{"id": "T1_all_20171211_0000", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2017-12-11", "context_summary": "ETH-USD over past 60 days: cumulative return +37.7%, annualized vol 79.6%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=320.88, end=441.72, cumulative_return=+37.7%, annualized_volatility=79.6%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 247.805, 'unemployment': 4.1, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.58, 't10y3m_spread': 1.1, 'breakeven_10y': 1.88, 'hy_oas': 3.63, 'ig_oas': 1.02, 'ted_spread': 0.29, 'mortgage_30y': 3.94, 'vix': 9.729999542236328}\nMarket regime: sideways\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": 0.499878, "explanation": "The actual 21-day forward return for ETH-USD starting 2017-12-11 was +49.99%, which classifies as 'positive'.", "metadata": {"future_return": 0.499878, "horizon_days": 21, "hist_return": 0.376575, "annualized_vol": 0.795546, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180613_0005", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2018-06-13", "context_summary": "BTC-USD over past 60 days: cumulative return -17.6%, annualized vol 53.8%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=7986.24, end=6582.36, cumulative_return=-17.6%, annualized_volatility=53.8%\nMacro context: {'fed_funds_rate': 1.7, 'cpi_yoy': 251.018, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.42, 't10y3m_spread': 1.04, 'breakeven_10y': 2.13, 'hy_oas': 3.38, 'ig_oas': 1.22, 'ted_spread': 0.45, 'mortgage_30y': 4.54, 'vix': 12.34000015258789}\nMarket regime: sideways\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": 0.039001, "explanation": "The actual 21-day forward return for BTC-USD starting 2018-06-13 was +3.90%, which classifies as 'positive'.", "metadata": {"future_return": 0.039001, "horizon_days": 21, "hist_return": -0.175787, "annualized_vol": 0.5384, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160127_0008", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2016-01-27", "context_summary": "QUAL over past 60 days: cumulative return -7.6%, annualized vol 17.6%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=56.42, end=52.15, cumulative_return=-7.6%, annualized_volatility=17.6%\nMacro context: {'fed_funds_rate': 0.38, 'cpi_yoy': 237.652, 'unemployment': 4.8, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.16, 't10y3m_spread': 1.7, 'breakeven_10y': 1.36, 'hy_oas': 7.83, 'ig_oas': 1.99, 'ted_spread': 0.31, 'mortgage_30y': 3.81, 'vix': 22.5}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-26] [\"Skyworks, Cirrus: Apple \\u2018Capitulation\\u2019 Will Be the Buy Sign, Says Pac Crest When Apple (AAPL) files fiscal Q1 results tomorrow, Tuesday, after the closing bell, it\\u2019ll be time to buy shares of SkyworksSolutions (SWKS) and Cirrus Logic (CRUS), according to John Vinh with Pacific Crest Securities in a note to clients today.Apple\\u2019s numbers, after months of hand-wringing about the volume of iPhone shipments that may happen in March \\u2014 something that carried right through to today \\u2014 is expected by Vinh to lead to a \\\"reset in expectations\\u201d that \\\"would be viewed as a positive catalyst for suppliers CRUS and SWKS.\\\"The stocks already probably reflect the worst for Cirrus and Skyworks, he writes:Read further...\", \"Apple Q1 Capitulation to Boost Cirrus, Skyworks Weaker-than-expected results and guidance from Apple is anticipated and would prove a catalyst to suppliers.\", \"Apple Earnings: 3 Supply Chain Stocks to Watch Asian suppliers are down 30% but don\\u2019t rush in: Market share gainers with strong cash flows are best bets.\", \"Can Tim Cook solve Apple\\u2019s China challenge? Chinese market holds the key to Apple\\u2019s earnings China, powered by a swelling middle class, last year became Apple Inc.\\u2019s biggest market after the Americas.\", \"10 stock market \\u2018darlings\\u2019 you may want to break up with Credit Suisse has identified the stocks most commonly held by funds \\u2014 and recommends selling a lot of them Credit Suisse has identified the stocks most commonly held by funds \\u2014 and recommends selling a lot of them.\", \"Here\\u2019s the chart that predicts Apple shares are headed for the $70s Critical intelligence before the U.S. stock market opens Apple reports Tuesday and a lot is on the line, both for investors in the stock and those in the S&P 500. The gloomsters won\\u2019t be silenced. Here\\u2019s one call that says the stock is headed to $70.\", \"The turning point in the stock market starts now Company earnings and economic reports support a rebound in equities Company earnings and economic reports support a rebound in equities, writes Tim Mullaney.\", \"Apple: Ahead of FYQ1 Report, Estimates Still Coming Down Shares of Apple (AAPL) are up 13 cents at $99.57, reversing losses at the open, as the company heads toward its fiscal Q1 report this afternoon, after the closing bell.Analysts are, on average, are modeling $76.6 billion and $3.23 per share. That includes an estimate for Apple to have sold 75 million iPhones, according to FactSet.For the March forecast, the Street is currently modeling $55.41 billion and $2.21 per share. That includes an iPhone number of 54 million units.There\\u2019s still time for analysts to get their vote in for tonight\\u2019s report. A couple are also still cutting their iPhone numbers for the full year that ends in September.Read further...\", \"Apple investors bracing for first decline in iPhone sales What to expect from Apple earnings, planned for Tuesday afternoon Apple is p\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": 0.034979, "explanation": "The actual 21-day forward return for QUAL starting 2016-01-27 was +3.50%, which classifies as 'positive'.", "metadata": {"future_return": 0.034979, "horizon_days": 21, "hist_return": -0.075668, "annualized_vol": 0.175828, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210326_0011", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2021-03-26", "context_summary": "FXI over past 60 days: cumulative return -0.4%, annualized vol 29.5%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=40.62, end=40.47, cumulative_return=-0.4%, annualized_volatility=29.5%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 264.961, 'unemployment': 6.1, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.49, 't10y3m_spread': 1.61, 'breakeven_10y': 2.32, 'hy_oas': 3.53, 'ig_oas': 1.02, 'ted_spread': 0.17, 'mortgage_30y': 3.17, 'vix': 19.809999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-03-25] [\"Playdate's mirror app links the handheld to a PC for streaming and control When Panic's Playdate portable console ships, you'll be able to plug it into a PC to mirror the screen for streaming, or control it from the computer.\", \"Gillmor Gang: Grifters Paradise The other day, I attended a celebration of one of the pioneers of collaboration technology, Ray Ozzie. The father of Lotus Notes, Ozzie left Lotus and his startup firm Iris after a hostile takeover by IBM, and eventually joined Microsoft when that company acquired his next startup, Groove. Ray's peers and partners gathered in a Zoom chat, with a tour of Ray's early days including amazing hardware like a touchscreen based enterprise chat system called Plato, and these strange things called floppy disks with the earliest source code for DOS and other prehistoric things called operating systems.\", \"SHAREHOLDER ALERT BY FORMER LOUISIANA ATTORNEY GENERAL: KSF REMINDS EBIX, EH, FUBO, MPLN INVESTORS of Lead Plaintiff Deadline in Class Action Lawsuits NEW ORLEANS, March 24, 2021 (GLOBE NEWSWIRE) -- Kahn Swick & Foti, LLC (\\u201cKSF\\u201d) and KSF partner, former Attorney General of Louisiana, Charles C. Foti, Jr., remind investors of pending deadlines in the following securities class action lawsuits: EHang Holdings Limited (EH) Class Period: 12/12/2019 \\u2013 2/16/2021 (2/16/21, purchases at or above the price of $112.00).Lead Plaintiff Motion Deadline: April 19, 2021SECURITIES FRAUD To learn more, visit https://www.ksfcounsel.com/cases/nasdaqgm-eh/ fuboTV Inc. (FUBO) Class Period: 3/23/2020 \\u2013 1/4/2021Lead Plaintiff Motion Deadline: April 19, 2021SECURITIES FRAUD To learn more, visit https://www.ksfcounsel.com/cases/nyse-fubo/ Ebix, Inc. (EBIX) Class Period: 11/9/2020 - 2/19/2021Lead Plaintiff Motion Deadline: April 23, 2021SECURITIES FRAUD To learn more, visit https://www.ksfcounsel.com/cases/nasdaqgs-ebix/ MultiPlan Corporation f/k/a Churchill Capital Corp. III (MPLN) Class Period: 7/12/2020 - 11/10/2020 and/or were holders of Churchill Capital Corp. III (\\u201cChurchill\\u201d) Class A common stock entitled to vote on Churchill\\u2019s merger with and acquisition of Polaris Parent Corp. and its consolidated subsidiaries completed in October 2020.Lead Plaintiff Motion Deadline: April 26, 2021SECURITIES FRAUD, MISLEADING PROSPECTUSTo learn more, visit https://www.ksfcounsel.com/cases/nyse-mpln/ If you purchased shares of the above companies and would like to discuss your legal rights and your right to recover for your economic loss, you may, without obligation or cost to you, contact KSF Managing Partner, Lewis Kahn, toll-free at 1-877-515-1850, via email (Lewis.Kahn@KSFcounsel.com), or via the case links above. If you wish to serve as a Lead Plaintiff in the class action, you must petition the Court on or before the Lead Plaintiff Motion deadline. About KSF, whose partners include former Louisiana Attorney General Charles C. Foti, Jr., is one of the nation\\u2019s premier boutique securities\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": 0.004285, "explanation": "The actual 21-day forward return for FXI starting 2021-03-26 was +0.43%, which classifies as 'flat'.", "metadata": {"future_return": 0.004285, "horizon_days": 21, "hist_return": -0.003517, "annualized_vol": 0.29462, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210520_0014", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-05-20", "context_summary": "DOT-USD over past 60 days: cumulative return -31.4%, annualized vol 116.7%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=36.79, end=25.23, cumulative_return=-31.4%, annualized_volatility=116.7%\nMacro context: {'fed_funds_rate': 0.06, 'cpi_yoy': 268.383, 'unemployment': 5.8, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.52, 't10y3m_spread': 1.67, 'breakeven_10y': 2.48, 'hy_oas': 3.4, 'ig_oas': 0.92, 'ted_spread': 0.14, 'mortgage_30y': 2.94, 'vix': 22.18000030517578}\nMarket regime: sideways\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": -0.221805, "explanation": "The actual 21-day forward return for DOT-USD starting 2021-05-20 was -22.18%, which classifies as 'negative'.", "metadata": {"future_return": -0.221805, "horizon_days": 21, "hist_return": -0.314361, "annualized_vol": 1.167115, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220127_0017", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2022-01-27", "context_summary": "EFA over past 60 days: cumulative return -6.1%, annualized vol 13.1%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=70.53, end=66.20, cumulative_return=-6.1%, annualized_volatility=13.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 282.543, 'unemployment': 4.0, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.72, 't10y3m_spread': 1.66, 'breakeven_10y': 2.38, 'hy_oas': 3.25, 'ig_oas': 1.03, 'ted_spread': 0.09, 'mortgage_30y': 3.56, 'vix': 31.959999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-26] [\"Adobe Systems (ADBE) Dips More Than Broader Markets: What You Should Know Adobe Systems (ADBE) closed the most recent trading day at $500.81, moving -0.38% from the previous trading session. This change lagged the S&P 500's 0.15% loss on the day. Meanwhile, the Dow lost 0.38%, and the Nasdaq, a tech-heavy index, lost 0.05%. Heading into today, shares of the software maker had lost 11.7% over the past month, outpacing the Computer and Technology sector's loss of 14.1% and lagging the S&P 500's loss of 7.66% in that time. Adobe Systems will be looking to display strength as it nears its next earnings release. On that day, Adobe Systems is projected to report earnings of $3.34 per share, which would represent year-over-year growth of 6.37%. Meanwhile, the Zacks Consensus Estimate for revenue is projecting net sales of $4.23 billion, up 8.34% from the year-ago period. For the full year, our Zacks Consensus Estimates are projecting earnings of $13.72 per share and revenue of $17.89 billion, which would represent changes of +9.94% and +13.35%, respectively, from the prior year. Investors might also notice recent changes to analyst estimates for Adobe Systems. These revisions typically reflect the latest short-term business trends, which can change frequently. As a result, we can interpret positive estimate revisions as a good sign for the company's business outlook. Based on our research, we believe these estimate revisions are directly related to near-team stock moves. To benefit from this, we have developed the Zacks Rank, a proprietary model which takes these estimate changes into account and provides an actionable 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 remained stagnant. Adobe Systems is holding a Zacks Rank of #5 (Strong Sell) right now. Valuation is also important, so investors should note that Adobe Systems has a Forward P/E ratio of 36.66 right now. This represents a premium compared to its industry's average Forward P/E of 31.57. Also, we should mention that ADBE has a PEG ratio of 2.12. The PEG ratio is similar to the widely-used P/E ratio, but this metric also takes the company's expected earnings growth rate into account. ADBE's industry had an average PEG ratio of 2.56 as of yesterday's close. The Computer - Software industry is part of the Computer and Technology sector. This industry currently has a Zacks Industry Rank of 89, which puts it in the top 35% of all 250+ industries. The Zacks Industry Rank gauges the strength of our industry groups by measuring the average Zacks Rank of the individual stocks within the groups. Our research shows that the top 50% rated industries outperform the bottom half by a factor of 2 to 1. You can find more information on all of these metrics, and much more, on Zacks.com. \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": 0.002148, "explanation": "The actual 21-day forward return for EFA starting 2022-01-27 was +0.21%, which classifies as 'flat'.", "metadata": {"future_return": 0.002148, "horizon_days": 21, "hist_return": -0.06129, "annualized_vol": 0.131156, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210218_0020", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2021-02-18", "context_summary": "ADA-USD over past 60 days: cumulative return +450.0%, annualized vol 136.7%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.16, end=0.89, cumulative_return=+450.0%, annualized_volatility=136.7%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 263.579, 'unemployment': 6.2, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.18, 't10y3m_spread': 1.25, 'breakeven_10y': 2.21, 'hy_oas': 3.44, 'ig_oas': 0.94, 'ted_spread': 0.14, 'mortgage_30y': 2.73, 'vix': 21.5}\nMarket regime: sideways\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": 0.230463, "explanation": "The actual 21-day forward return for ADA-USD starting 2021-02-18 was +23.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.230463, "horizon_days": 21, "hist_return": 4.499913, "annualized_vol": 1.367099, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200715_0023", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-07-15", "context_summary": "MATIC-USD over past 60 days: cumulative return +11.6%, annualized vol 85.8%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.02, end=0.02, cumulative_return=+11.6%, annualized_volatility=85.8%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 258.352, 'unemployment': 10.2, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.49, 't10y3m_spread': 0.48, 'breakeven_10y': 1.41, 'hy_oas': 6.03, 'ig_oas': 1.5, 'ted_spread': 0.12, 'mortgage_30y': 3.03, 'vix': 29.520000457763672}\nMarket regime: sideways\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": -0.04018, "explanation": "The actual 21-day forward return for MATIC-USD starting 2020-07-15 was -4.02%, which classifies as 'negative'.", "metadata": {"future_return": -0.04018, "horizon_days": 21, "hist_return": 0.115627, "annualized_vol": 0.857985, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200624_0026", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2020-06-24", "context_summary": "PALL over past 60 days: cumulative return -18.7%, annualized vol 38.0%. Market regime: sideways.", "question": "Asset: PALL\nHistorical prices (past 60 trading days): start=222.19, end=180.56, cumulative_return=-18.7%, annualized_volatility=38.0%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 257.042, 'unemployment': 11.0, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.54, 't10y3m_spread': 0.56, 'breakeven_10y': 1.38, 'hy_oas': 6.02, 'ig_oas': 1.56, 'ted_spread': 0.14, 'mortgage_30y': 3.13, 'vix': 31.3700008392334}\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": 0.153737, "explanation": "The actual 21-day forward return for PALL starting 2020-06-24 was +15.37%, which classifies as 'positive'.", "metadata": {"future_return": 0.153737, "horizon_days": 21, "hist_return": -0.187362, "annualized_vol": 0.37967, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20170817_0029", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2017-08-17", "context_summary": "BTC-USD over past 60 days: cumulative return +21.6%, annualized vol 72.3%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=3599.77, end=4376.63, cumulative_return=+21.6%, annualized_volatility=72.3%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 245.183, 'unemployment': 4.4, 'gdp_growth_qoq': 19660.766, 't10y2y_spread': 0.9, 't10y3m_spread': 1.21, 'breakeven_10y': 1.78, 'hy_oas': 3.88, 'ig_oas': 1.14, 'ted_spread': 0.32, 'mortgage_30y': 3.9, 'vix': 11.739999771118164}\nMarket regime: sideways\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": 0.061913, "explanation": "The actual 21-day forward return for BTC-USD starting 2017-08-17 was +6.19%, which classifies as 'positive'.", "metadata": {"future_return": 0.061913, "horizon_days": 21, "hist_return": 0.21581, "annualized_vol": 0.722691, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200901_0032", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2020-09-01", "context_summary": "SCHH over past 60 days: cumulative return -9.4%, annualized vol 24.6%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=17.18, end=15.57, cumulative_return=-9.4%, annualized_volatility=24.6%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 259.316, 'unemployment': 8.4, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.58, 't10y3m_spread': 0.61, 'breakeven_10y': 1.8, 'hy_oas': 5.02, 'ig_oas': 1.36, 'ted_spread': 0.14, 'mortgage_30y': 2.91, 'vix': 26.40999984741211}\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": -0.007001, "explanation": "The actual 21-day forward return for SCHH starting 2020-09-01 was -0.70%, which classifies as 'flat'.", "metadata": {"future_return": -0.007001, "horizon_days": 21, "hist_return": -0.093602, "annualized_vol": 0.246271, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180727_0037", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2018-07-27", "context_summary": "XLF over past 60 days: cumulative return +3.8%, annualized vol 15.0%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=23.31, end=24.20, cumulative_return=+3.8%, annualized_volatility=15.0%\nMacro context: {'fed_funds_rate': 1.91, 'cpi_yoy': 251.214, 'unemployment': 3.8, 'gdp_growth_qoq': 20276.154, 't10y2y_spread': 0.29, 't10y3m_spread': 0.99, 'breakeven_10y': 2.11, 'hy_oas': 3.42, 'ig_oas': 1.17, 'ted_spread': 0.39, 'mortgage_30y': 4.54, 'vix': 12.140000343322754}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-26] [\"This reversal shows there\\u2019s risk in the bullish stock market \\u2014 and Facebook is further proof Big tech stocks are faltering, so make sure to hold cash and maintain hedges Big tech stocks are faltering, so make sure to hold cash and maintain hedges, says Nigam Arora.\", \"This FAANG stock looks like the next Berkshire Hathaway \\u2014 a smart bet for the next 25 years Critical information for the U.S. trading day Tough day out there for tech stocks, but our call of the day says if you\\u2019ve got an eye on the future, then this superstar in that sector could be big like Berkshire in the next 25 years.\", \"Qualcomm drops NXP acquisition, leaves analysts concerned about Apple business Several price-target hikes follow better-than-expected earnings Nearly two years after Qualcomm Inc. announced its intent to acquire NXP Semiconductors NV, investors are pleased that the company is moving on.\", \"Is Facebook\\u2019s thud a bad omen for FAANG stocks? Simon Maierhofer looks at technical indicators that suggest the fundamentals are deteriorating Simon Maierhofer looks at technical indicators that suggest the fundamentals are deteriorating.\", \"Wall Street veteran who flagged Apple at $1.14 a share says these 5 overlooked stocks are buys \\u2018Turnaround Letter\\u2019 editor\\u2019s picks include Blue Apron, AMC Entertainment \\u2018Turnaround Letter\\u2019 editor\\u2019s picks include Blue Apron, AMC Entertainment, writes Mark Hulbert.\", \"Amazon earnings: Prime Day isn\\u2019t the only thing giving business a boost Amazon shares are up 25.3% for the last three months and the e-commerce giant is on the road to a $1 trillion market cap Amazon is expected to report earnings that reflect growth across advertising and cloud services as well as e-commerce.\", \"Intel earnings: After CEO departure, chip maker needs a win Data-center and PC revenue will be closely watched as Intel looks for a new leader Intel Corp. needs strong gains in its core personal-computer business as well as its server segment to overcome uncertainties about management succession and its manufacturing processes in the wake of a sudden shake-up.\", \"Why Facebook\\u2019s stock plunge may gather steam When stocks open 15% or lower after earnings, they tend to close even weaker by the end of session It is an ugly day for Facebook, but an unsightly tumble for the social-media giant may get worse before it gets better.\", \"Facebook Investors Want to Strip Zuckerberg of Chairman Title Trillium, which filed a shareholder proposal asking the company to remove Zuckerberg as chairman before the company announced disappointing results Wednesday, is the latest group of investors who want a change.\", \"Tech Today: Facebook\\u2019s Fall, AMD\\u2019s New High, an Apple Beat? Facebook's got a credibility gap to deal with, AMD is heading for its highest level in over a decade, and some see nice trends for Apple heading into its earnings report next Tuesday.\", \"\\u2018Oh sh-t!\\u2019 Facebook\\u2019s historic plunge, as\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": 0.017419, "explanation": "The actual 21-day forward return for XLF starting 2018-07-27 was +1.74%, which classifies as 'positive'.", "metadata": {"future_return": 0.017419, "horizon_days": 21, "hist_return": 0.038365, "annualized_vol": 0.150129, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160219_0040", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-02-19", "context_summary": "QQQ over past 60 days: cumulative return -11.2%, annualized vol 24.0%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=106.02, end=94.13, cumulative_return=-11.2%, annualized_volatility=24.0%\nMacro context: {'fed_funds_rate': 0.38, 'cpi_yoy': 237.336, 'unemployment': 4.9, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.04, 't10y3m_spread': 1.45, 'breakeven_10y': 1.24, 'hy_oas': 8.17, 'ig_oas': 2.16, 'ted_spread': 0.32, 'mortgage_30y': 3.65, 'vix': 21.63999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-02-18] Analog Devices Beats Q1 Earnings and Revenue Estimates Analog Devices Inc.ADI reported first-quarter fiscal 2016 earnings of 56 cents per share, which beat the Zacks Consensus Estimate of 53 cents. Adjusted earnings per share excluded one-time items but included stock-based compensation expenses. Following the first-quarter results, shares were down 1.1% in after-hour trading session due to weaker economic conditions and significant weakness in the portable consumer electronics sector. Revenues Analog Devices generated revenues of $769.4 million, down 21.4% sequentially and 0.3% year over year. The decline was due to significant weakness in the consumer market, especially the consumer portable segment. However, other end markets - industrial, automotive and communications infrastructure - performed in line with the company's expectations. However, revenues were above the company's recent revised guidance range of $745-$765 million as well as the Zacks Consensus Estimate of $761.0 million. Revenues by End Markets Industrial market generated 45% of Analog Devices' total revenue (down 5.1% sequentially and 1% year over year). This represents a diversified market for the company, including industrial automation, instrumentation, energy, defense and health care segments. Communications generated 22% of total revenue, up 4.1% sequentially but down 15.9% year over year. Within Communications, wireline applications improved both sequentially as well as year over year. However, wireless infrastructure grew from the last quarter but was down from the prior year. The Automotive segment generated around 17% of Analog Devices' first-quarter revenues, down 4.3% sequentially but up 2.2% year over year. Revenues in all the sub-segments under this business were flat to down sequentially and in line with the seasonal patterns. The Consumer segment, which Analog Devices clubbed with its computing and handset businesses, plummeted 60.3% sequentially but grew 31.6% year over year. It accounted for 16% of total revenue. Though audio/video applications decreased in line with seasonal patterns, revenues from portable consumer applications declined significantly due to weaker-than-expected customer demand. Margins Pro-forma gross margin was 62.2%, down 350 basis points (bps) sequentially and 340 bps year over year. The decline was primarily due to higher inventory reserves and lower utilization rates. Analog Devices reported adjusted operating expenses of $264.8 million, down 9.3% sequentially and 1.4% year over year. Pro-forma operating margin of 27.8% was down 810 bps sequentially and 304 bps year over year. Analog Devices Inc. - Earnings Surprise | FindTheBest Net Profit On a GAAP basis, Analog Devices recorded a net profit of $164.5 million or 52 cents per share compared with $96.3 million or 30 cents in the prior quarter. The company generated adjusted net profit of $176.3 million compared with $326.1 million in the fourth quarter. Pro-forma earnings per share came \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": 0.063758, "explanation": "The actual 21-day forward return for QQQ starting 2016-02-19 was +6.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.063758, "horizon_days": 21, "hist_return": -0.112164, "annualized_vol": 0.239744, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20191016_0043", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-10-16", "context_summary": "ETH-USD over past 60 days: cumulative return -2.3%, annualized vol 57.5%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=185.69, end=181.41, cumulative_return=-2.3%, annualized_volatility=57.5%\nMacro context: {'fed_funds_rate': 1.9, 'cpi_yoy': 257.155, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.16, 't10y3m_spread': 0.1, 'breakeven_10y': 1.56, 'hy_oas': 4.01, 'ig_oas': 1.2, 'ted_spread': 0.36, 'mortgage_30y': 3.57, 'vix': 13.539999961853027}\nMarket regime: sideways\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": 0.088518, "explanation": "The actual 21-day forward return for ETH-USD starting 2019-10-16 was +8.85%, which classifies as 'positive'.", "metadata": {"future_return": 0.088518, "horizon_days": 21, "hist_return": -0.023058, "annualized_vol": 0.574769, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160802_0046", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2016-08-02", "context_summary": "EEM over past 60 days: cumulative return +10.9%, annualized vol 19.4%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=26.30, end=29.18, cumulative_return=+10.9%, annualized_volatility=19.4%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 240.545, 'unemployment': 4.9, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.84, 't10y3m_spread': 1.22, 'breakeven_10y': 1.46, 'hy_oas': 5.69, 'ig_oas': 1.5, 'ted_spread': 0.47, 'mortgage_30y': 3.48, 'vix': 12.4399995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-08-01] [\"Tech Turbocharged By Earnings, Chart Breakouts Last week\\u2019s killer earnings from Facebook, Alphabet and Apple paced an already energized tech sector.\", \"The drive behind Uber and Didi\\u2019s odd billions Ride-hailing services battle for China with cash that isn\\u2019t coming from venture capital Two ride-hailing giants are bringing in billions of dollars from untraditional sources, and the goals seem clear.\", \"The complicated web of companies that will determine the future of cars Race with tech giants to autonomous services pushes partnerships between carmakers and ride-hailing startups Auto makers, ride-hailing companies and tech companies are all part of an intricate web of partnerships and investments working toward an autonomous future.\", \"Sony: Could Have 54% Upside; Four Reasons to Be Bullish Japanese electronics giant Sony (6758.JP) is making investors believe in the stock again. Shares are up 2.2% this morning following the company\\u2019s stunning June quarter earnings beat last Friday. The stock has rebounded 12% this year after having plummeted 35% in the second half ofSony unveiled a JPY56 billion operating profit for the June quarter, which is well above the JPY3 billion operating loss analysts were expecting. Revenues of JPY1.6 trillion were down 11% year-on-year although the fall narrows to 3% after adjusting for the stronger yen.READ MORE>>\", \"Didi Chuxing reaches deal to buy Uber\\u2019s China operations Uber, investors in UberChina unit will own 20% of Didi; Chinese ride-hailing company will invest $1 billion in Uber Global ride-hailing giant Uber Technologies Inc. has given up its costly battle for China\\u2019s riders, swapping its local operations there for a minority stake in the country\\u2019s homegrown champion, Didi Chuxing Technology Co.\", \"Earnings signal a bear market: \\u2018Sell the house, sell the car, sell the kids\\u2019 Critical intelligence before the U.S. market opens Investors are certainly looking for something to light a fire under this market, considering the S&P 500 over the past 11 days has been stuck in the narrowest range in 45 years.\", \"Worldwide tablet shipments plunge 12% in second quarter: IDC\", \"VirnetX's stock plunges 46% premarket after disappointing court ruling on Apple patent suits\", \"Apple grows share of total tablet market despite sales decline Worldwide shipments of tablets fell 12% in the second quarter, according to a new report from IDC. Roughly 65% of tablets shipped this past quarter were run on Alphabet Inc.'s Android operating system, followed by Apple Inc.'s ioS, which captured 26% of the market. Apple's shipments fell by 9% year-over-year, but the launch of a new iPad Pro earlier this year helped to increase average selling prices for iPads, lifting Apple's total share of the market from 25% last year. Samsung Electronics Co.'s share decreased to 15.6% from 18.2% a year ago, as its shipments plunged 25% during the quarter. Lenovo, Huawei and Amazon.com Inc. rounded out the top fi\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": 0.018116, "explanation": "The actual 21-day forward return for EEM starting 2016-08-02 was +1.81%, which classifies as 'positive'.", "metadata": {"future_return": 0.018116, "horizon_days": 21, "hist_return": 0.109472, "annualized_vol": 0.194315, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20171107_0049", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2017-11-07", "context_summary": "DBB over past 60 days: cumulative return +4.5%, annualized vol 16.1%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=14.97, end=15.65, cumulative_return=+4.5%, annualized_volatility=16.1%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 247.284, 'unemployment': 4.2, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.71, 't10y3m_spread': 1.13, 'breakeven_10y': 1.86, 'hy_oas': 3.55, 'ig_oas': 1.03, 'ted_spread': 0.23, 'mortgage_30y': 3.94, 'vix': 9.729999542236328}\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": "negative", "answer_numeric": -0.042139, "explanation": "The actual 21-day forward return for DBB starting 2017-11-07 was -4.21%, which classifies as 'negative'.", "metadata": {"future_return": -0.042139, "horizon_days": 21, "hist_return": 0.045354, "annualized_vol": 0.161086, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20211130_0052", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2021-11-30", "context_summary": "SOL-USD over past 60 days: cumulative return +26.4%, annualized vol 84.3%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=161.68, end=204.32, cumulative_return=+26.4%, annualized_volatility=84.3%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 278.919, 'unemployment': 4.1, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.01, 't10y3m_spread': 1.46, 'breakeven_10y': 2.54, 'hy_oas': 3.53, 'ig_oas': 1.02, 'ted_spread': 0.11, 'mortgage_30y': 3.1, 'vix': 22.959999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-11-29] \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": -0.126837, "explanation": "The actual 21-day forward return for SOL-USD starting 2021-11-30 was -12.68%, which classifies as 'negative'.", "metadata": {"future_return": -0.126837, "horizon_days": 21, "hist_return": 0.263708, "annualized_vol": 0.843428, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20221006_0055", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2022-10-06", "context_summary": "BNB-USD over past 60 days: cumulative return -8.9%, annualized vol 41.2%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=322.92, end=294.14, cumulative_return=-8.9%, annualized_volatility=41.2%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 298.007, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.39, 't10y3m_spread': 0.3, 'breakeven_10y': 2.22, 'hy_oas': 5.09, 'ig_oas': 1.61, 'ted_spread': 0.09, 'mortgage_30y': 6.7, 'vix': 28.549999237060547}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-05] \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": 0.000733, "explanation": "The actual 21-day forward return for BNB-USD starting 2022-10-06 was +0.07%, which classifies as 'flat'.", "metadata": {"future_return": 0.000733, "horizon_days": 21, "hist_return": -0.089135, "annualized_vol": 0.412077, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20210503_0058", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2021-05-03", "context_summary": "ETH-USD over past 60 days: cumulative return +91.5%, annualized vol 66.4%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1541.91, end=2952.06, cumulative_return=+91.5%, annualized_volatility=66.4%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 268.383, 'unemployment': 5.8, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.49, 't10y3m_spread': 1.64, 'breakeven_10y': 2.41, 'hy_oas': 3.28, 'ig_oas': 0.94, 'ted_spread': 0.17, 'mortgage_30y': 2.98, 'vix': 18.61000061035156}\nMarket regime: sideways\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": -0.229518, "explanation": "The actual 21-day forward return for ETH-USD starting 2021-05-03 was -22.95%, which classifies as 'negative'.", "metadata": {"future_return": -0.229518, "horizon_days": 21, "hist_return": 0.91454, "annualized_vol": 0.664362, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20211029_0065", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2021-10-29", "context_summary": "XLE over past 60 days: cumulative return +19.3%, annualized vol 27.2%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=20.60, end=24.58, cumulative_return=+19.3%, annualized_volatility=27.2%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.07, 't10y3m_spread': 1.51, 'breakeven_10y': 2.57, 'hy_oas': 3.08, 'ig_oas': 0.89, 'ted_spread': 0.07, 'mortgage_30y': 3.14, 'vix': 16.530000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-28] [\"The Morning After: Android 12L is Google's latest tablet effort Today\\u2019s headlines: Google gives Android on tablets another shot with Android 12L, Intel's hybrid 12th-gen chips are a major strike against AMD and iOS 15\\u2019s SharePlay is finally here.\", \"Fleksy raises Series A to expand its keyboard SDK biz after 10x growth Barcelona-based mobile keyboard software maker, Fleksy, has bagged a $1.6 million Series A to cement a pivot to b2b for its white-label SDK for Android and iOS. The AI keyboard maker has been a long time player in the third party smartphone keyboard space, initially developing a productivity-focused keyboard called ThingThing -- before acquiring the assets of better known US-based custom keyboard Fleksy (which had gone into stasis after its dev team got acquired by Pinterest) and making developing Fleksy the full focus. Tech giants like Apple and Google also throw their weight around in peculiar ways.\", \"Stock market news live updates: Stock futures as investors eye weaker-than-expected Q3 GDP, drop in jobless claims Stock futures rose Thursday morning, with the S&P 500 and Dow looking to resume advances after a pause on Wednesday. Traders looked ahead to more key earnings and economic data reports.\", \"Apple is the first public partner to join sustainable chip initiative With the Sustainable Semiconductor Technologies and Systems program, Imec wants to help chipmakers reduce their carbon footprint.\", \"Apple TV+ is coming to Comcast devices The Apple TV app will be available on Comcast devices in the months ahead, including its X1 boxes and XClass TVs.\", \"Apple's App Privacy Report launches into beta to show you what your apps are up to Apple has now launched a beta version of its \\\"App Privacy Report,\\\" a new feature that aims to provide iOS users with details about how often their everyday apps are requesting access to sensitive information, and where that information is being shared. The feature was first introduced at Apple's Worldwide Developer Conference in June, amid other privacy-focused improvements, including tools to block tracking pixels in emails, a private VPN, and more. Apple explained at the time the new report would include details about an app's access to user data and sensors, including the user's location, photos, contacts, and more, as well as a list of domains that the app contacts.\", \"Affirm founder Max Levchin on American Airlines deal, crypto Yahoo Finance Live chats with Affirm founder and CEO Max Levchin about his new deal with American Airlines and the outlook for crypto.\", \"Apple to report earnings amid chip shortage and supply crunch Apple will report its Q4 earnings after the bell on Thursday, with analysts looking to the potential impact of the chip shortage.\", \"Mark Zuckerberg takes thinly veiled shots at Apple for 'stifling innovation' via its platform policies Facebook (aka \\\"Meta\\\") CEO Mark Zuckerberg today took several thinly veiled shots at Apple and the overall app ecosystem when d\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": -0.027319, "explanation": "The actual 21-day forward return for XLE starting 2021-10-29 was -2.73%, which classifies as 'negative'.", "metadata": {"future_return": -0.027319, "horizon_days": 21, "hist_return": 0.193494, "annualized_vol": 0.272482, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20211008_0068", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2021-10-08", "context_summary": "XLP over past 60 days: cumulative return -0.5%, annualized vol 9.9%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=62.59, end=62.27, cumulative_return=-0.5%, annualized_volatility=9.9%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.26, 't10y3m_spread': 1.53, 'breakeven_10y': 2.46, 'hy_oas': 3.19, 'ig_oas': 0.9, 'ted_spread': 0.07, 'mortgage_30y': 2.99, 'vix': 19.540000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-07] November 26th Options Now Available For Analog Devices (ADI) Investors in Analog Devices Inc (Symbol: ADI) saw new options become available today, for the November 26th expiration. At Stock Options Channel, our YieldBoost formula has looked up and down the ADI options chain for the new November 26th contracts and identified one put and one call contract of particular interest. The put contract at the $165.00 strike price has a current bid of $4.80. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $165.00, but will also collect the premium, putting the cost basis of the shares at $160.20 (before broker commissions). To an investor already interested in purchasing shares of ADI, that could represent an attractive alternative to paying $168.30/share today. Because the $165.00 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 100%. 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 2.91% return on the cash commitment, or 21.22% annualized \u2014 at Stock Options Channel we call this the YieldBoost. Below is a chart showing the trailing twelve month trading history for Analog Devices Inc, and highlighting in green where the $165.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $170.00 strike price has a current bid of $4.60. If an investor was to purchase shares of ADI stock at the current price level of $168.30/share, and then sell-to-open that call contract as a \"covered call,\" they are committing to sell the stock at $170.00. Considering the call seller will also collect the premium, that would drive a total return (excluding dividends, if any) of 3.74% if the stock gets called away at the November 26th expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if ADI shares really soar, which is why looking at the trailing twelve month trading history for Analog Devices Inc, as well as studying the business fundamentals becomes important. Below is a chart showing ADI's trailing twelve month trading history, with the $170.00 strike highlighted in red: Considering the fact that the $170.00 strike represents an approximate 1% premium 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 covered call contract would expire worthless, in which case the investor would keep both their shares of stock and the premium collected. The current\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": 0.033833, "explanation": "The actual 21-day forward return for XLP starting 2021-10-08 was +3.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.033833, "horizon_days": 21, "hist_return": -0.005117, "annualized_vol": 0.098978, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160804_0071", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2016-08-04", "context_summary": "SCHH over past 60 days: cumulative return +5.0%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=16.06, end=16.87, cumulative_return=+5.0%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 240.545, 'unemployment': 4.9, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.88, 't10y3m_spread': 1.27, 'breakeven_10y': 1.46, 'hy_oas': 5.72, 'ig_oas': 1.51, 'ted_spread': 0.5, 'mortgage_30y': 3.48, 'vix': 12.859999656677246}\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": -0.005417, "explanation": "The actual 21-day forward return for SCHH starting 2016-08-04 was -0.54%, which classifies as 'flat'.", "metadata": {"future_return": -0.005417, "horizon_days": 21, "hist_return": 0.050115, "annualized_vol": 0.135155, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220915_0076", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2022-09-15", "context_summary": "XRP-USD over past 60 days: cumulative return -0.4%, annualized vol 46.1%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.34, end=0.34, cumulative_return=-0.4%, annualized_volatility=46.1%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 296.349, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.37, 't10y3m_spread': 0.17, 'breakeven_10y': 2.46, 'hy_oas': 4.74, 'ig_oas': 1.46, 'ted_spread': 0.09, 'mortgage_30y': 5.89, 'vix': 26.15999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-14] \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": 0.511281, "explanation": "The actual 21-day forward return for XRP-USD starting 2022-09-15 was +51.13%, which classifies as 'positive'.", "metadata": {"future_return": 0.511281, "horizon_days": 21, "hist_return": -0.003873, "annualized_vol": 0.461455, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20200106_0079", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2020-01-06", "context_summary": "XLRE over past 60 days: cumulative return -0.9%, annualized vol 12.1%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=31.52, end=31.24, cumulative_return=-0.9%, annualized_volatility=12.1%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 259.127, 'unemployment': 3.6, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.27, 't10y3m_spread': 0.28, 'breakeven_10y': 1.77, 'hy_oas': 3.61, 'ig_oas': 1.03, 'ted_spread': 0.38, 'mortgage_30y': 3.72, 'vix': 14.020000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-01-03] [\"Apple Was the Dow\\u2019s Best Stock in 2019. What Could Happen Next. If Barron\\u2019s gave out a Stock of the Year award, we\\u2019d have to hand it directly to Apple.\", \"CES 2020: Where have the tech companies gone? Big tech companies have gradually moved away from the biggest electronics trade show of the year, but 2020\\u2019s keynote lineup and absences show a more dramatic shift From keynote speeches to exhibitor booths, the annual weeklong high-tech bacchanal here will be distinguished as much by automakers and airlines as by chip makers and computer makers.\", \"Apple's stock slips 0.7% premarket, after rallying 2.3% on Thursday and 3.6% over the past 3 sessions\", \"Small-cap woes highlight stock market\\u2019s dependency on mega-cap names The Russell small cap index lost 0.1% Thursday. The phenomenon shows the market\\u2019s eagerness to bet on mega-cap, momentum stocks\", \"All 30 of the Dow's stocks are trading lower; 3M and Goldman shares are the biggest drags The 254-point selloff in the Dow Jones Industrial Average on Friday was unanimous in morning trading, with shares of consumer and industrial products maker 3M Co. leading all 30 components lower. 3M's stock fell 1.8%, and acted as the biggest drag as the $3.28 price decline shaved about 22 points off the Dow's price. The next biggest subtractor was Goldman Sachs Group Inc.'s stock , which fell $2.48, or 1.1%, to cut 17 points off the Dow's price. Among other higher-priced components, shares of Apple Inc. fell $1.71 to lower the Dow's price by about 12 points and Boeing Co. declined $2.19 to act as a 15-point drag. Weighing on the Dow was concerns over rising tensions in the Middle East after a U.S. drone airstrike that killed one of Iran's top military commanders, a spike in crude oil prices and a worse-than-expected reading on the U.S. manufacturing sector.\", \"Apple Stock Target Price Boosted by Two Wall Street Firms On Friday analysts at RBC Capital and BofA Securities upped their price targets for Apple shares, in response to the stock\\u2019s huge run-up.\", \"Buy Synaptics Stock to Play Apple\\u2019s 2020 iPhone Lineup, Analyst Says Synaptics shares are getting a boost from KeyBanc analyst John Vinh, who lifted his rating on the chip maker to Overweight from Sector Weight, setting a price target of $80.\", \"Apple's latest iPhone lineup was a hit during the holidays We're not very far into 2020, but Apple is starting the year off with some strong financials. The company's Q1 2020 earnings release just crossed the wire, and the numbers here are significant: Apple reported a total of $91.8 billion in quarterly revenue, setting new all-time quarterly record\", \"Apple tests UWB switch to keep the iPhone 11 from tracking your location Apple has started testing the location toggle button it promised to iPhone 11 users. Late last year, security researcher Brian Krebs discovered that the iPhone 11 Pro constantly checks for your location even if you disable Location Services. Apple explained that \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": 0.032199, "explanation": "The actual 21-day forward return for XLRE starting 2020-01-06 was +3.22%, which classifies as 'positive'.", "metadata": {"future_return": 0.032199, "horizon_days": 21, "hist_return": -0.008685, "annualized_vol": 0.121046, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20161101_0082", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2016-11-01", "context_summary": "ICSH over past 60 days: cumulative return +0.1%, annualized vol 2.0%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=38.79, end=38.82, cumulative_return=+0.1%, annualized_volatility=2.0%\nMacro context: {'fed_funds_rate': 0.31, 'cpi_yoy': 241.741, 'unemployment': 4.9, 'gdp_growth_qoq': 19304.352, 't10y2y_spread': 0.98, 't10y3m_spread': 1.5, 'breakeven_10y': 1.73, 'hy_oas': 4.91, 'ig_oas': 1.38, 'ted_spread': 0.54, 'mortgage_30y': 3.47, 'vix': 17.059999465942383}\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": 0.0008, "explanation": "The actual 21-day forward return for ICSH starting 2016-11-01 was +0.08%, which classifies as 'flat'.", "metadata": {"future_return": 0.0008, "horizon_days": 21, "hist_return": 0.000659, "annualized_vol": 0.01975, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190619_0085", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2019-06-19", "context_summary": "USO over past 60 days: cumulative return -8.8%, annualized vol 32.8%. Market regime: sideways.", "question": "Asset: USO\nHistorical prices (past 60 trading days): start=98.72, end=90.00, cumulative_return=-8.8%, annualized_volatility=32.8%\nMacro context: {'fed_funds_rate': 2.37, 'cpi_yoy': 255.213, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.2, 't10y3m_spread': -0.16, 'breakeven_10y': 1.64, 'hy_oas': 4.14, 'ig_oas': 1.3, 'ted_spread': 0.22, 'mortgage_30y': 3.82, 'vix': 15.149999618530272}\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": "positive", "answer_numeric": 0.0203, "explanation": "The actual 21-day forward return for USO starting 2019-06-19 was +2.03%, which classifies as 'positive'.", "metadata": {"future_return": 0.0203, "horizon_days": 21, "hist_return": -0.088331, "annualized_vol": 0.327551, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190729_0090", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2019-07-29", "context_summary": "IWM over past 60 days: cumulative return +0.1%, annualized vol 16.5%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=144.24, end=144.45, cumulative_return=+0.1%, annualized_volatility=16.5%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 255.802, 'unemployment': 3.7, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.22, 't10y3m_spread': -0.04, 'breakeven_10y': 1.78, 'hy_oas': 3.89, 'ig_oas': 1.14, 'ted_spread': 0.19, 'mortgage_30y': 3.75, 'vix': 12.15999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-26] [\"SoftBank launches another tech megafund, backed by Apple, Microsoft Second Vision Fund, with about $108 billion secured, will invest in AI SoftBank Group Corp. said it would start a second technology megafund and has secured $108 billion in commitments from investors including Apple Inc., Japanese banks, Taiwanese investors and Kazakhstan\\u2019s sovereign-wealth fund.\", \"SoftBank Unveils Plans For $108 Billion Vision Fund 2 The Japanese holding company said investors in the new fund include Apple, Microsoft, Foxconn, and others.\", \"Asian markets pull back as Japan-South Korea trade tensions escalate Japan reportedly will diminish South Korea\\u2019s trade status Asian shares were lower Friday as investors continued to watch the brewing trade conflict between China and the U.S., and any signs of what\\u2019s in store from central banks.\", \"Tesla\\u2019s key executive departures, in one handy list News that Tesla\\u2019s Chief Technology Officer J.B. Straubel is stepping down from that role is just the latest move in a long list The departure of Tesla Inc.\\u2019s J.B. Straubel is a song Tesla has heard before \\u2014 numerous times.\", \"Even Intel doesn\\u2019t seem to know what\\u2019s going to happen with Intel Amid sale of modem-chip business to Apple and a forecast flip-flop, Intel seems to be unsure of path for it, or the chip industry, in second half In the semiconductor industry, \\u201cmixed signal\\u201d usually refers to chips that combine digital and analog circuitry. When referring to Intel Corp. right now, though, the standard definition of that phrase is more apt.\", \"Alphabet earnings show Google revenue growth rebounding, stock pops higher Profit and revenue beat expectations amid reported antitrust scrutiny Alphabet Inc. shares jumped 7% in after-hours trading Thursday after the online giant announced better-than-expected financial results.\", \"Facebook tops Amazon and Google in second-quarter lobbying spending Partisan split means \\u2018we see little room for any legislation to actually materialize in the near term,\\u2019 analysts say Facebook spent $4.1 million on lobbying Washington in the second quarter, topping the outlays by other so-called FAANG companies and keeping the tech giant on pace for another record year of spending to influence lawmakers and regulators.\", \"Google Needs to Buy Back Even More Stock Wall Street cheered the latest numbers, but Alphabet\\u2019s repurchase program barely exceed its stock-based compensation, which totaled $5.5 billion in the first half of 2019.\", \"Are you a \\u2018zombie eater\\u2019? It could be bad for your health Distracted diners who stare at screens tend to eat more calories and choose fattier foods Distracted diners who stare at screens tend to eat more calories and choose fattier foods.\", \"Intel\\u2019s earnings beat gets fairly cold reception from analysts Surprise rise in PC sales overshadowed by new chip rollout pace, AMD challenges Intel Corp. shares slip Friday following a big earnings beat\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": -0.072366, "explanation": "The actual 21-day forward return for IWM starting 2019-07-29 was -7.24%, which classifies as 'negative'.", "metadata": {"future_return": -0.072366, "horizon_days": 21, "hist_return": 0.001486, "annualized_vol": 0.165083, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190620_0094", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2019-06-20", "context_summary": "BNB-USD over past 60 days: cumulative return +45.9%, annualized vol 75.8%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=24.19, end=35.29, cumulative_return=+45.9%, annualized_volatility=75.8%\nMacro context: {'fed_funds_rate': 2.37, 'cpi_yoy': 255.213, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.29, 't10y3m_spread': -0.15, 'breakeven_10y': 1.67, 'hy_oas': 4.16, 'ig_oas': 1.3, 'ted_spread': 0.26, 'mortgage_30y': 3.82, 'vix': 14.329999923706056}\nMarket regime: sideways\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": -0.19289, "explanation": "The actual 21-day forward return for BNB-USD starting 2019-06-20 was -19.29%, which classifies as 'negative'.", "metadata": {"future_return": -0.19289, "horizon_days": 21, "hist_return": 0.458521, "annualized_vol": 0.758033, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210913_0096", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2021-09-13", "context_summary": "AVAX-USD over past 60 days: cumulative return +422.1%, annualized vol 148.3%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=11.35, end=59.26, cumulative_return=+422.1%, annualized_volatility=148.3%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 273.91, 'unemployment': 4.7, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.12, 't10y3m_spread': 1.3, 'breakeven_10y': 2.4, 'hy_oas': 3.11, 'ig_oas': 0.91, 'ted_spread': 0.07, 'mortgage_30y': 2.88, 'vix': 20.950000762939453}\nMarket regime: sideways\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": 0.226881, "explanation": "The actual 21-day forward return for AVAX-USD starting 2021-09-13 was +22.69%, which classifies as 'positive'.", "metadata": {"future_return": 0.226881, "horizon_days": 21, "hist_return": 4.221148, "annualized_vol": 1.483238, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180406_0099", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2018-04-06", "context_summary": "ADA-USD over past 60 days: cumulative return -54.6%, annualized vol 108.2%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.33, end=0.15, cumulative_return=-54.6%, annualized_volatility=108.2%\nMacro context: {'fed_funds_rate': 1.69, 'cpi_yoy': 250.227, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.53, 't10y3m_spread': 1.11, 'breakeven_10y': 2.08, 'hy_oas': 3.59, 'ig_oas': 1.14, 'ted_spread': 0.64, 'mortgage_30y': 4.4, 'vix': 18.940000534057617}\nMarket regime: sideways\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": 0.997141, "explanation": "The actual 21-day forward return for ADA-USD starting 2018-04-06 was +99.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.997141, "horizon_days": 21, "hist_return": -0.545598, "annualized_vol": 1.082303, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160111_0102", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2016-01-11", "context_summary": "XLE over past 60 days: cumulative return -16.7%, annualized vol 27.9%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=22.28, end=18.55, cumulative_return=-16.7%, annualized_volatility=27.9%\nMacro context: {'fed_funds_rate': 0.36, 'cpi_yoy': 237.652, 'unemployment': 4.8, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.19, 't10y3m_spread': 1.93, 'breakeven_10y': 1.48, 'hy_oas': 7.23, 'ig_oas': 1.77, 'ted_spread': 0.42, 'mortgage_30y': 3.97, 'vix': 27.01000022888184}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-08] [\"Apple has dumped $100B in market value in past month iPhone maker dips below $100 a share for first time in 15 months Apple Inc.shares fell below $100 for the first time in 15 months, gripped by Thursday\\u2019s sharp market declines and signs of slowing growth in the two pillars of the company\\u2019s recent success: the iPhone and China.\", \"Samsung Profit Misses On Smartphone Slowdown, Stronger Won Samsung Electronics (005930.Korea/SSNLF) missed street expectations in the fourth-quarter.Operating profit rose 15% to 6.1 trillion won ($5 billion), less than the 6.64 trillion expected by the street.Both the semiconductor and the mobile businesses disappointed. Morgan Stanley's Shawn Kim wrote:READ MORE.\", \"Cirrus Logic Resurgent With IPhone Opportunity The chip supplier could see shares reach $40 after a reset in expectations and upbeat takeaways from CES.\", \"Who Are The Biggest Losers From China\\u2019s Financial Circus? Financial markets are calmer and bounced back a bit after China scrambled to rescue the slide of its stock markets.Here are Beijing's kitchen-sink measures: 1. The People's Bank of Chinaguided its yuan fix rate higher this morning; 2. The securities regulator China Securities Regulatory Commissionsuspended the much criticized new circuit breaker; 3. The CSRC said major shareholders are not allowed to sell more than 1% of total shares in the next three months as a massive lock-up expires today; 4. The PBoC injected 190 billion yuan into the banking system to avoid liquidity crunch. Phew.Earlier this week, Goldman Sachs said historically, China's yuan devaluation impacts oil prices the most, followed by Turkey, Poland and South Africa. The offshore yuan fell as much as 1.8% in 4 days this week.This blog is curious to find out which countries have been affected the most and if Goldman was right.READ MORE.\", \"Samsung warns of tough 2016 as phone market cools Samsung Electronics Co.'s fourth-quarter earnings estimates for last year reflected a mild recovery, but remarks from top executives show that the company is weighing new approaches as growth in the global smartphone market continues to slow and the upswing in semiconductor prices cools.\", \"What investors should (and shouldn\\u2019t) do in a rout How investors should handle recent drops in the stock market.\", \"Apple supplier Cirrus falls 3% premarket after guidance cut Shares in Cirrus Logic Inc. dropped 3% in premarket action Friday after the chip company reduced its revenue outlook for its quarter ended Dec. 26. The Apple Inc. supplier cited softer-than-expected demand for \\\"certain portable audio products.\\\" The weakness \\\"escalated over the last few weeks of December and is expected to continue to significantly impact our revenue in the March quarter,\\\" said Cirrus CEO Jason Rhode in a news release late Thursday. He said the company still expects its results for the 2016 fiscal year will \\\"reflect meaningful year-over-year revenue growth\\\" and anticipates \\\"strong growth\\\" for \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": -0.013856, "explanation": "The actual 21-day forward return for XLE starting 2016-01-11 was -1.39%, which classifies as 'negative'.", "metadata": {"future_return": -0.013856, "horizon_days": 21, "hist_return": -0.16729, "annualized_vol": 0.279407, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20150714_0107", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2015-07-14", "context_summary": "USMV over past 60 days: cumulative return +1.5%, annualized vol 10.2%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=33.55, end=34.05, cumulative_return=+1.5%, annualized_volatility=10.2%\nMacro context: {'fed_funds_rate': 0.13, 'cpi_yoy': 238.034, 'unemployment': 5.2, 'gdp_growth_qoq': 18857.418, 't10y2y_spread': 1.6623999999999977, 't10y3m_spread': 2.2947999999999955, 'breakeven_10y': 1.86, 'hy_oas': 4.93, 'ig_oas': 1.48, 'ted_spread': 0.27, 'mortgage_30y': 4.04, 'vix': 13.899999618530272}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-07-13] [\"Apple, HP Are Bucking a PC Slowdown Apple may be benefitting from Windows 10 uncertainty. HP has significant potential for upside.\", \"Earnings season distracts from \\u2018grotesque\\u2019 market bubbles Critical intelligence before the U.S. market opens While hand-wringing over China and Greece isn\\u2019t going away anytime soon, earnings season offers a welcome distraction from the global circus that has long dominated the headlines.\", \"BlackBerry hires Cisco executive as sales head BlackBerry Ltd. tapped Cisco Systems Inc. executive Carl Wiese to serve as head of sales. The move, announced Monday morning, comes as BlackBerry continues to position itself more as a software company than hardware amid weak smartphone sales and strong competition from industry leaders Apple Inc. and Samsung Electronics [kr: 005930]. Wiese, who most recently served as senior vice president directing sales at Cisco, replaces John Sims, who has left the company. Shares of BlackBerry were up 0.9% to $7.76 in premarket trade, though they have fallen 20% over the last three months, compared with a 0.8% decline for the broader S&P 500. Last month, BlackBerry reported a 153% year-over-year increase in software and technology licensing revenue but a further deceleration in hardware sales.\", \"Analyst reiterates Apple's buy rating, downplays China impact Shares of Apple Inc. rose on Monday after an analyst at Cantor Fitzgerald reiterated his buy rating on the stock. \\\"Although we believe further weakness in China's stock market could take away some of the 'bling' purchases of iPhones, we do not believe this will change the positive momentum for Apple,\\\" said Brian White in a note. He projected further growth in China for Apple with 15% to 20% of Chinese subscribers likely to be candidates for high-end phones in the next five years. The analyst also said Apple is in the midst of a \\\"transformational super cycle\\\" but its prospects are as bright as ever. Apple shares gained 1.2% to $124.69, up for a second session in a row. The stock fell 2.5% last week, its worst weekly decline since middle of January. White's 12-month price target for Apple is $195.\", \"S&P, Nasdaq reclaim the breakdown point Focus: Consumer Discretionary, XLY, AAPL, SIGM, UA, TRIP, MGNX U.S. stocks are firmly higher to start Monday, rising after Greece and its creditors reached a bailout agreement. Against this backdrop, the S&P 500 has reclaimed its 2,080 breakdown point, and a close at current levels would place the index on firmer technical ground.\", \"Has the cable-cutting revolution finally arrived? Comcast will offer a broadcast TV streaming service for $15 a month Comcast will offer a broadcast TV streaming service for $15 a month.\", \"Fitbit dominance not threatened by Apple and Jawbone Fitbit has estimated 85% share of U.S. fitness tracker market Fitbit was initiated at ratings equivalent to buy at a handful of Wall Street brokerages on Monday thanks to its dominant share of fitness tracker market.\", \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": 0.014897, "explanation": "The actual 21-day forward return for USMV starting 2015-07-14 was +1.49%, which classifies as 'positive'.", "metadata": {"future_return": 0.014897, "horizon_days": 21, "hist_return": 0.01511, "annualized_vol": 0.101979, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180402_0110", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2018-04-02", "context_summary": "XLV over past 60 days: cumulative return -3.2%, annualized vol 18.9%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=73.42, end=71.05, cumulative_return=-3.2%, annualized_volatility=18.9%\nMacro context: {'fed_funds_rate': 1.67, 'cpi_yoy': 250.227, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.47, 't10y3m_spread': 1.01, 'breakeven_10y': 2.05, 'hy_oas': 3.72, 'ig_oas': 1.17, 'ted_spread': 0.61, 'mortgage_30y': 4.44, 'vix': 19.96999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-03-29] [\"Can the stock market stand up to the tech wreck? Bull market loses its leader The key question for investors is whether a sharp selloff in tech shares puts the broader bull market in danger.\", \"How to know when to buy, sell or hold popular tech stocks today Amid increasing volatility, investors need to understand position size, time horizon and diversification Amid increasing volatility, investors need to understand position size, time horizon and diversification.\", \"Smart Home Devices: These Categories Are Growing the Fastest As new categories emerge, smart speakers are still expected to grow quickly.\", \"Spotify initiated at outperform by RBC ahead of trading debut RBC Capital Markets analyst Mark Mahaney initiated shares of Spotify Technology with an outperform rating and $220 price target, ahead of the stock's expected public debut in early April. Mahaney's target price represents \\\"70%+ upside vs. recent private transaction price of $127.50,\\\" he wrote. He likes the large total addressable market for music-streaming services and Spotify's leading position in the market. The Consumer Technology Association believes consumers will spend $6.6 billion on music streaming services in 2018. Spotify has nearly twice as many paid subscribers as Apple Inc.'s Apple Music does. \\\"Very high global aided brand awareness, relatively high customer satisfaction scores, and superior data-driven personalization all combine to help Spotify maintain its leadership position,\\\" Mahaney wrote. As for Spotify's financials, he believes gross margin can expand from 21% in 2017 to upwards of 30% by 2022. He also points to declining churn rates.\", \"Will a robot care for you in your old age? The great potential\\u2014and challenges\\u2014 of artificial intelligence for an aging population Realizing AI\\u2019s possibilities will require businesses to make it less expensive and for health care providers to embrace it.\", \"Nearly a billion smart home devices will ship in 2022, says IDC Market research firm IDC said Thursday that it expected shipments of smart home devices to grow at an 18.5% annual clip over the next five years, ultimately reaching 940 million devices shipped by 2022. Shipments of smart speakers will grow even faster over that period, IDC said, at a 32% annual rate. \\\"While it's still early days for the smart home market - and the wider consumer IoT ecosystem in general - we expect to see considerable growth over the next few years, especially as consumers become more aware of and increasingly interact with smart assistant platforms like Amazon's Alexa and [Alphabet Inc.'s ] Google Assistant,\\\" IDC senior research analyst Adam Wright said in a release. Amazon's Echo family of speakers is thought to be the market leader. Apple Inc. recently came out with its $349 HomePod speaker and will look to capture share of the market. Apple shares are up 18% over the past 12 months, while the Dow Jones Industrial Average has gained 17%.