-08-08", "context_summary": "Max weight deviation: 0.0162, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2384, target=0.2500\n XRP-USD: current=0.2495, target=0.2500\n VNQI: current=0.2459, target=0.2500\n HYG: current=0.2662, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0162.\nRebalancing threshold: 0.0500.\n0.0162 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0325, transaction cost = 0.000032 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2384, "XRP-USD": 0.2495, "VNQI": 0.2459, "HYG": 0.2662}, "target_weights": {"EEM": 0.25, "XRP-USD": 0.25, "VNQI": 0.25, "HYG": 0.25}, "max_deviation": 0.0162, "total_turnover": 0.03247, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": 0.0162}} +{"id": "T6_all_20240206_0164", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BNB-USD", "IAU", "HAUZ"], "decision_date": "2024-02-06", "context_summary": "Max weight deviation: 0.0210, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.1903, target=0.2500\n BNB-USD: current=0.3150, target=0.2500\n IAU: current=0.2231, target=0.2500\n HAUZ: current=0.2717, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of BNB-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0210.\nRebalancing threshold: 0.0500.\n0.0210 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0560, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.1903, "BNB-USD": 0.315, "IAU": 0.2231, "HAUZ": 0.2717}, "target_weights": {"ACWI": 0.25, "BNB-USD": 0.25, "IAU": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.056047, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "BNB-USD", "primary_trade": 0.065}} +{"id": "T6_all_20230719_0166", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BTC-USD", "BNO", "ITB"], "decision_date": "2023-07-19", "context_summary": "Max weight deviation: 0.0105, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2133, target=0.2500\n BTC-USD: current=0.2140, target=0.2500\n BNO: current=0.3148, target=0.2500\n ITB: current=0.2579, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0648 of BNO", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0105.\nRebalancing threshold: 0.0500.\n0.0105 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0236, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2133, "BTC-USD": 0.214, "BNO": 0.3148, "ITB": 0.2579}, "target_weights": {"MTUM": 0.25, "BTC-USD": 0.25, "BNO": 0.25, "ITB": 0.25}, "max_deviation": 0.064805, "total_turnover": 0.023558, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": 0.0648}} +{"id": "T6_all_20230116_0168", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ETH-USD", "DBB", "SCHP"], "decision_date": "2023-01-16", "context_summary": "Max weight deviation: 0.0224, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2597, target=0.2500\n ETH-USD: current=0.2167, target=0.2500\n DBB: current=0.3151, target=0.2500\n SCHP: current=0.2086, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of DBB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0224.\nRebalancing threshold: 0.0500.\n0.0224 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0515, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2597, "ETH-USD": 0.2167, "DBB": 0.3151, "SCHP": 0.2086}, "target_weights": {"XLE": 0.25, "ETH-USD": 0.25, "DBB": 0.25, "SCHP": 0.25}, "max_deviation": 0.065091, "total_turnover": 0.051517, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": 0.0651}} +{"id": "T6_all_20241127_0170", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "MATIC-USD", "SCHH", "SLV"], "decision_date": "2024-11-27", "context_summary": "Max weight deviation: 0.0159, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2148, target=0.2500\n MATIC-USD: current=0.2091, target=0.2500\n SCHH: current=0.2610, target=0.2500\n SLV: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SLV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0159.\nRebalancing threshold: 0.0500.\n0.0159 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0372, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2148, "MATIC-USD": 0.2091, "SCHH": 0.261, "SLV": 0.315}, "target_weights": {"QQQ": 0.25, "MATIC-USD": 0.25, "SCHH": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037153, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "SLV", "primary_trade": 0.065}} +{"id": "T6_all_20240805_0172", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "LINK-USD", "CSHI", "IYR"], "decision_date": "2024-08-05", "context_summary": "Max weight deviation: 0.0289, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.3150, target=0.2500\n LINK-USD: current=0.2471, target=0.2500\n CSHI: current=0.2307, target=0.2500\n IYR: current=0.2073, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of VLUE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0289.\nRebalancing threshold: 0.0500.\n0.0289 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0578, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.315, "LINK-USD": 0.2471, "CSHI": 0.2307, "IYR": 0.2073}, "target_weights": {"VLUE": 0.25, "LINK-USD": 0.25, "CSHI": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.057795, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "VLUE", "primary_trade": 0.065}} +{"id": "T6_all_20241004_0173", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "SOL-USD", "SOYB", "SGOV"], "decision_date": "2024-10-04", "context_summary": "Max weight deviation: 0.0292, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2349, target=0.2500\n SOL-USD: current=0.2468, target=0.2500\n SOYB: current=0.2391, target=0.2500\n SGOV: current=0.2792, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0292.\nRebalancing threshold: 0.0500.\n0.0292 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0585, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2349, "SOL-USD": 0.2468, "SOYB": 0.2391, "SGOV": 0.2792}, "target_weights": {"XLV": 0.25, "SOL-USD": 0.25, "SOYB": 0.25, "SGOV": 0.25}, "max_deviation": 0.0292, "total_turnover": 0.058494, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SGOV", "primary_trade": 0.0292}} +{"id": "T6_all_20241230_0174", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XRP-USD", "CSHI", "TIP"], "decision_date": "2024-12-30", "context_summary": "Max weight deviation: 0.0452, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2362, target=0.2500\n XRP-USD: current=0.2365, target=0.2500\n CSHI: current=0.3150, target=0.2500\n TIP: current=0.2123, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of CSHI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0452.\nRebalancing threshold: 0.0500.\n0.0452 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0904, transaction cost = 0.000090 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2362, "XRP-USD": 0.2365, "CSHI": 0.315, "TIP": 0.2123}, "target_weights": {"XLY": 0.25, "XRP-USD": 0.25, "CSHI": 0.25, "TIP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.090427, "transaction_cost": 9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "CSHI", "primary_trade": 0.065}} +{"id": "T6_all_20230621_0175", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "ITB", "CORN"], "decision_date": "2023-06-21", "context_summary": "Max weight deviation: 0.0651, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2578, target=0.2500\n LINK-USD: current=0.2590, target=0.2500\n ITB: current=0.2631, target=0.2500\n CORN: current=0.2200, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0651.\nRebalancing threshold: 0.0500.\n0.0651 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1301, transaction cost = 0.000130 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2578, "LINK-USD": 0.259, "ITB": 0.2631, "CORN": 0.22}, "target_weights": {"XLP": 0.25, "LINK-USD": 0.25, "ITB": 0.25, "CORN": 0.25}, "max_deviation": 0.02999, "total_turnover": 0.130127, "transaction_cost": 0.00013, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CORN", "primary_trade": -0.03}} +{"id": "T6_all_20231130_0178", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "GLD", "BIL"], "decision_date": "2023-11-30", "context_summary": "Max weight deviation: 0.0281, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.3149, target=0.2500\n XRP-USD: current=0.2102, target=0.2500\n GLD: current=0.2176, target=0.2500\n BIL: current=0.2573, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of XLRE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0281.\nRebalancing threshold: 0.0500.\n0.0281 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0625, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3149, "XRP-USD": 0.2102, "GLD": 0.2176, "BIL": 0.2573}, "target_weights": {"XLRE": 0.25, "XRP-USD": 0.25, "GLD": 0.25, "BIL": 0.25}, "max_deviation": 0.064927, "total_turnover": 0.062514, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": 0.0649}} +{"id": "T6_all_20241014_0180", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "STIP", "ICSH"], "decision_date": "2024-10-14", "context_summary": "Max weight deviation: 0.0173, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2376, target=0.2500\n ETH-USD: current=0.3116, target=0.2500\n STIP: current=0.1850, target=0.2500\n ICSH: current=0.2658, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of STIP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0173.\nRebalancing threshold: 0.0500.\n0.0173 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0412, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2376, "ETH-USD": 0.3116, "STIP": 0.185, "ICSH": 0.2658}, "target_weights": {"QUAL": 0.25, "ETH-USD": 0.25, "STIP": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.041164, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "STIP", "primary_trade": -0.065}} +{"id": "T6_all_20230829_0183", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "MATIC-USD", "BIL", "CORN"], "decision_date": "2023-08-29", "context_summary": "Max weight deviation: 0.0082, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2582, target=0.2500\n MATIC-USD: current=0.2428, target=0.2500\n BIL: current=0.2534, target=0.2500\n CORN: current=0.2456, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0082.\nRebalancing threshold: 0.0500.\n0.0082 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0232, transaction cost = 0.000023 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2582, "MATIC-USD": 0.2428, "BIL": 0.2534, "CORN": 0.2456}, "target_weights": {"USMV": 0.25, "MATIC-USD": 0.25, "BIL": 0.25, "CORN": 0.25}, "max_deviation": 0.0082, "total_turnover": 0.02318, "transaction_cost": 2.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": 0.0082}} +{"id": "T6_all_20230622_0185", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ETH-USD", "DBB", "XHB"], "decision_date": "2023-06-22", "context_summary": "Max weight deviation: 0.0226, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2274, target=0.2500\n ETH-USD: current=0.2504, target=0.2500\n DBB: current=0.2627, target=0.2500\n XHB: current=0.2596, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0226.\nRebalancing threshold: 0.0500.\n0.0226 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0452, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2274, "ETH-USD": 0.2504, "DBB": 0.2627, "XHB": 0.2596}, "target_weights": {"XLK": 0.25, "ETH-USD": 0.25, "DBB": 0.25, "XHB": 0.25}, "max_deviation": 0.0226, "total_turnover": 0.045215, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": -0.0226}} +{"id": "T6_all_20230104_0186", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "VCIT", "IAU"], "decision_date": "2023-01-04", "context_summary": "Max weight deviation: 0.0337, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.3150, target=0.2500\n ADA-USD: current=0.2832, target=0.2500\n VCIT: current=0.2162, target=0.2500\n IAU: current=0.1856, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of VEA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0337.\nRebalancing threshold: 0.0500.\n0.0337 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1019, transaction cost = 0.000102 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.315, "ADA-USD": 0.2832, "VCIT": 0.2162, "IAU": 0.1856}, "target_weights": {"VEA": 0.25, "ADA-USD": 0.25, "VCIT": 0.25, "IAU": 0.25}, "max_deviation": 0.065, "total_turnover": 0.101851, "transaction_cost": 0.000102, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VEA", "primary_trade": 0.065}} +{"id": "T6_all_20241217_0187", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "BTC-USD", "BIL", "PALL"], "decision_date": "2024-12-17", "context_summary": "Max weight deviation: 0.0163, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2499, target=0.2500\n BTC-USD: current=0.2554, target=0.2500\n BIL: current=0.2610, target=0.2500\n PALL: current=0.2337, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0163.\nRebalancing threshold: 0.0500.\n0.0163 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0329, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2499, "BTC-USD": 0.2554, "BIL": 0.261, "PALL": 0.2337}, "target_weights": {"XLV": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "PALL": 0.25}, "max_deviation": 0.0163, "total_turnover": 0.032854, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "PALL", "primary_trade": -0.0163}} +{"id": "T6_all_20230619_0190", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "XRP-USD", "CSHI", "TLH"], "decision_date": "2023-06-19", "context_summary": "Max weight deviation: 0.0048, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.2842, target=0.2500\n XRP-USD: current=0.1853, target=0.2500\n CSHI: current=0.2978, target=0.2500\n TLH: current=0.2327, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0647 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0048.\nRebalancing threshold: 0.0500.\n0.0048 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0121, transaction cost = 0.000012 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2842, "XRP-USD": 0.1853, "CSHI": 0.2978, "TLH": 0.2327}, "target_weights": {"XLB": 0.25, "XRP-USD": 0.25, "CSHI": 0.25, "TLH": 0.25}, "max_deviation": 0.064749, "total_turnover": 0.012072, "transaction_cost": 1.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.0647}} +{"id": "T6_all_20230720_0192", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "SOYB", "TIP"], "decision_date": "2023-07-20", "context_summary": "Max weight deviation: 0.0262, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.3150, target=0.2500\n DOT-USD: current=0.2426, target=0.2500\n SOYB: current=0.2386, target=0.2500\n TIP: current=0.2039, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0262.\nRebalancing threshold: 0.0500.\n0.0262 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0524, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.315, "DOT-USD": 0.2426, "SOYB": 0.2386, "TIP": 0.2039}, "target_weights": {"XLI": 0.25, "DOT-USD": 0.25, "SOYB": 0.25, "TIP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.052409, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLI", "primary_trade": 0.065}} +{"id": "T6_all_20241227_0196", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BNB-USD", "PALL", "ICSH"], "decision_date": "2024-12-27", "context_summary": "Max weight deviation: 0.0224, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2454, target=0.2500\n BNB-USD: current=0.1850, target=0.2500\n PALL: current=0.2819, target=0.2500\n ICSH: current=0.2877, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of BNB-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0224.\nRebalancing threshold: 0.0500.\n0.0224 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0480, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2454, "BNB-USD": 0.185, "PALL": 0.2819, "ICSH": 0.2877}, "target_weights": {"XLU": 0.25, "BNB-USD": 0.25, "PALL": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.048008, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "BNB-USD", "primary_trade": -0.065}} +{"id": "T6_all_20230522_0200", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "MATIC-USD", "ICSH", "HAUZ"], "decision_date": "2023-05-22", "context_summary": "Max weight deviation: 0.0154, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2462, target=0.2500\n MATIC-USD: current=0.3112, target=0.2500\n ICSH: current=0.2576, target=0.2500\n HAUZ: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of HAUZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0154.\nRebalancing threshold: 0.0500.\n0.0154 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0325, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2462, "MATIC-USD": 0.3112, "ICSH": 0.2576, "HAUZ": 0.185}, "target_weights": {"XLK": 0.25, "MATIC-USD": 0.25, "ICSH": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.032532, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HAUZ", "primary_trade": -0.065}} +{"id": "T6_all_20231127_0203", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "BNDX", "CSHI"], "decision_date": "2023-11-27", "context_summary": "Max weight deviation: 0.0221, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2360, target=0.2500\n ADA-USD: current=0.2516, target=0.2500\n BNDX: current=0.2404, target=0.2500\n CSHI: current=0.2721, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0221.\nRebalancing threshold: 0.0500.\n0.0221 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0472, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.236, "ADA-USD": 0.2516, "BNDX": 0.2404, "CSHI": 0.2721}, "target_weights": {"EFA": 0.25, "ADA-USD": 0.25, "BNDX": 0.25, "CSHI": 0.25}, "max_deviation": 0.0221, "total_turnover": 0.047247, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CSHI", "primary_trade": 0.0221}} +{"id": "T6_all_20230203_0206", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "CSHI", "XHB"], "decision_date": "2023-02-03", "context_summary": "Max weight deviation: 0.0210, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.3151, target=0.2500\n BTC-USD: current=0.2098, target=0.2500\n CSHI: current=0.2405, target=0.2500\n XHB: current=0.2346, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of USMV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0210.\nRebalancing threshold: 0.0500.\n0.0210 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0421, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.3151, "BTC-USD": 0.2098, "CSHI": 0.2405, "XHB": 0.2346}, "target_weights": {"USMV": 0.25, "BTC-USD": 0.25, "CSHI": 0.25, "XHB": 0.25}, "max_deviation": 0.065098, "total_turnover": 0.042065, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": 0.0651}} +{"id": "T6_all_20241206_0207", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX", "MATIC-USD", "BIL", "ITB"], "decision_date": "2024-12-06", "context_summary": "Max weight deviation: 0.0215, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2402, target=0.2500\n MATIC-USD: current=0.2429, target=0.2500\n BIL: current=0.2454, target=0.2500\n ITB: current=0.2715, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0215.\nRebalancing threshold: 0.0500.\n0.0215 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0430, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2402, "MATIC-USD": 0.2429, "BIL": 0.2454, "ITB": 0.2715}, "target_weights": {"^VIX": 0.25, "MATIC-USD": 0.25, "BIL": 0.25, "ITB": 0.25}, "max_deviation": 0.0215, "total_turnover": 0.042979, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "ITB", "primary_trade": 0.0215}} +{"id": "T6_all_20230629_0210", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "ITB", "TLH"], "decision_date": "2023-06-29", "context_summary": "Max weight deviation: 0.0205, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.2202, target=0.2500\n ADA-USD: current=0.2332, target=0.2500\n ITB: current=0.2316, target=0.2500\n TLH: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of TLH", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0205.\nRebalancing threshold: 0.0500.\n0.0205 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0411, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2202, "ADA-USD": 0.2332, "ITB": 0.2316, "TLH": 0.315}, "target_weights": {"XLI": 0.25, "ADA-USD": 0.25, "ITB": 0.25, "TLH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.041086, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": 0.065}} +{"id": "T6_all_20240919_0212", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "PDBC", "TLH"], "decision_date": "2024-09-19", "context_summary": "Max weight deviation: 0.0229, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.1973, target=0.2500\n ADA-USD: current=0.3151, target=0.2500\n PDBC: current=0.2646, target=0.2500\n TLH: current=0.2231, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of ADA-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0229.\nRebalancing threshold: 0.0500.\n0.0229 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0561, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.1973, "ADA-USD": 0.3151, "PDBC": 0.2646, "TLH": 0.2231}, "target_weights": {"EFA": 0.25, "ADA-USD": 0.25, "PDBC": 0.25, "TLH": 0.25}, "max_deviation": 0.065089, "total_turnover": 0.056089, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "ADA-USD", "primary_trade": 0.0651}} +{"id": "T6_all_20240715_0215", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLP", "BNB-USD", "IEF", "HAUZ"], "decision_date": "2024-07-15", "context_summary": "Max weight deviation: 0.0191, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2691, target=0.2500\n BNB-USD: current=0.2358, target=0.2500\n IEF: current=0.2567, target=0.2500\n HAUZ: current=0.2384, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0191.\nRebalancing threshold: 0.0500.\n0.0191 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0516, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2691, "BNB-USD": 0.2358, "IEF": 0.2567, "HAUZ": 0.2384}, "target_weights": {"XLP": 0.25, "BNB-USD": 0.25, "IEF": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0191, "total_turnover": 0.051561, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XLP", "primary_trade": 0.0191}} +{"id": "T6_all_20240514_0217", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLP", "ETH-USD", "XHB", "TLH"], "decision_date": "2024-05-14", "context_summary": "Max weight deviation: 0.0166, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2334, target=0.2500\n ETH-USD: current=0.2658, target=0.2500\n XHB: current=0.2464, target=0.2500\n TLH: current=0.2544, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0166.\nRebalancing threshold: 0.0500.\n0.0166 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0405, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2334, "ETH-USD": 0.2658, "XHB": 0.2464, "TLH": 0.2544}, "target_weights": {"XLP": 0.25, "ETH-USD": 0.25, "XHB": 0.25, "TLH": 0.25}, "max_deviation": 0.0166, "total_turnover": 0.040511, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XLP", "primary_trade": -0.0166}} +{"id": "T6_all_20230926_0221", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "MORT", "UNG"], "decision_date": "2023-09-26", "context_summary": "Max weight deviation: 0.0190, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2538, target=0.2500\n LINK-USD: current=0.2436, target=0.2500\n MORT: current=0.2336, target=0.2500\n UNG: current=0.2690, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0190.\nRebalancing threshold: 0.0500.\n0.0190 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0457, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2538, "LINK-USD": 0.2436, "MORT": 0.2336, "UNG": 0.269}, "target_weights": {"XLY": 0.25, "LINK-USD": 0.25, "MORT": 0.25, "UNG": 0.25}, "max_deviation": 0.019, "total_turnover": 0.045669, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": 0.019}} +{"id": "T6_all_20230710_0226", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "USO", "ICSH"], "decision_date": "2023-07-10", "context_summary": "Max weight deviation: 0.0328, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2484, target=0.2500\n MATIC-USD: current=0.2945, target=0.2500\n USO: current=0.2721, target=0.2500\n ICSH: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of ICSH", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0328.\nRebalancing threshold: 0.0500.\n0.0328 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0673, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2484, "MATIC-USD": 0.2945, "USO": 0.2721, "ICSH": 0.185}, "target_weights": {"QUAL": 0.25, "MATIC-USD": 0.25, "USO": 0.25, "ICSH": 0.25}, "max_deviation": 0.065037, "total_turnover": 0.067337, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.065}} +{"id": "T6_all_20231204_0227", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "XRP-USD", "SHY", "ICSH"], "decision_date": "2023-12-04", "context_summary": "Max weight deviation: 0.0316, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2467, target=0.2500\n XRP-USD: current=0.2609, target=0.2500\n SHY: current=0.2739, target=0.2500\n ICSH: current=0.2184, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0316.\nRebalancing threshold: 0.0500.\n0.0316 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0697, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2467, "XRP-USD": 0.2609, "SHY": 0.2739, "ICSH": 0.2184}, "target_weights": {"IVV": 0.25, "XRP-USD": 0.25, "SHY": 0.25, "ICSH": 0.25}, "max_deviation": 0.0316, "total_turnover": 0.069717, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0316}} +{"id": "T6_all_20231218_0229", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "XRP-USD", "BNO", "SHV"], "decision_date": "2023-12-18", "context_summary": "Max weight deviation: 0.0310, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2290, target=0.2500\n XRP-USD: current=0.2413, target=0.2500\n BNO: current=0.2487, target=0.2500\n SHV: current=0.2810, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0310.\nRebalancing threshold: 0.0500.\n0.0310 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0620, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.229, "XRP-USD": 0.2413, "BNO": 0.2487, "SHV": 0.281}, "target_weights": {"XLU": 0.25, "XRP-USD": 0.25, "BNO": 0.25, "SHV": 0.25}, "max_deviation": 0.031, "total_turnover": 0.06203, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SHV", "primary_trade": 0.031}} +{"id": "T6_all_20230913_0232", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "BIL", "VCIT"], "decision_date": "2023-09-13", "context_summary": "Max weight deviation: 0.0089, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.1849, target=0.2500\n BTC-USD: current=0.2870, target=0.2500\n BIL: current=0.2199, target=0.2500\n VCIT: current=0.3082, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0651 of IWM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0089.\nRebalancing threshold: 0.0500.\n0.0089 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0260, transaction cost = 0.000026 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.1849, "BTC-USD": 0.287, "BIL": 0.2199, "VCIT": 0.3082}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "VCIT": 0.25}, "max_deviation": 0.065135, "total_turnover": 0.026033, "transaction_cost": 2.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IWM", "primary_trade": -0.0651}} +{"id": "T6_all_20240801_0233", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BNB-USD", "INDS", "TIP"], "decision_date": "2024-08-01", "context_summary": "Max weight deviation: 0.0308, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2456, target=0.2500\n BNB-USD: current=0.2675, target=0.2500\n INDS: current=0.2192, target=0.2500\n TIP: current=0.2677, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0308.\nRebalancing threshold: 0.0500.\n0.0308 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0703, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2456, "BNB-USD": 0.2675, "INDS": 0.2192, "TIP": 0.2677}, "target_weights": {"XLV": 0.25, "BNB-USD": 0.25, "INDS": 0.25, "TIP": 0.25}, "max_deviation": 0.0308, "total_turnover": 0.070289, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "INDS", "primary_trade": -0.0308}} +{"id": "T6_all_20230731_0235", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "USO", "ITB"], "decision_date": "2023-07-31", "context_summary": "Max weight deviation: 0.0361, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2390, target=0.2500\n BTC-USD: current=0.2246, target=0.2500\n USO: current=0.2861, target=0.2500\n ITB: current=0.2502, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0361.\nRebalancing threshold: 0.0500.\n0.0361 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0727, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.239, "BTC-USD": 0.2246, "USO": 0.2861, "ITB": 0.2502}, "target_weights": {"EEM": 0.25, "BTC-USD": 0.25, "USO": 0.25, "ITB": 0.25}, "max_deviation": 0.0361, "total_turnover": 0.072722, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "USO", "primary_trade": 0.0361}} +{"id": "T6_all_20230818_0237", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "AVAX-USD", "SCHH", "BIL"], "decision_date": "2023-08-18", "context_summary": "Max weight deviation: 0.0415, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2400, target=0.2500\n AVAX-USD: current=0.2415, target=0.2500\n SCHH: current=0.2270, target=0.2500\n BIL: current=0.2915, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0415.\nRebalancing threshold: 0.0500.\n0.0415 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0830, transaction cost = 0.000083 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.24, "AVAX-USD": 0.2415, "SCHH": 0.227, "BIL": 0.2915}, "target_weights": {"XLV": 0.25, "AVAX-USD": 0.25, "SCHH": 0.25, "BIL": 0.25}, "max_deviation": 0.0415, "total_turnover": 0.082977, "transaction_cost": 8.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0415}} +{"id": "T6_all_20240925_0239", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "XRP-USD", "HAUZ", "SGOV"], "decision_date": "2024-09-25", "context_summary": "Max weight deviation: 0.0321, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2630, target=0.2500\n XRP-USD: current=0.2777, target=0.2500\n HAUZ: current=0.2179, target=0.2500\n SGOV: current=0.2413, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0321.\nRebalancing threshold: 0.0500.\n0.0321 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0815, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.263, "XRP-USD": 0.2777, "HAUZ": 0.2179, "SGOV": 0.2413}, "target_weights": {"QUAL": 0.25, "XRP-USD": 0.25, "HAUZ": 0.25, "SGOV": 0.25}, "max_deviation": 0.0321, "total_turnover": 0.081479, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "HAUZ", "primary_trade": -0.0321}} +{"id": "T6_all_20241016_0242", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "XRP-USD", "SGOV", "SHV"], "decision_date": "2024-10-16", "context_summary": "Max weight deviation: 0.0311, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.3041, target=0.2500\n XRP-USD: current=0.2559, target=0.2500\n SGOV: current=0.2550, target=0.2500\n SHV: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SHV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0311.\nRebalancing threshold: 0.0500.\n0.0311 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0621, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.3041, "XRP-USD": 0.2559, "SGOV": 0.255, "SHV": 0.185}, "target_weights": {"XLK": 0.25, "XRP-USD": 0.25, "SGOV": 0.25, "SHV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.062126, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SHV", "primary_trade": -0.065}} +{"id": "T6_all_20241017_0245", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "LINK-USD", "BIL", "PDBC"], "decision_date": "2024-10-17", "context_summary": "Max weight deviation: 0.0275, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2450, target=0.2500\n LINK-USD: current=0.2423, target=0.2500\n BIL: current=0.2775, target=0.2500\n PDBC: current=0.2352, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0275.\nRebalancing threshold: 0.0500.\n0.0275 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0551, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.245, "LINK-USD": 0.2423, "BIL": 0.2775, "PDBC": 0.2352}, "target_weights": {"^VIX": 0.25, "LINK-USD": 0.25, "BIL": 0.25, "PDBC": 0.25}, "max_deviation": 0.0275, "total_turnover": 0.055069, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "BIL", "primary_trade": 0.0275}} +{"id": "T6_all_20241204_0247", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "ETH-USD", "SGOV", "HAUZ"], "decision_date": "2024-12-04", "context_summary": "Max weight deviation: 0.0160, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2491, target=0.2500\n ETH-USD: current=0.2649, target=0.2500\n SGOV: current=0.2340, target=0.2500\n HAUZ: current=0.2520, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0160.\nRebalancing threshold: 0.0500.\n0.0160 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0338, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2491, "ETH-USD": 0.2649, "SGOV": 0.234, "HAUZ": 0.252}, "target_weights": {"MTUM": 0.25, "ETH-USD": 0.25, "SGOV": 0.25, "HAUZ": 0.25}, "max_deviation": 0.016, "total_turnover": 0.033778, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "SGOV", "primary_trade": -0.016}} +{"id": "T6_all_20230216_0248", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ADA-USD", "UNG", "BIL"], "decision_date": "2023-02-16", "context_summary": "Max weight deviation: 0.0145, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2908, target=0.2500\n ADA-USD: current=0.2742, target=0.2500\n UNG: current=0.1850, target=0.2500\n BIL: current=0.2500, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of UNG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0145.\nRebalancing threshold: 0.0500.\n0.0145 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0291, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2908, "ADA-USD": 0.2742, "UNG": 0.185, "BIL": 0.25}, "target_weights": {"VLUE": 0.25, "ADA-USD": 0.25, "UNG": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.029074, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "UNG", "primary_trade": -0.065}} +{"id": "T6_all_20240112_0251", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "WEAT", "ICSH"], "decision_date": "2024-01-12", "context_summary": "Max weight deviation: 0.0184, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2353, target=0.2500\n DOT-USD: current=0.2516, target=0.2500\n WEAT: current=0.2684, target=0.2500\n ICSH: current=0.2447, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0184.\nRebalancing threshold: 0.0500.\n0.0184 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0401, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2353, "DOT-USD": 0.2516, "WEAT": 0.2684, "ICSH": 0.2447}, "target_weights": {"XLE": 0.25, "DOT-USD": 0.25, "WEAT": 0.25, "ICSH": 0.25}, "max_deviation": 0.0184, "total_turnover": 0.040122, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "WEAT", "primary_trade": 0.0184}} +{"id": "T6_all_20240730_0255", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ETH-USD", "UNG", "VNQ"], "decision_date": "2024-07-30", "context_summary": "Max weight deviation: 0.0151, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2424, target=0.2500\n ETH-USD: current=0.2349, target=0.2500\n UNG: current=0.2581, target=0.2500\n VNQ: current=0.2646, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0151.\nRebalancing threshold: 0.0500.\n0.0151 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0454, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2424, "ETH-USD": 0.2349, "UNG": 0.2581, "VNQ": 0.2646}, "target_weights": {"XLY": 0.25, "ETH-USD": 0.25, "UNG": 0.25, "VNQ": 0.25}, "max_deviation": 0.0151, "total_turnover": 0.045389, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "ETH-USD", "primary_trade": -0.0151}} +{"id": "T6_all_20240710_0257", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "CPER", "CSHI"], "decision_date": "2024-07-10", "context_summary": "Max weight deviation: 0.0101, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2601, target=0.2500\n ETH-USD: current=0.2522, target=0.2500\n CPER: current=0.2464, target=0.2500\n CSHI: current=0.2413, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0101.\nRebalancing threshold: 0.0500.\n0.0101 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0246, transaction cost = 0.000025 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2601, "ETH-USD": 0.2522, "CPER": 0.2464, "CSHI": 0.2413}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "CPER": 0.25, "CSHI": 0.25}, "max_deviation": 0.0101, "total_turnover": 0.024602, "transaction_cost": 2.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "QQQ", "primary_trade": 0.0101}} +{"id": "T6_all_20230606_0261", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "AVAX-USD", "SCHH", "BNO"], "decision_date": "2023-06-06", "context_summary": "Max weight deviation: 0.0210, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2601, target=0.2500\n AVAX-USD: current=0.2399, target=0.2500\n SCHH: current=0.2710, target=0.2500\n BNO: current=0.2290, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0210.\nRebalancing threshold: 0.0500.\n0.0210 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0623, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2601, "AVAX-USD": 0.2399, "SCHH": 0.271, "BNO": 0.229}, "target_weights": {"XLF": 0.25, "AVAX-USD": 0.25, "SCHH": 0.25, "BNO": 0.25}, "max_deviation": 0.021, "total_turnover": 0.062301, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SCHH", "primary_trade": 0.021}} +{"id": "T6_all_20241007_0264", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "USO", "ICSH"], "decision_date": "2024-10-07", "context_summary": "Max weight deviation: 0.0119, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.1850, target=0.2500\n BTC-USD: current=0.2697, target=0.2500\n USO: current=0.2899, target=0.2500\n ICSH: current=0.2555, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of VLUE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0119.\nRebalancing threshold: 0.0500.\n0.0119 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0239, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.185, "BTC-USD": 0.2697, "USO": 0.2899, "ICSH": 0.2555}, "target_weights": {"VLUE": 0.25, "BTC-USD": 0.25, "USO": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.023897, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "VLUE", "primary_trade": -0.065}} +{"id": "T6_all_20240628_0268", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "BIL", "UNG"], "decision_date": "2024-06-28", "context_summary": "Max weight deviation: 0.0272, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2660, target=0.2500\n XRP-USD: current=0.1850, target=0.2500\n BIL: current=0.2947, target=0.2500\n UNG: current=0.2543, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0272.\nRebalancing threshold: 0.0500.\n0.0272 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0544, transaction cost = 0.000054 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.266, "XRP-USD": 0.185, "BIL": 0.2947, "UNG": 0.2543}, "target_weights": {"XLF": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "UNG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.054396, "transaction_cost": 5.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XRP-USD", "primary_trade": -0.065}} +{"id": "T6_all_20240523_0271", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "BIL", "SCHH"], "decision_date": "2024-05-23", "context_summary": "Max weight deviation: 0.0301, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2610, target=0.2500\n AVAX-USD: current=0.2485, target=0.2500\n BIL: current=0.2199, target=0.2500\n SCHH: current=0.2705, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0301.\nRebalancing threshold: 0.0500.\n0.0301 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0630, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.261, "AVAX-USD": 0.2485, "BIL": 0.2199, "SCHH": 0.2705}, "target_weights": {"EWJ": 0.25, "AVAX-USD": 0.25, "BIL": 0.25, "SCHH": 0.25}, "max_deviation": 0.0301, "total_turnover": 0.063041, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "BIL", "primary_trade": -0.0301}} +{"id": "T6_all_20230427_0274", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "BIL", "REZ"], "decision_date": "2023-04-27", "context_summary": "Max weight deviation: 0.0245, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2264, target=0.2500\n AVAX-USD: current=0.2349, target=0.2500\n BIL: current=0.3151, target=0.2500\n REZ: current=0.2235, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0245.\nRebalancing threshold: 0.0500.