\", \"Apple\\u2019s Cook Has Pointed Ad\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": 0.033564, "explanation": "The actual 21-day forward return for XLV starting 2018-04-02 was +3.36%, which classifies as 'positive'.", "metadata": {"future_return": 0.033564, "horizon_days": 21, "hist_return": -0.032271, "annualized_vol": 0.188794, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180607_0113", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2018-06-07", "context_summary": "BTC-USD over past 60 days: cumulative return +9.0%, annualized vol 55.0%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=7023.52, end=7653.98, cumulative_return=+9.0%, annualized_volatility=55.0%\nMacro context: {'fed_funds_rate': 1.7, 'cpi_yoy': 251.018, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.45, 't10y3m_spread': 1.02, 'breakeven_10y': 2.14, 'hy_oas': 3.44, 'ig_oas': 1.21, 'ted_spread': 0.41, 'mortgage_30y': 4.56, 'vix': 11.640000343322754}\nMarket regime: sideways\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": -0.231147, "explanation": "The actual 21-day forward return for BTC-USD starting 2018-06-07 was -23.11%, which classifies as 'negative'.", "metadata": {"future_return": -0.231147, "horizon_days": 21, "hist_return": 0.089764, "annualized_vol": 0.550122, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20171219_0116", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2017-12-19", "context_summary": "EEM over past 60 days: cumulative return +4.7%, annualized vol 13.0%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=36.60, end=38.30, cumulative_return=+4.7%, annualized_volatility=13.0%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 247.805, 'unemployment': 4.1, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.55, 't10y3m_spread': 1.01, 'breakeven_10y': 1.89, 'hy_oas': 3.64, 'ig_oas': 1.0, 'ted_spread': 0.27, 'mortgage_30y': 3.93, 'vix': 9.729999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-12-18] [\"AMD stock jumps after Macquarie upgrade Shares of Advanced Micro Devices rose 4.7% in Monday morning trading after analysts at Macquarie Research upgraded the stock to neutral from underperform. While the analysts, led by Srini Pajjuri, see \\\"headwinds\\\" in the cryptocurrency market and predict only moderate share gains in both PCs and graphics processing units (GPUs), they're more upbeat about other aspects of the business, including the opportunity for growth in average selling prices [ASP] and a recent partnership with Intel Corp. . The firm predicts \\\"further ASP tailwinds in GPUs driven by Apple iMac Pro win and the recent Intel partnership (for gaming notebooks).\\\" The analysts also see potential for AMD's server business, thanks to \\\"encouraging\\\" arrangements with Microsoft Inc. , Baidu Inc. , and Hewlett Packard Enterprise Co. , though they caution that share gains will take time. They raised their price target on shares to $11, from $10. AMD shares have fallen 5.8% so far in 2017, compared with a 20% gain for the S&P 500 Index and a 40% rise for the Philadelphia Semiconductor Index .\", \"Nasdaq breaks above 7,000 for the first time The Nasdaq Composite Index rallied to a record on Monday, breaking above the 7,000 level for the first time in its history. The index rose 0.9%, or 63 points, to hit an intraday record of 7,000.96. Among the biggest boosts to the index was Apple Inc. , the largest U.S. stock by market capitalization, which rose 1.4%. Alphabet Inc. , the parent company of Google, rose 1% on the day while Amazon.com Inc. was up 0.9%. The gains came on growing confidence congressional Republicans will succeed in getting a major tax bill passed this week. The Dow Jones Industrial Average rose 0.7% to 24,835 while the S&P 500 was up 0.7% at 2,693. Thus far this year, the Nasdaq is up 30%, boosted in large part by the outperformance of large-cap technology and internet stocks. According to Dow Jones data, it took the index 165 days to cross the milestone after hitting 6,000 for the first time. This is the third-fastest period that the Nasdaq has crossed a 1,000-point milestone in its history.\", \"Apple: Survey Says \\u2018Very Strong Demand\\u2019 for iPhone X in China, Says RBC The Chinese are pretty wild about Apple's iPhone X, despite prices of $999 or $1,149, depending on memory capacity, according to a survey conducted by RBC Capital's Amit Daryanani.\", \"How Audio Habits Differ by Age, in One Chart People between 18 and 29 reported giving traditional AM/FM radio just 24% of their listening time.\", \"AMD stock surges after analyst cheers server opportunities, mix shift The crypto business may present \\u2018headwinds\\u2019 in 2018, but other segments look promising AMD shares rallied Monday after an analyst upgraded shares to neutral.\", \"Stocks close at records in broad tax-driven rally; Dow posts 70th record close of 2017 Dow posts highest number of record closes in a year ever U.S. stocks closed higher on Monday, with major index\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": 0.102513, "explanation": "The actual 21-day forward return for EEM starting 2017-12-19 was +10.25%, which classifies as 'positive'.", "metadata": {"future_return": 0.102513, "horizon_days": 21, "hist_return": 0.046626, "annualized_vol": 0.130434, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20171218_0121", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2017-12-18", "context_summary": "FXI over past 60 days: cumulative return +2.6%, annualized vol 18.7%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=36.16, end=37.11, cumulative_return=+2.6%, annualized_volatility=18.7%\nMacro context: {'fed_funds_rate': 1.41, 'cpi_yoy': 247.805, 'unemployment': 4.1, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.51, 't10y3m_spread': 1.04, 'breakeven_10y': 1.88, 'hy_oas': 3.64, 'ig_oas': 1.0, 'ted_spread': 0.32, 'mortgage_30y': 3.93, 'vix': 9.729999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-12-15] [\"5 Stocks To Watch For December 15, 2017\", \"A Peek Into The Markets: U.S. Stock Futures Signal Higher Start On Wall Street\", \"5 Biggest Price Target Changes For Friday\", \"Mid-Morning Market Update: Markets Open Higher; Adobe Earnings Top Expectations\", \"6 Technical Levels To Watch From Friday. Morning's PreMarket Prep:\", \"Mid-Day Market Update: ShiftPixy Gains Following Q4 Results; Verastem Shares Plummet\", \"Mid-Afternoon Market Update: Dow Surges Over 150 Points; Longfin Shares Spike Higher\", \"Analysts React To Adobe's $2B Fourth Quarter\", \"Analysts React To Adobe's $2B Fourth Quarter\", \"Mid-Afternoon Market Update: Dow Surges Over 150 Points; Longfin Shares Spike Higher\", \"Mid-Day Market Update: ShiftPixy Gains Following Q4 Results; Verastem Shares Plummet\", \"6 Technical Levels To Watch From Friday. Morning's PreMarket Prep:\", \"Mid-Morning Market Update: Markets Open Higher; Adobe Earnings Top Expectations\", \"5 Biggest Price Target Changes For Friday\", \"A Peek Into The Markets: U.S. Stock Futures Signal Higher Start On Wall Street\", \"5 Stocks To Watch For December 15, 2017\", \"Mid-Day Market Update: ShiftPixy Gains Following Q4 Results; Verastem Shares Plummet Midway through trading Friday, the Dow traded up 0.58 percent to 24,649.56 while the NASDAQ climbed 0.55 percent to 6,894.42. The S&P also rose, gaining 0.72 percent to 2,671.12. Leading and Lagging Sectors On Friday, the financial sector proved to be a source of strength for the market. Leading the sector was strength from Wins Finance Holdings Inc (NASDAQ: WINS ) and Navient Corp (NASDAQ: NAVI ). In trading on Friday, consumer discretionary shares rose by just 0.2 percent. Top Headline Adobe Systems Incorporated (NASDAQ: ADBE ) posted stronger-than-expected profit for its fourth quarter on Thursday. Adobe reported Q4 adjusted earnings of $1.26 per share on revenue of $2.01 billion. Analysts expected earnings of $1.16 per share on revenue of $1.95 billion. Adobe expects Q1 adjusted earnings of $1.27 per share on revenue of $2.04 billion. Equities Trading UP ShiftPixy Inc (NASDAQ: PIXY ) shares shot up 99 percent to $4.31 following Q4 earnings report. ShiftPixy reported sales of $20.244 million in the fourth quarter, up from $8.46 million year-over-year. The company sees first quarter gross billings of $40 million. Shares of Longfin Corp (NASDAQ: LFIN ) got a boost, shooting up 96 percent to $10.56 after the company announced agreement to acquire Ziddu.com. Crocs, Inc. (NASDAQ: CROX ) shares were also up, gaining 12 percent to $12.25. Stifel Nicolaus upgraded Crocs from Hold to Buy. Equities Trading DOWN Verastem Inc (NASDAQ: VSTM ) shares dropped 13 percent to $3.19. Verastem priced its $25 million common stock offering. Shares of Rosetta Genomics Ltd. ( USA ) (NASDAQ: ROSG ) were down 16 percent to $0.53 after the company agreed to be acquired by Genoptix for $10 million. TrovaGene Inc (NASDAQ: TROV ) was down, falling around 42 percent to $0.25. Trovagene priced its 15 million share co\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": 0.132782, "explanation": "The actual 21-day forward return for FXI starting 2017-12-18 was +13.28%, which classifies as 'positive'.", "metadata": {"future_return": 0.132782, "horizon_days": 21, "hist_return": 0.026245, "annualized_vol": 0.186523, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20191126_0124", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2019-11-26", "context_summary": "XLV over past 60 days: cumulative return +10.8%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=80.21, end=88.90, cumulative_return=+10.8%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 257.879, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.15, 't10y3m_spread': 0.15, 'breakeven_10y': 1.62, 'hy_oas': 4.08, 'ig_oas': 1.12, 'ted_spread': 0.34, 'mortgage_30y': 3.66, 'vix': 11.869999885559082}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-25] [\"Noteworthy ETF Outflows: TQQQ, CMCSA, CSCO, ADBE Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel, one standout is the ProShares ProShares UltraPro QQQ (Symbol: TQQQ) where we have detected an approximate $92.8 million dollar outflow -- that's a 2.5% decrease week over week (from 49,850,000 to 48,600,000). Among the largest underlying components of TQQQ, in trading today Comcast Corp (Symbol: CMCSA) is off about 1.9%, Cisco Systems Inc (Symbol: CSCO) is up about 1%, and Adobe Inc (Symbol: ADBE) is higher by about 1.1%. For a complete list of holdings, visit the TQQQ Holdings page \\u00bb The chart below shows the one year price performance of TQQQ, versus its 200 day moving average: Looking at the chart above, TQQQ's low point in its 52 week range is $30.32 per share, with $76.47 as the 52 week high point \\u2014 that compares with a last trade of $76.36. 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 experienced notable outflows \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Why Adobe's Revenue Growth Rate Looks Poised To Increase In 2020 Adobe\\u00c2 (NASDAQ: ADBE)\\u00c2 makes money by selling software for creative content and marketing purposes with a focus on user experience. The company\\u00e2\\u0080\\u0099s products are offered as subscription-based service and through licenses.\\u00c2 Adobe competes with Apple, Autodesk, Avid, Corel, Microsoft, Affinity, Quark in its Digital Media offerings, and Google, IBM, Oracle, salesforce.com, SAP, SAS, Teradata, Shopify in its Digital Experience segment. Adobe\\u2019s strong results for the third quarter highlight the resilience of its revenue streams despite an uncertain macro-environment.\\u00c2 We highlight trends in Adobe\\u2019s Revenues over the years along with our forecast for 2019 and 2020 in an interactive dashboard. We believe that the company\\u2019s\\u00c2 2 core operating segments \\u2013 Digital Media as well as Digital Experience \\u2013 have significant growth prospects, which will help revenues\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": 0.040632, "explanation": "The actual 21-day forward return for XLV starting 2019-11-26 was +4.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.040632, "horizon_days": 21, "hist_return": 0.108281, "annualized_vol": 0.118861, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20170317_0129", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2017-03-17", "context_summary": "QQQ over past 60 days: cumulative return +9.9%, annualized vol 6.6%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=112.80, end=123.99, cumulative_return=+9.9%, annualized_volatility=6.6%\nMacro context: {'fed_funds_rate': 0.91, 'cpi_yoy': 243.892, 'unemployment': 4.4, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.18, 't10y3m_spread': 1.8, 'breakeven_10y': 2.02, 'hy_oas': 3.88, 'ig_oas': 1.22, 'ted_spread': 0.43, 'mortgage_30y': 4.3, 'vix': 11.210000038146973}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-03-16] [\"Q1 2017 Real-Time Call Brief\", \"Earnings Scheduled For March 16, 2017\", \"10 Stocks To Watch For March 16, 2017\", \"Adobe Reports Q1 Adj. EPS $0.94 vs $0.87 Est., Sales $1.68B vs $1.65B Est.\", \"Adobe Surges After Record Beat\", \"From Adobe Q1 Earnings Conference Call: Sees Q2 Sales ~$1.73B vs $1.72B Est., Adj. EPS ~$0.94 vs $0.91 Est.\", \"From Adobe Q1 Earnings Conference Call: Sees Q2 Sales ~$1.73B vs $1.72B Est., Adj. EPS ~$0.94 vs $0.91 Est.\", \"Adobe Surges After Record Beat\", \"Adobe Reports Q4 Adj. EPS $0.94 vs $0.87 Est., Sales $1.68B vs $1.65B Est.\", \"10 Stocks To Watch For March 16, 2017\", \"Earnings Scheduled For March 16, 2017\", \"Adobe Systems Incorporated (ADBE) Stock Soars on Earnings Beat InvestorPlace - Stock Market News, Stock Advice & Trading Tips I argued coming into Adobe Systems Incorporated (NASDAQ: ADBE ) earnings that there was no reason to bet against Adobe stock . Adobe earnings had come in ahead of consensus for four straight quarters. Adobe stock had quadrupled in less than five years. As the old saw goes, \\\"The trend is your friend.\\\" Clearly, that trend was in favor of ADBE. Source: Shutterstock For a fifth straight quarter, Adobe earnings came in ahead of analyst estimates. Non-GAAP earnings of 94 cents per share beat the Street by seven cents. Nearly 22% revenue growth was two points ahead of consensus. ADBE stock is up roughly 4% in after-hours trading, after yet another quarter that seems to support the long-term bull case for Adobe stock. Adobe Earnings: The Fifth Straight Beat Adobe's fiscal first-quarter earnings were even more impressive than past beats. On average, Adobe earnings had come in about 4% above consensus the past few quarters; in Q1 FY17, Adobe beat by a solid 8%. 7 Dividend Stocks With Yields That Grow Like Weeds Beyond the numbers, the news was good - and broad-based. Digital Media Annualized Recurring Revenue (ARR), a key measure of the company's success in \\\"cloud,\\\" hit $4.25 billion, up nearly 7% simply in the first three months. Marketing Cloud revenue of $477 million was up over 26% year-over-year, actually accelerating from prior-year growth of 21%. Non-GAAP operating income increased 42%, and non-GAAP net income rose 40%. As CFO Mark Garrett pointed out in the Q1 release, \\\"Adobe achieved record revenue, profit and cash flow\\\" in the quarter. All told, the Adobe earnings report was a blowout by any measure. What Earnings Mean for Adobe Stock Heading into the quarter, it seemed likely that ARR, in particular, would be a focus of investors. That figure is moving to a larger and larger share of overall revenue: now about 70% on a trailing twelve-month basis. The ability to continue torrid growth even on a base that size - and without simply taking revenue away from legacy product sales, like Microsoft Corporation (NASDAQ: MSFT ) does with Office - seems likely to support Adobe stock in trading on Friday. The second area of focus is in the Marketing Cloud business. Adobe obviously has little comp\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.001595, "explanation": "The actual 21-day forward return for QQQ starting 2017-03-17 was -0.16%, which classifies as 'flat'.", "metadata": {"future_return": -0.001595, "horizon_days": 21, "hist_return": 0.099259, "annualized_vol": 0.066396, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160823_0132", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2016-08-23", "context_summary": "EWJ over past 60 days: cumulative return +6.6%, annualized vol 15.8%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=38.26, end=40.77, cumulative_return=+6.6%, annualized_volatility=15.8%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 240.545, 'unemployment': 4.9, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.79, 't10y3m_spread': 1.26, 'breakeven_10y': 1.47, 'hy_oas': 5.18, 'ig_oas': 1.41, 'ted_spread': 0.54, 'mortgage_30y': 3.43, 'vix': 12.270000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-08-22] [\"Recent deaths reopen scrutiny of Foxconn working conditions Precarious existence for Chinese factory workers \\u201cWhy is it always the entry-level workers who jump?\\u201d asked one Foxconn employee.\", \"Viacom\\u2019s MTV and Comedy Central Can Come Back Apple and Converse were once left for dead by pop culture before reviving. Viacom\\u2019s key brands can too.\", \"Apple and augmented reality: Where we\\u2019re going, we won\\u2019t need iPhones iPhone could just be bridge to future where virtual and augmented reality are a $162 billion market Apple Inc.\\u2019s iPhone might be just a bridge to a world in which we no longer need a screen.\", \"Garmin: Raymond James Cuts to Hold as Improving Thesis \\u2018Largely Played Out\\u2019 Shares of navigational technology and wearables maker Garmin (GRMN) are down $1.17, or 2%, at $53.21, after Raymond James\\u2019s Tavis McCourt this morning cut his rating on the stock to Markert Perform from Outperform, warning that the balance of risk and of reward in the shares is \\\"more muted following 47% appreciation YTD and a 19% move since the company\\u2019s strong 2Q16 results.\\\"His thesis on the stock has \\u201cplayed out,\\u201d he writes:We upgraded Garmin in 2015 following a series of EPS disappointments driven by the euro decline and market share issues in its wearables business. Our thought process was that currency would normalize y/y in early 2016 and forthcoming product launches incorporating embedded heart rate monitors across its wearables product line would drive renewed growth.And the move in the stock\\u2019s valuation from \\\"~9x ex-cash P/E to about ~16x ex-cash P/E\\u201d means the shares are near \\u201clevels that have generally coincided with more muted performance.\\\"McCourt doesn\\u2019t expect much competition from Apple (AAPL) and Fitbit (FIT), but he is also wary of holding shares while both come out with new offerings:\", \"Apple Still Holds Vast Majority of Smartphone Profit, If a Bit Less, Says Canaccord Mike Walkley with Canaccord Genuity today reiterates a Buy rating on shares of Apple (AAPL), and a $120 price target, writing that the company still garners the lion\\u2019s share of smartphone industry profit with the iPhone, but that Samsung Electronics (005930KS) put a big dent in that with stepped-up promotions of its \\u201cGalaxy\\u201d line of devices.Apple went from 90% of smartphone profit in Q1 of this year to just 75%, estimates Walkley, as both asian competitors such as OPPO and Samsung stepped up their offerings last quarter:While Apple continues to capture strong share of the premium tier smartphone segment, its industry profits and market share have declined the past several quarters as the iPhone 6 and 6S cycles near the end of their 2-year run. Android OEMs have taken advantage of Apple\\u2019s aging products with improved results for several OEMs including Chinese OEMs and Samsung [\\u2026] Apple continues to dominate industry operating profits and captured 75% of Q2/ C2016 handset indust\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.035541, "explanation": "The actual 21-day forward return for EWJ starting 2016-08-23 was +3.55%, which classifies as 'positive'.", "metadata": {"future_return": 0.035541, "horizon_days": 21, "hist_return": 0.065594, "annualized_vol": 0.158397, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20181121_0137", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2018-11-21", "context_summary": "EMB over past 60 days: cumulative return -2.2%, annualized vol 5.4%. Market regime: sideways.", "question": "Asset: EMB\nHistorical prices (past 60 trading days): start=73.39, end=71.81, cumulative_return=-2.2%, annualized_volatility=5.4%\nMacro context: {'fed_funds_rate': 2.2, 'cpi_yoy': 252.594, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.27, 't10y3m_spread': 0.67, 'breakeven_10y': 1.97, 'hy_oas': 4.33, 'ig_oas': 1.39, 'ted_spread': 0.31, 'mortgage_30y': 4.94, 'vix': 22.479999542236328}\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": 0.016817, "explanation": "The actual 21-day forward return for EMB starting 2018-11-21 was +1.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.016817, "horizon_days": 21, "hist_return": -0.021557, "annualized_vol": 0.053809, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201021_0140", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2020-10-21", "context_summary": "BNB-USD over past 60 days: cumulative return +29.5%, annualized vol 87.9%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=22.24, end=28.80, cumulative_return=+29.5%, annualized_volatility=87.9%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.67, 't10y3m_spread': 0.71, 'breakeven_10y': 1.72, 'hy_oas': 4.9, 'ig_oas': 1.32, 'ted_spread': 0.12, 'mortgage_30y': 2.81, 'vix': 29.350000381469727}\nMarket regime: sideways\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": -0.061002, "explanation": "The actual 21-day forward return for BNB-USD starting 2020-10-21 was -6.10%, which classifies as 'negative'.", "metadata": {"future_return": -0.061002, "horizon_days": 21, "hist_return": 0.295129, "annualized_vol": 0.8788, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200911_0143", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2020-09-11", "context_summary": "IWM over past 60 days: cumulative return +5.9%, annualized vol 22.1%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=132.16, end=139.98, cumulative_return=+5.9%, annualized_volatility=22.1%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 259.997, 'unemployment': 7.8, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.54, 't10y3m_spread': 0.56, 'breakeven_10y': 1.69, 'hy_oas': 5.16, 'ig_oas': 1.37, 'ted_spread': 0.13, 'mortgage_30y': 2.86, 'vix': 29.709999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-10] [\"$718 mln options unwind signals more caution on tech stocks By April Joyner NEW YORK, Sept 10 (Reuters) - A large options player unwound bets on several technology-related companies on Thursday, offering another sign of the market's recently diminished appetite for shares in the sector. The unidentified investor took off around $718 million of notional value in bullish options spreads known as risk reversals in Facebook Inc FB.O, Netflix Inc NFLX.O and Adobe Inc ADBE.O, according to a Reuters analysis based on data from Susquehanna Financial Group. The investor partially closed a similar position in Saleforce.com Inc CRM.N on Tuesday. The trades were structured differently than positions widely attributed to SoftBank Group Corp 9984.T, whose big bets on equity derivatives tied to tech firms came to light last week. Thursday's unwinds were partial, and the positions still have a notional value of around $1.66 billion, the analysis showed. Still, investors following large institutional trades in tech-related names may view the moves as a bearish signal, said Christopher Murphy, co-head of derivatives strategy at Susquehanna Financial Group. \\\"Investors have been watching this big bullish flurry of trades that happened earlier in August, looking for signs of it beginning to be closed,\\\" he said. \\\"It could have a negative impact on sentiment.\\\" Robust options activity from institutions like SoftBank and hordes of retail investors is widely believed to have contributed to last month's big run-up in stocks, as well as a recent sell-off that the Nasdaq confirmed on Tuesday was a correction, commonly defined as a decline of 10% or more from an index's high. U.S. stocks closed lower after a choppy session on Thursday as heavyweight tech-related stocks resumed their decline following a sharp rebound the previous session. Overall, demand for protective put options has risen among tech-related names. But frothiness still remains in call options, which are used to position for upside in stocks, for certain companies such as Apple Inc AAPL.O and Tesla Inc TSLA.O, said Arnim Holzer, macro and correlation defense strategist at EAB Investment Group. Skew, a measure that gauges demand for puts in relation to calls, on Tesla options turned negative once again on Thursday, according to data from Trade Alert, reflecting surging demand for calls. \\\"There is a fair amount of call skew in some of those names,\\\" Holzer said. \\\"That gives us a sense that there can still be some downward pressure, relative to the S&P, in those very large-cap tech names.\\\" Most of the trades attributed to SoftBank, which are seen as bullish positions on tech-related names, remain in place. Some have been moved to higher strike prices in an apparent bet on a further rise in the underlying shares. SoftBank declined to comment. The trades attributed to SoftBank are call spreads - a combination of a put purchase and a put sale - several of which expire in November. By contrast, the bullish r\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": 0.102342, "explanation": "The actual 21-day forward return for IWM starting 2020-09-11 was +10.23%, which classifies as 'positive'.", "metadata": {"future_return": 0.102342, "horizon_days": 21, "hist_return": 0.05911, "annualized_vol": 0.220905, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20211022_0146", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2021-10-22", "context_summary": "XLY over past 60 days: cumulative return +5.2%, annualized vol 14.5%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=88.57, end=93.14, cumulative_return=+5.2%, annualized_volatility=14.5%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.23, 't10y3m_spread': 1.62, 'breakeven_10y': 2.64, 'hy_oas': 3.03, 'ig_oas': 0.89, 'ted_spread': 0.07, 'mortgage_30y': 3.09, 'vix': 15.010000228881836}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-21] [\"Customer engagement platform Batch raises $23 million after years of bootstrapping If you\\u2019ve been working in the French tech ecosystem, you may remember a startup called AppGratis. From the team that brought you AppGratis, Batch is a customer engagement platform that has been operating under the radar for many years. It\\u2019s a customer engagement platform that competes with Braze as well as big enterprise solutions from Salesforce, Adobe, Oracle, IBM and Microsoft.\", \"Apple will require unvaccinated employees to test for COVID-19 daily Apple will require all unvaccinated corporate employees to be tested for COVID-19 every time they have to work in the office.\", \"The Morning After: Will Facebook change its name? Today\\u2019s headlines: Some Windows 11 users can start testing Android apps, Netflix CEO says he 'screwed up' on Dave Chappelle as employees walk out, \\u2018Cyberpunk 2077' PS5 and Xbox Series X/S upgrades delayed until 2022.\", \"Apple will require unvaccinated employees to test for COVID-19 daily Apple has yet to issue a mandate similar to Google's that would require all employees to be vaccinated, but it's tightening its COVID-19 protocols nonetheless. According to Bloomberg, the tech giant will start requiring all unvaccinated corporate employees to be tested for COVID-19 every time they have to work in the office instead of working from home. Back in September, Bloomberg reported that Apple asked employees to share their vaccination status voluntarily.\", \"Apple's AirTags are 10 percent off at Woot today Apple's AirTags are down to $26 each when you buy them from Woot today only.\", \"Meet the 2021 Women in Technology Hall of Fame Inductees Female Executives and Leaders to be Honored for Their Impact and Achievements Featured Image for WITI - Women in Technology International Featured Image for WITI - Women in Technology International LOS ANGELES, Oct. 21, 2021 (GLOBE NEWSWIRE) -- Women in Technology International (WITI), the leading organization for the advancement and inclusion of women in business and technology, today announced its eight inductees into the 2021 Women in Technology Hall of Fame. The honorees will be inducted dur\", \"Product Marketing Alliance: From $0 to $1M+ ARR in 12 months: product marketing is the world's fastest-growing job role The role of product marketing is on the rise. It's no longer seen as a nice-to-have, it's a company commodity for forward-thinking, fast-growing, market-dominating organizations worldwide.\", \"Google lowers Play Store fees to 15% on subscription apps, as low as 10% for media apps Google is lowering commissions on all subscription-based businesses on the Google Play Store, the company announced today. Previously, the company had followed Apple's move by reducing commissions from 30% to 15% on the first $1 million of developer earnings. Instead of charging them 30% in the first year, which lowers to 15% in year two and beyond, Google says developers will only be charged 15% from day o\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": 0.094111, "explanation": "The actual 21-day forward return for XLY starting 2021-10-22 was +9.41%, which classifies as 'positive'.", "metadata": {"future_return": 0.094111, "horizon_days": 21, "hist_return": 0.05162, "annualized_vol": 0.144775, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20201110_0151", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2020-11-10", "context_summary": "ACWI over past 60 days: cumulative return +5.4%, annualized vol 18.6%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=73.41, end=77.40, cumulative_return=+5.4%, annualized_volatility=18.6%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.911, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.79, 't10y3m_spread': 0.85, 'breakeven_10y': 1.73, 'hy_oas': 4.22, 'ig_oas': 1.19, 'ted_spread': 0.1, 'mortgage_30y': 2.78, 'vix': 25.75}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-11-09] [\"Adobe to buy marketing workflow startup Workfront for $1.5 bln Adds detail of deal Nov 9 (Reuters) - Photoshop maker Adobe Inc ADBE.O said on Monday it would buy Workfront, a work management platform for marketers, for $1.5 billion to help its customers collaborate better at a time when millions are forced to work from home. Workfront, which has more than 3,000 customers and one million users, helps companies manage content, plan and track marketing campaigns as they attempt to keep productivity levels up with most of their employees working remotely. Both companies are longstanding partners and already have over 1,000 shared customers. Adobe is a premier software firm housing the industry's most renowned graphics and photo editing application, however, it has not had the same success with collaboration tools. Upon close, Workfront Chief Executive Officer Alex Shootman will continue to lead the Workfront team, Adobe said in a statement. The deal is expected to close during Adobe's first quarter of fiscal 2021. (Reporting by Shradha Singh in Bengaluru; Editing by Aditya Soni and Shailesh Kuber) ((Shradha.Singh@thomsonreuters.com; within U.S. +1 646 223 8780 Ext: 2804, outside U.S. +91 80 6182 2630;)) The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe To Buy Workfront For $1.5 Bln (RTTNews) - Adobe Inc. (ADBE) Monday announced it has agreed to acquire Workfront, a work management platform for marketers, for $1.5 billion. The deal is expected to close during the first quarter of 2021, subject to regulatory approval and customary closing conditions. Until the transaction closes, each company will continue to operate independently. Upon close, Workfront CEO Alex Shootman will continue to lead the Workfront team, reporting to Anil Chakravarthy, executive vice president and general manager, Digital Experience Business and Worldwide Field Operations. \\\"Adobe and Workfront share a common affinity to help the modern marketer thrive in an ever-evolving, increasingly demanding setting,\\\" said Alex Shootman, CEO, Workfront. \\\"We're excited to join Adobe and believe this will be a tremendous opportunity for our customers and partners.\\\" Adobe said that Workfront is equipped with APIs that enable a seamless connection to Adobe Creative Cloud and Adobe Experience Cloud. Adobe and Workfront share 1,000 of customers, including Deloitte, Under Armour, Nordstrom, Prudential Financial, T-Mobile, and The Home Depot. ADBE closed Monday's trading at $471.14, down $23.49 or 4.75%, on the Nasdaq. The stock, however, gained $0.05 or 0.01%, in the after-hours trade. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"SoftBank Discloses $20 Billion Tech-Stock Bet, Big Gains for Vision Fund The company has more cash than it can quickly deploy, and it has poured a lot of it into highly liquid tech sha\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": 0.050659, "explanation": "The actual 21-day forward return for ACWI starting 2020-11-10 was +5.07%, which classifies as 'positive'.", "metadata": {"future_return": 0.050659, "horizon_days": 21, "hist_return": 0.054359, "annualized_vol": 0.185646, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20201229_0154", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2020-12-29", "context_summary": "ACWI over past 60 days: cumulative return +13.7%, annualized vol 15.4%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=72.64, end=82.61, cumulative_return=+13.7%, annualized_volatility=15.4%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 262.045, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.81, 't10y3m_spread': 0.83, 'breakeven_10y': 1.97, 'hy_oas': 3.89, 'ig_oas': 1.05, 'ted_spread': 0.15, 'mortgage_30y': 2.71, 'vix': 21.700000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-12-28] [\"Stand By Chip Champ Advanced Micro Devices Even at Higher Price Points InvestorPlace - Stock Market News, Stock Advice & Trading Tips For investors in Advanced Micro Devices (NASDAQ:AMD), the temptation to take profits is understandable. Anyone who bought AMD stock early in 2020 can easily declare himself/herself a winner and cash out. AMD) logo outside of a corporate building\\\" width=\\\"300\\\" height=\\\"169\\\"> Source: Sundry Photography / Shutterstock.com After all, AMD is a stock that more than doubled from mid-March to December. Skeptics might wonder how much further AMD stock can possibly go after a run like that. As we\\u2019ll discover, the concerns over valuation are understandable. An argument can be made in favor of taking some chips off the table when it comes to AMD stock. On the other hand, it\\u2019s also possible to assess the company\\u2019s progress and choose to hold on to one\\u2019s AMD shares. Perhaps the bull run can continue into 2021. So, let\\u2019s home in on the AMD stock price and consider whether the stock\\u2019s valuation is a deal breaker. A Closer Look at AMD Stock At its lowest point in March of 2020, AMD stock bottomed out at $36.75. Even a tech stock like AMD wasn\\u2019t impervious to the Covid-19 crisis at that time. 7 Undervalued Stocks That Could Soar in 2021 Yet, by the middle of April, AMD stock had already returned to its pre-pandemic price. The swift recovery was likely due to the market\\u2019s belief that the technology sector could thrive during lockdowns. AMD stock took another big leg up during the summer of 2020. During that time, the stock quickly rocketed to the $85 level. Then the bulls took a much-needed breather for a couple of months. In December, the AMD stock bulls came back and began to push the share price beyond the $90 level. In fact, on Dec. 23, AMD shares hovered near $92 or $93. At that time, however, the trailing 12-month price-to-earnings ratio reached 125. Meanwhile, the trailing 12-month price-to-earnings ratio of rival Intel\\u2019s (NASDAQ:INTC) stock was around 9. Therefore, value-focused investors will need to be convinced that AMD stock is worth its price tag. Undeniable Revenue Growth If any AMD shareholders have been concerned about the stock\\u2019s valuation, a glance at the company\\u2019s fiscal stats should help to put them at ease. Suffice it to say that Advanced Micro Devices\\u2019 third quarter was an absolute blockbuster. Even the most optimistic commentators might not have expected the quarterly results that the company posted. Here are the bullet points for Advanced Micro Devices\\u2019 third quarter: $2.8 billion in revenues, up 56% year-over-year and 45% quarter-over-quarter Revenues from the computing and graphics segment totaled $1.67 billion, up 31% year-over-year and 22% quarter-over-quarter Net income was $390 million, a huge improvement over the $120 million posted a year ago and $157 million recorded in the prior quarter Diluted earnings per share came to 32 cents, \n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.000886, "explanation": "The actual 21-day forward return for ACWI starting 2020-12-29 was +0.09%, which classifies as 'flat'.", "metadata": {"future_return": 0.000886, "horizon_days": 21, "hist_return": 0.13727, "annualized_vol": 0.154156, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20201117_0159", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2020-11-17", "context_summary": "MTUM over past 60 days: cumulative return +3.0%, annualized vol 25.6%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=138.55, end=142.73, cumulative_return=+3.0%, annualized_volatility=25.6%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.911, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.72, 't10y3m_spread': 0.82, 'breakeven_10y': 1.72, 'hy_oas': 4.5, 'ig_oas': 1.19, 'ted_spread': 0.13, 'mortgage_30y': 2.84, 'vix': 22.450000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-11-16] [\"A Covid Vaccine Is Coming. Here\\u2019s What It Means for the Stock Market. After years of disappointment, a rotation into value-oriented investments from growth could gain traction. International stocks, small-caps, and gold could also climb.\", \"What GM Recall of the Bolt Electric Vehicle Means for the Stock The recall is tied to a battery charging issue. Recalls don\\u2019t usually hit auto maker shares, but this one is worth watching.\", \"Intel Can Shine Again Repeated manufacturing delays have dented Intel\\u2019s reputation. Why the stock is down but not out.\", \"Facebook Stock Will Continue to Benefit from Online Advertising\\u2019s Rebound The online advertising market appears on pace for continued acceleration through the fourth quarter, a J.P. Morgan analyst says.\", \"Dow, S&P 500 end at record highs Monday as stock market rallies amid further vaccine progress U.S. stocks book a round of fresh records Monday, as a rally fueled by optimism on the COVID-19 vaccine front overshadowed skyrocketing case numbers.\", \"Warren Buffett\\u2019s Berkshire Hathaway Confirms Apple Stock Sale, Buys of Pfizer, Merck Warren Buffett\\u2019s Berkshire Hathaway trimmed holdings in Apple, in line with our estimate. It also initiated positions in drug giants AbbVie, Pfizer, and Merck. Berkshire Hathaway also slashed its JPMorgan investment.\", \"Samsung's latest monitor is a smart TV with PC features It\\u2019s the brand\\u2019s first smart TV with built-in WiFi, Bluetooth and Wireless DeX capability.\", \"Ambu A/S: Reporting of transactions made by persons discharging managerial responsibilities Please see attached file. Attachment * 16_11_2020_Michael H\\u00f8jgaard II\", \"How FlyBy Auto Transport Rises to the Top of Its Competitive Industry LOS ANGELES, CA / ACCESSWIRE / November 16, 2020 / Amid the heavily competitive and saturated auto transport market, it all boils down to a company's reliability and performance, leading people to give their trust.\", \"Moderna reports its COVID-19 vaccine is 94.5% effective in first data from Phase 3 trial Following fast on the heels of Pfizer's announcement of its COVID-19 vaccine efficacy, Moderna is also sharing positive results from its Phase 3 trial on Monday. The biotech company says that its COVID-19 vaccine candidate has shown efficacy of 94.5% in its first interim data analysis, which covers 95 confirmed COVID cases among its study participants, of which 90 were given the placebo, and only 5 received Moderna's mRNA-based vaccine. Further, of 11 severe cases of COVID-19, none were found among those who received the actual vaccine candidate.\", \"The Morning After: Updating to macOS Big Sur is messing up some MacBook Pros Engadget's daily tech news bulletin.\", \"Techfugees non-profit brings on new CEO to engage tech industry with refugee issues Techfugees, the global non-profit which advocates the use of technology to aid refugees and displaced people, has appointed tech entrepreneur and Raj Burman as its new CEO. Burman succeeds Jo\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": 0.068938, "explanation": "The actual 21-day forward return for MTUM starting 2020-11-17 was +6.89%, which classifies as 'positive'.", "metadata": {"future_return": 0.068938, "horizon_days": 21, "hist_return": 0.030165, "annualized_vol": 0.255717, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20150916_0162", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2015-09-16", "context_summary": "EMB over past 60 days: cumulative return -1.2%, annualized vol 5.9%. Market regime: sideways.", "question": "Asset: EMB\nHistorical prices (past 60 trading days): start=65.67, end=64.85, cumulative_return=-1.2%, annualized_volatility=5.9%\nMacro context: {'fed_funds_rate': 0.14, 'cpi_yoy': 237.498, 'unemployment': 5.0, 'gdp_growth_qoq': 18857.418, 't10y2y_spread': 1.46, 't10y3m_spread': 2.21, 'breakeven_10y': 1.56, 'hy_oas': 5.54, 'ig_oas': 1.66, 'ted_spread': 0.26, 'mortgage_30y': 3.9, 'vix': 22.540000915527344}\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": 0.0114, "explanation": "The actual 21-day forward return for EMB starting 2015-09-16 was +1.14%, which classifies as 'positive'.", "metadata": {"future_return": 0.0114, "horizon_days": 21, "hist_return": -0.012446, "annualized_vol": 0.05885, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190312_0165", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2019-03-12", "context_summary": "BNB-USD over past 60 days: cumulative return +138.9%, annualized vol 80.8%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=6.08, end=14.51, cumulative_return=+138.9%, annualized_volatility=80.8%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 254.277, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.17, 't10y3m_spread': 0.18, 'breakeven_10y': 1.91, 'hy_oas': 4.12, 'ig_oas': 1.29, 'ted_spread': 0.2, 'mortgage_30y': 4.41, 'vix': 14.329999923706056}\nMarket regime: sideways\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": 0.284539, "explanation": "The actual 21-day forward return for BNB-USD starting 2019-03-12 was +28.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.284539, "horizon_days": 21, "hist_return": 1.389069, "annualized_vol": 0.80794, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190819_0172", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2019-08-19", "context_summary": "BIL over past 60 days: cumulative return +0.3%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=76.76, end=77.01, cumulative_return=+0.3%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 2.13, 'cpi_yoy': 256.036, 'unemployment': 3.6, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.07, 't10y3m_spread': -0.32, 'breakeven_10y': 1.54, 'hy_oas': 4.47, 'ig_oas': 1.31, 'ted_spread': 0.31, 'mortgage_30y': 3.6, 'vix': 18.46999931335449}\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": 0.000961, "explanation": "The actual 21-day forward return for BIL starting 2019-08-19 was +0.10%, which classifies as 'flat'.", "metadata": {"future_return": 0.000961, "horizon_days": 21, "hist_return": 0.003284, "annualized_vol": 0.002183, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181004_0175", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2018-10-04", "context_summary": "IVV over past 60 days: cumulative return +5.9%, annualized vol 6.8%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=245.77, end=260.31, cumulative_return=+5.9%, annualized_volatility=6.8%\nMacro context: {'fed_funds_rate': 2.18, 'cpi_yoy': 252.772, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.3, 't10y3m_spread': 0.92, 'breakeven_10y': 2.16, 'hy_oas': 3.16, 'ig_oas': 1.11, 'ted_spread': 0.22, 'mortgage_30y': 4.72, 'vix': 11.609999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-03] Adobe Unveils Major Document Updates, Enhances PDF Experience Adobe Systems IncorporatedADBE is firing on all cylinders to enhance presence in the document management system market on the back of its robust tools and software. The company has recently added useful updates to its Adobe Document Cloud, enabling the users to share and edit portable document format (PDF) files seamlessly and securely. Adobe aims to enrich the PDF user experience with its latest advances in order to gain further traction in this data driven world where e-documentation is of primary importance. Coming to the price performance, shares of Adobe have returned 55.3% on a year-to-date basis, outperforming the industry 's rally of 28.6%. New Updates to Drive Growth The company has introduced central document hub and home view in Acrobat DC which will allow the users of Acrobat DC desktop app, Acrobat Reader mobile app and the new Adobe Document Cloud web app to access the files and documents from one single point. Further, the new updates will offer cross-platform capabilities which will enable the users of Acrobat Pro DC to edit their documents on tablets with touch sensor of the devices similar to desktops. Additionally, the combination of Adobe's Sensei, Adobe Scan and Acrobat DC will aid in filling forms and scanning business cards. Further, with the help of modified Adobe Sign, people can electronically sign PDFs in Acrobat DC. Furthermore, an improvised content review process will help in tracking the activities related to a PDF file such as info on who is sharing the file with how many reviewers. This will ease the collection of feedbacks. Moreover, the new updates will assist in solving the feedbacks within the PDF itself. All these new useful features are likely to strengthen the company's product portfolio. Further, they will attract more users to the company's platform, thus expanding the adoption rate of Adobe Document Cloud. This will aid the subscription revenues, consequently aiding the company's top- line. Adobe Systems Incorporated Revenue (TTM) Adobe Systems Incorporated Revenue (TTM) | Adobe Systems Incorporated Quote Market Opportunities Per a report from MarketsandMarkets, the global document management system market is expected to reach $6.78 billion by 2023 at a CAGR of 11.17% between 2017 and 2023. Adobe's latest updates in Acrobat which offers a set of a cloud-based document and collaboration subscription services, supports centralized online file sharing and contract signing solutions, will aid it in reaping benefits from this potential market. Further, the company's robust Document Cloud will aid the company to rapidly penetrate the document-centric collaboration software market which as per a report from Technavio, is projected to witness a CAGR of more than 10% between 2017 and 2021. Notably, all these will help Adobe to fortify its presence in the rapidly growing cloud market in today's world. Zacks Rank & Stocks to Consider Currently, Adobe car\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": -0.061185, "explanation": "The actual 21-day forward return for IVV starting 2018-10-04 was -6.12%, which classifies as 'negative'.", "metadata": {"future_return": -0.061185, "horizon_days": 21, "hist_return": 0.059165, "annualized_vol": 0.068097, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220707_0178", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2022-07-07", "context_summary": "XLF over past 60 days: cumulative return -15.9%, annualized vol 26.9%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=35.32, end=29.70, cumulative_return=-15.9%, annualized_volatility=26.9%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.913, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.04, 't10y3m_spread': 1.03, 'breakeven_10y': 2.29, 'hy_oas': 5.8, 'ig_oas': 1.65, 'ted_spread': 0.09, 'mortgage_30y': 5.7, 'vix': 26.729999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-06] [\"Beyond Crypto: This Is the Secret Sauce to Retiring a Millionaire While many would agree that the stock market has been the best tool historically to building long-term wealth, cryptocurrencies have taken that title in the past several years. Bitcoin and Ethereum, for example, have produced trailing five-year returns of 700% and 310%, respectively, compared with the S&P 500's total return of only 73% during that time. But with cryptocurrencies getting absolutely hammered over the past few months, now is a good time to reassess your investment philosophy and the path you want to take to achieve adequate financial returns. And if you want to retire a millionaire, a valid argument can be made that avoiding crypto altogether might be the right course of action now. Image source: Getty Images. Don't chase the shiny object With stories of individuals becoming millionaires virtually overnight by trading digital assets, a fear of missing out can no doubt be the feeling many non-crypto investors have been experiencing. It's human nature. We see others having incredible success doing something and we immediately want to copy that behavior. The problem, however, is that it completely goes against what a rational person should do. What really matters is how much a person is consistently saving, the time until retirement, and their risk tolerance. Building a financial plan that helps one achieve personal goals is the ultimate objective. While some cryptocurrencies have crushed stocks in recent years, they are not the right investment for everyone. For starters, digital assets are ridiculously volatile with daily moves greater than 10% a normal occurrence. And because the sector as a whole just started its teenage years -- Bitcoin was launched in January 2009 -- the potential range of outcomes for the still-nascent asset class is extremely wide. This is too much uncertainty for most to stomach. Furthermore, the lack of regulation with cryptocurrencies, something that is not an issue in the traditional financial system, adds to the level of risk. There are countless stories of scams. And even with legitimate projects, the total risk involved with different crypto enterprises is simply unknown. We're seeing this play out right now, with major crypto hedge fund Three Arrows Capital filing for bankruptcy protection and Voyager Digital, a large crypto brokerage, suspending all trading because of market conditions. It can certainly be tempting to buy into the hype of cryptocurrencies, especially given the monster returns some speculators have achieved by buying digital assets, but a safer approach is to just focus on owning stocks for the long haul. Do this instead There really is no secret to retiring a millionaire. It's actually quite simple. People should start investing at a young age and let compounding take care of the rest. But what's the right way to invest? If you have the time to study and research different businesses, then actively picking stocks might\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": 0.0479, "explanation": "The actual 21-day forward return for XLF starting 2022-07-07 was +4.79%, which classifies as 'positive'.", "metadata": {"future_return": 0.0479, "horizon_days": 21, "hist_return": -0.159173, "annualized_vol": 0.268517, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210914_0185", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-09-14", "context_summary": "MATIC-USD over past 60 days: cumulative return +53.5%, annualized vol 118.1%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.81, end=1.25, cumulative_return=+53.5%, annualized_volatility=118.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 273.91, 'unemployment': 4.7, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.12, 't10y3m_spread': 1.27, 'breakeven_10y': 2.37, 'hy_oas': 3.09, 'ig_oas': 0.9, 'ted_spread': 0.07, 'mortgage_30y': 2.88, 'vix': 19.3700008392334}\nMarket regime: sideways\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": -0.001706, "explanation": "The actual 21-day forward return for MATIC-USD starting 2021-09-14 was -0.17%, which classifies as 'flat'.", "metadata": {"future_return": -0.001706, "horizon_days": 21, "hist_return": 0.535305, "annualized_vol": 1.180871, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181126_0187", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2018-11-26", "context_summary": "BNDX over past 60 days: cumulative return +0.1%, annualized vol 1.6%. Market regime: sideways.", "question": "Asset: BNDX\nHistorical prices (past 60 trading days): start=42.41, end=42.46, cumulative_return=+0.1%, annualized_volatility=1.6%\nMacro context: {'fed_funds_rate': 2.2, 'cpi_yoy': 252.594, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.24, 't10y3m_spread': 0.64, 'breakeven_10y': 1.96, 'hy_oas': 4.29, 'ig_oas': 1.38, 'ted_spread': 0.33, 'mortgage_30y': 4.81, 'vix': 21.520000457763672}\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": "positive", "answer_numeric": 0.010396, "explanation": "The actual 21-day forward return for BNDX starting 2018-11-26 was +1.04%, which classifies as 'positive'.", "metadata": {"future_return": 0.010396, "horizon_days": 21, "hist_return": 0.001177, "annualized_vol": 0.015612, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20170615_0190", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2017-06-15", "context_summary": "EWJ over past 60 days: cumulative return +6.0%, annualized vol 8.3%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=42.88, end=45.46, cumulative_return=+6.0%, annualized_volatility=8.3%\nMacro context: {'fed_funds_rate': 0.91, 'cpi_yoy': 244.163, 'unemployment': 4.3, 'gdp_growth_qoq': 19506.949, 't10y2y_spread': 0.8, 't10y3m_spread': 1.14, 'breakeven_10y': 1.71, 'hy_oas': 3.7, 'ig_oas': 1.18, 'ted_spread': 0.26, 'mortgage_30y': 3.89, 'vix': 10.640000343322754}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-06-14] [\"Apple, Tesla shares are two of the biggest shorts in the world right now Apple has $9 billion short interest, Tesla, $10 billion When it comes to the value of short interest in its stock, Apple (TICKER:AAPL) ranks third worldwide.\", \"Apple: Production Estimates Going Higher for iPhone, Says Credit Suisse Apple's production of iPhone is going higher in the second half of the year than previously expected, says Credit Suisse's Kulbinder Garcha, and a higher proportion of the most expensive version of the next iPhone may support higher average prices for the device later this year.\", \"Why investors ignore long-term alpha and get burned as a result Savita Subramanian: People don\\u2019t have patience, and that hurts retail and institutional returns over the long run The strategy that is most likely to earn investors excess return, or alpha, is also the one that is mostly overlooked, because investors have no patience, according to Savita Subramanian, equity and quant strategist at Bank of America Merrill Lynch\", \"Tesla: Not Competition. Serious Competition. Apple CEO Tim Cook said autonomous driving is a \\\"core technology.\\\" One analyst contends that means \\\"serious competition\\\" for Tesla.\", \"Apple V. Tesla: Probably, Apple Will Make a Car, Says Morgan Stanley Apple chief Tim Cook's remarks to Bloomberg yesterday that the company is working on \\\"autonomous systems\\\" suggest to Morgan Stanley's Katy Huberty that some day, Apple will make a full-blown car of its own.\", \"Here\\u2019s how to make easy money off the Fed interest-rate decision Wall Street will obsess, but look at Apple for proof of just how little it matters It\\u2019s difficult to see how the Fed\\u2019s decision has any real meaning for stock-market investors, says Mark Hulbert. Just look at Apple.\", \"A Turbocharged Trade On Tesla As analysts squabble over the car maker\\u2019s future, bold investors can swoop in and realize quick profits.\", \"'FAANG' stocks swing to losses after Fed raised interest rates Technology stocks turned sharply lower after the Federal Reserve raised interest rates, with most of the \\\"FAANG\\\" stocks swinging from gains to losses. Shares of Facebook Inc. dropped 0.7% in afternoon trade, after being up about 0.6% just before the Fed's announcement at 2 p.m. ET. Among other FAANG companies, shares of Apple Inc. extended losses to 1.2% after being down just 0.7% pre-Fed; Amazon.com Inc. swung to a loss of 0.7% from a pre-Fed gain of 0.2%; Netflix Inc. went from a gain of 0.1% pre-Fed to a current decline of 0.8%; Google parent Alphabet Inc. was down 0.5%, reversing a pre-Fed gain of 0.6%. The SPDR Technology Select Sector ETF extended losses to 0.7% from 0.1% pre-Fed. In comparison, the S&P 500 went from a pre-Fed loss of 0.1% to a current loss of 0.2%.\", \"Jabil Jumps 5% as CEO Sees Growth Across Business in 2018 Jabil Circuit, an important contract manufacturer for Apple, said it expects its best-ever August-ending quarter, after meeting May's financial expectations, \n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.000457, "explanation": "The actual 21-day forward return for EWJ starting 2017-06-15 was -0.05%, which classifies as 'flat'.", "metadata": {"future_return": -0.000457, "horizon_days": 21, "hist_return": 0.06007, "annualized_vol": 0.08287, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220110_0193", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2022-01-10", "context_summary": "MORT over past 60 days: cumulative return -3.7%, annualized vol 18.9%. Market regime: sideways.", "question": "Asset: MORT\nHistorical prices (past 60 trading days): start=11.34, end=10.92, cumulative_return=-3.7%, annualized_volatility=18.9%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 282.543, 'unemployment': 4.0, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.89, 't10y3m_spread': 1.66, 'breakeven_10y': 2.48, 'hy_oas': 3.2, 'ig_oas': 0.95, 'ted_spread': 0.14, 'mortgage_30y': 3.22, 'vix': 18.76000022888184}\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": -0.045654, "explanation": "The actual 21-day forward return for MORT starting 2022-01-10 was -4.57%, which classifies as 'negative'.", "metadata": {"future_return": -0.045654, "horizon_days": 21, "hist_return": -0.037132, "annualized_vol": 0.188784, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220117_0196", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2022-01-17", "context_summary": "IVV over past 60 days: cumulative return +2.8%, annualized vol 14.2%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=427.22, end=439.23, cumulative_return=+2.8%, annualized_volatility=14.2%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 282.543, 'unemployment': 4.0, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.79, 't10y3m_spread': 1.65, 'breakeven_10y': 2.44, 'hy_oas': 3.09, 'ig_oas': 0.97, 'ted_spread': 0.11, 'mortgage_30y': 3.45, 'vix': 19.190000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-14] [\"3 Downtrodden Stocks to Sell Before It Gets Worse InvestorPlace - Stock Market News, Stock Advice & Trading Tips Downtrends are multiplying across the land, and bears\\u2019 ranks are swelling. Despite the fact that the Nasdaq Composite still sitting a stone\\u2019s throw from its peak, some 40% of the index has been cut in half. There\\u2019s trouble beneath the surface, making for narrowing leadership and, ultimately, more vulnerability. I scanned my watchlist of the downtrodden and discovered three ugly stocks to sell before they get worse. And you don\\u2019t need to perform any mental gymnastics to grasp why lower prices are in the offing. The stocks below are stuck in nasty downtrends. And that matters greatly because trend direction is the most important of all technical signals. It sits atop the hierarchy of charting, demanding deference from all who employ technical analysis. In short, you\\u2019re far better off betting with the trend than against it. 7 Undervalued Stocks to Buy Before Wall Street Catches On That said, here are three struggling stocks that are poised for lower prices. PayPal (NASDAQ:PYPL) Snapchat (NYSE:SNAP) Adobe (NASDAQ:ADBE) Let\\u2019s review each chart in greater detail and map out a smart options trade you can use to bank on further weakness. Downtrodden Stocks to Sell: PayPal (PYPL) Source: The thinkorswim\\u00ae platform from TD Ameritrade Distance from Peak: -43% PayPal could still fall a great distance despite getting cut nearly in half. Going into the 2020 pandemic, PYPL was sitting at $125, another $50 lower from here. Over the past six weeks, the daily downtrend has slowed and formed a sideways trading range. But instead of powering to the top side and building a compelling bullish breakout, it\\u2019s knocking heavily on the lower-end. The $177 support shelf has held long enough to where its failure would prove a significant breakdown. If previous support breaks are any indication, we could see a swift move down to $160 if sellers press their bets. Given the higher volatility of the stock, I suggest using a spread trade over buying puts outright. The Trade: Buy the Feb $175/$160 put vertical for $4.75. You\\u2019re risking $4.75 to make $10.25 if PYPL stock falls to $160 by expiration. Snap (SNAP) Source: The thinkorswim\\u00ae platform from TD Ameritrade Distance from Peak: -56% Snap\\u2019s unraveling following last quarter\\u2019s earnings report has been deathly. For a single announcement to cause the stock to drop over 50% within a single quarter is horrific and speaks to just how much the Street hated the numbers. Prices are now submerged deep beneath all major moving averages. Once again, it\\u2019s tempting to argue SNAP stock is down so much that it can\\u2019t go lower. But like PayPal, it was way, way lower before the pandemic. Shareholders are hoping the quarterly report on Feb. 3 saves them. For now, I think the downtrend continues. Prices are down big over the past three days, so if you want to wait for\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": -0.021789, "explanation": "The actual 21-day forward return for IVV starting 2022-01-17 was -2.18%, which classifies as 'negative'.", "metadata": {"future_return": -0.021789, "horizon_days": 21, "hist_return": 0.028114, "annualized_vol": 0.141917, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210316_0201", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2021-03-16", "context_summary": "BNB-USD over past 60 days: cumulative return +522.4%, annualized vol 162.2%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=40.92, end=254.66, cumulative_return=+522.4%, annualized_volatility=162.2%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 264.961, 'unemployment': 6.1, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.48, 't10y3m_spread': 1.58, 'breakeven_10y': 2.27, 'hy_oas': 3.55, 'ig_oas': 1.02, 'ted_spread': 0.14, 'mortgage_30y': 3.05, 'vix': 20.030000686645508}\nMarket regime: sideways\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": 0.563695, "explanation": "The actual 21-day forward return for BNB-USD starting 2021-03-16 was +56.37%, which classifies as 'positive'.", "metadata": {"future_return": 0.563695, "horizon_days": 21, "hist_return": 5.223538, "annualized_vol": 1.621717, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191203_0203", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-12-03", "context_summary": "BTC-USD over past 60 days: cumulative return -10.8%, annualized vol 47.0%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=8205.94, end=7321.99, cumulative_return=-10.8%, annualized_volatility=47.0%\nMacro context: {'fed_funds_rate': 1.56, 'cpi_yoy': 258.63, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.22, 't10y3m_spread': 0.23, 'breakeven_10y': 1.65, 'hy_oas': 4.03, 'ig_oas': 1.11, 'ted_spread': 0.33, 'mortgage_30y': 3.68, 'vix': 14.90999984741211}\nMarket regime: sideways\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": 0.000326, "explanation": "The actual 21-day forward return for BTC-USD starting 2019-12-03 was +0.03%, which classifies as 'flat'.", "metadata": {"future_return": 0.000326, "horizon_days": 21, "hist_return": -0.107721, "annualized_vol": 0.46973, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201006_0208", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2020-10-06", "context_summary": "SHV over past 60 days: cumulative return -0.0%, annualized vol 0.1%. Market regime: sideways.", "question": "Asset: SHV\nHistorical prices (past 60 trading days): start=94.10, end=94.09, cumulative_return=-0.0%, annualized_volatility=0.1%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.64, 't10y3m_spread': 0.68, 'breakeven_10y': 1.68, 'hy_oas': 5.18, 'ig_oas': 1.4, 'ted_spread': 0.12, 'mortgage_30y': 2.88, 'vix': 27.959999084472656}\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": -2.7e-05, "explanation": "The actual 21-day forward return for SHV starting 2020-10-06 was -0.00%, which classifies as 'flat'.", "metadata": {"future_return": -2.7e-05, "horizon_days": 21, "hist_return": -6.3e-05, "annualized_vol": 0.000883, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191114_0211", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2019-11-14", "context_summary": "VEA over past 60 days: cumulative return +8.3%, annualized vol 9.9%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=32.55, end=35.24, cumulative_return=+8.3%, annualized_volatility=9.9%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 257.879, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.25, 't10y3m_spread': 0.31, 'breakeven_10y': 1.66, 'hy_oas': 4.05, 'ig_oas': 1.12, 'ted_spread': 0.37, 'mortgage_30y': 3.69, 'vix': 13.0}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-13] [\"The 2020 Hyundai Palisade: all-new 3-row SUV is comfortable and stylish A worthy successor to Hyundai\\u2019s Santa Fe The bigger, more powerful, more luxurious SUV has a comfy third row but only one powertrain.\", \"$700 Quintillion Is Way Too Much to Pay for an Asteroid NASA has plans to visit an asteroid worth in the neighborhood of $700 quintillion. Yet even if it was somehow hauled back to earth, it wouldn\\u2019t make everyone rich.\", \"Apple unveils new 16-inch MacBook Pro with Retina Display\", \"Apple's new MacBook Pro to start at $2,399\", \"Apple introduces new Mac Pro starting at $5,999 and Pro Display XDR starting at $4,999\", \"Apple Unveils New 16-inch MacBook Pro Laptop The 16-inch MacBook Pro laptop checks in with a starting price of $2,399, and, depending on options, goes up from there.\", \"Google Is Getting Into Banking. That\\u2019s Not as Crazy as It Sounds. The accounts will be offered through Citigroup and a Stanford University credit union, beginning in 2020.\", \"Disney+ Needs a Smash Hit. \\u2018The Mandalorian\\u2019 Star Wars Series Just Might Be It. Many fans have lamented the direction of the \\u2018Star Wars\\u2019 franchise, calling out the repetitive plots and cheesy dialogue. Thankfully, The Mandalorian, centered around a bounty hunter, is different.\", \"AMD stock touches highest price in 13 years, leads S&P 500 gains for year Advanced Micro Devices Inc. shares touched their highest price in more than a dozen years Wednesday and have more than doubled over the year. AMD shares were last up 2.4% at $37.58, after touching an intraday high of $37.96, their highest price since March 21, 2006, when shares priced at $38, according to FactSet data. Year to date, AMD shares are up nearly 104%, making them 2019's best performer so far on the S&P 500 index , which is up more than 23%. Second and third place go to chip-equipment makers Lam Research Corp. and KLA Corp. , respectively, shares of which have nearly doubled over the year. The PHLX Semiconductor Index is up 50% year-to-date. Shares of AMD rival Nvidia Corp. , which reports earnings on Thursday, are up nearly 57% for the year. AMD announced Wednesday that Apple Inc.'s new 16-inch MacBook Pro will feature the company's 7-nanometer Radeon Pro 5500M and 5300M mobile graphics processing units.\", \"Disney Stock Jumps After Big First Day for Disney+ The company said it has already secured 10 million subscribers for the new streaming service.\", \"These tech companies are staying flush despite concerns that Corporate America\\u2019s cash pile is set to dwindle this year Seven tech companies held 41% of the total cash among U.S. corporations in 2019 Even as cash stockpiles continue to dwindle at corporations, a select few tech firms have hoarded a chunk of these reserves\", \"Cisco Stock Gets a Thumbs-Up Ahead of Earnings Report RBC Capital launched coverage of Cisco Systems stock, saying it\\u2019s a buy just ahead of the company\\u2019s October quarter earnings report.\", \"Apple's stock surges 0.