\n0.0245 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0491, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2264, "AVAX-USD": 0.2349, "BIL": 0.3151, "REZ": 0.2235}, "target_weights": {"XLU": 0.25, "AVAX-USD": 0.25, "BIL": 0.25, "REZ": 0.25}, "max_deviation": 0.065084, "total_turnover": 0.049083, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0651}} +{"id": "T6_all_20230907_0276", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "BIL", "PALL"], "decision_date": "2023-09-07", "context_summary": "Max weight deviation: 0.0171, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.3150, target=0.2500\n ADA-USD: current=0.2367, target=0.2500\n BIL: current=0.2302, target=0.2500\n PALL: current=0.2181, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of ACWI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0171.\nRebalancing threshold: 0.0500.\n0.0171 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0342, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.315, "ADA-USD": 0.2367, "BIL": 0.2302, "PALL": 0.2181}, "target_weights": {"ACWI": 0.25, "ADA-USD": 0.25, "BIL": 0.25, "PALL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.03418, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": 0.065}} +{"id": "T6_all_20241105_0278", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ADA-USD", "SCHH", "SGOV"], "decision_date": "2024-11-05", "context_summary": "Max weight deviation: 0.0470, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2602, target=0.2500\n ADA-USD: current=0.2775, target=0.2500\n SCHH: current=0.2772, target=0.2500\n SGOV: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0470.\nRebalancing threshold: 0.0500.\n0.0470 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0941, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2602, "ADA-USD": 0.2775, "SCHH": 0.2772, "SGOV": 0.185}, "target_weights": {"IWM": 0.25, "ADA-USD": 0.25, "SCHH": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.094067, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SGOV", "primary_trade": -0.065}} +{"id": "T6_all_20240917_0280", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "XRP-USD", "REZ", "PPLT"], "decision_date": "2024-09-17", "context_summary": "Max weight deviation: 0.0316, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.3086, target=0.2500\n XRP-USD: current=0.2432, target=0.2500\n REZ: current=0.2633, target=0.2500\n PPLT: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of PPLT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0316.\nRebalancing threshold: 0.0500.\n0.0316 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0698, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.3086, "XRP-USD": 0.2432, "REZ": 0.2633, "PPLT": 0.185}, "target_weights": {"VEA": 0.25, "XRP-USD": 0.25, "REZ": 0.25, "PPLT": 0.25}, "max_deviation": 0.065038, "total_turnover": 0.06984, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "PPLT", "primary_trade": -0.065}} +{"id": "T6_all_20240703_0287", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD", "USO", "HYG"], "decision_date": "2024-07-03", "context_summary": "Max weight deviation: 0.0104, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2461, target=0.2500\n BNB-USD: current=0.2477, target=0.2500\n USO: current=0.2458, target=0.2500\n HYG: current=0.2604, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0104.\nRebalancing threshold: 0.0500.\n0.0104 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0207, transaction cost = 0.000021 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2461, "BNB-USD": 0.2477, "USO": 0.2458, "HYG": 0.2604}, "target_weights": {"QQQ": 0.25, "BNB-USD": 0.25, "USO": 0.25, "HYG": 0.25}, "max_deviation": 0.0104, "total_turnover": 0.020717, "transaction_cost": 2.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "HYG", "primary_trade": 0.0104}} +{"id": "T6_all_20230904_0288", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "HYG", "DBB"], "decision_date": "2023-09-04", "context_summary": "Max weight deviation: 0.0381, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.3150, target=0.2500\n ADA-USD: current=0.2201, target=0.2500\n HYG: current=0.2292, target=0.2500\n DBB: current=0.2357, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0381.\nRebalancing threshold: 0.0500.\n0.0381 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0762, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.315, "ADA-USD": 0.2201, "HYG": 0.2292, "DBB": 0.2357}, "target_weights": {"XLI": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.076158, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLI", "primary_trade": 0.065}} +{"id": "T6_all_20241101_0289", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "XHB", "CPER"], "decision_date": "2024-11-01", "context_summary": "Max weight deviation: 0.0048, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2486, target=0.2500\n DOT-USD: current=0.2548, target=0.2500\n XHB: current=0.2488, target=0.2500\n CPER: current=0.2478, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0048.\nRebalancing threshold: 0.0500.\n0.0048 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0096, transaction cost = 0.000010 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2486, "DOT-USD": 0.2548, "XHB": 0.2488, "CPER": 0.2478}, "target_weights": {"XLY": 0.25, "DOT-USD": 0.25, "XHB": 0.25, "CPER": 0.25}, "max_deviation": 0.0048, "total_turnover": 0.009619, "transaction_cost": 1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "DOT-USD", "primary_trade": 0.0048}} +{"id": "T6_all_20230502_0291", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD", "DBB", "XHB"], "decision_date": "2023-05-02", "context_summary": "Max weight deviation: 0.0100, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2567, target=0.2500\n DOT-USD: current=0.2403, target=0.2500\n DBB: current=0.2600, target=0.2500\n XHB: current=0.2430, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0100.\nRebalancing threshold: 0.0500.\n0.0100 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0334, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2567, "DOT-USD": 0.2403, "DBB": 0.26, "XHB": 0.243}, "target_weights": {"ACWI": 0.25, "DOT-USD": 0.25, "DBB": 0.25, "XHB": 0.25}, "max_deviation": 0.01, "total_turnover": 0.033378, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": 0.01}} +{"id": "T6_all_20230523_0293", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "HAUZ", "BIL"], "decision_date": "2023-05-23", "context_summary": "Max weight deviation: 0.0296, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2204, target=0.2500\n ADA-USD: current=0.2602, target=0.2500\n HAUZ: current=0.2590, target=0.2500\n BIL: current=0.2604, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0296.\nRebalancing threshold: 0.0500.\n0.0296 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0592, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2204, "ADA-USD": 0.2602, "HAUZ": 0.259, "BIL": 0.2604}, "target_weights": {"XLRE": 0.25, "ADA-USD": 0.25, "HAUZ": 0.25, "BIL": 0.25}, "max_deviation": 0.0296, "total_turnover": 0.05922, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": -0.0296}} +{"id": "T6_all_20240822_0295", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "LINK-USD", "ICSH", "IYR"], "decision_date": "2024-08-22", "context_summary": "Max weight deviation: 0.0174, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2396, target=0.2500\n LINK-USD: current=0.2538, target=0.2500\n ICSH: current=0.2674, target=0.2500\n IYR: current=0.2392, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0174.\nRebalancing threshold: 0.0500.\n0.0174 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0424, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2396, "LINK-USD": 0.2538, "ICSH": 0.2674, "IYR": 0.2392}, "target_weights": {"XLK": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "IYR": 0.25}, "max_deviation": 0.0174, "total_turnover": 0.042369, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ICSH", "primary_trade": 0.0174}} +{"id": "T6_all_20240812_0296", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "XRP-USD", "TIP", "REZ"], "decision_date": "2024-08-12", "context_summary": "Max weight deviation: 0.0125, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.1953, target=0.2500\n XRP-USD: current=0.2603, target=0.2500\n TIP: current=0.3148, target=0.2500\n REZ: current=0.2296, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0648 of TIP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0125.\nRebalancing threshold: 0.0500.\n0.0125 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0290, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.1953, "XRP-USD": 0.2603, "TIP": 0.3148, "REZ": 0.2296}, "target_weights": {"IVV": 0.25, "XRP-USD": 0.25, "TIP": 0.25, "REZ": 0.25}, "max_deviation": 0.064836, "total_turnover": 0.02898, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "TIP", "primary_trade": 0.0648}} +{"id": "T6_all_20231215_0297", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "XRP-USD", "DBB", "VNQ"], "decision_date": "2023-12-15", "context_summary": "Max weight deviation: 0.0061, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2478, target=0.2500\n XRP-USD: current=0.2556, target=0.2500\n DBB: current=0.2439, target=0.2500\n VNQ: current=0.2527, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0061.\nRebalancing threshold: 0.0500.\n0.0061 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0165, transaction cost = 0.000017 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2478, "XRP-USD": 0.2556, "DBB": 0.2439, "VNQ": 0.2527}, "target_weights": {"IWM": 0.25, "XRP-USD": 0.25, "DBB": 0.25, "VNQ": 0.25}, "max_deviation": 0.0061, "total_turnover": 0.016513, "transaction_cost": 1.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": -0.0061}} +{"id": "T6_all_20240722_0298", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "STIP", "ICSH"], "decision_date": "2024-07-22", "context_summary": "Max weight deviation: 0.0248, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2956, target=0.2500\n ETH-USD: current=0.1850, target=0.2500\n STIP: current=0.2605, target=0.2500\n ICSH: current=0.2589, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0248.\nRebalancing threshold: 0.0500.\n0.0248 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0495, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2956, "ETH-USD": 0.185, "STIP": 0.2605, "ICSH": 0.2589}, "target_weights": {"XLRE": 0.25, "ETH-USD": 0.25, "STIP": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.049519, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "ETH-USD", "primary_trade": -0.065}} +{"id": "T6_all_20240213_0299", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "WEAT", "EMB"], "decision_date": "2024-02-13", "context_summary": "Max weight deviation: 0.0303, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2366, target=0.2500\n BTC-USD: current=0.2197, target=0.2500\n WEAT: current=0.2775, target=0.2500\n EMB: current=0.2662, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0303.\nRebalancing threshold: 0.0500.\n0.0303 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0875, transaction cost = 0.000087 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2366, "BTC-USD": 0.2197, "WEAT": 0.2775, "EMB": 0.2662}, "target_weights": {"XLV": 0.25, "BTC-USD": 0.25, "WEAT": 0.25, "EMB": 0.25}, "max_deviation": 0.0303, "total_turnover": 0.087468, "transaction_cost": 8.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "BTC-USD", "primary_trade": -0.0303}} +{"id": "T6_all_20231115_0300", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "XHB", "CSHI"], "decision_date": "2023-11-15", "context_summary": "Max weight deviation: 0.0168, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.3149, target=0.2500\n LINK-USD: current=0.1942, target=0.2500\n XHB: current=0.2047, target=0.2500\n CSHI: current=0.2863, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of XLU", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0168.\nRebalancing threshold: 0.0500.\n0.0168 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0524, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.3149, "LINK-USD": 0.1942, "XHB": 0.2047, "CSHI": 0.2863}, "target_weights": {"XLU": 0.25, "LINK-USD": 0.25, "XHB": 0.25, "CSHI": 0.25}, "max_deviation": 0.064878, "total_turnover": 0.05237, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLU", "primary_trade": 0.0649}} +{"id": "T6_all_20230109_0302", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BNB-USD", "ITB", "SGOV"], "decision_date": "2023-01-09", "context_summary": "Max weight deviation: 0.0221, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.1850, target=0.2500\n BNB-USD: current=0.2991, target=0.2500\n ITB: current=0.2474, target=0.2500\n SGOV: current=0.2685, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XLV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0221.\nRebalancing threshold: 0.0500.\n0.0221 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0460, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.185, "BNB-USD": 0.2991, "ITB": 0.2474, "SGOV": 0.2685}, "target_weights": {"XLV": 0.25, "BNB-USD": 0.25, "ITB": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.045997, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLV", "primary_trade": -0.065}} +{"id": "T6_all_20230831_0304", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "TIP", "IAU"], "decision_date": "2023-08-31", "context_summary": "Max weight deviation: 0.0212, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.3150, target=0.2500\n ADA-USD: current=0.2580, target=0.2500\n TIP: current=0.2111, target=0.2500\n IAU: current=0.2160, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLK", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0212.\nRebalancing threshold: 0.0500.\n0.0212 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0476, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.315, "ADA-USD": 0.258, "TIP": 0.2111, "IAU": 0.216}, "target_weights": {"XLK": 0.25, "ADA-USD": 0.25, "TIP": 0.25, "IAU": 0.25}, "max_deviation": 0.065, "total_turnover": 0.047611, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": 0.065}} +{"id": "T6_all_20231212_0305", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "MATIC-USD", "TIP", "UNG"], "decision_date": "2023-12-12", "context_summary": "Max weight deviation: 0.0470, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2030, target=0.2500\n MATIC-USD: current=0.2694, target=0.2500\n TIP: current=0.2530, target=0.2500\n UNG: current=0.2746, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0470.\nRebalancing threshold: 0.0500.\n0.0470 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0941, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.203, "MATIC-USD": 0.2694, "TIP": 0.253, "UNG": 0.2746}, "target_weights": {"XLV": 0.25, "MATIC-USD": 0.25, "TIP": 0.25, "UNG": 0.25}, "max_deviation": 0.047, "total_turnover": 0.09408, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLV", "primary_trade": -0.047}} +{"id": "T6_all_20231211_0307", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "IAU", "SGOV"], "decision_date": "2023-12-11", "context_summary": "Max weight deviation: 0.0222, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2722, target=0.2500\n LINK-USD: current=0.2367, target=0.2500\n IAU: current=0.2473, target=0.2500\n SGOV: current=0.2438, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0222.\nRebalancing threshold: 0.0500.\n0.0222 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0444, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2722, "LINK-USD": 0.2367, "IAU": 0.2473, "SGOV": 0.2438}, "target_weights": {"EWJ": 0.25, "LINK-USD": 0.25, "IAU": 0.25, "SGOV": 0.25}, "max_deviation": 0.0222, "total_turnover": 0.044398, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EWJ", "primary_trade": 0.0222}} +{"id": "T6_all_20241213_0308", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "ETH-USD", "VNQI", "TIP"], "decision_date": "2024-12-13", "context_summary": "Max weight deviation: 0.0215, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2762, target=0.2500\n ETH-USD: current=0.2013, target=0.2500\n VNQI: current=0.2076, target=0.2500\n TIP: current=0.3149, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of TIP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0215.\nRebalancing threshold: 0.0500.\n0.0215 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0603, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2762, "ETH-USD": 0.2013, "VNQI": 0.2076, "TIP": 0.3149}, "target_weights": {"EFA": 0.25, "ETH-USD": 0.25, "VNQI": 0.25, "TIP": 0.25}, "max_deviation": 0.064905, "total_turnover": 0.060265, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "TIP", "primary_trade": 0.0649}} +{"id": "T6_all_20230307_0309", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "LINK-USD", "CPER", "BIL"], "decision_date": "2023-03-07", "context_summary": "Max weight deviation: 0.0340, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2297, target=0.2500\n LINK-USD: current=0.2447, target=0.2500\n CPER: current=0.2840, target=0.2500\n BIL: current=0.2416, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0340.\nRebalancing threshold: 0.0500.\n0.0340 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0679, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2297, "LINK-USD": 0.2447, "CPER": 0.284, "BIL": 0.2416}, "target_weights": {"XLK": 0.25, "LINK-USD": 0.25, "CPER": 0.25, "BIL": 0.25}, "max_deviation": 0.034, "total_turnover": 0.067936, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CPER", "primary_trade": 0.034}} +{"id": "T6_all_20230620_0311", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "VCIT", "WEAT"], "decision_date": "2023-06-20", "context_summary": "Max weight deviation: 0.0255, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2245, target=0.2500\n ADA-USD: current=0.2586, target=0.2500\n VCIT: current=0.2727, target=0.2500\n WEAT: current=0.2442, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0255.\nRebalancing threshold: 0.0500.\n0.0255 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0626, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2245, "ADA-USD": 0.2586, "VCIT": 0.2727, "WEAT": 0.2442}, "target_weights": {"FXI": 0.25, "ADA-USD": 0.25, "VCIT": 0.25, "WEAT": 0.25}, "max_deviation": 0.0255, "total_turnover": 0.062638, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "FXI", "primary_trade": -0.0255}} +{"id": "T6_all_20240319_0313", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "SOL-USD", "MORT", "GLD"], "decision_date": "2024-03-19", "context_summary": "Max weight deviation: 0.0470, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2488, target=0.2500\n SOL-USD: current=0.2260, target=0.2500\n MORT: current=0.2970, target=0.2500\n GLD: current=0.2282, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0470.\nRebalancing threshold: 0.0500.\n0.0470 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0940, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2488, "SOL-USD": 0.226, "MORT": 0.297, "GLD": 0.2282}, "target_weights": {"XLE": 0.25, "SOL-USD": 0.25, "MORT": 0.25, "GLD": 0.25}, "max_deviation": 0.047, "total_turnover": 0.093966, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "MORT", "primary_trade": 0.047}} +{"id": "T6_all_20230419_0315", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "USO", "MORT"], "decision_date": "2023-04-19", "context_summary": "Max weight deviation: 0.0171, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2474, target=0.2500\n BTC-USD: current=0.2331, target=0.2500\n USO: current=0.2524, target=0.2500\n MORT: current=0.2671, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0171.\nRebalancing threshold: 0.0500.\n0.0171 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0390, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2474, "BTC-USD": 0.2331, "USO": 0.2524, "MORT": 0.2671}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "USO": 0.25, "MORT": 0.25}, "max_deviation": 0.0171, "total_turnover": 0.038999, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MORT", "primary_trade": 0.0171}} +{"id": "T6_all_20240924_0316", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "AVAX-USD", "REZ", "EMB"], "decision_date": "2024-09-24", "context_summary": "Max weight deviation: 0.0123, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.3152, target=0.2500\n AVAX-USD: current=0.1941, target=0.2500\n REZ: current=0.2232, target=0.2500\n EMB: current=0.2676, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0652 of XLRE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0123.\nRebalancing threshold: 0.0500.\n0.0123 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0312, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3152, "AVAX-USD": 0.1941, "REZ": 0.2232, "EMB": 0.2676}, "target_weights": {"XLRE": 0.25, "AVAX-USD": 0.25, "REZ": 0.25, "EMB": 0.25}, "max_deviation": 0.065167, "total_turnover": 0.031248, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XLRE", "primary_trade": 0.0652}} +{"id": "T6_all_20240123_0318", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "AVAX-USD", "REZ", "CORN"], "decision_date": "2024-01-23", "context_summary": "Max weight deviation: 0.0372, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2929, target=0.2500\n AVAX-USD: current=0.2627, target=0.2500\n REZ: current=0.2594, target=0.2500\n CORN: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of CORN", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0372.\nRebalancing threshold: 0.0500.\n0.0372 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0744, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2929, "AVAX-USD": 0.2627, "REZ": 0.2594, "CORN": 0.185}, "target_weights": {"USMV": 0.25, "AVAX-USD": 0.25, "REZ": 0.25, "CORN": 0.25}, "max_deviation": 0.065032, "total_turnover": 0.074368, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "CORN", "primary_trade": -0.065}} +{"id": "T6_all_20230406_0319", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "LINK-USD", "PDBC", "HYG"], "decision_date": "2023-04-06", "context_summary": "Max weight deviation: 0.0230, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2648, target=0.2500\n LINK-USD: current=0.2596, target=0.2500\n PDBC: current=0.2486, target=0.2500\n HYG: current=0.2270, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0230.\nRebalancing threshold: 0.0500.\n0.0230 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0488, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2648, "LINK-USD": 0.2596, "PDBC": 0.2486, "HYG": 0.227}, "target_weights": {"IVV": 0.25, "LINK-USD": 0.25, "PDBC": 0.25, "HYG": 0.25}, "max_deviation": 0.023, "total_turnover": 0.048756, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": -0.023}} +{"id": "T6_all_20240621_0320", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "AVAX-USD", "EMB", "DBC"], "decision_date": "2024-06-21", "context_summary": "Max weight deviation: 0.0111, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.3090, target=0.2500\n AVAX-USD: current=0.2774, target=0.2500\n EMB: current=0.2288, target=0.2500\n DBC: current=0.1849, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0651 of DBC", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0111.\nRebalancing threshold: 0.0500.\n0.0111 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0295, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.309, "AVAX-USD": 0.2774, "EMB": 0.2288, "DBC": 0.1849}, "target_weights": {"ACWI": 0.25, "AVAX-USD": 0.25, "EMB": 0.25, "DBC": 0.25}, "max_deviation": 0.065108, "total_turnover": 0.029486, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "DBC", "primary_trade": -0.0651}} +{"id": "T6_all_20230814_0321", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BNB-USD", "EMB", "ICSH"], "decision_date": "2023-08-14", "context_summary": "Max weight deviation: 0.0337, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2538, target=0.2500\n BNB-USD: current=0.2226, target=0.2500\n EMB: current=0.2837, target=0.2500\n ICSH: current=0.2399, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0337.\nRebalancing threshold: 0.0500.\n0.0337 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0750, transaction cost = 0.000075 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2538, "BNB-USD": 0.2226, "EMB": 0.2837, "ICSH": 0.2399}, "target_weights": {"XLV": 0.25, "BNB-USD": 0.25, "EMB": 0.25, "ICSH": 0.25}, "max_deviation": 0.0337, "total_turnover": 0.074984, "transaction_cost": 7.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EMB", "primary_trade": 0.0337}} +{"id": "T6_all_20230324_0323", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "XRP-USD", "TIP", "ITB"], "decision_date": "2023-03-24", "context_summary": "Max weight deviation: 0.0326, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2174, target=0.2500\n XRP-USD: current=0.2694, target=0.2500\n TIP: current=0.2569, target=0.2500\n ITB: current=0.2563, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0326.\nRebalancing threshold: 0.0500.\n0.0326 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0652, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2174, "XRP-USD": 0.2694, "TIP": 0.2569, "ITB": 0.2563}, "target_weights": {"QUAL": 0.25, "XRP-USD": 0.25, "TIP": 0.25, "ITB": 0.25}, "max_deviation": 0.0326, "total_turnover": 0.065216, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "QUAL", "primary_trade": -0.0326}} +{"id": "T6_all_20240520_0324", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX", "LINK-USD", "SCHP", "DBB"], "decision_date": "2024-05-20", "context_summary": "Max weight deviation: 0.0295, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.3151, target=0.2500\n LINK-USD: current=0.2234, target=0.2500\n SCHP: current=0.2141, target=0.2500\n DBB: current=0.2474, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of ^VIX", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0295.\nRebalancing threshold: 0.0500.\n0.0295 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0590, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.3151, "LINK-USD": 0.2234, "SCHP": 0.2141, "DBB": 0.2474}, "target_weights": {"^VIX": 0.25, "LINK-USD": 0.25, "SCHP": 0.25, "DBB": 0.25}, "max_deviation": 0.065069, "total_turnover": 0.059041, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "^VIX", "primary_trade": 0.0651}} +{"id": "T6_all_20241113_0326", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SOL-USD", "CORN", "JNK"], "decision_date": "2024-11-13", "context_summary": "Max weight deviation: 0.0208, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2275, target=0.2500\n SOL-USD: current=0.2112, target=0.2500\n CORN: current=0.2462, target=0.2500\n JNK: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of JNK", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0208.\nRebalancing threshold: 0.0500.\n0.0208 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0415, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2275, "SOL-USD": 0.2112, "CORN": 0.2462, "JNK": 0.315}, "target_weights": {"VLUE": 0.25, "SOL-USD": 0.25, "CORN": 0.25, "JNK": 0.25}, "max_deviation": 0.065, "total_turnover": 0.041549, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "JNK", "primary_trade": 0.065}} +{"id": "T6_all_20240716_0328", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "VNQ", "SLV"], "decision_date": "2024-07-16", "context_summary": "Max weight deviation: 0.0180, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.1850, target=0.2500\n MATIC-USD: current=0.2063, target=0.2500\n VNQ: current=0.3081, target=0.2500\n SLV: current=0.3006, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of VTI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0180.\nRebalancing threshold: 0.0500.\n0.0180 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0603, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.185, "MATIC-USD": 0.2063, "VNQ": 0.3081, "SLV": 0.3006}, "target_weights": {"VTI": 0.25, "MATIC-USD": 0.25, "VNQ": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.060253, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "VTI", "primary_trade": -0.065}} +{"id": "T6_all_20230524_0330", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "XRP-USD", "XHB", "TLT"], "decision_date": "2023-05-24", "context_summary": "Max weight deviation: 0.0216, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2766, target=0.2500\n XRP-USD: current=0.1851, target=0.2500\n XHB: current=0.2459, target=0.2500\n TLT: current=0.2925, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0649 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0216.\nRebalancing threshold: 0.0500.\n0.0216 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0459, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2766, "XRP-USD": 0.1851, "XHB": 0.2459, "TLT": 0.2925}, "target_weights": {"^VIX": 0.25, "XRP-USD": 0.25, "XHB": 0.25, "TLT": 0.25}, "max_deviation": 0.064944, "total_turnover": 0.045867, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.0649}} +{"id": "T6_all_20241018_0331", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "AVAX-USD", "PALL", "ICSH"], "decision_date": "2024-10-18", "context_summary": "Max weight deviation: 0.0350, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2704, target=0.2500\n AVAX-USD: current=0.2640, target=0.2500\n PALL: current=0.2507, target=0.2500\n ICSH: current=0.2150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0350.\nRebalancing threshold: 0.0500.\n0.0350 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0700, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2704, "AVAX-USD": 0.264, "PALL": 0.2507, "ICSH": 0.215}, "target_weights": {"^VIX": 0.25, "AVAX-USD": 0.25, "PALL": 0.25, "ICSH": 0.25}, "max_deviation": 0.035, "total_turnover": 0.06998, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ICSH", "primary_trade": -0.035}} +{"id": "T6_all_20240209_0332", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "AVAX-USD", "REZ", "IAU"], "decision_date": "2024-02-09", "context_summary": "Max weight deviation: 0.0143, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.3150, target=0.2500\n AVAX-USD: current=0.2545, target=0.2500\n REZ: current=0.2155, target=0.2500\n IAU: current=0.2150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0143.\nRebalancing threshold: 0.0500.\n0.0143 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0306, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.315, "AVAX-USD": 0.2545, "REZ": 0.2155, "IAU": 0.215}, "target_weights": {"XLB": 0.25, "AVAX-USD": 0.25, "REZ": 0.25, "IAU": 0.25}, "max_deviation": 0.065, "total_turnover": 0.030621, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "XLB", "primary_trade": 0.065}} +{"id": "T6_all_20240719_0333", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "ITB", "BIL"], "decision_date": "2024-07-19", "context_summary": "Max weight deviation: 0.0251, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2402, target=0.2500\n BTC-USD: current=0.2385, target=0.2500\n ITB: current=0.2751, target=0.2500\n BIL: current=0.2462, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0251.\nRebalancing threshold: 0.0500.\n0.0251 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0502, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2402, "BTC-USD": 0.2385, "ITB": 0.2751, "BIL": 0.2462}, "target_weights": {"IVV": 0.25, "BTC-USD": 0.25, "ITB": 0.25, "BIL": 0.25}, "max_deviation": 0.0251, "total_turnover": 0.050155, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ITB", "primary_trade": 0.0251}} +{"id": "T6_all_20230105_0334", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "CORN", "HAUZ"], "decision_date": "2023-01-05", "context_summary": "Max weight deviation: 0.0288, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.1850, target=0.2500\n XRP-USD: current=0.2464, target=0.2500\n CORN: current=0.2643, target=0.2500\n HAUZ: current=0.3042, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XLRE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0288.\nRebalancing threshold: 0.0500.\n0.0288 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0606, transaction cost = 0.000061 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.185, "XRP-USD": 0.2464, "CORN": 0.2643, "HAUZ": 0.3042}, "target_weights": {"XLRE": 0.25, "XRP-USD": 0.25, "CORN": 0.25, "HAUZ": 0.25}, "max_deviation": 0.064958, "total_turnover": 0.060617, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": -0.065}} +{"id": "T6_all_20231117_0337", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "XHB", "TLT"], "decision_date": "2023-11-17", "context_summary": "Max weight deviation: 0.0334, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2469, target=0.2500\n DOT-USD: current=0.2582, target=0.2500\n XHB: current=0.2166, target=0.2500\n TLT: current=0.2783, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0334.\nRebalancing threshold: 0.0500.\n0.0334 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0731, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2469, "DOT-USD": 0.2582, "XHB": 0.2166, "TLT": 0.2783}, "target_weights": {"XLY": 0.25, "DOT-USD": 0.25, "XHB": 0.25, "TLT": 0.25}, "max_deviation": 0.0334, "total_turnover": 0.073074, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XHB", "primary_trade": -0.0334}} +{"id": "T6_all_20230707_0339", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "VNQI", "CSHI"], "decision_date": "2023-07-07", "context_summary": "Max weight deviation: 0.0075, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.2450, target=0.2500\n BTC-USD: current=0.2575, target=0.2500\n VNQI: current=0.2441, target=0.2500\n CSHI: current=0.2535, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0075.\nRebalancing threshold: 0.0500.\n0.0075 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0219, transaction cost = 0.000022 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.245, "BTC-USD": 0.2575, "VNQI": 0.2441, "CSHI": 0.2535}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "VNQI": 0.25, "CSHI": 0.25}, "max_deviation": 0.0075, "total_turnover": 0.021862, "transaction_cost": 2.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.0075}} +{"id": "T6_all_20241030_0340", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "MORT", "IAU"], "decision_date": "2024-10-30", "context_summary": "Max weight deviation: 0.0385, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.1850, target=0.2500\n BTC-USD: current=0.2812, target=0.2500\n MORT: current=0.2544, target=0.2500\n IAU: current=0.2794, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XLV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0385.\nRebalancing threshold: 0.0500.\n0.0385 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0770, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.185, "BTC-USD": 0.2812, "MORT": 0.2544, "IAU": 0.2794}, "target_weights": {"XLV": 0.25, "BTC-USD": 0.25, "MORT": 0.25, "IAU": 0.25}, "max_deviation": 0.065, "total_turnover": 0.07697, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "XLV", "primary_trade": -0.065}} +{"id": "T6_all_20231227_0341", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "SOYB", "EMB"], "decision_date": "2023-12-27", "context_summary": "Max weight deviation: 0.0134, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2606, target=0.2500\n LINK-USD: current=0.2366, target=0.2500\n SOYB: current=0.2519, target=0.2500\n EMB: current=0.2510, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0134.\nRebalancing threshold: 0.0500.\n0.0134 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0269, transaction cost = 0.000027 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2606, "LINK-USD": 0.2366, "SOYB": 0.2519, "EMB": 0.251}, "target_weights": {"FXI": 0.25, "LINK-USD": 0.25, "SOYB": 0.25, "EMB": 0.25}, "max_deviation": 0.0134, "total_turnover": 0.026896, "transaction_cost": 2.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.0134}} +{"id": "T6_all_20240314_0342", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BTC-USD", "LQD", "XHB"], "decision_date": "2024-03-14", "context_summary": "Max weight deviation: 0.0077, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.1850, target=0.2500\n BTC-USD: current=0.2424, target=0.2500\n LQD: current=0.2669, target=0.2500\n XHB: current=0.3057, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of QQQ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0077.\nRebalancing threshold: 0.0500.\n0.0077 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0171, transaction cost = 0.000017 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.185, "BTC-USD": 0.2424, "LQD": 0.2669, "XHB": 0.3057}, "target_weights": {"QQQ": 0.25, "BTC-USD": 0.25, "LQD": 0.25, "XHB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.017129, "transaction_cost": 1.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "QQQ", "primary_trade": -0.065}} +{"id": "T6_all_20230118_0344", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BNB-USD", "ICSH", "CPER"], "decision_date": "2023-01-18", "context_summary": "Max weight deviation: 0.0327, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.3013, target=0.2500\n BNB-USD: current=0.2536, target=0.2500\n ICSH: current=0.2601, target=0.2500\n CPER: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of CPER", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0327.\nRebalancing threshold: 0.0500.\n0.0327 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0655, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.3013, "BNB-USD": 0.2536, "ICSH": 0.2601, "CPER": 0.185}, "target_weights": {"IWM": 0.25, "BNB-USD": 0.25, "ICSH": 0.25, "CPER": 0.25}, "max_deviation": 0.065, "total_turnover": 0.065481, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "CPER", "primary_trade": -0.065}} +{"id": "T6_all_20240429_0345", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ADA-USD", "ICSH", "IYR"], "decision_date": "2024-04-29", "context_summary": "Max weight deviation: 0.0275, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2640, target=0.2500\n ADA-USD: current=0.2225, target=0.2500\n ICSH: current=0.2731, target=0.2500\n IYR: current=0.2403, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0275.\nRebalancing threshold: 0.0500.\n0.0275 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0743, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.264, "ADA-USD": 0.2225, "ICSH": 0.2731, "IYR": 0.2403}, "target_weights": {"XLU": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "IYR": 0.25}, "max_deviation": 0.0275, "total_turnover": 0.074276, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ADA-USD", "primary_trade": -0.0275}} +{"id": "T6_all_20231226_0346", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "HYG", "CORN"], "decision_date": "2023-12-26", "context_summary": "Max weight deviation: 0.0396, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2031, target=0.2500\n ADA-USD: current=0.2272, target=0.2500\n HYG: current=0.2546, target=0.2500\n CORN: current=0.3151, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of CORN", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0396.\nRebalancing threshold: 0.0500.\n0.0396 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0849, transaction cost = 0.000085 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2031, "ADA-USD": 0.2272, "HYG": 0.2546, "CORN": 0.3151}, "target_weights": {"^VIX": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "CORN": 0.25}, "max_deviation": 0.065052, "total_turnover": 0.084857, "transaction_cost": 8.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "CORN", "primary_trade": 0.0651}} +{"id": "T6_all_20240927_0347", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BNB-USD", "CPER", "CSHI"], "decision_date": "2024-09-27", "context_summary": "Max weight deviation: 0.0034, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2488, target=0.2500\n BNB-USD: current=0.2530, target=0.2500\n CPER: current=0.2516, target=0.2500\n CSHI: current=0.2466, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0034.\nRebalancing threshold: 0.0500.\n0.0034 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0093, transaction cost = 0.000009 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2488, "BNB-USD": 0.253, "CPER": 0.2516, "CSHI": 0.2466}, "target_weights": {"^VIX": 0.25, "BNB-USD": 0.25, "CPER": 0.25, "CSHI": 0.25}, "max_deviation": 0.0034, "total_turnover": 0.00928, "transaction_cost": 9e-06, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "CSHI", "primary_trade": -0.0034}} +{"id": "T6_all_20231006_0348", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "XRP-USD", "VNQ", "SGOV"], "decision_date": "2023-10-06", "context_summary": "Max weight deviation: 0.0130, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2926, target=0.2500\n XRP-USD: current=0.2091, target=0.2500\n VNQ: current=0.1851, target=0.2500\n SGOV: current=0.3132, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0649 of VNQ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0130.\nRebalancing threshold: 0.0500.\n0.0130 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0423, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2926, "XRP-USD": 0.2091, "VNQ": 0.1851, "SGOV": 0.3132}, "target_weights": {"FXI": 0.25, "XRP-USD": 0.25, "VNQ": 0.25, "SGOV": 0.25}, "max_deviation": 0.064907, "total_turnover": 0.042286, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQ", "primary_trade": -0.0649}} +{"id": "T6_all_20231003_0349", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "SOL-USD", "CSHI", "SCHH"], "decision_date": "2023-10-03", "context_summary": "Max weight deviation: 0.0366, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2742, target=0.2500\n SOL-USD: current=0.2134, target=0.2500\n CSHI: current=0.2591, target=0.2500\n SCHH: current=0.2533, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0366.\nRebalancing threshold: 0.0500.\n0.0366 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0733, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2742, "SOL-USD": 0.2134, "CSHI": 0.2591, "SCHH": 0.2533}, "target_weights": {"ACWI": 0.25, "SOL-USD": 0.25, "CSHI": 0.25, "SCHH": 0.25}, "max_deviation": 0.0366, "total_turnover": 0.073283, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": -0.0366}} +{"id": "T6_all_20230605_0350", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "VNQ", "SCHP"], "decision_date": "2023-06-05", "context_summary": "Max weight deviation: 0.0200, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2458, target=0.2500\n ADA-USD: current=0.2487, target=0.2500\n VNQ: current=0.1905, target=0.2500\n SCHP: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SCHP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0200.\nRebalancing threshold: 0.0500.\n0.0200 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0400, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2458, "ADA-USD": 0.2487, "VNQ": 0.1905, "SCHP": 0.315}, "target_weights": {"IVV": 0.25, "ADA-USD": 0.25, "VNQ": 0.25, "SCHP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.039987, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": 0.065}} +{"id": "T6_all_20240515_0351", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "XRP-USD", "BNO", "BIL"], "decision_date": "2024-05-15", "context_summary": "Max weight deviation: 0.0103, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2533, target=0.2500\n XRP-USD: current=0.2397, target=0.2500\n BNO: current=0.2529, target=0.2500\n BIL: current=0.2542, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0103.\nRebalancing threshold: 0.0500.\n0.0103 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0207, transaction cost = 0.000021 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2533, "XRP-USD": 0.2397, "BNO": 0.2529, "BIL": 0.2542}, "target_weights": {"EEM": 0.25, "XRP-USD": 0.25, "BNO": 0.25, "BIL": 0.25}, "max_deviation": 0.0103, "total_turnover": 0.020685, "transaction_cost": 2.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XRP-USD", "primary_trade": -0.0103}} +{"id": "T6_all_20230608_0352", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "SOL-USD", "BNO", "SGOV"], "decision_date": "2023-06-08", "context_summary": "Max weight deviation: 0.0333, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2910, target=0.2500\n SOL-USD: current=0.1850, target=0.2500\n BNO: current=0.2512, target=0.2500\n SGOV: current=0.2728, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SOL-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0333.\nRebalancing threshold: 0.0500.\n0.0333 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0666, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.291, "SOL-USD": 0.185, "BNO": 0.2512, "SGOV": 0.2728}, "target_weights": {"QQQ": 0.25, "SOL-USD": 0.25, "BNO": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.066598, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": -0.065}} +{"id": "T6_all_20240424_0353", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "AVAX-USD", "TIP", "IYR"], "decision_date": "2024-04-24", "context_summary": "Max weight deviation: 0.0370, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2750, target=0.2500\n AVAX-USD: current=0.2620, target=0.2500\n TIP: current=0.2130, target=0.2500\n IYR: current=0.2499, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0370.\nRebalancing threshold: 0.0500.\n0.0370 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0741, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.275, "AVAX-USD": 0.262, "TIP": 0.213, "IYR": 0.2499}, "target_weights": {"XLP": 0.25, "AVAX-USD": 0.25, "TIP": 0.25, "IYR": 0.25}, "max_deviation": 0.037, "total_turnover": 0.074143, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "TIP", "primary_trade": -0.037}} +{"id": "T6_all_20240521_0354", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "XRP-USD", "DBC", "VNQI"], "decision_date": "2024-05-21", "context_summary": "Max weight deviation: 0.0168, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2357, target=0.2500\n XRP-USD: current=0.1989, target=0.2500\n DBC: current=0.3150, target=0.2500\n VNQI: current=0.2504, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of DBC", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0168.\nRebalancing threshold: 0.0500.\n0.0168 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0337, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2357, "XRP-USD": 0.1989, "DBC": 0.315, "VNQI": 0.2504}, "target_weights": {"EEM": 0.25, "XRP-USD": 0.25, "DBC": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.033718, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "DBC", "primary_trade": 0.065}} +{"id": "T6_all_20230516_0356", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BTC-USD", "STIP", "HAUZ"], "decision_date": "2023-05-16", "context_summary": "Max weight deviation: 0.0385, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.1850, target=0.2500\n BTC-USD: current=0.2735, target=0.2500\n STIP: current=0.2459, target=0.2500\n HAUZ: current=0.2956, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of EWJ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0385.\nRebalancing threshold: 0.0500.\n0.0385 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0818, transaction cost = 0.000082 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.185, "BTC-USD": 0.2735, "STIP": 0.2459, "HAUZ": 0.2956}, "target_weights": {"EWJ": 0.25, "BTC-USD": 0.25, "STIP": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.081751, "transaction_cost": 8.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EWJ", "primary_trade": -0.065}} +{"id": "T6_all_20230823_0359", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "MATIC-USD", "BNO", "TLH"], "decision_date": "2023-08-23", "context_summary": "Max weight deviation: 0.0149, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2372, target=0.2500\n MATIC-USD: current=0.2476, target=0.2500\n BNO: current=0.2503, target=0.2500\n TLH: current=0.2649, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0149.\nRebalancing threshold: 0.0500.\n0.0149 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0304, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2372, "MATIC-USD": 0.2476, "BNO": 0.2503, "TLH": 0.2649}, "target_weights": {"XLY": 0.25, "MATIC-USD": 0.25, "BNO": 0.25, "TLH": 0.25}, "max_deviation": 0.0149, "total_turnover": 0.030446, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": 0.0149}} +{"id": "T6_all_20240909_0360", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "STIP", "ICSH"], "decision_date": "2024-09-09", "context_summary": "Max weight deviation: 0.0286, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.3150, target=0.2500\n ADA-USD: current=0.2532, target=0.2500\n STIP: current=0.1893, target=0.2500\n ICSH: current=0.2425, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of USMV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0286.\nRebalancing threshold: 0.0500.\n0.0286 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0601, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.315, "ADA-USD": 0.2532, "STIP": 0.1893, "ICSH": 0.2425}, "target_weights": {"USMV": 0.25, "ADA-USD": 0.25, "STIP": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.060064, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "USMV", "primary_trade": 0.065}} +{"id": "T6_all_20240301_0362", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "SLV", "LQD"], "decision_date": "2024-03-01", "context_summary": "Max weight deviation: 0.0291, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.1934, target=0.2500\n AVAX-USD: current=0.2341, target=0.2500\n SLV: current=0.2575, target=0.2500\n LQD: current=0.3149, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of LQD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0291.\nRebalancing threshold: 0.0500.\n0.0291 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0648, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.1934, "AVAX-USD": 0.2341, "SLV": 0.2575, "LQD": 0.3149}, "target_weights": {"EEM": 0.25, "AVAX-USD": 0.25, "SLV": 0.25, "LQD": 0.25}, "max_deviation": 0.06493, "total_turnover": 0.064835, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "LQD", "primary_trade": 0.0649}} +{"id": "T6_all_20230706_0363", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "DOT-USD", "CSHI", "SOYB"], "decision_date": "2023-07-06", "context_summary": "Max weight deviation: 0.0247, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2669, target=0.2500\n DOT-USD: current=0.2327, target=0.2500\n CSHI: current=0.2257, target=0.2500\n SOYB: current=0.2747, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0247.\nRebalancing threshold: 0.0500.\n0.0247 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0832, transaction cost = 0.000083 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2669, "DOT-USD": 0.2327, "CSHI": 0.2257, "SOYB": 0.2747}, "target_weights": {"EWJ": 0.25, "DOT-USD": 0.25, "CSHI": 0.25, "SOYB": 0.25}, "max_deviation": 0.0247, "total_turnover": 0.083168, "transaction_cost": 8.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": 0.0247}} +{"id": "T6_all_20231017_0364", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "TIP", "MORT"], "decision_date": "2023-10-17", "context_summary": "Max weight deviation: 0.0155, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2529, target=0.2500\n ETH-USD: current=0.3150, target=0.2500\n TIP: current=0.2076, target=0.2500\n MORT: current=0.2244, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0155.\nRebalancing threshold: 0.0500.\n0.0155 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0324, transaction cost = 0.000032 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2529, "ETH-USD": 0.315, "TIP": 0.2076, "MORT": 0.2244}, "target_weights": {"XLU": 0.25, "ETH-USD": 0.25, "TIP": 0.25, "MORT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.032367, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.065}} +{"id": "T6_all_20241106_0365", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "DOT-USD", "PPLT", "CSHI"], "decision_date": "2024-11-06", "context_summary": "Max weight deviation: 0.0140, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2360, target=0.2500\n DOT-USD: current=0.2583, target=0.2500\n PPLT: current=0.2503, target=0.2500\n CSHI: current=0.2554, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0140.\nRebalancing threshold: 0.0500.\n0.0140 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0279, transaction cost = 0.000028 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.236, "DOT-USD": 0.2583, "PPLT": 0.2503, "CSHI": 0.2554}, "target_weights": {"FXI": 0.25, "DOT-USD": 0.25, "PPLT": 0.25, "CSHI": 0.25}, "max_deviation": 0.014, "total_turnover": 0.027907, "transaction_cost": 2.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "FXI", "primary_trade": -0.014}} +{"id": "T6_all_20240506_0367", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "SCHP", "BIL"], "decision_date": "2024-05-06", "context_summary": "Max weight deviation: 0.0532, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2753, target=0.2500\n ETH-USD: current=0.2510, target=0.2500\n SCHP: current=0.2200, target=0.2500\n BIL: current=0.2537, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0532.\nRebalancing threshold: 0.0500.\n0.0532 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1064, transaction cost = 0.000106 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2753, "ETH-USD": 0.251, "SCHP": 0.22, "BIL": 0.2537}, "target_weights": {"EEM": 0.25, "ETH-USD": 0.25, "SCHP": 0.25, "BIL": 0.25}, "max_deviation": 0.03, "total_turnover": 0.106419, "transaction_cost": 0.000106, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SCHP", "primary_trade": -0.03}} +{"id": "T6_all_20231018_0368", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BNB-USD", "SCHP", "INDS"], "decision_date": "2023-10-18", "context_summary": "Max weight deviation: 0.0313, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2799, target=0.2500\n BNB-USD: current=0.3092, target=0.2500\n SCHP: current=0.2259, target=0.2500\n INDS: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of INDS", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0313.\nRebalancing threshold: 0.0500.\n0.0313 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0857, transaction cost = 0.000086 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2799, "BNB-USD": 0.3092, "SCHP": 0.2259, "INDS": 0.185}, "target_weights": {"MTUM": 0.25, "BNB-USD": 0.25, "SCHP": 0.25, "INDS": 0.25}, "max_deviation": 0.065, "total_turnover": 0.085718, "transaction_cost": 8.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "INDS", "primary_trade": -0.065}} +{"id": "T6_all_20241001_0369", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "ICSH", "DBB"], "decision_date": "2024-10-01", "context_summary": "Max weight deviation: 0.0246, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2254, target=0.2500\n ADA-USD: current=0.2616, target=0.2500\n ICSH: current=0.2609, target=0.2500\n DBB: current=0.2520, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0246.\nRebalancing threshold: 0.0500.\n0.0246 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0492, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2254, "ADA-USD": 0.2616, "ICSH": 0.2609, "DBB": 0.252}, "target_weights": {"QUAL": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "DBB": 0.25}, "max_deviation": 0.0246, "total_turnover": 0.049189, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "QUAL", "primary_trade": -0.0246}} +{"id": "T6_all_20240627_0370", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "XRP-USD", "BIL", "REZ"], "decision_date": "2024-06-27", "context_summary": "Max weight deviation: 0.0273, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.1850, target=0.2500\n XRP-USD: current=0.2698, target=0.2500\n BIL: current=0.2796, target=0.2500\n REZ: current=0.2655, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SPY", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0273.\nRebalancing threshold: 0.0500.\n0.0273 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0545, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.185, "XRP-USD": 0.2698, "BIL": 0.2796, "REZ": 0.2655}, "target_weights": {"SPY": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "REZ": 0.25}, "max_deviation": 0.064956, "total_turnover": 0.054524, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SPY", "primary_trade": -0.065}} +{"id": "T6_all_20230308_0372", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "BNO", "CSHI"], "decision_date": "2023-03-08", "context_summary": "Max weight deviation: 0.0080, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.3150, target=0.2500\n BNB-USD: current=0.2622, target=0.2500\n BNO: current=0.1964, target=0.2500\n CSHI: current=0.2264, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLK", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0080.\nRebalancing threshold: 0.0500.\n0.0080 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0190, transaction cost = 0.000019 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.315, "BNB-USD": 0.2622, "BNO": 0.1964, "CSHI": 0.2264}, "target_weights": {"XLK": 0.25, "BNB-USD": 0.25, "BNO": 0.25, "CSHI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.01901, "transaction_cost": 1.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": 0.065}} +{"id": "T6_all_20240524_0373", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "BIL", "XHB"], "decision_date": "2024-05-24", "context_summary": "Max weight deviation: 0.0312, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2566, target=0.2500\n BNB-USD: current=0.2241, target=0.2500\n BIL: current=0.2812, target=0.2500\n XHB: current=0.2382, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0312.\nRebalancing threshold: 0.0500.\n0.0312 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0755, transaction cost = 0.000075 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2566, "BNB-USD": 0.2241, "BIL": 0.2812, "XHB": 0.2382}, "target_weights": {"EWJ": 0.25, "BNB-USD": 0.25, "BIL": 0.25, "XHB": 0.25}, "max_deviation": 0.0312, "total_turnover": 0.075492, "transaction_cost": 7.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "BIL", "primary_trade": 0.0312}} +{"id": "T6_all_20240729_0375", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "ITB", "SLV"], "decision_date": "2024-07-29", "context_summary": "Max weight deviation: 0.0170, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2469, target=0.2500\n LINK-USD: current=0.2611, target=0.2500\n ITB: current=0.2330, target=0.2500\n SLV: current=0.2591, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0170.\nRebalancing threshold: 0.0500.\n0.0170 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0404, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2469, "LINK-USD": 0.2611, "ITB": 0.233, "SLV": 0.2591}, "target_weights": {"XLY": 0.25, "LINK-USD": 0.25, "ITB": 0.25, "SLV": 0.25}, "max_deviation": 0.017, "total_turnover": 0.04036, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ITB", "primary_trade": -0.017}} +{"id": "T6_all_20230901_0376", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "AVAX-USD", "TIP", "CORN"], "decision_date": "2023-09-01", "context_summary": "Max weight deviation: 0.0343, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2644, target=0.2500\n AVAX-USD: current=0.2943, target=0.2500\n TIP: current=0.1850, target=0.2500\n CORN: current=0.2563, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of TIP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0343.\nRebalancing threshold: 0.0500.\n0.0343 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0685, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2644, "AVAX-USD": 0.2943, "TIP": 0.185, "CORN": 0.2563}, "target_weights": {"XLE": 0.25, "AVAX-USD": 0.25, "TIP": 0.25, "CORN": 0.25}, "max_deviation": 0.065, "total_turnover": 0.068535, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "TIP", "primary_trade": -0.065}} +{"id": "T6_all_20231123_0377", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SOL-USD", "ICSH", "IAU"], "decision_date": "2023-11-23", "context_summary": "Max weight deviation: 0.0202, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2364, target=0.2500\n SOL-USD: current=0.2420, target=0.2500\n ICSH: current=0.2513, target=0.2500\n IAU: current=0.2702, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0202.\nRebalancing threshold: 0.0500.\n0.0202 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0432, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2364, "SOL-USD": 0.242, "ICSH": 0.2513, "IAU": 0.2702}, "target_weights": {"EEM": 0.25, "SOL-USD": 0.25, "ICSH": 0.25, "IAU": 0.25}, "max_deviation": 0.0202, "total_turnover": 0.043161, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IAU", "primary_trade": 0.0202}} +{"id": "T6_all_20240517_0378", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "AVAX-USD", "EMB", "CSHI"], "decision_date": "2024-05-17", "context_summary": "Max weight deviation: 0.0256, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2808, target=0.2500\n AVAX-USD: current=0.3151, target=0.2500\n EMB: current=0.2038, target=0.2500\n CSHI: current=0.2003, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of AVAX-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0256.\nRebalancing threshold: 0.0500.\n0.0256 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0755, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2808, "AVAX-USD": 0.3151, "EMB": 0.2038, "CSHI": 0.2003}, "target_weights": {"FXI": 0.25, "AVAX-USD": 0.25, "EMB": 0.25, "CSHI": 0.25}, "max_deviation": 0.06508, "total_turnover": 0.075503, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "AVAX-USD", "primary_trade": 0.0651}} +{"id": "T6_all_20231225_0379", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BTC-USD", "ITB", "SHY"], "decision_date": "2023-12-25", "context_summary": "Max weight deviation: 0.0099, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.2579, target=0.2500\n BTC-USD: current=0.2476, target=0.2500\n ITB: current=0.2543, target=0.2500\n SHY: current=0.2401, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0099.\nRebalancing threshold: 0.0500.\n0.0099 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0245, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2579, "BTC-USD": 0.2476, "ITB": 0.2543, "SHY": 0.2401}, "target_weights": {"XLI": 0.25, "BTC-USD": 0.25, "ITB": 0.25, "SHY": 0.25}, "max_deviation": 0.0099, "total_turnover": 0.024496, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SHY", "primary_trade": -0.0099}} +{"id": "T6_all_20240117_0380", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "SOL-USD", "HYG", "BNO"], "decision_date": "2024-01-17", "context_summary": "Max weight deviation: 0.0111, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.1851, target=0.2500\n SOL-USD: current=0.2912, target=0.2500\n HYG: current=0.3076, target=0.2500\n BNO: current=0.2162, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0649 of XLB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0111.\nRebalancing threshold: 0.0500.\n0.0111 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0337, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.1851, "SOL-USD": 0.2912, "HYG": 0.3076, "BNO": 0.2162}, "target_weights": {"XLB": 0.25, "SOL-USD": 0.25, "HYG": 0.25, "BNO": 0.25}, "max_deviation": 0.064892, "total_turnover": 0.033693, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLB", "primary_trade": -0.0649}} +{"id": "T6_all_20230112_0382", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "SOL-USD", "CORN", "BNDX"], "decision_date": "2023-01-12", "context_summary": "Max weight deviation: 0.0107, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2429, target=0.2500\n SOL-USD: current=0.2234, target=0.2500\n CORN: current=0.2185, target=0.2500\n BNDX: current=0.3152, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0652 of BNDX", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0107.\nRebalancing threshold: 0.0500.\n0.0107 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0214, transaction cost = 0.000021 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2429, "SOL-USD": 0.2234, "CORN": 0.2185, "BNDX": 0.3152}, "target_weights": {"ACWI": 0.25, "SOL-USD": 0.25, "CORN": 0.25, "BNDX": 0.25}, "max_deviation": 0.065191, "total_turnover": 0.021435, "transaction_cost": 2.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNDX", "primary_trade": 0.0652}} +{"id": "T6_all_20240611_0384", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "SCHH", "BNDX"], "decision_date": "2024-06-11", "context_summary": "Max weight deviation: 0.0223, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.1850, target=0.2500\n ADA-USD: current=0.2754, target=0.2500\n SCHH: current=0.2777, target=0.2500\n BNDX: current=0.2620, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of EWJ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0223.\nRebalancing threshold: 0.0500.\n0.0223 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0447, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.185, "ADA-USD": 0.2754, "SCHH": 0.2777, "BNDX": 0.262}, "target_weights": {"EWJ": 0.25, "ADA-USD": 0.25, "SCHH": 0.25, "BNDX": 0.25}, "max_deviation": 0.065, "total_turnover": 0.044665, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "EWJ", "primary_trade": -0.065}} +{"id": "T6_all_20240912_0385", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "TLH", "SGOV"], "decision_date": "2024-09-12", "context_summary": "Max weight deviation: 0.0369, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2541, target=0.2500\n AVAX-USD: current=0.2667, target=0.2500\n TLH: current=0.2660, target=0.2500\n SGOV: current=0.2131, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0369.\nRebalancing threshold: 0.0500.\n0.0369 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0737, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2541, "AVAX-USD": 0.2667, "TLH": 0.266, "SGOV": 0.2131}, "target_weights": {"EFA": 0.25, "AVAX-USD": 0.25, "TLH": 0.25, "SGOV": 0.25}, "max_deviation": 0.0369, "total_turnover": 0.073744, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SGOV", "primary_trade": -0.0369}} +{"id": "T6_all_20241126_0386", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "REZ", "IEF"], "decision_date": "2024-11-26", "context_summary": "Max weight deviation: 0.0216, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.3072, target=0.2500\n LINK-USD: current=0.2307, target=0.2500\n REZ: current=0.1850, target=0.2500\n IEF: current=0.2771, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of REZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0216.\nRebalancing threshold: 0.0500.\n0.0216 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0559, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.3072, "LINK-USD": 0.2307, "REZ": 0.185, "IEF": 0.2771}, "target_weights": {"XLP": 0.25, "LINK-USD": 0.25, "REZ": 0.25, "IEF": 0.25}, "max_deviation": 0.065, "total_turnover": 0.055942, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "REZ", "primary_trade": -0.065}} +{"id": "T6_all_20230103_0387", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ETH-USD", "IGOV", "WEAT"], "decision_date": "2023-01-03", "context_summary": "Max weight deviation: 0.0140, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2360, target=0.2500\n ETH-USD: current=0.2632, target=0.2500\n IGOV: current=0.2591, target=0.2500\n WEAT: current=0.2418, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0140.\nRebalancing threshold: 0.0500.\n0.0140 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0445, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.236, "ETH-USD": 0.2632, "IGOV": 0.2591, "WEAT": 0.2418}, "target_weights": {"XLP": 0.25, "ETH-USD": 0.25, "IGOV": 0.25, "WEAT": 0.25}, "max_deviation": 0.014, "total_turnover": 0.044514, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLP", "primary_trade": -0.014}} +{"id": "T6_all_20230417_0389", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "REZ", "SHY"], "decision_date": "2023-04-17", "context_summary": "Max weight deviation: 0.0281, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2581, target=0.2500\n ADA-USD: current=0.2556, target=0.2500\n REZ: current=0.2644, target=0.2500\n SHY: current=0.2219, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0281.\nRebalancing threshold: 0.0500.\n0.0281 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0562, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2581, "ADA-USD": 0.2556, "REZ": 0.2644, "SHY": 0.2219}, "target_weights": {"QUAL": 0.25, "ADA-USD": 0.25, "REZ": 0.25, "SHY": 0.25}, "max_deviation": 0.0281, "total_turnover": 0.056184, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SHY", "primary_trade": -0.0281}} +{"id": "T6_all_20241219_0391", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "MORT", "CPER"], "decision_date": "2024-12-19", "context_summary": "Max weight deviation: 0.0170, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2330, target=0.2500\n MATIC-USD: current=0.2528, target=0.2500\n MORT: current=0.2635, target=0.2500\n CPER: current=0.2506, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0170.\nRebalancing threshold: 0.0500.\n0.0170 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0339, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.233, "MATIC-USD": 0.2528, "MORT": 0.2635, "CPER": 0.2506}, "target_weights": {"IWM": 0.25, "MATIC-USD": 0.25, "MORT": 0.25, "CPER": 0.25}, "max_deviation": 0.017, "total_turnover": 0.033911, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "IWM", "primary_trade": -0.017}} +{"id": "T6_all_20231114_0392", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "WEAT", "ICSH"], "decision_date": "2023-11-14", "context_summary": "Max weight deviation: 0.0181, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2698, target=0.2500\n XRP-USD: current=0.3150, target=0.2500\n WEAT: current=0.1997, target=0.2500\n ICSH: current=0.2155, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0181.\nRebalancing threshold: 0.0500.\n0.0181 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0472, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2698, "XRP-USD": 0.315, "WEAT": 0.1997, "ICSH": 0.2155}, "target_weights": {"XLF": 0.25, "XRP-USD": 0.25, "WEAT": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.047241, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": 0.065}} +{"id": "T6_all_20240509_0394", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "DOT-USD", "HAUZ", "SOYB"], "decision_date": "2024-05-09", "context_summary": "Max weight deviation: 0.0333, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.3150, target=0.2500\n DOT-USD: current=0.2385, target=0.2500\n HAUZ: current=0.2166, target=0.2500\n SOYB: current=0.2299, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLK", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0333.\nRebalancing threshold: 0.0500.\n0.0333 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0667, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.315, "DOT-USD": 0.2385, "HAUZ": 0.2166, "SOYB": 0.2299}, "target_weights": {"XLK": 0.25, "DOT-USD": 0.25, "HAUZ": 0.25, "SOYB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.066672, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XLK", "primary_trade": 0.065}} +{"id": "T6_all_20230320_0395", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "SOL-USD", "UNG", "CSHI"], "decision_date": "2023-03-20", "context_summary": "Max weight deviation: 0.0162, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2338, target=0.2500\n SOL-USD: current=0.2634, target=0.2500\n UNG: current=0.2652, target=0.2500\n CSHI: current=0.2375, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0162.\nRebalancing threshold: 0.0500.\n0.0162 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0573, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2338, "SOL-USD": 0.2634, "UNG": 0.2652, "CSHI": 0.2375}, "target_weights": {"XLE": 0.25, "SOL-USD": 0.25, "UNG": 0.25, "CSHI": 0.25}, "max_deviation": 0.0162, "total_turnover": 0.05725, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XLE", "primary_trade": -0.0162}} +{"id": "T6_all_20240607_0397", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "HAUZ", "ICSH"], "decision_date": "2024-06-07", "context_summary": "Max weight deviation: 0.0301, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2402, target=0.2500\n ADA-USD: current=0.2562, target=0.2500\n HAUZ: current=0.2801, target=0.2500\n ICSH: current=0.2236, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0301.\nRebalancing threshold: 0.0500.\n0.0301 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0725, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2402, "ADA-USD": 0.2562, "HAUZ": 0.2801, "ICSH": 0.2236}, "target_weights": {"XLE": 0.25, "ADA-USD": 0.25, "HAUZ": 0.25, "ICSH": 0.25}, "max_deviation": 0.0301, "total_turnover": 0.072546, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "HAUZ", "primary_trade": 0.0301}} +{"id": "T6_all_20240408_0399", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "VNQ", "PPLT"], "decision_date": "2024-04-08", "context_summary": "Max weight deviation: 0.0314, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2739, target=0.2500\n BTC-USD: current=0.2576, target=0.2500\n VNQ: current=0.2186, target=0.2500\n PPLT: current=0.2500, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0314.\nRebalancing threshold: 0.0500.\n0.0314 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0629, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2739, "BTC-USD": 0.2576, "VNQ": 0.2186, "PPLT": 0.25}, "target_weights": {"ACWI": 0.25, "BTC-USD": 0.25, "VNQ": 0.25, "PPLT": 0.25}, "max_deviation": 0.0314, "total_turnover": 0.062851, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "VNQ", "primary_trade": -0.0314}} +{"id": "T6_all_20230914_0400", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ETH-USD", "SGOV", "HAUZ"], "decision_date": "2023-09-14", "context_summary": "Max weight deviation: 0.0184, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2832, target=0.2500\n ETH-USD: current=0.2482, target=0.2500\n SGOV: current=0.1850, target=0.2500\n HAUZ: current=0.2836, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0184.\nRebalancing threshold: 0.0500.\n0.0184 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0379, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2832, "ETH-USD": 0.2482, "SGOV": 0.185, "HAUZ": 0.2836}, "target_weights": {"XLK": 0.25, "ETH-USD": 0.25, "SGOV": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037866, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": -0.065}} +{"id": "T6_all_20230301_0401", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "CSHI", "TLT"], "decision_date": "2023-03-01", "context_summary": "Max weight deviation: 0.0212, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2537, target=0.2500\n AVAX-USD: current=0.2712, target=0.2500\n CSHI: current=0.2379, target=0.2500\n TLT: current=0.2372, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0212.\nRebalancing threshold: 0.0500.\n0.0212 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0499, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2537, "AVAX-USD": 0.2712, "CSHI": 0.2379, "TLT": 0.2372}, "target_weights": {"EFA": 0.25, "AVAX-USD": 0.25, "CSHI": 0.25, "TLT": 0.25}, "max_deviation": 0.0212, "total_turnover": 0.049851, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": 0.0212}} +{"id": "T6_all_20230131_0402", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "SGOV", "UNG"], "decision_date": "2023-01-31", "context_summary": "Max weight deviation: 0.0075, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2316, target=0.2500\n BTC-USD: current=0.1848, target=0.2500\n SGOV: current=0.2714, target=0.2500\n UNG: current=0.3121, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0652 of BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0075.\nRebalancing threshold: 0.0500.\n0.0075 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0193, transaction cost = 0.000019 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2316, "BTC-USD": 0.1848, "SGOV": 0.2714, "UNG": 0.3121}, "target_weights": {"XLE": 0.25, "BTC-USD": 0.25, "SGOV": 0.25, "UNG": 0.25}, "max_deviation": 0.06516, "total_turnover": 0.019266, "transaction_cost": 1.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.0652}} +{"id": "T6_all_20230918_0403", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "BIL", "INDS"], "decision_date": "2023-09-18", "context_summary": "Max weight deviation: 0.0337, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2360, target=0.2500\n SOL-USD: current=0.2837, target=0.2500\n BIL: current=0.2375, target=0.2500\n INDS: current=0.2427, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0337.\nRebalancing threshold: 0.0500.\n0.0337 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0674, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.236, "SOL-USD": 0.2837, "BIL": 0.2375, "INDS": 0.2427}, "target_weights": {"QUAL": 0.25, "SOL-USD": 0.25, "BIL": 0.25, "INDS": 0.25}, "max_deviation": 0.0337, "total_turnover": 0.067439, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": 0.0337}} +{"id": "T6_all_20240711_0404", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "LINK-USD", "EMB", "XHB"], "decision_date": "2024-07-11", "context_summary": "Max weight deviation: 0.0445, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2032, target=0.2500\n LINK-USD: current=0.2817, target=0.2500\n EMB: current=0.3150, target=0.2500\n XHB: current=0.2002, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of EMB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0445.\nRebalancing threshold: 0.0500.\n0.0445 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1323, transaction cost = 0.000132 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2032, "LINK-USD": 0.2817, "EMB": 0.315, "XHB": 0.2002}, "target_weights": {"EEM": 0.25, "LINK-USD": 0.25, "EMB": 0.25, "XHB": 0.25}, "max_deviation": 0.064954, "total_turnover": 0.132341, "transaction_cost": 0.000132, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "EMB", "primary_trade": 0.065}} +{"id": "T6_all_20241115_0406", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XRP-USD", "ITB", "DBA"], "decision_date": "2024-11-15", "context_summary": "Max weight deviation: 0.0339, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.1850, target=0.2500\n XRP-USD: current=0.3119, target=0.2500\n ITB: current=0.2492, target=0.2500\n DBA: current=0.2538, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of MTUM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0339.\nRebalancing threshold: 0.0500.\n0.0339 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0686, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.185, "XRP-USD": 0.3119, "ITB": 0.2492, "DBA": 0.2538}, "target_weights": {"MTUM": 0.25, "XRP-USD": 0.25, "ITB": 0.25, "DBA": 0.25}, "max_deviation": 0.065, "total_turnover": 0.068635, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "MTUM", "primary_trade": -0.065}} +{"id": "T6_all_20230323_0407", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ADA-USD", "IYR", "UNG"], "decision_date": "2023-03-23", "context_summary": "Max weight deviation: 0.0110, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2562, target=0.2500\n ADA-USD: current=0.2601, target=0.2500\n IYR: current=0.2390, target=0.2500\n UNG: current=0.2446, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0110.\nRebalancing threshold: 0.0500.\n0.0110 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0327, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2562, "ADA-USD": 0.2601, "IYR": 0.239, "UNG": 0.2446}, "target_weights": {"XLF": 0.25, "ADA-USD": 0.25, "IYR": 0.25, "UNG": 0.25}, "max_deviation": 0.011, "total_turnover": 0.032688, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IYR", "primary_trade": -0.011}} +{"id": "T6_all_20240419_0409", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BNB-USD", "SGOV", "UNG"], "decision_date": "2024-04-19", "context_summary": "Max weight deviation: 0.0298, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.2715, target=0.2500\n BNB-USD: current=0.2561, target=0.2500\n SGOV: current=0.2522, target=0.2500\n UNG: current=0.2202, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0298.\nRebalancing threshold: 0.0500.\n0.0298 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0595, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2715, "BNB-USD": 0.2561, "SGOV": 0.2522, "UNG": 0.2202}, "target_weights": {"VEA": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "UNG": 0.25}, "max_deviation": 0.0298, "total_turnover": 0.059505, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "UNG", "primary_trade": -0.0298}} +{"id": "T6_all_20230221_0411", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "IYR", "SGOV"], "decision_date": "2023-02-21", "context_summary": "Max weight deviation: 0.0362, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2403, target=0.2500\n LINK-USD: current=0.2138, target=0.2500\n IYR: current=0.2774, target=0.2500\n SGOV: current=0.2685, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0362.\nRebalancing threshold: 0.0500.\n0.0362 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0918, transaction cost = 0.000092 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2403, "LINK-USD": 0.2138, "IYR": 0.2774, "SGOV": 0.2685}, "target_weights": {"EWJ": 0.25, "LINK-USD": 0.25, "IYR": 0.25, "SGOV": 0.25}, "max_deviation": 0.0362, "total_turnover": 0.091841, "transaction_cost": 9.