\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": 0.025665, "explanation": "The actual 21-day forward return for VEA starting 2019-11-14 was +2.57%, which classifies as 'positive'.", "metadata": {"future_return": 0.025665, "horizon_days": 21, "hist_return": 0.082915, "annualized_vol": 0.098623, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190826_0214", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2019-08-26", "context_summary": "IGOV over past 60 days: cumulative return +3.2%, annualized vol 6.2%. Market regime: sideways.", "question": "Asset: IGOV\nHistorical prices (past 60 trading days): start=48.46, end=50.01, cumulative_return=+3.2%, annualized_volatility=6.2%\nMacro context: {'fed_funds_rate': 2.12, 'cpi_yoy': 256.036, 'unemployment': 3.6, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.01, 't10y3m_spread': -0.45, 'breakeven_10y': 1.54, 'hy_oas': 4.25, 'ig_oas': 1.25, 'ted_spread': 0.21, 'mortgage_30y': 3.55, 'vix': 19.8700008392334}\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": "flat", "answer_numeric": -0.008395, "explanation": "The actual 21-day forward return for IGOV starting 2019-08-26 was -0.84%, which classifies as 'flat'.", "metadata": {"future_return": -0.008395, "horizon_days": 21, "hist_return": 0.032135, "annualized_vol": 0.0618, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20170104_0219", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2017-01-04", "context_summary": "ACWI over past 60 days: cumulative return +2.4%, annualized vol 9.1%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=49.14, end=50.33, cumulative_return=+2.4%, annualized_volatility=9.1%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 243.618, 'unemployment': 4.7, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.23, 't10y3m_spread': 1.92, 'breakeven_10y': 1.98, 'hy_oas': 4.13, 'ig_oas': 1.28, 'ted_spread': 0.47, 'mortgage_30y': 4.32, 'vix': 12.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-03] [\"Seven highly valued tech startups that could IPO in 2017 Unicorns like Snap and Spotify are expected to reach Wall Street in 2017, but what about Uber, Lyft, Airbnb, Dropbox and Palantir? After a dismal year for IPOs, investors expects to see more billion dollar startups test the public market or at least make moves in that direction.\", \"Go after these long-term stock plays in 2017 \\u2014 don\\u2019t chase what already happened Critical information for the U.S. trading day The new year has kicked off with what looks like a bright start for stocks, but investors should check their desire to chase the market at the door. Our call of the day offers these ideas for investing in some themes that will deliver.\", \"Intel seeks German digital-map venture stake BERLIN-- Intel Corp. is positioning itself to join BMW AG, Daimler AG and Volkswagen AG's Audi unit in developing navigation technology for self-driving cars. The U.S. tech bellwether filed a request for regulatory approval in Germany to make a strategic acquisition of a minority stake in the digital-mapping service Here International B.V., the Berlin-based company that Germany's big-three car makers bought from Nokia in 2015 for about EUR2.5 billion ($2.6 billion).\", \"CES 2017: Can Virtual Reality Finally Go Mainstream? For VR, 2016 was supposed to be the year when everything came together. But VR headsets remain bulky, expensive, and nausea inducing. What to expect in 2017.\", \"Virtual Reality Fertile Ground for Loup Ventures Despite Failures Thus Far A couple weeks ago I spoke by phone with former analyst , who left the firm after many years being a star analyst on (AAPL) to become a venture capitalist, along with colleagues and .Their firm, , will invest in four areas, , , , and , which they sees as among the most promising tech trends of the next several years. They want to combin investment with dissemination of research notes like they have done as sell-side analysts.More info is available on their Web site.I was interested to talk with the trio because my own experience with virtual reality, related in this space, is that it's at best immature as a consumer product, and at worst, it just plain sucks.\", \"As India Investment Slumps, Will GDP Follow? Announcements about new investments in India declined in the quarter ending December 30, continuing a stubborn quarterly trend.Add demonetization to the mix, and one has to ask if expectations for India's economy are too elevated. Read More>>\", \"Intel buys 15% stake in German digital-map co. Intel Corp. is acquiring a 15% stake in Here International B.V. for an undisclosed sum, joining the digital mapmaker's core shareholders BMW AG, Daimler AG and Volkswagen AG's Audi unit in developing navigation technology for self-driving cars.\", \"Apple\\u2019s Key Risk: Nokia Litigation The beginning of the year will likely be quiet in terms of legal outcomes, but the second half could bring volatility.\", \"Meet the world\\u2019s friendliest home robot Kuri, deve\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": 0.02012, "explanation": "The actual 21-day forward return for ACWI starting 2017-01-04 was +2.01%, which classifies as 'positive'.", "metadata": {"future_return": 0.02012, "horizon_days": 21, "hist_return": 0.024227, "annualized_vol": 0.09081, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20161010_0222", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2016-10-10", "context_summary": "BTC-USD over past 60 days: cumulative return +0.0%, annualized vol 15.8%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=3599.77, end=3599.77, cumulative_return=+0.0%, annualized_volatility=15.8%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 241.741, 'unemployment': 4.9, 'gdp_growth_qoq': 19304.352, 't10y2y_spread': 0.9, 't10y3m_spread': 1.4, 'breakeven_10y': 1.63, 'hy_oas': 4.76, 'ig_oas': 1.38, 'ted_spread': 0.56, 'mortgage_30y': 3.42, 'vix': 13.479999542236328}\nMarket regime: sideways\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": 0.0, "explanation": "The actual 21-day forward return for BTC-USD starting 2016-10-10 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.157982, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20150622_0227", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2015-06-22", "context_summary": "EEM over past 60 days: cumulative return +1.8%, annualized vol 14.6%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=30.81, end=31.37, cumulative_return=+1.8%, annualized_volatility=14.6%\nMacro context: {'fed_funds_rate': 0.13, 'cpi_yoy': 237.657, 'unemployment': 5.3, 'gdp_growth_qoq': 18782.243, 't10y2y_spread': 1.61, 't10y3m_spread': 2.25, 'breakeven_10y': 1.86, 'hy_oas': 4.73, 'ig_oas': 1.44, 'ted_spread': 0.27, 'mortgage_30y': 4.0, 'vix': 13.960000038146973}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-06-19] [\"Maxim Integrated, others named as potential Texas Instruments target\", \"Maxim Integrated, others named as potential Texas Instruments target\", \"Analog Devices Inc. Reportedly Wins a Design Inside the Next Apple Inc. iPhone According to Barron's , Citigroup analyst Chris Danely said chipmaker Analog Devices has \\\"likely won a slot in Apple 's next iPhone.\\\" This win could positively impact Analog Devices' revenue and profit in 2016, according to the report. Let's take a closer look at what Danely had to say. What's this design win worth? Danely said this win could be worth $160 million in revenue to Analog Devices in 2016, adding about 4% to the company's expected top line for the year. The analyst estimated the deal's operating margin at 23.5%, lower than the 32.4% company-wide operating profit margin he expects for the full year. To explain his relatively low margin expectation for the deal, Danely said margins from \\\"high volume consumer products and large customers such as Apple\\\" are generally lower than \\\"high-performance analog products for industrial applications.\\\" At any rate, the deal is still expected to be accretive to both revenue and earnings. Concordant with that view, Danely raised his 2016 earnings-per-share estimate for Analog by about 2.7%, from $2.98 to $3.06. A \\\"low-quality\\\" win? Danely noted that although the iPhone win should \\\"boost revenue and [earnings per share] in a meaningful and material way\\\" for Analog, that Citi has \\\"a lot of concern on the long-term quality\\\" of this new revenue. \\\"Apple is notorious for giving and taking away large design wins,\\\" Danely wrote in his research note. He added that Analog Devices has previously had \\\"large design wins\\\" with Apple that \\\"ended abruptly.\\\" Those design-outs eventually led to \\\"downside to Consensus estimates and the stock selling off,\\\" he noted. This isn't the first time we've heard of this win, though Analog Devices is up \\\"just\\\" 1.44% following the publication of this research note as of this writing. The Nasdaq index is up 1.35% and the iShares PHLX Semiconductor ETF is up 1.5%, meaning Analog Devices shares aren't outperforming the relevant indices due to this news. This is likely because the Apple win for future iPhones -- and possibly also iPads -- was already reported by analysts at Barclays (via MarketWatch) back in March. Analog Devices shares rallied by about 10% following that initial report. Additionally, at that time the Barclays analyst claimed that the wins at Apple for \\\"high accuracy\\\" analog-to-digital converters inside next-generation iPhones and iPads to enable Force Touch would add \\\"at least\\\" $0.80 to the company's 2016 earnings per share. It's not surprising, then, that a separate confirmation of news that is already \\\"known\\\" wouldn't move the stock much, if at all. Investment takeaway It seems as though Analog Devices has won a spot inside the next-generation iPhone. I'd argue that winning this spot is good, although the company will \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": -0.058746, "explanation": "The actual 21-day forward return for EEM starting 2015-06-22 was -5.87%, which classifies as 'negative'.", "metadata": {"future_return": -0.058746, "horizon_days": 21, "hist_return": 0.018044, "annualized_vol": 0.145845, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20150901_0230", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2015-09-01", "context_summary": "BNDX over past 60 days: cumulative return +0.3%, annualized vol 3.7%. Market regime: sideways.", "question": "Asset: BNDX\nHistorical prices (past 60 trading days): start=38.39, end=38.52, cumulative_return=+0.3%, annualized_volatility=3.7%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 238.033, 'unemployment': 5.1, 'gdp_growth_qoq': 18857.418, 't10y2y_spread': 1.47, 't10y3m_spread': 2.13, 'breakeven_10y': 1.63, 'hy_oas': 5.7, 'ig_oas': 1.69, 'ted_spread': 0.27, 'mortgage_30y': 3.84, 'vix': 28.43000030517578}\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": 0.005509, "explanation": "The actual 21-day forward return for BNDX starting 2015-09-01 was +0.55%, which classifies as 'flat'.", "metadata": {"future_return": 0.005509, "horizon_days": 21, "hist_return": 0.003284, "annualized_vol": 0.037053, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200819_0233", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-08-19", "context_summary": "LINK-USD over past 60 days: cumulative return +289.4%, annualized vol 102.4%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=4.17, end=16.24, cumulative_return=+289.4%, annualized_volatility=102.4%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 259.316, 'unemployment': 8.4, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.53, 't10y3m_spread': 0.58, 'breakeven_10y': 1.68, 'hy_oas': 5.26, 'ig_oas': 1.37, 'ted_spread': 0.16, 'mortgage_30y': 2.96, 'vix': 21.51000022888184}\nMarket regime: sideways\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": -0.237851, "explanation": "The actual 21-day forward return for LINK-USD starting 2020-08-19 was -23.79%, which classifies as 'negative'.", "metadata": {"future_return": -0.237851, "horizon_days": 21, "hist_return": 2.894095, "annualized_vol": 1.023739, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20211015_0236", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2021-10-15", "context_summary": "XLRE over past 60 days: cumulative return +1.3%, annualized vol 13.1%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=39.14, end=39.63, cumulative_return=+1.3%, annualized_volatility=13.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.16, 't10y3m_spread': 1.47, 'breakeven_10y': 2.52, 'hy_oas': 3.18, 'ig_oas': 0.9, 'ted_spread': 0.07, 'mortgage_30y': 3.05, 'vix': 16.860000610351562}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-14] [\"Apple extends repair program for crackling AirPods Pro buds for one more year Apple's repair program for AirPods Pro units with crackling sounds gets extended until October 2022.\", \"AI shopping assistant Karma raises $25 million in Series A funding led by Target Global AI shopping assistant and shopping network Karma announced that it has raised $25 million in Series A funding led by Target Global followed by MoreTech Ventures, with participation from existing investors including NFX and Altair Capital. Karma allows users to plan their next online purchases, get notified about real-time price and inventory updates, access coupons and earn automatic cashback. The Tel Aviv-based company was founded in 2014 by Jonathan Freidman and Ronen Yuval-Hoch as a simple bookmarklet tool to help consumers save and track products.\", \"The Morning After: Apple Watch Series 7, reviewed Today\\u2019s headlines: Apple may be exploring ways to use AirPods as health devices, Facebook\\u2019s latest effort to curtail leaks immediately leaked, William Shatner becomes the oldest person to reach space.\", \"Apple's rumored AirPods would be just its latest attempt to make you healthier Apple is reportedly moving deeper into the health care industry with a new pair of AirPods.\", \"What to expect from Apple\\u2019s October 18th \\u2018Unleashed\\u2019 event We take a look at everything we could potentially see Apple announce during its upcoming October 18th hardware event.\", \"What chip shortage? MagicCube raises $15M to 'replace all chips,' starting with POS terminals MagicCube, a mobile security startup, has raised $15 million in a round led by Mosaik Partners. Bold Capital, Epic Ventures, card-reader/POS hardware maker ID Tech and unnamed individual investors in the fintech space also participated in the financing, which brings the Santa Clara-based startup\\u2019s total funding raised to $30 million since its 2014 inception. Put simply, MagicCube\\u2019s software-based security technology is aimed at replacing all security chips, which have historically been the standard for safely storing sensitive data and authenticating whoever needs access to it.\", \"WhatsApp now lets users encrypt their chat backups in the cloud WhatsApp is beginning to roll out a new feature that will provide its two billion users the option to encrypt their chat history backup in iCloud or Google Drive, patching a major loophole that has been exploited by governments to obtain and review private communication between individuals. WhatsApp has long end-to-end encrypted chats between users on its app. It has been widely reported that law enforcement agencies across the globe have been able to access the private communications between suspect individuals on WhatsApp by exploiting this loophole.\", \"Senate bill would prevent tech companies from favoring their products over rivals Senators are introducing a bipartisan bill that would prevent Amazon, Apple and others from prioritizing their own products on their p\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": 0.048918, "explanation": "The actual 21-day forward return for XLRE starting 2021-10-15 was +4.89%, which classifies as 'positive'.", "metadata": {"future_return": 0.048918, "horizon_days": 21, "hist_return": 0.012619, "annualized_vol": 0.130958, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20211018_0239", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2021-10-18", "context_summary": "DBB over past 60 days: cumulative return +17.4%, annualized vol 18.2%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=17.44, end=20.48, cumulative_return=+17.4%, annualized_volatility=18.2%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.18, 't10y3m_spread': 1.54, 'breakeven_10y': 2.56, 'hy_oas': 3.12, 'ig_oas': 0.89, 'ted_spread': 0.07, 'mortgage_30y': 3.05, 'vix': 16.299999237060547}\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": "negative", "answer_numeric": -0.119017, "explanation": "The actual 21-day forward return for DBB starting 2021-10-18 was -11.90%, which classifies as 'negative'.", "metadata": {"future_return": -0.119017, "horizon_days": 21, "hist_return": 0.173785, "annualized_vol": 0.18156, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190104_0246", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2019-01-04", "context_summary": "XLY over past 60 days: cumulative return -12.9%, annualized vol 27.4%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=52.42, end=45.64, cumulative_return=-12.9%, annualized_volatility=27.4%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 252.561, 'unemployment': 4.0, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.17, 't10y3m_spread': 0.15, 'breakeven_10y': 1.68, 'hy_oas': 5.44, 'ig_oas': 1.63, 'ted_spread': 0.44, 'mortgage_30y': 4.51, 'vix': 25.450000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-03] [\"Apple cuts holiday sales forecast on iPhone and China weakness, stock falls 8% CEO Tim Cook cites weaker-than-expected iPhone sales, China economy in reducing revenue forecast Apple Inc. lowered its holiday-quarter revenue forecast Wednesday afternoon, largely due to slowing iPhone sales and pressure in China.\", \"Asian markets mostly down as Apple\\u2019s warning weighs on tech stocks Apple suppliers hit hard after tech giant cuts sales forecast Asian markets were mostly lower Thursday after tumbling more than 1% on the first trading day of 2019.\", \"Apple's stock tumbles 8.9% premarket after revenue warning late Monday\", \"Apple's stock on track to open at lowest level since July 2017\", \"Apple stock price target cut to $200 from $275 at Wedbush\", \"Apple stock price target cut to $187 from $222 at Piper Jaffray\", \"Dow Set to Tumble as Apple Wrecks Any Chance for a Rally After battling back into positive territory on Wednesday, it would have been nice to see the market gain even more on Thursday. Apple\\u2019s drop virtually guarantees that won\\u2019t happen.\", \"Copper falls as data signals China slowdown LONDON--Copper prices were under pressure Thursday, after a surprise cut to Apple's sales forecast in China pointed to slowing growth in the country just a day after a measure of Chinese manufacturing activity fell into contraction territory.\", \"Apple stock price target cut to $228 from $266 at J.P. Morgan\", \"Apple's stock plunge cuts about 90 points off Dow's price The plunge in Apple Inc.'s stock in Thursday's premarket, following the technology giant's revenue warning, is the biggest reason for the selloff in Dow Jones Industrial Average futures , but it's not the only reason. Apple shares shed 8.5% ahead of the open, putting them on track to open at the lowest level seen during regular-session hours since July 2017. The price decline would shave about 91 points off the Dow's price , while Dow futures 332 dropped points. All 27 of the Dow components trading in the premarket are losing ground.\", \"Apple stock price target cut to $200 from $300 at Monness Crespi Hardt\", \"Apple average analyst stock price target drops to $198.18 from $215.91 on Monday--FactSet\", \"Lumentum's stock tumbles 7.3% premarket in wake of Apple's revenue warning\", \"Apple downgraded to hold from buy at Jefferies\", \"Apple stock price target cut to $160 from $225 at Jefferies\", \"Apple Supplier Stocks Saw Problems Coming Even if the Market Didn\\u2019t Shares in Apple suppliers have been taking it on the chin since reports surfaced that the tech giant was slashing orders for iPhone components.\", \"Apple's average stock price target slashed to 9-month low Apple Inc.'s revenue warning has prompted a host of Wall Street analysts to slash their stock price targets, bringing the average target down to the lowest level since April 2018. The smartphone maker's stock tumbled 8.2% in premarket trade, putting it on track to open at the lowest level seen during regular-session hours since Ju\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": 0.070019, "explanation": "The actual 21-day forward return for XLY starting 2019-01-04 was +7.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.070019, "horizon_days": 21, "hist_return": -0.129276, "annualized_vol": 0.273958, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20221028_0250", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2022-10-28", "context_summary": "ADA-USD over past 60 days: cumulative return -13.8%, annualized vol 52.0%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.45, end=0.39, cumulative_return=-13.8%, annualized_volatility=52.0%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 298.007, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.34, 't10y3m_spread': -0.17, 'breakeven_10y': 2.45, 'hy_oas': 4.76, 'ig_oas': 1.68, 'ted_spread': 0.09, 'mortgage_30y': 7.08, 'vix': 27.38999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-27] \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": -0.193534, "explanation": "The actual 21-day forward return for ADA-USD starting 2022-10-28 was -19.35%, which classifies as 'negative'.", "metadata": {"future_return": -0.193534, "horizon_days": 21, "hist_return": -0.137576, "annualized_vol": 0.519875, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20191224_0255", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2019-12-24", "context_summary": "FXI over past 60 days: cumulative return +10.2%, annualized vol 14.8%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=34.07, end=37.54, cumulative_return=+10.2%, annualized_volatility=14.8%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 258.63, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.29, 't10y3m_spread': 0.34, 'breakeven_10y': 1.75, 'hy_oas': 3.52, 'ig_oas': 1.01, 'ted_spread': 0.39, 'mortgage_30y': 3.73, 'vix': 12.609999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-23] [\"Apple\\u2019s AirPods Will Be Hot in 2020, but Sales May Die Off Quickly Like They Did With iPads, Analyst Says Despite exuberance for next year, there\\u2019s some doubt that people who buy Apple\\u2019s iPhones second hand would be willing to fork over $150 for a set of AirPods to match, a Bernstein analyst says.\", \"Apple price target lifted to $350 from $325 at Wedbush, outperform stock rating maintained\", \"Apple iPhone demand will soar in 2020 with launch of 5G, say Wedbush analysts Demand for the Apple Inc. iPhone is poised to skyrocket thanks to new 5G devices, according to Wedbush analysts, who raised their price target to $350 from $325 and maintained their outperform stock rating in a Monday note. Apple faced a number of challenges at the start of 2019, including smartphone competition, diminished demand in China and a lack of 5G innovation. Now, China is in better shape, Apple has settled its lawsuit with Qualcomm and brought the iPhone 11 to market. \\\"We believe iPhone 11 is just the front end of this current 'supercycle' for Cupertino with a slate of 5G smartphones set to be unveiled in September that will open up the floodgates on iPhone upgrades across the board that the Street continues to underestimate,\\\" analysts wrote. Analysts say five versions of the iPhone will launch in 2020 and \\\"supplier checks indicate a double digit increase for expectations for overall units (10%+ year-over-year).\\\" Wedbush thinks 200 million units will be the \\\"starting point\\\" with 350 million iPhones within range for an upgrade. Apple stock us up 85.4% over the past year while the S&P 500 index has gained 33.3% and the Dow Jones Industrial Average is up 26.8% for the period.\", \"Buy Apple Stock Ahead of 5G iPhone \\u2018Supercycle,\\u2019 Says Wedbush Analyst Wedbush analyst Dan Ives repeated his Overweight rating on Apple stock, lifting his price target to a Street-high $350, from $325, ahead of what he expects will be spectacular growth for the iPhone starting late in 2020.\", \"\\u2018What kind of fancy a\\u2014 child\\u2019 plays with a Fisher-Price charcuterie set? Shoppers are split over whether this Mattel toy is too fancy for kids \\u2014 but it\\u2019s far from \\u2018bougie\\u2019-est option out there Shoppers are split on whether this Mattel toy is too fancy for kids \\u2014 but there\\u2019s even more bougie baby gifts out there.\", \"Dow jumps 87 points on gains in Boeing, 3M shares\", \"Popular chat app ToTok is spyware from UAE government: report Emirates said to use app to track users, spy on human rights activists A chat app that quickly became popular in the United Arab Emirates for communicating with friends and family is actually a spying tool used by the government to track its users, according to a newspaper report.\", \"Plenty of Fish app was leaking users' hidden names and postal codes Dating app Plenty of Fish has pushed out a fix for its app after a security researcher found it was leaking information that users had set to \\\"private\\\" on their p\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": -0.017857, "explanation": "The actual 21-day forward return for FXI starting 2019-12-24 was -1.79%, which classifies as 'negative'.", "metadata": {"future_return": -0.017857, "horizon_days": 21, "hist_return": 0.101788, "annualized_vol": 0.148406, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200729_0258", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2020-07-29", "context_summary": "VEA over past 60 days: cumulative return +17.2%, annualized vol 19.0%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=29.11, end=34.12, cumulative_return=+17.2%, annualized_volatility=19.0%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 258.352, 'unemployment': 10.2, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.45, 't10y3m_spread': 0.48, 'breakeven_10y': 1.51, 'hy_oas': 5.27, 'ig_oas': 1.4, 'ted_spread': 0.16, 'mortgage_30y': 3.01, 'vix': 25.440000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-07-28] [\"AMD forecasts current-quarter sales above estimates July 28 (Reuters) - Advanced Micro Devices Inc AMD.O on Tuesday forecast current-quarter revenue above Wall Street expectations, driven by a surge in chip demand from data-center operators and PC makers scrambling to meet coronavirus-induced remote work needs. The company expects third-quarter revenue to be about $2.55 billion, plus or minus $100 million, compared to analysts' average estimate of $2.32 billion, according to IBES data from Refinitiv. (Reporting by Munsif Vengattil in Bengaluru and Stephen Nellis in San Francisco; Editing by Sriraj Kalluvila and Maju Samuel) ((munsif.vengattil@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.\", \"After Hours Most Active for Jul 28, 2020 : KODK, AMD, INTC, AMC, BGFV, HBAN, QQQ, BAC, EBAY, AMCR, VICI, AEO The NASDAQ 100 After Hours Indicator is up 42.42 to 10,705.4. The total After hours volume is currently 103,219,306 shares traded. The following are the most active stocks for the after hours session: Eastman Kodak Company (KODK) is +5.27 at $13.21, with 21,152,582 shares traded., following a 52-week high recorded in today's regular session. Advanced Micro Devices, Inc. (AMD) is +6.99 at $74.60, with 15,821,275 shares traded., following a 52-week high recorded in today's regular session. Intel Corporation (INTC) is -0.27 at $48.97, with 6,100,316 shares traded. Over the last four weeks they have had 4 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2020. The consensus EPS forecast is $1.07. INTC's current last sale is 81.62% of the target price of $60. AMC Entertainment Holdings, Inc. (AMC) is -0.12 at $4.03, with 3,036,668 shares traded. AMC's current last sale is 100.75% of the target price of $4. Big 5 Sporting Goods Corporation (BGFV) is +1.81 at $6.28, with 2,509,705 shares traded. Reuters Reports: BUZZ-U.S. STOCKS ON THE MOVE-Anthem, General Dynamics, Superior Group Huntington Bancshares Incorporated (HBAN) is +0.06 at $9.19, with 2,373,403 shares traded. Over the last four weeks they have had 6 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2020. The consensus EPS forecast is $0.21. HBAN's current last sale is 91.9% of the target price of $10. Invesco QQQ Trust, Series 1 (QQQ) is +0.92 at $257.73, with 2,220,810 shares traded. This represents a 56.27% increase from its 52 Week Low. Bank of America Corporation (BAC) is +0.03 at $24.39, with 2,148,501 shares traded. Over the last four weeks they have had 6 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2020. The consensus EPS forecast is $0.41. BAC's current last sale is 90.33% of the target price of $27. eBay Inc. (EBAY) is -1.85 at $54.50, with 2,139,650 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2020. The consensus EPS fo\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": 0.017497, "explanation": "The actual 21-day forward return for VEA starting 2020-07-29 was +1.75%, which classifies as 'positive'.", "metadata": {"future_return": 0.017497, "horizon_days": 21, "hist_return": 0.172035, "annualized_vol": 0.19007, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210705_0261", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-07-05", "context_summary": "DOT-USD over past 60 days: cumulative return -61.4%, annualized vol 151.4%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=41.53, end=16.01, cumulative_return=-61.4%, annualized_volatility=151.4%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 271.903, 'unemployment': 5.4, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.2, 't10y3m_spread': 1.39, 'breakeven_10y': 2.33, 'hy_oas': 3.04, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 2.98, 'vix': 15.06999969482422}\nMarket regime: sideways\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": -0.084268, "explanation": "The actual 21-day forward return for DOT-USD starting 2021-07-05 was -8.43%, which classifies as 'negative'.", "metadata": {"future_return": -0.084268, "horizon_days": 21, "hist_return": -0.614431, "annualized_vol": 1.514449, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20171201_0265", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2017-12-01", "context_summary": "ICSH over past 60 days: cumulative return +0.1%, annualized vol 0.4%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=39.38, end=39.44, cumulative_return=+0.1%, annualized_volatility=0.4%\nMacro context: {'fed_funds_rate': 1.07, 'cpi_yoy': 247.284, 'unemployment': 4.2, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.64, 't10y3m_spread': 1.15, 'breakeven_10y': 1.86, 'hy_oas': 3.61, 'ig_oas': 1.03, 'ted_spread': 0.24, 'mortgage_30y': 3.9, 'vix': 11.279999732971191}\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": 0.00082, "explanation": "The actual 21-day forward return for ICSH starting 2017-12-01 was +0.08%, which classifies as 'flat'.", "metadata": {"future_return": 0.00082, "horizon_days": 21, "hist_return": 0.001499, "annualized_vol": 0.004372, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180620_0270", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2018-06-20", "context_summary": "EEM over past 60 days: cumulative return -8.7%, annualized vol 17.7%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=40.32, end=36.80, cumulative_return=-8.7%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 1.91, 'cpi_yoy': 251.018, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.35, 't10y3m_spread': 0.95, 'breakeven_10y': 2.12, 'hy_oas': 3.4, 'ig_oas': 1.24, 'ted_spread': 0.42, 'mortgage_30y': 4.62, 'vix': 13.350000381469728}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-06-19] [\"Beyonc\\u00e9 and Jay-Z\\u2019s new album goes to multiple streaming platforms, and is already a hit \\u2018Everything Is Love\\u2019 album available more places than just Tidal Beyonc\\u00e9 and Jay-Z have made their new album available for streaming across all major music services \\u2014 as long as listeners are paying for it.\", \"Trump reportedly told Apple that tariffs against China would spare iPhones Tech giant worries China will retaliate as trade tensions heat up Apple Inc. iPhones assembled in China will not be subject to U.S. tariffs, according to a report Monday, but the tech giant may get punished by a possible trade war.\", \"Chinese stocks end at 2-year low, Apple suppliers sink on trade-war worries iPhone component-makers\\u2019 shares hit hard in Hong Kong, Taiwan Asian exporters took a heavy hit Tuesday, with China stocks suffering their lowest close in two years, following President Donald Trump\\u2019s announcement of potentially $400 billion in additional tariffs against imports from that country.\", \"Beware the \\u2018perpetual-motion machine\\u2019 driving this market, warns billionaire Howard Marks Critical information for the U.S. trading day President Trump and China just keep ramping up their trade battle, sending stocks worldwide into the woodchipper. But it\\u2019s billionaire investor Howard Marks\\u2019s memo on another hot topic that provides our call of the day.\", \"Apple fined as Australian customers win right-to-repair court fight Apple Inc. was fined in Australia for refusing to offer free fixes for iPhones and iPads that were previously serviced by non-Apple stores, the latest episode in a global dispute between companies and consumers about the right to repair.\", \"Trump\\u2019s latest trade-war threat wreaks havoc for markets \\u2014 here\\u2019s how, in five charts iPhone suppliers, copper, yen China-related markets were taking some heat on Tuesday as a fresh chapter in the trade war with the U.S. threatened to blow up. Here are five charts showing how dramatic a day it has been for global markets.\", \"Universal Display stock slides for sixth straight day, on track to close at 52-week low Shares of Universal Display Corp. are down 3.4% in Tuesday morning trading, marking the sixth straight day that the stock is down and the ninth day out of the last 10 trading sessions. UDC's stock recently changed hands at $87. and is on pace to close at a 52-week low. Shares closed at $87.55 on April 25. The stock has been hammered in recent days amid concerns about Apple Inc.'s plans for its next iPhone lineup. The Wall Street Journal reported last week that Apple expects more than half of iPhones sold this fall to have liquid-crystal-display screens rather than organic-light-emitting-diode screens. Universal Display makes OLED technology. The stock is off 27% over the past 12 months, while the S&P 500 has gained 12%.\", \"China can\\u2019t match Trump in a tariff fight, but it does have other weapons Widening trade dispute is already hurting \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": -0.002949, "explanation": "The actual 21-day forward return for EEM starting 2018-06-20 was -0.29%, which classifies as 'flat'.", "metadata": {"future_return": -0.002949, "horizon_days": 21, "hist_return": -0.087238, "annualized_vol": 0.176584, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160108_0273", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2016-01-08", "context_summary": "USMV over past 60 days: cumulative return -0.3%, annualized vol 12.9%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=33.82, end=33.71, cumulative_return=-0.3%, annualized_volatility=12.9%\nMacro context: {'fed_funds_rate': 0.36, 'cpi_yoy': 237.652, 'unemployment': 4.8, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.2, 't10y3m_spread': 1.96, 'breakeven_10y': 1.5, 'hy_oas': 7.24, 'ig_oas': 1.75, 'ted_spread': 0.42, 'mortgage_30y': 3.97, 'vix': 24.989999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-07] [\"Sony Dips On Apple Weakness, Credit Suisse Warns Asia Tech Profit Tumble Sony Corp. (6758.Japan/SNE) tumbles 5% in Tokyo this morning after customer Apple (AAPL) at one point fell through $100 per share, ending down 2% to $100.70 on Wednesday. The market is worried that Apple will dramatically cut its iPhone production in the March quarter.Separately, Nitto Denko (6988.Japan), rumored to supply OLED screens for future generation iPhones, dipped 4.8% as well.READ MORE.\", \"With smartphone sales booming, Huawei eyes U.S. market Fast-growing Chinese manufacturer introduces new phone at CES Huawei Technologies Co. boasted of dramatic gains in the global smartphone market as it launched a new flagship handset that signals its ambitions in the lucrative U.S. market.\", \"Apple Casing Supplier Catcher Tech Sees No Sales Growth In First-Half So Apple (AAPL) is cutting its production orders in the March quarter for real?After releasing disappointing December sales numbers yesterday, Apple metal casing supplier Catcher Technology (2474.Taiwan) told analysts that it expected 2016 first-half sales to be flattish year-on-year and we should not see growth till the second-half. Catcher also said capital expenditure this year would be lower than the previous two.READ MORE.\", \"5 black swans that could rock markets in 2016 What if Apple failed the next iPhone launch, or peace broke out in Syria? Matthew Lynn lists five potential black swans -- inherently unpredictable events -- that could rock financial markets in 2016.\", \"Apple stock price tumbles 3% premarket, now trades well below $100\", \"Market bears roar as $2.5 trillion gets wiped out Critical information before the U.S. market\\u2019s open Our chart of the day shows why analysts expect a lot of pain for the S&P 500 in the near term. Our suggests the Shanghai index could plunge below the low it hit during last summer\\u2019s swoon.\", \"Apple: RBC Slashes iPhone Numbers; \\u2018Higher Than Optimal Inventory\\u2019 Apple (AAPL) this morning gets yet another in a string of estimate cuts following speculation this week that the company cut its iPhone production for the March quarter, this note being from RBC Capital Markets\\u2019s Amit Daryanani, who cut his estimate for March to 45 million units from what he had thought would be 54 million, citing \\\"incremental softness and recent production cuts.\\\"Writes Daryanani, who has an Outperform rating on the stock, but who cuts his price target from $140 to $130, Apple is sitting on \\\"higher than optimal inventory across multiple geographies\\u201d:Our discussions with a host of supply chain companies and recent results from Catcher lead us to think Mar- EPS, Ops Diluted 2014A qtr iPhone units could come in well below current buyside and Street Prev. expectations (50\\u201358M).Read further...\", \"Apple just bought a startup that reads people\\u2019s emotions Emotient technology is used to assess emotions by reading facial expressions Apple Inc. has purchased Emotient Inc., a s\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": -0.003728, "explanation": "The actual 21-day forward return for USMV starting 2016-01-08 was -0.37%, which classifies as 'flat'.", "metadata": {"future_return": -0.003728, "horizon_days": 21, "hist_return": -0.003073, "annualized_vol": 0.129242, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190314_0276", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2019-03-14", "context_summary": "XLI over past 60 days: cumulative return +12.4%, annualized vol 19.7%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=59.11, end=66.47, cumulative_return=+12.4%, annualized_volatility=19.7%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 254.277, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.16, 't10y3m_spread': 0.16, 'breakeven_10y': 1.92, 'hy_oas': 3.99, 'ig_oas': 1.28, 'ted_spread': 0.21, 'mortgage_30y': 4.41, 'vix': 13.40999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-03-13] [\"How your internet surfing could make you money in the coming blockchain revolution Decentralized internet will give people online privacy and data ownership A decentralized internet will give people online privacy and data ownership, writes Michael Edesess.\", \"Spotify shares aren't trading in the premarket\", \"Apple's stock adds 0.3% before the opening bell\", \"Spotify files antitrust complaint against Apple in European Union: reports\", \"Spotify files EU antitrust complaint over Apple\\u2019s App store Complaint alleges Apple abused its control over which apps appear in its App Store Music-streaming service Spotify Technology SA has filed an antitrust complaint in Europe against Apple Inc., a new salvo in the broader battle over how and whether to rein in alleged wrongdoing by tech giants.\", \"Spotify Is Hitting Apple With an Antitrust Complaint Over the \\u2018Unfair Advantage\\u2019 of the App Store Spotify CEO Daniel Elk said the App Store gives Apple\\u2019s own applications and services \\u201can unfair advantage at every turn.\\u201d\", \"Apple\\u2019s China Problems May Be Getting Even Worse Analysts expect Apple to report earnings of $2.38 per share on revenue of $57.54 billion, indicating declines of 13% and 5.9%, respectively, from the year-ago period.\", \"Charting a headline breakout attempt, S&P 500 challenges major resistance (2,817) Focus: Apple confirms its uptrend, Real estate sector tags 11-year highs, Utilities finally knife to record territory, AAPL, IYR, XLU, PANW, DDS, NRG U.S. stocks are firmly higher early Wednesday, rising amid distinctly bullish price action ahead of a key Brexit vote. Against this backdrop, the S&P 500 and Nasdaq Composite are challenging their five-month range top \\u2014 S&P 2,817 and Nasdaq 7,670 \\u2014 areas defining the immediate bull-bear tension. An eventual breakout opens the path to less-charted territory, and potentially material follow-through.\", \"Should stock-market investors watch out for a volatility pickup? \\u2018The cost of being wrong using options has seldom been lower,\\u2019 says BTIG\\u2019s Emanuel A 2019 stock-market rally comes alongside a fall in volatility. One analyst says investors can\\u2019t go wrong buying protection against a potential pickup.\", \"Podcast: Microsoft\\u2019s Surprising Comeback This week on The Readback, Alex Eule is joined by associate editor Jack Hough to talk about the surprising comeback of Microsoft.\", \"Apple, Amazon, Google, Facebook cast in Europe as harmful monopolies Spotify claims antitrust against Apple as U.K. report recommends new rules, oversight of big tech firms Facebook, Google, Amazon and Apple are once again being cast as monopolies that have become too powerful for society\\u2019s good, a recurring theme that\\u2019s increasing the pressure to rein them in.\", \"Apple Courts HBO and Showtime for Service to Challenge Netflix The company will host A-list celebrities and media executives on March 25 to outline how it will take on competitors like Amazon.com Inc\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": 0.04078, "explanation": "The actual 21-day forward return for XLI starting 2019-03-14 was +4.08%, which classifies as 'positive'.", "metadata": {"future_return": 0.04078, "horizon_days": 21, "hist_return": 0.124428, "annualized_vol": 0.197463, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190117_0281", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-01-17", "context_summary": "ETH-USD over past 60 days: cumulative return -30.2%, annualized vol 108.9%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=177.07, end=123.55, cumulative_return=-30.2%, annualized_volatility=108.9%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 252.561, 'unemployment': 4.0, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.18, 't10y3m_spread': 0.3, 'breakeven_10y': 1.82, 'hy_oas': 4.44, 'ig_oas': 1.52, 'ted_spread': 0.4, 'mortgage_30y': 4.45, 'vix': 19.040000915527344}\nMarket regime: sideways\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": -0.013813, "explanation": "The actual 21-day forward return for ETH-USD starting 2019-01-17 was -1.38%, which classifies as 'negative'.", "metadata": {"future_return": -0.013813, "horizon_days": 21, "hist_return": -0.302258, "annualized_vol": 1.088547, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160505_0284", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2016-05-05", "context_summary": "SHV over past 60 days: cumulative return +0.1%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SHV\nHistorical prices (past 60 trading days): start=88.76, end=88.86, cumulative_return=+0.1%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 239.557, 'unemployment': 4.8, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 1.04, 't10y3m_spread': 1.6, 'breakeven_10y': 1.63, 'hy_oas': 6.39, 'ig_oas': 1.54, 'ted_spread': 0.44, 'mortgage_30y': 3.66, 'vix': 16.049999237060547}\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": -0.000172, "explanation": "The actual 21-day forward return for SHV starting 2016-05-05 was -0.02%, which classifies as 'flat'.", "metadata": {"future_return": -0.000172, "horizon_days": 21, "hist_return": 0.001106, "annualized_vol": 0.002059, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20221214_0291", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2022-12-14", "context_summary": "HYG over past 60 days: cumulative return +4.9%, annualized vol 12.5%. Market regime: sideways.", "question": "Asset: HYG\nHistorical prices (past 60 trading days): start=59.56, end=62.48, cumulative_return=+4.9%, annualized_volatility=12.5%\nMacro context: {'fed_funds_rate': 3.83, 'cpi_yoy': 298.832, 'unemployment': 3.5, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.71, 't10y3m_spread': -0.84, 'breakeven_10y': 2.24, 'hy_oas': 4.34, 'ig_oas': 1.36, 'ted_spread': 0.09, 'mortgage_30y': 6.33, 'vix': 22.549999237060547}\nMarket regime: sideways\n\nPredict whether the return of HYG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.018011, "explanation": "The actual 21-day forward return for HYG starting 2022-12-14 was +1.80%, which classifies as 'positive'.", "metadata": {"future_return": 0.018011, "horizon_days": 21, "hist_return": 0.049032, "annualized_vol": 0.124601, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20150511_0298", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2015-05-11", "context_summary": "XLP over past 60 days: cumulative return -0.5%, annualized vol 10.5%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=36.89, end=36.70, cumulative_return=-0.5%, annualized_volatility=10.5%\nMacro context: {'fed_funds_rate': 0.13, 'cpi_yoy': 237.001, 'unemployment': 5.6, 'gdp_growth_qoq': 18782.243, 't10y2y_spread': 1.57, 't10y3m_spread': 2.15, 'breakeven_10y': 1.88, 'hy_oas': 4.53, 'ig_oas': 1.34, 'ted_spread': 0.27, 'mortgage_30y': 3.8, 'vix': 12.859999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-05-08] Dow 30 Stock Roundup: Disney, Visa Beat, Chevron Reports Mixed Results - Analyst Blog The Dow went through another volatile week, losing for two consecutive days, while it moved up during other sessions. Stocks ended in the green for the second straight session on Monday boosted by a handful of upbeat earnings results. The Dow declined on Tuesday, dragged down by losses in technology, biotechnology and small-cap stocks. Markets ended in the red for the second consecutive day on Wednesday following Fed Chair Janet Yellen's comments that stock valuations are \"quite high.\" The Dow rebounded on Thursday following easing in bond yields and gains in technology stocks. The Dow has lost 0.5% during the first four trading days. LastWeek's Performance Last Friday, the Dow gained more than 1% as investors added beaten down stocks to their portfolios. Stocks from the health and technology sectors found favor. Apple Inc. AAPL boosted the tech sector and also the broader markets after gaining almost 3.1%. It was the biggest daily percentage gain since Jan this year. Investors also cheered positive US auto sales numbers. According to Autodata, April auto sales were at an annual rate of 16.45 million, better than 16.05 million in the year-ago period. ISM's April PMI was flat month on month at 51.5%. March's construction spending dropped 0.6% from February. However, April consumer sentiment rose to the second best level since 2007. Friday's robust gains could limit weekly losses. The Dow declined 0.3% over the week. Benchmarks ended in the red on Monday, Wednesday and Thursday, and were mixed on Tuesday. Each of the benchmarks had lost over 1% on Thursday, dragged by losses in technology and biotechnology stocks. The major disappointment last week was the weaker-than-expected GDP data. According to the \"advance\" estimate, first quarter GDP increased at an annual rate of 0.2%, less than the consensus estimate of an increase by 1%. On the other hand, Fed officials gave no clear guidance on the timing of interest rate hike, which did little to boost investor sentiment. Among other data, investors received discouraging report on consumer confidence. However, personal income improved marginally in April. Some major companies reported encouraging earnings numbers. The DowThisWeek Stocks ended in the green for the second straight session on Monday boosted by a handful of upbeat earnings results. New orders for manufactured goods increased 2.1% in March, its biggest rise in eight months. Meanwhile, president of the Federal Reserve Bank of Chicago, Charles Evans, said hiking federal funds rate won't be appropriate until next year due to weak first quarter economic reports. This increase in factory orders for March was in line with the consensus estimate. However, the underlying trend remains weak as the increase in new orders for manufactured goods was due to a 13.5% jump in transportation orders. Positive news emanating from Europe also added to the bullish sentiment. Th\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": -0.014294, "explanation": "The actual 21-day forward return for XLP starting 2015-05-11 was -1.43%, which classifies as 'negative'.", "metadata": {"future_return": -0.014294, "horizon_days": 21, "hist_return": -0.005206, "annualized_vol": 0.104955, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20170301_0301", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2017-03-01", "context_summary": "SCHP over past 60 days: cumulative return +1.1%, annualized vol 4.1%. Market regime: sideways.", "question": "Asset: SCHP\nHistorical prices (past 60 trading days): start=20.59, end=20.81, cumulative_return=+1.1%, annualized_volatility=4.1%\nMacro context: {'fed_funds_rate': 0.57, 'cpi_yoy': 244.006, 'unemployment': 4.6, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.14, 't10y3m_spread': 1.83, 'breakeven_10y': 2.02, 'hy_oas': 3.74, 'ig_oas': 1.21, 'ted_spread': 0.53, 'mortgage_30y': 4.16, 'vix': 12.920000076293944}\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": 0.003078, "explanation": "The actual 21-day forward return for SCHP starting 2017-03-01 was +0.31%, which classifies as 'flat'.", "metadata": {"future_return": 0.003078, "horizon_days": 21, "hist_return": 0.010947, "annualized_vol": 0.041481, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200217_0304", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2020-02-17", "context_summary": "VTI over past 60 days: cumulative return +8.8%, annualized vol 9.6%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=144.07, end=156.72, cumulative_return=+8.8%, annualized_volatility=9.6%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 259.25, 'unemployment': 3.5, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.17, 't10y3m_spread': 0.01, 'breakeven_10y': 1.66, 'hy_oas': 3.56, 'ig_oas': 1.02, 'ted_spread': 0.14, 'mortgage_30y': 3.47, 'vix': 13.68000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-02-14] [\"Applied Materials (AMAT): Strong Industry, Solid Earnings Estimate Revisions\", \"Tiger Management Buys Amazon.com Inc, NXP Semiconductors NV, CommScope Holding Co Inc, Sells ...\", \"Company News for Feb 14, 2020\", \"Top Research Reports for VMware, Applied Materials & Equinix\", \"Thames Capital Management Llc Buys Citigroup Inc, Applied Materials Inc, NVIDIA Corp, Sells ...\", \"Composite Rating For Applied Materials Jumps To 98\", \"Top Research Reports for VMware, Applied Materials & Equinix\", \"Thames Capital Management Llc Buys Citigroup Inc, Applied Materials Inc, NVIDIA Corp, Sells ...\", \"Composite Rating For Applied Materials Jumps To 98\", \"Company News for Feb 14, 2020\", \"Tiger Management Buys Amazon.com Inc, NXP Semiconductors NV, CommScope Holding Co Inc, Sells ...\", \"Applied Materials (AMAT): Strong Industry, Solid Earnings Estimate Revisions\", \"Ex-Dividend Reminder: Consolidated Edison, AFLAC and Applied Materials Looking at the universe of stocks we cover at Dividend Channel, on 2/18/20, Consolidated Edison Inc (Symbol: ED), AFLAC Inc (Symbol: AFL), and Applied Materials, Inc. (Symbol: AMAT) will all trade ex-dividend for their respective upcoming dividends. Consolidated Edison Inc will pay its quarterly dividend of $0.765 on 3/16/20, AFLAC Inc will pay its quarterly dividend of $0.28 on 3/2/20, and Applied Materials, Inc. will pay its quarterly dividend of $0.21 on 3/11/20. As a percentage of ED's recent stock price of $93.85, this dividend works out to approximately 0.82%, so look for shares of Consolidated Edison Inc to trade 0.82% lower \\u2014 all else being equal \\u2014 when ED shares open for trading on 2/18/20. Similarly, investors should look for AFL to open 0.53% lower in price and for AMAT to open 0.31% lower, all else being equal. Below are dividend history charts for ED, AFL, and AMAT, showing historical dividends prior to the most recent ones declared. Consolidated Edison Inc (Symbol: ED): AFLAC Inc (Symbol: AFL): Applied Materials, Inc. (Symbol: AMAT): In general, dividends are not always predictable, following the ups and downs of company profits over time. Therefore, a good first due diligence step in forming an expectation of annual yield going forward, is looking at the history above, for a sense of stability over time. This can help in judging whether the most recent dividends from these companies are likely to continue. If they do continue, the current estimated yields on annualized basis would be 3.26% for Consolidated Edison Inc, 2.13% for AFLAC Inc, and 1.25% for Applied Materials, Inc.. In Friday trading, Consolidated Edison Inc shares are currently up about 0.2%, AFLAC Inc shares are up about 0.1%, and Applied Materials, Inc. shares are up about 0.1% on the day. Click here to learn which 25 S.A.F.E. dividend stocks should be on your radar screen \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Top Research Reports for VMwa\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.304086, "explanation": "The actual 21-day forward return for VTI starting 2020-02-17 was -30.41%, which classifies as 'negative'.", "metadata": {"future_return": -0.304086, "horizon_days": 21, "hist_return": 0.08785, "annualized_vol": 0.095929, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20201013_0309", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-10-13", "context_summary": "MATIC-USD over past 60 days: cumulative return -36.4%, annualized vol 86.5%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.03, end=0.02, cumulative_return=-36.4%, annualized_volatility=86.5%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.63, 't10y3m_spread': 0.69, 'breakeven_10y': 1.73, 'hy_oas': 4.92, 'ig_oas': 1.34, 'ted_spread': 0.12, 'mortgage_30y': 2.87, 'vix': 25.06999969482422}\nMarket regime: sideways\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": -0.281444, "explanation": "The actual 21-day forward return for MATIC-USD starting 2020-10-13 was -28.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.281444, "horizon_days": 21, "hist_return": -0.363808, "annualized_vol": 0.864881, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210309_0312", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2021-03-09", "context_summary": "USMV over past 60 days: cumulative return +0.3%, annualized vol 12.4%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=61.20, end=61.38, cumulative_return=+0.3%, annualized_volatility=12.4%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 264.961, 'unemployment': 6.1, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.42, 't10y3m_spread': 1.54, 'breakeven_10y': 2.21, 'hy_oas': 3.57, 'ig_oas': 1.02, 'ted_spread': 0.13, 'mortgage_30y': 3.02, 'vix': 25.46999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-03-08] [\"Here Are 4 Tech Plays That Offer Solid Yield and Dividend Growth The tech sector typically requires a trade-off for equity income investors: low yields in exchange for growing dividends. Here are some that give investors the best of both.\", \"Volkswagen and ViacomCBS Are Reinventing Themselves Why their pivots, toward electric vehicles and streaming, respectively, are good for their stocks.\", \"10 new cars you can get for less than $300 a month There are plenty of affordable cars that offer modern features, comfortable interiors, lots of safety features, and unexpected technology.\", \"Investors may have a \\u2018buy\\u2019 signal, as these big tech stocks have dropped up to 32% in only three weeks Now might be \\\"a golden opportunity\\\" to own the \\\"secular tech winners\\\" for the next 12 to 18 months, according to Wedbush analyst Daniel Ives.\", \"Apple stock falls 2.4% to pace the Dow's decliners\", \"Apple's stock in danger of lowest close since Nov. 27\", \"Apple Will Lead in AR, Analyst Says. Watch for Its Contact Lenses. TFI Asset Management's Ming-Chi Kuo says Apple's history in defining how computers and people interact gives it an advantage for the shift toward augmented reality.\", \"Tech stocks are under pressure. Don\\u2019t buy the dip, sell the bounces, strategist says Technology stocks are under pressure at the start of the week, as bond yields continue to rise.\", \"\\u2018Would you consider working for me?\\u2019 Clubhouse, the invite-only social network, is a hotbed for job interviews 'One of the massive benefits of Clubhouse is you can actually hear the real person --- not a CV,' said one recruiter.\", \"Apple stock falls toward 3-month low with bear market now in sight, even as Dow rallies Shares of Apple Inc. sank 3.4% in afternoon trading Monday, putting them on track for the lowest close in more than three months, as large-capitalization technology stocks continue to pull back despite the rally in the broader stock market. Apple was leading just the five of 30 Dow Jones Industrial Average components losing ground Monday, as the Dow soared 488 points, or 1.6%. Apple's stock, which is headed for the lowest close since Nov. 27, has now lost 18.1% since the Jan. 26 record close of $143.16. A close below $114.53 would put the stock in a bear market, which many define as a decline of 20% or more from a significant high. Separately, the 200-day moving average, which many chart watchers use as a dividing line between longer-term uptrends and downtrends, currently extends to $114.10; the last close below the 200-day was April 3, 2020. Apple's stock has shed 5.7% over the past three months, while the technology-heavy Nasdaq 100 has given up 1.7% and the Dow has rallied 6.0%.\", \"Roblox is going public: 5 things to know about the tween-centric gaming platform Investors waiting on the long-awaited public debut of Roblox Corp. finally have a date for when the tween-centric gaming platform will roll out its direct listing.\", \"Apple Inc. stock underperforms Mo\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": 0.052721, "explanation": "The actual 21-day forward return for USMV starting 2021-03-09 was +5.27%, which classifies as 'positive'.", "metadata": {"future_return": 0.052721, "horizon_days": 21, "hist_return": 0.00289, "annualized_vol": 0.123951, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190211_0315", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2019-02-11", "context_summary": "XLP over past 60 days: cumulative return -4.0%, annualized vol 15.7%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=46.23, end=44.40, cumulative_return=-4.0%, annualized_volatility=15.7%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 253.319, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.18, 't10y3m_spread': 0.2, 'breakeven_10y': 1.82, 'hy_oas': 4.32, 'ig_oas': 1.34, 'ted_spread': 0.32, 'mortgage_30y': 4.41, 'vix': 15.720000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-08] [\"If you own Apple, Amazon, Facebook or AMD, look out below Those shares have been bid up by the average investor, but buying could slow or even reverse Those shares have been bid up by the average investor, but buying could slow or even reverse.\", \"Hasbro Falls, Trade Worries Worsen, and Dow Is in Line for Another Loss U.S. stock markets were poised to open lower for a third consecutive day.\", \"The stock market dip? Keep buying, says Bank of America Merrill Lynch Critical information for the U.S. trading day Stocks are on track to end the week on a sour note. If you\\u2019re a fan of the \\u2018buy-the-dip\\u2019 strategy, our call of the day from Bank of America Merrill Lynch, along with our chart of a stoic S&P says now is not the time to give up.\", \"Cody Willard: I\\u2019m most bullish on Apple, Alphabet and Verizon Also reviewed today: Amazon, Intel, Palo Alto Networks, Facebook and Nvidia Also reviewed today: Amazon, Intel, Palo Alto Networks, Facebook and Nvidia.\", \"Amazon Investors Are Worried About Bezos Blackmail Case Shares of the e-commerce giant are down nearly 3% on Friday, in the wake of CEO Jeff Bezos\\u2019 startling revelations.\", \"GoPro predicts profit, thanks to years of massive layoffs Company expects to flip to profit in 2019 despite single-digit revenue growth, after chopping expenses with layoffs in 2017 and 2018 GoPro Inc. executives have been sounding bullish in the last two months, and Wednesday\\u2019s fourth quarter conference call was no exception, with a forecast for profitability in 2019 for the action camera maker, but its results were helped by past cost cutting and company layoffs.\", \"3 Stocks Bucking the Earnings Slowdown Most companies these days seem to beat earnings estimates. This is a screen for stocks whose earnings estimates have been rising in the first quarter. Boeing and two more favorites.\", \"AT&T\\u2019s 5G Act Is Bad for Everyone Wireless phone service is full of confusing labels, but AT&T\\u2019s latest \\u201c5GE\\u201d is raising new ire from consumers and industry rivals.\", \"Apple Gives New Retail Head Stock Grants Worth About $8 Million The Cupertino, California-based technology giant gave O\\u2019Brien two sets of 23,922 restricted stock units -- one group that will vest across three years beginning Aug. 5, 2021, and the other based on the company\\u2019s performance that may vest on Oct. 1, 2021, according to a regulatory filing. Each set is\", \"Apple isn't too happy about apps that secretly record your phone's screen Following TechCrunch's report that certain iOS apps are using technology from a company called Glassbox to record everything a user does within the app, Apple has started telling app developers that they either need to disclose this to users or face getting banned from the App Store. \\\"Our App\", \"Dow Jones Rout: The Cat is in the Bag, the Bag is in Trump\\u2019s Hand Friday started off badly for the Dow Jones industrial average, with all major stock indexes trading markedly lower right out o\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": 0.01502, "explanation": "The actual 21-day forward return for XLP starting 2019-02-11 was +1.50%, which classifies as 'positive'.", "metadata": {"future_return": 0.01502, "horizon_days": 21, "hist_return": -0.039593, "annualized_vol": 0.156897, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190201_0318", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2019-02-01", "context_summary": "IWM over past 60 days: cumulative return -2.9%, annualized vol 23.2%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=140.17, end=136.13, cumulative_return=-2.9%, annualized_volatility=23.2%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 252.561, 'unemployment': 4.0, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.18, 't10y3m_spread': 0.22, 'breakeven_10y': 1.85, 'hy_oas': 4.37, 'ig_oas': 1.38, 'ted_spread': 0.38, 'mortgage_30y': 4.46, 'vix': 16.56999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-31] [\"Apple may soup up cameras, boost AR capabilities in new iPhones: report With iPhone growth slowing, Apple Inc. hopes to reboot sales by significantly upgrading the smartphone's cameras and augmented-reality capabilities, Bloomberg News reported Wednesday. The 2019 phone could have three rear cameras, compared to the current two, and the 2020 model may have a rear 3D camera system, whereas the current version only has a front 3D camera, the report said. The new cameras for 2019 would also have a more powerful zoom, better resolution and a wider field of vision than the current iPhone's cameras. The 2020 version would reportedly include a laser-powered 3D camera that would improve depth perception to render more accurate augmented-reality overlays. Bloomberg reported Apple is in talks with Sony Corp. over sensors for the new 3D camera, and the 2020 phone could lead to a long-awaited AR headset. Bloomberg also said Apple is testing USB-C connectors with the 2019 iPhone, suggesting an eventual replacement to the Lightning port.\", \"Chip shortages cut into Microsoft's gains Microsoft Corp. said computer-chip shortages sliced expected sales of its Windows operating system in the last three months of 2018, and that the scarcity will likely continue to hurt sales in the months ahead.\", \"Qualcomm says disputes are weighing on revenue Qualcomm Inc. said revenue dropped 20% in its latest quarter and is likely to fall by a smaller amount in the current period, as disputes with customers including Apple Inc. continue to take a toll on the maker of communications chips.\", \"Will free Apple Music make us hate flying less? The wackiest new in-flight perks Airlines work to turn time wasted on flights into an opportunity Airlines work to turn time wasted on flights into an opportunity.\", \"Here are the biggest stock winners on the day the Fed went soft on interest rates A policy reversal by the central bank excites investors A policy reversal by the central bank excites investors.\", \"Amazon Earnings Will Highlight the Threat It Poses to Cloud and Ad Rivals Earnings figures, due out Thursday, will show how worried companies such as Netflix and Google should be as Amazon pushes into their turf.\", \"3 ETF Picks With Dividends You Can Trust These funds focus on Dividend Aristocrat indexes that feature long-term payout growth.\", \"Facebook faces more privacy questions, even as it announces record profit The social-media giant has admitted to monitoring the online activity of children The social-media giant has admitted to monitoring the online activity of children.\", \"The U.S. economy is fundamentally strong \\u2014 for now Job growth is great, the Fed is patient, and Trump may be ready to make a deal with China The fundamentals in the U.S. economy look strong, now that the shutdown has ended and the Fed has eased off, writes Tim Mullaney.\", \"Debt Could Hurt Netflix, GM, and CBS Stock, Bernstein Says Companies have become a lot less creditworthy over the past two decades, \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": 0.051146, "explanation": "The actual 21-day forward return for IWM starting 2019-02-01 was +5.11%, which classifies as 'positive'.", "metadata": {"future_return": 0.051146, "horizon_days": 21, "hist_return": -0.028838, "annualized_vol": 0.232083, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210907_0323", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2021-09-07", "context_summary": "SOL-USD over past 60 days: cumulative return +394.2%, annualized vol 116.9%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=33.26, end=164.38, cumulative_return=+394.2%, annualized_volatility=116.9%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 273.91, 'unemployment': 4.7, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.12, 't10y3m_spread': 1.28, 'breakeven_10y': 2.34, 'hy_oas': 3.13, 'ig_oas': 0.92, 'ted_spread': 0.07, 'mortgage_30y': 2.87, 'vix': 16.40999984741211}\nMarket regime: sideways\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": -0.240323, "explanation": "The actual 21-day forward return for SOL-USD starting 2021-09-07 was -24.03%, which classifies as 'negative'.", "metadata": {"future_return": -0.240323, "horizon_days": 21, "hist_return": 3.94161, "annualized_vol": 1.168978, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190130_0326", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-01-30", "context_summary": "ETH-USD over past 60 days: cumulative return +0.0%, annualized vol 94.5%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=122.03, end=122.03, cumulative_return=+0.0%, annualized_volatility=94.5%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 252.561, 'unemployment': 4.0, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.16, 't10y3m_spread': 0.3, 'breakeven_10y': 1.78, 'hy_oas': 4.4, 'ig_oas': 1.39, 'ted_spread': 0.37, 'mortgage_30y': 4.45, 'vix': 19.1299991607666}\nMarket regime: sideways\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": 0.225527, "explanation": "The actual 21-day forward return for ETH-USD starting 2019-01-30 was +22.55%, which classifies as 'positive'.", "metadata": {"future_return": 0.225527, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.944858, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220114_0331", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2022-01-14", "context_summary": "AVAX-USD over past 60 days: cumulative return +0.0%, annualized vol 112.1%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=82.96, end=82.96, cumulative_return=+0.0%, annualized_volatility=112.