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.0362}} +{"id": "T6_all_20240426_0412", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ADA-USD", "REZ", "DBC"], "decision_date": "2024-04-26", "context_summary": "Max weight deviation: 0.0341, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2229, target=0.2500\n ADA-USD: current=0.2031, target=0.2500\n REZ: current=0.3150, target=0.2500\n DBC: current=0.2590, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of REZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0341.\nRebalancing threshold: 0.0500.\n0.0341 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0776, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2229, "ADA-USD": 0.2031, "REZ": 0.315, "DBC": 0.259}, "target_weights": {"IWM": 0.25, "ADA-USD": 0.25, "REZ": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.077572, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "REZ", "primary_trade": 0.065}} +{"id": "T6_all_20230712_0413", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "SGOV", "VCIT"], "decision_date": "2023-07-12", "context_summary": "Max weight deviation: 0.0186, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2523, target=0.2500\n SOL-USD: current=0.2686, target=0.2500\n SGOV: current=0.2409, target=0.2500\n VCIT: current=0.2382, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0186.\nRebalancing threshold: 0.0500.\n0.0186 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0417, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2523, "SOL-USD": 0.2686, "SGOV": 0.2409, "VCIT": 0.2382}, "target_weights": {"IVV": 0.25, "SOL-USD": 0.25, "SGOV": 0.25, "VCIT": 0.25}, "max_deviation": 0.0186, "total_turnover": 0.04175, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": 0.0186}} +{"id": "T6_all_20240228_0415", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "MATIC-USD", "DBC", "SHV"], "decision_date": "2024-02-28", "context_summary": "Max weight deviation: 0.0163, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.2443, target=0.2500\n MATIC-USD: current=0.2429, target=0.2500\n DBC: current=0.2465, target=0.2500\n SHV: current=0.2663, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0163.\nRebalancing threshold: 0.0500.\n0.0163 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0326, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2443, "MATIC-USD": 0.2429, "DBC": 0.2465, "SHV": 0.2663}, "target_weights": {"XLB": 0.25, "MATIC-USD": 0.25, "DBC": 0.25, "SHV": 0.25}, "max_deviation": 0.0163, "total_turnover": 0.032624, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SHV", "primary_trade": 0.0163}} +{"id": "T6_all_20230817_0417", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "TIP", "MORT"], "decision_date": "2023-08-17", "context_summary": "Max weight deviation: 0.0329, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2829, target=0.2500\n ETH-USD: current=0.2478, target=0.2500\n TIP: current=0.2310, target=0.2500\n MORT: current=0.2383, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0329.\nRebalancing threshold: 0.0500.\n0.0329 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0657, transaction cost = 0.000066 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2829, "ETH-USD": 0.2478, "TIP": 0.231, "MORT": 0.2383}, "target_weights": {"XLU": 0.25, "ETH-USD": 0.25, "TIP": 0.25, "MORT": 0.25}, "max_deviation": 0.0329, "total_turnover": 0.065712, "transaction_cost": 6.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLU", "primary_trade": 0.0329}} +{"id": "T6_all_20231110_0420", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "VNQ", "IGOV"], "decision_date": "2023-11-10", "context_summary": "Max weight deviation: 0.0335, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.3039, target=0.2500\n ADA-USD: current=0.2417, target=0.2500\n VNQ: current=0.2694, target=0.2500\n IGOV: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of IGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0335.\nRebalancing threshold: 0.0500.\n0.0335 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0757, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.3039, "ADA-USD": 0.2417, "VNQ": 0.2694, "IGOV": 0.185}, "target_weights": {"IVV": 0.25, "ADA-USD": 0.25, "VNQ": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.075666, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IGOV", "primary_trade": -0.065}} +{"id": "T6_all_20240516_0421", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "DBB", "BIL"], "decision_date": "2024-05-16", "context_summary": "Max weight deviation: 0.0260, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2713, target=0.2500\n MATIC-USD: current=0.2240, target=0.2500\n DBB: current=0.2756, target=0.2500\n BIL: current=0.2291, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0260.\nRebalancing threshold: 0.0500.\n0.0260 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0938, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2713, "MATIC-USD": 0.224, "DBB": 0.2756, "BIL": 0.2291}, "target_weights": {"VTI": 0.25, "MATIC-USD": 0.25, "DBB": 0.25, "BIL": 0.25}, "max_deviation": 0.026, "total_turnover": 0.093848, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "MATIC-USD", "primary_trade": -0.026}} +{"id": "T6_all_20240422_0422", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "BIL", "INDS"], "decision_date": "2024-04-22", "context_summary": "Max weight deviation: 0.0130, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2010, target=0.2500\n BTC-USD: current=0.2765, target=0.2500\n BIL: current=0.3150, target=0.2500\n INDS: current=0.2075, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0130.\nRebalancing threshold: 0.0500.\n0.0130 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0364, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.201, "BTC-USD": 0.2765, "BIL": 0.315, "INDS": 0.2075}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "INDS": 0.25}, "max_deviation": 0.065, "total_turnover": 0.036448, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "BIL", "primary_trade": 0.065}} +{"id": "T6_all_20240603_0424", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BNB-USD", "BIL", "SHY"], "decision_date": "2024-06-03", "context_summary": "Max weight deviation: 0.0132, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2431, target=0.2500\n BNB-USD: current=0.1850, target=0.2500\n BIL: current=0.2658, target=0.2500\n SHY: current=0.3061, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of BNB-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0132.\nRebalancing threshold: 0.0500.\n0.0132 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0292, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2431, "BNB-USD": 0.185, "BIL": 0.2658, "SHY": 0.3061}, "target_weights": {"EFA": 0.25, "BNB-USD": 0.25, "BIL": 0.25, "SHY": 0.25}, "max_deviation": 0.065, "total_turnover": 0.029166, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "BNB-USD", "primary_trade": -0.065}} +{"id": "T6_all_20240828_0425", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "DOT-USD", "MORT", "DBB"], "decision_date": "2024-08-28", "context_summary": "Max weight deviation: 0.0120, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2489, target=0.2500\n DOT-USD: current=0.2620, target=0.2500\n MORT: current=0.2382, target=0.2500\n DBB: current=0.2509, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0120.\nRebalancing threshold: 0.0500.\n0.0120 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0258, transaction cost = 0.000026 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2489, "DOT-USD": 0.262, "MORT": 0.2382, "DBB": 0.2509}, "target_weights": {"QUAL": 0.25, "DOT-USD": 0.25, "MORT": 0.25, "DBB": 0.25}, "max_deviation": 0.012, "total_turnover": 0.025831, "transaction_cost": 2.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "DOT-USD", "primary_trade": 0.012}} +{"id": "T6_all_20240410_0426", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "SOL-USD", "LQD", "SCHH"], "decision_date": "2024-04-10", "context_summary": "Max weight deviation: 0.0165, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.1952, target=0.2500\n SOL-USD: current=0.3150, target=0.2500\n LQD: current=0.2480, target=0.2500\n SCHH: current=0.2417, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SOL-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0165.\nRebalancing threshold: 0.0500.\n0.0165 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0329, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.1952, "SOL-USD": 0.315, "LQD": 0.248, "SCHH": 0.2417}, "target_weights": {"EWJ": 0.25, "SOL-USD": 0.25, "LQD": 0.25, "SCHH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.032932, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SOL-USD", "primary_trade": 0.065}} +{"id": "T6_all_20240412_0427", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "MATIC-USD", "SCHP", "DBB"], "decision_date": "2024-04-12", "context_summary": "Max weight deviation: 0.0289, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.2211, target=0.2500\n MATIC-USD: current=0.2413, target=0.2500\n SCHP: current=0.2756, target=0.2500\n DBB: current=0.2620, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0289.\nRebalancing threshold: 0.0500.\n0.0289 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0752, transaction cost = 0.000075 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2211, "MATIC-USD": 0.2413, "SCHP": 0.2756, "DBB": 0.262}, "target_weights": {"VEA": 0.25, "MATIC-USD": 0.25, "SCHP": 0.25, "DBB": 0.25}, "max_deviation": 0.0289, "total_turnover": 0.075238, "transaction_cost": 7.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "VEA", "primary_trade": -0.0289}} +{"id": "T6_all_20240806_0429", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "SOL-USD", "SCHH", "CPER"], "decision_date": "2024-08-06", "context_summary": "Max weight deviation: 0.0226, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2516, target=0.2500\n SOL-USD: current=0.2311, target=0.2500\n SCHH: current=0.2726, target=0.2500\n CPER: current=0.2447, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0226.\nRebalancing threshold: 0.0500.\n0.0226 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0484, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2516, "SOL-USD": 0.2311, "SCHH": 0.2726, "CPER": 0.2447}, "target_weights": {"XLU": 0.25, "SOL-USD": 0.25, "SCHH": 0.25, "CPER": 0.25}, "max_deviation": 0.0226, "total_turnover": 0.048396, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SCHH", "primary_trade": 0.0226}} +{"id": "T6_all_20240905_0430", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "BTC-USD", "VNQ", "BIL"], "decision_date": "2024-09-05", "context_summary": "Max weight deviation: 0.0315, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.3150, target=0.2500\n BTC-USD: current=0.2611, target=0.2500\n VNQ: current=0.2246, target=0.2500\n BIL: current=0.1992, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SPY", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0315.\nRebalancing threshold: 0.0500.\n0.0315 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0737, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.315, "BTC-USD": 0.2611, "VNQ": 0.2246, "BIL": 0.1992}, "target_weights": {"SPY": 0.25, "BTC-USD": 0.25, "VNQ": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.073692, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SPY", "primary_trade": 0.065}} +{"id": "T6_all_20240110_0432", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XRP-USD", "REZ", "ICSH"], "decision_date": "2024-01-10", "context_summary": "Max weight deviation: 0.0256, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2294, target=0.2500\n XRP-USD: current=0.1850, target=0.2500\n REZ: current=0.2777, target=0.2500\n ICSH: current=0.3079, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0256.\nRebalancing threshold: 0.0500.\n0.0256 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0675, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2294, "XRP-USD": 0.185, "REZ": 0.2777, "ICSH": 0.3079}, "target_weights": {"XLY": 0.25, "XRP-USD": 0.25, "REZ": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.067495, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.065}} +{"id": "T6_all_20241231_0433", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "MORT", "DBB"], "decision_date": "2024-12-31", "context_summary": "Max weight deviation: 0.0210, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2301, target=0.2500\n ETH-USD: current=0.2642, target=0.2500\n MORT: current=0.2348, target=0.2500\n DBB: current=0.2710, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0210.\nRebalancing threshold: 0.0500.\n0.0210 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0703, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2301, "ETH-USD": 0.2642, "MORT": 0.2348, "DBB": 0.271}, "target_weights": {"XLRE": 0.25, "ETH-USD": 0.25, "MORT": 0.25, "DBB": 0.25}, "max_deviation": 0.021, "total_turnover": 0.070318, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "DBB", "primary_trade": 0.021}} +{"id": "T6_all_20240930_0434", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "SOL-USD", "BIL", "CPER"], "decision_date": "2024-09-30", "context_summary": "Max weight deviation: 0.0354, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.3150, target=0.2500\n SOL-USD: current=0.2056, target=0.2500\n BIL: current=0.2305, target=0.2500\n CPER: current=0.2489, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0354.\nRebalancing threshold: 0.0500.\n0.0354 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0708, transaction cost = 0.000071 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.315, "SOL-USD": 0.2056, "BIL": 0.2305, "CPER": 0.2489}, "target_weights": {"XLP": 0.25, "SOL-USD": 0.25, "BIL": 0.25, "CPER": 0.25}, "max_deviation": 0.065, "total_turnover": 0.070813, "transaction_cost": 7.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XLP", "primary_trade": 0.065}} +{"id": "T6_all_20230801_0435", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "BIL", "JNK"], "decision_date": "2023-08-01", "context_summary": "Max weight deviation: 0.0224, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2527, target=0.2500\n XRP-USD: current=0.2519, target=0.2500\n BIL: current=0.2276, target=0.2500\n JNK: current=0.2678, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0224.\nRebalancing threshold: 0.0500.\n0.0224 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0447, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2527, "XRP-USD": 0.2519, "BIL": 0.2276, "JNK": 0.2678}, "target_weights": {"XLP": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "JNK": 0.25}, "max_deviation": 0.0224, "total_turnover": 0.044743, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.0224}} +{"id": "T6_all_20230428_0436", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BNB-USD", "ITB", "PPLT"], "decision_date": "2023-04-28", "context_summary": "Max weight deviation: 0.0270, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2478, target=0.2500\n BNB-USD: current=0.3150, target=0.2500\n ITB: current=0.2483, target=0.2500\n PPLT: current=0.1889, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of BNB-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0270.\nRebalancing threshold: 0.0500.\n0.0270 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0540, transaction cost = 0.000054 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2478, "BNB-USD": 0.315, "ITB": 0.2483, "PPLT": 0.1889}, "target_weights": {"^VIX": 0.25, "BNB-USD": 0.25, "ITB": 0.25, "PPLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.05399, "transaction_cost": 5.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.065}} +{"id": "T6_all_20230515_0438", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "AVAX-USD", "ICSH", "TLT"], "decision_date": "2023-05-15", "context_summary": "Max weight deviation: 0.0374, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2278, target=0.2500\n AVAX-USD: current=0.2161, target=0.2500\n ICSH: current=0.3150, target=0.2500\n TLT: current=0.2411, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of ICSH", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0374.\nRebalancing threshold: 0.0500.\n0.0374 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0748, transaction cost = 0.000075 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2278, "AVAX-USD": 0.2161, "ICSH": 0.315, "TLT": 0.2411}, "target_weights": {"USMV": 0.25, "AVAX-USD": 0.25, "ICSH": 0.25, "TLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.074755, "transaction_cost": 7.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": 0.065}} +{"id": "T6_all_20230214_0439", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "GLD", "CSHI"], "decision_date": "2023-02-14", "context_summary": "Max weight deviation: 0.0171, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2450, target=0.2500\n DOT-USD: current=0.2329, target=0.2500\n GLD: current=0.2561, target=0.2500\n CSHI: current=0.2661, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0171.\nRebalancing threshold: 0.0500.\n0.0171 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0443, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.245, "DOT-USD": 0.2329, "GLD": 0.2561, "CSHI": 0.2661}, "target_weights": {"XLY": 0.25, "DOT-USD": 0.25, "GLD": 0.25, "CSHI": 0.25}, "max_deviation": 0.0171, "total_turnover": 0.044323, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DOT-USD", "primary_trade": -0.0171}} +{"id": "T6_all_20240220_0440", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "WEAT", "CSHI"], "decision_date": "2024-02-20", "context_summary": "Max weight deviation: 0.0139, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.3028, target=0.2500\n XRP-USD: current=0.3150, target=0.2500\n WEAT: current=0.1972, target=0.2500\n CSHI: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0139.\nRebalancing threshold: 0.0500.\n0.0139 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0504, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3028, "XRP-USD": 0.315, "WEAT": 0.1972, "CSHI": 0.185}, "target_weights": {"XLRE": 0.25, "XRP-USD": 0.25, "WEAT": 0.25, "CSHI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.050404, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XRP-USD", "primary_trade": 0.065}} +{"id": "T6_all_20241125_0441", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "VNQ", "SOYB"], "decision_date": "2024-11-25", "context_summary": "Max weight deviation: 0.0256, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2625, target=0.2500\n AVAX-USD: current=0.2343, target=0.2500\n VNQ: current=0.2276, target=0.2500\n SOYB: current=0.2756, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0256.\nRebalancing threshold: 0.0500.\n0.0256 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0761, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2625, "AVAX-USD": 0.2343, "VNQ": 0.2276, "SOYB": 0.2756}, "target_weights": {"EFA": 0.25, "AVAX-USD": 0.25, "VNQ": 0.25, "SOYB": 0.25}, "max_deviation": 0.0256, "total_turnover": 0.076146, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "SOYB", "primary_trade": 0.0256}} +{"id": "T6_all_20230511_0442", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XRP-USD", "XHB", "ICSH"], "decision_date": "2023-05-11", "context_summary": "Max weight deviation: 0.0133, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.3126, target=0.2500\n XRP-USD: current=0.2871, target=0.2500\n XHB: current=0.1850, target=0.2500\n ICSH: current=0.2153, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XHB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0133.\nRebalancing threshold: 0.0500.\n0.0133 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0408, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.3126, "XRP-USD": 0.2871, "XHB": 0.185, "ICSH": 0.2153}, "target_weights": {"MTUM": 0.25, "XRP-USD": 0.25, "XHB": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.040763, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XHB", "primary_trade": -0.065}} +{"id": "T6_all_20231229_0444", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "ICSH", "DBC"], "decision_date": "2023-12-29", "context_summary": "Max weight deviation: 0.0334, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2984, target=0.2500\n XRP-USD: current=0.2854, target=0.2500\n ICSH: current=0.2313, target=0.2500\n DBC: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of DBC", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0334.\nRebalancing threshold: 0.0500.\n0.0334 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0861, transaction cost = 0.000086 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2984, "XRP-USD": 0.2854, "ICSH": 0.2313, "DBC": 0.185}, "target_weights": {"VLUE": 0.25, "XRP-USD": 0.25, "ICSH": 0.25, "DBC": 0.25}, "max_deviation": 0.065036, "total_turnover": 0.086053, "transaction_cost": 8.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBC", "primary_trade": -0.065}} +{"id": "T6_all_20240304_0445", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "SGOV", "SCHH"], "decision_date": "2024-03-04", "context_summary": "Max weight deviation: 0.0224, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2276, target=0.2500\n LINK-USD: current=0.2443, target=0.2500\n SGOV: current=0.2598, target=0.2500\n SCHH: current=0.2683, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0224.\nRebalancing threshold: 0.0500.\n0.0224 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0563, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2276, "LINK-USD": 0.2443, "SGOV": 0.2598, "SCHH": 0.2683}, "target_weights": {"XLE": 0.25, "LINK-USD": 0.25, "SGOV": 0.25, "SCHH": 0.25}, "max_deviation": 0.0224, "total_turnover": 0.056259, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XLE", "primary_trade": -0.0224}} +{"id": "T6_all_20240708_0446", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "VNQ", "DBC"], "decision_date": "2024-07-08", "context_summary": "Max weight deviation: 0.0161, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.3150, target=0.2500\n DOT-USD: current=0.2472, target=0.2500\n VNQ: current=0.1915, target=0.2500\n DBC: current=0.2464, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of XLP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0161.\nRebalancing threshold: 0.0500.\n0.0161 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0323, transaction cost = 0.000032 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.315, "DOT-USD": 0.2472, "VNQ": 0.1915, "DBC": 0.2464}, "target_weights": {"XLP": 0.25, "DOT-USD": 0.25, "VNQ": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.032263, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XLP", "primary_trade": 0.065}} +{"id": "T6_all_20240103_0448", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "IYR", "HYG"], "decision_date": "2024-01-03", "context_summary": "Max weight deviation: 0.0253, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2739, target=0.2500\n LINK-USD: current=0.2891, target=0.2500\n IYR: current=0.2521, target=0.2500\n HYG: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of HYG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0253.\nRebalancing threshold: 0.0500.\n0.0253 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0506, transaction cost = 0.000051 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2739, "LINK-USD": 0.2891, "IYR": 0.2521, "HYG": 0.185}, "target_weights": {"XLY": 0.25, "LINK-USD": 0.25, "IYR": 0.25, "HYG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.050554, "transaction_cost": 5.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": -0.065}} +{"id": "T6_all_20230426_0449", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "CORN", "MORT"], "decision_date": "2023-04-26", "context_summary": "Max weight deviation: 0.0173, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2348, target=0.2500\n ADA-USD: current=0.2434, target=0.2500\n CORN: current=0.2673, target=0.2500\n MORT: current=0.2546, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0173.\nRebalancing threshold: 0.0500.\n0.0173 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0437, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2348, "ADA-USD": 0.2434, "CORN": 0.2673, "MORT": 0.2546}, "target_weights": {"MTUM": 0.25, "ADA-USD": 0.25, "CORN": 0.25, "MORT": 0.25}, "max_deviation": 0.0173, "total_turnover": 0.043745, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CORN", "primary_trade": 0.0173}} +{"id": "T6_all_20230420_0450", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "BIL", "CORN"], "decision_date": "2023-04-20", "context_summary": "Max weight deviation: 0.0290, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2795, target=0.2500\n ETH-USD: current=0.1850, target=0.2500\n BIL: current=0.2441, target=0.2500\n CORN: current=0.2914, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0290.\nRebalancing threshold: 0.0500.\n0.0290 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0632, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2795, "ETH-USD": 0.185, "BIL": 0.2441, "CORN": 0.2914}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "BIL": 0.25, "CORN": 0.25}, "max_deviation": 0.065041, "total_turnover": 0.063231, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.065}} +{"id": "T6_all_20230330_0452", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "LINK-USD", "IGOV", "BIL"], "decision_date": "2023-03-30", "context_summary": "Max weight deviation: 0.0208, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2091, target=0.2500\n LINK-USD: current=0.3150, target=0.2500\n IGOV: current=0.2047, target=0.2500\n BIL: current=0.2712, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of LINK-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0208.\nRebalancing threshold: 0.0500.\n0.0208 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0552, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2091, "LINK-USD": 0.315, "IGOV": 0.2047, "BIL": 0.2712}, "target_weights": {"ACWI": 0.25, "LINK-USD": 0.25, "IGOV": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.055228, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": 0.065}} +{"id": "T6_all_20240902_0454", "template": "T6", "complexity": 3, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "DOT-USD", "UNG", "IGOV"], "decision_date": "2024-09-02", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2619, target=0.2500\n DOT-USD: current=0.2097, target=0.2500\n UNG: current=0.3150, target=0.2500\n IGOV: current=0.2134, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of UNG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0213.\nRebalancing threshold: 0.0500.\n0.0213 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0505, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2619, "DOT-USD": 0.2097, "UNG": 0.315, "IGOV": 0.2134}, "target_weights": {"EFA": 0.25, "DOT-USD": 0.25, "UNG": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.050459, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "UNG", "primary_trade": 0.065}} +{"id": "T6_all_20230210_0455", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "MATIC-USD", "CSHI", "VNQI"], "decision_date": "2023-02-10", "context_summary": "Max weight deviation: 0.0270, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2273, target=0.2500\n MATIC-USD: current=0.2359, target=0.2500\n CSHI: current=0.2770, target=0.2500\n VNQI: current=0.2598, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0270.\nRebalancing threshold: 0.0500.\n0.0270 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0736, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2273, "MATIC-USD": 0.2359, "CSHI": 0.277, "VNQI": 0.2598}, "target_weights": {"MTUM": 0.25, "MATIC-USD": 0.25, "CSHI": 0.25, "VNQI": 0.25}, "max_deviation": 0.027, "total_turnover": 0.073585, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CSHI", "primary_trade": 0.027}} +{"id": "T6_all_20230508_0456", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "BIL", "MORT"], "decision_date": "2023-05-08", "context_summary": "Max weight deviation: 0.0072, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.1850, target=0.2500\n ADA-USD: current=0.2491, target=0.2500\n BIL: current=0.2726, target=0.2500\n MORT: current=0.2933, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of USMV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0072.\nRebalancing threshold: 0.0500.\n0.0072 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0146, transaction cost = 0.000015 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.185, "ADA-USD": 0.2491, "BIL": 0.2726, "MORT": 0.2933}, "target_weights": {"USMV": 0.25, "ADA-USD": 0.25, "BIL": 0.25, "MORT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.014563, "transaction_cost": 1.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": -0.065}} +{"id": "T6_all_20231108_0458", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "DBA", "SHV"], "decision_date": "2023-11-08", "context_summary": "Max weight deviation: 0.0124, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2715, target=0.2500\n ETH-USD: current=0.2065, target=0.2500\n DBA: current=0.2070, target=0.2500\n SHV: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SHV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0124.\nRebalancing threshold: 0.0500.\n0.0124 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0330, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2715, "ETH-USD": 0.2065, "DBA": 0.207, "SHV": 0.315}, "target_weights": {"ACWI": 0.25, "ETH-USD": 0.25, "DBA": 0.25, "SHV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.033021, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SHV", "primary_trade": 0.065}} +{"id": "T6_all_20241112_0459", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "CSHI", "LQD"], "decision_date": "2024-11-12", "context_summary": "Max weight deviation: 0.0312, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2415, target=0.2500\n ADA-USD: current=0.2431, target=0.2500\n CSHI: current=0.2341, target=0.2500\n LQD: current=0.2812, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0312.\nRebalancing threshold: 0.0500.\n0.0312 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0625, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2415, "ADA-USD": 0.2431, "CSHI": 0.2341, "LQD": 0.2812}, "target_weights": {"XLE": 0.25, "ADA-USD": 0.25, "CSHI": 0.25, "LQD": 0.25}, "max_deviation": 0.0312, "total_turnover": 0.062476, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "LQD", "primary_trade": 0.0312}} +{"id": "T6_all_20240926_0460", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "MATIC-USD", "BNO", "SCHP"], "decision_date": "2024-09-26", "context_summary": "Max weight deviation: 0.0317, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.3045, target=0.2500\n MATIC-USD: current=0.2937, target=0.2500\n BNO: current=0.2168, target=0.2500\n SCHP: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SCHP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0317.\nRebalancing threshold: 0.0500.\n0.0317 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0957, transaction cost = 0.000096 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.3045, "MATIC-USD": 0.2937, "BNO": 0.2168, "SCHP": 0.185}, "target_weights": {"VEA": 0.25, "MATIC-USD": 0.25, "BNO": 0.25, "SCHP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.09574, "transaction_cost": 9.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SCHP", "primary_trade": -0.065}} +{"id": "T6_all_20240618_0463", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "LINK-USD", "DBB", "HAUZ"], "decision_date": "2024-06-18", "context_summary": "Max weight deviation: 0.0174, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2484, target=0.2500\n LINK-USD: current=0.2334, target=0.2500\n DBB: current=0.2508, target=0.2500\n HAUZ: current=0.2674, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0174.\nRebalancing threshold: 0.0500.\n0.0174 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0363, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2484, "LINK-USD": 0.2334, "DBB": 0.2508, "HAUZ": 0.2674}, "target_weights": {"XLK": 0.25, "LINK-USD": 0.25, "DBB": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0174, "total_turnover": 0.036344, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "HAUZ", "primary_trade": 0.0174}} +{"id": "T6_all_20240911_0464", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "PALL", "HYG"], "decision_date": "2024-09-11", "context_summary": "Max weight deviation: 0.0175, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2530, target=0.2500\n XRP-USD: current=0.1850, target=0.2500\n PALL: current=0.2998, target=0.2500\n HYG: current=0.2623, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0175.\nRebalancing threshold: 0.0500.\n0.0175 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0349, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.253, "XRP-USD": 0.185, "PALL": 0.2998, "HYG": 0.2623}, "target_weights": {"EWJ": 0.25, "XRP-USD": 0.25, "PALL": 0.25, "HYG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.034919, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XRP-USD", "primary_trade": -0.065}} +{"id": "T6_all_20230518_0465", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "STIP", "ITB"], "decision_date": "2023-05-18", "context_summary": "Max weight deviation: 0.0349, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2343, target=0.2500\n ADA-USD: current=0.2266, target=0.2500\n STIP: current=0.2849, target=0.2500\n ITB: current=0.2542, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0349.\nRebalancing threshold: 0.0500.\n0.0349 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0782, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2343, "ADA-USD": 0.2266, "STIP": 0.2849, "ITB": 0.2542}, "target_weights": {"EWJ": 0.25, "ADA-USD": 0.25, "STIP": 0.25, "ITB": 0.25}, "max_deviation": 0.0349, "total_turnover": 0.078175, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "STIP", "primary_trade": 0.0349}} +{"id": "T6_all_20241024_0467", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "BNB-USD", "INDS", "EMB"], "decision_date": "2024-10-24", "context_summary": "Max weight deviation: 0.0121, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2379, target=0.2500\n BNB-USD: current=0.2587, target=0.2500\n INDS: current=0.2578, target=0.2500\n EMB: current=0.2456, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0121.\nRebalancing threshold: 0.0500.\n0.0121 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0330, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2379, "BNB-USD": 0.2587, "INDS": 0.2578, "EMB": 0.2456}, "target_weights": {"XLRE": 0.25, "BNB-USD": 0.25, "INDS": 0.25, "EMB": 0.25}, "max_deviation": 0.0121, "total_turnover": 0.032999, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "XLRE", "primary_trade": -0.0121}} +{"id": "T6_all_20230726_0468", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "DOT-USD", "BIL", "USO"], "decision_date": "2023-07-26", "context_summary": "Max weight deviation: 0.0289, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2239, target=0.2500\n DOT-USD: current=0.2290, target=0.2500\n BIL: current=0.3149, target=0.2500\n USO: current=0.2322, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0289.\nRebalancing threshold: 0.0500.\n0.0289 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0578, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2239, "DOT-USD": 0.229, "BIL": 0.3149, "USO": 0.2322}, "target_weights": {"XLV": 0.25, "DOT-USD": 0.25, "BIL": 0.25, "USO": 0.25}, "max_deviation": 0.064929, "total_turnover": 0.057782, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0649}} +{"id": "T6_all_20230224_0470", "template": "T6", "complexity": 3, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD", "IYR", "PDBC"], "decision_date": "2023-02-24", "context_summary": "Max weight deviation: 0.0177, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.1849, target=0.2500\n LINK-USD: current=0.2595, target=0.2500\n IYR: current=0.2591, target=0.2500\n PDBC: current=0.2965, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0651 of EFA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0177.\nRebalancing threshold: 0.0500.\n0.0177 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0355, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.1849, "LINK-USD": 0.2595, "IYR": 0.2591, "PDBC": 0.2965}, "target_weights": {"EFA": 0.25, "LINK-USD": 0.25, "IYR": 0.25, "PDBC": 0.25}, "max_deviation": 0.065068, "total_turnover": 0.035455, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "EFA", "primary_trade": -0.0651}} +{"id": "T7_all_20240626_0005", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-26", "context_summary": "Regime: bull. SPY trailing return: +4.7%, annualized vol: 10.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=509.75, end=533.60, trailing_return=+4.68%\nAnnualized volatility: 10.72%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4200, t10y3m_spread=-1.2600, breakeven_10y=2.2200, hy_oas=3.1900, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.8700, vix=12.8400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.68%\n Annualized volatility: 10.72%\n Macro: fed_funds=5.3300, vix=12.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.046782, "annualized_vol": 0.107169, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240423_0009", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-23", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 11.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=474.36, end=487.85, trailing_return=+2.84%\nAnnualized volatility: 11.94%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3500, t10y3m_spread=-0.8000, breakeven_10y=2.4100, hy_oas=3.2900, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=7.1000, vix=16.9400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.84%\n Annualized volatility: 11.94%\n Macro: fed_funds=5.3300, vix=16.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.028442, "annualized_vol": 0.119413, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240815_0016", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-15", "context_summary": "Regime: sideways. SPY trailing return: +2.9%, annualized vol: 13.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=517.47, end=532.54, trailing_return=+2.91%\nAnnualized volatility: 13.90%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1100, t10y3m_spread=-1.4900, breakeven_10y=2.0600, hy_oas=3.4600, ig_oas=1.0200, ted_spread=0.0900, mortgage_30y=6.4700, vix=16.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.91%\n Annualized volatility: 13.90%\n Macro: fed_funds=5.3300, vix=16.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.029137, "annualized_vol": 0.139032, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241212_0021", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-12", "context_summary": "Regime: bull. SPY trailing return: +8.5%, annualized vol: 10.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=549.83, end=596.77, trailing_return=+8.54%\nAnnualized volatility: 10.42%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1100, t10y3m_spread=-0.1200, breakeven_10y=2.3000, hy_oas=2.6600, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.6900, vix=13.5800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.54%\n Annualized volatility: 10.42%\n Macro: fed_funds=4.5800, vix=13.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.085364, "annualized_vol": 0.104205, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240610_0024", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-10", "context_summary": "Regime: sideways. SPY trailing return: +4.0%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=501.16, end=521.32, trailing_return=+4.02%\nAnnualized volatility: 10.95%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4400, t10y3m_spread=-1.0900, breakeven_10y=2.3000, hy_oas=3.1500, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.9900, vix=12.2200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.02%\n Annualized volatility: 10.95%\n Macro: fed_funds=5.3300, vix=12.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.040236, "annualized_vol": 0.109455, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241225_0027", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-25", "context_summary": "Regime: sideways. SPY trailing return: +6.1%, annualized vol: 12.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=558.61, end=592.70, trailing_return=+6.10%\nAnnualized volatility: 11.98%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.3000, t10y3m_spread=0.1900, breakeven_10y=2.3500, hy_oas=2.8600, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=14.2700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.10%\n Annualized volatility: 11.98%\n Macro: fed_funds=4.3300, vix=14.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.061031, "annualized_vol": 0.119761, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240620_0032", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-20", "context_summary": "Regime: bull. SPY trailing return: +5.5%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=507.42, end=535.46, trailing_return=+5.53%\nAnnualized volatility: 10.79%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4700, t10y3m_spread=-1.2800, breakeven_10y=2.2100, hy_oas=3.2400, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.3000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.53%\n Annualized volatility: 10.79%\n Macro: fed_funds=5.3300, vix=12.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.055255, "annualized_vol": 0.107873, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240503_0034", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-03", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 11.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=484.76, end=493.03, trailing_return=+1.71%\nAnnualized volatility: 11.89%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.2900, t10y3m_spread=-0.8800, breakeven_10y=2.3700, hy_oas=3.1600, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=7.2200, vix=14.6800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.71%\n Annualized volatility: 11.89%\n Macro: fed_funds=5.3300, vix=14.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017063, "annualized_vol": 0.118935, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240411_0038", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-11", "context_summary": "Regime: sideways. SPY trailing return: +8.6%, annualized vol: 11.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=462.21, end=501.91, trailing_return=+8.59%\nAnnualized volatility: 11.23%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4200, t10y3m_spread=-0.9000, breakeven_10y=2.4000, hy_oas=3.1000, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.8200, vix=15.8000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.59%\n Annualized volatility: 11.23%\n Macro: fed_funds=5.3300, vix=15.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.085881, "annualized_vol": 0.112343, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240619_0042", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-19", "context_summary": "Regime: bull. SPY trailing return: +5.5%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=507.42, end=535.46, trailing_return=+5.53%\nAnnualized volatility: 10.79%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4700, t10y3m_spread=-1.2800, breakeven_10y=2.2100, hy_oas=3.2400, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.3000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.53%\n Annualized volatility: 10.79%\n Macro: fed_funds=5.3300, vix=12.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.055255, "annualized_vol": 0.107873, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241129_0050", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-29", "context_summary": "Regime: bull. SPY trailing return: +9.3%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=538.28, end=588.29, trailing_return=+9.29%\nAnnualized volatility: 11.28%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0600, t10y3m_spread=-0.3500, breakeven_10y=2.2600, hy_oas=2.6900, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.8100, vix=14.1000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.29%\n Annualized volatility: 11.28%\n Macro: fed_funds=4.5800, vix=14.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.092896, "annualized_vol": 0.112849, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240617_0054", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-17", "context_summary": "Regime: sideways. SPY trailing return: +3.9%, annualized vol: 10.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=509.79, end=529.88, trailing_return=+3.94%\nAnnualized volatility: 10.71%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4700, t10y3m_spread=-1.3100, breakeven_10y=2.1700, hy_oas=3.2900, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.6600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.94%\n Annualized volatility: 10.71%\n Macro: fed_funds=5.3300, vix=12.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.03941, "annualized_vol": 0.107063, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241111_0059", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-11", "context_summary": "Regime: sideways. SPY trailing return: +8.2%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=542.89, end=587.66, trailing_return=+8.25%\nAnnualized volatility: 12.25%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0400, t10y3m_spread=-0.3300, breakeven_10y=2.3500, hy_oas=2.6600, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.7900, vix=14.9400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.25%\n Annualized volatility: 12.25%\n Macro: fed_funds=4.5800, vix=14.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.082472, "annualized_vol": 0.122476, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240305_0061", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-05", "context_summary": "Regime: sideways. SPY trailing return: +8.1%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=498.58, trailing_return=+8.11%\nAnnualized volatility: 11.46%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.2600, breakeven_10y=2.3400, hy_oas=3.2600, ig_oas=1.0000, ted_spread=0.0900, mortgage_30y=6.9400, vix=13.4900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.11%\n Annualized volatility: 11.46%\n Macro: fed_funds=5.3300, vix=13.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.081075, "annualized_vol": 0.114598, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241015_0064", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-15", "context_summary": "Regime: sideways. SPY trailing return: +5.7%, annualized vol: 15.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=543.22, end=574.03, trailing_return=+5.67%\nAnnualized volatility: 15.72%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1300, t10y3m_spread=-0.6500, breakeven_10y=2.3300, hy_oas=2.9700, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.3200, vix=19.7000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.67%\n Annualized volatility: 15.72%\n Macro: fed_funds=4.8300, vix=19.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.056724, "annualized_vol": 0.157234, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240701_0066", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-01", "context_summary": "Regime: sideways. SPY trailing return: +6.4%, annualized vol: 10.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=500.88, end=533.00, trailing_return=+6.41%\nAnnualized volatility: 10.65%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3500, t10y3m_spread=-1.1200, breakeven_10y=2.2800, hy_oas=3.2100, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.8600, vix=12.4400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.41%\n Annualized volatility: 10.65%\n Macro: fed_funds=5.3300, vix=12.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.064135, "annualized_vol": 0.106478, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240313_0068", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-13", "context_summary": "Regime: sideways. SPY trailing return: +9.1%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=502.94, trailing_return=+9.05%\nAnnualized volatility: 11.58%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4200, t10y3m_spread=-1.3200, breakeven_10y=2.3000, hy_oas=3.2000, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.8800, vix=13.8400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.05%\n Annualized volatility: 11.58%\n Macro: fed_funds=5.3300, vix=13.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.090529, "annualized_vol": 0.115792, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240819_0073", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-19", "context_summary": "Regime: bull. SPY trailing return: +5.0%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=517.24, end=542.89, trailing_return=+4.96%\nAnnualized volatility: 14.31%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1700, t10y3m_spread=-1.4400, breakeven_10y=2.0800, hy_oas=3.2900, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.4900, vix=14.8000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.96%\n Annualized volatility: 14.31%\n Macro: fed_funds=5.3300, vix=14.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.049579, "annualized_vol": 0.143072, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240702_0076", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-02", "context_summary": "Regime: sideways. SPY trailing return: +5.5%, annualized vol: 10.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=506.11, end=534.10, trailing_return=+5.53%\nAnnualized volatility: 10.29%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2900, t10y3m_spread=-0.9900, breakeven_10y=2.3200, hy_oas=3.2100, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.8600, vix=12.2200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.53%\n Annualized volatility: 10.29%\n Macro: fed_funds=5.3300, vix=12.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.0553, "annualized_vol": 0.102931, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240814_0078", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-14", "context_summary": "Regime: sideways. SPY trailing return: +2.7%, annualized vol: 13.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=516.87, end=530.87, trailing_return=+2.71%\nAnnualized volatility: 13.89%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0800, t10y3m_spread=-1.4700, breakeven_10y=2.0900, hy_oas=3.5400, ig_oas=1.0400, ted_spread=0.0900, mortgage_30y=6.4700, vix=18.1200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.71%\n Annualized volatility: 13.89%\n Macro: fed_funds=5.3300, vix=18.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.027082, "annualized_vol": 0.138937, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240510_0082", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-10", "context_summary": "Regime: bull. SPY trailing return: +4.7%, annualized vol: 11.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=485.22, end=507.81, trailing_return=+4.66%\nAnnualized volatility: 11.82%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3500, t10y3m_spread=-1.0100, breakeven_10y=2.3200, hy_oas=3.1400, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.0900, vix=12.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.66%\n Annualized volatility: 11.82%\n Macro: fed_funds=5.3300, vix=12.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.046566, "annualized_vol": 0.118171, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240325_0087", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-25", "context_summary": "Regime: bull. SPY trailing return: +10.3%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=508.83, trailing_return=+10.33%\nAnnualized volatility: 11.13%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3700, t10y3m_spread=-1.2400, breakeven_10y=2.3500, hy_oas=3.0800, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8700, vix=13.0600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.33%\n Annualized volatility: 11.13%\n Macro: fed_funds=5.3300, vix=13.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.103295, "annualized_vol": 0.111302, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241211_0091", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-11", "context_summary": "Regime: bull. SPY trailing return: +7.4%, annualized vol: 10.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=551.47, end=592.19, trailing_return=+7.38%\nAnnualized volatility: 10.33%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0700, t10y3m_spread=-0.1900, breakeven_10y=2.2900, hy_oas=2.6700, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.6900, vix=14.1800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.38%\n Annualized volatility: 10.33%\n Macro: fed_funds=4.5800, vix=14.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.073843, "annualized_vol": 0.103346, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240222_0093", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-22", "context_summary": "Regime: sideways. SPY trailing return: +4.9%, annualized vol: 11.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=483.89, trailing_return=+4.92%\nAnnualized volatility: 11.31%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3200, t10y3m_spread=-1.1200, breakeven_10y=2.3400, hy_oas=3.3400, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.7700, vix=15.3400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.92%\n Annualized volatility: 11.31%\n Macro: fed_funds=5.3300, vix=15.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.049232, "annualized_vol": 0.113118, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240425_0095", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-25", "context_summary": "Regime: sideways. SPY trailing return: +3.3%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=477.74, end=493.40, trailing_return=+3.28%\nAnnualized volatility: 12.07%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.2400, t10y3m_spread=-0.8100, breakeven_10y=2.4100, hy_oas=3.1900, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=7.1000, vix=15.9700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.28%\n Annualized volatility: 12.07%\n Macro: fed_funds=5.3300, vix=16.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.032778, "annualized_vol": 0.120676, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240430_0097", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-30", "context_summary": "Regime: sideways. SPY trailing return: +3.5%, annualized vol: 11.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=481.11, end=497.94, trailing_return=+3.50%\nAnnualized volatility: 11.45%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3400, t10y3m_spread=-0.8200, breakeven_10y=2.4100, hy_oas=3.1200, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=7.1700, vix=14.6700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.50%\n Annualized volatility: 11.45%\n Macro: fed_funds=5.3300, vix=14.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.034985, "annualized_vol": 0.114474, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240827_0101", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-27", "context_summary": "Regime: bull. SPY trailing return: +6.7%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=514.84, end=549.23, trailing_return=+6.68%\nAnnualized volatility: 14.35%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0900, t10y3m_spread=-1.4200, breakeven_10y=2.1500, hy_oas=3.1500, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.4600, vix=16.1500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.68%\n Annualized volatility: 14.35%\n Macro: fed_funds=5.3300, vix=16.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.066802, "annualized_vol": 0.143497, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241010_0103", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-10", "context_summary": "Regime: sideways. SPY trailing return: +3.9%, annualized vol: 16.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=545.46, end=566.98, trailing_return=+3.94%\nAnnualized volatility: 16.07%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0700, t10y3m_spread=-0.6900, breakeven_10y=2.2900, hy_oas=2.9400, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.1200, vix=20.8600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.94%\n Annualized volatility: 16.07%\n Macro: fed_funds=4.8300, vix=20.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.039448, "annualized_vol": 0.160722, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241209_0105", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-09", "context_summary": "Regime: bull. SPY trailing return: +8.5%, annualized vol: 10.2%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=550.43, end=597.11, trailing_return=+8.48%\nAnnualized volatility: 10.24%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0500, t10y3m_spread=-0.2700, breakeven_10y=2.2400, hy_oas=2.6700, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.6900, vix=12.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.48%\n Annualized volatility: 10.24%\n Macro: fed_funds=4.5800, vix=12.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.08481, "annualized_vol": 0.10242, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240920_0107", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-20", "context_summary": "Regime: sideways. SPY trailing return: +4.7%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=534.27, end=559.21, trailing_return=+4.67%\nAnnualized volatility: 15.95%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.1400, t10y3m_spread=-1.0700, breakeven_10y=2.1700, hy_oas=3.1000, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.0900, vix=16.3300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.67%\n Annualized volatility: 15.95%\n Macro: fed_funds=4.8300, vix=16.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.04669, "annualized_vol": 0.159525, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241224_0113", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-24", "context_summary": "Regime: sideways. SPY trailing return: +4.0%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=563.66, end=586.19, trailing_return=+4.00%\nAnnualized volatility: 11.80%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.2900, t10y3m_spread=0.2300, breakeven_10y=2.3200, hy_oas=2.8500, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=16.7800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.00%\n Annualized volatility: 11.80%\n Macro: fed_funds=4.3300, vix=16.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.039967, "annualized_vol": 0.118047, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240614_0115", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-14", "context_summary": "Regime: sideways. SPY trailing return: +4.2%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=508.11, end=529.56, trailing_return=+4.22%\nAnnualized volatility: 10.85%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4400, t10y3m_spread=-1.2700, breakeven_10y=2.2100, hy_oas=3.2000, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.9500, vix=11.9400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.22%\n Annualized volatility: 10.85%\n Macro: fed_funds=5.3300, vix=11.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.042211, "annualized_vol": 0.108472, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240725_0117", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-25", "context_summary": "Regime: sideways. SPY trailing return: +6.5%, annualized vol: 10.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=497.94, end=530.08, trailing_return=+6.45%\nAnnualized volatility: 10.74%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0900, t10y3m_spread=-1.1200, breakeven_10y=2.2800, hy_oas=3.1000, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.7700, vix=18.0400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.45%\n Annualized volatility: 10.74%\n Macro: fed_funds=5.3300, vix=18.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.064533, "annualized_vol": 0.107408, "has_text": true, "text_chars": 9047}} +{"id": "T7_all_20241021_0120", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-21", "context_summary": "Regime: sideways. SPY trailing return: +7.7%, annualized vol: 14.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=533.22, end=574.30, trailing_return=+7.70%\nAnnualized volatility: 14.86%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1300, t10y3m_spread=-0.6500, breakeven_10y=2.3100, hy_oas=2.8800, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.4400, vix=18.0300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.70%\n Annualized volatility: 14.86%\n Macro: fed_funds=4.8300, vix=18.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.077039, "annualized_vol": 0.148629, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20241210_0126", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-10", "context_summary": "Regime: bull. SPY trailing return: +7.8%, annualized vol: 10.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=551.24, end=594.03, trailing_return=+7.76%\nAnnualized volatility: 10.30%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0700, t10y3m_spread=-0.2200, breakeven_10y=2.2700, hy_oas=2.6700, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.6900, vix=14.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.76%\n Annualized volatility: 10.30%\n Macro: fed_funds=4.5800, vix=14.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.077632, "annualized_vol": 0.102968, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241118_0129", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-18", "context_summary": "Regime: sideways. SPY trailing return: +4.5%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=550.54, end=575.44, trailing_return=+4.52%\nAnnualized volatility: 12.43%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1200, t10y3m_spread=-0.1700, breakeven_10y=2.3300, hy_oas=2.7200, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7800, vix=16.1400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.52%\n Annualized volatility: 12.43%\n Macro: fed_funds=4.5800, vix=16.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.045215, "annualized_vol": 0.124274, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240802_0131", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-02", "context_summary": "Regime: sideways. SPY trailing return: +5.3%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=504.85, end=531.82, trailing_return=+5.34%\nAnnualized volatility: 10.83%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1700, t10y3m_spread=-1.3800, breakeven_10y=2.2000, hy_oas=3.3500, ig_oas=1.0000, ted_spread=0.0900, mortgage_30y=6.7300, vix=18.5900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.34%\n Annualized volatility: 10.83%\n Macro: fed_funds=5.3300, vix=18.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.053412, "annualized_vol": 0.10829, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20241203_0135", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-03", "context_summary": "Regime: bull. SPY trailing return: +10.8%, annualized vol: 10.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=535.15, end=593.00, trailing_return=+10.81%\nAnnualized volatility: 10.62%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0200, t10y3m_spread=-0.3200, breakeven_10y=2.2600, hy_oas=2.6800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8100, vix=13.3400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.81%\n Annualized volatility: 10.62%\n Macro: fed_funds=4.5800, vix=13.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.108109, "annualized_vol": 0.106211, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240531_0141", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-31", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 11.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=496.10, end=510.19, trailing_return=+2.84%\nAnnualized volatility: 11.06%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3700, t10y3m_spread=-0.9100, breakeven_10y=2.3600, hy_oas=3.1900, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=7.0300, vix=14.4700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.84%\n Annualized volatility: 11.06%\n Macro: fed_funds=5.3300, vix=14.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.028414, "annualized_vol": 0.110562, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240910_0143", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-10", "context_summary": "Regime: sideways. SPY trailing return: +1.1%, annualized vol: 15.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=529.56, end=535.15, trailing_return=+1.05%\nAnnualized volatility: 15.44%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0200, t10y3m_spread=-1.4100, breakeven_10y=2.0400, hy_oas=3.3600, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.3500, vix=19.4500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.05%\n Annualized volatility: 15.44%\n Macro: fed_funds=5.3300, vix=19.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.01055, "annualized_vol": 0.154415, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240219_0147", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-19", "context_summary": "Regime: sideways. SPY trailing return: +5.4%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=486.13, trailing_return=+5.41%\nAnnualized volatility: 11.49%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3400, t10y3m_spread=-1.1400, breakeven_10y=2.3300, hy_oas=3.3400, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.7700, vix=14.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.41%\n Annualized volatility: 11.49%\n Macro: fed_funds=5.3300, vix=14.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.054085, "annualized_vol": 0.11491, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240315_0151", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-15", "context_summary": "Regime: sideways. SPY trailing return: +8.7%, annualized vol: 11.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=501.16, trailing_return=+8.67%\nAnnualized volatility: 11.40%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.1900, breakeven_10y=2.3000, hy_oas=3.1500, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.7400, vix=14.4000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.67%\n Annualized volatility: 11.40%\n Macro: fed_funds=5.3300, vix=14.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.086667, "annualized_vol": 0.11398, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240916_0154", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-16", "context_summary": "Regime: sideways. SPY trailing return: +3.1%, annualized vol: 15.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=534.00, end=550.43, trailing_return=+3.08%\nAnnualized volatility: 15.63%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0900, t10y3m_spread=-1.3100, breakeven_10y=2.0800, hy_oas=3.3700, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.2000, vix=16.5600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.08%\n Annualized volatility: 15.63%\n Macro: fed_funds=5.3300, vix=16.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.030755, "annualized_vol": 0.156294, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240416_0158", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-16", "context_summary": "Regime: sideways. SPY trailing return: +4.9%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=469.51, end=492.46, trailing_return=+4.89%\nAnnualized volatility: 11.84%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3000, t10y3m_spread=-0.8200, breakeven_10y=2.4300, hy_oas=3.2800, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8800, vix=19.2300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.89%\n Annualized volatility: 11.84%\n Macro: fed_funds=5.3300, vix=19.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.048893, "annualized_vol": 0.118427, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240415_0160", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-15", "context_summary": "Regime: sideways. SPY trailing return: +7.5%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=463.73, end=498.71, trailing_return=+7.54%\nAnnualized volatility: 11.60%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3800, t10y3m_spread=-0.9500, breakeven_10y=2.3900, hy_oas=3.2500, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8800, vix=17.3100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.54%\n Annualized volatility: 11.60%\n Macro: fed_funds=5.3300, vix=17.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.075442, "annualized_vol": 0.116036, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241009_0162", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-09", "context_summary": "Regime: sideways. SPY trailing return: +1.8%, annualized vol: 16.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=553.22, end=563.08, trailing_return=+1.78%\nAnnualized volatility: 16.06%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0600, t10y3m_spread=-0.7100, breakeven_10y=2.2700, hy_oas=2.9900, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.1200, vix=21.4200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.78%\n Annualized volatility: 16.06%\n Macro: fed_funds=4.8300, vix=21.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017824, "annualized_vol": 0.160564, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240306_0165", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-06", "context_summary": "Regime: sideways. SPY trailing return: +7.0%, annualized vol: 11.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=493.60, trailing_return=+7.03%\nAnnualized volatility: 11.69%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4100, t10y3m_spread=-1.3400, breakeven_10y=2.3200, hy_oas=3.3100, ig_oas=1.0100, ted_spread=0.0900, mortgage_30y=6.9400, vix=14.4600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.03%\n Annualized volatility: 11.69%\n Macro: fed_funds=5.3300, vix=14.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.070271, "annualized_vol": 0.116871, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240704_0168", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-04", "context_summary": "Regime: sideways. SPY trailing return: +6.5%, annualized vol: 10.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=506.98, end=540.09, trailing_return=+6.53%\nAnnualized volatility: 10.20%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3500, t10y3m_spread=-1.1100, breakeven_10y=2.2700, hy_oas=3.2500, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.0900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.53%\n Annualized volatility: 10.20%\n Macro: fed_funds=5.3300, vix=12.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.065315, "annualized_vol": 0.102015, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240502_0170", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-02", "context_summary": "Regime: sideways. SPY trailing return: +1.6%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=480.75, end=488.46, trailing_return=+1.60%\nAnnualized volatility: 11.76%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3300, t10y3m_spread=-0.8300, breakeven_10y=2.3800, hy_oas=3.2100, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=7.1700, vix=15.3900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.60%\n Annualized volatility: 11.76%\n Macro: fed_funds=5.3300, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.016042, "annualized_vol": 0.117607, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240328_0174", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-28", "context_summary": "Regime: bull. SPY trailing return: +10.7%, annualized vol: 11.0%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=510.74, trailing_return=+10.74%\nAnnualized volatility: 10.99%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3400, t10y3m_spread=-1.2500, breakeven_10y=2.3200, hy_oas=3.1500, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.8700, vix=12.7800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.74%\n Annualized volatility: 10.99%\n Macro: fed_funds=5.3300, vix=12.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.107444, "annualized_vol": 0.109924, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240808_0177", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-08", "context_summary": "Regime: sideways. SPY trailing return: -0.1%, annualized vol: 13.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=508.53, end=507.97, trailing_return=-0.11%\nAnnualized volatility: 13.05%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0400, t10y3m_spread=-1.3800, breakeven_10y=2.1100, hy_oas=3.5700, ig_oas=1.0700, ted_spread=0.0900, mortgage_30y=6.7300, vix=27.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -0.11%\n Annualized volatility: 13.05%\n Macro: fed_funds=5.3300, vix=27.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.001107, "annualized_vol": 0.130543, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240311_0186", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-11", "context_summary": "Regime: sideways. SPY trailing return: +8.0%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=498.01, trailing_return=+7.99%\nAnnualized volatility: 11.63%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.3700, breakeven_10y=2.2800, hy_oas=3.2600, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.8800, vix=14.7400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.99%\n Annualized volatility: 11.63%\n Macro: fed_funds=5.3300, vix=14.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.079851, "annualized_vol": 0.116276, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240513_0194", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-13", "context_summary": "Regime: bull. SPY trailing return: +4.1%, annualized vol: 11.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=488.56, end=508.47, trailing_return=+4.07%\nAnnualized volatility: 11.70%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3700, t10y3m_spread=-0.9700, breakeven_10y=2.3400, hy_oas=3.1200, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.0900, vix=12.5500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.07%\n Annualized volatility: 11.70%\n Macro: fed_funds=5.3300, vix=12.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.040733, "annualized_vol": 0.116953, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240527_0197", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-27", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 11.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=499.11, end=516.86, trailing_return=+3.56%\nAnnualized volatility: 11.21%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4700, t10y3m_spread=-1.0000, breakeven_10y=2.3200, hy_oas=3.1100, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.9400, vix=11.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.56%\n Annualized volatility: 11.21%\n Macro: fed_funds=5.3300, vix=11.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.035556, "annualized_vol": 0.112111, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240418_0202", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-18", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 11.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=471.87, end=488.66, trailing_return=+3.56%\nAnnualized volatility: 11.69%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3400, t10y3m_spread=-0.8600, breakeven_10y=2.3900, hy_oas=3.4200, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.8800, vix=18.2100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.56%\n Annualized volatility: 11.69%\n Macro: fed_funds=5.3300, vix=18.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.035567, "annualized_vol": 0.11692, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241023_0207", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-23", "context_summary": "Regime: sideways. SPY trailing return: +8.0%, annualized vol: 14.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=530.83, end=573.05, trailing_return=+7.95%\nAnnualized volatility: 14.74%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1700, t10y3m_spread=-0.5200, breakeven_10y=2.3300, hy_oas=2.9200, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.4400, vix=18.2000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.95%\n Annualized volatility: 14.74%\n Macro: fed_funds=4.8300, vix=18.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.079537, "annualized_vol": 0.147402, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20241127_0210", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-27", "context_summary": "Regime: sideways. SPY trailing return: +9.4%, annualized vol: 11.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=539.60, end=590.08, trailing_return=+9.36%\nAnnualized volatility: 11.27%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0900, t10y3m_spread=-0.3100, breakeven_10y=2.2800, hy_oas=2.6800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8400, vix=14.1000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.36%\n Annualized volatility: 11.27%\n Macro: fed_funds=4.5800, vix=14.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.093552, "annualized_vol": 0.112702, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240805_0212", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-05", "context_summary": "Regime: sideways. SPY trailing return: +3.4%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=504.90, end=521.92, trailing_return=+3.37%\nAnnualized volatility: 11.56%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0800, t10y3m_spread=-1.4900, breakeven_10y=2.0400, hy_oas=3.7200, ig_oas=1.0600, ted_spread=0.0900, mortgage_30y=6.7300, vix=23.3900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.37%\n Annualized volatility: 11.56%\n Macro: fed_funds=5.3300, vix=23.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.0337, "annualized_vol": 0.115553, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240904_0214", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-04", "context_summary": "Regime: bull. SPY trailing return: +3.7%, annualized vol: 14.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=521.32, end=540.70, trailing_return=+3.72%\nAnnualized volatility: 14.94%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0400, t10y3m_spread=-1.3500, breakeven_10y=2.1100, hy_oas=3.3100, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.3500, vix=20.7200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.72%\n Annualized volatility: 14.94%\n Macro: fed_funds=5.3300, vix=20.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.037173, "annualized_vol": 0.149399, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241004_0216", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-04", "context_summary": "Regime: sideways. SPY trailing return: +2.4%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=545.01, end=557.82, trailing_return=+2.35%\nAnnualized volatility: 15.89%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1500, t10y3m_spread=-0.8300, breakeven_10y=2.2100, hy_oas=3.0400, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.1200, vix=20.4900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.35%\n Annualized volatility: 15.89%\n Macro: fed_funds=4.8300, vix=20.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.023508, "annualized_vol": 0.158892, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241230_0218", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-30", "context_summary": "Regime: sideways. SPY trailing return: +5.1%, annualized vol: 12.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=557.82, end=586.50, trailing_return=+5.14%\nAnnualized volatility: 12.04%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.3100, t10y3m_spread=0.3100, breakeven_10y=2.3400, hy_oas=2.8400, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8500, vix=15.9500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.14%\n Annualized volatility: 12.04%\n Macro: fed_funds=4.3300, vix=15.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.051412, "annualized_vol": 0.120365, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240723_0222", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-23", "context_summary": "Regime: sideways. SPY trailing return: +10.5%, annualized vol: 9.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=491.53, end=543.22, trailing_return=+10.52%\nAnnualized volatility: 9.68%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2400, t10y3m_spread=-1.1700, breakeven_10y=2.3000, hy_oas=3.0500, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7700, vix=14.9100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.52%\n Annualized volatility: 9.68%\n Macro: fed_funds=5.3300, vix=14.