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 282.543, 'unemployment': 4.0, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.79, 't10y3m_spread': 1.58, 'breakeven_10y': 2.43, 'hy_oas': 3.1, 'ig_oas': 0.97, 'ted_spread': 0.12, 'mortgage_30y': 3.45, 'vix': 20.309999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-13] \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": -0.068039, "explanation": "The actual 21-day forward return for AVAX-USD starting 2022-01-14 was -6.80%, which classifies as 'negative'.", "metadata": {"future_return": -0.068039, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 1.121072, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20221010_0335", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-10-10", "context_summary": "ETH-USD over past 60 days: cumulative return -29.7%, annualized vol 63.0%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1881.22, end=1322.60, cumulative_return=-29.7%, annualized_volatility=63.0%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 298.007, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.41, 't10y3m_spread': 0.44, 'breakeven_10y': 2.27, 'hy_oas': 5.02, 'ig_oas': 1.6, 'ted_spread': 0.09, 'mortgage_30y': 6.66, 'vix': 31.36000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-09] \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": 0.217896, "explanation": "The actual 21-day forward return for ETH-USD starting 2022-10-10 was +21.79%, which classifies as 'positive'.", "metadata": {"future_return": 0.217896, "horizon_days": 21, "hist_return": -0.296945, "annualized_vol": 0.630136, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20220418_0338", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2022-04-18", "context_summary": "MORT over past 60 days: cumulative return -4.4%, annualized vol 19.5%. Market regime: sideways.", "question": "Asset: MORT\nHistorical prices (past 60 trading days): start=10.43, end=9.97, cumulative_return=-4.4%, annualized_volatility=19.5%\nMacro context: {'fed_funds_rate': 0.33, 'cpi_yoy': 288.561, 'unemployment': 3.7, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.36, 't10y3m_spread': 2.04, 'breakeven_10y': 2.86, 'hy_oas': 3.68, 'ig_oas': 1.26, 'ted_spread': 0.09, 'mortgage_30y': 5.0, 'vix': 22.700000762939453}\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": -0.034056, "explanation": "The actual 21-day forward return for MORT starting 2022-04-18 was -3.41%, which classifies as 'negative'.", "metadata": {"future_return": -0.034056, "horizon_days": 21, "hist_return": -0.044269, "annualized_vol": 0.194826, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201005_0341", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2020-10-05", "context_summary": "BNB-USD over past 60 days: cumulative return +27.5%, annualized vol 88.3%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=22.71, end=28.94, cumulative_return=+27.5%, annualized_volatility=88.3%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.57, 't10y3m_spread': 0.61, 'breakeven_10y': 1.64, 'hy_oas': 5.38, 'ig_oas': 1.43, 'ted_spread': 0.14, 'mortgage_30y': 2.88, 'vix': 27.6299991607666}\nMarket regime: sideways\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": 0.087074, "explanation": "The actual 21-day forward return for BNB-USD starting 2020-10-05 was +8.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.087074, "horizon_days": 21, "hist_return": 0.274629, "annualized_vol": 0.883405, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20150915_0344", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2015-09-15", "context_summary": "FXI over past 60 days: cumulative return -22.7%, annualized vol 36.9%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=35.80, end=27.67, cumulative_return=-22.7%, annualized_volatility=36.9%\nMacro context: {'fed_funds_rate': 0.14, 'cpi_yoy': 237.498, 'unemployment': 5.0, 'gdp_growth_qoq': 18857.418, 't10y2y_spread': 1.45, 't10y3m_spread': 2.11, 'breakeven_10y': 1.56, 'hy_oas': 5.62, 'ig_oas': 1.67, 'ted_spread': 0.27, 'mortgage_30y': 3.9, 'vix': 24.25}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-09-14] [\"Apple's stock may rise 50% on iPhone program: Barron's Shares in Apple Inc. \\\"could soar 50% in the coming year\\\" thanks in large part to the tech giant's new plan to lease iPhones and offer annual upgrades, says a story in the past weekend's edition of Barron's. \\\"The leasing program attacks the primary bear case on Apple--slowing iPhone growth,\\\" the Barron's story adds. Shares in Apple were up 0.5% in thin premarket trading early Monday.\", \"Apple's stock climbs 1.1% in premarket trade\", \"Apple's new iPhone pre-orders off to a 'strong' start, analyst says Apple Inc.'s stock climbed 1.5% in premarket trade Monday, amid signs that pre-orders for iPhone 6s and iPhone 6s Plus are off to a strong start, with particular strength out of China, according to Analyst Daniel Ives at FBR & Co. \\\"Initial demand looks strong, based on estimated wait times as displayed on Apple's Web site and various blogs,\\\" Ives wrote in a note to clients. \\\"While there are still unknowns about inventory levels, we note that China demand in particular looks 'very strong' out of the gates and is a positive sign that the white-hot momentum out of this region shows no signs of abating despite macro headwinds out of China.\\\" He said wait times for 6s Plus are roughly three to four weeks in the U.S., U.K. and China. For the 6s, wait times are shorter in the U.S. and U.K., depending on the carrier, and two to three weeks in China. Given recent data, Ives said he believes pre-sales of the new iPhones will exceed the 4 million orders Apple had for iPhone 6/iPhone 6 Plus a year ago. The stock has dropped 10% over the past three months through Friday, while the Dow Jones Industrial Average has lost 8.2%.\", \"Is Twitter negotiating with a CEO or working on an acquisition? Opinion: There could be several reasons that CEO search has topped three months The search for Twitter Inc.\\u2019s chief executive is now three months old, why is it taking so long? A lot of factors, including the Jack Dorsey question, could be at play.\", \"Here\\u2019s why the next 15 years will be great for stocks Critical intelligence before the U.S. market opens We enter Monday\\u2019s session on the heels of a rare weekly win. It wasn\\u2019t easy, either. Expect more of these violent spurts of volatility as we enter a week punctuated by the Federal Reserve\\u2019s decision on interest rates. Will they? Won\\u2019t they?\", \"Apple TV needs Angry Birds-like app to be successful gaming platform Analysts at Sterne Agee said in a note on Monday that Apple Inc.'s new Apple TV device has the potential to become a player in, and help expand the video-gaming market. Apple's much-anticipated device, unveiled last week with a $149-$199 price tag, streams video content and has gaming capabilities, including the capability for third-party video-game apps to be developed for it through the device's tvOS. While lead analyst Arvind Bhatia said existing mobile game apps will undoubtedly be ported to Apple TV, the Cupertino-based comp\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": 0.052126, "explanation": "The actual 21-day forward return for FXI starting 2015-09-15 was +5.21%, which classifies as 'positive'.", "metadata": {"future_return": 0.052126, "horizon_days": 21, "hist_return": -0.227064, "annualized_vol": 0.369063, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20170103_0347", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2017-01-03", "context_summary": "IYR over past 60 days: cumulative return +1.8%, annualized vol 16.0%. Market regime: sideways.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=58.01, end=59.04, cumulative_return=+1.8%, annualized_volatility=16.0%\nMacro context: {'fed_funds_rate': 0.55, 'cpi_yoy': 243.618, 'unemployment': 4.7, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.25, 't10y3m_spread': 1.94, 'breakeven_10y': 1.95, 'hy_oas': 4.22, 'ig_oas': 1.3, 'ted_spread': 0.5, 'mortgage_30y': 4.32, 'vix': 14.039999961853027}\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": "flat", "answer_numeric": -0.003495, "explanation": "The actual 21-day forward return for IYR starting 2017-01-03 was -0.35%, which classifies as 'flat'.", "metadata": {"future_return": -0.003495, "horizon_days": 21, "hist_return": 0.01773, "annualized_vol": 0.160323, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20151026_0350", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["CORN"], "decision_date": "2015-10-26", "context_summary": "CORN over past 60 days: cumulative return -1.0%, annualized vol 19.1%. Market regime: sideways.", "question": "Asset: CORN\nHistorical prices (past 60 trading days): start=23.14, end=22.90, cumulative_return=-1.0%, annualized_volatility=19.1%\nMacro context: {'fed_funds_rate': 0.12, 'cpi_yoy': 237.733, 'unemployment': 5.0, 'gdp_growth_qoq': 18892.206, 't10y2y_spread': 1.43, 't10y3m_spread': 2.08, 'breakeven_10y': 1.51, 'hy_oas': 5.97, 'ig_oas': 1.67, 'ted_spread': 0.31, 'mortgage_30y': 3.79, 'vix': 14.460000038146973}\nMarket regime: sideways\n\nPredict whether the return of CORN over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.050453, "explanation": "The actual 21-day forward return for CORN starting 2015-10-26 was -5.05%, which classifies as 'negative'.", "metadata": {"future_return": -0.050453, "horizon_days": 21, "hist_return": -0.010372, "annualized_vol": 0.190539, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20221202_0353", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2022-12-02", "context_summary": "DBB over past 60 days: cumulative return +4.4%, annualized vol 24.1%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=16.49, end=17.20, cumulative_return=+4.4%, annualized_volatility=24.1%\nMacro context: {'fed_funds_rate': 3.83, 'cpi_yoy': 298.832, 'unemployment': 3.5, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.72, 't10y3m_spread': -0.8, 'breakeven_10y': 2.36, 'hy_oas': 4.48, 'ig_oas': 1.41, 'ted_spread': 0.09, 'mortgage_30y': 6.49, 'vix': 19.84000015258789}\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": "negative", "answer_numeric": -0.041362, "explanation": "The actual 21-day forward return for DBB starting 2022-12-02 was -4.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.041362, "horizon_days": 21, "hist_return": 0.043636, "annualized_vol": 0.240501, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181212_0356", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2018-12-12", "context_summary": "ADA-USD over past 60 days: cumulative return -58.0%, annualized vol 82.6%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.07, end=0.03, cumulative_return=-58.0%, annualized_volatility=82.6%\nMacro context: {'fed_funds_rate': 2.19, 'cpi_yoy': 252.767, 'unemployment': 3.9, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.11, 't10y3m_spread': 0.48, 'breakeven_10y': 1.83, 'hy_oas': 4.48, 'ig_oas': 1.51, 'ted_spread': 0.41, 'mortgage_30y': 4.75, 'vix': 21.76000022888184}\nMarket regime: sideways\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": 0.472907, "explanation": "The actual 21-day forward return for ADA-USD starting 2018-12-12 was +47.29%, which classifies as 'positive'.", "metadata": {"future_return": 0.472907, "horizon_days": 21, "hist_return": -0.579675, "annualized_vol": 0.826476, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201203_0359", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2020-12-03", "context_summary": "QUAL over past 60 days: cumulative return +9.2%, annualized vol 19.0%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=97.33, end=106.27, cumulative_return=+9.2%, annualized_volatility=19.0%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 262.045, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.79, 't10y3m_spread': 0.86, 'breakeven_10y': 1.85, 'hy_oas': 4.17, 'ig_oas': 1.08, 'ted_spread': 0.14, 'mortgage_30y': 2.72, 'vix': 21.170000076293945}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-12-02] [\"Are Microsoft And Adobe Coming For Salesforce's Market Share? Adobe (NASDAQ: ADBE) and Microsoft (NASDAQ: MSFT) have teamed up to take on customer relationship management (CRM), which has historically been Salesforce's (NYSE: CRM) domain. ProShares' Executive Director of Thematic Investing Scott Helfstein shares what investors need to know about how the COVID-19 pandemic has accelerated market trends in the cloud and how their new ETF ProShares MSCI Transformational Changes ETF (NYSEMKT: ANEW) is capitalizing on these transformations. 10 stocks we like better than Salesforce.com When investing geniuses David and Tom Gardner have 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.* David and Tom just revealed what they believe are the ten best stocks for investors to buy right now... and Salesforce.com 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 November 20, 2020 Corinne Cardina: Awesome. There are also a couple of more traditional tech stocks in the future of work part of the basket. Adobe, I think a lot of people, what comes to mind is Photoshop, Illustrator, InDesign. Microsoft people tend to think about their Office Suite, and Windows. What are some of the ways that these older tech companies are really transforming and how the pandemic has spurred that along? Scott Helfstein: Microsoft is a juggernaut. It's one that's hard for people to wrap their brain around, because it is so prominent. We work with the Office Suite, and Word, Excel, and our operating system. But they've taken a lot of their revenue into the cloud with subscription service. We see that cloud and productivity tools make up about two-thirds. It's really interesting that you talk about Microsoft and Adobe because they've actually announced a partnership a little while ago to take on customer relationship management. So CRM is a new segment, the two of them working in conjunction. By the way, Microsoft, as I think you were implying, also has a big gaming division with Xbox. As we think about virtualizing work, it's a little crazy to think about this. But what about the virtual reality coffee break? Or the virtual reality water cooler? There are some companies that are uniquely positioned to be able to facilitate a new and different remote working environment. Microsoft I think is one that investors should continue to pay attention to. Really important from a productivity standpoint, and Adobe as well. My 11-year-old wanted a subscription to Illustrator for his birthday this year. They are not just talking about PDFs, but they are important in secure document management. However, we've got Photoshop, we've got Illustrator, they also have an artificial intelligence product called Sensei, which actually helps people to do their graphic and document management. They're on the cutting edge of artificial\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": 0.023947, "explanation": "The actual 21-day forward return for QUAL starting 2020-12-03 was +2.39%, which classifies as 'positive'.", "metadata": {"future_return": 0.023947, "horizon_days": 21, "hist_return": 0.091856, "annualized_vol": 0.189847, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210420_0362", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2021-04-20", "context_summary": "XLI over past 60 days: cumulative return +14.1%, annualized vol 16.9%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=81.76, end=93.33, cumulative_return=+14.1%, annualized_volatility=16.9%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 266.614, 'unemployment': 6.1, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.45, 't10y3m_spread': 1.59, 'breakeven_10y': 2.34, 'hy_oas': 3.25, 'ig_oas': 0.95, 'ted_spread': 0.17, 'mortgage_30y': 3.04, 'vix': 17.290000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-04-19] [\"The Station: A chat with Scale AI's Alexandr Wang, the NYC scooter winners and TuSimple goes public The Station is a weekly newsletter dedicated to all things transportation. Sign up here \\u2014 just click The Station \\u2014 to receive it every weekend in your inbox. This is The Station, a weekly newsletter dedicated to all the ways people and packages move (today and in the future) from Point A to Point B.\", \"FleetPride Acquires Steubenville Truck Center, Continues Parts and Service Expansion FleetPride, Inc. announced today that it has acquired the assets of Steubenville Truck Center in Steubenville, Ohio. For nearly 70 years, Steubenville Truck Center has been providing outstanding truck parts and service to customers in eastern Ohio, northern West Virginia, and western Pennsylvania. The company has been in its current location since 1998 and is managed by Larry Remp.\", \"Verizon starts C-Band equipment deployment What you need to know: Basebands, radios and antennas from Ericsson and Samsung are currently being deployed in the Verizon network.The arrival of RAN equipment in combination with Verizon\\u2019s recent tower agreements will speed deployment of 5G Ultra Wideband on existing infrastructure using C-band spectrum.100 million customers will have access to the game-changing 5G Ultra Wideband service using C-band spectrum by the end of the first quarter in 2022 NEW YORK, April 19, 2021 (GLOBE NEWSWIRE) -- Verizon recently began installation of C-band equipment from Ericsson and Samsung Electronics Co., Ltd to speed deployment of its 5G Ultra Wideband and fixed wireless broadband service on its recently acquired C-band spectrum. Verizon secured an average of 161 MHz of C-band spectrum nationwide in the recent FCC auction, which will allow the company to offer expanded mobility and broadband services to millions more consumers and businesses. C-band spectrum provides a valuable middle ground between capacity and coverage for 5G networks, and will enable 5G Ultra Wideband speeds and coverage for both mobility, home broadband and business internet solutions. Deploying 5G Ultra Wideband on this spectrum requires new network equipment including basebands, radios and antennas to be placed on existing towers. Verizon tapped Ericsson and Samsung to supply the Radio Access Network (RAN) equipment for this massive deployment. Although the initial spectrum won\\u2019t be cleared until the end of this year, Verizon and its vendor partners have already begun the work to ensure the super-fast 5G Ultra Wideband service using C-band is deployed to 100 million customers by March 2022. \\u201cWe\\u2019re moving fast, with cooperation from our equipment partners, to have everything in place as soon as this C-band spectrum is cleared for use,\\u201d said Kyle Malady, Chief Technology Officer at Verizon. \\u201cThis is a massive undertaking designed to add this game-changing capability as quickly as possible to the network our customers already rely on for consiste\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": 0.027106, "explanation": "The actual 21-day forward return for XLI starting 2021-04-20 was +2.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.027106, "horizon_days": 21, "hist_return": 0.141453, "annualized_vol": 0.169041, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210430_0367", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2021-04-30", "context_summary": "BIL over past 60 days: cumulative return -0.0%, annualized vol 0.1%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=77.77, end=77.76, cumulative_return=-0.0%, annualized_volatility=0.1%\nMacro context: {'fed_funds_rate': 0.06, 'cpi_yoy': 266.614, 'unemployment': 6.1, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.49, 't10y3m_spread': 1.64, 'breakeven_10y': 2.42, 'hy_oas': 3.24, 'ig_oas': 0.94, 'ted_spread': 0.17, 'mortgage_30y': 2.98, 'vix': 17.610000610351562}\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": -0.000109, "explanation": "The actual 21-day forward return for BIL starting 2021-04-30 was -0.01%, which classifies as 'flat'.", "metadata": {"future_return": -0.000109, "horizon_days": 21, "hist_return": -0.000109, "annualized_vol": 0.001213, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160308_0370", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2016-03-08", "context_summary": "ICSH over past 60 days: cumulative return +0.1%, annualized vol 2.3%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=38.50, end=38.54, cumulative_return=+0.1%, annualized_volatility=2.3%\nMacro context: {'fed_funds_rate': 0.36, 'cpi_yoy': 238.08, 'unemployment': 5.0, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.0, 't10y3m_spread': 1.59, 'breakeven_10y': 1.48, 'hy_oas': 7.03, 'ig_oas': 1.93, 'ted_spread': 0.32, 'mortgage_30y': 3.64, 'vix': 17.350000381469727}\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": 0.002407, "explanation": "The actual 21-day forward return for ICSH starting 2016-03-08 was +0.24%, which classifies as 'flat'.", "metadata": {"future_return": 0.002407, "horizon_days": 21, "hist_return": 0.000904, "annualized_vol": 0.023464, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20221124_0373", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-11-24", "context_summary": "ETH-USD over past 60 days: cumulative return -8.6%, annualized vol 70.7%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1294.22, end=1183.20, cumulative_return=-8.6%, annualized_volatility=70.7%\nMacro context: {'fed_funds_rate': 3.83, 'cpi_yoy': 298.786, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.75, 't10y3m_spread': -0.69, 'breakeven_10y': 2.32, 'hy_oas': 4.51, 'ig_oas': 1.42, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 20.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-23] \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": 0.051804, "explanation": "The actual 21-day forward return for ETH-USD starting 2022-11-24 was +5.18%, which classifies as 'positive'.", "metadata": {"future_return": 0.051804, "horizon_days": 21, "hist_return": -0.085779, "annualized_vol": 0.70652, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20180320_0376", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2018-03-20", "context_summary": "TIP over past 60 days: cumulative return +0.2%, annualized vol 1.0%. Market regime: sideways.", "question": "Asset: TIP\nHistorical prices (past 60 trading days): start=77.16, end=77.29, cumulative_return=+0.2%, annualized_volatility=1.0%\nMacro context: {'fed_funds_rate': 1.43, 'cpi_yoy': 249.577, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.54, 't10y3m_spread': 1.05, 'breakeven_10y': 2.08, 'hy_oas': 3.65, 'ig_oas': 1.1, 'ted_spread': 0.45, 'mortgage_30y': 4.44, 'vix': 19.020000457763672}\nMarket regime: sideways\n\nPredict whether the return of TIP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003608, "explanation": "The actual 21-day forward return for TIP starting 2018-03-20 was +0.36%, which classifies as 'flat'.", "metadata": {"future_return": 0.003608, "horizon_days": 21, "hist_return": 0.001706, "annualized_vol": 0.010401, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20221107_0381", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2022-11-07", "context_summary": "VCIT over past 60 days: cumulative return -8.6%, annualized vol 8.8%. Market regime: sideways.", "question": "Asset: VCIT\nHistorical prices (past 60 trading days): start=70.79, end=64.72, cumulative_return=-8.6%, annualized_volatility=8.8%\nMacro context: {'fed_funds_rate': 3.83, 'cpi_yoy': 298.786, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.49, 't10y3m_spread': -0.04, 'breakeven_10y': 2.48, 'hy_oas': 4.77, 'ig_oas': 1.61, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 24.549999237060547}\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": "positive", "answer_numeric": 0.058136, "explanation": "The actual 21-day forward return for VCIT starting 2022-11-07 was +5.81%, which classifies as 'positive'.", "metadata": {"future_return": 0.058136, "horizon_days": 21, "hist_return": -0.085838, "annualized_vol": 0.088368, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20221026_0384", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2022-10-26", "context_summary": "XLK over past 60 days: cumulative return -9.9%, annualized vol 28.8%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=69.45, end=62.60, cumulative_return=-9.9%, annualized_volatility=28.8%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 298.007, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.32, 't10y3m_spread': -0.04, 'breakeven_10y': 2.51, 'hy_oas': 4.88, 'ig_oas': 1.69, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 28.459999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-25] [\"Why Is Everyone Talking About Apple? Apple's (NASDAQ: AAPL) stock has fallen about 10% since mid-September. The leading causes for the dip have been numerous reports that sales for its base-model iPhone 14 and 14 Plus have been underwhelming and an overall slowdown of consumer demand in the tech market. As the highest-valued company in the world, with a market cap of $2.37 trillion, Apple is one of the world's most scrutinized companies. The last two months have been no different as analysts pick apart the company's September iPhone launch and its 2022 iPad lineup unveiling in mid-October. Understanding the strategy behind Apple's recently announced products can be a great way to predict how far your investment will go. So, here's why Apple's new products have been making headlines. A confusing iPad launch On Oct. 18, Apple unveiled its 2022 iPad refresh by introducing a newly designed base iPad and upgraded iPad Pros. Time will tell how the new Apple tablets fare with consumers, but the media has been quick to criticize the devices. Bloomberg has called the new iPad lineup \\\"perplexing,\\\" while Techradar said its \\\"software and now hardware is a mess.\\\" The primary reason for the confusion lies in upgrades to the entry-level iPads, but not the Pro versions. The base iPads received a redesign with new colors, relocation of the front-facing camera to the landscape's edge, and a revamped Magic Keyboard accessory. Meanwhile, the 2022 iPad Pro models received the smallest update in their history. They were bumped up to the M2 chip, making them 15% faster than their predecessors, along with other minor performance upgrades. However, the higher-cost versions didn't receive the same optimal camera relocation or the redesigned Magic Keyboard. The Pro models didn't even receive the customary camera or display improvements that consumers have come to expect year to year. As a result, Apple has given consumers little reason to upgrade to the 2022 iPad Pro and created confusion by omitting features given to the base iPad. Moreover, despite the base iPad's more enticing improvements, it has not been left unscathed by criticism. The tablet has undergone a significant redesign, including its charging port going from lightning to the market-preferred USB-C. However, it is still only compatible with the 2015 Apple Pencil accessory that charges via lightning rather than the redesigned 2018 version that charges magnetically along the side of higher-tiered iPads. As a result, users need to use an adapter to charge their Apple Pencil with the new base iPad. iPhone 14 Plus is a bust In addition to a confusing iPad lineup, Apple has reportedly faced dismal demand for its iPhone 14 Plus, which hit stores on Oct. 7. The base-model iPhone was announced on Sept. 7, along with two new Pro models and a standard-sized base model. Apple had high hopes for the larger iPhone 14 as it signified a shakeup in the lineup. There hasn't been a Plus-sized base model since 2017's iPho\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": 0.06361, "explanation": "The actual 21-day forward return for XLK starting 2022-10-26 was +6.36%, which classifies as 'positive'.", "metadata": {"future_return": 0.06361, "horizon_days": 21, "hist_return": -0.098697, "annualized_vol": 0.288216, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190513_0387", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2019-05-13", "context_summary": "QQQ over past 60 days: cumulative return +8.2%, annualized vol 11.5%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=163.66, end=177.15, cumulative_return=+8.2%, annualized_volatility=11.5%\nMacro context: {'fed_funds_rate': 2.38, 'cpi_yoy': 255.296, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.21, 't10y3m_spread': 0.04, 'breakeven_10y': 1.88, 'hy_oas': 4.01, 'ig_oas': 1.22, 'ted_spread': 0.15, 'mortgage_30y': 4.1, 'vix': 16.040000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-05-10] [\"Definitely Don\\u2019t Buy Intel Stock Today! Conditions have quickly gone from gone from dismay to sell-in-May in a very big way for Intel Corporation (NASDAQ:) the past couple weeks. And for INTC bulls, while there\\u2019s a technical case for a bottom, I\\u2019d suggest waiting patiently. Remember, there\\u2019s always a line somewhere. Let me explain. Source: Shutterstock Just when INTC investors thought it couldn\\u2019t possibly get any worse, Thursday proved otherwise. Following late April\\u2019s weak guidance and the company\\u2019s first decline in data center sales and profits in a decade as its earnings centerpiece, Intel\\u2019s first analyst day in over two years served to rattle already frazzled investors even more. INTC shares tumbled more than 5% and towards four-month lows as detailed positive trends for free cash flow, capital allocation and operating margins were derailed by surprisingly weak gross margins guidance and declining market share amid growing competition from rival Advanced Micro Devices (NASDAQ:). Along with Intel\\u2019s continued difficulties off and on the price chart, Thursday\\u2019s confessional saw BMO Capital Markets downgrade shares to market perform, as well as receiving from brokers Cowen & Co. and Bernstein. Intel Stock Monthly Price Chart I like to say there\\u2019s always a line somewhere when it comes to the price chart. For bullish investors, it\\u2019s a warning to guard against technically coming up with overly aggressive reasons to remain long or initiate a purchase in the face of an adverse price move. Right now, INTC stock is showing those supportive-looking lines in spades on the monthly view. And that could be very costly if bulls aren\\u2019t careful. Rationalizing a low in Intel shares based on the next level of support, whether it\\u2019s a trend-line or Fibonacci level as I\\u2019ve detailed, could take bulls from today\\u2019s $46 down to around $28 a share. That\\u2019s not to say investors shouldn\\u2019t buy INTC stock as key price levels are being tested. However, having a game plan and exit strategy is critical to avoid potentially deep losses. Buying Intel Stock My recommendation for buying into Intel stock\\u2019s uptrend is to wait for a stronger entry. This is likely to look like one of two scenarios on the INTC price chart. The first is if a technical floor is found near current levels and Intel\\u2019s steepest trend-line and highest layers of Fibonacci support manage to hold the stock price above $45. I\\u2019m not holding my breath. But if a bullish candlestick pattern can develop over the next couple weeks with support still intact, buying INTC stock makes more sense in conjunction with a stop-loss. The second situation where price action in Intel might warrant buying shares is continued persistent weakness. I\\u2019d personally avoid buying shares in between $40 to $45. The next area where INTC stock has the backing of both an uptrend line and Fibonacci supports and where I\\u2019d be interes\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": 0.021055, "explanation": "The actual 21-day forward return for QQQ starting 2019-05-13 was +2.11%, which classifies as 'positive'.", "metadata": {"future_return": 0.021055, "horizon_days": 21, "hist_return": 0.082448, "annualized_vol": 0.114634, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220628_0390", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHY"], "decision_date": "2022-06-28", "context_summary": "SHY over past 60 days: cumulative return -0.5%, annualized vol 2.2%. Market regime: sideways.", "question": "Asset: SHY\nHistorical prices (past 60 trading days): start=73.07, end=72.73, cumulative_return=-0.5%, annualized_volatility=2.2%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.957, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.12, 't10y3m_spread': 1.41, 'breakeven_10y': 2.55, 'hy_oas': 5.11, 'ig_oas': 1.54, 'ted_spread': 0.09, 'mortgage_30y': 5.81, 'vix': 26.950000762939453}\nMarket regime: sideways\n\nPredict whether the return of SHY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0052, "explanation": "The actual 21-day forward return for SHY starting 2022-06-28 was +0.52%, which classifies as 'flat'.", "metadata": {"future_return": 0.0052, "horizon_days": 21, "hist_return": -0.004597, "annualized_vol": 0.022295, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200904_0393", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2020-09-04", "context_summary": "XLY over past 60 days: cumulative return +20.2%, annualized vol 19.2%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=59.11, end=71.08, cumulative_return=+20.2%, annualized_volatility=19.2%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 259.997, 'unemployment': 7.8, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.5, 't10y3m_spread': 0.52, 'breakeven_10y': 1.65, 'hy_oas': 5.04, 'ig_oas': 1.35, 'ted_spread': 0.14, 'mortgage_30y': 2.93, 'vix': 33.599998474121094}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-03] [\"Apple's stock falls 2.2% premarket, after shedding 2.1% on Wednesday\", \"These 74 stocks in the S&P 500 hit all-time records on Wednesday It was a broad rally, one that wasn\\u2019t led by the information technology sector It was a broad rally, one that wasn\\u2019t led by the information technology sector.\", \"This Election Could Be Really Weird. Hedge Your Portfolio. Investors should consider insulating their investment portfolios from bizarre political shocks. Here\\u2019s how.\", \"How to get your stock trades through when Robinhood, Vanguard and other brokerages go down, as they did this week Use apps and spread your money across more than one platform Use apps and spread your money across more than one platform, says Michael Brush.\", \"Tyson Foods to open on-site health clinics Shares of Tyson Foods Inc. gained 0.2% in premarket trading on Thursday after the food giant said it will open seven health clinics near its facilities for employees and their families. The clinics, which will be operated by Marathon Health, a privately held provider of worksite health clinics, are expected to open in 2021. Employers are facing rising costs of health care services provided to their employees, and in recent years several large companies including Apple Inc. and Amazon Inc. have announced plans to set up health clinics for their workers. In July Tyson announced that it will create the company's first chief medical officer role. It also outlined a COVID-19 testing strategy that requires it to test thousands of workers for the virus following several coronavirus outbreaks among its workers this summer. Tyson's stock is down 30.3% for the year, while the S&P 500 is up 10.8%.\", \"Barron\\u2019s Daily: The Tech-Stock Rally Is Taking a Breather Facebook bans political ads the week before the election, widely available steroids help most severely ill Covid-19 patients, U.S. debt is set to surpass the size of the economy, and other news to start your day.\", \"13 Cheap Stocks That Could Be Traps Some stocks are cheap for a reason. They are in declining industries or facing long-term problems in place before the onset of Covid-19.\", \"Here are Bank of America\\u2019s \\u2018must-know\\u2019 market stats that show \\u2018epic polarization\\u2019 Michael Hartnett, chief investment strategist for Bank of America, has put together his annual list of the top stats on the size, composition, risks, returns, leverage, yields and valuations of the bond and equity universe.\", \"Dow's nearly 300-point drop led by losses for Apple Inc., Salesforce.com Inc. stocks\", \"Dow's 550-point drop led by losses in shares of Apple Inc., Salesforce.com Inc.\", \"Tech stocks and the rest of the market are both very expensive \\u2014 for 2 \\u2018completely different reasons\\u2019 Highflying tech-related stocks and the rest of the market are both very expensive by historical measures, but for different reasons -- a bifurcation that raises an important question for investors, according to one market watcher.\"\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": 0.023037, "explanation": "The actual 21-day forward return for XLY starting 2020-09-04 was +2.30%, which classifies as 'positive'.", "metadata": {"future_return": 0.023037, "horizon_days": 21, "hist_return": 0.202375, "annualized_vol": 0.192193, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180227_0396", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2018-02-27", "context_summary": "PALL over past 60 days: cumulative return +7.0%, annualized vol 25.1%. Market regime: sideways.", "question": "Asset: PALL\nHistorical prices (past 60 trading days): start=94.71, end=101.30, cumulative_return=+7.0%, annualized_volatility=25.1%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 249.529, 'unemployment': 4.1, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.64, 't10y3m_spread': 1.2, 'breakeven_10y': 2.13, 'hy_oas': 3.5, 'ig_oas': 1.0, 'ted_spread': 0.33, 'mortgage_30y': 4.4, 'vix': 15.800000190734863}\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": "negative", "answer_numeric": -0.070743, "explanation": "The actual 21-day forward return for PALL starting 2018-02-27 was -7.07%, which classifies as 'negative'.", "metadata": {"future_return": -0.070743, "horizon_days": 21, "hist_return": 0.069581, "annualized_vol": 0.250911, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210922_0399", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2021-09-22", "context_summary": "ADA-USD over past 60 days: cumulative return +61.1%, annualized vol 94.1%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=1.23, end=1.99, cumulative_return=+61.1%, annualized_volatility=94.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 273.91, 'unemployment': 4.7, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.11, 't10y3m_spread': 1.3, 'breakeven_10y': 2.29, 'hy_oas': 3.17, 'ig_oas': 0.91, 'ted_spread': 0.1, 'mortgage_30y': 2.86, 'vix': 24.36000061035156}\nMarket regime: sideways\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": -0.034035, "explanation": "The actual 21-day forward return for ADA-USD starting 2021-09-22 was -3.40%, which classifies as 'negative'.", "metadata": {"future_return": -0.034035, "horizon_days": 21, "hist_return": 0.61089, "annualized_vol": 0.941244, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201027_0402", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-10-27", "context_summary": "LINK-USD over past 60 days: cumulative return -22.5%, annualized vol 108.8%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=15.16, end=11.75, cumulative_return=-22.5%, annualized_volatility=108.8%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.65, 't10y3m_spread': 0.7, 'breakeven_10y': 1.72, 'hy_oas': 5.03, 'ig_oas': 1.3, 'ted_spread': 0.11, 'mortgage_30y': 2.8, 'vix': 32.459999084472656}\nMarket regime: sideways\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": 0.106138, "explanation": "The actual 21-day forward return for LINK-USD starting 2020-10-27 was +10.61%, which classifies as 'positive'.", "metadata": {"future_return": 0.106138, "horizon_days": 21, "hist_return": -0.224871, "annualized_vol": 1.088283, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20171009_0409", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2017-10-09", "context_summary": "XLB over past 60 days: cumulative return +5.4%, annualized vol 9.6%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=23.16, end=24.40, cumulative_return=+5.4%, annualized_volatility=9.6%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 246.626, 'unemployment': 4.2, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.83, 't10y3m_spread': 1.3, 'breakeven_10y': 1.87, 'hy_oas': 3.52, 'ig_oas': 1.04, 'ted_spread': 0.3, 'mortgage_30y': 3.85, 'vix': 9.729999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-10-06] [\"IYW, ADBE, CRM, CTSH: Large Outflows Detected at ETF Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the iShares U.S. Technology ETF (Symbol: IYW) where we have detected an approximate $98.7 million dollar outflow -- that's a 2.6% decrease week over week (from 24,600,000 to 23,950,000). Among the largest underlying components of IYW, in trading today Adobe Systems Inc (Symbol: ADBE) is up about 0.5%, Salesforce.com Inc (Symbol: CRM) is up about 0.7%, and Cognizant Technology Solutions Corp. (Symbol: CTSH) is higher by about 0.6%. For a complete list of holdings, visit the IYW Holdings page \\u00bb The chart below shows the one year price performance of IYW, versus its 200 day moving average: Looking at the chart above, IYW's low point in its 52 week range is $114.68 per share, with $151.91 as the 52 week high point - that compares with a last trade of $151.86. 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 experienced notable outflows \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"MKSI Instruments Looks Bullish on Robust Growth Drivers We issued an updated research report on premium scientific and technical instruments company, MKS Instruments, Inc.MKSI , on Oct 6. In the last month, shares of this Zacks Rank #2 (Buy) stock have yielded a return of 91.2%, outperforming 57.4% growth recorded by the industry . Notably, the attractiveness of this stock as a current investment choice is further accentuated by its favorable VGM Score B. Also, the stock's projected sales growth is 41.8% and earnings per share growth is 79.5% for 2017 compared to the respective tallies of 10.7% and 57.1% estimated for the industry. Moreover, the company's earnings are projected to be up 15.7% in the next three to five years. Why Should You Grab the Stock? MKS Instruments has a well-balanced technology portfolio and in\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": 0.012956, "explanation": "The actual 21-day forward return for XLB starting 2017-10-09 was +1.30%, which classifies as 'positive'.", "metadata": {"future_return": 0.012956, "horizon_days": 21, "hist_return": 0.053608, "annualized_vol": 0.096191, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220126_0414", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2022-01-26", "context_summary": "DBB over past 60 days: cumulative return +9.5%, annualized vol 17.9%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=18.13, end=19.86, cumulative_return=+9.5%, annualized_volatility=17.9%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 282.543, 'unemployment': 4.0, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.76, 't10y3m_spread': 1.59, 'breakeven_10y': 2.41, 'hy_oas': 3.39, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 3.56, 'vix': 31.15999984741211}\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": 0.043984, "explanation": "The actual 21-day forward return for DBB starting 2022-01-26 was +4.40%, which classifies as 'positive'.", "metadata": {"future_return": 0.043984, "horizon_days": 21, "hist_return": 0.095418, "annualized_vol": 0.17864, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220721_0419", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2022-07-21", "context_summary": "XLK over past 60 days: cumulative return -5.3%, annualized vol 36.7%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=70.41, end=66.69, cumulative_return=-5.3%, annualized_volatility=36.7%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.913, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.21, 't10y3m_spread': 0.53, 'breakeven_10y': 2.38, 'hy_oas': 4.9, 'ig_oas': 1.52, 'ted_spread': 0.09, 'mortgage_30y': 5.51, 'vix': 23.8799991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-20] [\"US STOCKS-Nasdaq rises on positive earnings signals as inflation concerns loom By Echo Wang July 20 (Reuters) - The tech-heavy Nasdaq climbed over 1% on Wednesday as investors digest the latest earnings as positive signals of the economy, albeit rising concerns on inflation and a tightening Fed. The S&P 500 edged up 0.39% while the Dow Jones Industrial Average slipped 0.12%. Netflix Inc's NFLX.O shares jumped 6% after the company predicted it would return to customer growth during the third quarter, while posting a smaller-than-expected 1 million drop in subscribers in the second quarter. Other high-growth stocks extended gains following the forecast from the streaming service provider. Shares of Apple Inc AAPL.O, Amazon.com Inc AMZN.O, Microsoft Corp MSFT.O and Meta Platforms Inc META.O added between 1% and 3.6%. The S&P 500 technology sector index .SPLRCT rose 1.3%. \\u201cInflation remains a very strong consideration on investors\\u2019 minds\\u2026 what we are seeing today are some positive earnings announcements allowing investors to hang their hats on some positive news that should bode better for the remainder of Q3, and 2022,\\u201d said Greg Bassuk, chief executive at AXS Investments in Port Chester, New York. \\u201cFor Tesla, and Netflix and some of these bellwether companies \\u2026 investors are looking for messaging on the outlook that these companies have on the balance of 2022.\\u201d Electric vehicle maker Tesla Inc TSLA.O added 0.6% ahead of its earnings report after market close. Analysts expect aggregate year-on-year S&P 500 profit to grow 5.9% in this reporting season, down from the 6.8% estimate at the start of the quarter, according to Refinitiv data. Runaway inflation initially led markets to price in a full 100-basis-point hike in interest rates at the Fed's upcoming meeting next week, until some policymakers signaled a 75-basis-point increase. At 1:45 p.m. ET, the Dow Jones Industrial Average .DJI fell 37.45 points, or 0.12%, to 31,789.6, the S&P 500 .SPX gained 15.19 points, or 0.39%, to 3,951.88 and the Nasdaq Composite .IXIC added 145.44 points, or 1.24%, to 11,858.59. Trading remained volatile in thin volumes, with the CBOE Volatility index .VIX last down 24.05 points to its lowest in over a month. \\\"Low volumes accentuate market moves historically and even though we've wiped off $10 or $15 trillion from global equities this year, there's still a lot of excess liquidity. So low volume on excess liquidity can still accentuate moves,\\\" John Lynch, chief investment officer for Comerica Wealth Management, said. Health insurer Elevance Health Inc ELV.N plunged 9% as the largest S&P percentage loser, as the company\\u2019s medical costs failed to decrease in line with rival UnitedHealth Group Inc. Baker Hughes Co BKR.O tumbled 7.8% as the oilfield services provider reported a bigger second-quarter loss, while its adjusted profit also missed estimates. Advancing issues outnumbered declining ones on the NYSE by a 1.55-to-1 ratio; \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": 0.064468, "explanation": "The actual 21-day forward return for XLK starting 2022-07-21 was +6.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.064468, "horizon_days": 21, "hist_return": -0.052768, "annualized_vol": 0.367183, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20221020_0422", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2022-10-20", "context_summary": "FXI over past 60 days: cumulative return -25.6%, annualized vol 28.3%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=28.94, end=21.52, cumulative_return=-25.6%, annualized_volatility=28.3%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 298.007, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.41, 't10y3m_spread': 0.07, 'breakeven_10y': 2.42, 'hy_oas': 4.97, 'ig_oas': 1.7, 'ted_spread': 0.09, 'mortgage_30y': 6.92, 'vix': 30.76000022888184}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-19] [\"US STOCKS-Wall St struggles to gain as soaring Treasury yields hurt earnings confidence For a Reuters live blog on U.S., UK and European stock markets, click LIVE/ or type LIVE/ in a news window. U.S. 10-year Treasury yield at highest since July 2008 Netflix jumps after reversing customer losses Tesla third quarter earnings awaited Procter & Gamble up on Q1 revenue, profit beat Indexes: Dow up 0.21%, S&P down 0.10%, Nasdaq down 0.10% Updates prices to open By Ankika Biswas and Shreyashi Sanyal Oct 19 (Reuters) - Wall Street's main indexes struggled for direction on Wednesday as a surge in Treasury yields to 14-year highs on expectations of bigger interest rate hikes dampened budding optimism from a bright start to the earnings season. The yield on the benchmark 10-year Treasury note US10YT=RRclimbed to its highest levels since July 2008 in a steep selloff in U.S. government bonds, with a weak U.S. housing report failing to deter investors from selling bonds. Housing starts, a measure of new residential constructions, dropped 8.1% in September in the latest sign of the economy losing steam, taking a hit from the Federal Reserve aggressive monetary policy tightening. The PHLX Housing Index .HGX fell 3.4%, adding more pain to stock markets attempting to break out of months of declines, with the three main indexes remaining deep in bear market territory. While some gauges of the equity market's health showed that the latest rally may be the start of a sustained move higher, many investors are awaiting signs of cooling inflation, which is way above the Federal Reserve's target. The U.S. central bank is likely to raise rates by 75-basis points for the fourth straight time this year in November. \\\"We probably just saw a bear market bounce and it is going to be in this kind of environment where the market's going to face volatility until the Fed feels comfortable enough to slow their pace of rate hikes,\\\" said Robert Pavlik, senior portfolio manager at Dakota Wealth in Fairfield, Connecticut. \\\"That probably won't be coming until we start to see some weakness in the labor market, which is helping fuel inflation pressures.\\\" Analysts have cut their third-quarter profit growth expectations for S&P 500 companies to just 2.8%, from an 11.1% increase forecast at the start of July, according to Refinitiv data. At 10:41 a.m. ET the Dow Jones Industrial Average .DJI was up 63.29 points, or 0.21%, at 30,587.09, the S&P 500 .SPX was down 3.85 points, or 0.10%, at 3,716.13 and the Nasdaq Composite .IXIC was down 11.31 points, or 0.10%, at 10,761.10. Netflix NFLX.O jumped 14.8% after it attracted 2.4 million new subscribers worldwide in the third quarter, more than double the consensus forecast, and guided for 4.5 million additions by year end. Dow components Procter & Gamble CoPG.N and Travelers Companies IncTRV.N rose 3.4% and 2.6%, respectively, after the companies posted better-than expected quarterly profit. Growth stocks including Amazon.com AMZN.O, Microsof\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": 0.097602, "explanation": "The actual 21-day forward return for FXI starting 2022-10-20 was +9.76%, which classifies as 'positive'.", "metadata": {"future_return": 0.097602, "horizon_days": 21, "hist_return": -0.256209, "annualized_vol": 0.283331, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210810_0425", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2021-08-10", "context_summary": "XLF over past 60 days: cumulative return +0.6%, annualized vol 19.1%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=34.72, end=34.93, cumulative_return=+0.6%, annualized_volatility=19.1%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 272.676, 'unemployment': 5.1, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.1, 't10y3m_spread': 1.27, 'breakeven_10y': 2.37, 'hy_oas': 3.34, 'ig_oas': 0.93, 'ted_spread': 0.07, 'mortgage_30y': 2.77, 'vix': 16.719999313354492}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-08-09] [\"QUAL, BLK, TGT, ADBE: Large Inflows Detected at ETF Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel, one standout is the iShares MSCI USA Quality Factor ETF (Symbol: QUAL) where we have detected an approximate $194.4 million dollar inflow -- that's a 0.8% increase week over week in outstanding units (from 174,250,000 to 175,650,000). Among the largest underlying components of QUAL, in trading today Blackrock Inc (Symbol: BLK) is trading flat, Target Corp (Symbol: TGT) is up about 0.2%, and Adobe Inc (Symbol: ADBE) is lower by about 0.2%. For a complete list of holdings, visit the QUAL Holdings page \\u00bb The chart below shows the one year price performance of QUAL, versus its 200 day moving average: Looking at the chart above, QUAL's low point in its 52 week range is $99.1678 per share, with $139.05 as the 52 week high point \\u2014 that compares with a last trade of $138.72. 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 The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"What Is The Likelihood Of A Rise In Adobe's Stock? Adobe\\u2019s stock (NASDAQ: ADBE) rose by 4.8% to $626 in the last twenty-one trading days. In comparison, the broader S&P500 rose by 1.7% over the last twenty-one trading days. The shift toward Digitization and cloud offerings due to the pandemic has continued to be beneficial to the company as they reported a 23% y-o-y in increase in revenue for Q2. For Q2 2021, Digital Media segment revenue was $2.79 billion (up by 25% y-o-y), Creative revenue was $2.32 billion (up 24% y-o-y), and Document Cloud revenue was $469 million (up 30% y-o-y). Now, is ADBE stock poised to grow? Based on our machine learning analysis of trends in the stock price over the last ten years, there is a 64% chance of a near term rise in ADBE stock over the next month (twenty-one trading days). See our analysis on Adobe\\u2019s Stock Chances Of Rise for more details. Five Days: ADBE 0.8%, vs. S&P500 0.03%; Outperformed market (47% event pro\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": -0.013034, "explanation": "The actual 21-day forward return for XLF starting 2021-08-10 was -1.30%, which classifies as 'negative'.", "metadata": {"future_return": -0.013034, "horizon_days": 21, "hist_return": 0.006081, "annualized_vol": 0.19079, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200612_0428", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2020-06-12", "context_summary": "QUAL over past 60 days: cumulative return +24.0%, annualized vol 30.7%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=70.15, end=87.00, cumulative_return=+24.0%, annualized_volatility=30.7%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 257.042, 'unemployment': 11.0, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.47, 't10y3m_spread': 0.49, 'breakeven_10y': 1.21, 'hy_oas': 6.4, 'ig_oas': 1.7, 'ted_spread': 0.14, 'mortgage_30y': 3.21, 'vix': 40.790000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-11] [\"Can the all-new Cadillac CT5 take on its European competitors? Review: It\\u2019s meant to compete with European big boys like the BMW 3 Series and the Audi A4 The 2020 Cadillac CT5 review: The price is well below its in-segment competitors, but it doesn\\u2019t raise the bar.\", \"American muscle: We compare a Chevy Camaro to Dodge Challenger Take a look at the differences and similarities between the Challenger and the Camaro and see which one is right for you Dare to compare: The Challenger and Camaro are direct competitors in American muscle cars.\", \"Apple stock gets an upgrade at HSBC on services optimism Apple Inc. has a big opportunity to leverage its installed base of devices to drive services growth, HSBC analyst Nicolas Cote-Colisson wrote in a Wednesday note to clients. He upgraded Apple's stock to hold from sell in the report, writing that while he still has macroeconomic concerns about the company's overall business, there's also potential for the company to \\\"sustain innovation\\\" that could drive further momentum for its services segment, particularly around health care. \\\"The pandemic will, in our view, create more demand for health-related tools and Apple could play a large role in addressing that demand,\\\" Cote-Colisson wrote. Health represents \\\"the first or second largest sector in the economy\\\" depending on countries, he said, though Apple could face challenges getting regulatory clearance to collect health data. Cote-Colisson raised his price target on Apple to $295 from $225 in the report. Wells Fargo's Aaron Rakers took a more upbeat view, boosting his target to $385 from $315 in a Thursday note. \\\" Despite the strong [year-to-date] outperformance we have seen in shares of Apple...we continue to believe investors will view this as a favored high-quality large cap name given continued evidence of a post-COVID recovery in smartphone demand, coupled with an expectation of a positive 5G cycle materializing into late-2020/2021,\\\" Rakers wrote, even if that cycle is delayed by a month or two due to the pandemic. Apple shares are down 1.5% in premarket trading Thursday, though they've gained 12% over the past month as the Dow Jones Industrial Average has added 11%.\", \"Apple stock price target raised to $390 from $340 at BofA Securities\", \"As Apple Stock Hits Record Prices, Analysts See Higher Highs Ahead Three more Wall Street pundits turned incrementally more positive on the prospects for the company, which yesterday crossed the $1.5 trillion market capitalization level for the first time ever.\", \"Picking Winners and Losers as Video Streaming and Cord-Cutting Grow Consumers have finally hit a ceiling on how much money they\\u2019re willing to spend on video content\\u2014and the market is headed for a period of deep disruption that will only exaggerate recent trends in cord-cutting and subscription services.\", \"Apple to devote $100 Million to racial-justice initiative \\u2018Things must change\\u2019 Apple Chief Executive Tim Cook said\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": 0.028502, "explanation": "The actual 21-day forward return for QUAL starting 2020-06-12 was +2.85%, which classifies as 'positive'.", "metadata": {"future_return": 0.028502, "horizon_days": 21, "hist_return": 0.240229, "annualized_vol": 0.30651, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190809_0433", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2019-08-09", "context_summary": "VEA over past 60 days: cumulative return -0.0%, annualized vol 11.1%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=32.82, end=32.81, cumulative_return=-0.0%, annualized_volatility=11.1%\nMacro context: {'fed_funds_rate': 2.12, 'cpi_yoy': 256.036, 'unemployment': 3.6, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.1, 't10y3m_spread': -0.3, 'breakeven_10y': 1.65, 'hy_oas': 4.31, 'ig_oas': 1.26, 'ted_spread': 0.2, 'mortgage_30y': 3.6, 'vix': 16.90999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-08-08] 4 Safe Stocks to Buy Amid Trade War Turbulence The U.S.-China trade war is on and that makes finding good, safe stocks to buy much more difficult than before. Over the past few months there was a semantics debate over what exactly the trade tensions between the U.S. and China should be labeled as. Is it a full blown trade war? Or is it just a trade dispute, or trade skirmish? Today, that question seems fully answered. U.S. President Donald Trump upped the ante in early August by promising to introduce a 10% tariff on $300 billion worth of Chinese goods by September. China responded in force, suspending the purchase of new U.S. agricultural products and devaluing its own currency to decade lows against the U.S. Dollar. As such, there\u2019s no question about it. With both sides upping the ante to much more serious levels than before, the U.S.-China trade war is fully here. Stocks dropped in response. Big time. In just a few trading days, the S&P 500 dropped more than 5%. As of this writing, it looks likely that the market\u2019s decline will run into 10%-plus territory within the next few trading days. Thus, in a matter of a few trading days, stocks have gone from making new all-time highs, to being in correction territory. That is the definition of volatility. And when volatility comes roaring back into markets, investors flock to safety. Common financial safe havens included Treasuries (which have been rally in mode) and gold (which just made a six year high). Another financial safe haven is the class of high quality, high moat, big that won\u2019t be hit hard by this trade war drama. As such, I fully expect those \u201csafe stocks\u201d to out-perform so long as trade war drama hangs around. Which stocks fall into the safety stocks category? Let\u2019s take a closer look at four safe stocks to buy amid the recent trade war turbulence. Safe Stocks to Buy Amid Trade Turbulence: AT&T (T) Source: Shutterstock The first safety stock on this list is a telecom giant with a big yield, stable operations, minimal trade war exposure and huge forthcoming catalysts on the horizon. AT&T (NYSE:) is one of America\u2019s largest telecom companies. As a U.S. telecom giant, AT&T\u2019s operations won\u2019t be disrupted by a trade war. Consumers will still need internet service and mobile coverage, and will be willing to pay up for it so long as labor conditions remain favorable (which they do). Furthermore, T stock has a 6% yield which: 1) is pretty much higher than every other blue-chip yield in the market, and 2) looks really attractive next to a 10-Year Treasury yield that is below 2%. Also of note, AT&T has huge catalysts on the horizon that could breathe life back into this sluggish stock. First, AT&T is set to launch HBO Max soon, and this streaming service has enough content firepower from the Time Warner acquisition to make noise in the streaming landscape. If so, AT&T could pivot its negative cord-cutting narrative, into a positive streaming sub growth narrative. That will put upward pressure on \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": 0.027318, "explanation": "The actual 21-day forward return for VEA starting 2019-08-09 was +2.73%, which classifies as 'positive'.", "metadata": {"future_return": 0.027318, "horizon_days": 21, "hist_return": -0.000309, "annualized_vol": 0.110954, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200625_0436", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2020-06-25", "context_summary": "XLI over past 60 days: cumulative return +13.4%, annualized vol 32.1%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=53.84, end=61.08, cumulative_return=+13.4%, annualized_volatility=32.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 257.042, 'unemployment': 11.0, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.5, 't10y3m_spread': 0.54, 'breakeven_10y': 1.33, 'hy_oas': 6.23, 'ig_oas': 1.6, 'ted_spread': 0.13, 'mortgage_30y': 3.13, 'vix': 33.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-24] [\"European stocks in the red as investors fret about rising U.S. Covid-19 infections Cluster of M&A news and weakness by drug groups marks trading European stocks traded lower on Wednesday, as markets struggled to gain traction against a backdrop of rising coronavirus cases in the U.S. Technology stocks were a bright spot after another record session for the Nasdaq Composite\", \"Apple's stock slips 0.7% premarket, after rallying 4.8% the past 2 days to Tuesday's record close\", \"Apple Chip Supplier Upgrades Outlook on Lockdown Demand Apple chip supplier Dialog Semiconductor raised its revenue outlook on Wednesday, citing strong demand for tablets and wearable products\", \"Barron\\u2019s Daily: Even the Nasdaq Is Falling as Covid Spike Spurs Demand for Stay-at-Home Stocks A new stimulus bill could pass in July, Covid-19 testing will increase in the U.S., tech stocks reach new highs, and other news to start your day.\", \"Apple stock falls after report says Justice Department looking at App Store investigation Apple Inc. could face heightened antitrust scrutiny in the U.S. as the Department of Justice and state attorneys general are looking at an investigation that would focus on the company's App Store, according to a Politico report. European regulators also have investigations underway that look into Apple's App Store and Apple Pay practices. Apple takes a cut of revenue when users make in-app purchases of digital services through third-party apps, which some developers have criticized as anticompetitive and arbitrary. The European investigation of Apple Pay will examine Apple's control over the NFC reader on iPhones, which enables contactless payments. The company has restricted the way third parties can tap into this technology. Apple shares are off 0.6% in premarket trading Wednesday. The stock has gained 48% over the past three months as the Dow Jones Industrial Average has risen 26%.\", \"Facebook, Microsoft, Zoom, More Software Stocks Get a Lift Goldman Sachs technology analyst Heather Bellini does a deep dive on valuation for the stocks she covers, in the process lifting her targets for a slew of familiar software names.\", \"Apple acquires security company Fleetsmith Apple Inc. has acquired security company Fleetsmith, according to a blog post on the Fleetsmith website. Fleetsmith helps with device setup and security patching for Apple devices including Macs and iPhones that are used in enterprise settings. The company's tools help businesses automatically set up Apple devices for new employees and manage fleet-wide issues in a single place. \\\"Our shared values of putting the customer at the center of everything we do without sacrificing privacy and security, means we can truly meet our mission, delivering Fleetsmith to businesses and institutions of all sizes, around the world,\\\" Fleetsmith said of the Apple deal. Apple didn't immediately respond to a MarketWatch request for comment. Terms of the deal weren't disclosed in the Fleetsmith post. App\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": 0.066033, "explanation": "The actual 21-day forward return for XLI starting 2020-06-25 was +6.60%, which classifies as 'positive'.", "metadata": {"future_return": 0.066033, "horizon_days": 21, "hist_return": 0.134484, "annualized_vol": 0.321315, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20221116_0439", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2022-11-16", "context_summary": "ACWI over past 60 days: cumulative return -1.6%, annualized vol 23.4%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=83.79, end=82.46, cumulative_return=-1.6%, annualized_volatility=23.4%\nMacro context: {'fed_funds_rate': 3.83, 'cpi_yoy': 298.786, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.57, 't10y3m_spread': -0.51, 'breakeven_10y': 2.35, 'hy_oas': 4.64, 'ig_oas': 1.48, 'ted_spread': 0.09, 'mortgage_30y': 7.08, 'vix': 24.540000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-15] [\"US STOCKS-Wall Street jumps on growing evidence of easing inflation By Amruta Khandekar and Ankika Biswas Nov 15 (Reuters) - Wall Street's main indexes jumped on Tuesday as growing evidence of cooling inflation bolstered hopes of smaller rate hikes by the Federal Reserve, while Walmart's upbeat forecast powered gains in retail sector. Data showed U.S. producer prices increased less than expected, rising 8% in the 12 months through October against an estimated 8.3% rise, according to a Reuters poll of economists. The report follows a softer-than-expected consumer prices reading late last week, which sparked a massive rally on hopes that the Fed would tone down its aggressive monetary policy approach that has roiled markets this year. Following the latest data, traders' bets of a 50-basis points rate hike in December surged to 91% compared with 71.5% last week. FEDWATCH \\\"Going into the final months of the year, this (the inflation data) gives the Fed a chance to go from at least 75 to 50 basis points and potentially even further,\\\" said Phil Blancato, chief executive of Ladenburg Thalmann Asset Management in New York. Shares of Walmart Inc WMT.N jumped 7% after the top U.S. retailer lifted its annual sales and profit forecasts, benefiting from a steady demand for groceries despite higher prices. Its results boosted stocks of other major retailers, including Target Corp TGT.N and Costco COST.O. Target will report results on Wednesday. Home Depot Inc HD.Nleft its annual forecasts unchanged, but the home improvement chain's results exceeded Wall Street expectations and shares rose 1.6% amid a jump in shares of retailers. Among the S&P 500 sectors, consumer staples was up .SPLRCS 1.2%, while the consumer discretionary .SPLRCD index jumped 1.9%. Boosting the Nasdaq .IXIC, shares of megacap technology and other growth stocks such as Apple AAPL.O, Microsoft Corp MSFT.O and Alphabet GOOGL.O rose between 1% and 3%. Focus was also on comments from policymakers, after Fed Vice Chair Lael Brainard and Governor Christoper Waller in recent days emphasized on the need to keep raising rates to rein in inflation. Atlanta President Raphael Bostic echoed the views, saying he sees little evidence that the central bank's aggressive monetary policy tightening is slowing inflation. At 12:41 a.m. ET, the Dow Jones Industrial Average .DJI was up 164.48 points, or 0.49%, at 33,701.18, the S&P 500 .SPX was up 51.46 points, or 1.30%, at 4,008.71, and the Nasdaq Composite .IXIC was up 253.48 points, or 2.26%, at 11,449.70. U.S.-listed shares of Chinese firms including JD.Com JD.O, Alibaba Group Holding BABA.N rose between 7% and 12% after President Joe Biden and Chinese leader Xi Jinping's meeting on Monday where they pledged more frequent communications. U.S.-listed shares of Taiwan Semiconductor Manufacturing TSM.N jumped 12.2% after Warren Buffett's Berkshire Hathaway BRKa.Nbought more than $4.1 billion of stock in the company. Advancing issues outnumbered decliners by a\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": -0.016136, "explanation": "The actual 21-day forward return for ACWI starting 2022-11-16 was -1.61%, which classifies as 'negative'.", "metadata": {"future_return": -0.016136, "horizon_days": 21, "hist_return": -0.015834, "annualized_vol": 0.234319, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210217_0442", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2021-02-17", "context_summary": "BIL over past 60 days: cumulative return +0.0%, annualized vol 0.1%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=77.79, end=77.79, cumulative_return=+0.0%, annualized_volatility=0.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 263.579, 'unemployment': 6.2, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.17, 't10y3m_spread': 1.26, 'breakeven_10y': 2.24, 'hy_oas': 3.41, 'ig_oas': 0.95, 'ted_spread': 0.15, 'mortgage_30y': 2.73, 'vix': 21.459999084472656}\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": -0.000219, "explanation": "The actual 21-day forward return for BIL starting 2021-02-17 was -0.02%, which classifies as 'flat'.", "metadata": {"future_return": -0.000219, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.001298, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200128_0445", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-01-28", "context_summary": "LINK-USD over past 60 days: cumulative return +11.4%, annualized vol 66.7%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=2.34, end=2.61, cumulative_return=+11.4%, annualized_volatility=66.7%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 259.127, 'unemployment': 3.6, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.17, 't10y3m_spread': 0.06, 'breakeven_10y': 1.63, 'hy_oas': 4.03, 'ig_oas': 1.04, 'ted_spread': 0.25, 'mortgage_30y': 3.6, 'vix': 18.229999542236328}\nMarket regime: sideways\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": 0.711193, "explanation": "The actual 21-day forward return for LINK-USD starting 2020-01-28 was +71.12%, which classifies as 'positive'.", "metadata": {"future_return": 0.711193, "horizon_days": 21, "hist_return": 0.113989, "annualized_vol": 0.66684, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220809_0448", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2022-08-09", "context_summary": "TLH over past 60 days: cumulative return +1.2%, annualized vol 15.8%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=105.32, end=106.57, cumulative_return=+1.2%, annualized_volatility=15.8%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 295.097, 'unemployment': 3.6, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.44, 't10y3m_spread': 0.12, 'breakeven_10y': 2.48, 'hy_oas': 4.41, 'ig_oas': 1.49, 'ted_spread': 0.09, 'mortgage_30y': 4.99, 'vix': 21.290000915527344}\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": -0.058006, "explanation": "The actual 21-day forward return for TLH starting 2022-08-09 was -5.80%, which classifies as 'negative'.", "metadata": {"future_return": -0.058006, "horizon_days": 21, "hist_return": 0.011865, "annualized_vol": 0.158026, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20170120_0453", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2017-01-20", "context_summary": "HYG over past 60 days: cumulative return +1.6%, annualized vol 7.3%. Market regime: sideways.", "question": "Asset: HYG\nHistorical prices (past 60 trading days): start=52.55, end=53.40, cumulative_return=+1.6%, annualized_volatility=7.3%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 243.618, 'unemployment': 4.7, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.22, 't10y3m_spread': 1.95, 'breakeven_10y': 2.04, 'hy_oas': 3.99, 'ig_oas': 1.28, 'ted_spread': 0.53, 'mortgage_30y': 4.09, 'vix': 12.779999732971191}\nMarket regime: sideways\n\nPredict whether the return of HYG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.010959, "explanation": "The actual 21-day forward return for HYG starting 2017-01-20 was +1.10%, which classifies as 'positive'.", "metadata": {"future_return": 0.010959, "horizon_days": 21, "hist_return": 0.016195, "annualized_vol": 0.073332, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191231_0460", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SLV"], "decision_date": "2019-12-31", "context_summary": "SLV over past 60 days: cumulative return +0.8%, annualized vol 16.5%. Market regime: sideways.", "question": "Asset: SLV\nHistorical prices (past 60 trading days): start=16.61, end=16.74, cumulative_return=+0.8%, annualized_volatility=16.5%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 258.63, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.32, 't10y3m_spread': 0.33, 'breakeven_10y': 1.75, 'hy_oas': 3.6, 'ig_oas': 1.0, 'ted_spread': 0.37, 'mortgage_30y': 3.74, 'vix': 14.81999969482422}\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": -0.016187, "explanation": "The actual 21-day forward return for SLV starting 2019-12-31 was -1.62%, which classifies as 'negative'.", "metadata": {"future_return": -0.016187, "horizon_days": 21, "hist_return": 0.007827, "annualized_vol": 0.164778, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200521_0465", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2020-05-21", "context_summary": "EMB over past 60 days: cumulative return -6.1%, annualized vol 17.0%. Market regime: sideways.", "question": "Asset: EMB\nHistorical prices (past 60 trading days): start=85.32, end=80.08, cumulative_return=-6.1%, annualized_volatility=17.0%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 255.802, 'unemployment': 13.2, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.52, 't10y3m_spread': 0.56, 'breakeven_10y': 1.16, 'hy_oas': 7.16, 'ig_oas': 2.01, 'ted_spread': 0.24, 'mortgage_30y': 3.28, 'vix': 27.989999771118164}\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": 0.026934, "explanation": "The actual 21-day forward return for EMB starting 2020-05-21 was +2.69%, which classifies as 'positive'.", "metadata": {"future_return": 0.026934, "horizon_days": 21, "hist_return": -0.06138, "annualized_vol": 0.170051, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160729_0468", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-07-29", "context_summary": "QQQ over past 60 days: cumulative return +9.7%, annualized vol 15.4%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=97.87, end=107.41, cumulative_return=+9.7%, annualized_volatility=15.4%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 240.101, 'unemployment': 4.8, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.8, 't10y3m_spread': 1.27, 'breakeven_10y': 1.52, 'hy_oas': 5.54, 'ig_oas': 1.49, 'ted_spread': 0.51, 'mortgage_30y': 3.48, 'vix': 12.720000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-07-28] [\"3M Stock Seen Edging Up to $186 Second-quarter margins expanded by about 50 basis points year-over-year, and should accelerate through the second half.\", \"An Aerospace Parts Maker That Can Fly 35% Higher Shares of airplane power systems supplier Astronics have lost altitude but could rise significantly.\", \"Cirrus Logic Surges 13%: Ride That iPhone Headset Plug! Shares of chip maker Cirrus Logic (CRUS), a prominent supplier to Apple (AAPL), are up $5.24, or 13%, at $47.01, after last night easily topping fiscal Q1 expectations and forecasting this quarter\\u2019s revenue well ahead of consensus as well.And, indeed, a big part of last night\\u2019s conference call with analysts was the company indirectly confirming a \\u201cdigital\\u201d jack for headsets for the next iPhone, presumably an \\\"iPhone 7,\\u201d which many think will appear in September. All that headphone capability now in a USB or \\u201clightning\\u201d port, believe analysts, translates directly into higher revenue for Cirrus for each phone sold.The company\\u2019s CEO, Jason Rhode, was asked by Needham & Co.\\u2019s Rajvindra Gill what he sees as the general increase in using \\u201cdigital,\\u201d or \\u201cUSB\\u201d ports for headphones. Said Rhode:Well, like I referred to earlier, we are excited to see there's already models on the market that have switched over to USBC completely, and either ship with -- either ship with or have available accessory USBC headsets or adapters, one or the other, or both. The interesting thing is that as the core chipsets stand today, that's quite a painful thing to do, just the way the USBC stack is handled and routing of audio and uses of voice interface is kind of clumsy in the handsets themselves. So, we see that getting sorted out over the next 6 to 12 months in a way that makes it significantly easier for handset manufacturers to go that route, and so we would anticipate that would gain a lot of momentum over that timeframe. And, like I say, I think we're extremely well-positioned to capitalize on that.\", \"MasterCard profit, revenue beat expectations MasterCard Inc. said profit and revenue grew in the second quarter as transactions increased at the credit card company. Results topped expectations, and shares climbed 1.8% premarket. Like fellow card company Visa Inc., MasterCard charges fees to financial institutions for transactions that travel over their networks.\", \"Smartphone market stagnant for second straight quarter The global smartphone market struggled to grow in the second quarter. Vendors shipped 343.3 million smartphones, a 0.3% increase from 342.4 million in the year-earlier period, according to IDC. That was the second straight quarter of stagnant volumes. Samsung Electronics maintained its lead in the market, nabbing a 22.4% global share, versus 21.3% last year. Apple Inc.'s share declined slightly, to 11.8% from 13.9%, while smaller Asian vendors such as Huawei, OPPO and Vivo continued to steal a larger part of the pie. Anthony Scarsel\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": 0.01484, "explanation": "The actual 21-day forward return for QQQ starting 2016-07-29 was +1.48%, which classifies as 'positive'.", "metadata": {"future_return": 0.01484, "horizon_days": 21, "hist_return": 0.097442, "annualized_vol": 0.153806, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190111_0471", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2019-01-11", "context_summary": "XLU over past 60 days: cumulative return +1.3%, annualized vol 17.4%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=21.05, end=21.32, cumulative_return=+1.3%, annualized_volatility=17.4%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 252.561, 'unemployment': 4.0, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.18, 't10y3m_spread': 0.31, 'breakeven_10y': 1.81, 'hy_oas': 4.54, 'ig_oas': 1.55, 'ted_spread': 0.42, 'mortgage_30y': 4.45, 'vix': 19.5}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-10] [\"Apple's stock slips 0.7% premarket, after rising 3.6% the past 2 sessions\", \"The stock market is too damaged for a sustained rally, strategist warns Morgan Stanley\\u2019s Wilson: Too much resistance in stock market for a \\u2018straight up\\u2019 recovery The stock market is in the midst of its longest winning streak in months but at least one Wall Street strategist is not convinced that investors are out of the woods yet.\", \"Q&A with Cody Willard: Apple, Disney, Adobe and small-cap stocks Stocks are vulnerable to another leg down Stocks are vulnerable to another leg down.\", \"Many retail investors panicked and sold during last month\\u2019s market meltdown (again) Yes, Main Street missed the latest rally, fund industry analyst says Yes, Main Street missed the latest rally, fund industry analyst says.\", \"Cisco Sees Its Chance as Internet Traffic Builds Cisco Systems used the Consumer Electronics Show as a place to tout its high-speed networks and security tools, products that will be more critical as the volume of data on the internet grows, and the flow speeds up.\", \"Elon Musk Goes to China at a Vital Time for Tesla and for the U.S. The backdrop of Musk\\u2019s visit was hard not to notice: The U.S. and China this week wrapped up the latest round of talks that investors hope will stabilize trade relations.\", \"The sharpest investors use this simple tool to pick stocks Valuing a public company like a private business gives a more realistic picture of its potential Valuing a public company like a private business gives a more realistic picture of its potential, writes Vitaliy Katsenelson.\", \"Roaring U.S. jobs market, waning inflation give Fed room to pause on interest rates Consumer price index likely softened again at end of 2018 A gargantuan surge in new jobs in December, a recent lull in inflation and a more cautious Federal Reserve have dispelled fears that the U.S. faces a looming recession.\", \"High-end cars and other luxury goods join Apple in feeling effect of China\\u2019s slowdown Jaguar Land Rover cites China demand as it cuts 4,500 jobs in the U.K. Automobile makers join luxury-goods companies in seeing demand dented as China\\u2019s economy slows and Chinese consumers\\u2019 mood takes a turn for the worse.\", \"Lenovo overtakes HP in PC sales as market contracts Overall worldwide PC sales declined for both the fourth quarter and year in 2018, while Lenovo Group Ltd. and Dell Technologies Inc.'s share of the market grew, according to research firm Gartner on Thursday. Global PC sales fell 4.3% to 68.6 million units in the fourth quarter, and 1.3% to 259.4 million in 2018, Gartner said. \\\"Just when demand in the PC market started seeing positive results, a shortage of CPUs (central processing units) created supply chain issues,\\\" said Mikako Kitagawa, senior principal analyst at Gartner, in a statement. \\\"After two quarters of growth in 2Q18 and 3Q18, PC shipments declined in the fourth quarter.\\\" Market share for Lenovo and Dell grew, however. \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": 0.045651, "explanation": "The actual 21-day forward return for XLU starting 2019-01-11 was +4.57%, which classifies as 'positive'.", "metadata": {"future_return": 0.045651, "horizon_days": 21, "hist_return": 0.012854, "annualized_vol": 0.174078, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210203_0474", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2021-02-03", "context_summary": "SOL-USD over past 60 days: cumulative return +166.2%, annualized vol 157.8%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=1.98, end=5.27, cumulative_return=+166.2%, annualized_volatility=157.8%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 263.579, 'unemployment': 6.2, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.01, 't10y3m_spread': 1.05, 'breakeven_10y': 2.15, 'hy_oas': 3.75, 'ig_oas': 1.02, 'ted_spread': 0.12, 'mortgage_30y': 2.73, 'vix': 25.559999465942383}\nMarket regime: sideways\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": 2.027071, "explanation": "The actual 21-day forward return for SOL-USD starting 2021-02-03 was +202.71%, which classifies as 'positive'.", "metadata": {"future_return": 2.027071, "horizon_days": 21, "hist_return": 1.662006, "annualized_vol": 1.577825, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210514_0479", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2021-05-14", "context_summary": "EWJ over past 60 days: cumulative return -7.0%, annualized vol 16.3%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=62.83, end=58.46, cumulative_return=-7.0%, annualized_volatility=16.3%\nMacro context: {'fed_funds_rate': 0.06, 'cpi_yoy': 268.383, 'unemployment': 5.8, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.5, 't10y3m_spread': 1.64, 'breakeven_10y': 2.51, 'hy_oas': 3.37, 'ig_oas': 0.93, 'ted_spread': 0.14, 'mortgage_30y': 2.94, 'vix': 23.1299991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-05-13] Can DocuSign Fend Off Adobe's E-Signature Product? There's plenty of competition for DocuSign's (NASDAQ: DOCU) flagship e-signature product, but the digital agreement software continues to lead in the market. On a Fool Live episode recorded on April 28, Fool contributors Brian Feroldi and Brian Withers discuss the e-signature specialist's biggest competitor and how investors should think about this rivalry. 10 stocks we like better than DocuSign When investing geniuses David and Tom Gardner have 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.* David and Tom just revealed what they believe are the ten best stocks for investors to buy right now... and DocuSign 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 February 24, 2021 Brian Feroldi: I do see a question here that I do want to take. It's from MS Regular saying, \"Is there any competitor for DocuSign?\" Yes. There's a lot of competitors for DocuSign. The number one competitor is a little company called Adobe. Adobe is not a company that should be overlooked because they have deep relationships, and they have a growing marketing and sales business that is focused on business services and it is winning. Their e-signature solution is part of their product. But look at the results, what are the results clearly say? Clearly, there's plenty of customers that are choosing DocuSign, and DocuSign is the top dog, and first mover in this space. Moreover, DocuSign has hundreds upon hundreds of integrations directly with some of the leading products that are out there. DocuSign works directly with Microsoft's products, with salesforce.com, etc. Don't overlook that as a competitive advantage. Finally, I always think about what is the value of this thing compared to the costs to a company. The productivity gains that you get from using an e-signature solution are just so massive compared to the costs of it. I don't think once you adopt DocuSign that you're going to be going away from it. Competition is something to watch, but DocuSign is basically a verb at this point and they have clearly done a great job about staying the lead husky. Brian Withers: Yeah. I wanted to tag onto that, Brian. DocuSign has got like 70 percent-plus market share, Adobe is in the single digits. But do you have to remember and I think you stated it well, is people don't necessarily go to Adobe to buy the e-signature product they go to buy more of a holistic solution. Recently there was an announcement that I saw that \"Adobe partners with all 50 states to modernize digital experience for citizens\", and really if you read through the documentation what they're doing is they're putting together websites and experiences for customers and some small part of that is a signature process. Maybe they're building online forms for people, or questionnaires to allow the\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.035185, "explanation": "The actual 21-day forward return for EWJ starting 2021-05-14 was +3.52%, which classifies as 'positive'.", "metadata": {"future_return": 0.035185, "horizon_days": 21, "hist_return": -0.069535, "annualized_vol": 0.163343, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210216_0482", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2021-02-16", "context_summary": "BTC-USD over past 60 days: cumulative return +107.2%, annualized vol 74.5%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=23137.96, end=47945.06, cumulative_return=+107.2%, annualized_volatility=74.5%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 263.579, 'unemployment': 6.2, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.09, 't10y3m_spread': 1.16, 'breakeven_10y': 2.21, 'hy_oas': 3.47, 'ig_oas': 0.97, 'ted_spread': 0.15, 'mortgage_30y': 2.73, 'vix': 19.96999931335449}\nMarket regime: sideways\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": 0.114314, "explanation": "The actual 21-day forward return for BTC-USD starting 2021-02-16 was +11.43%, which classifies as 'positive'.", "metadata": {"future_return": 0.114314, "horizon_days": 21, "hist_return": 1.072138, "annualized_vol": 0.745064, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181123_0487", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2018-11-23", "context_summary": "BTC-USD over past 60 days: cumulative return -33.8%, annualized vol 43.7%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=6595.41, end=4365.94, cumulative_return=-33.8%, annualized_volatility=43.7%\nMacro context: {'fed_funds_rate': 2.2, 'cpi_yoy': 252.594, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.25, 't10y3m_spread': 0.65, 'breakeven_10y': 1.97, 'hy_oas': 4.25, 'ig_oas': 1.38, 'ted_spread': 0.32, 'mortgage_30y': 4.81, 'vix': 20.799999237060547}\nMarket regime: sideways\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": -0.171917, "explanation": "The actual 21-day forward return for BTC-USD starting 2018-11-23 was -17.19%, which classifies as 'negative'.", "metadata": {"future_return": -0.171917, "horizon_days": 21, "hist_return": -0.338034, "annualized_vol": 0.436981, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220425_0490", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2022-04-25", "context_summary": "BNB-USD over past 60 days: cumulative return +10.5%, annualized vol 46.8%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=361.23, end=399.11, cumulative_return=+10.5%, annualized_volatility=46.8%\nMacro context: {'fed_funds_rate': 0.33, 'cpi_yoy': 288.561, 'unemployment': 3.7, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.18, 't10y3m_spread': 2.07, 'breakeven_10y': 2.86, 'hy_oas': 3.65, 'ig_oas': 1.33, 'ted_spread': 0.09, 'mortgage_30y': 5.11, 'vix': 28.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-24] \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": -0.263732, "explanation": "The actual 21-day forward return for BNB-USD starting 2022-04-25 was -26.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.263732, "horizon_days": 21, "hist_return": 0.104837, "annualized_vol": 0.468232, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20180403_0497", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2018-04-03", "context_summary": "HAUZ over past 60 days: cumulative return -2.5%, annualized vol 15.5%. Market regime: sideways.", "question": "Asset: HAUZ\nHistorical prices (past 60 trading days): start=22.17, end=21.60, cumulative_return=-2.5%, annualized_volatility=15.5%\nMacro context: {'fed_funds_rate': 1.68, 'cpi_yoy': 250.227, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.48, 't10y3m_spread': 0.96, 'breakeven_10y': 2.05, 'hy_oas': 3.77, 'ig_oas': 1.17, 'ted_spread': 0.61, 'mortgage_30y': 4.44, 'vix': 23.6200008392334}\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": "positive", "answer_numeric": 0.030534, "explanation": "The actual 21-day forward return for HAUZ starting 2018-04-03 was +3.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.030534, "horizon_days": 21, "hist_return": -0.025476, "annualized_vol": 0.154805, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160223_0500", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2016-02-23", "context_summary": "IVV over past 60 days: cumulative return -6.4%, annualized vol 19.8%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=176.55, end=165.23, cumulative_return=-6.4%, annualized_volatility=19.8%\nMacro context: {'fed_funds_rate': 0.38, 'cpi_yoy': 237.336, 'unemployment': 4.9, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 0.99, 't10y3m_spread': 1.44, 'breakeven_10y': 1.31, 'hy_oas': 8.09, 'ig_oas': 2.14, 'ted_spread': 0.29, 'mortgage_30y': 3.65, 'vix': 19.3799991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-02-22] [\"China bans foreign publishing content online All online content must be on servers hosted within China China has issued broad new rules for online publishing that formalize the government\\u2019s already strict control of the Internet and seek to expand the scope of online content stored inside its borders.\", \"Samsung\\u2019s Flagship Galaxy S7 Disappoints At the annual Mobile World Congress in Barcelona, whereas LG Electronics (066570.Korea) got good reviews for its new module smartphone G5, Samsung Electronics' (005930.Korea/SSNLF) flagship Galaxy S7 turns out lackluster.Year-to-date, Samsung fell 6.3%, broadly in line with competitor Apple's (AAPL) 8.8% decline.Galaxy S7 offers few new bells and whistles, reviewedThe Wall Street Journal colleagues Jonathan Cheng and Min-Jeong Lee:The high-end Galaxy S7 and its curved-screen companion, the Galaxy S7 Edge, released on the sidelines of the Mobile World Congress trade show Sunday, look strikingly similar to their predecessors and lack fresh features to set them apart in a crowded field of Android handsets.The smartphones come with an improved camera and longer battery life, in addition to two features that had been dropped from the Galaxy S6 last year: removable memory storage and water resistance.Morgan Stanley's Shawn Kim agrees:READ MORE.\", \"FBI boss to Apple backers: \\u2018Stop saying the world is ending\\u2019 James Comey argues agency won\\u2019t \\u2018set a master key loose\\u2019 Protesters worldwide plan to blast the FBI for trying to break into a terror suspect\\u2019s iPhone, and the public looks like it\\u2019s mostly with Apple in this fight. Meanwhile, the FBI\\u2019s director, James Comey, says everyone should essentially chill out.\", \"Samsung\\u2019s Faster Charging without Wires\", \"Looking for bottoms in oil prices and the stock market? Keep looking Critical intelligence before the U.S. market opens The final dispatches of an already-dead earnings season and another batch of Fed blather may sway investors\\u2019 mood in the week ahead. But perhaps even more relevant to the stock market\\u2019s odds of building on last week\\u2019s big push \\u2014 the best of the year so far \\u2014 is oil\\u2019s next move.\", \"Apple holds firm against FBI, calls for expert panel to discuss encryption Tim Cook posts his own Q&A over San Bernardino phone Apple renews its defense for why it has refused to help law enforcement unlock the phone of a shooter in the San Bernardino terror attack and suggests the government form a commission to address the thorny problems posed by the growing use of encryption.\", \"Apple still giving the FBI advice on how to crack San Bernardino shooter\\u2019s phone The tech giant says it\\u2019s done everything within its power to help The tech giant says it\\u2019s done everything within its power to help.\", \"What Apple and the head of the FBI agree on The tech giant and authorities have some common ground The tech giant and authorities have some common ground.\", \"Read the letter Tim C\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": 0.056688, "explanation": "The actual 21-day forward return for IVV starting 2016-02-23 was +5.67%, which classifies as 'positive'.", "metadata": {"future_return": 0.056688, "horizon_days": 21, "hist_return": -0.064116, "annualized_vol": 0.198361, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200206_0503", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2020-02-06", "context_summary": "^VIX over past 60 days: cumulative return +25.5%, annualized vol 113.3%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=12.07, end=15.15, cumulative_return=+25.5%, annualized_volatility=113.3%\nMacro context: {'fed_funds_rate': 1.59, 'cpi_yoy': 259.25, 'unemployment': 3.5, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.22, 't10y3m_spread': 0.09, 'breakeven_10y': 1.66, 'hy_oas': 3.75, 'ig_oas': 1.05, 'ted_spread': 0.2, 'mortgage_30y': 3.51, 'vix': 15.149999618530272}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-02-05] [\"Stocks That Hit 52-Week Highs On Wednesday\", \"Stocks That Hit 52-Week Highs On Wednesday\", \"Adobe Stock Could Head Higher, but Tread Carefully With shares up 31% since Nov. 1, is Adobe (NASDAQ:) stock a buy at the current price level? After December\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s earning beat, the company could see its impressive level of growth continue \\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0094 and push ADBE stock even higher. Source: r.classen / Shutterstock.com Currently sitting at , Adobe shares sell at a rich valuation. In this runaway bull market, that hardly seems to matter. So, with the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s growth story continuing, shares could reach new highs in the near-term. Furthermore, it\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s safe to say that with ADBE stock, you are buying a business with a tremendous economic moat. The company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s software offerings are invaluable assets. Whether we are talking about the unit, Document Cloud unit or , the company plays a heavy role in the new economy. However, is buying Adobe stock today a smart play long term? It may pay to be patient, and wait for a dip to accumulate shares. That said, let\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s dive in, and see why buying later is the best call for ADBE stock. ADBE Stock Has Gotten Ahead of Itself As InvestorPlace\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s Luke Lango discussed Dec. 19, the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s revenue growth justified a price target of . But now, shares trade above that price target and are closer to the $365 level. It\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s tough to say the recent rise of ADBE stock is due to fundamentals. After December\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s earnings beat, much of Adobe\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s future upside was priced into shares. So, what\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s driving the recent run-up? Mr. Market, or specifically, Mr. Broad Market. Major indices are even after the coronavirus panic, so it\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s no mystery why ADBE stock keeps climbing higher. With its de facto monopoly on digital design, Adobe should be christened a Nasdaq Composite blue chip. Given major tech names like Microsoft (NASDAQ:) are ripping to new highs, there\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s no reason to leave out Adobe shares from the fun. However, outside of the broad market, what could send ADBE stock lower? How about the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s projected revenue growth slowdown? As this Seeking Alpha contributor discussed, it\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s hard to justify Adobe\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s high forward price-to-earnings (P/E) ratio when the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s growth rate is expected to drop below the . Once investors get back to using fundamentals \\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0094 not momentum \\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0094 to\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": 1.803476, "explanation": "The actual 21-day forward return for ^VIX starting 2020-02-06 was +180.35%, which classifies as 'positive'.", "metadata": {"future_return": 1.803476, "horizon_days": 21, "hist_return": 0.255178, "annualized_vol": 1.132919, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220810_0508", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2022-08-10", "context_summary": "MTUM over past 60 days: cumulative return +0.1%, annualized vol 23.4%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=135.53, end=135.64, cumulative_return=+0.1%, annualized_volatility=23.4%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 295.097, 'unemployment': 3.6, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.48, 't10y3m_spread': 0.13, 'breakeven_10y': 2.47, 'hy_oas': 4.46, 'ig_oas': 1.5, 'ted_spread': 0.09, 'mortgage_30y': 4.99, 'vix': 21.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-08-09] [\"Down 47% in a Year, Time to Buy This Growth Stock? With a market cap of $8.3 billion, Cognex Corporation (NASDAQ: CGNX) is not a small-cap company. However, it's still a growth company trying to build out the adoption of technology with explosive growth potential. As the leader in machine vision, Cognex's strategic aim is to grow into a served market (estimated as being worth $4.2 billion in 2018) that management sees as growing at a 12% annual rate. The good news from 2022 is Cognex is achieving many of its strategic aims; the bad news is almost everything seems to be working against the company right now. Here's the lowdown. What a growth company needs If you are going to make up an informal list of objectives for a growth company, it will include the following: Win over some highly prominent and visible customers to demonstrate your technology's efficacy, expand revenue, win follow-up business, and sell to lower-tier players as they follow their industry leaders in adopting machine vision. Ensure you satisfy high-profile customers by investing in a high level of service. Continue establishing your technology in new growth markets. As alluded to earlier, Cognex is doing all three things. The company's three major machine vision markets are automotive, consumer electronics, and logistics/e-commerce. The biggest names in two of those three industries are Apple (named as a significant customer in a previous Cognex SEC filing) and Amazon.com (NASDAQ: AMZN). The latter was not named on Cognex's recentearnings call Still, Cognex's last 10-K filing referred to a large customer in the logistics industry that represented approximately 17% of their total revenue. When an analyst refers to \\\"the world's largest e-commerce customer,\\\" it's a reasonable bet that it's Amazon. One clear thing is that Cognex has won some very high-profile customers in the last five years, so you can tick off the first box on the checklist. Servicing customers and establishing new markets The other two boxes can be ticked off as well. Three sources indicate that Cognex is very careful in servicing its customers (an excellent quality in a growing company). First, back in 2014, when Cognex started working on Apple orders (its machine vision solutions help smartphone manufacturers fit screens), management significantly ramped its operating expenses to support the orders. Second, it was the same in 2021, with Cognex incurring an extra cost in providing a \\\"higher level of support on a large deployment by a customer in logistics.\\\" Third, back on the fourth-quarterearnings callin February, CEO Robert Willett disclosed Cognex had \\\"been prioritizing delivery during this time of global chip shortages that added incremental costs in 2021, due to the significant premiums we've paid to procure components through brokers, and for expedited freight.\\\" As for establishing new markets, the logistics market is a relatively new one for Cognex that's grown at a compound annual growth rate 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": "flat", "answer_numeric": 0.005094, "explanation": "The actual 21-day forward return for MTUM starting 2022-08-10 was +0.51%, which classifies as 'flat'.", "metadata": {"future_return": 0.005094, "horizon_days": 21, "hist_return": 0.000787, "annualized_vol": 0.234064, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190521_0510", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2019-05-21", "context_summary": "IWM over past 60 days: cumulative return -3.8%, annualized vol 16.7%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=144.47, end=138.98, cumulative_return=-3.8%, annualized_volatility=16.7%\nMacro context: {'fed_funds_rate': 2.39, 'cpi_yoy': 255.296, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.2, 't10y3m_spread': 0.02, 'breakeven_10y': 1.81, 'hy_oas': 4.06, 'ig_oas': 1.24, 'ted_spread': 0.18, 'mortgage_30y': 4.07, 'vix': 16.309999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-05-20] Credit Suisse Absolutely Is Right to Double Down on Pfizer Stock After upgrading Pfizer (NYSE:) to \u201cOutperform\u201d in January and raising its price target on Pfizer stock to $48 in May, one would think there\u2019s nothing else Credit Suisse could so to bolster its bullish case, but there is. Source: Following a meeting with the pharmaceutical giant\u2019s top brass just a few days ago, on Thursday, \u201ctop pick.\u201d It was apparently one heck of a meeting. The specifics prompting the accolade weren\u2019t made crystal clear, though Credit Suisse did note that the company\u2019s prospects for new products was compelling. Translation: Whatever stoked Credit Suisse\u2019s fires is likely to be in the company\u2019s late-stage pipeline, which is admittedly more exciting than it has been in a long while. A Brief Look at Pfizer It\u2019s not a story that needs a great deal of retelling. It was an unstoppable powerhouse when it had full patent protection of its erectile dysfunction drug Viagra and faced little competition. But, seeing the writing on the wall, the drugmaker allowed Teva Pharmaceutical Industries (NYSE:) to begin selling a generic version of the drug in 2017. In the meantime, consumer interest in ED drugs has broadly waned. Pfizer is about to lose ground with blockbuster neuropathic pain drug Lyrica too, which lost patent protection last year, threatening to once generic alternatives become available. It\u2019s the same story that plays out over and over within the pharmaceutical industry; these organizations must constantly replenish their portfolios with patent-protected drugs, or risk losing ground. It\u2019s something Pfizer hasn\u2019t done especially well in recent years. Although Pfizer stock has made reliable if choppy progress since turning around with all other stocks in 2009, revenue growth hasn\u2019t been overwhelming. The was not remarkable better than the $52.7 billion figure from a year earlier. \u201cPfizer has been working through a dark period with extensive patent expirations,\u201d said in late January. \u201cThat period is now nearing an end.\u201d Solid Pipeline What Pfizer told Credit Suisse at the meeting remains veiled, though when Divan upgraded Pfizer stock early this year he explicitly noted opportunities for several cancer and autoimmune disease drugs along with vaccinations. Two of the drugs Divan had in mind are (though they\u2019re actually different doses of the same molecule), which combats the buildup for amyloid in the heart. Alnylam Pharmaceuticals (NASDAQ:) and Ionis Pharmaceuticals (NASDAQ:) already make similar rival drugs, but their versions are considerably more expensive. Divan foresees peak sales of $2 billion for Vyndaqel, but is willing to entertain a number \u201csignificantly larger than that if Pfizer is able to commercialize it successfully.\u201d Pfizer has also partnered with Eli Lilly (NYSE:) on the development of a non-opioid arthritis treatment called tanezumab, another one of the 15 game-changing drugs Pfizer believes could be brought to the market within the next five years. So\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": 0.013115, "explanation": "The actual 21-day forward return for IWM starting 2019-05-21 was +1.31%, which classifies as 'positive'.", "metadata": {"future_return": 0.013115, "horizon_days": 21, "hist_return": -0.037963, "annualized_vol": 0.167057, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200311_0513", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2020-03-11", "context_summary": "XLRE over past 60 days: cumulative return +1.0%, annualized vol 21.9%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=30.14, end=30.45, cumulative_return=+1.0%, annualized_volatility=21.9%\nMacro context: {'fed_funds_rate': 1.09, 'cpi_yoy': 258.076, 'unemployment': 4.4, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.26, 't10y3m_spread': 0.32, 'breakeven_10y': 1.07, 'hy_oas': 6.38, 'ig_oas': 1.87, 'ted_spread': 0.35, 'mortgage_30y': 3.29, 'vix': 43.34999847412109}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-03-10] [\"123 Biggest Movers From Yesterday\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Morning Market Stats In 5 Minutes\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Morning Market Stats In 5 Minutes\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"123 Biggest Movers From Yesterday\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Morning Market Stats In 5 Minutes\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"123 Biggest Movers From Yesterday\", \"Has the coronavirus selloff created a stock-buying opportunity, or is it too early? Here\\u2019s what analysts and strategists are advising Is it safe to go back into the water after stocks have been rocked by the COVID-19 outbreak?\", \"These 3 EVs are the lowest cost to own over 5 years The 5-Year Cost to Own equation includes insurance, fuel economy, interest rates, and depreciation\\u2014the Nissan Leaf comes out on top The Nissan Leaf takes home KBB\\u2019s Best EV 5-Year Cost to Own Award for the third year in a row.\", \"After markets plunge on fears of OPEC \\u2018price war\\u2019 and coronavirus \\u2014 5 questions to ask your financial adviser right now Advisers say this is a \\u2018great litmus test\\u2019 to evaluate your risk tolerance, but they say retail investors should proceed cautiously Advisers say this is a \\u2018great litmus test\\u2019 to evaluate your risk tolerance, but they say retail investors should proceed ca\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00806, "explanation": "The actual 21-day forward return for XLRE starting 2020-03-11 was +0.81%, which classifies as 'flat'.", "metadata": {"future_return": 0.00806, "horizon_days": 21, "hist_return": 0.010076, "annualized_vol": 0.21889, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190306_0516", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2019-03-06", "context_summary": "DBB over past 60 days: cumulative return +3.2%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=13.53, end=13.96, cumulative_return=+3.2%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 254.277, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.17, 't10y3m_spread': 0.26, 'breakeven_10y': 1.93, 'hy_oas': 3.91, 'ig_oas': 1.27, 'ted_spread': 0.2, 'mortgage_30y': 4.35, 'vix': 14.739999771118164}\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": 0.024699, "explanation": "The actual 21-day forward return for DBB starting 2019-03-06 was +2.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.024699, "horizon_days": 21, "hist_return": 0.031806, "annualized_vol": 0.142804, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190225_0519", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2019-02-25", "context_summary": "HAUZ over past 60 days: cumulative return +8.5%, annualized vol 14.8%. Market regime: sideways.", "question": "Asset: HAUZ\nHistorical prices (past 60 trading days): start=19.55, end=21.21, cumulative_return=+8.5%, annualized_volatility=14.8%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 253.319, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.17, 't10y3m_spread': 0.19, 'breakeven_10y': 1.91, 'hy_oas': 4.05, 'ig_oas': 1.32, 'ted_spread': 0.24, 'mortgage_30y': 4.35, 'vix': 13.510000228881836}\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": "positive", "answer_numeric": 0.032188, "explanation": "The actual 21-day forward return for HAUZ starting 2019-02-25 was +3.22%, which classifies as 'positive'.", "metadata": {"future_return": 0.032188, "horizon_days": 21, "hist_return": 0.084841, "annualized_vol": 0.148056, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220706_0522", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2022-07-06", "context_summary": "ADA-USD over past 60 days: cumulative return -39.9%, annualized vol 107.7%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.76, end=0.46, cumulative_return=-39.9%, annualized_volatility=107.7%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.913, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': 0.0, 't10y3m_spread': 0.92, 'breakeven_10y': 2.3, 'hy_oas': 5.99, 'ig_oas': 1.67, 'ted_spread': 0.09, 'mortgage_30y': 5.7, 'vix': 27.540000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-05] \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": 0.104665, "explanation": "The actual 21-day forward return for ADA-USD starting 2022-07-06 was +10.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.104665, "horizon_days": 21, "hist_return": -0.39934, "annualized_vol": 1.077233, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20190207_0525", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-02-07", "context_summary": "BTC-USD over past 60 days: cumulative return -0.4%, annualized vol 53.4%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=3614.23, end=3599.77, cumulative_return=-0.4%, annualized_volatility=53.4%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 253.319, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.18, 't10y3m_spread': 0.28, 'breakeven_10y': 1.86, 'hy_oas': 4.13, 'ig_oas': 1.32, 'ted_spread': 0.37, 'mortgage_30y': 4.46, 'vix': 15.380000114440918}\nMarket regime: sideways\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": 0.070843, "explanation": "The actual 21-day forward return for BTC-USD starting 2019-02-07 was +7.08%, which classifies as 'positive'.", "metadata": {"future_return": 0.070843, "horizon_days": 21, "hist_return": -0.004003, "annualized_vol": 0.534201, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210824_0528", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2021-08-24", "context_summary": "EFA over past 60 days: cumulative return +0.6%, annualized vol 11.6%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=69.20, end=69.59, cumulative_return=+0.6%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 272.676, 'unemployment': 5.1, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.02, 't10y3m_spread': 1.2, 'breakeven_10y': 2.27, 'hy_oas': 3.34, 'ig_oas': 0.95, 'ted_spread': 0.08, 'mortgage_30y': 2.86, 'vix': 17.149999618530273}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-08-23] [\"Global Cider Market Report 2021-2027: Market to Reach $16.6 Billion - Heineken Revels in Cider Business while C&C Languishes Dublin, Aug. 23, 2021 (GLOBE NEWSWIRE) -- The \\\"Cider - Global Market Trajectory & Analytics\\\" report has been added to ResearchAndMarkets.com's offering. Global Cider Market to Reach $16.6 Billion by 2027Amid the COVID-19 crisis, the global market for Cider estimated at US$12.2 Billion in the year 2020, is projected to reach a revised size of US$16.6 Billion by 2027, growing at a CAGR of 4.4% over the analysis period 2020-2027. Apple Flavored, one of the segments analyzed in the report, is projec\", \"The Morning After: WhatsApp might finally launch an iPad app Today\\u2019s headlines: Google has already discontinued the Pixel 5 and Pixel 4a with 5G, A more powerful Apple Mac mini might land this fall and four new games come to the... Atari Lynx.\", \"Water Ways Announces Its Shares Being Quoted for Trading on the Frankfurt Stock Exchange NOT FOR DISTRIBUTION TO U.S. NEWSWIRE SERVICES OR DISSEMINATION IN THE UNITED STATES TORONTO, Aug. 23, 2021 (GLOBE NEWSWIRE) -- Water Ways Technologies Inc. (TSXV: WWT) (\\\"Water Ways\\\" or the \\\"Company\\\"), a global provider of Israeli-based agriculture technology, providing water irrigation solutions to agricultural producers, is pleased to announce its shares being quoted for trade on the Frankfurt Stock Exchange (FSE) under the symbol 977. Ohad Haber Water Ways' CEO and Chairman, commented: \\\"We ar\", \"T-Mobile is giving customers a free year of Apple TV+ For a few years now, wireless carriers in the US have offered their customers all manner of video and music freebies. Verizon (Engadget's parent company) has offered free subscriptions to Disney+, Apple Music and AMC+ recently, while T-Mobile has long offered its customers free Netflix access. Today, T-Mobile is adding another freebie to its offerings: Apple TV+. Starting on August 25th, customers on the carrier's Magenta or Magenta Max plans (as well as some Sprint legacy plans) will get one year of free Apple TV+ access.\", \"Video: Jamie Windsor Shares the Truth on Being Successful on YouTube ly concerned about views and popularity, some industry members reject their credibility as skilled photographers. But that can hardly be fair. Surely there's more depth to a photographer who makes YouTube content? I was eager to find out. So I invited popular YouTuber Jamie Windsor on to The Phoblographer's official podcast: Inside The Photographers Mind.\", \"Apple employees are organizing to push for 'real change' at the company A group of current and former Apple employees are calling on their colleagues to publicly share stories of discrimination, harassment and retaliation they experienced while working at the company.\", \"Enjoy Technology Announces Second Quarter and First Half 2021 Financial Results Enjoy Technology, Inc., (\\\"Enjoy\\\"), a technology-powered service platform reinventing \\\"Commerce at Home,\\\" today reported its financial results for\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": 0.008711, "explanation": "The actual 21-day forward return for EFA starting 2021-08-24 was +0.87%, which classifies as 'flat'.", "metadata": {"future_return": 0.008711, "horizon_days": 21, "hist_return": 0.005648, "annualized_vol": 0.115976, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20150312_0531", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2015-03-12", "context_summary": "IVV over past 60 days: cumulative return -0.4%, annualized vol 14.0%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=170.65, end=170.03, cumulative_return=-0.4%, annualized_volatility=14.0%\nMacro context: {'fed_funds_rate': 0.11, 'cpi_yoy': 235.976, 'unemployment': 5.4, 'gdp_growth_qoq': 18666.621, 't10y2y_spread': 1.41, 't10y3m_spread': 2.08, 'breakeven_10y': 1.72, 'hy_oas': 4.61, 'ig_oas': 1.32, 'ted_spread': 0.24, 'mortgage_30y': 3.75, 'vix': 16.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-03-11] [\"How to Get a 6.2% Yield On a Blue Chip Stock Enhance AT&T\\u2019s already juicy yield by selling puts while waiting to see how market reacts to Dow ejection.\", \"It would take 2.5 years of Foxconn wages to afford $10,000 Apple Watch $10,000 watch underscores gap between suppliers, customers While Apple has pledged to improve supply-chain working conditions, China Labor Watch says problems persist\", \"Elon Musk wants you to know that Tesla\\u2019s priciest Model S is a badass on ice In Norway, the pricey P85D is a winner on the ice Could a Tesla Model S race across a frozen Norwegian lake help put the sexy back into shares? Can\\u2019t blame Elon Musk for trying.\", \"Which is the better value play, Qualcomm or Apple? By forgetting about the actual price of the stock and focusing on both trailing and forward earnings when trying to determine whether or a stock is properly priced brings a much clearer picture when making such a choice.\", \"This 15-year-old bear market will be around a while longer A generation comes of age learning that stocks have miserable returns Major stock market indexes are finally back to 2000 levels, but the psychological bear market is likely to be with us for a long time to come, writes Matthew Lynn.\", \"A stock market versus a market of stocks The latest issue of Hulbert On Markets One of the longest-lived debates on Wall Street is between those who think it\\u2019s a \\u201cstock market\\u201d and those who consider it to be a \\u201cmarket of stocks.\\u201d Mark Hulbert discusses who\\u2019s winning this debate right now, and what it means for your investments.\", \"Apple\\u2019s app stores are knocked out of commission iTunes store is temporarily out of commission.\", \"Apple\\u2019s App Stores Out of Order\", \"Ericsson to cut 2,200 jobs Telecom-equipment giant Ericsson AB said Wednesday it will shed 2,200 jobs, the latest move by Chief Executive Hans Vestberg to transition the company from a hardware provider into a global leader in mobile-network software.\", \"Apple's stock falls behind AT&T since Dow changes announced NEW YORK (MarketWatch) -- The curse of new Dow Jones Industrial Average components may be taking a bite out of Apple Inc.'s shares , as they have fallen behind AT&T since it was announced that the technology giant will replace the telecom company within the blue-chip index . Apple's stock dropped 1.8% on Wednesday to close at a one-month low. It has now lost 3.4% since Friday, the day S&P S&P Dow Jones Indices said Apple would join the Dow after the March 18 close. Meanwhile, AT&T's stock has lost just 2.6% this week. The last three stocks to be booted from the Dow have outperformed their respective replacements since those changes went into effect. Separately, Apple's stock now suffered the biggest two-session drop--3.9%--since it fell 4.6% in the two days ending Sept. 25, when reports of bending iPhones made the rounds.\", \"Drug dealer in China says he only did it to buy an Apple Watch The high price tag of the Apple Wat\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": 0.018643, "explanation": "The actual 21-day forward return for IVV starting 2015-03-12 was +1.86%, which classifies as 'positive'.", "metadata": {"future_return": 0.018643, "horizon_days": 21, "hist_return": -0.003628, "annualized_vol": 0.140357, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160510_0534", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2016-05-10", "context_summary": "REZ over past 60 days: cumulative return +21.2%, annualized vol 16.3%. Market regime: sideways.", "question": "Asset: REZ\nHistorical prices (past 60 trading days): start=40.78, end=49.42, cumulative_return=+21.2%, annualized_volatility=16.3%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 239.557, 'unemployment': 4.8, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 1.05, 't10y3m_spread': 1.53, 'breakeven_10y': 1.59, 'hy_oas': 6.53, 'ig_oas': 1.56, 'ted_spread': 0.39, 'mortgage_30y': 3.61, 'vix': 14.56999969482422}\nMarket regime: sideways\n\nPredict whether the return of REZ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.043634, "explanation": "The actual 21-day forward return for REZ starting 2016-05-10 was -4.36%, which classifies as 'negative'.", "metadata": {"future_return": -0.043634, "horizon_days": 21, "hist_return": 0.211781, "annualized_vol": 0.163089, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201020_0537", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2020-10-20", "context_summary": "EFA over past 60 days: cumulative return +0.6%, annualized vol 16.0%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=54.34, end=54.69, cumulative_return=+0.6%, annualized_volatility=16.0%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.62, 't10y3m_spread': 0.67, 'breakeven_10y': 1.71, 'hy_oas': 4.91, 'ig_oas': 1.32, 'ted_spread': 0.1, 'mortgage_30y': 2.81, 'vix': 29.18000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-10-19] Is Groupon's Stock Attractive At $21? We believe there may be better places for your money than Groupon\u2019s stock (NASDAQ: GRPN) after it has climbed 70% off the March bottom. Groupon\u2019s stock has rallied from $12 to $21 off the recent bottom compared to the S&P which moved 55%. The primary reason for the high recovery was the Fed\u2019s multi-billion dollar stimulus package announced on March 23rd which lifted market sentiments. The stock saw a further recovery post Q2 2020 results as the revenue and earnings beat market estimates. The company has seen a fall in revenue over recent years, while its P/S multiple has also dropped. We believe the stock is likely to see negligible upside after the recent rally and the potential weakness from a recession driven by the Covid outbreak. Our dashboard What Factors Drove -79% Change in Groupon Stock between 2017 and now? has the underlying numbers. Some of the fall over the last two years is justified by the roughly 22% fall seen in Groupon\u2019s revenues from 2017 to 2019, which in turn led to a -23% fall in revenue per share (RPS) during this period as the number of shares outstanding saw an increase of 1%. Further, its Net Income has fallen from $14 Bil in 2017 to $-22 Bil in 2019. Groupon\u2019s P/S multiple changed from 1x in 2017 to 0.6x in 2019. The company\u2019s P/S is now 0.3x as the pandemic has adversely affected the industry. Effect of Coronavirus The global spread of coronavirus has led to lockdown in various cities across the globe, which has affected industrial and economic activity. Due to the stay-at-home orders there is reduced discretionary spending which has adversely affected consumption as consumers focus on essentials. In addition, there have likely been supply disruptions in China and elsewhere from the global Coronavirus crisis. This could be seen in Groupon\u2019s Q2 2020 results as revenue fell to $395 million, down by 26% y-o-y. Meanwhile earnings were recorded at $-2.53 for Q2 2020 compared to $-1.42 in the same period of the previous year. The actual recovery and its timing hinge on the broader containment of the coronavirus spread. Our dashboard Trends In U.S. Covid-19 Cases provides an overview of how the pandemic has been spreading in the U.S. and contrasts with trends in Brazil and Russia. Following the Fed stimulus \u2014 which set a floor on fear \u2014 the market has been willing to \u201clook through\u201d the current weak period and take a longer-term view. With investors focusing their attention on 2021 results, the valuations become important in finding value. Though market sentiment can be fickle, and evidence of an uptick in new cases could spook investors once again. What if you\u2019re looking for a more balanced portfolio instead? Here\u2019s a high quality portfolio to beat the market, with over 100% return since 2016, versus 55% for the S&P 500. Comprised of companies with strong revenue growth, healthy profits, lots of cash, and low risk, it has outperformed the broader market year after year, consistently. See \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": 0.074514, "explanation": "The actual 21-day forward return for EFA starting 2020-10-20 was +7.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.074514, "horizon_days": 21, "hist_return": 0.006397, "annualized_vol": 0.159906, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160628_0540", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2016-06-28", "context_summary": "VEA over past 60 days: cumulative return -4.1%, annualized vol 18.3%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=26.11, end=25.04, cumulative_return=-4.1%, annualized_volatility=18.3%\nMacro context: {'fed_funds_rate': 0.41, 'cpi_yoy': 240.222, 'unemployment': 4.9, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 0.85, 't10y3m_spread': 1.19, 'breakeven_10y': 1.34, 'hy_oas': 6.57, 'ig_oas': 1.64, 'ted_spread': 0.36, 'mortgage_30y': 3.56, 'vix': 23.850000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-06-27] [\"FedEx, Oracle, Adobe and Alcoa are part of Zacks Earnings Preview: For Immediate Release Chicago, IL -June 27, 2016 - Zacks.com releases the list of companies likely to issue earnings surprises. This week's list includes FedEx ( FDX ), Oracle ( ORCL ), Adobe ( ADBE ) and Alcoa ( AA ). To see more earnings analysis, visit https://at.zacks.com/?id=3207 . Every day, Zacks.com makes their Bull Stock of the Day available, free of charge. To see it, click here . Q2 Earnings Season Gets Underway No one is expected to pay attention to earnings given the unexpected Brexit vote, but the Q2 earnings season has gotten underway, with results from 10 S&P 500 members already out. All of these early reporters, which includes major operators like FedEx ( FDX ), Oracle ( ORCL ) and Adobe ( ADBE ), have fiscal quarters ending in May, but get clubbed as part of the June quarter tally. We have another 11 index members with fiscal quarters ending in May on deck to report results this week. All in all, we will have seen Q2 results from almost two dozen S&P 500 members by the time Alcoa ( AA ) comes out with its results on July 11 th . We are about three weeks away from the reporting cycle really ramping up. Expectations for the Quarter Total earnings for the 10 index members that have reported results are up +4.1% on +4.2% higher revenues, with 60% beating EPS estimates and equal proportion coming ahead of top-line expectations. Comparison of the Q2 results thus far with prior periods offers a mixed picture. But it's likely too small a sample to draw any conclusions from in any case. For Q2 as a whole, total earnings for the S&P 500 are expected to be down -6.1% on -0.7% lower revenues, with growth in negative territory for 9 of the 16 Zacks sectors. As has been the pattern in other recent periods, the Energy sector remains the biggest drag on the aggregate growth picture, with total earnings for the sector expected to be down -78.9% on -27.1% lower revenues. Excluding the Energy sector, earnings for the rest of the index would be down -2.7%. Estimates for Q2 faithfully followed the well-trodden path of previous quarters. As negative as this revisions trend looks, it is nevertheless an improvement over what we had seen in the comparable period(s) in other recent quarters. The improved commodity-price backdrop and the reduced dollar drag are some of the explanations for this development. It will be interesting to see if this trend of decelerated negative revisions will continue this earnings season. But we will have to wait a few more weeks to get a better read on this development after companies start reporting June quarter results and guide towards Q3 estimates. Current estimates for Q3 are showing flat growth from the year-earlier level. Expectations Beyond Q2 Growth is expected to be negative in 2016 Q2 and flat in the following quarter. The only meaningful positive earnings growth this year is expected to come from the last quarter of the year, which is then expe\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": 0.061207, "explanation": "The actual 21-day forward return for VEA starting 2016-06-28 was +6.12%, which classifies as 'positive'.", "metadata": {"future_return": 0.061207, "horizon_days": 21, "hist_return": -0.040936, "annualized_vol": 0.182821, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160517_0543", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2016-05-17", "context_summary": "REZ over past 60 days: cumulative return +12.8%, annualized vol 16.6%. Market regime: sideways.", "question": "Asset: REZ\nHistorical prices (past 60 trading days): start=43.30, end=48.84, cumulative_return=+12.8%, annualized_volatility=16.6%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 239.557, 'unemployment': 4.8, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 0.96, 't10y3m_spread': 1.47, 'breakeven_10y': 1.6, 'hy_oas': 6.3, 'ig_oas': 1.56, 'ted_spread': 0.35, 'mortgage_30y': 3.57, 'vix': 14.68000030517578}\nMarket regime: sideways\n\nPredict whether the return of REZ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.00184, "explanation": "The actual 21-day forward return for REZ starting 2016-05-17 was -0.18%, which classifies as 'flat'.", "metadata": {"future_return": -0.00184, "horizon_days": 21, "hist_return": 0.127998, "annualized_vol": 0.165539, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190213_0546", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-02-13", "context_summary": "ETH-USD over past 60 days: cumulative return +0.4%, annualized vol 92.9%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=122.03, end=122.57, cumulative_return=+0.4%, annualized_volatility=92.9%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 253.319, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.18, 't10y3m_spread': 0.25, 'breakeven_10y': 1.83, 'hy_oas': 4.17, 'ig_oas': 1.33, 'ted_spread': 0.31, 'mortgage_30y': 4.41, 'vix': 15.43000030517578}\nMarket regime: sideways\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": 0.132479, "explanation": "The actual 21-day forward return for ETH-USD starting 2019-02-13 was +13.25%, which classifies as 'positive'.", "metadata": {"future_return": 0.132479, "horizon_days": 21, "hist_return": 0.004422, "annualized_vol": 0.929235, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200724_0549", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2020-07-24", "context_summary": "IWM over past 60 days: cumulative return +9.8%, annualized vol 33.4%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=125.86, end=138.21, cumulative_return=+9.8%, annualized_volatility=33.4%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 258.352, 'unemployment': 10.2, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.43, 't10y3m_spread': 0.47, 'breakeven_10y': 1.49, 'hy_oas': 5.26, 'ig_oas': 1.39, 'ted_spread': 0.12, 'mortgage_30y': 3.01, 'vix': 26.07999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-07-23] [\"Elon Musk doesn\\u2019t want Tesla to be \\u2018super profitable\\u2019 as it soars toward a $300 billion valuation CEO says he wants to be \\u2018slightly profitable\\u2019 long-term while exaggerating timeline to full self-driving and counting on flagging solar business, but that doesn\\u2019t stop the stock Tesla Inc. Chief Executive Elon Musk, who heads a company with a valuation approaching $300 billion, doesn\\u2019t want his electric vehicle maker to be \\u201csuper profitable.\\u201d\", \"The Ariya is Nissan\\u2019s new electric crossover SUV, and it will have some semiautonomous tech If it comes on the market in a timely fashion, it can offer some competition for the Tesla Model Y With 300 miles of driving range, it offers some competition to the Tesla Model Y and Toyota RAV4 Prime.\", \"Tesla Stock\\u2019s Run-Up Isn\\u2019t Over Yet. How to Play It With Less Risk. To manage risk without ceding exposure to higher highs, investors can consider a \\u201cbull spread\\u201d that positions them for continued advances without meaningful exposure to weakness in the stock.\", \"This index ETF is beating the S&P 500 by excluding \\u2018losers\\u2019 Eliminating weak companies has led to outperformance for the GraniteShares XOUT U.S. Large Cap ETF Eliminating weak companies has led to outperformance for the GraniteShares XOUT U.S. Large Cap ETF.\", \"Apple joins tech rivals with pledge to be 100% carbon neutral by 2030 Apple says it has improved technology to pull rare earth magnets from old iPhones and is backing a first-ever carbon-free aluminum smelting process for MacBooks Apple Inc. on Tuesday joined the ambitious aim of rival tech giants, believing it can reduce and offset emissions along its entire supply chain and in the production of its iPhones and other devices, all in less than 10 years.\", \"The doctor behind a cognitive test Trump took says \\u2018it\\u2019s supposed to be easy\\u2019 The Montreal Cognitive Assessment, or MoCA, test discussed by President Trump and Chris Wallace is \\u2018not an IQ test,\\u2019 Dr. Ziad Nasreddine tells MarketWatch The Montreal Cognitive Assessment, or MoCA, test discussed by President Trump and Chris Wallace is \\u2018not an IQ test,\\u2019 Dr. Ziad Nasreddine tells MarketWatch\", \"Dow Inc., Travelers share losses lead Dow's nearly 150-point fall\", \"Hot Tech Stocks Show Signs of Cooling. Apple Could Be Next. With its stock up 33% year to date and sky-high Wall Street expectations for second quarter earnings, Apple could be the next disappointment.\", \"\\u2018We want a stable dollar,\\u2019 says U.S. Treasury Secretary Mnuchin: \\u2018It is the reserve currency of the world and we\\u2019re going to protect that\\u2019 Treasury Secretary Steven Mnuchin says that a stable U.S. dollar is the goal of the Trump administration, while, separately, noting that some froth was percolating in the stock market that has surged since its coronavirus lows in late March\", \"Dow's 75-point fall led by losses in shares of Dow Inc., Travelers\", \"Dow, Nasda\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": 0.069482, "explanation": "The actual 21-day forward return for IWM starting 2020-07-24 was +6.95%, which classifies as 'positive'.", "metadata": {"future_return": 0.069482, "horizon_days": 21, "hist_return": 0.098194, "annualized_vol": 0.334299, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220930_0552", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2022-09-30", "context_summary": "STIP over past 60 days: cumulative return -2.5%, annualized vol 3.7%. Market regime: sideways.", "question": "Asset: STIP\nHistorical prices (past 60 trading days): start=89.27, end=87.08, cumulative_return=-2.5%, annualized_volatility=3.7%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 296.349, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.4, 't10y3m_spread': 0.4, 'breakeven_10y': 2.19, 'hy_oas': 5.5, 'ig_oas': 1.68, 'ted_spread': 0.09, 'mortgage_30y': 6.7, 'vix': 31.84000015258789}\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": "positive", "answer_numeric": 0.011445, "explanation": "The actual 21-day forward return for STIP starting 2022-09-30 was +1.14%, which classifies as 'positive'.", "metadata": {"future_return": 0.011445, "horizon_days": 21, "hist_return": -0.024583, "annualized_vol": 0.03664, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20221220_0555", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2022-12-20", "context_summary": "SOL-USD over past 60 days: cumulative return -57.5%, annualized vol 116.7%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=28.11, end=11.93, cumulative_return=-57.5%, annualized_volatility=116.