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.105165, "annualized_vol": 0.096827, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240221_0224", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-21", "context_summary": "Regime: sideways. SPY trailing return: +4.8%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=483.46, trailing_return=+4.83%\nAnnualized volatility: 11.49%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3200, t10y3m_spread=-1.1700, breakeven_10y=2.3200, hy_oas=3.3700, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.7700, vix=15.4200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.83%\n Annualized volatility: 11.49%\n Macro: fed_funds=5.3300, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.048282, "annualized_vol": 0.11486, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20241014_0227", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-14", "context_summary": "Regime: sideways. SPY trailing return: +5.9%, annualized vol: 15.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=537.68, end=569.38, trailing_return=+5.90%\nAnnualized volatility: 15.73%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1300, t10y3m_spread=-0.6500, breakeven_10y=2.3300, hy_oas=2.9800, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.3200, vix=20.4600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.90%\n Annualized volatility: 15.73%\n Macro: fed_funds=4.8300, vix=20.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.058959, "annualized_vol": 0.157325, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240816_0231", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-16", "context_summary": "Regime: sideways. SPY trailing return: +4.4%, annualized vol: 14.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=518.74, end=541.67, trailing_return=+4.42%\nAnnualized volatility: 14.31%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1600, t10y3m_spread=-1.4200, breakeven_10y=2.1200, hy_oas=3.3100, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.4900, vix=15.2300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.42%\n Annualized volatility: 14.31%\n Macro: fed_funds=5.3300, vix=15.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.044216, "annualized_vol": 0.143082, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240813_0234", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-13", "context_summary": "Regime: sideways. SPY trailing return: +1.2%, annualized vol: 13.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=516.13, end=522.28, trailing_return=+1.19%\nAnnualized volatility: 13.50%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1100, t10y3m_spread=-1.4300, breakeven_10y=2.1100, hy_oas=3.5200, ig_oas=1.0500, ted_spread=0.0900, mortgage_30y=6.4700, vix=20.7100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.19%\n Annualized volatility: 13.50%\n Macro: fed_funds=5.3300, vix=20.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.011917, "annualized_vol": 0.135038, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241217_0237", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-17", "context_summary": "Regime: bull. SPY trailing return: +6.5%, annualized vol: 10.0%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=559.64, end=596.11, trailing_return=+6.52%\nAnnualized volatility: 9.95%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1400, t10y3m_spread=0.0200, breakeven_10y=2.3200, hy_oas=2.6900, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.6000, vix=14.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.52%\n Annualized volatility: 9.95%\n Macro: fed_funds=4.5800, vix=14.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.065161, "annualized_vol": 0.099535, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240326_0245", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-26", "context_summary": "Regime: bull. SPY trailing return: +10.0%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=507.42, trailing_return=+10.02%\nAnnualized volatility: 11.07%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.2900, t10y3m_spread=-1.2100, breakeven_10y=2.3300, hy_oas=3.1100, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8700, vix=13.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.02%\n Annualized volatility: 11.07%\n Macro: fed_funds=5.3300, vix=13.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.100247, "annualized_vol": 0.110722, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241227_0247", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-27", "context_summary": "Regime: sideways. SPY trailing return: +6.1%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=558.85, end=592.74, trailing_return=+6.07%\nAnnualized volatility: 11.80%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.2800, t10y3m_spread=0.2300, breakeven_10y=2.3500, hy_oas=2.8600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8500, vix=14.7300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.07%\n Annualized volatility: 11.80%\n Macro: fed_funds=4.3300, vix=14.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.060655, "annualized_vol": 0.118014, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240726_0250", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-26", "context_summary": "Regime: sideways. SPY trailing return: +7.6%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=490.05, end=527.31, trailing_return=+7.60%\nAnnualized volatility: 10.81%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1400, t10y3m_spread=-1.1200, breakeven_10y=2.2800, hy_oas=3.0800, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.7800, vix=18.4600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.60%\n Annualized volatility: 10.81%\n Macro: fed_funds=5.3300, vix=18.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.076033, "annualized_vol": 0.108059, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240624_0253", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-24", "context_summary": "Regime: bull. SPY trailing return: +4.4%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=510.74, end=533.29, trailing_return=+4.41%\nAnnualized volatility: 10.78%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4500, t10y3m_spread=-1.2400, breakeven_10y=2.2300, hy_oas=3.2100, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.8700, vix=13.2000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.41%\n Annualized volatility: 10.78%\n Macro: fed_funds=5.3300, vix=13.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.044147, "annualized_vol": 0.107817, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241226_0256", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-26", "context_summary": "Regime: sideways. SPY trailing return: +6.1%, annualized vol: 12.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=558.61, end=592.70, trailing_return=+6.10%\nAnnualized volatility: 11.98%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.3000, t10y3m_spread=0.1900, breakeven_10y=2.3500, hy_oas=2.8600, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=14.2700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.10%\n Annualized volatility: 11.98%\n Macro: fed_funds=4.3300, vix=14.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.061031, "annualized_vol": 0.119761, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241206_0260", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-06", "context_summary": "Regime: bull. SPY trailing return: +8.8%, annualized vol: 10.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=547.57, end=595.98, trailing_return=+8.84%\nAnnualized volatility: 10.34%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0200, t10y3m_spread=-0.2900, breakeven_10y=2.2500, hy_oas=2.6600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.6900, vix=13.5400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.84%\n Annualized volatility: 10.34%\n Macro: fed_funds=4.5800, vix=13.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.088413, "annualized_vol": 0.103418, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240919_0263", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-19", "context_summary": "Regime: sideways. SPY trailing return: +3.0%, annualized vol: 15.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=533.60, end=549.83, trailing_return=+3.04%\nAnnualized volatility: 15.61%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0900, t10y3m_spread=-1.1400, breakeven_10y=2.1200, hy_oas=3.2100, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.2000, vix=18.2300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.04%\n Annualized volatility: 15.61%\n Macro: fed_funds=5.3300, vix=18.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.030413, "annualized_vol": 0.156089, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240715_0265", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-15", "context_summary": "Regime: bull. SPY trailing return: +12.2%, annualized vol: 9.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=488.66, end=548.45, trailing_return=+12.24%\nAnnualized volatility: 9.33%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2700, t10y3m_spread=-1.2500, breakeven_10y=2.2400, hy_oas=3.1900, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8900, vix=12.4600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +12.24%\n Annualized volatility: 9.33%\n Macro: fed_funds=5.3300, vix=12.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.122359, "annualized_vol": 0.093303, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240514_0267", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-14", "context_summary": "Regime: bull. SPY trailing return: +4.6%, annualized vol: 11.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=486.13, end=508.53, trailing_return=+4.61%\nAnnualized volatility: 11.63%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3700, t10y3m_spread=-0.9700, breakeven_10y=2.3300, hy_oas=3.1400, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=7.0900, vix=13.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.61%\n Annualized volatility: 11.63%\n Macro: fed_funds=5.3300, vix=13.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.046082, "annualized_vol": 0.116266, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241119_0271", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-19", "context_summary": "Regime: sideways. SPY trailing return: +5.2%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=549.23, end=577.80, trailing_return=+5.20%\nAnnualized volatility: 12.28%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1300, t10y3m_spread=-0.2100, breakeven_10y=2.3400, hy_oas=2.7200, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7800, vix=15.5800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.20%\n Annualized volatility: 12.28%\n Macro: fed_funds=4.5800, vix=15.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.052005, "annualized_vol": 0.12281, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240731_0275", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-31", "context_summary": "Regime: sideways. SPY trailing return: +6.3%, annualized vol: 10.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=499.14, end=530.83, trailing_return=+6.35%\nAnnualized volatility: 10.32%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2000, t10y3m_spread=-1.2500, breakeven_10y=2.2500, hy_oas=3.2000, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.7800, vix=17.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.35%\n Annualized volatility: 10.32%\n Macro: fed_funds=5.3300, vix=17.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.063484, "annualized_vol": 0.103243, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240612_0277", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-12", "context_summary": "Regime: sideways. SPY trailing return: +4.7%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=500.68, end=524.19, trailing_return=+4.70%\nAnnualized volatility: 10.83%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4200, t10y3m_spread=-1.1300, breakeven_10y=2.2700, hy_oas=3.1900, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.9900, vix=12.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.70%\n Annualized volatility: 10.83%\n Macro: fed_funds=5.3300, vix=12.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.046972, "annualized_vol": 0.108329, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240404_0282", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-04", "context_summary": "Regime: sideways. SPY trailing return: +9.8%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.89, end=507.07, trailing_return=+9.78%\nAnnualized volatility: 10.82%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3200, t10y3m_spread=-1.0600, breakeven_10y=2.3600, hy_oas=3.2300, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.7900, vix=14.3300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.78%\n Annualized volatility: 10.82%\n Macro: fed_funds=5.3300, vix=14.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.097817, "annualized_vol": 0.108171, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241002_0284", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-02", "context_summary": "Regime: sideways. SPY trailing return: +2.6%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=544.36, end=558.61, trailing_return=+2.62%\nAnnualized volatility: 16.00%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1300, t10y3m_spread=-0.9700, breakeven_10y=2.1900, hy_oas=3.0700, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.0800, vix=19.2600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.62%\n Annualized volatility: 16.00%\n Macro: fed_funds=4.8300, vix=19.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.026167, "annualized_vol": 0.160042, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240801_0287", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-01", "context_summary": "Regime: sideways. SPY trailing return: +7.0%, annualized vol: 10.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=504.30, end=539.46, trailing_return=+6.97%\nAnnualized volatility: 10.53%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2000, t10y3m_spread=-1.3200, breakeven_10y=2.2400, hy_oas=3.2500, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.7800, vix=16.3600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.97%\n Annualized volatility: 10.53%\n Macro: fed_funds=5.3300, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.069723, "annualized_vol": 0.105263, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240925_0292", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-25", "context_summary": "Regime: sideways. SPY trailing return: +5.1%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=534.10, end=561.24, trailing_return=+5.08%\nAnnualized volatility: 15.94%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.2500, t10y3m_spread=-0.9500, breakeven_10y=2.1900, hy_oas=3.2100, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.0900, vix=15.3900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.08%\n Annualized volatility: 15.94%\n Macro: fed_funds=4.8300, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.050817, "annualized_vol": 0.159391, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241016_0294", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-16", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 15.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=542.37, end=569.57, trailing_return=+5.02%\nAnnualized volatility: 15.71%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0800, t10y3m_spread=-0.7000, breakeven_10y=2.2800, hy_oas=2.9300, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.3200, vix=20.6400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.02%\n Annualized volatility: 15.71%\n Macro: fed_funds=4.8300, vix=20.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.050161, "annualized_vol": 0.157093, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240229_0296", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-29", "context_summary": "Regime: sideways. SPY trailing return: +6.8%, annualized vol: 11.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=492.70, trailing_return=+6.83%\nAnnualized volatility: 11.71%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3700, t10y3m_spread=-1.1800, breakeven_10y=2.3300, hy_oas=3.3100, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.9000, vix=13.8400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.83%\n Annualized volatility: 11.71%\n Macro: fed_funds=5.3300, vix=13.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.06833, "annualized_vol": 0.117131, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240417_0298", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-17", "context_summary": "Regime: sideways. SPY trailing return: +4.5%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=470.50, end=491.57, trailing_return=+4.48%\nAnnualized volatility: 11.62%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3000, t10y3m_spread=-0.7800, breakeven_10y=2.4300, hy_oas=3.3600, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.8800, vix=18.4000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.48%\n Annualized volatility: 11.62%\n Macro: fed_funds=5.3300, vix=18.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.044771, "annualized_vol": 0.11615, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241017_0300", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-17", "context_summary": "Regime: sideways. SPY trailing return: +7.9%, annualized vol: 15.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=530.08, end=572.05, trailing_return=+7.92%\nAnnualized volatility: 15.72%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0900, t10y3m_spread=-0.7000, breakeven_10y=2.2700, hy_oas=2.9000, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.3200, vix=19.5800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.92%\n Annualized volatility: 15.72%\n Macro: fed_funds=4.8300, vix=19.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.079183, "annualized_vol": 0.15718, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241204_0302", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-04", "context_summary": "Regime: bull. SPY trailing return: +10.4%, annualized vol: 10.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=537.48, end=593.28, trailing_return=+10.38%\nAnnualized volatility: 10.45%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0600, t10y3m_spread=-0.2600, breakeven_10y=2.2800, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.8100, vix=13.3000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.38%\n Annualized volatility: 10.45%\n Macro: fed_funds=4.5800, vix=13.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.103814, "annualized_vol": 0.104457, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240403_0306", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-03", "context_summary": "Regime: sideways. SPY trailing return: +9.8%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=506.51, trailing_return=+9.83%\nAnnualized volatility: 10.82%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3400, t10y3m_spread=-1.0600, breakeven_10y=2.3600, hy_oas=3.2300, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7900, vix=14.6100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.83%\n Annualized volatility: 10.82%\n Macro: fed_funds=5.3300, vix=14.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.098278, "annualized_vol": 0.108165, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240730_0310", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-30", "context_summary": "Regime: sideways. SPY trailing return: +8.2%, annualized vol: 10.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=493.03, end=533.53, trailing_return=+8.21%\nAnnualized volatility: 10.37%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1900, t10y3m_spread=-1.2400, breakeven_10y=2.2500, hy_oas=3.1300, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.7800, vix=16.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.21%\n Annualized volatility: 10.37%\n Macro: fed_funds=5.3300, vix=16.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.082149, "annualized_vol": 0.103697, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240710_0312", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-10", "context_summary": "Regime: bull. SPY trailing return: +9.2%, annualized vol: 9.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=498.71, end=544.36, trailing_return=+9.15%\nAnnualized volatility: 9.89%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3200, t10y3m_spread=-1.1600, breakeven_10y=2.2600, hy_oas=3.2100, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.5100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.15%\n Annualized volatility: 9.89%\n Macro: fed_funds=5.3300, vix=12.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.09154, "annualized_vol": 0.098931, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241022_0314", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-22", "context_summary": "Regime: sideways. SPY trailing return: +7.5%, annualized vol: 14.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=533.53, end=573.36, trailing_return=+7.46%\nAnnualized volatility: 14.74%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1700, t10y3m_spread=-0.5400, breakeven_10y=2.3100, hy_oas=2.8800, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.4400, vix=18.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.46%\n Annualized volatility: 14.74%\n Macro: fed_funds=4.8300, vix=18.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.074639, "annualized_vol": 0.147364, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240320_0316", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-20", "context_summary": "Regime: sideways. SPY trailing return: +9.2%, annualized vol: 11.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=503.46, trailing_return=+9.17%\nAnnualized volatility: 11.29%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3800, t10y3m_spread=-1.1800, breakeven_10y=2.3000, hy_oas=3.1000, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.7400, vix=13.8200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.17%\n Annualized volatility: 11.29%\n Macro: fed_funds=5.3300, vix=13.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.091653, "annualized_vol": 0.112949, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240227_0320", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-27", "context_summary": "Regime: sideways. SPY trailing return: +6.8%, annualized vol: 12.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=492.44, trailing_return=+6.78%\nAnnualized volatility: 12.01%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4100, t10y3m_spread=-1.1900, breakeven_10y=2.3100, hy_oas=3.2300, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.9000, vix=13.7400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.78%\n Annualized volatility: 12.01%\n Macro: fed_funds=5.3300, vix=13.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.06776, "annualized_vol": 0.120056, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240312_0322", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-12", "context_summary": "Regime: sideways. SPY trailing return: +7.9%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=497.59, trailing_return=+7.89%\nAnnualized volatility: 11.52%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4100, t10y3m_spread=-1.3800, breakeven_10y=2.2700, hy_oas=3.2600, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.8800, vix=15.2200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.89%\n Annualized volatility: 11.52%\n Macro: fed_funds=5.3300, vix=15.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.078923, "annualized_vol": 0.115161, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241007_0324", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-07", "context_summary": "Regime: sideways. SPY trailing return: +2.6%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=548.45, end=562.89, trailing_return=+2.63%\nAnnualized volatility: 15.88%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0500, t10y3m_spread=-0.7500, breakeven_10y=2.2300, hy_oas=2.8900, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.1200, vix=19.2100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.63%\n Annualized volatility: 15.88%\n Macro: fed_funds=4.8300, vix=19.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.026335, "annualized_vol": 0.158797, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240628_0328", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-28", "context_summary": "Regime: sideways. SPY trailing return: +5.5%, annualized vol: 10.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=507.07, end=535.11, trailing_return=+5.53%\nAnnualized volatility: 10.60%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4100, t10y3m_spread=-1.2000, breakeven_10y=2.2600, hy_oas=3.2100, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.8600, vix=12.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.53%\n Annualized volatility: 10.60%\n Macro: fed_funds=5.3300, vix=12.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.055299, "annualized_vol": 0.106012, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240523_0331", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-23", "context_summary": "Regime: bull. SPY trailing return: +5.0%, annualized vol: 11.0%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=492.70, end=517.24, trailing_return=+4.98%\nAnnualized volatility: 11.04%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4300, t10y3m_spread=-1.0200, breakeven_10y=2.3300, hy_oas=3.1100, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.0200, vix=12.2900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.98%\n Annualized volatility: 11.04%\n Macro: fed_funds=5.3300, vix=12.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.049809, "annualized_vol": 0.110438, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241008_0333", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-08", "context_summary": "Regime: sideways. SPY trailing return: +1.4%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=549.96, end=557.80, trailing_return=+1.43%\nAnnualized volatility: 15.95%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0400, t10y3m_spread=-0.7400, breakeven_10y=2.2700, hy_oas=2.9500, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.1200, vix=22.6400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.43%\n Annualized volatility: 15.95%\n Macro: fed_funds=4.8300, vix=22.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.014267, "annualized_vol": 0.159543, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240401_0335", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-01", "context_summary": "Regime: bull. SPY trailing return: +10.7%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=510.64, trailing_return=+10.72%\nAnnualized volatility: 10.91%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.2600, breakeven_10y=2.3200, hy_oas=3.1500, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.7900, vix=13.0100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.72%\n Annualized volatility: 10.91%\n Macro: fed_funds=5.3300, vix=13.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.107232, "annualized_vol": 0.109063, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241218_0340", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-18", "context_summary": "Regime: bull. SPY trailing return: +5.8%, annualized vol: 10.0%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=561.24, end=593.65, trailing_return=+5.77%\nAnnualized volatility: 10.00%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1500, t10y3m_spread=0.0200, breakeven_10y=2.3100, hy_oas=2.7500, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.6000, vix=15.8700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.77%\n Annualized volatility: 10.00%\n Macro: fed_funds=4.5800, vix=15.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.057745, "annualized_vol": 0.100043, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240402_0342", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-02", "context_summary": "Regime: bull. SPY trailing return: +10.5%, annualized vol: 10.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=509.75, trailing_return=+10.53%\nAnnualized volatility: 10.73%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3900, t10y3m_spread=-1.1100, breakeven_10y=2.3500, hy_oas=3.1200, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7900, vix=13.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.53%\n Annualized volatility: 10.73%\n Macro: fed_funds=5.3300, vix=13.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.105306, "annualized_vol": 0.107338, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241223_0344", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-23", "context_summary": "Regime: sideways. SPY trailing return: +3.8%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=561.41, end=582.70, trailing_return=+3.79%\nAnnualized volatility: 11.76%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.2200, t10y3m_spread=0.1800, breakeven_10y=2.2900, hy_oas=2.8600, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=18.3600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.79%\n Annualized volatility: 11.76%\n Macro: fed_funds=4.3300, vix=18.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.037919, "annualized_vol": 0.117612, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241105_0346", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-05", "context_summary": "Regime: sideways. SPY trailing return: +7.2%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=522.28, end=559.78, trailing_return=+7.18%\nAnnualized volatility: 12.12%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1400, t10y3m_spread=-0.3400, breakeven_10y=2.2800, hy_oas=2.8700, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.7200, vix=21.9800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.18%\n Annualized volatility: 12.12%\n Macro: fed_funds=4.8300, vix=22.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.071798, "annualized_vol": 0.121216, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240913_0348", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-13", "context_summary": "Regime: sideways. SPY trailing return: +2.3%, annualized vol: 15.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=535.46, end=547.57, trailing_return=+2.26%\nAnnualized volatility: 15.60%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0400, t10y3m_spread=-1.3800, breakeven_10y=2.0500, hy_oas=3.3900, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.2000, vix=17.0700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.26%\n Annualized volatility: 15.60%\n Macro: fed_funds=5.3300, vix=17.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.022614, "annualized_vol": 0.156043, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240917_0350", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-17", "context_summary": "Regime: sideways. SPY trailing return: +3.4%, annualized vol: 15.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=533.29, end=551.24, trailing_return=+3.37%\nAnnualized volatility: 15.62%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0700, t10y3m_spread=-1.3300, breakeven_10y=2.0900, hy_oas=3.3200, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.2000, vix=17.1400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.37%\n Annualized volatility: 15.62%\n Macro: fed_funds=5.3300, vix=17.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.033663, "annualized_vol": 0.156166, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241120_0352", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-20", "context_summary": "Regime: sideways. SPY trailing return: +5.4%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=549.99, end=579.91, trailing_return=+5.44%\nAnnualized volatility: 12.28%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1200, t10y3m_spread=-0.2300, breakeven_10y=2.3400, hy_oas=2.6900, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7800, vix=16.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.44%\n Annualized volatility: 12.28%\n Macro: fed_funds=4.5800, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.054403, "annualized_vol": 0.122776, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241202_0355", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-02", "context_summary": "Regime: bull. SPY trailing return: +11.9%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=529.22, end=591.94, trailing_return=+11.85%\nAnnualized volatility: 11.30%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0500, t10y3m_spread=-0.4000, breakeven_10y=2.2600, hy_oas=2.7400, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.8100, vix=13.5100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +11.85%\n Annualized volatility: 11.30%\n Macro: fed_funds=4.5800, vix=13.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.11851, "annualized_vol": 0.112989, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240329_0358", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-29", "context_summary": "Regime: bull. SPY trailing return: +10.7%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=510.64, trailing_return=+10.72%\nAnnualized volatility: 10.91%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.2600, breakeven_10y=2.3200, hy_oas=3.1200, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7900, vix=13.0100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.72%\n Annualized volatility: 10.91%\n Macro: fed_funds=5.3300, vix=13.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.107232, "annualized_vol": 0.109063, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240703_0360", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-03", "context_summary": "Regime: sideways. SPY trailing return: +6.2%, annualized vol: 10.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=506.40, end=537.70, trailing_return=+6.18%\nAnnualized volatility: 10.18%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3100, t10y3m_spread=-1.0400, breakeven_10y=2.3000, hy_oas=3.2300, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.8600, vix=12.0300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.18%\n Annualized volatility: 10.18%\n Macro: fed_funds=5.3300, vix=12.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.061808, "annualized_vol": 0.101776, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240522_0362", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-22", "context_summary": "Regime: bull. SPY trailing return: +5.1%, annualized vol: 11.0%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=493.35, end=518.74, trailing_return=+5.14%\nAnnualized volatility: 11.02%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4100, t10y3m_spread=-1.0400, breakeven_10y=2.3200, hy_oas=3.0700, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.0200, vix=11.8600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.14%\n Annualized volatility: 11.02%\n Macro: fed_funds=5.3300, vix=11.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.051449, "annualized_vol": 0.110191, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240508_0364", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-08", "context_summary": "Regime: sideways. SPY trailing return: +3.5%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=487.56, end=504.85, trailing_return=+3.55%\nAnnualized volatility: 12.15%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3500, t10y3m_spread=-0.9800, breakeven_10y=2.3200, hy_oas=3.0600, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=7.2200, vix=13.2300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.55%\n Annualized volatility: 12.15%\n Macro: fed_funds=5.3300, vix=13.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.035464, "annualized_vol": 0.121546, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241101_0368", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-01", "context_summary": "Regime: sideways. SPY trailing return: +7.5%, annualized vol: 12.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=519.71, end=558.63, trailing_return=+7.49%\nAnnualized volatility: 12.75%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1200, t10y3m_spread=-0.3600, breakeven_10y=2.3300, hy_oas=2.8800, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.7200, vix=23.1600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.49%\n Annualized volatility: 12.75%\n Macro: fed_funds=4.8300, vix=23.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.074878, "annualized_vol": 0.127534, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240820_0370", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-20", "context_summary": "Regime: bull. SPY trailing return: +6.7%, annualized vol: 14.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=513.46, end=548.08, trailing_return=+6.74%\nAnnualized volatility: 14.40%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2000, t10y3m_spread=-1.4500, breakeven_10y=2.0700, hy_oas=3.2100, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.4900, vix=14.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.74%\n Annualized volatility: 14.40%\n Macro: fed_funds=5.3300, vix=14.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.067411, "annualized_vol": 0.143977, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240604_0375", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-04", "context_summary": "Regime: sideways. SPY trailing return: +3.5%, annualized vol: 11.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=498.01, end=515.26, trailing_return=+3.46%\nAnnualized volatility: 10.99%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4100, t10y3m_spread=-1.1100, breakeven_10y=2.3300, hy_oas=3.1700, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=7.0300, vix=13.1100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.46%\n Annualized volatility: 10.99%\n Macro: fed_funds=5.3300, vix=13.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.034628, "annualized_vol": 0.109882, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240327_0376", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-27", "context_summary": "Regime: sideways. SPY trailing return: +9.8%, annualized vol: 11.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=506.48, trailing_return=+9.82%\nAnnualized volatility: 11.00%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3200, t10y3m_spread=-1.2200, breakeven_10y=2.3200, hy_oas=3.1500, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.8700, vix=13.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.82%\n Annualized volatility: 11.00%\n Macro: fed_funds=5.3300, vix=13.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.098215, "annualized_vol": 0.109998, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240822_0377", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-22", "context_summary": "Regime: bull. SPY trailing return: +6.2%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=517.22, end=549.07, trailing_return=+6.16%\nAnnualized volatility: 14.27%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1300, t10y3m_spread=-1.4700, breakeven_10y=2.0700, hy_oas=3.2700, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.4900, vix=16.2700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.16%\n Annualized volatility: 14.27%\n Macro: fed_funds=5.3300, vix=16.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.061567, "annualized_vol": 0.142668, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240724_0378", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-24", "context_summary": "Regime: sideways. SPY trailing return: +9.3%, annualized vol: 9.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=496.18, end=542.37, trailing_return=+9.31%\nAnnualized volatility: 9.64%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1500, t10y3m_spread=-1.1600, breakeven_10y=2.2900, hy_oas=3.0200, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7700, vix=14.7200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.31%\n Annualized volatility: 9.64%\n Macro: fed_funds=5.3300, vix=14.