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 298.832, 'unemployment': 3.5, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.68, 't10y3m_spread': -0.8, 'breakeven_10y': 2.15, 'hy_oas': 4.67, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 6.31, 'vix': 22.420000076293945}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-19] \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": 0.318896, "explanation": "The actual 21-day forward return for SOL-USD starting 2022-12-20 was +31.89%, which classifies as 'positive'.", "metadata": {"future_return": 0.318896, "horizon_days": 21, "hist_return": -0.575481, "annualized_vol": 1.166788, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20160714_0560", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2016-07-14", "context_summary": "XLV over past 60 days: cumulative return +4.5%, annualized vol 14.1%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=60.01, end=62.72, cumulative_return=+4.5%, annualized_volatility=14.1%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 240.101, 'unemployment': 4.8, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.8, 't10y3m_spread': 1.17, 'breakeven_10y': 1.45, 'hy_oas': 5.58, 'ig_oas': 1.52, 'ted_spread': 0.37, 'mortgage_30y': 3.41, 'vix': 13.039999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-07-13] [\"SAP-APWorks Team Up to Accelerate Industrial 3D Printing Taking another step in its 3D printing initiative, German software solutions corporation SAP SESAP inked a co-innovation agreement with APWorks, to accelerate the adoption and standardization of industrial 3D printing. This follows a promising collaboration with UPS in May, which aimed to establish a U.S. wide on-demand 3D printing network, by integrating SAP's extended supply chain solutions with UPS's additive industrial manufacturing and logistics network. SAP's deal with UPS aimed to provide access to on-demand manufacturing to companies, thus streamlining their supply chains, enhancing cost efficiency and reducing time-to-market. The APWorks Deal APWorks, a subsidiary of Airbus Defense and Space GmbH, and SAP intend to work toward facilitating the adoption and standardization of industrial 3D printing for the aerospace and defense industry. APWorks will leverage SAP's 3D printing services network to facilitate the development of a bionics network that will connect experts to end users. Using SAP's technology, APWorks will manufacture 3D printed components, enhance fuel efficiency and reduce CO2 emissions, along with managing spare part orders in real time. This will help it deliver qualified products on time for safety-critical applications in industries like aerospace and defense. In essence, SAP will be working with APWorks to manage orders better as they manufacture 3D printed components to deliver to industries where safety and quality is critical. Evolution of 3D Printing 3D printing has evolved past simple industrial prototyping and is fast racing toward manufacturing industries which use multiple materials like metals, plastics, and ceramics in 3D printing. This technology is on its way to revolutionize traditional manufacturing and redefine conventional notions of the industrial supply chain. It makes great sense for industries such as aerospace, where 3D printing will allow users to print the parts they need, thus ensuring the removal of several costs associated with traditional manufacturing. SAP's Initiatives SAP's collaborations corroborate the shift in manufacturing supply chain that 3D printing is enabling. In fact, SAP recently said that it intends to rationalize the supply chain in terms of collaborating and delivering certification cloud services for industrial 3D printing, using their own SAP HANA Cloud Platform. They also plan to create an on-demand 3D printing manufacturing network. This is in line with SAP's plans with APWorks, which will offer manufacturing and logistical cost savings while eliminating supply chain issues. SAP AG ADR Price SAP AG ADR Price | SAP AG ADR Quote However, SAP's prospects in the near term look gloomy as it contends with headwinds like stiff competition in the IT services industry, persistent weakness in multiple end-markets like Latin America and Brazil, and escalating research and development expenses. SAP currently has a Zacks Rank \n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.008632, "explanation": "The actual 21-day forward return for XLV starting 2016-07-14 was +0.86%, which classifies as 'flat'.", "metadata": {"future_return": 0.008632, "horizon_days": 21, "hist_return": 0.045082, "annualized_vol": 0.141412, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200914_0563", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2020-09-14", "context_summary": "IVV over past 60 days: cumulative return +7.6%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=286.82, end=308.69, cumulative_return=+7.6%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 259.997, 'unemployment': 7.8, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.54, 't10y3m_spread': 0.56, 'breakeven_10y': 1.65, 'hy_oas': 5.21, 'ig_oas': 1.37, 'ted_spread': 0.14, 'mortgage_30y': 2.86, 'vix': 26.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-11] Ambarella Stock Could See Further Downside Ambarella Incorporated stock (NASDAQ: AMBA) is down 22% since the beginning of this year, but at the current price of $47 per share, we believe that Ambarella stock has a significant downside. Why is that? Our belief stems from the fact that Ambarella\u2019s stock has risen almost 35% from the low seen in early 2019. Our dashboard What Factors Drove 34% Change In Ambarella Inc. Stock Between 2018 And Now? provides the key numbers behind our thinking, and we explain more below. Ambarella is a semiconductor design company, manufacturing processors used across a variety of applications such as video compression, image processing, and computer vision. The stock rise over the past 2 years came despite a 22% drop in Ambarella\u2019s revenues, which combined with a roughly unchanged outstanding share count, led to a 22% fall in revenue per share (RPS) from 2018 to 2020. However, Ambarella\u2019s P/S ratio rose from about 3.9x at the end of 2018 to 8.7x at the end of 2019, but has dropped to 6.8x now. This fall came due to a drop in the company\u2019s profitability, with EPS falling from $0.57 in 2018 to -$1.35 in 2020, on the back of falling revenues and gross margins. Also, given the volatility of the current situation, there is further possible downside for Ambarella\u2019s multiple when compared to levels seen in the past years \u2013 P/S of 5.9x at the start of 2018, and 3.9x as recently as early 2019. So what\u2019s the likely trigger and timing to this downside? The global spread of coronavirus, and the resulting lockdowns and quarantine has led to a drop in demand for computing devices. Further, the rise in competitors in the video compression and computer vision markets has led to a drop in selling prices, weighing down company revenue. Ambarella\u2019s revenue for Q2 2021 came in at $50.1 million vs $56.4 million for the same period last year, and with expenses not dropping at the same rate, EPS came in at -$0.43 vs -$0.31. We expect this revenue drop to continue in the medium term. We believe Ambarella\u2019s Q3 results in December will confirm this and will also likely accompany a lower 2021 guidance. Regardless, if there isn\u2019t clear evidence of containment of the virus anytime soon, we believe the stock will see its P/S multiple decline from the current level of 6.8x to around 6x, which combined with a slight reduction in revenues and margins could result in the stock price shrinking to as low as $40. Want a more balanced portfolio instead? Here\u2019s a top quality portfolio to outperform the market, with over 100% return since 2016, versus 55% for the S&P 500. Comprised of companies with strong revenue growth, healthy profits, lots of cash, and low risk. It has outperformed the broader market year after year, consistently. See all Trefis Price Estimates and Download Trefis Data here What\u2019s behind Trefis? See How It\u2019s Powering New Collaboration and What-Ifs For CFOs and Finance Teams | Product, R&D, and Marketing Teams The views and opinions expre\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": 0.038684, "explanation": "The actual 21-day forward return for IVV starting 2020-09-14 was +3.87%, which classifies as 'positive'.", "metadata": {"future_return": 0.038684, "horizon_days": 21, "hist_return": 0.076247, "annualized_vol": 0.172122, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200609_0566", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2020-06-09", "context_summary": "EEM over past 60 days: cumulative return +13.9%, annualized vol 32.4%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=31.65, end=36.05, cumulative_return=+13.9%, annualized_volatility=32.4%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 257.042, 'unemployment': 11.0, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.66, 't10y3m_spread': 0.71, 'breakeven_10y': 1.28, 'hy_oas': 5.51, 'ig_oas': 1.56, 'ted_spread': 0.14, 'mortgage_30y': 3.18, 'vix': 25.809999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-08] [\"UBS Maintains Buy on Adobe, Raises Price Target to $450\", \"UBS Maintains Buy on Adobe, Raises Price Target to $450\", \"3 Top E-Commerce Stocks to Watch in June Many e-commerce businesses have seen tailwinds this year as conditions created by the novel coronavirus pandemic resulted in stores closing and spending migrating to digital channels. With many brick-and-mortar businesses beginning to reopen in conjunction with coronavirus restrictions being eased, June could provide valuable data about what the future of retail looks like. Investors interested in e-commerce stocks should keep an eye on Shopify (NYSE: SHOP), Baozun (NASDAQ: BZUN), and Adobe Systems (NASDAQ: ADBE) this month. Image source: Getty Images. 1. Shopify Shopify provides software that allows businesses to easily create and manage online-retail websites, and it's one of the e-commerce space's hottest stocks. Shares are crushing the market in 2020, climbing roughly 89.5% year to date after rallying 187% in 2019. SHOP data by YCharts. Shopify has posted torrid growth as it's brought more large companies on board its platform and become solidified as the category-leading e-commerce services provider for small-and-medium-size enterprises. The company saw heightened merchant-customer additions and shopper engagement as the novel coronavirus began disrupting brick-and-mortar retail operations in mid-March. Shopify stock hit a lifetime high in May, but shares have actually pulled back over the last couple of weeks despite the S&P 500 index climbing roughly 8% across the same stretch. The e-commerce company's valuation is currently down roughly 13% from the lifetime high it hit in May. With brick-and-mortar retail businesses beginning to reopen in the U.S. and other territories, Shopify's coronavirus-related momentum could be tested in June. Despite the potential for near-term volatility, the company's long-term growth outlook remains promising. E-commerce will only become more important for businesses, and pullback on the stock could present an entry point for long-term investors. 2. Baozun Baozun is sometimes referred to as \\\"the Shopify of China\\\" because it also provides website-creation tools and other e-commerce services. However, most of Baozun's customers are large companies, and its core business hinges on providing services for Western brands aiming to expand their presence in China's fast-growing e-commerce market. The stock is up roughly 4% year to date following Baozun's first-quarter earnings beat and encouraging Q2 guidance it published on June 2. Even with shares now in positive territory across 2020's trading, they're still down roughly 48% from their lifetime high two years ago due to slowing growth and tensions between the U.S. and China. Baozun is seeing business pick back up as the Chinese economy recovers from coronavirus-related conditions, but the country's increasingly fraught relationship with the U.S. could create obstacles to a sustained stock rebound. Phase on\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": 0.070495, "explanation": "The actual 21-day forward return for EEM starting 2020-06-09 was +7.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.070495, "horizon_days": 21, "hist_return": 0.139181, "annualized_vol": 0.324051, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190902_0571", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2019-09-02", "context_summary": "BIL over past 60 days: cumulative return +0.3%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=76.82, end=77.06, cumulative_return=+0.3%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 2.13, 'cpi_yoy': 256.43, 'unemployment': 3.5, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.0, 't10y3m_spread': -0.49, 'breakeven_10y': 1.55, 'hy_oas': 4.13, 'ig_oas': 1.26, 'ted_spread': 0.19, 'mortgage_30y': 3.58, 'vix': 18.979999542236328}\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": 0.00129, "explanation": "The actual 21-day forward return for BIL starting 2019-09-02 was +0.13%, which classifies as 'flat'.", "metadata": {"future_return": 0.00129, "horizon_days": 21, "hist_return": 0.003119, "annualized_vol": 0.002284, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160125_0576", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2016-01-25", "context_summary": "BIL over past 60 days: cumulative return -0.0%, annualized vol 0.3%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=74.05, end=74.03, cumulative_return=-0.0%, annualized_volatility=0.3%\nMacro context: {'fed_funds_rate': 0.38, 'cpi_yoy': 237.652, 'unemployment': 4.8, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.19, 't10y3m_spread': 1.76, 'breakeven_10y': 1.35, 'hy_oas': 7.87, 'ig_oas': 1.96, 'ted_spread': 0.32, 'mortgage_30y': 3.81, 'vix': 22.34000015258789}\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": 0.0, "explanation": "The actual 21-day forward return for BIL starting 2016-01-25 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": -0.000219, "annualized_vol": 0.00323, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210107_0579", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2021-01-07", "context_summary": "INDS over past 60 days: cumulative return -2.5%, annualized vol 22.0%. Market regime: sideways.", "question": "Asset: INDS\nHistorical prices (past 60 trading days): start=31.34, end=30.56, cumulative_return=-2.5%, annualized_volatility=22.0%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 262.687, 'unemployment': 6.4, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 0.9, 't10y3m_spread': 0.95, 'breakeven_10y': 2.06, 'hy_oas': 3.8, 'ig_oas': 1.04, 'ted_spread': 0.14, 'mortgage_30y': 2.71, 'vix': 25.06999969482422}\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": "positive", "answer_numeric": 0.086266, "explanation": "The actual 21-day forward return for INDS starting 2021-01-07 was +8.63%, which classifies as 'positive'.", "metadata": {"future_return": 0.086266, "horizon_days": 21, "hist_return": -0.02491, "annualized_vol": 0.219994, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160824_0582", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2016-08-24", "context_summary": "BIL over past 60 days: cumulative return +0.0%, annualized vol 0.3%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=74.08, end=74.10, cumulative_return=+0.0%, annualized_volatility=0.3%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 240.545, 'unemployment': 4.9, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.81, 't10y3m_spread': 1.25, 'breakeven_10y': 1.48, 'hy_oas': 5.14, 'ig_oas': 1.4, 'ted_spread': 0.53, 'mortgage_30y': 3.43, 'vix': 12.380000114440918}\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": 0.0, "explanation": "The actual 21-day forward return for BIL starting 2016-08-24 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.000219, "annualized_vol": 0.003102, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180109_0585", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2018-01-09", "context_summary": "MTUM over past 60 days: cumulative return +10.7%, annualized vol 8.6%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=87.92, end=97.29, cumulative_return=+10.7%, annualized_volatility=8.6%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 248.859, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.53, 't10y3m_spread': 1.04, 'breakeven_10y': 2.02, 'hy_oas': 3.35, 'ig_oas': 0.97, 'ted_spread': 0.28, 'mortgage_30y': 3.95, 'vix': 9.729999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-01-08] [\"Activist shareholders want Apple to help kids kick iPhone addictions Jana, teachers group push for better corporate responsibility The iPhone has made Apple Inc. and Wall Street hundreds of billions of dollars. Now some big shareholders are asking at what cost, in an unusual campaign to make the company more socially responsible.\", \"Consumer Tech To Hit Record $351 Billion In 2018: CES The semi-annual industry report, released shortly before the start of the Consumer Electronics Show (CES) here, includes for the first time a projection for consumer spending on music and video-streaming services, which it says will account for $19.5 billion.\", \"Whirlpool appliances to communicate with Apple Watch in early 2018 Whirlpool Corp. said Monday it will activate Apple Watch functionality for its home appliances in early 2018. Consumers will be able to remotely communicate with ovens, washers and dryers via Apple Inc.'s Apple Watch, with the roll out to more than 20 Whirlpool brand appliances. \\\"Bringing intuitive technology and functionality to the appliance category that helps take the friction out of household chores is chief among our goals as we innovate for the smart home,\\\" said Brett Dibkey, vice president of brand strategy. \\\"Our consumers are sophisticated and expect their appliances to work smarter, not harder.\\\" Separately, Whirlpool said it was collaborating with Honeywell International Inc. , to allow consumers to connect smart appliances from Whirlpool to Honeywell's thermostats. Whirlpool's stock was still inactive in premarket trade, while Apple shares eased 0.1%. Over the past three months, Whirlpool's stock has dropped 7.1%, Apple shares have climbed 12.7%, Honeywell shares have tacked on 8.3% and the Dow Jones Industrial Average has rallied 11.1%.\", \"U.S. consumer electronics sales expected to reach record $351B in 2018 with help from streaming services The U.S. consumer technology industry is expected to reach record sales of $351 billion in 2018, up 3.9% from 2017, according to the Consumer Technology Association. This year's sales got a boost from the addition of on-demand video services like Netflix Inc. , Hulu and Sling TV, and on-demand audio services like Spotify, Pandora and Apple Music . The CTA included these services for the first time in order \\\"to better capture the full expanse of the ever-evolving and expanding consumer technology market.\\\" Without these services, 2018 growth would only be 2.2%. Some of the technologies expected to drive sales this year are smart speakers, with sales expected to grow 60% this year, smart home items like smart locks and doorbells, expected to grow 41%, and virtual reality headsets and eyewear, expected to be up 25%. The top five \\\"mature\\\" technologies, including smartphones, laptops and TVs are expected to make up 51% of revenue for the year. The Consumer Electronics Show will be Jan. 9 through Jan. 12.\", \"6 ways to make smartphones more humane \\u2014 and less addictive 39% of millennia\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": -0.050926, "explanation": "The actual 21-day forward return for MTUM starting 2018-01-09 was -5.09%, which classifies as 'negative'.", "metadata": {"future_return": -0.050926, "horizon_days": 21, "hist_return": 0.10659, "annualized_vol": 0.085668, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160121_0588", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2016-01-21", "context_summary": "VNQ over past 60 days: cumulative return -7.1%, annualized vol 17.7%. Market regime: sideways.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=52.95, end=49.17, cumulative_return=-7.1%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 237.652, 'unemployment': 4.8, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.16, 't10y3m_spread': 1.75, 'breakeven_10y': 1.32, 'hy_oas': 8.17, 'ig_oas': 1.98, 'ted_spread': 0.36, 'mortgage_30y': 3.92, 'vix': 27.59000015258789}\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": "positive", "answer_numeric": 0.014662, "explanation": "The actual 21-day forward return for VNQ starting 2016-01-21 was +1.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.014662, "horizon_days": 21, "hist_return": -0.071326, "annualized_vol": 0.176787, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20150217_0591", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2015-02-17", "context_summary": "ACWI over past 60 days: cumulative return +3.6%, annualized vol 15.9%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=47.00, end=48.68, cumulative_return=+3.6%, annualized_volatility=15.9%\nMacro context: {'fed_funds_rate': 0.12, 'cpi_yoy': 235.342, 'unemployment': 5.5, 'gdp_growth_qoq': 18666.621, 't10y2y_spread': 1.36, 't10y3m_spread': 2.01, 'breakeven_10y': 1.68, 'hy_oas': 4.69, 'ig_oas': 1.43, 'ted_spread': 0.25, 'mortgage_30y': 3.69, 'vix': 14.6899995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-02-13] [\"London wants a piece of New York\\u2019s startups U.K. led startup funding in Europe last month, raising $294 million The U.K. government launched a new initiative called HQUK this week to try and lure foreign businesses to the British isles.\", \"Goldman traded its reputation for quick profits It was once known as an investment bank but now it\\u2019s a hedge fund It was once known as an investment bank but now it\\u2019s a hedge fund, says David Weidner.\", \"Apple price target raised to $135 at BMO Capital Markets\", \"Apple price target raised to $150 at UBS\", \"Apple developing 'mega-ecosystem' as target raised to $150 NEW YORK (MarketWatch) - Apple Inc.'s price target was raised to $150 at UBS and to $135 at BMO Capital Markets on Friday, as analysts continue to grow more bullish on the iPhone maker's product line. On Thursday, Apple's stock closed at a record split-adjusted high of $126.46, valuing the company at more than $736 billion, the highest valuation of any U.S. company in history. UBS analyst Steven Milunovich, who rates Apple a buy, said Apple is creating a \\\"mega-ecosystem\\\" that is quickly turning the company into a platform, rather than just a device, company. \\\"Apple the platform company may take it to $1 trillion,\\\" he said. At $150, UBS is one of the most bullish brokerages on Apple's stock, behind just Cantor Fitzgerald, which has a $160 target on Apple. Meanwhile, BMO analyst Keith Bachman, who has an outperform rating on the stock, said he thinks Apple is adding \\\"far more users than are leaving the brand\\\" and that its fiscal 2015 iPhone unit forecast may be conservative. Shares of Apple edged 0.4% higher to $126.98 in premarket trade. To get to a $1 trillion market valuation, shares of Apple will have to reach $172.\", \"Apple\\u2019s expanding \\u2018Appleverse\\u2019 will lure you in Apple creating mega-ecosystem as target raised to $150 at UBS Apple wants iOS to permeate all aspects of consumers\\u2019 lives, more than it already does.\", \"Lovelorn single people should move to these cities Some singletons this Valentine\\u2019s Day may be looking for love in all the wrong places (or cities).\", \"Week in Review: Musk, Holocaust Chic and Homer go into \\u2018insane mode\\u2019 Marek Fuchs reviews the top events of the week, including news from Elon Musk, Holocaust Chic and Homer Simpson.\", \"American Express: After Costco, the Deluge\", \"10 biggest financial-market events this week Rising oil prices, energy stocks, Greece and Ukraine led the news Rising oil prices, energy stocks, Greece and Ukraine led the news.\", \"Groupon rallies as Zynga sinks; Tesla struggles Apple shrugs off analysts\\u2019 price target hikes Groupon, Zynga, Tesla, and Apple are among notable movers in Friday\\u2019s session.\", \"David Tepper's Appaloosa slashes equity holdings; closes Apple, Facebook positions NEW YORK (MarketWatch) -- David Tepper's hedge fund Appaloosa Management disclosed that the value of its equity holdings were reduced by 40% late last year, accor\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.004133, "explanation": "The actual 21-day forward return for ACWI starting 2015-02-17 was +0.41%, which classifies as 'flat'.", "metadata": {"future_return": 0.004133, "horizon_days": 21, "hist_return": 0.035641, "annualized_vol": 0.158604, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210729_0594", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2021-07-29", "context_summary": "LINK-USD over past 60 days: cumulative return -29.2%, annualized vol 106.1%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=26.87, end=19.03, cumulative_return=-29.2%, annualized_volatility=106.1%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 271.903, 'unemployment': 5.4, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.06, 't10y3m_spread': 1.21, 'breakeven_10y': 2.41, 'hy_oas': 3.26, 'ig_oas': 0.92, 'ted_spread': 0.08, 'mortgage_30y': 2.78, 'vix': 18.309999465942383}\nMarket regime: sideways\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": 0.398996, "explanation": "The actual 21-day forward return for LINK-USD starting 2021-07-29 was +39.90%, which classifies as 'positive'.", "metadata": {"future_return": 0.398996, "horizon_days": 21, "hist_return": -0.291755, "annualized_vol": 1.061247, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191011_0597", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2019-10-11", "context_summary": "XRP-USD over past 60 days: cumulative return -9.4%, annualized vol 58.0%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.30, end=0.27, cumulative_return=-9.4%, annualized_volatility=58.0%\nMacro context: {'fed_funds_rate': 1.82, 'cpi_yoy': 257.155, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.14, 't10y3m_spread': -0.01, 'breakeven_10y': 1.52, 'hy_oas': 4.26, 'ig_oas': 1.25, 'ted_spread': 0.34, 'mortgage_30y': 3.57, 'vix': 17.56999969482422}\nMarket regime: sideways\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": 0.079465, "explanation": "The actual 21-day forward return for XRP-USD starting 2019-10-11 was +7.95%, which classifies as 'positive'.", "metadata": {"future_return": 0.079465, "horizon_days": 21, "hist_return": -0.094062, "annualized_vol": 0.580165, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191010_0600", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2019-10-10", "context_summary": "^VIX over past 60 days: cumulative return +33.4%, annualized vol 152.0%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=13.97, end=18.64, cumulative_return=+33.4%, annualized_volatility=152.0%\nMacro context: {'fed_funds_rate': 1.82, 'cpi_yoy': 257.155, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.12, 't10y3m_spread': -0.1, 'breakeven_10y': 1.49, 'hy_oas': 4.32, 'ig_oas': 1.25, 'ted_spread': 0.32, 'mortgage_30y': 3.65, 'vix': 18.63999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-10-09] [\"Monness Crespi Hardt becomes latest to slash its Netflix price target on competition concerns Monness Crespi Hardt became the latest house to slash its stock price target for Netflix Inc. on Wednesday, when it shaved $100 off its target to lower it to $340. Analyst Brian White reiterated his buy rating on the stock in a note to clients ahead of the streaming company's third-quarter earnings next week. \\\"In light of the weakening macro environment since Netflix last provided guidance, combined with more details last month from Apple around its planned launch of Apple TV+ and incremental data points around increasingly fierce competition for content, we are adjusting our estimates for Netflix accordingly and lowering our 12-month price target to $340 from $440,\\\" White wrote. Evercore analyst Vijay Jayant slashed his Netflix price target to $300 from $380 on Monday, also citing concerns about coming competition from providers including Disney . Netflix shares were up 0.4% premarket but have fallen 24% in the last 12 months, while the S&P 500 has gained 0.4%.\", \"Apple blasted by China\\u2019s state media for \\u2018unwise and reckless decision\\u2019 to allow apps that help Hong Kong protesters A separate newspaper identified the app as HKmap.live Apple accused of offering a mobile app that \\u201cclaims to provide transportation information for the convenience of the public,\\u201d but instead identifies police locations, the China paper says.\", \"China Trade Speed Bumps May Keep Haunting Investors U.S. stock futures are climbing on hopes that China may be ready to agree a partial trade deal, in a week that has whipsawed investors around over worries that talks between the two countries face big headwinds.\", \"Tech investors need to brace for this pivotal $160 billion \\u2018gut punch\\u2019 in December, says analyst Dan Ives Critical information for the U.S. trading day Our call of the day warns investors to mark their calendar for a \\u201cpivotal $160 billion\\u201d crucial moment ahead for the tech space.\", \"Apple Stock Is Beating the Market. Analyst Expects More Gains. Canaccord cited the success of the iPhone 11 and growth in the services business. The launch of Apple TV+ in November could give the stock an extra push.\", \"The Dow Is Up 146 Points Because Hopes Are Up for a China Trade Deal Stocks are holding onto gains approaching midday Wednesday. Investors are still hanging onto hope that there could be some progress on trade when the U.S. and China resume tariff talks tomorrow.\", \"Netflix Stock Could Take a Hit From Rising Content Costs, Analyst Says Rosenblatt Securities says Netflix stock is not attractive even after its big decline in recent months.\", \"Google is working on 5G version of smartphone: report Alphabet Inc.\\u2019s Google will probably join the 5G fray in 2020, leaving Apple Inc. as the last major vendor to announce its plans Alphabet Inc. is working on a 5G-version of its Pixel 4 smartphone, but don\\u2019t expect a sneak peek next we\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": -0.313034, "explanation": "The actual 21-day forward return for ^VIX starting 2019-10-10 was -31.30%, which classifies as 'negative'.", "metadata": {"future_return": -0.313034, "horizon_days": 21, "hist_return": 0.334288, "annualized_vol": 1.519572, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20191202_0605", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2019-12-02", "context_summary": "XLV over past 60 days: cumulative return +9.5%, annualized vol 11.7%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=81.28, end=88.97, cumulative_return=+9.5%, annualized_volatility=11.7%\nMacro context: {'fed_funds_rate': 1.56, 'cpi_yoy': 258.63, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.17, 't10y3m_spread': 0.19, 'breakeven_10y': 1.61, 'hy_oas': 4.02, 'ig_oas': 1.11, 'ted_spread': 0.35, 'mortgage_30y': 3.68, 'vix': 12.619999885559082}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-29] [\"Amazon's International Segment Expected To Grow The Slowest Over Coming Years Amazon (NASDAQ:AMZN) makes money through its consumer ventures (online and offline retail sales, search advertising, content streaming etc) and cloud services (rental of compute, storage etc) and competes with industry leaders in the retail as well as technology industry including Walmart, Facebook, Google, Microsoft, IBM, eBay and Oracle. Trefis highlights trends in Amazon\\u2019s Revenues over recent years along with our forecast for 2019 and 2020 in an interactive dashboard. While the technology giant did well to surpass Q3 earnings expectations, we believe that its growth rate over coming years will be dragged down by sub-par growth internationally. While growth from India and Japan are guided to be weaker for the current quarter due to country-specific events, we expect headwinds to Amazon\\u2019s international growth to extend over several quarters \\u2013 making its international segment the slowest growing division in the near future. A Quick Look at Amazon\\u2019s Revenues Amazon has 3 Operating Segments Amazon North America: Segment revenues are derived from the sale of consumer products and subscriptions across North America. Amazon International: Segment revenues are derived from the sale of consumer products and subscriptions globally, excluding North America. Amazon Web Services (AWS): Segment revenues are derived from the sale of compute, storage, database, and other enterprise service offerings. Amazon\\u2019s revenue grew 71.3% over 2016 to 2018 to $233 billion and is expected to increase 50% to nearly $350 billion by 2020. (1) Amazon North America Division revenues have grown $61.6 billion over 2016-18, and we expect it to growth $69 billion over the next two years thanks to same-day shipping and frictionless payments. This represents an increase in Amazon\\u2019s North America revenues by nearly 50% between 2018 and 2020. (2) Amazon International Division revenues have grown $21.9 billion over 2016-18 and we expect these revenues to grow by $29 billion over the next two years due to the growing trend of digitization in International markets. However, this represents an effective growth of 44% in the division\\u2019s revenues through 2020 \\u2013 a figure which pales in comparison to the expected 50%-growth for the much bigger North America division over the same period. (3) Amazon Web Services Division revenue growth of $19 billion over the next two years is likely to be driven by AWS\\u2019s leadership position in public cloud and AWS\\u2019s initiatives to expand into the private cloud. This represents a strong 75% growth in the segment\\u2019s revenues over 2018-20. What\\u2019s behind Trefis? See How It\\u2019s Powering New Collaboration and What-Ifs For CFOs and Finance Teams | Product, R&D, and Marketing Teams More Trefis Research Like our charts? Explore example interactive dashboards and create your own. The views and opinions expressed herein are the vi\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": 0.042104, "explanation": "The actual 21-day forward return for XLV starting 2019-12-02 was +4.21%, which classifies as 'positive'.", "metadata": {"future_return": 0.042104, "horizon_days": 21, "hist_return": 0.09459, "annualized_vol": 0.117413, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220720_0608", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2022-07-20", "context_summary": "BNB-USD over past 60 days: cumulative return -14.0%, annualized vol 64.7%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=312.47, end=268.82, cumulative_return=-14.0%, annualized_volatility=64.7%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.913, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.22, 't10y3m_spread': 0.49, 'breakeven_10y': 2.39, 'hy_oas': 5.1, 'ig_oas': 1.54, 'ted_spread': 0.09, 'mortgage_30y': 5.51, 'vix': 24.5}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-19] \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": 0.271474, "explanation": "The actual 21-day forward return for BNB-USD starting 2022-07-20 was +27.15%, which classifies as 'positive'.", "metadata": {"future_return": 0.271474, "horizon_days": 21, "hist_return": -0.139691, "annualized_vol": 0.647499, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20210728_0611", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2021-07-28", "context_summary": "XLY over past 60 days: cumulative return +2.8%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=85.49, end=87.87, cumulative_return=+2.8%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 271.903, 'unemployment': 5.4, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.05, 't10y3m_spread': 1.2, 'breakeven_10y': 2.38, 'hy_oas': 3.27, 'ig_oas': 0.92, 'ted_spread': 0.08, 'mortgage_30y': 2.78, 'vix': 19.36000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-07-27] [\"Advanced Micro Devices Q2 21 Earnings Conference Call At 5:00 PM ET (RTTNews) - Advanced Micro Devices Inc. (AMD) will host a conference call at 5:00 PM ET on July 27, 2021, to discuss Q2 21 earnings results. Advanced Micro Devices is scheduled to report results on Tuesday, July 27, after market close. To access the live webcast, log on to http://ir.amd.com The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Advanced Micro Devices (AMD) Q2 2021 Earnings Call Transcript Image source: The Motley Fool. Advanced Micro Devices (NASDAQ: AMD) Q2 2021 Earnings Call Jul 27, 2021, 5:00 p.m. ET Contents: Prepared Remarks Questions and Answers Call Participants Prepared Remarks: Operator Hello, and welcome to the AMD second-quarter 2021earnings conference call [Operator instructions] As a reminder, this conference is being recorded. It's now my pleasure to turn the call over to Laura Graves, corporate vice president of investor relations. Laura, please go ahead. Laura Graves -- Corporate Vice President of Investor Relations Thank you, and welcome to AMD's second-quarter 2021 financial results conference call. By now, we hope you have had the opportunity to review a copy of our earnings press release and slides. If you have not reviewed these documents yet, they can be found on the Investor Relations page of amd.com. Participants on today's conference call are Dr. Lisa Su, our president and chief executive officer; and Devinder Kumar, our executive vice president, chief financial officer, and treasurer. This is a live call and will be replayed via webcast on our website. Before we begin, I would like to note that Saeid Moshkelani, senior vice president and general manager of our client business; and Ruth Cotter, senior vice president of worldwide marketing, human resources, investor relations and strategy, will attend the Jefferies semiconductor and hardware summit on Tuesday, August 31. Devinder Kumar will attend the Deutsche Bank technology conference on Friday, September 10. 10 stocks we like better than Advanced Micro Devices When our award-winning 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 Advanced Micro Devices 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 June 7, 2021 And our third-quarter 2021 quiet time is expected to begin at the close of business on Friday, September 10. Today's discussion contains forward-looking statements based on current beliefs, assumptions and expectations, speak only as of today and as such, involve risks and uncertainties that could cause actual results to differ materially from our current expectations. We refer to the cautionary statemen\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": -0.010814, "explanation": "The actual 21-day forward return for XLY starting 2021-07-28 was -1.08%, which classifies as 'negative'.", "metadata": {"future_return": -0.010814, "horizon_days": 21, "hist_return": 0.02786, "annualized_vol": 0.142943, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210929_0618", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2021-09-29", "context_summary": "EEM over past 60 days: cumulative return -6.3%, annualized vol 17.8%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=48.10, end=45.09, cumulative_return=-6.3%, annualized_volatility=17.8%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 273.91, 'unemployment': 4.7, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.23, 't10y3m_spread': 1.5, 'breakeven_10y': 2.38, 'hy_oas': 3.13, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 2.88, 'vix': 23.25}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-28] [\"Logitech's MX Keys Mini is a compact keyboard for minimalists Logitech has unveiled the MX Keys Mini, a compact keyboard for minimalists who don't want mechanical switches.\", \"Ableton Live 11.1 beta available now with Apple M1 support Ableton Live 11.1 beta available now with Apple M1 support, a new pitch shifting device and more.\", \"How to Buy Used and Refurbished Cameras and Lenses \\\"But it's so expensive,\\\" is what everyone says when a new camera or lens goes on sale. And so I'd like to welcome you to the world of photography that Leica camera users have known about for years. There is a massive benefit to the used and refurbished market for this reason. Don't want to pay $3,000 for that new Sony lens? Do you think that the Canon R5 is way too much money? Well, hyper-focusing on the original price point, I think, is sometimes excessive. It gets in the way of you getting tha\", \"United States Natural Language Processing Market Report 2021 Featuring Google, IBM, Microsoft, Intel, Apple, AWS, Facebook, Inbenta Technologies, Veritone, SAS Institute Dublin, Sept. 28, 2021 (GLOBE NEWSWIRE) -- The \\\"United States Natural Language Processing Market, By Component (Solution and Services), By Deployment (On-Premise, Cloud), By Organization Size (SME's Vs Large Enterprises), By Type, By Application, By End User, By Region, Competition, Forecast & Opportunities, 2026\\\" report has been added to ResearchAndMarkets.com's offering. United States natural language processing market is expected to grow at an impressive rate over the forecast period Growing\", \"1Password can now randomly generate email addresses for logins The Masked Email feature allows you to create unique email addresses for your logins.\", \"1Password can now randomly generate email addresses for logins Since 2019, Sign in with Apple has allowed iPhone and Mac users to protect their privacy by allowing them to generate random email addresses when they need to access a new website, service or app. It\\u2019s one of those small features that can have an outsized impact, and now something similar is coming to 1Password. Like its Apple counterpart, the tool allows you to create unique email addresses for your logins.\", \"Highnote emerges from stealth with $54M and a plan to take on Marqeta in the world of card issuing as a service Fintech startups have thrown a curve ball into the world of financial services, by building more flexible, cheaper and user-friendly tools to businesses and consumers, who in turn are walking away from older incumbents and taking their custom to newer providers. In the latest development, a startup called Highnote is launching with ambitions to make waves in the world of card issuing, by making it easy for any company of any size to provide virtual payment cards to their customers. Founded by PayPal alums, the company is exiting stealth mode today and also announcing $54 million in funding to take its first steps.\", \"IIROC Trading Resumption - STUV Trading resumes in:\", \"Wit\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": 0.033813, "explanation": "The actual 21-day forward return for EEM starting 2021-09-29 was +3.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.033813, "horizon_days": 21, "hist_return": -0.062616, "annualized_vol": 0.178115, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220204_0621", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2022-02-04", "context_summary": "SOYB over past 60 days: cumulative return +17.5%, annualized vol 16.6%. Market regime: sideways.", "question": "Asset: SOYB\nHistorical prices (past 60 trading days): start=21.72, end=25.52, cumulative_return=+17.5%, annualized_volatility=16.6%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 284.5, 'unemployment': 3.9, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.63, 't10y3m_spread': 1.62, 'breakeven_10y': 2.38, 'hy_oas': 3.51, 'ig_oas': 1.08, 'ted_spread': 0.09, 'mortgage_30y': 3.55, 'vix': 24.350000381469727}\nMarket regime: sideways\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": 0.054672, "explanation": "The actual 21-day forward return for SOYB starting 2022-02-04 was +5.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.054672, "horizon_days": 21, "hist_return": 0.174954, "annualized_vol": 0.166301, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200409_0626", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2020-04-09", "context_summary": "XLRE over past 60 days: cumulative return -12.5%, annualized vol 35.0%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=31.58, end=27.63, cumulative_return=-12.5%, annualized_volatility=35.0%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 256.032, 'unemployment': 14.8, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.5, 't10y3m_spread': 0.55, 'breakeven_10y': 1.19, 'hy_oas': 8.17, 'ig_oas': 2.34, 'ted_spread': 0.9852, 'mortgage_30y': 3.33, 'vix': 43.34999847412109}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-04-08] [\"iPhone Maker Foxconn To Produce Ventilators In US\", \"Hearing Piper Sandler Raised Apple Price Target From $260 To $300; Unconfirmed\", \"JP Morgan Maintains Overweight on Apple, Lowers Price Target to $335\", \"10 Biggest Price Target Changes For Wednesday\", \"Shares of several technology companies are trading higher amid overall market strength on optimism that US coronavirus cases could soon leveling off. NOTE: Some names in the sector have potentially benefited from recent work-at-home trends.\", \"Watching Apple Shares; Hearing Traders Circulating Word Of Earlier Article From China Publication Suggesting Apple Cut Orders From China Suppliers\", \"Global Payments Firm Papaya Global Publishes International COVID-19 Crisis Guides For Employers\", \"The Show Must Go On \\u2013 Event Industry Rising To The Challenge Of COVID-19\", \"Netflix, YouTube, Disney+: Which Video Streaming Platform Do Teens Watch The Most?\", \"Disney Shares Climb 7% As Video On Demand Service Crosses 50M Subscribers\", \"Netflix, YouTube, Disney+: Which Video Streaming Platform Do Teens Watch The Most?\", \"The Show Must Go On \\u2013 Event Industry Rising To The Challenge Of COVID-19\", \"Global Payments Firm Papaya Global Publishes International COVID-19 Crisis Guides For Employers\", \"Watching Apple Shares; Hearing Traders Circulating Word Of Earlier Article From China Publication Suggesting Apple Cut Orders From China Suppliers\", \"Shares of several technology companies are trading higher amid overall market strength on optimism that US coronavirus cases could soon leveling off. NOTE: Some names in the sector have potentially benefited from recent work-at-home trends.\", \"10 Biggest Price Target Changes For Wednesday\", \"JP Morgan Maintains Overweight on Apple, Lowers Price Target to $335\", \"Hearing Piper Sandler Raised Apple Price Target From $260 To $300; Unconfirmed\", \"iPhone Maker Foxconn To Produce Ventilators In US\", \"Disney Shares Climb 7% As Video On Demand Service Crosses 50M Subscribers\", \"Netflix, YouTube, Disney+: Which Video Streaming Platform Do Teens Watch The Most?\", \"The Show Must Go On \\u2013 Event Industry Rising To The Challenge Of COVID-19\", \"Global Payments Firm Papaya Global Publishes International COVID-19 Crisis Guides For Employers\", \"Watching Apple Shares; Hearing Traders Circulating Word Of Earlier Article From China Publication Suggesting Apple Cut Orders From China Suppliers\", \"Shares of several technology companies are trading higher amid overall market strength on optimism that US coronavirus cases could soon leveling off. NOTE: Some names in the sector have potentially benefited from recent work-at-home trends.\", \"10 Biggest Price Target Changes For Wednesday\", \"JP Morgan Maintains Overweight on Apple, Lowers Price Target to $335\", \"Hearing Piper Sandler Raised Apple Price Target From $260 To $300; Unconfirmed\", \"iPhone Maker Foxconn To Produce Ventilators In US\", \"Mercedes-Benz GLS-Class: New full-size luxury SUV fits the bill A review of the all-new 2020 SUV\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": -0.061356, "explanation": "The actual 21-day forward return for XLRE starting 2020-04-09 was -6.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.061356, "horizon_days": 21, "hist_return": -0.125303, "annualized_vol": 0.350262, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220921_0629", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-09-21", "context_summary": "ETH-USD over past 60 days: cumulative return -14.5%, annualized vol 75.5%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1549.30, end=1324.39, cumulative_return=-14.5%, annualized_volatility=75.5%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 296.349, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.39, 't10y3m_spread': 0.22, 'breakeven_10y': 2.4, 'hy_oas': 4.88, 'ig_oas': 1.47, 'ted_spread': 0.09, 'mortgage_30y': 6.02, 'vix': 27.15999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-20] \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": 0.033768, "explanation": "The actual 21-day forward return for ETH-USD starting 2022-09-21 was +3.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.033768, "horizon_days": 21, "hist_return": -0.145169, "annualized_vol": 0.754641, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20190813_0634", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-08-13", "context_summary": "LINK-USD over past 60 days: cumulative return +42.0%, annualized vol 114.5%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=1.68, end=2.38, cumulative_return=+42.0%, annualized_volatility=114.5%\nMacro context: {'fed_funds_rate': 2.12, 'cpi_yoy': 256.036, 'unemployment': 3.6, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.07, 't10y3m_spread': -0.35, 'breakeven_10y': 1.61, 'hy_oas': 4.4, 'ig_oas': 1.27, 'ted_spread': 0.22, 'mortgage_30y': 3.6, 'vix': 21.09000015258789}\nMarket regime: sideways\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": -0.231402, "explanation": "The actual 21-day forward return for LINK-USD starting 2019-08-13 was -23.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.231402, "horizon_days": 21, "hist_return": 0.419562, "annualized_vol": 1.144751, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160715_0637", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2016-07-15", "context_summary": "TLH over past 60 days: cumulative return +5.3%, annualized vol 8.0%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=105.98, end=111.55, cumulative_return=+5.3%, annualized_volatility=8.0%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 240.101, 'unemployment': 4.8, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.85, 't10y3m_spread': 1.21, 'breakeven_10y': 1.45, 'hy_oas': 5.44, 'ig_oas': 1.5, 'ted_spread': 0.37, 'mortgage_30y': 3.42, 'vix': 12.81999969482422}\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": "flat", "answer_numeric": 0.007233, "explanation": "The actual 21-day forward return for TLH starting 2016-07-15 was +0.72%, which classifies as 'flat'.", "metadata": {"future_return": 0.007233, "horizon_days": 21, "hist_return": 0.052554, "annualized_vol": 0.080204, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20170110_0642", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2017-01-10", "context_summary": "EWJ over past 60 days: cumulative return +3.5%, annualized vol 11.1%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=40.67, end=42.11, cumulative_return=+3.5%, annualized_volatility=11.1%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 243.618, 'unemployment': 4.7, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.17, 't10y3m_spread': 1.88, 'breakeven_10y': 1.95, 'hy_oas': 4.02, 'ig_oas': 1.29, 'ted_spread': 0.51, 'mortgage_30y': 4.2, 'vix': 11.5600004196167}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-09] [\"The Medicines Co LDL-Lowering Drug Positive in Phase II The Medicines CompanyMDCO announced positive top-line results from a Day 180 interim analysis of the ongoing ORION-1 phase II study on its pipeline candidate, Inclisiran (formerly PCSK9si), for the treatment of hypercholesterolemia. The Medicines Company is developing Inclisiran under a collaboration agreement with Alnylam Pharmaceuticals, Inc. ALNY , which was inked in early 2013. The Medicines Company is solely responsible for the development and commercialization of the candidate. The Medicines Company's three-month share price movement shows that the stock has outperformed the Zacks classified Medical - Biomedical and Genetics industry. Specifically, the company lost 1.7%, while the industry lost 3.7%. ORION-1 is a placebo-controlled, double-blinded, randomized, dose-finding phase II study. It compares and evaluates the effect of various doses of single or multiple subcutaneous injections of Inclisiran. The study was conducted in a total of 501 patients with atherosclerotic cardiovascular disease (ASCVD) or ASCVD-risk equivalents (hypercholesterolemia). Interim data demonstrated that Inclisiran led to a significant and durable reduction of LDL (low-density lipoprotein) cholesterol up to Day 210. Inclisiran was well tolerated throughout the study, with infrequent and mild or moderate injection site reactions. Data from the study will be presented at the annual meeting of the American College of Cardiology, scheduled to be held in Mar 2017. The company expects to move Inclisiran into phase III development (OROPN-4 study) after discussions with regulatory authorities. Meanwhile, the company announced the initiation of ORION-2 for evaluating the efficacy, safety and tolerability of Inclisiran in patients with homozygous familial hypercholesterolemia (HoFH). Moreover, the company commenced enrollment of ORION-1 patients in the phase II ORION-3 extension study, which will evaluate the efficacy, safety and tolerability of long-term dosing of Inclisiran. Note that, apart from Inclisiran, The Medicines Company has several interesting pipeline candidates targeting key focus areas. Three of these candidates - MDCO-216 (atherosclerotic plaque burden), ABP-700 (general anesthesia for surgical care) and Carbavance (treatment of hospitalized patients with serious gram-negative bacterial infections) - have blockbuster potential. The Medicines Company Price The Medicines Company Price | The Medicines Company Quote Zacks Rank & Other Key Picks The Medicines Company currently carries a Zacks Rank #2 (Buy). A couple of other favorably placed stocks in the health care sector include Orexigen Therapeutics, Inc. OREX and Arbutus Biopharma Corporation ABUS . Both the stocks sport a Zacks Rank #1 (Strong Buy). You can see the complete list of today's Zacks #1 Rank stocks here . Orexigen's loss estimates widened from $8.93 to $8.17 for 2016 and from $5.19 to $2.17 for 2017 over the last 60 days. The company pos\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.013911, "explanation": "The actual 21-day forward return for EWJ starting 2017-01-10 was +1.39%, which classifies as 'positive'.", "metadata": {"future_return": 0.013911, "horizon_days": 21, "hist_return": 0.035226, "annualized_vol": 0.111424, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20201111_0647", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2020-11-11", "context_summary": "AVAX-USD over past 60 days: cumulative return -31.5%, annualized vol 92.4%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=5.23, end=3.59, cumulative_return=-31.5%, annualized_volatility=92.4%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.911, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.79, 't10y3m_spread': 0.88, 'breakeven_10y': 1.76, 'hy_oas': 4.37, 'ig_oas': 1.19, 'ted_spread': 0.11, 'mortgage_30y': 2.78, 'vix': 24.799999237060547}\nMarket regime: sideways\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": 0.070906, "explanation": "The actual 21-day forward return for AVAX-USD starting 2020-11-11 was +7.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.070906, "horizon_days": 21, "hist_return": -0.31492, "annualized_vol": 0.923899, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210908_0650", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2021-09-08", "context_summary": "XLRE over past 60 days: cumulative return +6.1%, annualized vol 12.6%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=38.75, end=41.13, cumulative_return=+6.1%, annualized_volatility=12.6%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 273.91, 'unemployment': 4.7, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.16, 't10y3m_spread': 1.33, 'breakeven_10y': 2.36, 'hy_oas': 3.16, 'ig_oas': 0.92, 'ted_spread': 0.07, 'mortgage_30y': 2.87, 'vix': 18.13999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-07] [\"3 Top Stocks to Buy in September It's been a topsy-turvy summer for investors, but things don't cool down just because fall is around the corner. September is often a sleepy period, but there are some interesting companies that are still expected to make waves this month. Adobe (NASDAQ: ADBE), fuboTV (NYSE: FUBO), and Walt Disney (NYSE: DIS) are three companies that have some potential catalysts kicking in this month. Let's take a closer look to see why they are some of the top stocks to buy in September. Image source: Getty Images. Adobe Earnings season has come and gone, but some companies like Adobe march to the beat of a different fiscal drummer. The desktop publishing giant reports fresh financials for its fiscal third quarter in two weeks. Adobe isn't just the company behind Photoshop and PDF files. Its Creative Cloud suite of digital publishing tools is the cloud-based standard for more than just creative types. Adobe is also also a major player in the booming e-signature market. This is also a far more consistent growth stock than you might think, with steady and growing subscription revenue now accounting for 92% of the top-line mix. It has rattled off six consecutive fiscal years of revenue growth of 15% or better. It's a strong bet to stretch that streak to seven after posting 26% and 23% top-line growth in its first two fiscal quarters. A master of the \\\"beat and raise\\\" game that is so rewarding to shareholders, it would be a shock if Adobe doesn't land ahead of Wall Street targets again in two weeks. It's also helping make its own luck on a per-share basis by perpetually buying back more shares than its prints out. Adobe's fiscal year-end share count has declined for five years. fuboTV The fastest-growing live TV streaming service has had a wild first year of trading. fuboTV stock has more than tripled since going public at $10 just 11 months ago, but it's trading for less than half of its late-December peak. The sports-heavy platform has seen its revenue accelerate throughout its brief tenure on the market, soaring 196% in its latest quarter. fuboTV isn't one of the handful of companies reporting financial results this month, but it is putting one important component of its master plan into action in September. Last week, fuboTV rolled real-time sporting event stats and free-to-play games out of beta, coinciding with the new round of South American Qatar World Cup 2022 qualifying matches. Subscribers can now opt to have their game screens resized to make room for its FanView stats. There are also predictive games that are free to play but with real cash prizes for the best prognosticators. With a small yet fast-growing sports-centric subscriber base of more than 680,000 premium accounts, all of this month's new toys are just the beginning. The real star will come later this year when fuboTV launches its own sportsbook through a dedicated smartphone app. fuboTV viewers already trust the platform for their programming and with thei\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": -0.0643, "explanation": "The actual 21-day forward return for XLRE starting 2021-09-08 was -6.43%, which classifies as 'negative'.", "metadata": {"future_return": -0.0643, "horizon_days": 21, "hist_return": 0.061309, "annualized_vol": 0.125722, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220811_0653", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2022-08-11", "context_summary": "AVAX-USD over past 60 days: cumulative return +67.5%, annualized vol 104.9%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=17.39, end=29.12, cumulative_return=+67.5%, annualized_volatility=104.9%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 295.097, 'unemployment': 3.6, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.45, 't10y3m_spread': 0.13, 'breakeven_10y': 2.43, 'hy_oas': 4.33, 'ig_oas': 1.47, 'ted_spread': 0.09, 'mortgage_30y': 4.99, 'vix': 19.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-08-10] \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": -0.323878, "explanation": "The actual 21-day forward return for AVAX-USD starting 2022-08-11 was -32.39%, which classifies as 'negative'.", "metadata": {"future_return": -0.323878, "horizon_days": 21, "hist_return": 0.674617, "annualized_vol": 1.048737, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20190614_0656", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2019-06-14", "context_summary": "ADA-USD over past 60 days: cumulative return +9.0%, annualized vol 91.4%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.08, end=0.09, cumulative_return=+9.0%, annualized_volatility=91.4%\nMacro context: {'fed_funds_rate': 2.37, 'cpi_yoy': 255.213, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.27, 't10y3m_spread': -0.09, 'breakeven_10y': 1.68, 'hy_oas': 4.24, 'ig_oas': 1.32, 'ted_spread': 0.27, 'mortgage_30y': 3.82, 'vix': 15.81999969482422}\nMarket regime: sideways\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": -0.155453, "explanation": "The actual 21-day forward return for ADA-USD starting 2019-06-14 was -15.55%, which classifies as 'negative'.", "metadata": {"future_return": -0.155453, "horizon_days": 21, "hist_return": 0.090296, "annualized_vol": 0.914356, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160509_0659", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2016-05-09", "context_summary": "VEA over past 60 days: cumulative return +6.1%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=25.04, end=26.56, cumulative_return=+6.1%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 239.557, 'unemployment': 4.8, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 1.05, 't10y3m_spread': 1.6, 'breakeven_10y': 1.61, 'hy_oas': 6.48, 'ig_oas': 1.56, 'ted_spread': 0.44, 'mortgage_30y': 3.61, 'vix': 14.720000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-06] FEYE Stock: FireEye Inc Tumbles, But It\u2019s Not Beat InvestorPlaceInvestorPlace - Stock Market News, Stock Advice & Trading Tips Heading into the first-quarter earnings report for FireEye Inc ( FEYE ), Wall Street analysts weren't short on worries \u2026 and it looks like that anxiety was warranted. Source: David via Flickr (Modified) FireEye is cratering this morning, off 14% after a pretty lousy report and a change in the C-suite. The biggest news of the day is that CEO David DeWalt is out - and stepping in will be company President Kevin Mandia, who founded Mandiant , which FireEye paid $1 billion to acquire back in 2014. Mandia will take the reins on June 15, and DeWalt will slip back to jsut being executive chairman. But the change in leadership isn't coming because all is hunky-dory. The financials from FireEye's Q1 report were far from encouraging. 7 Blue Chips That Are Getting Ugly in a Hurry An adjusted loss of 47 cents per share came in 3 cents ahead of expectations, and billings - a vital stat in the software space - came in at $186 million to easily best estimates for $176.2 million. But revenues were weak, at $168 million versus expectations of $171.7 million, and guidance didn't please anyone. FEYE expects Q2 sales to come in between $178 million to $185 million, with the entire range falling below analysts' estimate of $192.75 million. Those numbers also represent a deceleration in the growth path for FireEye. Yes, revenues were up 34% year-over-year \u2026 but that's far less than the 69% growth it saw in Q1 2015. Similarly, billings growth declined from 53% to 23%. A Bright Side to FEYE Stock? But that said, FEYE is a company in transition. It has been struggling to revamp its product line for the cloud, as well as to offer subscriptions to customers. And those are the right moves - they simply take time to pull off. Just ask Adobe Systems Incorporated ( ADBE ). Plus, FireEye is making some bold plays to make the transition successful, including acquiring firms such as iSight Partners and Invotas . What's more, Mandia may be the right person to lead the charge. I recently talked to Paul Kraus, founder and CEO of Eastwind Networks , who said: \"The board seems to believe he is a proven leader who can execute against FireEye's broader vision of monetizing its branded version of security-as-a service - FireEye-as-a-service or FaaS. \"Can Mandia propel FireEye to achieve its top-line revenue projections for FaaS? That will likely unfold over the coming quarters and remains to be seen. Cybersecurity is a hyper-crowded and rapidly evolving sector, and Mandia will have a clear charter to continue to focus on services, grab market share, and eventually turn a profit.\" Of course, that's an uphill climb, considering FireEye will be trying to grab that market share against companies like Palo Alto Networks Inc ( PANW ) and Cyberark Software Ltd ( CYBR ), as well as mega-tech firms like Cisco Systems, Inc. ( CSCO ) and International Business Machines Corp\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": 0.045695, "explanation": "The actual 21-day forward return for VEA starting 2016-05-09 was +4.57%, which classifies as 'positive'.", "metadata": {"future_return": 0.045695, "horizon_days": 21, "hist_return": 0.06065, "annualized_vol": 0.172123, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180131_0662", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2018-01-31", "context_summary": "ICSH over past 60 days: cumulative return +0.3%, annualized vol 0.6%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=39.44, end=39.57, cumulative_return=+0.3%, annualized_volatility=0.6%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 248.859, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.6, 't10y3m_spread': 1.29, 'breakeven_10y': 2.1, 'hy_oas': 3.33, 'ig_oas': 0.91, 'ted_spread': 0.35, 'mortgage_30y': 4.15, 'vix': 14.789999961853027}\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": 0.000579, "explanation": "The actual 21-day forward return for ICSH starting 2018-01-31 was +0.06%, which classifies as 'flat'.", "metadata": {"future_return": 0.000579, "horizon_days": 21, "hist_return": 0.003221, "annualized_vol": 0.005607, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191017_0665", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2019-10-17", "context_summary": "XLRE over past 60 days: cumulative return +6.6%, annualized vol 12.5%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=29.58, end=31.52, cumulative_return=+6.6%, annualized_volatility=12.5%\nMacro context: {'fed_funds_rate': 1.9, 'cpi_yoy': 257.155, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.17, 't10y3m_spread': 0.09, 'breakeven_10y': 1.57, 'hy_oas': 4.01, 'ig_oas': 1.2, 'ted_spread': 0.37, 'mortgage_30y': 3.57, 'vix': 13.68000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-10-16] [\"Citigroup Downgrades Adobe to Neutral\", \"Adobe shares are trading lower after Citigroup downgraded the company's stock from Buy to Neutral.\", \"23 Stocks Moving in Wednesday's Pre-Market Session\", \"9 Technology Stocks Moving In Wednesday's Pre-Market Session\", \"Citi Steps To Sidelines On Adobe\", \"44 Stocks Moving In Wednesday's Mid-Day Session\", \"Benzinga's Top Upgrades, Downgrades For October 16, 2019\", \"PreMarket Prep Recap: Stormy Outlook For Cloud Stocks, Opioid Makers Rally On Settlement Talks\", \"PreMarket Prep Recap: Stormy Outlook For Cloud Stocks, Opioid Makers Rally On Settlement Talks\", \"Benzinga's Top Upgrades, Downgrades For October 16, 2019\", \"44 Stocks Moving In Wednesday's Mid-Day Session\", \"Citi Steps To Sidelines On Adobe\", \"9 Technology Stocks Moving In Wednesday's Pre-Market Session\", \"23 Stocks Moving in Wednesday's Pre-Market Session\", \"Adobe shares are trading lower after Citigroup downgraded the company's stock from Buy to Neutral.\", \"Citigroup Downgrades Adobe to Neutral\", \"5 Top Stock Trades for Thursday: ADBE, NFLX, ABT The indices did not move too much on Wednesday, but a handful of tech stocks were hit hard on the day. Let\\u2019s look at a few of the top stock trades going into the latter half of the week. Top Stock Trades for Tomorrow No. 1: Adobe (ADBE) Adobe Systems (NASDAQ:) came under pressure Wednesday following a downgrade from Citi analysts. Shares have been trying to break out over downtrend resistance (blue line) and were actually succeeding before Wednesday. However, the tepid bullish action was not enough to withstand today\\u2019s selling. Nor were the 20-day and 200-day moving averages, as ADBE stock gapped below both metrics. However, it\\u2019s finding some reprieve from the 38.2% retracement. Now investors want to know, can ADBE reclaim the 200-day and downtrend resistance or are lower prices in store? If it\\u2019s the latter, look for a decline down into the $258 to $260 area. There it will find a notable level of support as well as the 50% retracement. If that fails to hold, ADBE stock may be in trouble. On the upside, the charts are pretty cluttered until Adobe can clear the 50-day moving average. Top Stock Trades for Tomorrow No. 2: Netflix (NFLX) Netflix (NASDAQ:) is very much a mixed picture ahead of the company\\u2019s earnings report on Wednesday after the close. On the plus side, shares have broken out over downtrend resistance (blue line) and are maintaining above the 20-day moving average. On the downside, they are stuck below the 50-day moving average and the 38.2% retracement. So what now? Should shares decline, look to see if the 23.6% retracement at $267.75 can support the name. If not, $260 could be on deck, with the September low of $252.28 below that. Below the September low and the December low is possible. On the upside, see that NFLX reclaims and holds the 50-day moving average and 38.2% retracement. Above that opens the door to the 50% and 61.8% retracements at $308.61 and $326.81, \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": -0.024791, "explanation": "The actual 21-day forward return for XLRE starting 2019-10-17 was -2.48%, which classifies as 'negative'.", "metadata": {"future_return": -0.024791, "horizon_days": 21, "hist_return": 0.065864, "annualized_vol": 0.124578, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180130_0668", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2018-01-30", "context_summary": "VTI over past 60 days: cumulative return +10.7%, annualized vol 6.7%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=115.81, end=128.21, cumulative_return=+10.7%, annualized_volatility=6.7%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 248.859, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.59, 't10y3m_spread': 1.26, 'breakeven_10y': 2.09, 'hy_oas': 3.26, 'ig_oas': 0.92, 'ted_spread': 0.34, 'mortgage_30y': 4.15, 'vix': 13.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-01-29] [\"Alibaba, Foxconn lead big investment in Chinese electric-car maker Tech companies branch out into burgeoning industry Chinese e-commerce giant Alibaba Group Holding Ltd. and Foxconn Technology Group have co-led a 2.2 billion yuan ($348 million) funding round into Chinese electric-vehicle manufacturer Xiaopeng Motors, marking Alibaba\\u2019s first big investment in a car maker\", \"Immersion enters settlement and license deal with Apple\", \"Immersion settles with Apple, reaches license agreements Immersion Corp. said Monday it has entered into settlement and license deals with Apple Inc. . Immersion, which develops touch feedback technology, had filed patent infringement lawsuits against Apple for technology used in iPhones and the trackpads used in MacBooks. Immersion said the terms of the agreements reached with Apple are confidential. The stock, which was still inactive in premarket trade, has tumbled 30% over the past 12 months, while the S&P 500 has gained 25%.\", \"Apple stock drops after report of iPhone X production cut Apple Inc. shares are down 0.5% in premarket trading Monday after a report in the Nikkei Asia Review said that the company planned to trim its iPhone X production target to 20 million for the March quarter, half of what it expected a few months ago. The Nikkei Asian Review attributes the production cut to lower-than-anticipated sales of the device. The phone's price tag of at least $999 could be a key reason for the demand issues, the publication said. Wall Street analysts have also been weighing in on the prospect of significantly weaker-than-expected iPhone X sales, with analysts at JP Morgan predicting last week that Apple would cut its build orders for the device by 50% in the March quarter, causing them to take a more cautious stance on a number of Apple suppliers. Apple shares are up 41% over the past 12 months, while the Dow Jones Industrial Average is up 30%.\", \"Robinhood\\u2019s crypto biz has drawn nearly 1 million in user interest: Watch out Coinbase! Coinbase is the No. 1\\u2013ranked U.S. crypto exchange platform over the past six months. Can Robinhood give it a run for its money in bitcoin, Ethereum trading? New-age brokerage platform Robinhood is jumping in on the cryptocurrency craze, declaring that it will allow trading in bitcoin and Ethereum\\u2019s currency starting in February, with more virtual currencies expected to be added soon.\", \"This \\u2018parabolic\\u2019 move for stocks has some investors nervous, but should it? Critical information for the U.S. trading day Is this bull market finally starting to feel a bit top-heavy? According to official MarketWatch records, this marks the 698th time that very question has been asked in this space since Trump took office.\", \"\\u2018Get Out\\u2019 is headed back to theaters after its 4 Oscar nominations \\u2018Get Out\\u2019 grossed $254.7 million at box offices worldwide on just a $4.5 million production budget It has been almost a year since \\u201cGet Out\\u201d opened i\n\nPredict whether the return of VTI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.048691, "explanation": "The actual 21-day forward return for VTI starting 2018-01-30 was -4.87%, which classifies as 'negative'.", "metadata": {"future_return": -0.048691, "horizon_days": 21, "hist_return": 0.107032, "annualized_vol": 0.067197, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20170224_0671", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2017-02-24", "context_summary": "ICSH over past 60 days: cumulative return +0.2%, annualized vol 1.5%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=38.90, end=38.97, cumulative_return=+0.2%, annualized_volatility=1.5%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 244.006, 'unemployment': 4.6, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.2, 't10y3m_spread': 1.87, 'breakeven_10y': 2.03, 'hy_oas': 3.77, 'ig_oas': 1.23, 'ted_spread': 0.54, 'mortgage_30y': 4.16, 'vix': 11.710000038146973}\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": 0.00038, "explanation": "The actual 21-day forward return for ICSH starting 2017-02-24 was +0.04%, which classifies as 'flat'.", "metadata": {"future_return": 0.00038, "horizon_days": 21, "hist_return": 0.001681, "annualized_vol": 0.015424, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200520_0673", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-05-20", "context_summary": "LINK-USD over past 60 days: cumulative return +72.7%, annualized vol 78.5%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=2.27, end=3.92, cumulative_return=+72.7%, annualized_volatility=78.5%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 255.802, 'unemployment': 13.2, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.53, 't10y3m_spread': 0.57, 'breakeven_10y': 1.15, 'hy_oas': 7.35, 'ig_oas': 2.06, 'ted_spread': 0.24, 'mortgage_30y': 3.28, 'vix': 30.530000686645508}\nMarket regime: sideways\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": 0.085789, "explanation": "The actual 21-day forward return for LINK-USD starting 2020-05-20 was +8.58%, which classifies as 'positive'.", "metadata": {"future_return": 0.085789, "horizon_days": 21, "hist_return": 0.726735, "annualized_vol": 0.784926, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200806_0676", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2020-08-06", "context_summary": "VEA over past 60 days: cumulative return +16.5%, annualized vol 19.7%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=29.52, end=34.39, cumulative_return=+16.5%, annualized_volatility=19.7%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 259.316, 'unemployment': 8.4, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.44, 't10y3m_spread': 0.45, 'breakeven_10y': 1.61, 'hy_oas': 5.04, 'ig_oas': 1.37, 'ted_spread': 0.14, 'mortgage_30y': 2.99, 'vix': 22.989999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-08-05] Why MongoDB Stock Is Cheaper Than It Looks MongoDB, Inc. (NASDAQ: MDB) stock has climbed over 65% since the beginning of the year, trouncing the S&P 500's single-digit gains, and has attracted the attention of tech investors. MDB data by YCharts Along with the stock gains, the price-to-sales ratio has run up over 40%, causing some to flinch at its lofty valuation. But this cloud database specialist is worth the price. Let's take a deeper look at its business, the growth plans, and its valuation to see why this stock could be cheaper than it looks. The business of a cloud database MongoDB was founded in 2007 to create a database that could address the shortcomings of legacy relational databases in powering high-performance cloud-based applications. Since then, it has become a developer favorite, consistently ranked as the top non-relational database according to DB-Engines. This popularity has helped it reach $462 million in trailing 12-month revenues and serve more than 18,000 customers in 100 countries. Image source: Getty Images. Over the last three years, the company has had explosive growth, increasing its top line by a 61% compound annual growth rate from fiscal 2017 to its most recent fiscal year ending Jan. 31, 2020. This impressive trend continued into last quarter's 46% year-over-year top-line gain, but the company isn't profitable, as it's pouring its profits into growth efforts. A $977 million pile of cash and marketable securities provide the company with plenty of flexibility to operate this way for years. The company has two core products: MongoDB Enterprise Advanced (EA), its on-premise solution, and Atlas, its cloud-based offering. Atlas only made up 42% of its revenue last quarter, but it's growing faster at 75% year over year and is an important element in driving overall growth. Atlas is key to growth Atlas was released in 2016 as a way for software developers to experience the benefits of its product more easily. As a cloud-based subscription platform, developers just need a sign-on and a credit card to get started. This simple on-ramp allows information technology teams to experiment with the platform in non-mission-critical applications before committing to the technology to take over larger portions of the enterprise. This approach has been highly successful. Atlas customers have almost tripled from 5,700 in January 2018 to 16,800 in its most recent quarter ending April 30, 2020. What's even more exciting is that as a cloud product, the company can keep tabs on what developers are doing. This enables the company to better understand how the product is used, make improvements, and call on customers who've increased usage to discuss upselling opportunities. Although Atlas customers only average around $6,000 to $7,000 in revenue per year, it can be a path to its EA product that typically exceeds $100,000 annually. In its most recent quarter, MongoDB reported 780 customers spending more than $100,000 annually, up from 598 a ye\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": 0.010454, "explanation": "The actual 21-day forward return for VEA starting 2020-08-06 was +1.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.010454, "horizon_days": 21, "hist_return": 0.1649, "annualized_vol": 0.197195, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190606_0681", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2019-06-06", "context_summary": "MTUM over past 60 days: cumulative return +5.2%, annualized vol 10.6%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=101.42, end=106.70, cumulative_return=+5.2%, annualized_volatility=10.6%\nMacro context: {'fed_funds_rate': 2.38, 'cpi_yoy': 255.213, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.29, 't10y3m_spread': -0.23, 'breakeven_10y': 1.75, 'hy_oas': 4.48, 'ig_oas': 1.34, 'ted_spread': 0.17, 'mortgage_30y': 3.99, 'vix': 16.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-06-05] [\"Can Red-Hot AMD Stock Finally Take Out the $30 Level? Advanced Micro Devices (NASDAQ:) stock has held its own in choppy waters over the past month, outperforming both the stock market and other semiconductor names by a wide margin. Since the start of May, the S&P 500 has dropped more than 5%, and the iShares PHLX Semiconductor ETF (NASDAQ:) is off more than 15%. Source: Shutterstock Over that same stretch, AMD stock has actually risen more than 5%. Why did AMD stock outperform by such a wide margin during the May market rout? A few fundamental catalysts emerged in May, which showed that AMD\\u2019s non-cyclical market share expansion outlook remains intact. Investors continued to rally behind that outlook, ignoring trade-war worries, causing AMD stock to drift higher. Will this upturn of AMD stock continue? In the long-run, yes. AMD\\u2019s market-share expansion will persist for the foreseeable future, and as long as it does, AMD stock can remain well-positioned to reach $50 over the next few years. But in the short-run, the rally in AMD stock will likely be short-circuited yet again around the $30 level. That $30 level is a critical area which the stock hasn\\u2019t consistently ever held. Long-term growth fundamentals imply that a move over $30 by Advanced Micro Devices stock won\\u2019t be justified until the end of the year. As a result, while AMD stock will eventually take out the critical $30 level, it won\\u2019t do so anytime soon. AMD\\u2019s Growth Outlook Remains Healthy The long-term growth outlook of AMD has been, still is, and will remain for the foreseeable future healthy enough to move Advanced Micro Devices stock higher in a multi-year window. In a nutshell, AMD is the David of both the computer processing unit (CPU) and graphics processing unit (GPU) worlds. This David is fighting two Goliaths. In the CPU world, the Goliath is Intel (NASDAQ:), which has dominated the PC market for many years, and is now paralleling that dominance in the data center market. Meanwhile, in the GPU world, the Goliath is Nvidia (NASDAQ:), the graphics chip giant that has dominated the gaming market and is now dominating the artificial intelligence (AI) market. But David is finally putting up a fight against and winning share from Goliath, on both the CPU and GPU fronts, due to its faster innovation, promising product lineup, and expansion into new markets. As a result, AMD has generated healthy revenue growth, margin expansion, and profit growth over the past several years, pushing AMD stock considerably higher. In May, investors got confirmation that AMD\\u2019s market-share expansion remains as vigorous as ever. The company reported strong first-quarter numbers (on the heels of bad first quarter numbers from Intel), announced an impressive 7nm product road map which analysts said lays the groundwork for further market-share expansion, and won a graphics licensing deal with Samsung. Overall, AMD continues to win share from both Intel and Nvidia. Ultimat\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": 0.047143, "explanation": "The actual 21-day forward return for MTUM starting 2019-06-06 was +4.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.047143, "horizon_days": 21, "hist_return": 0.052056, "annualized_vol": 0.10604, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20170111_0684", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2017-01-11", "context_summary": "ICSH over past 60 days: cumulative return +0.1%, annualized vol 2.1%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=38.88, end=38.91, cumulative_return=+0.1%, annualized_volatility=2.1%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 243.618, 'unemployment': 4.7, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.19, 't10y3m_spread': 1.86, 'breakeven_10y': 1.95, 'hy_oas': 4.0, 'ig_oas': 1.29, 'ted_spread': 0.51, 'mortgage_30y': 4.2, 'vix': 11.489999771118164}\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": 0.00128, "explanation": "The actual 21-day forward return for ICSH starting 2017-01-11 was +0.13%, which classifies as 'flat'.", "metadata": {"future_return": 0.00128, "horizon_days": 21, "hist_return": 0.000863, "annualized_vol": 0.020561, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180119_0687", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2018-01-19", "context_summary": "HYG over past 60 days: cumulative return +0.4%, annualized vol 3.6%. Market regime: sideways.", "question": "Asset: HYG\nHistorical prices (past 60 trading days): start=56.25, end=56.46, cumulative_return=+0.4%, annualized_volatility=3.6%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 248.859, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.57, 't10y3m_spread': 1.17, 'breakeven_10y': 2.05, 'hy_oas': 3.35, 'ig_oas': 0.94, 'ted_spread': 0.31, 'mortgage_30y': 4.04, 'vix': 12.220000267028809}\nMarket regime: sideways\n\nPredict whether the return of HYG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.008294, "explanation": "The actual 21-day forward return for HYG starting 2018-01-19 was -0.83%, which classifies as 'flat'.", "metadata": {"future_return": -0.008294, "horizon_days": 21, "hist_return": 0.003668, "annualized_vol": 0.035518, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210715_0692", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2021-07-15", "context_summary": "XRP-USD over past 60 days: cumulative return -57.3%, annualized vol 125.8%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=1.45, end=0.62, cumulative_return=-57.3%, annualized_volatility=125.8%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 271.903, 'unemployment': 5.4, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.14, 't10y3m_spread': 1.31, 'breakeven_10y': 2.34, 'hy_oas': 3.1, 'ig_oas': 0.89, 'ted_spread': 0.07, 'mortgage_30y': 2.9, 'vix': 16.329999923706055}\nMarket regime: sideways\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": 0.22818, "explanation": "The actual 21-day forward return for XRP-USD starting 2021-07-15 was +22.82%, which classifies as 'positive'.", "metadata": {"future_return": 0.22818, "horizon_days": 21, "hist_return": -0.572958, "annualized_vol": 1.257919, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181017_0695", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2018-10-17", "context_summary": "^VIX over past 60 days: cumulative return +42.0%, annualized vol 122.4%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=12.41, end=17.62, cumulative_return=+42.0%, annualized_volatility=122.4%\nMacro context: {'fed_funds_rate': 2.18, 'cpi_yoy': 252.772, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.29, 't10y3m_spread': 0.86, 'breakeven_10y': 2.13, 'hy_oas': 3.45, 'ig_oas': 1.16, 'ted_spread': 0.18, 'mortgage_30y': 4.9, 'vix': 17.6200008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-16] [\"12 Stocks To Watch For October 16, 2018\", \"Barclays Maintains Overweight on Adobe, Raises Price Target to $304\", \"Adobe shares are trading higher after the company reaffirmed Q4 guidance and said it expects revenue to increase 20% in 2019.\", \"26 Stocks Moving In Tuesday's Pre-Market Session\", \"10 Biggest Price Target Changes For Tuesday\", \"40 Stocks Moving In Tuesday's Mid-Day Session\", \"40 Stocks Moving In Tuesday's Mid-Day Session\", \"10 Biggest Price Target Changes For Tuesday\", \"26 Stocks Moving In Tuesday's Pre-Market Session\", \"Adobe shares are trading higher after the company reaffirmed Q4 guidance and said it expects revenue to increase 20% in 2019.\", \"Barclays Maintains Overweight on Adobe, Raises Price Target to $304\", \"12 Stocks To Watch For October 16, 2018\", \"S&P 500 Movers: GWW, ADBE In early trading on Tuesday, shares of Adobe ( ADBE ) topped the list of the day's best performing components of the S&P 500 index, trading up 7.3%. Year to date, Adobe registers a 45.7% gain. And the worst performing S&P 500 component thus far on the day is W.W. Grainger ( GWW ), trading down 12.8%. W.W. Grainger is showing a gain of 17.3% looking at the year to date performance. Two other components making moves today are Blackrock ( BLK ), trading down 4.5%, and Progressive ( PGR ), trading up 5.0% on the day. VIDEO: S&P 500 Movers: GWW, ADBE The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe Stock Is Floating in the Sunny Skies of the Cloud InvestorPlace - Stock Market News, Stock Advice & Trading Tips The chief benefits of open source go to the users. The cloud is a product of open source. I've been writing those two sentences, repeatedly, for over a decade now, and they're as true today as they ever were. Companies that fully embraced the economics of cloud have ridden it to glory. Few have done so as spectacularly as Adobe Systems (NASDAQ: ADBE ). By the standards of Silicon Valley it's old money, founded in 1982, its squat skyscraper a few blocks from the San Jose convention center. John Warnock and Charles Geschke founded Adobe around PC tools like PostScript and Photoshop. Shantanu Narayen re-invented the company by embracing the cloud and subscription as a service. Over the last five years the stock is up 342%, even with the recent tech wreck taking 13% out of the price. Clear Sailing Adobe said Oct. 15 it expects top-line growth of 20% next year, to $10.8 billion, well above previous analyst estimates , and the stock rose almost 6% in response . 10 Small-Caps With Straight-A Potential Both the recent fall and this rise are unsurprising. Even at its October 15 close of $238, Adobe was selling at an eye-popping 49 times earnings. The October 16 gains will send that even higher. But when you've got Amazon.Com (NASDAQ: AMZ\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": 0.148276, "explanation": "The actual 21-day forward return for ^VIX starting 2018-10-17 was +14.83%, which classifies as 'positive'.", "metadata": {"future_return": 0.148276, "horizon_days": 21, "hist_return": 0.419823, "annualized_vol": 1.223724, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20181011_0698", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2018-10-11", "context_summary": "VNQI over past 60 days: cumulative return -8.0%, annualized vol 12.6%. Market regime: sideways.", "question": "Asset: VNQI\nHistorical prices (past 60 trading days): start=42.11, end=38.76, cumulative_return=-8.0%, annualized_volatility=12.6%\nMacro context: {'fed_funds_rate': 2.18, 'cpi_yoy': 252.772, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.34, 't10y3m_spread': 0.95, 'breakeven_10y': 2.16, 'hy_oas': 3.51, 'ig_oas': 1.13, 'ted_spread': 0.2, 'mortgage_30y': 4.71, 'vix': 22.959999084472656}\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": 0.026171, "explanation": "The actual 21-day forward return for VNQI starting 2018-10-11 was +2.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.026171, "horizon_days": 21, "hist_return": -0.079561, "annualized_vol": 0.126345, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220328_0701", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2022-03-28", "context_summary": "DOT-USD over past 60 days: cumulative return +23.8%, annualized vol 67.1%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=18.13, end=22.45, cumulative_return=+23.8%, annualized_volatility=67.1%\nMacro context: {'fed_funds_rate': 0.33, 'cpi_yoy': 287.674, 'unemployment': 3.7, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.18, 't10y3m_spread': 1.93, 'breakeven_10y': 2.86, 'hy_oas': 3.51, 'ig_oas': 1.29, 'ted_spread': 0.09, 'mortgage_30y': 4.42, 'vix': 20.809999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-03-27] \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": -0.173001, "explanation": "The actual 21-day forward return for DOT-USD starting 2022-03-28 was -17.30%, which classifies as 'negative'.", "metadata": {"future_return": -0.173001, "horizon_days": 21, "hist_return": 0.237833, "annualized_vol": 0.670518, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20210603_0704", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2021-06-03", "context_summary": "ICSH over past 60 days: cumulative return +0.1%, annualized vol 0.3%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=42.38, end=42.41, cumulative_return=+0.1%, annualized_volatility=0.3%\nMacro context: {'fed_funds_rate': 0.06, 'cpi_yoy': 270.654, 'unemployment': 5.9, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.46, 't10y3m_spread': 1.57, 'breakeven_10y': 2.44, 'hy_oas': 3.31, 'ig_oas': 0.9, 'ted_spread': 0.11, 'mortgage_30y': 2.95, 'vix': 17.479999542236328}\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": -0.000198, "explanation": "The actual 21-day forward return for ICSH starting 2021-06-03 was -0.02%, which classifies as 'flat'.", "metadata": {"future_return": -0.000198, "horizon_days": 21, "hist_return": 0.000713, "annualized_vol": 0.003086, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160428_0707", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2016-04-28", "context_summary": "ICSH over past 60 days: cumulative return +0.0%, annualized vol 1.0%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=38.58, end=38.58, cumulative_return=+0.0%, annualized_volatility=1.0%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 238.992, 'unemployment': 5.1, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 1.04, 't10y3m_spread': 1.63, 'breakeven_10y': 1.68, 'hy_oas': 6.25, 'ig_oas': 1.53, 'ted_spread': 0.4, 'mortgage_30y': 3.59, 'vix': 13.770000457763672}\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": 0.000601, "explanation": "The actual 21-day forward return for ICSH starting 2016-04-28 was +0.06%, which classifies as 'flat'.", "metadata": {"future_return": 0.000601, "horizon_days": 21, "hist_return": 0.000201, "annualized_vol": 0.010067, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20211103_0711", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2021-11-03", "context_summary": "SOL-USD over past 60 days: cumulative return +48.3%, annualized vol 101.6%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=139.11, end=206.25, cumulative_return=+48.3%, annualized_volatility=101.6%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 278.919, 'unemployment': 4.1, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.1, 't10y3m_spread': 1.51, 'breakeven_10y': 2.51, 'hy_oas': 3.21, 'ig_oas': 0.91, 'ted_spread': 0.1, 'mortgage_30y': 3.14, 'vix': 16.030000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-11-02] \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": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for SOL-USD starting 2021-11-03 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.482628, "annualized_vol": 1.016082, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20210720_0713", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2021-07-20", "context_summary": "IVV over past 60 days: cumulative return +2.3%, annualized vol 11.1%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=389.78, end=398.85, cumulative_return=+2.3%, annualized_volatility=11.1%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 271.903, 'unemployment': 5.4, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 0.98, 't10y3m_spread': 1.14, 'breakeven_10y': 2.24, 'hy_oas': 3.44, 'ig_oas': 0.93, 'ted_spread': 0.08, 'mortgage_30y': 2.88, 'vix': 22.5}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-07-19] This Segment of Tech Stocks Will Outpace the Rest Over the Next 4 Years Technology stocks have been the must-own sector for more than a couple of decades now. That's not apt to change in the foreseeable future either. If you think one technology stock is as good as another though, think again. They can be dramatically different when it comes to growth prospects, and enterprise software companies like Microsoft (NASDAQ: MSFT) and ServiceNow (NYSE: NOW) are poised to outgrow other tech names for the foreseeable future. That's the call from technology market research outfit Gartner (NYSE: IT) anyway, which recently posted its long-term IT spending outlook. The organization believes global tech spending will improve by 9% year over year in 2021, led by more than a 13% swell in software outlays. Unlike other technology arenas, however, enterprise software sales will remain abnormally brisk through 2025. Investors should make a point of holding exposure to this sliver of the tech sector during this time. Image source: Getty Images. Better than the rest All of the technology sector's key industries should benefit from IT spending growth this year, for the record, and this widespread progress is expected to persist through 2022. The rising tide isn't expected to lift all boats equally, however. The graphic below puts things in perspective. Services of all sorts will see steady growth through 2025, according to Gartner, and data center systems and device manufacturers are apt to fare even better. The standout area, however, is clearly enterprise software. Gartner estimates software spending will grow at a double-digit percentage pace every year through 2025. In fact, it will be the technology sector's only segment to achieve double-digit growth in any year except for this year's expected 13.9% growth in spending on devices, which is exaggerated this year due to last year's decline. Data source: Gartner Inc. Chart by author. And in case you're wondering, infrastructure software spending is projected to lead the way, albeit just barely. Spending on enterprise-level apps, or computer programs, should see almost as much growth, suggesting software spending plans are well balanced. Best of the best The stage may be set for growth, but which software stocks will make for the most productive picks? One of the most obvious beneficiaries of this projected growth is, of course, Microsoft. It's hardly a pure play, with offerings ranging from operating systems to video gaming to personal productivity to cloud computing. Its Intelligent Cloud division is now the company's single-biggest operating unit though, accounting for $15.1 billion of last quarter's revenue of $41.7 billion. Its cloud-management interface Azure saw a 46% year-over-year improvement in revenue, as enterprises embrace highly capable off-the-shelf solutions. Market researcher Canalys estimates Microsoft leveraged Azure to end Q1 with 19% of the world's cloud infrastructure spending market share, up \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": 0.018823, "explanation": "The actual 21-day forward return for IVV starting 2021-07-20 was +1.88%, which classifies as 'positive'.", "metadata": {"future_return": 0.018823, "horizon_days": 21, "hist_return": 0.023258, "annualized_vol": 0.111324, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210701_0716", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2021-07-01", "context_summary": "TIP over past 60 days: cumulative return +1.5%, annualized vol 2.1%. Market regime: sideways.", "question": "Asset: TIP\nHistorical prices (past 60 trading days): start=87.03, end=88.30, cumulative_return=+1.5%, annualized_volatility=2.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 270.654, 'unemployment': 5.9, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.2, 't10y3m_spread': 1.4, 'breakeven_10y': 2.32, 'hy_oas': 3.04, 'ig_oas': 0.86, 'ted_spread': 0.1, 'mortgage_30y': 3.02, 'vix': 15.829999923706056}\nMarket regime: sideways\n\nPredict whether the return of TIP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.013054, "explanation": "The actual 21-day forward return for TIP starting 2021-07-01 was +1.31%, which classifies as 'positive'.", "metadata": {"future_return": 0.013054, "horizon_days": 21, "hist_return": 0.014641, "annualized_vol": 0.020752, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190122_0718", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2019-01-22", "context_summary": "BIL over past 60 days: cumulative return +0.3%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=75.77, end=76.02, cumulative_return=+0.3%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 252.561, 'unemployment': 4.0, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.17, 't10y3m_spread': 0.38, 'breakeven_10y': 1.83, 'hy_oas': 4.27, 'ig_oas': 1.46, 'ted_spread': 0.4, 'mortgage_30y': 4.45, 'vix': 17.799999237060547}\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": 0.001301, "explanation": "The actual 21-day forward return for BIL starting 2019-01-22 was +0.13%, which classifies as 'flat'.", "metadata": {"future_return": 0.001301, "horizon_days": 21, "hist_return": 0.003361, "annualized_vol": 0.001622, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210215_0720", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2021-02-15", "context_summary": "BNB-USD over past 60 days: cumulative return +352.0%, annualized vol 109.4%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=30.18, end=136.43, cumulative_return=+352.0%, annualized_volatility=109.4%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 263.579, 'unemployment': 6.2, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.09, 't10y3m_spread': 1.16, 'breakeven_10y': 2.21, 'hy_oas': 3.48, 'ig_oas': 0.97, 'ted_spread': 0.15, 'mortgage_30y': 2.73, 'vix': 19.96999931335449}\nMarket regime: sideways\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": 0.85477, "explanation": "The actual 21-day forward return for BNB-USD starting 2021-02-15 was +85.48%, which classifies as 'positive'.", "metadata": {"future_return": 0.85477, "horizon_days": 21, "hist_return": 3.519809, "annualized_vol": 1.094309, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180801_0722", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2018-08-01", "context_summary": "VNQ over past 60 days: cumulative return +6.3%, annualized vol 11.5%. Market regime: sideways.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=57.18, end=60.78, cumulative_return=+6.3%, annualized_volatility=11.5%\nMacro context: {'fed_funds_rate': 1.91, 'cpi_yoy': 251.214, 'unemployment': 3.8, 'gdp_growth_qoq': 20276.154, 't10y2y_spread': 0.29, 't10y3m_spread': 0.93, 'breakeven_10y': 2.12, 'hy_oas': 3.46, 'ig_oas': 1.16, 'ted_spread': 0.36, 'mortgage_30y': 4.54, 'vix': 12.829999923706056}\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": "positive", "answer_numeric": 0.014541, "explanation": "The actual 21-day forward return for VNQ starting 2018-08-01 was +1.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.014541, "horizon_days": 21, "hist_return": 0.062841, "annualized_vol": 0.114934, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20221021_0724", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-10-21", "context_summary": "ETH-USD over past 60 days: cumulative return -20.9%, annualized vol 56.8%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1622.51, end=1283.20, cumulative_return=-20.9%, annualized_volatility=56.8%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 298.007, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.38, 't10y3m_spread': 0.15, 'breakeven_10y': 2.51, 'hy_oas': 4.89, 'ig_oas': 1.69, 'ted_spread': 0.09, 'mortgage_30y': 6.94, 'vix': 29.979999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-20] \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": -0.009789, "explanation": "The actual 21-day forward return for ETH-USD starting 2022-10-21 was -0.98%, which classifies as 'flat'.", "metadata": {"future_return": -0.009789, "horizon_days": 21, "hist_return": -0.209124, "annualized_vol": 0.568116, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20171115_0726", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2017-11-15", "context_summary": "TLH over past 60 days: cumulative return -0.9%, annualized vol 5.4%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=107.20, end=106.27, cumulative_return=-0.9%, annualized_volatility=5.4%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 247.284, 'unemployment': 4.2, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.7, 't10y3m_spread': 1.12, 'breakeven_10y': 1.87, 'hy_oas': 3.84, 'ig_oas': 1.06, 'ted_spread': 0.18, 'mortgage_30y': 3.9, 'vix': 11.59000015258789}\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": "flat", "answer_numeric": 0.001858, "explanation": "The actual 21-day forward return for TLH starting 2017-11-15 was +0.19%, which classifies as 'flat'.", "metadata": {"future_return": 0.001858, "horizon_days": 21, "hist_return": -0.008738, "annualized_vol": 0.053835, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220623_0729", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2022-06-23", "context_summary": "SOL-USD over past 60 days: cumulative return -65.6%, annualized vol 120.6%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=99.24, end=34.12, cumulative_return=-65.6%, annualized_volatility=120.6%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.957, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.1, 't10y3m_spread': 1.55, 'breakeven_10y': 2.54, 'hy_oas': 5.32, 'ig_oas': 1.54, 'ted_spread': 0.09, 'mortgage_30y': 5.78, 'vix': 28.950000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-22] \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": -0.027961, "explanation": "The actual 21-day forward return for SOL-USD starting 2022-06-23 was -2.80%, which classifies as 'negative'.", "metadata": {"future_return": -0.027961, "horizon_days": 21, "hist_return": -0.656156, "annualized_vol": 1.206289, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20200709_0731", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLT"], "decision_date": "2020-07-09", "context_summary": "TLT over past 60 days: cumulative return -1.6%, annualized vol 15.3%. Market regime: sideways.", "question": "Asset: TLT\nHistorical prices (past 60 trading days): start=140.47, end=138.26, cumulative_return=-1.6%, annualized_volatility=15.3%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 258.352, 'unemployment': 10.2, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.51, 't10y3m_spread': 0.52, 'breakeven_10y': 1.42, 'hy_oas': 6.06, 'ig_oas': 1.51, 'ted_spread': 0.12, 'mortgage_30y': 3.07, 'vix': 28.07999992370605}\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": "flat", "answer_numeric": 0.000726, "explanation": "The actual 21-day forward return for TLT starting 2020-07-09 was +0.07%, which classifies as 'flat'.", "metadata": {"future_return": 0.000726, "horizon_days": 21, "hist_return": -0.01574, "annualized_vol": 0.152637, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190726_0733", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2019-07-26", "context_summary": "XLF over past 60 days: cumulative return +2.6%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=24.34, end=24.99, cumulative_return=+2.6%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 255.802, 'unemployment': 3.7, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.22, 't10y3m_spread': -0.02, 'breakeven_10y': 1.8, 'hy_oas': 3.93, 'ig_oas': 1.15, 'ted_spread': 0.2, 'mortgage_30y': 3.75, 'vix': 12.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-25] [\"Asian markets little changed as investors await central bank decisions Stocks in Japan, Hong Kong rise slightly Asian markets were little changed in early trading Thursday, despite new record highs on Wall Street.\", \"Microsoft and 7 Other Tech Stocks That Yield Steady Payouts Technology stocks aren\\u2019t traditional dividend havens the way utilities, consumer staples, and other sectors have been. But that\\u2019s shifting as companies such as Microsoft, Apple, Cisco, and others operate mature businesses that throw off excess cash.\", \"Why App Stores Could Be an Early Target of Regulators Apple and Google take 30% on revenue generated from their app stores. That could be one area of interest as the Justice Department reviews online platforms.\", \"This GMO Strategist Is Bearish on U.S. Stocks but Positive on Modern Monetary Theory James Montier likes emerging markets, cites Monty Python, and is critical of Larry Summers\", \"Voice assistants gain new skills \\u2014 texting us, showing us graphics Multimodal responses to voice commands will make consumers more comfortable with artificial intelligence Multimodal responses to voice commands will make consumers more comfortable with artificial intelligence.\", \"U.S. government\\u2019s broadside against Big Tech could cause the stock rally to stumble Large technology companies have been the stock market leaders Large technology companies have been the stock market leaders.\", \"Big Tech could have avoided this antitrust mess with the stroke of a pen Humble advice to Alphabet, Amazon, Facebook and Apple: Get out your checkbooks Humble advice to Alphabet, Amazon, Facebook and Apple: Get out your checkbooks.\", \"Southwest takes drastic action to address 737 Max issues and stock is rewarded Earnings Watch: Alphabet and Amazon lurk on deck as antitrust interest heats up Air carriers have spent the past two weeks giving updates on the continued Boeing 737 Max groundings, and Southwest Airlines Co. just announced the most drastic plan so far.\", \"OK Google, tell us why your earnings growth is slowing down ... hello? Anyone there? Alphabet executives avoided discussing growth slowdown in last earnings report, and numbers don\\u2019t tell much of a story either As the parent company of Google nears its fiscal second quarter results on July 25, the chorus of disapproval over its evasive reporting policy has risen on Wall Street.\", \"A worrying theory after Equifax and Facebook settlements \\u2014 aggregated data is NOT enough to protect your privacy A new study says it\\u2019s possible to \\u2018reverse engineer\\u2019 anonymous data to identify individuals A new study says it\\u2019s possible to \\u2018reverse engineer\\u2019 anonymous data to identify individuals.\", \"Apple to acquire majority of Intel smartphone business for $1 billion\", \"Trump prods Republicans to back budget deal as he hails worker-pledge anniversary CEOs from Lockheed, Siemens join president at White House event President Donald Trump on Thursday urged House \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": -0.081562, "explanation": "The actual 21-day forward return for XLF starting 2019-07-26 was -8.16%, which classifies as 'negative'.", "metadata": {"future_return": -0.081562, "horizon_days": 21, "hist_return": 0.026434, "annualized_vol": 0.142999, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180316_0735", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2018-03-16", "context_summary": "BNO over past 60 days: cumulative return +2.3%, annualized vol 19.0%. Market regime: sideways.", "question": "Asset: BNO\nHistorical prices (past 60 trading days): start=17.48, end=17.89, cumulative_return=+2.3%, annualized_volatility=19.0%\nMacro context: {'fed_funds_rate': 1.43, 'cpi_yoy': 249.577, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.53, 't10y3m_spread': 1.05, 'breakeven_10y': 2.08, 'hy_oas': 3.62, 'ig_oas': 1.1, 'ted_spread': 0.44, 'mortgage_30y': 4.44, 'vix': 16.59000015258789}\nMarket regime: sideways\n\nPredict whether the return of BNO over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.086406, "explanation": "The actual 21-day forward return for BNO starting 2018-03-16 was +8.64%, which classifies as 'positive'.", "metadata": {"future_return": 0.086406, "horizon_days": 21, "hist_return": 0.023455, "annualized_vol": 0.189577, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190801_0737", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2019-08-01", "context_summary": "XRP-USD over past 60 days: cumulative return -27.9%, annualized vol 63.5%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.44, end=0.32, cumulative_return=-27.9%, annualized_volatility=63.5%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 255.802, 'unemployment': 3.7, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.13, 't10y3m_spread': -0.06, 'breakeven_10y': 1.76, 'hy_oas': 3.93, 'ig_oas': 1.14, 'ted_spread': 0.23, 'mortgage_30y': 3.75, 'vix': 16.1200008392334}\nMarket regime: sideways\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": -0.147723, "explanation": "The actual 21-day forward return for XRP-USD starting 2019-08-01 was -14.77%, which classifies as 'negative'.", "metadata": {"future_return": -0.147723, "horizon_days": 21, "hist_return": -0.278508, "annualized_vol": 0.635404, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200402_0740", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2020-04-02", "context_summary": "XLP over past 60 days: cumulative return -13.2%, annualized vol 22.8%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=52.61, end=45.68, cumulative_return=-13.2%, annualized_volatility=22.8%\nMacro context: {'fed_funds_rate': 0.06, 'cpi_yoy': 256.032, 'unemployment': 14.8, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.39, 't10y3m_spread': 0.53, 'breakeven_10y': 1.07, 'hy_oas': 8.17, 'ig_oas': 2.34, 'ted_spread': 0.9852, 'mortgage_30y': 3.5, 'vix': 43.34999847412109}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-04-01] [\"Apple Acquires DarkSky, Weather App To Be Pulled From Android\", \"Here's How The 'MAGA' Tech Giant Stocks Performed In Q1\", \"A Peek Into The Markets: US Stock Futures Tumble Ahead Of ADP, Manufacturing Reports\", \"Shares of several technology, semiconductor, and software companies are trading lower amid market weakness as macro concerns continue to grow as a result of the coronavirus pandemic. The White House said it expects a surge in cases over the next 2 weeks.\", \"Some Staples Stocks Bouncing Back After Sliding In Recent Rally As Caution Tightens Grip\", \"Apple Analyst Projects 'Multi-Quarter Impact' On iPhone Shipments From COVID-19 Pandemic\", \"Hearing Apple, Goldman To Let Card Holders Defer April Payments\", \"Is Roku Above Other Streamers \\u2013 A SWOT Approach\", \"Is Roku Above Other Streamers \\u2013 A SWOT Approach\", \"Hearing Apple, Goldman To Let Card Holders Defer April Payments\", \"Apple Analyst Projects 'Multi-Quarter Impact' On iPhone Shipments From COVID-19 Pandemic\", \"Some Staples Stocks Bouncing Back After Sliding In Recent Rally As Caution Tightens Grip\", \"Shares of several technology, semiconductor, and software companies are trading lower amid market weakness as macro concerns continue to grow as a result of the coronavirus pandemic. The White House said it expects a surge in cases over the next 2 weeks.\", \"A Peek Into The Markets: US Stock Futures Tumble Ahead Of ADP, Manufacturing Reports\", \"Here's How The 'MAGA' Tech Giant Stocks Performed In Q1\", \"Is Roku Above Other Streamers \\u2013 A SWOT Approach\", \"Hearing Apple, Goldman To Let Card Holders Defer April Payments\", \"Apple Analyst Projects 'Multi-Quarter Impact' On iPhone Shipments From COVID-19 Pandemic\", \"Some Staples Stocks Bouncing Back After Sliding In Recent Rally As Caution Tightens Grip\", \"Shares of several technology, semiconductor, and software companies are trading lower amid market weakness as macro concerns continue to grow as a result of the coronavirus pandemic. The White House said it expects a surge in cases over the next 2 weeks.\", \"A Peek Into The Markets: US Stock Futures Tumble Ahead Of ADP, Manufacturing Reports\", \"Here's How The 'MAGA' Tech Giant Stocks Performed In Q1\", \"Only one stock in the Dow rose during the first quarter \\u2014 and it was up by only one penny January through March was the worst quarter for the Dow Jones Industrial Average since 1987 January through March was the worst quarter for the Dow Jones Industrial Average since 1987.\", \"The Dow's 30 stocks are all falling, led by Boeing's 6+% selloff Shares of all 30 components of the Dow Jones Industrial Average are all falling in premarket trading Wednesday amid a broad stock market selloff, with Boeing Co.'s stock leading the way down by sinking 6.2%. Boeing's stock is starting the second quarter the way it ended the first quarter, in which it plummeted 54.2% to suffer its worst-ever quarterly performance. The stock's implied price decline ahead of Wednesday's open would shave about 63 po\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": 0.049162, "explanation": "The actual 21-day forward return for XLP starting 2020-04-02 was +4.92%, which classifies as 'positive'.", "metadata": {"future_return": 0.049162, "horizon_days": 21, "hist_return": -0.131764, "annualized_vol": 0.227633, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20201211_0742", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2020-12-11", "context_summary": "VTI over past 60 days: cumulative return +12.0%, annualized vol 18.2%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=157.34, end=176.28, cumulative_return=+12.0%, annualized_volatility=18.2%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 262.045, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.78, 't10y3m_spread': 0.84, 'breakeven_10y': 1.88, 'hy_oas': 4.08, 'ig_oas': 1.11, 'ted_spread': 0.14, 'mortgage_30y': 2.71, 'vix': 22.520000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-12-10] [\"Adobe Guides Q1, FY21 Above Estimates - Quick Facts (RTTNews) - While reporting financial results for the fourth quarter and fiscal 2020 on Thursday, software company Adobe, Inc. (ADBE) initiated earnings and revenue guidance for the first quarter and full-year 2021. For the first quarter, the company expects earnings of about $2.19 per share and adjusted earnings about $2.78 per share on revenues about $3.75 billion. On average, analysts polled by Thomson Reuters expect the company to report earnings of $2.59 per share on revenues of $3.50 billion for the quarter. Analysts' estimates typically exclude special items. For the fiscal 2021, the company now projects earnings of about $8.57 per share and adjusted earnings about $11.20 per share on revenues about $15.15 billion. The Street is looking for earnings of $11.17 per share on revenues of $14.78 billion for the year. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe Approves Repurchase Of Up To $15 Billion In Common Stock Through 2024 - Quick Facts (RTTNews) - Ahead of its virtual financial analyst meeting with investors and financial analysts on Thursday, software company Adobe, Inc. (ADBE) announced that its board of directors has approved a new stock repurchase authority, granting the company additional authority to repurchase up to $15 billion in common stock through its fiscal year 2024. The previous program authorizing the repurchase of up to $8 billion in common stock through fiscal year 2021 is expected to be exhausted in the first half of 2021. The new program is expected to be funded from Adobe's future cash flows from operations and is incorporated into the company's fiscal year 2021 financial targets. Adobe also said its total addressable market has expanded to approximately $147 billion by 2023. This is based on its proven ability to create new categories and consistently innovate across our creativity, digital documents and customer experience management businesses. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe Systems Inc. Q4 adjusted earnings Beat Estimates (RTTNews) - Adobe Systems Inc. (ADBE) released earnings for its fourth quarter that advanced from the same period last year. The company's bottom line came in at $2.25 billion, or $4.64 per share. This compares with $0.85 billion, or $1.74 per share, in last year's fourth quarter. Excluding items, Adobe Systems Inc. reported adjusted earnings of $1.36 billion or $2.81 per share for the period. Analysts had expected the company to earn $2.66 per share, according to figures compiled by Thomson Reuters. Analysts' estimates typically exclude special items. The company's revenue for the quarter rose 14.4% to $3.42 billion from $2.99 billion last year. Adobe Systems Inc. earnings at a glance: -Earnings (Q4): $1.36 Bln. vs. $1.12 Bln. last yea\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": 0.045665, "explanation": "The actual 21-day forward return for VTI starting 2020-12-11 was +4.57%, which classifies as 'positive'.", "metadata": {"future_return": 0.045665, "horizon_days": 21, "hist_return": 0.12036, "annualized_vol": 0.181807, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160624_0745", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2016-06-24", "context_summary": "IYR over past 60 days: cumulative return +3.5%, annualized vol 11.6%. Market regime: sideways.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=57.90, end=59.92, cumulative_return=+3.5%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 0.39, 'cpi_yoy': 240.222, 'unemployment': 4.9, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 0.96, 't10y3m_spread': 1.43, 'breakeven_10y': 1.5, 'hy_oas': 5.83, 'ig_oas': 1.54, 'ted_spread': 0.34, 'mortgage_30y': 3.56, 'vix': 17.25}\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": 0.076816, "explanation": "The actual 21-day forward return for IYR starting 2016-06-24 was +7.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.076816, "horizon_days": 21, "hist_return": 0.034965, "annualized_vol": 0.115992, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191218_0747", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2019-12-18", "context_summary": "MATIC-USD over past 60 days: cumulative return -13.1%, annualized vol 142.6%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.01, end=0.01, cumulative_return=-13.1%, annualized_volatility=142.6%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 258.63, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.26, 't10y3m_spread': 0.33, 'breakeven_10y': 1.75, 'hy_oas': 3.58, 'ig_oas': 1.03, 'ted_spread': 0.37, 'mortgage_30y': 3.73, 'vix': 12.289999961853027}\nMarket regime: sideways\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": 0.179717, "explanation": "The actual 21-day forward return for MATIC-USD starting 2019-12-18 was +17.97%, which classifies as 'positive'.", "metadata": {"future_return": 0.179717, "horizon_days": 21, "hist_return": -0.13061, "annualized_vol": 1.426438, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200224_0749", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2020-02-24", "context_summary": "TLH over past 60 days: cumulative return +4.5%, annualized vol 8.9%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=120.17, end=125.58, cumulative_return=+4.5%, annualized_volatility=8.9%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 259.25, 'unemployment': 3.5, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.12, 't10y3m_spread': -0.1, 'breakeven_10y': 1.61, 'hy_oas': 3.66, 'ig_oas': 1.05, 'ted_spread': 0.15, 'mortgage_30y': 3.49, 'vix': 17.079999923706055}\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": 0.087393, "explanation": "The actual 21-day forward return for TLH starting 2020-02-24 was +8.74%, which classifies as 'positive'.", "metadata": {"future_return": 0.087393, "horizon_days": 21, "hist_return": 0.045083, "annualized_vol": 0.088866, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220607_0751", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2022-06-07", "context_summary": "XLY over past 60 days: cumulative return -7.2%, annualized vol 35.6%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=80.40, end=74.63, cumulative_return=-7.2%, annualized_volatility=35.6%\nMacro context: {'fed_funds_rate': 0.83, 'cpi_yoy': 294.957, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.31, 't10y3m_spread': 1.78, 'breakeven_10y': 2.76, 'hy_oas': 4.19, 'ig_oas': 1.37, 'ted_spread': 0.09, 'mortgage_30y': 5.09, 'vix': 25.06999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-06] [\"Stock Market News for June 6, 2022 U.S. stocks ended sharply lower on Friday as a better-than-expected jobs report reignited fears that the Fed would continue with its aggressive monetary policy and go for steep rate hikes in the coming months. All the major indexes ended in negative territory. How Did The Benchmarks Perform? The Dow Jones Industrial Average (DJI) shed 1% or 348.58 points to close at 32,899.70 points. The S&P 500 fell 1.6% or 68.28 points to finish at 4,108.54 points. Consumer discretionary and tech stocks were the worst performers. The Consumer Discretionary Select Sector SPDR (XLY) and the Technology Select Sector SPDR (XLK) declined 2.9% and 2.4%, respectively. Ten of the 11 sectors of the benchmark index ended in negative territory. The tech-heavy Nasdaq slid 2.5% or 304.16 points to end at 12,012.73 points. The fear-gauge CBOE Volatility Index (VIX) was up 0.28% to 24.79. Decliners outnumbered advancers on the NYSE by a 2.68-to-1 ratio. On Nasdaq, a 1.79-to-1 ratio favored declining issues. A total of 9.42 billion shares were traded on Friday, lower than the last 20-session average of 12.89 billion. Steeper Rate Hike Fears Worry Investors Stocks fell suffered once again on Friday on a holiday-shortened week as data showed nonfarm payrolls rose better than expected in May. This ate into expectations of the Fed slowing down on steep rate hikes in the coming months. The Fed has so far gone for rate hikes by 75 basis points in its last two meetings and steeper hikes are expected in the coming months in a bid to control decades-high inflation. This at the same time reignited fears that steeper rate hikes could push the country into an economic slowdown. Investors, thus, couldn\\u2019t welcome the impressive jobs data on Friday. Growing worries of investors could be seen in the bond market, as investors aggressively sold Treasurys across the board. The benchmark 10-year Treasury yield rose 5 basis points following the jobs report and crossed the 2.9% mark. Tech stocks were the biggest losers as a result of this. Shares of Apple Inc. AAPL declined 3.9%, while Amazon.com, Inc. AMZN finished 2.5% lower. Apple has a Zacks Rank #3 (Hold). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. Economic Data The May jobs data released on Friday came in impressive but raised worries for investors. The Bureau of Labor Statistics said that the U.S. economy added 390,000 jobs in May, higher than economists\\u2019 expectations of a gain of 328,000. Also, the unemployment rate remained unchanged at 3.6% in May, slightly above the lowest level since December 1969. Average hourly wage gains also remained strong in May, increasing 0.3% from April, a shade lower than expectations of 0.4%. On a year-over-year basis, average hourly wages increased 5.2%, which came in line with expectations. Weekly Roundup All the three major indexes ended the week in the red. The Dow and the S&P 500 lost 0.9% and 1.2%, respectively, for the\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": -0.048274, "explanation": "The actual 21-day forward return for XLY starting 2022-06-07 was -4.83%, which classifies as 'negative'.", "metadata": {"future_return": -0.048274, "horizon_days": 21, "hist_return": -0.071692, "annualized_vol": 0.355861, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20221122_0753", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2022-11-22", "context_summary": "VEA over past 60 days: cumulative return +2.2%, annualized vol 22.5%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=36.55, end=37.35, cumulative_return=+2.2%, annualized_volatility=22.5%\nMacro context: {'fed_funds_rate': 3.83, 'cpi_yoy': 298.786, 'unemployment': 3.6, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.65, 't10y3m_spread': -0.58, 'breakeven_10y': 2.31, 'hy_oas': 4.64, 'ig_oas': 1.44, 'ted_spread': 0.09, 'mortgage_30y': 6.61, 'vix': 22.36000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-21] [\"Should Vanguard Mega Cap ETF (MGC) Be on Your Investing Radar? If you're interested in broad exposure to the Large Cap Blend segment of the US equity market, look no further than the Vanguard Mega Cap ETF (MGC), a passively managed exchange traded fund launched on 12/17/2007. The fund is sponsored by Vanguard. It has amassed assets over $3.62 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 Companies that find themselves in the large cap category typically have a market capitalization above $10 billion. Overall, they are usually a stable option, with less risk and more sure-fire cash flows 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 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 counterparts, other things remaining the same. Annual operating expenses for this ETF are 0.07%, making it one of the least expensive products in the space. It has a 12-month trailing dividend yield of 1.55%. 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. This ETF has heaviest allocation to the Information Technology sector--about 29.30% of the portfolio. Healthcare and Financials round out the top three. Looking at individual holdings, Apple Inc. (AAPL) accounts for about 8.48% of total assets, followed by Microsoft Corp. (MSFT) and Amazon.com Inc. (AMZN). The top 10 holdings account for about 33.08% of total assets under management. Performance and Risk MGC seeks to match the performance of the CRSP US Mega Cap Index before fees and expenses. The CRSP U.S. Mega Cap Index includes the largest U.S. companies, with a target of including the top 70% of investable market capitalization. The index includes securities traded on NYSE, NYSE Market, NASDAQ or ARCA. The ETF has lost about -17.90% so far this year and is down about -16.42% in the last one year (as of 11/21/2022). In the past 52-week period, it has traded between $124.31 and $169.35. The ETF has a beta of 1 and standard deviation of 25.25% for the trailing three-year period, making it a medium risk choice in the space. With about 239 holdings, it effectively diversifies company-specific risk. Alternatives Vanguard Mega Cap 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, MGC 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) and the SPDR\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": -0.000663, "explanation": "The actual 21-day forward return for VEA starting 2022-11-22 was -0.07%, which classifies as 'flat'.", "metadata": {"future_return": -0.000663, "horizon_days": 21, "hist_return": 0.021862, "annualized_vol": 0.22465, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160615_0755", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2016-06-15", "context_summary": "ACWI over past 60 days: cumulative return -0.5%, annualized vol 12.1%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=46.22, end=46.00, cumulative_return=-0.5%, annualized_volatility=12.1%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 240.222, 'unemployment': 4.9, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 0.88, 't10y3m_spread': 1.35, 'breakeven_10y': 1.45, 'hy_oas': 6.19, 'ig_oas': 1.59, 'ted_spread': 0.38, 'mortgage_30y': 3.6, 'vix': 20.5}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-06-14] [\"Are Smartphones Set For A Rebound? By now, slowing Chinese demand for smartphones is well known - Apple's stock (AAPL) has fallen 6.5% this year, dragging its Asian suppliers with it. But there is evidence that smartphone component prices are bottoming, which bodes well for Asian component suppliers, according to Morgan Stanley.READ MORE.\", \"Did Microsoft overpay for LinkedIn? Microsoft\\u2019s largest-ever acquisition follows Nokia write-off in 2015 Microsoft paid more than $26 billion for LinkedIn, hoping for a Windows moment akin to the 1990s.\", \"Deepak Chopra\\u2019s new app wants to show you how to live Jiyo is more of a soulmate than an app Jiyo is the alternative medicine guru\\u2019s latest venture.\", \"Here\\u2019s why U.S. investors might squeak past Brexit worries Critical information ahead of the U.S. open The financial world has turned a little, with German bunds now trading negative for the first time ever. Wipe away the chaos as our call of the day finds a reason why U.S. stocks still have some juice left.\", \"Apple shares gain 0.9% to $98.20 in early trade to top Dow industrials\", \"Five potential takeovers following the Microsoft-LinkedIn deal There are many large companies with ambitions to grow and lots of cash There are many large companies with ambitions to grow and lots of cash, writes Michael Brush.\", \"Apple\\u2019s WWDC: Drexel Loves \\u2018The Matrix,\\u2019 Others Praise \\u2018Enhancements\\u2019 Shares of (AAPL) are down 19 cents at $97.15, a day after the company held the keynote for its annual developer conference in San Francisco, as the Street continues to assess what it heard.Among the most bullish notes today is that of of , who reiterates his Buy rating and $185 price target, titling his report \\\"Building a bigger, stronger and smarter Planet Apple.\\\"White lauds what he calls the \\\"\\\": In our view, Apple's expansive digital matrix across software, services and hardware, that delivers a seamless experience to an installed base of 1 billion devices, will continue to differentiate Apple from its mobile device competitors. We find it virtually impossible for Android-based competitors to ever create a digital matrix that rivals \\\"Planet Apple\\\".White believes the company's application \\\"got a lot cooler with iOS 10 given the addition of full screen animations (e.g., fireworks, balloons, confetti) and invisible ink that hides a message until the recipient swipes over it.\\\"And he thinks the update of Apple's operating system, now called \\\"macOS,\\\" was \\\"a big update with Siri and Apple Pay finally finding its way to the Mac.\\\"Others were more muted in their praise.'s, who has a Buy rating on the shares, and a $120 price target, writes that none of the \\\"enhancements\\\" shown yesterday \\\"accelerate Service revenue\\u2019s ~23% YoY growth,\\\" but \\\"they do give confidence that Apple\\u2019s +90% loyalty rate will remain intact.\\\"He is sticking with his calculation for \\\"services revenue forecast for FY16 of $24.4bn, ~12% of total reve\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": 0.045996, "explanation": "The actual 21-day forward return for ACWI starting 2016-06-15 was +4.60%, which classifies as 'positive'.", "metadata": {"future_return": 0.045996, "horizon_days": 21, "hist_return": -0.004821, "annualized_vol": 0.12054, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200908_0757", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2020-09-08", "context_summary": "XLRE over past 60 days: cumulative return +2.8%, annualized vol 20.1%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=29.06, end=29.86, cumulative_return=+2.8%, annualized_volatility=20.1%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 259.997, 'unemployment': 7.8, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.58, 't10y3m_spread': 0.61, 'breakeven_10y': 1.7, 'hy_oas': 5.13, 'ig_oas': 1.35, 'ted_spread': 0.14, 'mortgage_30y': 2.93, 'vix': 30.75}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-04] [\"Asian markets slide, following Wall Street\\u2019s tumble Stocks fall in Tokyo, Hong Kong, Seoul Asian markets skidded Friday after Wall Street had its worst day since June, as investors\\u2019 exuberance faltered after a spate of record highs.\", \"Podcast: Nasdaq Composite Drops 5% Many of the pandemic\\u2019s hottest stocks saw steep declines on Thursday. The latest government jobs report looks worse than economists forecast. But spending on wireless spectrum licenses was up $4.5 billion last month.\", \"Coronavirus update: Global tally climbs above 26 million, U.S. above 6.1 million, amid concerns CDC will rush out a vaccine The global tally for confirmed cases of the coronavirus that causes COVID-19 climbed above 26 million on Thursday, while in the U.S. there were growing concerns that President Donald Trump\\u2019s administration will attempt to rush out a vaccine ahead of the November presidential election.\", \"Here are the biggest stock-market losers on Thursday as the tech sector tanks All S&P 500 sectors ended lower Thursday\\u2019s decline was broad, with all sectors of the S&P 500 ending lower.\", \"Just $5 and an iPhone can open the door to investing in the world\\u2019s rarest fine wines The pandemic has reinvigorated many people\\u2019s passion for hobbies and nostalgia, Rally\\u2019s co-founder says Rally\\u2019s wine offerings will have a combined value of $148,000 and include a \\u201905 Chateau Latour and 2016 Chateau Petrus\", \"Apple Stock Falls Again as the Nasdaq Keeps Dropping The Nasdaq\\u2019s loss in futures trading builds on Thursday\\u2019s sharp decline.\", \"Tech bloodbath aside, ride these two giants for the second half of the recovery, veteran analyst says Critical information for the U.S. trading day Never mind the carnage. One analyst says the second phase of the economic rebound, during the second half of this year and into 2021, will \\u201csupercharge\\u201d the fundamentals and growth trajectories of well positioned tech stocks\", \"Apple delays privacy policy change, much to the relief of Facebook, mobile ad sellers Digital advertising firms have dreaded the planned privacy changes that would require them to explain in their notifications why they are seeking tracking permissions Apple Inc. says it will delay until early next year changes to its privacy policy that Facebook Inc. and others claim will eviscerate advertising sales targeting users on iPhones and iPads.\", \"Apple Lost $180 Billion In Market Value Thursday. It\\u2019s the Biggest Loss For a Company Ever. Apple stock slid 8% on Thursday, a rotten day for technology shares. That translated to a loss of roughly $180 billion in the iPhone maker\\u2019s market capitalization.