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.093076, "annualized_vol": 0.096401, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240826_0379", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-26", "context_summary": "Regime: bull. SPY trailing return: +7.9%, annualized vol: 14.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=510.19, end=550.54, trailing_return=+7.91%\nAnnualized volatility: 14.42%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0900, t10y3m_spread=-1.4400, breakeven_10y=2.1300, hy_oas=3.1900, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.4600, vix=15.8600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.91%\n Annualized volatility: 14.42%\n Macro: fed_funds=5.3300, vix=15.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.07909, "annualized_vol": 0.144222, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240812_0380", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-12", "context_summary": "Regime: sideways. SPY trailing return: +0.9%, annualized vol: 13.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=517.19, end=522.01, trailing_return=+0.93%\nAnnualized volatility: 13.73%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1100, t10y3m_spread=-1.3900, breakeven_10y=2.1000, hy_oas=3.4900, ig_oas=1.0500, ted_spread=0.0900, mortgage_30y=6.4700, vix=20.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.93%\n Annualized volatility: 13.73%\n Macro: fed_funds=5.3300, vix=20.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.009305, "annualized_vol": 0.137311, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240722_0381", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-22", "context_summary": "Regime: sideways. SPY trailing return: +9.0%, annualized vol: 9.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=493.40, end=537.68, trailing_return=+8.97%\nAnnualized volatility: 9.52%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2400, t10y3m_spread=-1.1800, breakeven_10y=2.3200, hy_oas=3.0900, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7700, vix=16.5200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.97%\n Annualized volatility: 9.52%\n Macro: fed_funds=5.3300, vix=16.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.089731, "annualized_vol": 0.095214, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240718_0382", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-18", "context_summary": "Regime: sideways. SPY trailing return: +11.8%, annualized vol: 9.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=487.85, end=545.46, trailing_return=+11.81%\nAnnualized volatility: 9.52%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2600, t10y3m_spread=-1.2700, breakeven_10y=2.2600, hy_oas=3.0900, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.8900, vix=14.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +11.81%\n Annualized volatility: 9.52%\n Macro: fed_funds=5.3300, vix=14.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.1181, "annualized_vol": 0.095165, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240906_0383", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-06", "context_summary": "Regime: sideways. SPY trailing return: +2.7%, annualized vol: 14.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=524.19, end=538.28, trailing_return=+2.69%\nAnnualized volatility: 14.95%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0200, t10y3m_spread=-1.4200, breakeven_10y=2.0300, hy_oas=3.2900, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.3500, vix=19.9000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.69%\n Annualized volatility: 14.95%\n Macro: fed_funds=5.3300, vix=19.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.02688, "annualized_vol": 0.149484, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241107_0384", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-07", "context_summary": "Regime: sideways. SPY trailing return: +9.0%, annualized vol: 12.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=532.54, end=580.63, trailing_return=+9.03%\nAnnualized volatility: 12.59%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1500, t10y3m_spread=-0.2200, breakeven_10y=2.3800, hy_oas=2.7400, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7200, vix=16.2700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.03%\n Annualized volatility: 12.59%\n Macro: fed_funds=4.8300, vix=16.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.090304, "annualized_vol": 0.125891, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241213_0385", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-13", "context_summary": "Regime: bull. SPY trailing return: +6.2%, annualized vol: 10.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=559.21, end=593.69, trailing_return=+6.17%\nAnnualized volatility: 10.47%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1400, t10y3m_spread=-0.0300, breakeven_10y=2.3200, hy_oas=2.6600, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.6000, vix=13.9200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.17%\n Annualized volatility: 10.47%\n Macro: fed_funds=4.5800, vix=13.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.061655, "annualized_vol": 0.104682, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240319_0386", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-19", "context_summary": "Regime: sideways. SPY trailing return: +8.6%, annualized vol: 11.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=500.68, trailing_return=+8.56%\nAnnualized volatility: 11.37%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.1400, breakeven_10y=2.3100, hy_oas=3.1300, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.7400, vix=14.3300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.56%\n Annualized volatility: 11.37%\n Macro: fed_funds=5.3300, vix=14.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.08562, "annualized_vol": 0.113726, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240924_0387", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-24", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=533.00, end=559.64, trailing_return=+5.00%\nAnnualized volatility: 15.96%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.1800, t10y3m_spread=-0.9700, breakeven_10y=2.1700, hy_oas=3.1500, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.0900, vix=15.8900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.00%\n Annualized volatility: 15.96%\n Macro: fed_funds=4.8300, vix=15.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.049975, "annualized_vol": 0.159636, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240621_0388", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-21", "context_summary": "Regime: sideways. SPY trailing return: +5.4%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=506.48, end=534.00, trailing_return=+5.43%\nAnnualized volatility: 10.79%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4500, t10y3m_spread=-1.2500, breakeven_10y=2.2500, hy_oas=3.2300, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.8700, vix=13.2800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.43%\n Annualized volatility: 10.79%\n Macro: fed_funds=5.3300, vix=13.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.054336, "annualized_vol": 0.107866, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240530_0389", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-30", "context_summary": "Regime: sideways. SPY trailing return: +4.1%, annualized vol: 11.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=493.60, end=513.60, trailing_return=+4.05%\nAnnualized volatility: 11.17%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3500, t10y3m_spread=-0.8500, breakeven_10y=2.3600, hy_oas=3.1500, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.9400, vix=14.2800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.05%\n Annualized volatility: 11.17%\n Macro: fed_funds=5.3300, vix=14.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.040527, "annualized_vol": 0.111718, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240318_0390", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-18", "context_summary": "Regime: sideways. SPY trailing return: +7.9%, annualized vol: 11.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=497.72, trailing_return=+7.92%\nAnnualized volatility: 11.44%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4100, t10y3m_spread=-1.1700, breakeven_10y=2.3200, hy_oas=3.1600, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7400, vix=14.4100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.92%\n Annualized volatility: 11.44%\n Macro: fed_funds=5.3300, vix=14.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.079206, "annualized_vol": 0.114444, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240520_0391", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-20", "context_summary": "Regime: bull. SPY trailing return: +4.6%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=494.25, end=516.87, trailing_return=+4.58%\nAnnualized volatility: 11.05%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4100, t10y3m_spread=-1.0400, breakeven_10y=2.3200, hy_oas=3.0900, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.0200, vix=11.9900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.58%\n Annualized volatility: 11.05%\n Macro: fed_funds=5.3300, vix=12.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.045771, "annualized_vol": 0.110526, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241113_0392", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-13", "context_summary": "Regime: sideways. SPY trailing return: +7.2%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=547.19, end=586.39, trailing_return=+7.17%\nAnnualized volatility: 12.16%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0900, t10y3m_spread=-0.2000, breakeven_10y=2.3500, hy_oas=2.6600, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.7900, vix=14.7100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.17%\n Annualized volatility: 12.16%\n Macro: fed_funds=4.5800, vix=14.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.07165, "annualized_vol": 0.121563, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240716_0393", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-16", "context_summary": "Regime: bull. SPY trailing return: +12.8%, annualized vol: 9.2%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=487.65, end=549.96, trailing_return=+12.78%\nAnnualized volatility: 9.19%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2100, t10y3m_spread=-1.2000, breakeven_10y=2.2700, hy_oas=3.1300, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8900, vix=13.1200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +12.78%\n Annualized volatility: 9.19%\n Macro: fed_funds=5.3300, vix=13.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.127766, "annualized_vol": 0.091904, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241104_0394", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-04", "context_summary": "Regime: sideways. SPY trailing return: +7.5%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=522.01, end=560.99, trailing_return=+7.47%\nAnnualized volatility: 12.12%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1600, t10y3m_spread=-0.2400, breakeven_10y=2.3300, hy_oas=2.8300, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.7200, vix=21.8800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.47%\n Annualized volatility: 12.12%\n Macro: fed_funds=4.8300, vix=21.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.074676, "annualized_vol": 0.121194, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240807_0395", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-07", "context_summary": "Regime: sideways. SPY trailing return: +0.6%, annualized vol: 13.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=508.47, end=511.39, trailing_return=+0.57%\nAnnualized volatility: 12.98%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0900, t10y3m_spread=-1.4400, breakeven_10y=2.1200, hy_oas=3.6700, ig_oas=1.0800, ted_spread=0.0900, mortgage_30y=6.7300, vix=27.7100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.57%\n Annualized volatility: 12.98%\n Macro: fed_funds=5.3300, vix=27.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.00575, "annualized_vol": 0.129809, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241018_0396", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-18", "context_summary": "Regime: sideways. SPY trailing return: +8.5%, annualized vol: 14.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=527.31, end=572.10, trailing_return=+8.49%\nAnnualized volatility: 14.92%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1300, t10y3m_spread=-0.6500, breakeven_10y=2.3000, hy_oas=2.8900, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.4400, vix=19.1100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.49%\n Annualized volatility: 14.92%\n Macro: fed_funds=4.8300, vix=19.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.084928, "annualized_vol": 0.14916, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240705_0397", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-05", "context_summary": "Regime: sideways. SPY trailing return: +6.5%, annualized vol: 10.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=506.98, end=540.09, trailing_return=+6.53%\nAnnualized volatility: 10.20%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3500, t10y3m_spread=-1.1100, breakeven_10y=2.2700, hy_oas=3.2500, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.0900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.53%\n Annualized volatility: 10.20%\n Macro: fed_funds=5.3300, vix=12.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.065315, "annualized_vol": 0.102015, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240405_0398", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-05", "context_summary": "Regime: sideways. SPY trailing return: +8.6%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=500.88, trailing_return=+8.61%\nAnnualized volatility: 10.88%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3400, t10y3m_spread=-1.1000, breakeven_10y=2.3400, hy_oas=3.2400, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8200, vix=16.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.61%\n Annualized volatility: 10.88%\n Macro: fed_funds=5.3300, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.086064, "annualized_vol": 0.108822, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240719_0399", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-19", "context_summary": "Regime: sideways. SPY trailing return: +9.6%, annualized vol: 9.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=493.64, end=541.27, trailing_return=+9.65%\nAnnualized volatility: 9.60%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2600, t10y3m_spread=-1.2300, breakeven_10y=2.3100, hy_oas=3.0900, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7700, vix=15.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.65%\n Annualized volatility: 9.60%\n Macro: fed_funds=5.3300, vix=15.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.096495, "annualized_vol": 0.09603, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240507_0400", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-07", "context_summary": "Regime: sideways. SPY trailing return: +3.4%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=487.78, end=504.30, trailing_return=+3.39%\nAnnualized volatility: 12.20%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3300, t10y3m_spread=-0.9600, breakeven_10y=2.3500, hy_oas=3.0300, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=7.2200, vix=13.4900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.39%\n Annualized volatility: 12.20%\n Macro: fed_funds=5.3300, vix=13.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.033869, "annualized_vol": 0.122007, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241030_0401", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-30", "context_summary": "Regime: sideways. SPY trailing return: +11.8%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=511.39, end=571.53, trailing_return=+11.76%\nAnnualized volatility: 12.13%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1700, t10y3m_spread=-0.4200, breakeven_10y=2.3000, hy_oas=2.8500, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.5400, vix=19.3400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +11.76%\n Annualized volatility: 12.13%\n Macro: fed_funds=4.8300, vix=19.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.117599, "annualized_vol": 0.121338, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240314_0402", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-14", "context_summary": "Regime: sideways. SPY trailing return: +8.9%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=502.15, trailing_return=+8.88%\nAnnualized volatility: 11.48%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4200, t10y3m_spread=-1.2900, breakeven_10y=2.3000, hy_oas=3.1500, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.8800, vix=13.7500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.88%\n Annualized volatility: 11.48%\n Macro: fed_funds=5.3300, vix=13.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.08882, "annualized_vol": 0.114843, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241121_0403", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-21", "context_summary": "Regime: sideways. SPY trailing return: +6.1%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=546.79, end=580.10, trailing_return=+6.09%\nAnnualized volatility: 12.28%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1000, t10y3m_spread=-0.2100, breakeven_10y=2.3500, hy_oas=2.6700, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.7800, vix=17.1600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.09%\n Annualized volatility: 12.28%\n Macro: fed_funds=4.5800, vix=17.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.060919, "annualized_vol": 0.122776, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240429_0404", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-29", "context_summary": "Regime: sideways. SPY trailing return: +4.2%, annualized vol: 11.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=476.10, end=496.18, trailing_return=+4.22%\nAnnualized volatility: 11.71%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.2900, t10y3m_spread=-0.7900, breakeven_10y=2.4300, hy_oas=3.1600, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=7.1700, vix=15.0300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.22%\n Annualized volatility: 11.71%\n Macro: fed_funds=5.3300, vix=15.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.04219, "annualized_vol": 0.117074, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240927_0405", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-27", "context_summary": "Regime: sideways. SPY trailing return: +4.1%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=540.09, end=562.22, trailing_return=+4.10%\nAnnualized volatility: 15.92%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.1900, t10y3m_spread=-0.8900, breakeven_10y=2.1600, hy_oas=3.1400, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.0800, vix=15.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.10%\n Annualized volatility: 15.92%\n Macro: fed_funds=4.8300, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.040974, "annualized_vol": 0.159157, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241003_0406", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-03", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=549.75, end=558.85, trailing_return=+1.65%\nAnnualized volatility: 16.00%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1600, t10y3m_spread=-0.9000, breakeven_10y=2.2100, hy_oas=3.0600, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.0800, vix=18.9000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.65%\n Annualized volatility: 16.00%\n Macro: fed_funds=4.8300, vix=18.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.016541, "annualized_vol": 0.160039, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240515_0407", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-15", "context_summary": "Regime: bull. SPY trailing return: +5.7%, annualized vol: 11.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=483.46, end=510.87, trailing_return=+5.67%\nAnnualized volatility: 11.59%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3600, t10y3m_spread=-0.9900, breakeven_10y=2.3300, hy_oas=3.1400, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=7.0900, vix=13.4200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.67%\n Annualized volatility: 11.59%\n Macro: fed_funds=5.3300, vix=13.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.056699, "annualized_vol": 0.11593, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240424_0408", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-24", "context_summary": "Regime: sideways. SPY trailing return: +3.2%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=478.11, end=493.64, trailing_return=+3.25%\nAnnualized volatility: 12.16%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.2500, t10y3m_spread=-0.8400, breakeven_10y=2.4100, hy_oas=3.2000, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=7.1000, vix=15.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.25%\n Annualized volatility: 12.16%\n Macro: fed_funds=5.3300, vix=15.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.032469, "annualized_vol": 0.121594, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240521_0409", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-21", "context_summary": "Regime: bull. SPY trailing return: +5.1%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=492.44, end=517.47, trailing_return=+5.08%\nAnnualized volatility: 11.05%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3800, t10y3m_spread=-1.0100, breakeven_10y=2.3300, hy_oas=3.0700, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=7.0200, vix=12.1500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.08%\n Annualized volatility: 11.05%\n Macro: fed_funds=5.3300, vix=12.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.050825, "annualized_vol": 0.110529, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240829_0410", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-29", "context_summary": "Regime: bull. SPY trailing return: +6.0%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=515.84, end=546.79, trailing_return=+6.00%\nAnnualized volatility: 14.33%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0100, t10y3m_spread=-1.3700, breakeven_10y=2.1500, hy_oas=3.1900, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.4600, vix=17.1100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.00%\n Annualized volatility: 14.33%\n Macro: fed_funds=5.3300, vix=17.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.060015, "annualized_vol": 0.14327, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240909_0411", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-09", "context_summary": "Regime: sideways. SPY trailing return: +0.1%, annualized vol: 15.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=528.50, end=529.22, trailing_return=+0.14%\nAnnualized volatility: 15.36%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0600, t10y3m_spread=-1.4100, breakeven_10y=2.0300, hy_oas=3.3900, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.3500, vix=22.3800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.14%\n Annualized volatility: 15.36%\n Macro: fed_funds=5.3300, vix=22.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.001373, "annualized_vol": 0.153639, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240301_0412", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-01", "context_summary": "Regime: sideways. SPY trailing return: +7.2%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=494.47, trailing_return=+7.22%\nAnnualized volatility: 11.57%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.2000, breakeven_10y=2.3300, hy_oas=3.2900, ig_oas=1.0000, ted_spread=0.0900, mortgage_30y=6.9400, vix=13.4000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.22%\n Annualized volatility: 11.57%\n Macro: fed_funds=5.3300, vix=13.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.07217, "annualized_vol": 0.11571, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241106_0413", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-06", "context_summary": "Regime: sideways. SPY trailing return: +6.7%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=530.87, end=566.55, trailing_return=+6.72%\nAnnualized volatility: 12.32%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0700, t10y3m_spread=-0.3800, breakeven_10y=2.2700, hy_oas=2.8600, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.7200, vix=20.4900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.72%\n Annualized volatility: 12.32%\n Macro: fed_funds=4.8300, vix=20.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.067207, "annualized_vol": 0.12323, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240506_0414", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-06", "context_summary": "Regime: sideways. SPY trailing return: +2.9%, annualized vol: 12.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=484.97, end=499.14, trailing_return=+2.92%\nAnnualized volatility: 12.03%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3100, t10y3m_spread=-0.9500, breakeven_10y=2.3500, hy_oas=3.0800, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.2200, vix=13.4900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.92%\n Annualized volatility: 12.03%\n Macro: fed_funds=5.3300, vix=13.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.029215, "annualized_vol": 0.120347, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241001_0415", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-01", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=543.84, end=563.66, trailing_return=+3.64%\nAnnualized volatility: 15.88%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.1500, t10y3m_spread=-0.9200, breakeven_10y=2.1800, hy_oas=3.0300, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.0800, vix=16.7300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.64%\n Annualized volatility: 15.88%\n Macro: fed_funds=4.8300, vix=16.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.03645, "annualized_vol": 0.15883, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240627_0416", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-27", "context_summary": "Regime: bull. SPY trailing return: +5.5%, annualized vol: 10.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=506.51, end=534.27, trailing_return=+5.48%\nAnnualized volatility: 10.70%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3900, t10y3m_spread=-1.1800, breakeven_10y=2.2600, hy_oas=3.1800, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.8700, vix=12.5500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.48%\n Annualized volatility: 10.70%\n Macro: fed_funds=5.3300, vix=12.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.054795, "annualized_vol": 0.107049, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240524_0417", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-24", "context_summary": "Regime: bull. SPY trailing return: +3.8%, annualized vol: 11.2%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=494.47, end=513.46, trailing_return=+3.84%\nAnnualized volatility: 11.16%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4400, t10y3m_spread=-0.9900, breakeven_10y=2.3000, hy_oas=3.1000, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.9400, vix=12.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.84%\n Annualized volatility: 11.16%\n Macro: fed_funds=5.3300, vix=12.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.038408, "annualized_vol": 0.111608, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240729_0418", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-29", "context_summary": "Regime: sideways. SPY trailing return: +9.2%, annualized vol: 10.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=488.46, end=533.22, trailing_return=+9.16%\nAnnualized volatility: 10.41%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1600, t10y3m_spread=-1.1800, breakeven_10y=2.2700, hy_oas=3.1000, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.7800, vix=16.3900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.16%\n Annualized volatility: 10.41%\n Macro: fed_funds=5.3300, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.091629, "annualized_vol": 0.104134, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240517_0419", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-17", "context_summary": "Regime: bull. SPY trailing return: +4.5%, annualized vol: 11.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=493.91, end=516.13, trailing_return=+4.50%\nAnnualized volatility: 11.77%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4000, t10y3m_spread=-1.0700, breakeven_10y=2.3100, hy_oas=3.0800, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.0200, vix=12.4200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.50%\n Annualized volatility: 11.77%\n Macro: fed_funds=5.3300, vix=12.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.04499, "annualized_vol": 0.117688, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240529_0420", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-29", "context_summary": "Regime: sideways. SPY trailing return: +3.7%, annualized vol: 11.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=498.58, end=517.22, trailing_return=+3.74%\nAnnualized volatility: 11.07%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4000, t10y3m_spread=-0.9200, breakeven_10y=2.3400, hy_oas=3.0900, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.9400, vix=12.9200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.74%\n Annualized volatility: 11.07%\n Macro: fed_funds=5.3300, vix=12.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.037392, "annualized_vol": 0.110667, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240611_0421", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-11", "context_summary": "Regime: sideways. SPY trailing return: +5.1%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=497.72, end=522.93, trailing_return=+5.07%\nAnnualized volatility: 10.94%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4000, t10y3m_spread=-1.0500, breakeven_10y=2.3100, hy_oas=3.1500, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.9900, vix=12.7400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.07%\n Annualized volatility: 10.94%\n Macro: fed_funds=5.3300, vix=12.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.050664, "annualized_vol": 0.109433, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240912_0422", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-12", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 15.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=534.10, end=542.99, trailing_return=+1.66%\nAnnualized volatility: 15.59%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0300, t10y3m_spread=-1.4500, breakeven_10y=2.0400, hy_oas=3.4400, ig_oas=1.0100, ted_spread=0.0900, mortgage_30y=6.3500, vix=17.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.66%\n Annualized volatility: 15.59%\n Macro: fed_funds=5.3300, vix=17.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.016649, "annualized_vol": 0.155946, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241126_0423", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-26", "context_summary": "Regime: sideways. SPY trailing return: +8.6%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=540.70, end=587.01, trailing_return=+8.56%\nAnnualized volatility: 12.12%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0600, t10y3m_spread=-0.3500, breakeven_10y=2.2900, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.8400, vix=14.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.56%\n Annualized volatility: 12.12%\n Macro: fed_funds=4.5800, vix=14.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.085645, "annualized_vol": 0.12122, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20241128_0424", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-28", "context_summary": "Regime: bull. SPY trailing return: +9.3%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=538.28, end=588.29, trailing_return=+9.29%\nAnnualized volatility: 11.28%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0600, t10y3m_spread=-0.3500, breakeven_10y=2.2600, hy_oas=2.6900, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.8100, vix=14.1000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.29%\n Annualized volatility: 11.28%\n Macro: fed_funds=4.5800, vix=14.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.092896, "annualized_vol": 0.112849, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20241219_0425", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-19", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=560.00, end=575.96, trailing_return=+2.85%\nAnnualized volatility: 11.56%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1500, t10y3m_spread=0.1400, breakeven_10y=2.3200, hy_oas=2.7300, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.6000, vix=27.6200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.85%\n Annualized volatility: 11.56%\n Macro: fed_funds=4.5800, vix=27.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.028489, "annualized_vol": 0.115556, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240226_0426", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-26", "context_summary": "Regime: sideways. SPY trailing return: +7.2%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=494.25, trailing_return=+7.17%\nAnnualized volatility: 12.08%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4100, t10y3m_spread=-1.2000, breakeven_10y=2.3000, hy_oas=3.2300, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.9000, vix=13.7500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.17%\n Annualized volatility: 12.08%\n Macro: fed_funds=5.3300, vix=13.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.071685, "annualized_vol": 0.120833, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240509_0427", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-09", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=480.85, end=504.90, trailing_return=+5.00%\nAnnualized volatility: 12.15%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3600, t10y3m_spread=-0.9700, breakeven_10y=2.3100, hy_oas=3.1000, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=7.2200, vix=13.0000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.00%\n Annualized volatility: 12.15%\n Macro: fed_funds=5.3300, vix=13.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.050026, "annualized_vol": 0.121532, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240215_0428", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-15", "context_summary": "Regime: sideways. SPY trailing return: +5.2%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=485.22, trailing_return=+5.21%\nAnnualized volatility: 11.62%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.2900, t10y3m_spread=-1.1600, breakeven_10y=2.3000, hy_oas=3.3800, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.6400, vix=14.3800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.21%\n Annualized volatility: 11.62%\n Macro: fed_funds=5.3300, vix=14.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.052102, "annualized_vol": 0.116153, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20241122_0429", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-22", "context_summary": "Regime: sideways. SPY trailing return: +6.7%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=546.84, end=583.22, trailing_return=+6.65%\nAnnualized volatility: 12.23%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0900, t10y3m_spread=-0.2000, breakeven_10y=2.3400, hy_oas=2.6600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8400, vix=16.8700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.65%\n Annualized volatility: 12.23%\n Macro: fed_funds=4.5800, vix=16.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.066519, "annualized_vol": 0.122326, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240607_0430", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-07", "context_summary": "Regime: sideways. SPY trailing return: +3.9%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=502.15, end=521.96, trailing_return=+3.94%\nAnnualized volatility: 10.95%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4400, t10y3m_spread=-1.2300, breakeven_10y=2.2800, hy_oas=3.2000, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.9900, vix=12.5800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.94%\n Annualized volatility: 10.95%\n Macro: fed_funds=5.3300, vix=12.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.039443, "annualized_vol": 0.109483, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240918_0431", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-18", "context_summary": "Regime: sideways. SPY trailing return: +3.7%, annualized vol: 15.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=531.55, end=551.47, trailing_return=+3.75%\nAnnualized volatility: 15.61%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0600, t10y3m_spread=-1.3000, breakeven_10y=2.1200, hy_oas=3.2500, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.2000, vix=17.6100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.75%\n Annualized volatility: 15.61%\n Macro: fed_funds=5.3300, vix=17.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.037458, "annualized_vol": 0.156118, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240408_0432", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-08", "context_summary": "Regime: sideways. SPY trailing return: +9.1%, annualized vol: 11.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=463.80, end=506.11, trailing_return=+9.12%\nAnnualized volatility: 11.02%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3400, t10y3m_spread=-1.0400, breakeven_10y=2.3700, hy_oas=3.1800, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8200, vix=16.0300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.12%\n Annualized volatility: 11.02%\n Macro: fed_funds=5.3300, vix=16.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.091239, "annualized_vol": 0.110209, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241114_0433", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-14", "context_summary": "Regime: sideways. SPY trailing return: +6.8%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=549.07, end=586.68, trailing_return=+6.85%\nAnnualized volatility: 12.14%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1700, t10y3m_spread=-0.1600, breakeven_10y=2.3500, hy_oas=2.6600, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.7900, vix=14.0200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.85%\n Annualized volatility: 12.14%\n Macro: fed_funds=4.5800, vix=14.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.068499, "annualized_vol": 0.121441, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240709_0434", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-09", "context_summary": "Regime: sideways. SPY trailing return: +7.5%, annualized vol: 10.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=505.69, end=543.84, trailing_return=+7.54%\nAnnualized volatility: 9.98%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3400, t10y3m_spread=-1.1800, breakeven_10y=2.2700, hy_oas=3.2000, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.54%\n Annualized volatility: 9.98%\n Macro: fed_funds=5.3300, vix=12.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.075428, "annualized_vol": 0.099764, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240307_0435", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-07", "context_summary": "Regime: sideways. SPY trailing return: +7.6%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=496.10, trailing_return=+7.57%\nAnnualized volatility: 11.58%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4400, t10y3m_spread=-1.3600, breakeven_10y=2.3000, hy_oas=3.2700, ig_oas=1.0100, ted_spread=0.0900, mortgage_30y=6.9400, vix=14.5000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.57%\n Annualized volatility: 11.58%\n Macro: fed_funds=5.3300, vix=14.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.075694, "annualized_vol": 0.115792, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241205_0436", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-05", "context_summary": "Regime: bull. SPY trailing return: +9.9%, annualized vol: 10.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=542.99, end=596.96, trailing_return=+9.94%\nAnnualized volatility: 10.47%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0600, t10y3m_spread=-0.2800, breakeven_10y=2.2900, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.8100, vix=13.4500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.94%\n Annualized volatility: 10.47%\n Macro: fed_funds=4.5800, vix=13.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.09939, "annualized_vol": 0.104728, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240528_0437", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-28", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 11.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=499.11, end=516.86, trailing_return=+3.56%\nAnnualized volatility: 11.21%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4700, t10y3m_spread=-1.0000, breakeven_10y=2.3200, hy_oas=3.1200, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.9400, vix=11.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.56%\n Annualized volatility: 11.21%\n Macro: fed_funds=5.3300, vix=11.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.035556, "annualized_vol": 0.112111, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240606_0438", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-06", "context_summary": "Regime: bull. SPY trailing return: +3.8%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=502.94, end=521.97, trailing_return=+3.78%\nAnnualized volatility: 11.14%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4300, t10y3m_spread=-1.2200, breakeven_10y=2.3000, hy_oas=3.2000, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=7.0300, vix=12.6300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.78%\n Annualized volatility: 11.14%\n Macro: fed_funds=5.3300, vix=12.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.037833, "annualized_vol": 0.111403, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240711_0439", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-11", "context_summary": "Regime: bull. SPY trailing return: +11.6%, annualized vol: 9.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=492.46, end=549.75, trailing_return=+11.63%\nAnnualized volatility: 9.53%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3400, t10y3m_spread=-1.1800, breakeven_10y=2.2700, hy_oas=3.1700, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +11.63%\n Annualized volatility: 9.53%\n Macro: fed_funds=5.3300, vix=12.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.116326, "annualized_vol": 0.095326, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241115_0440", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-15", "context_summary": "Regime: sideways. SPY trailing return: +7.0%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=544.76, end=582.90, trailing_return=+7.00%\nAnnualized volatility: 12.23%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0900, t10y3m_spread=-0.1800, breakeven_10y=2.3300, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7800, vix=14.3100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.00%\n Annualized volatility: 12.23%\n Macro: fed_funds=4.5800, vix=14.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.070026, "annualized_vol": 0.122316, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240419_0441", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-19", "context_summary": "Regime: sideways. SPY trailing return: +3.2%, annualized vol: 11.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=472.39, end=487.65, trailing_return=+3.23%\nAnnualized volatility: 11.69%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3400, t10y3m_spread=-0.8200, breakeven_10y=2.4000, hy_oas=3.3900, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=7.1000, vix=18.0000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.23%\n Annualized volatility: 11.69%\n Macro: fed_funds=5.3300, vix=18.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.032308, "annualized_vol": 0.11695, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240308_0442", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-08", "context_summary": "Regime: sideways. SPY trailing return: +8.6%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=501.02, trailing_return=+8.64%\nAnnualized volatility: 11.61%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.4100, t10y3m_spread=-1.3800, breakeven_10y=2.2800, hy_oas=3.2700, ig_oas=1.0000, ted_spread=0.0900, mortgage_30y=6.8800, vix=14.4400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.64%\n Annualized volatility: 11.61%\n Macro: fed_funds=5.3300, vix=14.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.086372, "annualized_vol": 0.116086, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240426_0443", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-26", "context_summary": "Regime: sideways. SPY trailing return: +4.6%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=469.95, end=491.53, trailing_return=+4.59%\nAnnualized volatility: 12.10%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.2600, t10y3m_spread=-0.7700, breakeven_10y=2.4200, hy_oas=3.2400, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=7.1700, vix=15.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.59%\n Annualized volatility: 12.10%\n Macro: fed_funds=5.3300, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.045921, "annualized_vol": 0.120975, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241028_0444", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-28", "context_summary": "Regime: sideways. SPY trailing return: +9.0%, annualized vol: 14.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=521.92, end=568.85, trailing_return=+8.99%\nAnnualized volatility: 14.16%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1400, t10y3m_spread=-0.4800, breakeven_10y=2.2900, hy_oas=2.8900, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.5400, vix=20.3300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.99%\n Annualized volatility: 14.16%\n Macro: fed_funds=4.8300, vix=20.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.089915, "annualized_vol": 0.141631, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240605_0445", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-05", "context_summary": "Regime: sideways. SPY trailing return: +3.7%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=497.59, end=515.84, trailing_return=+3.67%\nAnnualized volatility: 10.91%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4400, t10y3m_spread=-1.1900, breakeven_10y=2.3100, hy_oas=3.2200, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=7.0300, vix=13.1600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.67%\n Annualized volatility: 10.91%\n Macro: fed_funds=5.3300, vix=13.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.036676, "annualized_vol": 0.109053, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240228_0446", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-28", "context_summary": "Regime: sideways. SPY trailing return: +7.0%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=493.35, trailing_return=+6.97%\nAnnualized volatility: 11.84%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3900, t10y3m_spread=-1.1400, breakeven_10y=2.3200, hy_oas=3.2600, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.9000, vix=13.4300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.97%\n Annualized volatility: 11.84%\n Macro: fed_funds=5.3300, vix=13.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.069743, "annualized_vol": 0.118423, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241031_0447", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-31", "context_summary": "Regime: sideways. SPY trailing return: +12.2%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=507.97, end=569.80, trailing_return=+12.17%\nAnnualized volatility: 12.08%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1400, t10y3m_spread=-0.3800, breakeven_10y=2.3400, hy_oas=2.8000, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.5400, vix=20.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +12.17%\n Annualized volatility: 12.08%\n Macro: fed_funds=4.8300, vix=20.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.121716, "annualized_vol": 0.12082, "has_text": true, "text_chars": 9047}} +{"id": "T7_all_20240712_0448", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-12", "context_summary": "Regime: sideways. SPY trailing return: +10.9%, annualized vol: 9.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=491.57, end=545.01, trailing_return=+10.87%\nAnnualized volatility: 9.31%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3000, t10y3m_spread=-1.2400, breakeven_10y=2.2500, hy_oas=3.1800, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.8900, vix=12.9200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.87%\n Annualized volatility: 9.31%\n Macro: fed_funds=5.3300, vix=12.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.108723, "annualized_vol": 0.093126, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240830_0449", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-30", "context_summary": "Regime: bull. SPY trailing return: +4.8%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=521.97, end=546.84, trailing_return=+4.77%\nAnnualized volatility: 14.33%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0000, t10y3m_spread=-1.3500, breakeven_10y=2.1600, hy_oas=3.1500, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.3500, vix=15.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.77%\n Annualized volatility: 14.33%\n Macro: fed_funds=5.3300, vix=15.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.047658, "annualized_vol": 0.143282, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240516_0450", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-16", "context_summary": "Regime: bull. SPY trailing return: +6.9%, annualized vol: 11.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=483.89, end=517.19, trailing_return=+6.88%\nAnnualized volatility: 11.75%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.1750, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3700, t10y3m_spread=-1.0900, breakeven_10y=2.3100, hy_oas=3.1300, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=7.0900, vix=12.4500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.88%\n Annualized volatility: 11.75%\n Macro: fed_funds=5.3300, vix=12.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.068816, "annualized_vol": 0.117507, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240422_0451", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-22", "context_summary": "Regime: sideways. SPY trailing return: +1.8%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=474.96, end=483.40, trailing_return=+1.78%\nAnnualized volatility: 11.85%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3500, t10y3m_spread=-0.8300, breakeven_10y=2.4100, hy_oas=3.3700, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=7.1000, vix=18.7100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.78%\n Annualized volatility: 11.85%\n Macro: fed_funds=5.3300, vix=18.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017762, "annualized_vol": 0.118489, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240923_0452", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-23", "context_summary": "Regime: sideways. SPY trailing return: +4.3%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=535.11, end=558.25, trailing_return=+4.32%\nAnnualized volatility: 15.96%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.1800, t10y3m_spread=-1.0200, breakeven_10y=2.1500, hy_oas=3.1500, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.0900, vix=16.1500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.32%\n Annualized volatility: 15.96%\n Macro: fed_funds=4.8300, vix=16.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.043236, "annualized_vol": 0.159604, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240603_0453", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-03", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 11.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=501.02, end=514.84, trailing_return=+2.76%\nAnnualized volatility: 11.16%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3800, t10y3m_spread=-0.9500, breakeven_10y=2.3500, hy_oas=3.2000, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=7.0300, vix=12.9200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.76%\n Annualized volatility: 11.16%\n Macro: fed_funds=5.3300, vix=12.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.02758, "annualized_vol": 0.111562, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240409_0454", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-09", "context_summary": "Regime: sideways. SPY trailing return: +9.2%, annualized vol: 11.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=463.59, end=506.40, trailing_return=+9.23%\nAnnualized volatility: 10.99%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3600, t10y3m_spread=-1.0100, breakeven_10y=2.3800, hy_oas=3.1500, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.8200, vix=15.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.23%\n Annualized volatility: 10.99%\n Macro: fed_funds=5.3300, vix=15.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.092331, "annualized_vol": 0.109895, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240717_0455", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-17", "context_summary": "Regime: sideways. SPY trailing return: +14.4%, annualized vol: 9.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=483.40, end=553.22, trailing_return=+14.44%\nAnnualized volatility: 9.19%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.2600, t10y3m_spread=-1.2600, breakeven_10y=2.2600, hy_oas=3.0800, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8900, vix=13.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +14.44%\n Annualized volatility: 9.19%\n Macro: fed_funds=5.3300, vix=13.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.144443, "annualized_vol": 0.091864, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240321_0456", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-21", "context_summary": "Regime: bull. SPY trailing return: +10.2%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=508.11, trailing_return=+10.17%\nAnnualized volatility: 11.30%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3200, t10y3m_spread=-1.2000, breakeven_10y=2.3100, hy_oas=3.1400, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.7400, vix=13.0400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.17%\n Annualized volatility: 11.30%\n Macro: fed_funds=5.3300, vix=13.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.10175, "annualized_vol": 0.113047, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240828_0457", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-28", "context_summary": "Regime: bull. SPY trailing return: +6.7%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=515.26, end=549.99, trailing_return=+6.74%\nAnnualized volatility: 14.26%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0000, t10y3m_spread=-1.4000, breakeven_10y=2.1500, hy_oas=3.1700, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.4600, vix=15.4300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.74%\n Annualized volatility: 14.26%\n Macro: fed_funds=5.3300, vix=15.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.067396, "annualized_vol": 0.142566, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241025_0458", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-25", "context_summary": "Regime: sideways. SPY trailing return: +7.0%, annualized vol: 14.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=531.82, end=569.04, trailing_return=+7.00%\nAnnualized volatility: 14.51%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1400, t10y3m_spread=-0.4900, breakeven_10y=2.3000, hy_oas=2.9300, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.5400, vix=19.0800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.00%\n Annualized volatility: 14.51%\n Macro: fed_funds=4.8300, vix=19.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.069993, "annualized_vol": 0.145077, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240501_0459", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-05-01", "context_summary": "Regime: sideways. SPY trailing return: +2.2%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=479.36, end=490.05, trailing_return=+2.23%\nAnnualized volatility: 11.77%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3500, t10y3m_spread=-0.7700, breakeven_10y=2.4100, hy_oas=3.1800, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=7.1700, vix=15.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.23%\n Annualized volatility: 11.77%\n Macro: fed_funds=5.3300, vix=15.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.022312, "annualized_vol": 0.117661, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240410_0460", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-10", "context_summary": "Regime: sideways. SPY trailing return: +9.3%, annualized vol: 11.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=463.91, end=506.98, trailing_return=+9.28%\nAnnualized volatility: 10.98%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3800, t10y3m_spread=-1.0700, breakeven_10y=2.3600, hy_oas=3.1400, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.8200, vix=14.9800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.28%\n Annualized volatility: 10.98%\n Macro: fed_funds=5.3300, vix=15.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.092837, "annualized_vol": 0.109826, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240412_0461", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-04-12", "context_summary": "Regime: sideways. SPY trailing return: +9.7%, annualized vol: 11.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=505.69, trailing_return=+9.65%\nAnnualized volatility: 11.26%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0230, unemployment=3.9000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.3700, t10y3m_spread=-0.8900, breakeven_10y=2.4000, hy_oas=3.1600, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.8800, vix=14.9100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.65%\n Annualized volatility: 11.26%\n Macro: fed_funds=5.3300, vix=14.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.0965, "annualized_vol": 0.112562, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240223_0462", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-23", "context_summary": "Regime: sideways. SPY trailing return: +7.1%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=493.91, trailing_return=+7.09%\nAnnualized volatility: 12.25%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3600, t10y3m_spread=-1.1200, breakeven_10y=2.3100, hy_oas=3.2200, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.9000, vix=14.5400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.09%\n Annualized volatility: 12.25%\n Macro: fed_funds=5.3300, vix=14.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.070946, "annualized_vol": 0.122544, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240806_0463", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-06", "context_summary": "Regime: sideways. SPY trailing return: -0.2%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=507.81, end=506.72, trailing_return=-0.22%\nAnnualized volatility: 12.90%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1100, t10y3m_spread=-1.5700, breakeven_10y=2.0700, hy_oas=3.9300, ig_oas=1.1200, ted_spread=0.0900, mortgage_30y=6.7300, vix=38.5700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -0.22%\n Annualized volatility: 12.90%\n Macro: fed_funds=5.3300, vix=38.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.002155, "annualized_vol": 0.128978, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240905_0464", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-05", "context_summary": "Regime: bull. SPY trailing return: +3.2%, annualized vol: 14.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=522.93, end=539.60, trailing_return=+3.19%\nAnnualized volatility: 14.95%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0100, t10y3m_spread=-1.4100, breakeven_10y=2.0700, hy_oas=3.3500, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.3500, vix=21.3200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.19%\n Annualized volatility: 14.95%\n Macro: fed_funds=5.3300, vix=21.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.031863, "annualized_vol": 0.149452, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241220_0465", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-20", "context_summary": "Regime: sideways. SPY trailing return: +2.4%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=562.22, end=575.78, trailing_return=+2.41%\nAnnualized volatility: 11.54%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.2500, t10y3m_spread=0.2200, breakeven_10y=2.2900, hy_oas=2.9100, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=24.0900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.41%\n Annualized volatility: 11.54%\n Macro: fed_funds=4.3300, vix=24.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.024113, "annualized_vol": 0.115437, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241231_0466", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-31", "context_summary": "Regime: sideways. SPY trailing return: +3.0%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=562.89, end=579.81, trailing_return=+3.01%\nAnnualized volatility: 12.29%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.3100, t10y3m_spread=0.1800, breakeven_10y=2.3100, hy_oas=2.9400, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.8500, vix=17.4000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.01%\n Annualized volatility: 12.29%\n Macro: fed_funds=4.3300, vix=17.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.030053, "annualized_vol": 0.12286, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240930_0467", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-30", "context_summary": "Regime: sideways. SPY trailing return: +3.4%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=543.21, end=561.41, trailing_return=+3.35%\nAnnualized volatility: 15.90%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.2000, t10y3m_spread=-0.9300, breakeven_10y=2.1500, hy_oas=3.1400, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.0800, vix=16.9600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.35%\n Annualized volatility: 15.90%\n Macro: fed_funds=4.8300, vix=17.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.033504, "annualized_vol": 0.15903, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240823_0468", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-23", "context_summary": "Regime: bull. SPY trailing return: +6.1%, annualized vol: 14.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=513.60, end=544.76, trailing_return=+6.07%\nAnnualized volatility: 14.38%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1300, t10y3m_spread=-1.4200, breakeven_10y=2.1000, hy_oas=3.2100, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.4600, vix=17.5500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.07%\n Annualized volatility: 14.38%\n Macro: fed_funds=5.3300, vix=17.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.060662, "annualized_vol": 0.143826, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241029_0469", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-29", "context_summary": "Regime: sideways. SPY trailing return: +12.6%, annualized vol: 13.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=506.72, end=570.60, trailing_return=+12.61%\nAnnualized volatility: 13.55%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1600, t10y3m_spread=-0.4200, breakeven_10y=2.2900, hy_oas=2.8200, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.5400, vix=19.8000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +12.61%\n Annualized volatility: 13.55%\n Macro: fed_funds=4.8300, vix=19.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.126081, "annualized_vol": 0.135452, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240220_0470", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-20", "context_summary": "Regime: sideways. SPY trailing return: +5.4%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=486.13, trailing_return=+5.41%\nAnnualized volatility: 11.49%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3400, t10y3m_spread=-1.1400, breakeven_10y=2.3300, hy_oas=3.3400, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.7700, vix=14.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.41%\n Annualized volatility: 11.49%\n Macro: fed_funds=5.3300, vix=14.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.054085, "annualized_vol": 0.11491, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241125_0471", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-25", "context_summary": "Regime: sideways. SPY trailing return: +6.0%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=552.06, end=585.03, trailing_return=+5.97%\nAnnualized volatility: 12.24%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0400, t10y3m_spread=-0.2200, breakeven_10y=2.3400, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.8400, vix=15.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.97%\n Annualized volatility: 12.24%\n Macro: fed_funds=4.5800, vix=15.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.059709, "annualized_vol": 0.122384, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240216_0472", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-16", "context_summary": "Regime: sideways. SPY trailing return: +5.9%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=488.56, trailing_return=+5.94%\nAnnualized volatility: 11.51%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3200, t10y3m_spread=-1.1900, breakeven_10y=2.3000, hy_oas=3.3500, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.7700, vix=14.0100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.94%\n Annualized volatility: 11.51%\n Macro: fed_funds=5.3300, vix=14.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.059361, "annualized_vol": 0.115121, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20240304_0473", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-04", "context_summary": "Regime: sideways. SPY trailing return: +8.2%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=499.11, trailing_return=+8.22%\nAnnualized volatility: 11.58%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3500, t10y3m_spread=-1.2300, breakeven_10y=2.3200, hy_oas=3.3200, ig_oas=1.0100, ted_spread=0.0900, mortgage_30y=6.9400, vix=13.1100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.22%\n Annualized volatility: 11.58%\n Macro: fed_funds=5.3300, vix=13.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.082236, "annualized_vol": 0.115773, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240708_0474", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-07-08", "context_summary": "Regime: sideways. SPY trailing return: +8.2%, annualized vol: 10.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=501.91, end=543.21, trailing_return=+8.23%\nAnnualized volatility: 10.25%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.5690, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.3200, t10y3m_spread=-1.1800, breakeven_10y=2.2800, hy_oas=3.2700, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.23%\n Annualized volatility: 10.25%\n Macro: fed_funds=5.3300, vix=12.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.082295, "annualized_vol": 0.102465, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240821_0475", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-21", "context_summary": "Regime: bull. SPY trailing return: +5.9%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=516.86, end=547.19, trailing_return=+5.87%\nAnnualized volatility: 14.30%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.1700, t10y3m_spread=-1.4700, breakeven_10y=2.0700, hy_oas=3.2500, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.4900, vix=15.8800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.87%\n Annualized volatility: 14.30%\n Macro: fed_funds=5.3300, vix=15.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.058671, "annualized_vol": 0.143044, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240809_0476", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-08-09", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 13.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=510.87, end=519.71, trailing_return=+1.73%\nAnnualized volatility: 13.73%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.0620, unemployment=4.2000, gdp_growth_qoq=23478.5700, t10y2y_spread=-0.0500, t10y3m_spread=-1.3500, breakeven_10y=2.1200, hy_oas=3.4800, ig_oas=1.0500, ted_spread=0.0900, mortgage_30y=6.4700, vix=23.7900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.73%\n Annualized volatility: 13.73%\n Macro: fed_funds=5.3300, vix=23.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017317, "annualized_vol": 0.137334, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240902_0477", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-02", "context_summary": "Regime: bull. SPY trailing return: +5.8%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=521.96, end=552.06, trailing_return=+5.77%\nAnnualized volatility: 14.26%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0000, t10y3m_spread=-1.3000, breakeven_10y=2.1500, hy_oas=3.1700, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.3500, vix=15.0000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.77%\n Annualized volatility: 14.26%\n Macro: fed_funds=5.3300, vix=15.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.057679, "annualized_vol": 0.142611, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241112_0478", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-12", "context_summary": "Regime: sideways. SPY trailing return: +7.3%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=548.08, end=588.22, trailing_return=+7.32%\nAnnualized volatility: 12.25%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.0400, t10y3m_spread=-0.3300, breakeven_10y=2.3500, hy_oas=2.6600, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.7900, vix=14.9700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.32%\n Annualized volatility: 12.25%\n Macro: fed_funds=4.5800, vix=15.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.073241, "annualized_vol": 0.122462, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240625_0479", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-25", "context_summary": "Regime: sideways. SPY trailing return: +4.1%, annualized vol: 10.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=510.64, end=531.55, trailing_return=+4.10%\nAnnualized volatility: 10.70%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4600, t10y3m_spread=-1.2500, breakeven_10y=2.2200, hy_oas=3.1900, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.8700, vix=13.3300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.10%\n Annualized volatility: 10.70%\n Macro: fed_funds=5.3300, vix=13.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.040952, "annualized_vol": 0.106987, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240926_0480", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-26", "context_summary": "Regime: sideways. SPY trailing return: +4.1%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=537.70, end=560.00, trailing_return=+4.15%\nAnnualized volatility: 15.95%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.2600, t10y3m_spread=-0.9000, breakeven_10y=2.1800, hy_oas=3.1900, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.0900, vix=15.4100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.15%\n Annualized volatility: 15.95%\n Macro: fed_funds=4.8300, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.04149, "annualized_vol": 0.159494, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241108_0481", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-11-08", "context_summary": "Regime: sideways. SPY trailing return: +8.0%, annualized vol: 12.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=541.67, end=585.12, trailing_return=+8.02%\nAnnualized volatility: 12.65%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=316.5280, unemployment=4.2000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1000, t10y3m_spread=-0.3200, breakeven_10y=2.3300, hy_oas=2.7300, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.7900, vix=15.2000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.02%\n Annualized volatility: 12.65%\n Macro: fed_funds=4.8300, vix=15.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.080219, "annualized_vol": 0.126501, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240903_0482", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-03", "context_summary": "Regime: bull. SPY trailing return: +5.8%, annualized vol: 14.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=521.96, end=552.06, trailing_return=+5.77%\nAnnualized volatility: 14.26%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0000, t10y3m_spread=-1.3000, breakeven_10y=2.1500, hy_oas=3.1700, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.3500, vix=15.0000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.77%\n Annualized volatility: 14.26%\n Macro: fed_funds=5.3300, vix=15.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.057679, "annualized_vol": 0.142611, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240322_0483", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-03-22", "context_summary": "Regime: bull. SPY trailing return: +10.5%, annualized vol: 11.2%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=509.79, trailing_return=+10.54%\nAnnualized volatility: 11.20%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=312.3450, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3500, t10y3m_spread=-1.2100, breakeven_10y=2.3400, hy_oas=3.0500, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.8700, vix=12.9200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.54%\n Annualized volatility: 11.20%\n Macro: fed_funds=5.3300, vix=12.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.105391, "annualized_vol": 0.112039, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240618_0484", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-18", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=508.83, end=534.10, trailing_return=+4.97%\nAnnualized volatility: 10.80%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4700, t10y3m_spread=-1.2400, breakeven_10y=2.2200, hy_oas=3.2600, ig_oas=0.9500, ted_spread=0.0900, mortgage_30y=6.9500, vix=12.7500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.97%\n Annualized volatility: 10.80%\n Macro: fed_funds=5.3300, vix=12.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.049673, "annualized_vol": 0.107959, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240911_0485", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-09-11", "context_summary": "Regime: sideways. SPY trailing return: +1.4%, annualized vol: 15.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=529.88, end=537.48, trailing_return=+1.43%\nAnnualized volatility: 15.46%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=314.7320, unemployment=4.1000, gdp_growth_qoq=23478.5700, t10y2y_spread=0.0600, t10y3m_spread=-1.4100, breakeven_10y=2.0200, hy_oas=3.4600, ig_oas=1.0100, ted_spread=0.0900, mortgage_30y=6.3500, vix=19.0800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.43%\n Annualized volatility: 15.46%\n Macro: fed_funds=5.3300, vix=19.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.014335, "annualized_vol": 0.154605, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241216_0486", "template": "T7", "complexity": 4, "split": "val", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-12-16", "context_summary": "Regime: bull. SPY trailing return: +6.3%, annualized vol: 9.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=558.25, end=593.57, trailing_return=+6.33%\nAnnualized volatility: 9.95%\nMacro indicators: fed_funds_rate=4.5800, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1500, t10y3m_spread=0.0600, breakeven_10y=2.3300, hy_oas=2.6800, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.6000, vix=13.8100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.33%\n Annualized volatility: 9.95%\n Macro: fed_funds=4.5800, vix=13.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.063282, "annualized_vol": 0.099462, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241011_0487", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-11", "context_summary": "Regime: sideways. SPY trailing return: +4.6%, annualized vol: 15.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=541.27, end=565.99, trailing_return=+4.57%\nAnnualized volatility: 15.79%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1100, t10y3m_spread=-0.6600, breakeven_10y=2.3300, hy_oas=2.9900, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.3200, vix=20.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.57%\n Annualized volatility: 15.79%\n Macro: fed_funds=4.8300, vix=20.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.045665, "annualized_vol": 0.15792, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20240613_0488", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-06-13", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=503.46, end=528.50, trailing_return=+4.97%\nAnnualized volatility: 10.89%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=313.0440, unemployment=4.1000, gdp_growth_qoq=23286.5080, t10y2y_spread=-0.4400, t10y3m_spread=-1.2000, breakeven_10y=2.2200, hy_oas=3.0900, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.9900, vix=12.0400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.97%\n Annualized volatility: 10.89%\n Macro: fed_funds=5.3300, vix=12.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.049737, "annualized_vol": 0.108875, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20241024_0489", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-10-24", "context_summary": "Regime: sideways. SPY trailing return: +5.3%, annualized vol: 14.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=539.46, end=567.81, trailing_return=+5.26%\nAnnualized volatility: 14.84%\nMacro indicators: fed_funds_rate=4.8300, cpi_yoy=315.6310, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.1700, t10y3m_spread=-0.4900, breakeven_10y=2.3100, hy_oas=2.9500, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.4400, vix=19.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.26%\n Annualized volatility: 14.84%\n Macro: fed_funds=4.8300, vix=19.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.052564, "annualized_vol": 0.148384, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20240214_0490", "template": "T7", "complexity": 4, "split": "val", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2024-02-14", "context_summary": "Regime: sideways. SPY trailing return: +4.3%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=461.19, end=480.85, trailing_return=+4.26%\nAnnualized volatility: 11.61%\nMacro indicators: fed_funds_rate=5.3300, cpi_yoy=310.9670, unemployment=3.9000, gdp_growth_qoq=23082.1190, t10y2y_spread=-0.3300, t10y3m_spread=-1.1400, breakeven_10y=2.2900, hy_oas=3.3600, ig_oas=0.9900, ted_spread=0.0900, mortgage_30y=6.6400, vix=15.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.26%\n Annualized volatility: 11.61%\n Macro: fed_funds=5.3300, vix=15.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.042627, "annualized_vol": 0.116111, "has_text": true, "text_chars": 9046}}