\", \"Salesforce.com Inc., Apple Inc. share losses lead Dow's 532-point fall\", \"Barron\\u2019s Daily: Tech Stocks Slide Again Trump takes aim at cities\\u2019 funding, \\u201cTenet\\u201d will be in many U.S. movie theaters this weekend, Fed\\u2019s Charles Evans says U.S. economy needs more support, and other ne\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": 0.023728, "explanation": "The actual 21-day forward return for XLRE starting 2020-09-08 was +2.37%, which classifies as 'positive'.", "metadata": {"future_return": 0.023728, "horizon_days": 21, "hist_return": 0.027828, "annualized_vol": 0.20137, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180907_0759", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2018-09-07", "context_summary": "VTI over past 60 days: cumulative return +3.9%, annualized vol 8.0%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=126.95, end=131.95, cumulative_return=+3.9%, annualized_volatility=8.0%\nMacro context: {'fed_funds_rate': 1.92, 'cpi_yoy': 252.182, 'unemployment': 3.7, 'gdp_growth_qoq': 20276.154, 't10y2y_spread': 0.24, 't10y3m_spread': 0.75, 'breakeven_10y': 2.08, 'hy_oas': 3.52, 'ig_oas': 1.21, 'ted_spread': 0.24, 'mortgage_30y': 4.54, 'vix': 14.649999618530272}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-09-06] [\"7 Lucrative Biotech Stocks With Up to 300% Upside InvestorPlace - Stock Market News, Stock Advice & Trading Tips Forget market dynamics. These biotechs are playing to their own tune. According to the Street's top analysts this can be a very lucrative path. Biotech stocks can spike massively on positive news - be it key trial results or regulatory approvals. Of course, the opposite is also true and the biotech sector can crash just as quickly on unexpected disappointments. But the key point remains: Biotechs provide an outlet away from the rest of the market to potentially make serious money. That's especially welcome in the month of September - a notoriously tricky time for the markets. Indeed, September has been the worst performing month of the year for the Dow Jones Industrial Average and the S&P 500 since 1950. Your Chance to Cash In With Legal Sports Betting With that in mind, let's now turn to these seven strong buy biotechs now. I used TipRanks to ensure two crucial points: 1) big support from the Street, especially from top-performing analysts and 2) eye-watering upside potential ahead. Now let's see how these stocks tick these two boxes: Biotech Stocks to Buy: ObsEva (OBSV) ObsEva (NASDAQ: OBSV ) is developing best-in-class drug candidates to improve women's reproductive health. The lead is Linzagolix (OBE2109), a potentially best-in-class orally-dosed GnRH antagonist to treat symptoms of endometriosis (Ph2b) and uterine fibroids (Ph3). Top HC Wainwright analyst Ram Selvaraju ( Profile & Recommendations ) is very bullish on the stock's potential. He has just reiterated his \\\"buy\\\" rating with a $44 price target. From current levels that indicates massive upside potential of 237%! He notes that just-released data from AbbVie Inc (NYSE: ABBV ) reduces the risk for OBSV's Linzagolix. \\\"In our view, the long-term efficacy for elagolix should bode well for future development of linzagolix in uterine fibroids, since both drugs are GnRH receptor antagonists and have shown comparable potency in clinical studies.\\\" However, one of the key advantages for Linzagolix is the potential to be administered in certain patients without needing add-back therapy (ABT). This is the addition of a small amount of the hormones estrogen and/or progesterone to reduce undesirable effects of GnRH. Overall, six analysts have published back-to-back buy ratings on OBSV stock. This is with a $32 price target (147% upside potential). See what other Top Analysts are saying about OBSV . Biotech Stocks to Buy: Tocagen Inc (TOCA) This cutting-edge biotech stock is at the forefront of cancer therapy. Tocagen Inc (NASDAQ: TOCA ) is developing an RRV platform that can selectively deliver therapeutic genes into the DNA of cancer cells. Right now, all eyes are on Toca 511 and Toca FC. These drugs are in pivotal Phase 3 trials for recurrent high-grade gliomas (HGGs), with data due in 1H19. These are extremely difficult to treat cancers. \\\"Given the robustness of overall dataset\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": -0.002395, "explanation": "The actual 21-day forward return for VTI starting 2018-09-07 was -0.24%, which classifies as 'flat'.", "metadata": {"future_return": -0.002395, "horizon_days": 21, "hist_return": 0.039417, "annualized_vol": 0.080437, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220902_0762", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2022-09-02", "context_summary": "EWJ over past 60 days: cumulative return -5.8%, annualized vol 17.6%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=51.33, end=48.36, cumulative_return=-5.8%, annualized_volatility=17.6%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 296.349, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.25, 't10y3m_spread': 0.29, 'breakeven_10y': 2.45, 'hy_oas': 5.08, 'ig_oas': 1.5, 'ted_spread': 0.09, 'mortgage_30y': 5.66, 'vix': 25.559999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-01] [\"Where Will Snap Stock Be in 1 Year? Snap's (NYSE: SNAP) stock popped nearly 9% on Aug. 31 after the company announced that it would lay off about 1,200 employees, or approximately 20% of its workforce, as it grapples with a severe slowdown. Snap will discontinue its investments in its Snap Originals videos, its Minis mini-programs, its video games, and its Pixy selfie drone. It will also shut down its location-based social networking app Zenly, which it acquired in 2017, and its music creation app Voisey, which it bought in 2020. In an internal memo, CEO Evan Spiegel said Snap's revenue had only risen about 8% year over year so far in the third quarter, which was \\\"well below\\\" its own expectations and would represent its slowest growth rate as a public company. Spiegel said Snap \\\"must now face the consequences\\\" of that slowdown and \\\"adapt to the market environment.\\\" Image source: Getty Images. Spiegel said Snap's restructuring would focus its future on just \\\"three strategic priorities: community growth, revenue growth, and augmented reality.\\\" Everything else would likely be cut. Two of Snap's top executives -- its chief business officer Jeremi Gorman and its vice-president for ad sales Peter Naylor -- also abruptly left the company and joined Netflix in that seismic shuffle. That's a lot of information for Snap's investors to process, so let's take a breath and review its prior problems, its aggressive turnaround plans, and the potential challenges to see if its stock can recover over the next 12 months. What happened to Snap? During Snap's investor day presentation last February, the company impressed the bulls by saying it could grow its annual revenue by more than 50% over the next few years. But since then, Snap's year-over-year growth in daily active users (DAUs), average revenue per user (ARPU), and total revenue have all significantly decelerated. PERIOD Q2 2021 Q3 2021 Q4 2021 Q1 2022 Q2 2022 DAU growth (all figures YOY) 23% 23% 20% 18% 18% ARPU growth (decline) 76% 28% 18% 17% (4%) Revenue growth 116% 57% 42% 38% 13% Data source: Snap. YOY = year over year. Snap's growth ground to a halt for three main reasons. First, it vastly underestimated the impact of Apple's privacy changes on iOS, which enabled its users to opt out of data-tracking features and ads. Second, Snapchat likely lost a lot of its younger users to ByteDance's TikTok, even after it launched a similar Spotlight short-video feature in late 2020. TikTok also overtook Snapchat as the top social media platform for U.S. teens for the first time this spring, according to Piper Sandler's latest Taking Stock with Teens survey. And third, the entire ad sector cooled off as inflation, rising interest rates, and other macroeconomic headwinds rattled the broader economy. But despite facing all those bright red flags, Snap refused to officially abandon its long-term target of achieving more than 50% annual revenue growth. Analysts had expected Snap's revenue to rise 11% to $4.\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": -0.05041, "explanation": "The actual 21-day forward return for EWJ starting 2022-09-02 was -5.04%, which classifies as 'negative'.", "metadata": {"future_return": -0.05041, "horizon_days": 21, "hist_return": -0.057896, "annualized_vol": 0.176099, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190218_0764", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2019-02-18", "context_summary": "IWM over past 60 days: cumulative return +5.3%, annualized vol 22.6%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=135.49, end=142.67, cumulative_return=+5.3%, annualized_volatility=22.6%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 253.319, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.14, 't10y3m_spread': 0.23, 'breakeven_10y': 1.86, 'hy_oas': 4.12, 'ig_oas': 1.32, 'ted_spread': 0.3, 'mortgage_30y': 4.37, 'vix': 14.90999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-15] [\"Your smartphone is killing your relationship \\u2014 and evolution is to blame Researchers have a new theory for why we\\u2019re so addicted to our phones Researchers have a new theory for why we\\u2019re so addicted to our phones.\", \"Google\\u2019s Waymo holds on to its driverless-car lead Waymo, GM\\u2019s Cruise test cars drive the longest without a hitch Driverless cars by Google\\u2019s Waymo drive the most \\u2014 and the most without incidents \\u2014 in California.\", \"Why Momentum Stocks Have Lost Their Momentum Momentum has taken a defensive tilt, and companies like Amazon.com, Apple, Boeing, and Netflix no longer make the cut.\", \"Apple video efforts may not help reaccelerate growth, says Jefferies Apple Inc. appears ready to launch its long-awaited video streaming service in the spring, but Jefferies analyst Tim O'Shea isn't yet convinced that the efforts will help Apple achieve an inflection in growth. \\\"Even with video, services growth is not enough to offset iPhone unit declines, which should persist through 2019 and beyond,\\\" he wrote. Apple is reportedly having trouble signing big potential video partners such as Netflix Inc. , which has been pushing back in general against Apple's take rate. \\\"The 30% revenue share could reduce the amount of third party video content in this service, limiting its potential,\\\" O'Shea said, though it's still not clear exactly what the company's revenue-sharing arrangements for the video service will be as the company has yet to announce the offering. While publishers like Netflix are rebelling against Apple's 30% cut of App Store revenue, the largest app there only accounts for 0.3% of total services revenue. \\\" For video, if a single major producer pulls out it would be a much bigger problem,\\\" O'Shea wrote. Apple shares are off 0.4% in premarket trading Friday. The stock has fallen 11% over the past three months, as the Dow Jones Industrial Average has risen 0.6%.\", \"Why are Democrats suddenly so stupid? Fighting for more equality isn\\u2019t the same as government running things \\u2014 badly The only way Democrats can lose to Trump is to promise to take away Americans\\u2019 cars, health insurance and economic freedom, writes Tim Mullaney.\", \"Missing the Recent Stock Market Rally Isn\\u2019t as Bad as It Seems The stock market is off to the best start of the year in more than three decades, but here are 5 reasons you shouldn\\u2019t be kicking yourself if you missed it.\", \"Get used to wild swings for this stock market, and thank the Fed for that, says analyst Critical information for the U.S. trading day Our call of the day, from Seema Shah, global investment strategist at Principal Global Investors, says get used data-driven volatility for stocks as the Fed leaves the market and investors hanging.\", \"Apple's stock slips 0.3%, is the only Dow component losing ground\", \"Stocks Were Down, but Berkshire Hathaway Didn\\u2019t Buy Much Berkshire Hathaway added a surprisingly small amount of stocks to its huge eq\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": -0.019033, "explanation": "The actual 21-day forward return for IWM starting 2019-02-18 was -1.90%, which classifies as 'negative'.", "metadata": {"future_return": -0.019033, "horizon_days": 21, "hist_return": 0.052954, "annualized_vol": 0.225842, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200417_0766", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2020-04-17", "context_summary": "XLI over past 60 days: cumulative return -26.9%, annualized vol 35.2%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=75.18, end=54.99, cumulative_return=-26.9%, annualized_volatility=35.2%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 256.032, 'unemployment': 14.8, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.41, 't10y3m_spread': 0.47, 'breakeven_10y': 1.07, 'hy_oas': 7.58, 'ig_oas': 2.34, 'ted_spread': 0.9852, 'mortgage_30y': 3.31, 'vix': 40.11000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-04-16] [\"Software Rises Above Semiconductors And Hardware As Tech Heads Into Earnings Season\", \"'Apple's only retail store in South Korea reopening April 18' -9to5Mac\", \"Morgan Stanley Misses On EPS, But Shows Strong Trading Results For Q1 As Banks Wrap Up\", \"Deutsche Bank Maintains Buy on Apple, Raises Price Target to $285\", \"Apple shares are trading higher after Deutsche Bank maintained its Buy rating on the stock and raised its price target from $270 to $285 per share.\", \"Comcast's Peacock Takes Well-Timed Flight\", \"Apple's Tim Cook Tells Staff Mgmt. Is Unclear When Employees Will Be Able To Return To Offices, Says Offices Will Likely Have Temperature Checks, Social Distancing Efforts\", \"S&P 500 Futures Up 3.2% After Hours; Many Other Stocks Moving Higher With Futures; Investors Reacting Favorably To White Phase Guidelines On Reopening Economy\", \"Big Stocks Moving After Hours As Market Cheers Gilead, 'Reopening' Updates\", \"Big Stocks Moving After Hours As Market Cheers Gilead, 'Reopening' Updates\", \"S&P 500 Futures Up 3.2% After Hours; Many Other Stocks Moving Higher With Futures; Investors Reacting Favorably To White Phase Guidelines On Reopening Economy\", \"Apple's Tim Cook Tells Staff Mgmt. Is Unclear When Employees Will Be Able To Return To Offices, Says Offices Will Likely Have Temperature Checks, Social Distancing Efforts\", \"Comcast's Peacock Takes Well-Timed Flight\", \"Apple shares are trading higher after Deutsche Bank maintained its Buy rating on the stock and raised its price target from $270 to $285 per share.\", \"Deutsche Bank Maintains Buy on Apple, Raises Price Target to $285\", \"Morgan Stanley Misses On EPS, But Shows Strong Trading Results For Q1 As Banks Wrap Up\", \"'Apple's only retail store in South Korea reopening April 18' -9to5Mac\", \"Big Stocks Moving After Hours As Market Cheers Gilead, 'Reopening' Updates\", \"S&P 500 Futures Up 3.2% After Hours; Many Other Stocks Moving Higher With Futures; Investors Reacting Favorably To White Phase Guidelines On Reopening Economy\", \"Apple's Tim Cook Tells Staff Mgmt. Is Unclear When Employees Will Be Able To Return To Offices, Says Offices Will Likely Have Temperature Checks, Social Distancing Efforts\", \"Comcast's Peacock Takes Well-Timed Flight\", \"Apple shares are trading higher after Deutsche Bank maintained its Buy rating on the stock and raised its price target from $270 to $285 per share.\", \"Deutsche Bank Maintains Buy on Apple, Raises Price Target to $285\", \"Morgan Stanley Misses On EPS, But Shows Strong Trading Results For Q1 As Banks Wrap Up\", \"'Apple's only retail store in South Korea reopening April 18' -9to5Mac\", \"Apple stock price target raised to $285 from $270 at Deutsche Bank\", \"Apple is working on high-end over-the-ear headphones: report Apple Inc. has seen considerable success with its AirPods earphones and now the company is looking to make high-end over-the-ear wireless headphones to add to its product lineup, according to a Bloomberg report Thursday. The story, which cites mult\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": 0.004437, "explanation": "The actual 21-day forward return for XLI starting 2020-04-17 was +0.44%, which classifies as 'flat'.", "metadata": {"future_return": 0.004437, "horizon_days": 21, "hist_return": -0.26857, "annualized_vol": 0.351652, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210817_0768", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2021-08-17", "context_summary": "BNB-USD over past 60 days: cumulative return +23.9%, annualized vol 70.5%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=336.81, end=417.47, cumulative_return=+23.9%, annualized_volatility=70.5%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 272.676, 'unemployment': 5.1, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.05, 't10y3m_spread': 1.2, 'breakeven_10y': 2.36, 'hy_oas': 3.38, 'ig_oas': 0.93, 'ted_spread': 0.07, 'mortgage_30y': 2.87, 'vix': 16.1200008392334}\nMarket regime: sideways\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": 0.038814, "explanation": "The actual 21-day forward return for BNB-USD starting 2021-08-17 was +3.88%, which classifies as 'positive'.", "metadata": {"future_return": 0.038814, "horizon_days": 21, "hist_return": 0.239486, "annualized_vol": 0.70475, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220701_0770", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2022-07-01", "context_summary": "DOT-USD over past 60 days: cumulative return -53.0%, annualized vol 114.5%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=14.98, end=7.04, cumulative_return=-53.0%, annualized_volatility=114.5%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.957, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.06, 't10y3m_spread': 1.26, 'breakeven_10y': 2.33, 'hy_oas': 5.87, 'ig_oas': 1.64, 'ted_spread': 0.09, 'mortgage_30y': 5.7, 'vix': 28.709999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-30] \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": 0.086098, "explanation": "The actual 21-day forward return for DOT-USD starting 2022-07-01 was +8.61%, which classifies as 'positive'.", "metadata": {"future_return": 0.086098, "horizon_days": 21, "hist_return": -0.53, "annualized_vol": 1.145376, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20180302_0772", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2018-03-02", "context_summary": "BIL over past 60 days: cumulative return +0.2%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=74.64, end=74.81, cumulative_return=+0.2%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 249.577, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.59, 't10y3m_spread': 1.18, 'breakeven_10y': 2.1, 'hy_oas': 3.59, 'ig_oas': 1.04, 'ted_spread': 0.42, 'mortgage_30y': 4.43, 'vix': 22.46999931335449}\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": 0.000656, "explanation": "The actual 21-day forward return for BIL starting 2018-03-02 was +0.07%, which classifies as 'flat'.", "metadata": {"future_return": 0.000656, "horizon_days": 21, "hist_return": 0.002244, "annualized_vol": 0.002155, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210201_0774", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2021-02-01", "context_summary": "XLB over past 60 days: cumulative return +7.1%, annualized vol 21.3%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=29.73, end=31.84, cumulative_return=+7.1%, annualized_volatility=21.3%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 262.687, 'unemployment': 6.4, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.0, 't10y3m_spread': 1.05, 'breakeven_10y': 2.13, 'hy_oas': 3.84, 'ig_oas': 1.03, 'ted_spread': 0.14, 'mortgage_30y': 2.73, 'vix': 33.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-01-29] Dolby Laboratories Stock Could Drop To $75 Dolby Laboratories stock (NYSE: DLB) is up around 35% since the beginning of 2020, and at the current price around $90 per share, we believe that Dolby Laboratories stock has over 15% potential downside. Why is that? Our belief stems from the fact that DLB stock is up 2x its low in March this year, while the S&P has moved a little over 70% in comparison. Further, after posting weak Q4 2020 numbers, and with demand struggling to rise to pre-Covid levels, we believe Dolby stock could slide lower. Our dashboard What Factors Drove 51% Change In Dolby Laboratories Stock Between 2018 And Now? provides the key numbers behind our thinking, and we explain more below. Dolby Laboratories specializes in audio noise reduction and audio encoding/compression software and hardware, licensing its technology to sound system manufacturers. Dolby\u2019s price rise since 2018 came due to a 13% rise in revenue per share (RPS), driven by a 10% rise in revenue combined with a 3% drop in the outstanding share count. Further, DLB\u2019s P/S (price-to-sales) ratio shrank from 6.1x in 2018 to 5.6x in 2019, but has since jumped to 8.1x, riding the rally in technology stocks. We believe that given Dolby\u2019s weak Q4 \u201920 performance, there is a possible downside risk for the P/S multiple. So what\u2019s the likely trigger and timing to this downside? The global spread of coronavirus and the resulting lockdowns have led to a drop in demand for medium to large scale sound systems, as theaters have remained closed and large-scale events are not as frequent, due to the pandemic. This has led to a drop in demand for Dolby\u2019s products, which is evident from their Q4 2020 results, where revenue came in at $1.16 billion vs $1.24 billion in 2019. Products and services revenue dropped almost 40% from $134 million to $83 million over this period. Further, as operating expenses didn\u2019t drop at the same rate as revenue, operating margins fell to 18.8% in FY\u201920 vs 20.7% in FY \u201919. Despite a lower effective tax rate, EPS came in lower at $2.30 vs $2.51 in 2019. Going forward, we expect revenues to stay weak in the near to medium term, and if the company is not able to control expenses, we believe the stock will see its P/S multiple decline from the current level of 8.1x to around 7x, which combined with a reduction in revenues and margins could result in the stock price shrinking to as low as $75, a downside of more than 15% from the current price near $90. may have moved, 2020 has created many pricing discontinuities which can offer attractive trading opportunities. For example, you'll be surprised how counter-intuitive the stock valuation is for Intel vs Cisco. \\n\\nBased on article theme, variations to \\\"While may have moved\\\" can be (a) While may be overvalued (or undervalued) (b) While can move (c) Although may not be attractive (d) While is worth considering\"}\" data-sheets-userformat=\"{\"2\":1049345,\"3\":{\"1\":0},\"11\":4,\"12\":0,\"23\":1}\" data-sheets-textstyleruns=\"{\"1\":\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": 0.050511, "explanation": "The actual 21-day forward return for XLB starting 2021-02-01 was +5.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.050511, "horizon_days": 21, "hist_return": 0.070784, "annualized_vol": 0.213317, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220125_0776", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2022-01-25", "context_summary": "BTC-USD over past 60 days: cumulative return -31.6%, annualized vol 50.7%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=53569.77, end=36654.33, cumulative_return=-31.6%, annualized_volatility=50.7%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 282.543, 'unemployment': 4.0, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.76, 't10y3m_spread': 1.56, 'breakeven_10y': 2.38, 'hy_oas': 3.44, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 3.56, 'vix': 29.89999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-24] \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": 0.206235, "explanation": "The actual 21-day forward return for BTC-USD starting 2022-01-25 was +20.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.206235, "horizon_days": 21, "hist_return": -0.315765, "annualized_vol": 0.50697, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20201002_0778", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2020-10-02", "context_summary": "ACWI over past 60 days: cumulative return +6.2%, annualized vol 15.5%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=68.92, end=73.19, cumulative_return=+6.2%, annualized_volatility=15.5%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.54, 't10y3m_spread': 0.59, 'breakeven_10y': 1.63, 'hy_oas': 5.36, 'ig_oas': 1.43, 'ted_spread': 0.14, 'mortgage_30y': 2.88, 'vix': 26.700000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-10-01] BUZZ-U.S. STOCKS ON THE MOVE-Walt Disney, Amazon.com, Ford Motor, Skyworks Eikon search string for individual stock moves: STXBZ The Day Ahead newsletter: http://tmsnrt.rs/2ggOmBi The Morning News Call newsletter: http://tmsnrt.rs/2fwPLTh Wall Street's main indexes jumped at the open on Thursday as investors bet on more fiscal stimulus after data showed a recovery in the labor market was cooling. .N At 10:51 a.m. ET, the Dow Jones Industrial Average .DJI was up 0.33% at 27,872.05. The S&P 500 .SPX was up 0.38% at 3,375.8 and the Nasdaq Composite .IXIC was up 0.88% at 11,266.005. The top three S&P 500 .PG.INX percentage gainers: ** ETSY Inc , up 4.9% ** Autodesk Inc , up 3.1% ** Gap Inc , up 3.1% The top three S&P 500 .PL.INX percentage losers: ** Valero Energy , down 6.3% ** Halliburton Co , down 5.9% ** Hess Corp , down 4.6% The top three NYSE .PG.N percentage gainers: ** American Equity Investment Life Holding Co , up 36.3% ** SailPoint Technologies Holdings Inc , up 14.3% ** Leaf Group Ltd , up 11% The top three NYSE .PL.N percentage losers: ** Mizuho Financial Group Inc , down 90% ** Ambow Education Holding Ltd , down 17.2% ** BBX Capital Corp , down 16% The top three Nasdaq .PG.O percentage gainers: ** Solid Biosciencs Inc , up 127.6% ** Enlivex Therapeutics Ltd , up 52.5% ** AMAG Pharmaceuticals Inc , up 43.1% The top three Nasdaq .PL.O percentage losers: ** LogicBio Therapeutics Inc , down 33% ** Lixiang Education Holding Co Ltd , down 22.6% ** Kismet Acquisition Once Corp , down 21.1% ** Amazon.com Inc AMZN.O: up 1.2% BUZZ-Amazon.com: Pivotal says ad business underappreciated, boosts PT to Street high ** Snowflake Inc SNOW.N: down 3.3% BUZZ-Jefferies starts coverage on the sidelines, cites valuation ** Houghton Mifflin Harcourt Co HMHC.O: up 16.8% BUZZ-Soars on restructuring plan; to slash 22% jobs ** Cyclerion Therapeutics Inc CYCN.O: up 2.0% BUZZ-Up on sickle cell, nervous system disease study updates ** Skyworks SWKS.O: up 1.5% BUZZ-Cowen hikes PT as OEMs seek to fill Huawei void ** VAALCO Energy Inc EGY.N: up 6.5% BUZZ-Jumps on Q3 production outlook ** Bed Bath & Beyond Inc BBBY.O: up 30.0% BUZZ-Surges as co swings to quarterly profit ** Abbott Laboratories ABT.N: up 0.8% BUZZ-Up after Air Canada says finalizing order for 25,000 COVID-19 tests ** Pfizer Inc PFE.N: down 0.6% BUZZ-Obtains FDA 'Fast Track' designation for muscle degeneration therapy ** Pennsylvania Real Estate Investment Trust: PEI.N: up 3.2% BUZZ-Up on securing one-month extension to liquidity facility ** Advanced Emissions Solutions Inc ADES.O: up 36.9% BUZZ-Surges on 15-year carbon supply contract ** Enlivex Therapeutics Ltd ENLV.O: up 52.5% BUZZ-Surges on positive data from potential COVID-19 treatment ** Gridsum Holding Inc GSUM.O: up 39.5% BUZZ-Soars on take-private offer ** American Equity Investment Life Holding Co AEL.N: up 36.4% BUZZ-Jumps on report of Athene, MassMutual $3-bln-plus takeover bid ** Papa John's International Inc PZZA.O: up 3.2% BUZZ-KeyBanc star\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": -0.011388, "explanation": "The actual 21-day forward return for ACWI starting 2020-10-02 was -1.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.011388, "horizon_days": 21, "hist_return": 0.061989, "annualized_vol": 0.154707, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220412_0780", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2022-04-12", "context_summary": "AVAX-USD over past 60 days: cumulative return -9.3%, annualized vol 84.4%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=81.73, end=74.17, cumulative_return=-9.3%, annualized_volatility=84.4%\nMacro context: {'fed_funds_rate': 0.33, 'cpi_yoy': 288.561, 'unemployment': 3.7, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.29, 't10y3m_spread': 2.02, 'breakeven_10y': 2.86, 'hy_oas': 3.73, 'ig_oas': 1.22, 'ted_spread': 0.09, 'mortgage_30y': 4.72, 'vix': 24.3700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-11] \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": -0.2187, "explanation": "The actual 21-day forward return for AVAX-USD starting 2022-04-12 was -21.87%, which classifies as 'negative'.", "metadata": {"future_return": -0.2187, "horizon_days": 21, "hist_return": -0.092501, "annualized_vol": 0.843523, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20211101_0782", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2021-11-01", "context_summary": "IVV over past 60 days: cumulative return +4.1%, annualized vol 11.3%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=415.31, end=432.44, cumulative_return=+4.1%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.07, 't10y3m_spread': 1.5, 'breakeven_10y': 2.51, 'hy_oas': 3.15, 'ig_oas': 0.89, 'ted_spread': 0.08, 'mortgage_30y': 3.14, 'vix': 16.260000228881836}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AAPL 2021-10-29] aapl-20210925 false 2021 FY 0000320193 P1Y P5Y P1Y 64 P1Y 26 P1Y 8 2 http://fasb.org/us-gaap/2021-01-31#OtherAssetsNoncurrent http://fasb.org/us-gaap/2021-01-31#OtherAssetsNoncurrent http://fasb.org/us-gaap/2021-01-31#PropertyPlantAndEquipmentNet http://fasb.org/us-gaap/2021-01-31#PropertyPlantAndEquipmentNet http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2021-01-31#OtherLiabilitiesNoncurrent 0000320193 2020-09-27 2021-09-25 0000320193 us-gaap:CommonStockMember 2020-09-27 2021-09-25 0000320193 aapl:A1.000NotesDue2022Member 2020-09-27 2021-09-25 0000320193 aapl:A1.375NotesDue2024Member 2020-09-27 2021-09-25 0000320193 aapl:A0.000Notesdue2025Member 2020-09-27 2021-09-25 0000320193 aapl:A0.875NotesDue2025Member 2020-09-27 2021-09-25 0000320193 aapl:A1.625NotesDue2026Member 2020-09-27 2021-09-25 0000320193 aapl:A2.000NotesDue2027Member 2020-09-27 2021-09-25 0000320193 aapl:A1.375NotesDue2029Member 2020-09-27 2021-09-25 0000320193 aapl:A3.050NotesDue2029Member 2020-09-27 2021-09-25 0000320193 aapl:A0.500Notesdue2031Member 2020-09-27 2021-09-25 0000320193 aapl:A3.600NotesDue2042Member 2020-09-27 2021-09-25 iso4217:USD 0000320193 2021-03-26 xbrli:shares 0000320193 2021-10-15 0000320193 us-gaap:ProductMember 2020-09-27 2021-09-25 0000320193 us-gaap:ProductMember 2019-09-29 2020-09-26 0000320193 us-gaap:ProductMember 2018-09-30 2019-09-28 0000320193 us-gaap:ServiceMember 2020-09-27 2021-09-25 0000320193 us-gaap:ServiceMember 2019-09-29 2020-09-26 0000320193 us-gaap:ServiceMember 2018-09-30 2019-09-28 0000320193 2019-09-29 2020-09-26 0000320193 2018-09-30 2019-09-28 iso4217:USD xbrli:shares 0000320193 2021-09-25 0000320193 2020-09-26 0000320193 2019-09-28 0000320193 2018-09-29 0000320193 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2020-09-26 0000320193 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2019-09-28 0000320193 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2018-09-29 0000320193 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2020-09-27 2021-09-25 0000320193 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2019-09-29 2020-09-26 0000320193 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2018-09-30 2019-09-28 0000320193 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2021-09-25 0000320193 us-gaap:RetainedEarningsMember 2020-09-26 0000320193 us-gaap:RetainedEarningsMember 2019-09-28 0000320193 us-gaap:RetainedEarningsMember 2018-09-29 0000320193 us-gaap:RetainedEarningsMember 2020-09-27 2021-09-25 0000320193 us-gaap:RetainedEarningsMember 2019-09-29 2020-09-26 0000320193 us-gaap:RetainedEarningsMember 2018-09-30 2019-09-28 0000320193 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2020-09-26 0000320193 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2019-09-28 0000320193 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2018-09-29 0000320193 us-gaap:RetainedEarningsMember 2021-09-25 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-09-26 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-09-28 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2018-09-29 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-09-27 2021-09-25 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-09-29 2020-09-26 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2018-09-30 2019-09-28 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2020-09-26 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2019-09-28 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2018-09-29 0000320193 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-09-25 0000320193 us-gaap:BuildingMember srt:MaximumMember 2020-09-27 2021-09-25 0000320193 srt:MinimumMember us-gaap:MachineryAndEquipmentMember 2020-09-27 2021-09-25 0000320193 srt:MaximumMember us-gaap:MachineryAndEquipmentMember 2020-09-27 2021-09-25 0000320193 srt:MinimumMember us-gaap:SoftwareAndSoftwareDevelopmentCostsMember 2020-09-27 2021-09-25 0000320193 srt:MaximumMember us-gaap:SoftwareAndSoftwareDevelopmentCostsMember 2020-09-27 2021-09-25 aapl:obligation xbrli:pure 0000320193 2021-09-26 2021-09-25 0000320193 2022-09-25 2021-09-25 0000320193 2023-10-01 2021-09-25 0000320193 2024-09-29 2021-09-25 0000320193 aapl:IPhoneMember 2020-09-27 2021-09-25 0000320193 aapl:IPhoneMember 2019-09-29 2020-09-26 0000320193 aapl:IPhoneMember 2018-09-30 2019-09-28 0000320193 aapl:MacMember 2020-09-27 2021-09-25 0000320193 aapl:MacMember 2019-09-29 2020-09-26 0000320193 aapl:MacMember 2018-09-30 2019-09-28 0000320193 aapl:IPadMember 2020-09-27 2021-09-25 0000320193 aapl:IPadMember 2019-09-29 2020-09-26 0000320193 aapl:IPadMember 2018-09-30 2019-09-28 0000320193 aapl:WearablesHomeandAccessoriesMember 2020-09-27 2021-09-25 0000320193 aapl:WearablesHomeandAccessoriesMember 2019-09-29 2020-09-26 0000320193 aapl:WearablesHomeandAccessoriesMember 2018-09-30 2019-09-28 0000320193 us-gaap:CashMember 2021-09-25 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2021-09-25 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MutualFundMember 2021-09-25 0000320193 us-gaap:FairValueInputsLevel1Member 2021-09-25 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:EquitySecuritiesMember 2021-09-25 0000320193 us-gaap:FairValueInputsLevel2Member us [...TRUNCATED...] cer. 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 consolidated financial statements and accompanying notes in Part II, Item 8, &#8220;Financial Statements and Supplementary Data&#8221; of this Annual Report on Form 10-K. 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.&#160;&#160;&#160;&#160;Form 10-K Summary None. Apple Inc. | 2021 Form 10-K | 59 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: October&#160;28, 2021 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) October 28, 2021 TIMOTHY D. COOK /s/ Luca Maestri Senior Vice President, Chief Financial Officer (Principal Financial Officer) October 28, 2021 LUCA MAESTRI /s/ Chris Kondo Senior Director of Corporate Accounting (Principal Accounting Officer) October 28, 2021 CHRIS KONDO /s/ James A. Bell Director October 28, 2021 JAMES A. BELL /s/ Al Gore Director October 28, 2021 AL GORE /s/ Andrea Jung Director October 28, 2021 ANDREA JUNG /s/ Arthur D. Levinson Director and Chair of the Board October 28, 2021 ARTHUR D. LEVINSON /s/ Monica Lozano Director October 28, 2021 MONICA LOZANO /s/ Ronald D. Sugar Director October 28, 2021 RONALD D. SUGAR /s/ Susan L. Wagner Director October 28, 2021 SUSAN L. WAGNER Apple Inc. | 2021 Form 10-K | 60\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": -0.02089, "explanation": "The actual 21-day forward return for IVV starting 2021-11-01 was -2.09%, which classifies as 'negative'.", "metadata": {"future_return": -0.02089, "horizon_days": 21, "hist_return": 0.041232, "annualized_vol": 0.113494, "has_text": true, "text_chars": 9046}}
{"id": "T1_all_20190522_0783", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2019-05-22", "context_summary": "REZ over past 60 days: cumulative return +6.0%, annualized vol 13.0%. Market regime: sideways.", "question": "Asset: REZ\nHistorical prices (past 60 trading days): start=56.22, end=59.57, cumulative_return=+6.0%, annualized_volatility=13.0%\nMacro context: {'fed_funds_rate': 2.39, 'cpi_yoy': 255.296, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.17, 't10y3m_spread': 0.04, 'breakeven_10y': 1.83, 'hy_oas': 3.99, 'ig_oas': 1.24, 'ted_spread': 0.18, 'mortgage_30y': 4.07, 'vix': 14.949999809265137}\nMarket regime: sideways\n\nPredict whether the return of REZ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.032678, "explanation": "The actual 21-day forward return for REZ starting 2019-05-22 was +3.27%, which classifies as 'positive'.", "metadata": {"future_return": 0.032678, "horizon_days": 21, "hist_return": 0.059624, "annualized_vol": 0.130417, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220411_0785", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2022-04-11", "context_summary": "XLP over past 60 days: cumulative return +2.8%, annualized vol 14.6%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=68.74, end=70.69, cumulative_return=+2.8%, annualized_volatility=14.6%\nMacro context: {'fed_funds_rate': 0.33, 'cpi_yoy': 288.561, 'unemployment': 3.7, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.19, 't10y3m_spread': 2.02, 'breakeven_10y': 2.86, 'hy_oas': 3.57, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 4.72, 'vix': 21.15999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-08] [\"Top Stock Reports for Costco, AstraZeneca & Medtronic Friday, April 8, 2022 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 Costco Wholesale Corporation (COST), AstraZeneca PLC (AZN), and Medtronic plc (MDT). 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 Costco have outperformed the Zacks Retail - Discount Stores industry over the past year (+69.5% vs. +23.7%), reflecting the company's growth strategies, better price management, decent membership trend, and increasing penetration of e-commerce business. The strategy to sell products at discounted prices has helped draw customers seeking both value and convenience. These factors have been aiding in registering impressive sales and earnings numbers. Costco put up a decent performance in second-quarter fiscal 2022, wherein both the top and the bottom lines improved year over year. Also, Costco has been witnessing stellar comps sales run. While the aforementioned factors raise optimism. However, supply chain bottlenecks and higher labor and freight costs remain concerns. Any deleverage in SG&A rate may hurt margins. (You can read the full research report on Costco here >>>) Shares of AstraZeneca have outperformed the Zacks Large Cap Pharmaceuticals industry over the past year (+47% vs. +38.5%). The Zacks analyst believes that the company\\u2019s newer drugs, mainly cancer medicines, Lynparza, Tagrisso and Imfinzi should keep driving revenues. Its pipeline is strong with several phase III data readouts lined up. AstraZeneca has also engaged in external acquisitions and strategic collaborations to boost its pipeline while investing in geographic areas of high growth like emerging markets. Cost-cutting efforts should drive earnings. The Alexion buyout strengthens its immunology franchise, adding several drugs that can boost its top line. However, AstraZeneca\\u2019s diabetes franchise faces stiff competition while pricing pressure is hurting sales in the respiratory unit. Sales of some medicines are being hurt due to COVID-19. Sales are slowing down in key markets, China, due to pricing pressure. (You can read the full research report on AstraZeneca here >>>) Shares of Medtronic have outperformed the Zacks Medical - Products industry over the year-to-date period (+9.3% vs. -7.3%). Medtronic has registered organic growth in the Cardiovascular, Neuroscience and Diabetes segments. The company claims share gains in 60% of its businesses. However, the sluggish top-line results reflect the unfavorable market impact of COVID-19 and health system labor shortages. CRDN sales decreased in the mid-single digits, given the impact of COVID-19 on PCI procedures. Also, there have been low double-digit organic declines in RGR with sales of ventilators declining in the high-fif\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": -0.032781, "explanation": "The actual 21-day forward return for XLP starting 2022-04-11 was -3.28%, which classifies as 'negative'.", "metadata": {"future_return": -0.032781, "horizon_days": 21, "hist_return": 0.028444, "annualized_vol": 0.146201, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200916_0787", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2020-09-16", "context_summary": "BNB-USD over past 60 days: cumulative return +58.8%, annualized vol 80.8%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=17.13, end=27.20, cumulative_return=+58.8%, annualized_volatility=80.8%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 259.997, 'unemployment': 7.8, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.54, 't10y3m_spread': 0.57, 'breakeven_10y': 1.67, 'hy_oas': 5.14, 'ig_oas': 1.36, 'ted_spread': 0.14, 'mortgage_30y': 2.86, 'vix': 25.59000015258789}\nMarket regime: sideways\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": -0.009289, "explanation": "The actual 21-day forward return for BNB-USD starting 2020-09-16 was -0.93%, which classifies as 'flat'.", "metadata": {"future_return": -0.009289, "horizon_days": 21, "hist_return": 0.588302, "annualized_vol": 0.807921, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220509_0789", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLT"], "decision_date": "2022-05-09", "context_summary": "TLT over past 60 days: cumulative return -16.4%, annualized vol 19.2%. Market regime: sideways.", "question": "Asset: TLT\nHistorical prices (past 60 trading days): start=117.40, end=98.19, cumulative_return=-16.4%, annualized_volatility=19.2%\nMacro context: {'fed_funds_rate': 0.83, 'cpi_yoy': 291.298, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.4, 't10y3m_spread': 2.27, 'breakeven_10y': 2.86, 'hy_oas': 4.18, 'ig_oas': 1.4, 'ted_spread': 0.09, 'mortgage_30y': 5.27, 'vix': 30.190000534057617}\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": "flat", "answer_numeric": 0.00571, "explanation": "The actual 21-day forward return for TLT starting 2022-05-09 was +0.57%, which classifies as 'flat'.", "metadata": {"future_return": 0.00571, "horizon_days": 21, "hist_return": -0.163635, "annualized_vol": 0.191683, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190220_0791", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2019-02-20", "context_summary": "EWJ over past 60 days: cumulative return +1.3%, annualized vol 17.5%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=46.20, end=46.81, cumulative_return=+1.3%, annualized_volatility=17.5%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 253.319, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.15, 't10y3m_spread': 0.2, 'breakeven_10y': 1.87, 'hy_oas': 4.11, 'ig_oas': 1.32, 'ted_spread': 0.23, 'mortgage_30y': 4.37, 'vix': 14.880000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-19] After Hours Most Active for Feb 19, 2019 : SIRI, PFE, CHK, MO, VER, FDC, ZAYO, WBA, PYPL, AGNC, ADBE, SHY The NASDAQ 100 After Hours Indicator is up 1.03 to 7,067.64. The total After hours volume is currently 51,827,821 shares traded. The following are the most active stocks for the after hours session : Sirius XM Holdings Inc. ( SIRI ) is unchanged at $6.00, with 3,769,562 shares traded. As reported in the last short interest update the days to cover for SIRI is 8.93504; this calculation is based on the average trading volume of the stock. Pfizer, Inc. ( PFE ) is -0.2 at $42.40, with 2,262,941 shares traded. PFE's current last sale is 94.22% of the target price of $45. Chesapeake Energy Corporation ( CHK ) is unchanged at $2.68, with 1,818,617 shares traded. Over the last four weeks they have had 5 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2018. The consensus EPS forecast is $0.17. CHK's current last sale is 89.33% of the target price of $3. Altria Group ( MO ) is +0.13 at $49.12, with 1,447,860 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Jun 2019. The consensus EPS forecast is $1.07. MO's current last sale is 83.97% of the target price of $58.5. VEREIT Inc. ( VER ) is unchanged at $8.26, with 1,314,873 shares traded.VER is scheduled to provide an earnings report on 2/21/2019, for the fiscal quarter ending Dec2018. The consensus earnings per share forecast is 0.17 per share, which represents a 18 percent increase over the EPS one Year Ago First Data Corporation ( FDC ) is +0.03 at $25.53, with 1,273,073 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2019. The consensus EPS forecast is $0.27. FDC's current last sale is 102.12% of the target price of $25. Zayo Group Holdings, Inc. ( ZAYO ) is +0.1198 at $25.57, with 1,218,521 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2019. The consensus EPS forecast is $0.18. As reported by Zacks, the current mean recommendation for ZAYO is in the \"buy range\". Walgreens Boots Alliance, Inc. ( WBA ) is +0.4 at $74.83, with 991,822 shares traded. WBA's current last sale is 99.77% of the target price of $75. PayPal Holdings, Inc. ( PYPL ) is -0.02 at $95.00, with 877,652 shares traded. As reported by Zacks, the current mean recommendation for PYPL is in the \"buy range\". AGNC Investment Corp. ( AGNC ) is +0.01 at $17.70, with 813,667 shares traded. AGNC's current last sale is 98.33% of the target price of $18. Adobe Inc. ( ADBE ) is -0.0077 at $257.80, with 795,058 shares traded. As reported by Zacks, the current mean recommendation for ADBE is in the \"buy range\". iShares 1-3 Year Treasury Bond ETF ( SHY ) is unchanged at $83.74, with 792,213 shares traded. This represents a 1.1% increase from its 52 Week Low. The views and opinions expre\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00421, "explanation": "The actual 21-day forward return for EWJ starting 2019-02-20 was +0.42%, which classifies as 'flat'.", "metadata": {"future_return": 0.00421, "horizon_days": 21, "hist_return": 0.013338, "annualized_vol": 0.175371, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180810_0793", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2018-08-10", "context_summary": "ETH-USD over past 60 days: cumulative return -31.4%, annualized vol 61.8%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=533.28, end=365.59, cumulative_return=-31.4%, annualized_volatility=61.8%\nMacro context: {'fed_funds_rate': 1.91, 'cpi_yoy': 251.663, 'unemployment': 3.8, 'gdp_growth_qoq': 20276.154, 't10y2y_spread': 0.29, 't10y3m_spread': 0.87, 'breakeven_10y': 2.11, 'hy_oas': 3.38, 'ig_oas': 1.16, 'ted_spread': 0.32, 'mortgage_30y': 4.59, 'vix': 11.270000457763672}\nMarket regime: sideways\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": -0.153129, "explanation": "The actual 21-day forward return for ETH-USD starting 2018-08-10 was -15.31%, which classifies as 'negative'.", "metadata": {"future_return": -0.153129, "horizon_days": 21, "hist_return": -0.314459, "annualized_vol": 0.618445, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20171229_0795", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2017-12-29", "context_summary": "VNQ over past 60 days: cumulative return +1.2%, annualized vol 8.9%. Market regime: sideways.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=59.68, end=60.37, cumulative_return=+1.2%, annualized_volatility=8.9%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 247.805, 'unemployment': 4.1, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.52, 't10y3m_spread': 1.04, 'breakeven_10y': 1.96, 'hy_oas': 3.55, 'ig_oas': 0.98, 'ted_spread': 0.32, 'mortgage_30y': 3.99, 'vix': 10.18000030517578}\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": -0.052543, "explanation": "The actual 21-day forward return for VNQ starting 2017-12-29 was -5.25%, which classifies as 'negative'.", "metadata": {"future_return": -0.052543, "horizon_days": 21, "hist_return": 0.01159, "annualized_vol": 0.089119, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201113_0797", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLT"], "decision_date": "2020-11-13", "context_summary": "TLT over past 60 days: cumulative return -4.2%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: TLT\nHistorical prices (past 60 trading days): start=139.58, end=133.65, cumulative_return=-4.2%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.911, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.71, 't10y3m_spread': 0.78, 'breakeven_10y': 1.71, 'hy_oas': 4.62, 'ig_oas': 1.21, 'ted_spread': 0.12, 'mortgage_30y': 2.84, 'vix': 25.350000381469727}\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": "flat", "answer_numeric": 0.002095, "explanation": "The actual 21-day forward return for TLT starting 2020-11-13 was +0.21%, which classifies as 'flat'.", "metadata": {"future_return": 0.002095, "horizon_days": 21, "hist_return": -0.042466, "annualized_vol": 0.135289, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20171023_0799", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2017-10-23", "context_summary": "EEM over past 60 days: cumulative return +5.7%, annualized vol 11.6%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=35.89, end=37.95, cumulative_return=+5.7%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 246.626, 'unemployment': 4.2, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.79, 't10y3m_spread': 1.28, 'breakeven_10y': 1.87, 'hy_oas': 3.42, 'ig_oas': 1.01, 'ted_spread': 0.27, 'mortgage_30y': 3.88, 'vix': 9.970000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-10-20] [\"38 Biggest Movers From Yesterday\", \"Adobe MAX 2017 Event Concludes Today\", \"Adobe MAX 2017 Event Concludes Today\", \"38 Biggest Movers From Yesterday\", \"Adobe Systems Sees Its Composite Rating Rise To 99 Adobe Systems ( ADBE ) saw its IBD SmartSelect Composite Rating jump to 99 Friday, up from 94 the day before. [ibd-display-video id=2385970 width=50 float=left autostart=true] The new rating shows the stock is outpacing 99% of all stocks when it comes to the most important stock-picking criteria. The top-performing stocks tend to have a 95 or better grade as they begin to launch a significant move. Adobe Systems is currently extended beyond a proper buy zone after breaking out from a 157.99 buy point in a flat base. Looking For The Best Stocks To Buy And Watch? Start Here The stock has a 93 EPS Rating, which means its recent quarterly and annual earnings growth is outpacing 93% of all stocks. Its Accumulation/Distribution Rating of B- shows moderate buying by institutional investors over the last 13 weeks. In Q3, the company reported 47% EPS growth. That means it's now delivered two straight quarters of rising EPS gains. Sales growth fell to 26%, down from 27% in the prior quarter. Adobe Systems holds the No. 1 rank among its peers in the Computer Software-Desktop industry group. Red Hat ( RHT ) and Microsoft ( MSFT ) are also among the group's highest-rated stocks. RELATED: Which Companies Are Now Outperforming 95% Of All Stocks? The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"4 Top Liquid Stocks to Buy for Stellar Returns The liquidity position is indicative of whether a company's business is heading in the right direction. Favorable liquidity may help a company see strong business growth, which in turn may drive its price performance. Liquidity is a measure of a company's capability of meeting its debt obligations by converting its assets into liquid cash and equivalents. However, one should exercise caution before investing in such stocks. While a high liquidity level may imply that the company is meeting its obligations at a faster rate compared to peers, it may also indicate that the company is failing to use its assets efficiently. Hence, one may consider the efficiency level of a company in addition to its liquidity to identify potential winners. Measures to Identify Liquid Stocks Liquidity ratios like Current Ratio, Quick Ratio and Cash Ratio are primarily used to identify companies with strong liquidity. Current Ratio : It measures current assets relative to current liabilities. This ratio is used for measuring a company's potential to meet both short- and long-term debt obligations. Thus, a current ratio - also known as working capital ratio - below 1 indicates that the company has more liabilities than assets. Howe\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": 0.039224, "explanation": "The actual 21-day forward return for EEM starting 2017-10-23 was +3.92%, which classifies as 'positive'.", "metadata": {"future_return": 0.039224, "horizon_days": 21, "hist_return": 0.057372, "annualized_vol": 0.116089, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200529_0803", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2020-05-29", "context_summary": "ACWI over past 60 days: cumulative return -5.0%, annualized vol 32.3%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=68.38, end=64.95, cumulative_return=-5.0%, annualized_volatility=32.3%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 255.802, 'unemployment': 13.2, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.53, 't10y3m_spread': 0.55, 'breakeven_10y': 1.18, 'hy_oas': 6.6, 'ig_oas': 1.87, 'ted_spread': 0.2, 'mortgage_30y': 3.15, 'vix': 28.59000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-05-28] [\"Tweedy Browne's \\u2014\\u2026\\u2014\\u2026 Annual Letter to Shareholders\", \"The Momentum Trade Driving Stocks Higher May Be About To Snap\", \"Kroger: Capital Preservation and More at a Good Price\", \"Tredje AP-fonden Buys Microsoft Corp, Amazon.com Inc, Apple Inc, Sells iShares U.S. ...\", \"Growth Stocks for 2020: Trading Tech Stocks + FANG Stocks\", \"Swiss National Bank Ready To Buy Much More Tech Stocks To Weaken The Franc\", \"Stocks Are Struggling To Post Gains On May 28 Ahead Of Initial Claims\", \"The Zacks Analyst Blog Highlights: Apple, Exxon Mobil, Cisco System and Chevron\", \"Tech Companies Aren't 'State Actors,' Judge Dismisses Conservative Bias Lawsuit Against Facebook, Twitter, Google, Apple\", \"Martin Scorsese's Next Movie Will Be Financed By Apple: Report\", \"Costco Earnings On Tap After Close As Investors Mull Strong Toll Brothers Results\", \"Trump's Executive Order To Expose Social Media To Lawsuits Over Content Policies\", \"Trump's Executive Order To Expose Social Media To Lawsuits Over Content Policies\", \"Costco Earnings On Tap After Close As Investors Mull Strong Toll Brothers Results\", \"Martin Scorsese's Next Movie Will Be Financed By Apple: Report\", \"Tech Companies Aren't 'State Actors,' Judge Dismisses Conservative Bias Lawsuit Against Facebook, Twitter, Google, Apple\", \"The Momentum Trade Driving Stocks Higher May Be About To Snap\", \"Tweedy Browne's \\u2014\\u2026\\u2014\\u2026 Annual Letter to Shareholders\", \"Kroger: Capital Preservation and More at a Good Price\", \"Tredje AP-fonden Buys Microsoft Corp, Amazon.com Inc, Apple Inc, Sells iShares U.S. ...\", \"The Zacks Analyst Blog Highlights: Apple, Exxon Mobil, Cisco System and Chevron\", \"Growth Stocks for 2020: Trading Tech Stocks + FANG Stocks\", \"Stocks Are Struggling To Post Gains On May 28 Ahead Of Initial Claims\", \"Swiss National Bank Ready To Buy Much More Tech Stocks To Weaken The Franc\", \"Trump's Executive Order To Expose Social Media To Lawsuits Over Content Policies\", \"Costco Earnings On Tap After Close As Investors Mull Strong Toll Brothers Results\", \"Martin Scorsese's Next Movie Will Be Financed By Apple: Report\", \"Tech Companies Aren't 'State Actors,' Judge Dismisses Conservative Bias Lawsuit Against Facebook, Twitter, Google, Apple\", \"The Momentum Trade Driving Stocks Higher May Be About To Snap\", \"Tweedy Browne's \\u2014\\u2026\\u2014\\u2026 Annual Letter to Shareholders\", \"Kroger: Capital Preservation and More at a Good Price\", \"Tredje AP-fonden Buys Microsoft Corp, Amazon.com Inc, Apple Inc, Sells iShares U.S. ...\", \"The Zacks Analyst Blog Highlights: Apple, Exxon Mobil, Cisco System and Chevron\", \"Growth Stocks for 2020: Trading Tech Stocks + FANG Stocks\", \"Stocks Are Struggling To Post Gains On May 28 Ahead Of Initial Claims\", \"Swiss National Bank Ready To Buy Much More Tech Stocks To Weaken The Franc\", \"Apple makes streaming deal for Martin Scorsese movie starring Leonardo DiCaprio \\u2018Killers of the Flower Moon\\u2019 to stream exclusively on Apple TV+ Apple Inc. has nabbed\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": 0.022703, "explanation": "The actual 21-day forward return for ACWI starting 2020-05-29 was +2.27%, which classifies as 'positive'.", "metadata": {"future_return": 0.022703, "horizon_days": 21, "hist_return": -0.050224, "annualized_vol": 0.322891, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200630_0805", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2020-06-30", "context_summary": "ADA-USD over past 60 days: cumulative return +63.6%, annualized vol 79.4%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.05, end=0.08, cumulative_return=+63.6%, annualized_volatility=79.4%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 257.042, 'unemployment': 11.0, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.48, 't10y3m_spread': 0.5, 'breakeven_10y': 1.34, 'hy_oas': 6.52, 'ig_oas': 1.62, 'ted_spread': 0.16, 'mortgage_30y': 3.13, 'vix': 31.780000686645508}\nMarket regime: sideways\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": 0.479438, "explanation": "The actual 21-day forward return for ADA-USD starting 2020-06-30 was +47.94%, which classifies as 'positive'.", "metadata": {"future_return": 0.479438, "horizon_days": 21, "hist_return": 0.636169, "annualized_vol": 0.793697, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190114_0807", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2019-01-14", "context_summary": "XLP over past 60 days: cumulative return -2.2%, annualized vol 16.8%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=43.59, end=42.62, cumulative_return=-2.2%, annualized_volatility=16.8%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 252.561, 'unemployment': 4.0, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.16, 't10y3m_spread': 0.28, 'breakeven_10y': 1.83, 'hy_oas': 4.55, 'ig_oas': 1.54, 'ted_spread': 0.41, 'mortgage_30y': 4.45, 'vix': 18.190000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-11] [\"Friday's ETF with Unusual Volume: SIZE The iShares Edge MSCI USA Size Factor ETF is seeing unusually high volume in afternoon trading Friday, with over 314,000 shares traded versus three month average volume of about 32,000. Shares of SIZE were down about 0.2% on the day. Components of that ETF with the highest volume on Friday were General Electric, trading off about 0.1% with over 39.2 million shares changing hands so far this session, and Advanced Micro Devices, up about 0.5% on volume of over 37.5 million shares. General Motors is the component faring the best Friday, higher by about 8.3% on the day, while Vail Resorts is lagging other components of the iShares Edge MSCI USA Size Factor ETF, trading lower by about 13%. VIDEO: Friday's ETF with Unusual Volume: SIZE The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Noteworthy ETF Inflows: SOXX, NVDA, AMD, XLNX Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the iShares PHLX Semiconductor ETF (Symbol: SOXX) where we have detected an approximate $88.9 million dollar inflow -- that's a 8.2% increase week over week in outstanding units (from 6,700,000 to 7,250,000). Among the largest underlying components of SOXX, in trading today NVIDIA Corp (Symbol: NVDA) is off about 0.6%, Advanced Micro Devices Inc (Symbol: AMD) is off about 0.6%, and Xilinx, Inc. (Symbol: XLNX) is lower by about 0.3%. For a complete list of holdings, visit the SOXX Holdings page \\u00bb The chart below shows the one year price performance of SOXX, versus its 200 day moving average: Looking at the chart above, SOXX's low point in its 52 week range is $144.79 per share, with $198.84 as the 52 week high point - that compares with a last trade of $163.35. 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 The views and opinions expressed herein are the views and opi\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": 0.059751, "explanation": "The actual 21-day forward return for XLP starting 2019-01-14 was +5.98%, which classifies as 'positive'.", "metadata": {"future_return": 0.059751, "horizon_days": 21, "hist_return": -0.022284, "annualized_vol": 0.168166, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210104_0809", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2021-01-04", "context_summary": "BNB-USD over past 60 days: cumulative return +48.7%, annualized vol 61.4%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=27.68, end=41.15, cumulative_return=+48.7%, annualized_volatility=61.4%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 262.687, 'unemployment': 6.4, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 0.8, 't10y3m_spread': 0.84, 'breakeven_10y': 1.99, 'hy_oas': 3.86, 'ig_oas': 1.03, 'ted_spread': 0.15, 'mortgage_30y': 2.71, 'vix': 22.75}\nMarket regime: sideways\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": 0.017039, "explanation": "The actual 21-day forward return for BNB-USD starting 2021-01-04 was +1.70%, which classifies as 'positive'.", "metadata": {"future_return": 0.017039, "horizon_days": 21, "hist_return": 0.486818, "annualized_vol": 0.613556, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200212_0813", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2020-02-12", "context_summary": "IYR over past 60 days: cumulative return +7.3%, annualized vol 10.9%. Market regime: sideways.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=77.64, end=83.27, cumulative_return=+7.3%, annualized_volatility=10.9%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 259.25, 'unemployment': 3.5, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.18, 't10y3m_spread': 0.02, 'breakeven_10y': 1.65, 'hy_oas': 3.65, 'ig_oas': 1.04, 'ted_spread': 0.17, 'mortgage_30y': 3.45, 'vix': 15.18000030517578}\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": "negative", "answer_numeric": -0.177895, "explanation": "The actual 21-day forward return for IYR starting 2020-02-12 was -17.79%, which classifies as 'negative'.", "metadata": {"future_return": -0.177895, "horizon_days": 21, "hist_return": 0.072637, "annualized_vol": 0.10876, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201016_0818", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2020-10-16", "context_summary": "SOYB over past 60 days: cumulative return +12.8%, annualized vol 14.6%. Market regime: sideways.", "question": "Asset: SOYB\nHistorical prices (past 60 trading days): start=14.33, end=16.17, cumulative_return=+12.8%, annualized_volatility=14.6%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.6, 't10y3m_spread': 0.63, 'breakeven_10y': 1.69, 'hy_oas': 5.01, 'ig_oas': 1.34, 'ted_spread': 0.11, 'mortgage_30y': 2.81, 'vix': 26.96999931335449}\nMarket regime: sideways\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": 0.089608, "explanation": "The actual 21-day forward return for SOYB starting 2020-10-16 was +8.96%, which classifies as 'positive'.", "metadata": {"future_return": 0.089608, "horizon_days": 21, "hist_return": 0.128402, "annualized_vol": 0.145753, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200731_0822", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2020-07-31", "context_summary": "BTC-USD over past 60 days: cumulative return +9.3%, annualized vol 37.5%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=10167.27, end=11111.21, cumulative_return=+9.3%, annualized_volatility=37.5%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 258.352, 'unemployment': 10.2, 'gdp_growth_qoq': 20558.879, 't10y2y_spread': 0.44, 't10y3m_spread': 0.46, 'breakeven_10y': 1.52, 'hy_oas': 5.14, 'ig_oas': 1.41, 'ted_spread': 0.16, 'mortgage_30y': 2.99, 'vix': 24.76000022888184}\nMarket regime: sideways\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": 0.023758, "explanation": "The actual 21-day forward return for BTC-USD starting 2020-07-31 was +2.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.023758, "horizon_days": 21, "hist_return": 0.092842, "annualized_vol": 0.374903, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200310_0824", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2020-03-10", "context_summary": "BTC-USD over past 60 days: cumulative return -3.0%, annualized vol 45.0%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=8166.55, end=7923.64, cumulative_return=-3.0%, annualized_volatility=45.0%\nMacro context: {'fed_funds_rate': 1.09, 'cpi_yoy': 258.076, 'unemployment': 4.4, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.16, 't10y3m_spread': 0.21, 'breakeven_10y': 1.07, 'hy_oas': 6.68, 'ig_oas': 1.88, 'ted_spread': 0.45, 'mortgage_30y': 3.29, 'vix': 43.34999847412109}\nMarket regime: sideways\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": -0.185984, "explanation": "The actual 21-day forward return for BTC-USD starting 2020-03-10 was -18.60%, which classifies as 'negative'.", "metadata": {"future_return": -0.185984, "horizon_days": 21, "hist_return": -0.029744, "annualized_vol": 0.450495, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180918_0828", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2018-09-18", "context_summary": "VLUE over past 60 days: cumulative return +4.0%, annualized vol 8.8%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=68.54, end=71.26, cumulative_return=+4.0%, annualized_volatility=8.8%\nMacro context: {'fed_funds_rate': 1.92, 'cpi_yoy': 252.182, 'unemployment': 3.7, 'gdp_growth_qoq': 20276.154, 't10y2y_spread': 0.21, 't10y3m_spread': 0.83, 'breakeven_10y': 2.1, 'hy_oas': 3.29, 'ig_oas': 1.15, 'ted_spread': 0.21, 'mortgage_30y': 4.6, 'vix': 13.68000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-09-17] [\"New Apple Watch doesn\\u2019t have the feature most consumers want Price is the key factor for Apple smartwatch sales, analyst says, so most will buy older models instead of Apple Watch Series 4 \\u2018We continue to expect the lowest price option will account for the bulk of Watch volume on a global basis,\\u2019 says an analyst.\", \"Jeff Bezos\\u2019 fortune is growing even faster than he can give it away Bezos\\u2019 personal wealth has grown by about $4 billion this week The Amazon founder and CEO, the richest man in modern history, on Thursday stepped up his plans for major philanthropic giving by pledging $2 billion to set up the charitable \\u201cBezos Day One Fund.\\u201d\", \"Trade-war fears to loom large over stocks Bove: The Fed\\u2019s interest-rate hikes could trigger a recession The single biggest fear dogging the financial markets is not the possible unraveling of emerging markets or the U.S. midterm elections but the specter of a full blown trade war, according to some strategists.\", \"Apple's stock could be blamed for all of the Dow's decline Shares of Apple Inc. dropped 1.7% in morning trade Monday, enough to pace the Dow Jones Industrial Average's decliners and to pull the blue-chip barometer down into negative territory. Apple's price decline shaved about 26 points off the Dow's price, which was down 19 points. Instinet analyst Jeffrey Kvaal reiterated his neutral rating on the stock, saying his analysis of weekend orders for Apple's new iPhones suggests shipments are tracking in line with expectations. Apple's stock was still up 16.5% over the past three months while the Dow was up 4.1%.\", \"Tech stocks haven't had a losing month since March and that may change as Nasdaq suffers September slump The Nasdaq Composite Index slumped late-morning Monday, with the day's slide helping to push the technology-and-internet focused gauge to its first monthly loss since March, according to FactSet data. The Nasdaq in late-morning trade was down about 80 points, or 1%, at 7,931. Worries that the U.S. trade clash with China was on the verge of escalating this week has kept investors on edge, particularly in tech, because that sector could be harmed by another round of tech-focused tariffs, market participants said. The Trump administration is planning to unveil new import duties on $200 billion in Chinese goods. The Nasdaq was on pace to shed 2.1% in September, which would be the index's worst monthly and only decline since a 2.9% fall. Beyond tariffs, industry watchers also have feared that shares within the group have gotten rich. Meanwhile, the Dow Jones Industrial Average was experiencing a less-severe slide on Monday, down 0.1% at 26,132, while the S&P 500 index was down 0.3% at 2,895. Notably, shares of Apple Inc. and Amazon.com Inc. , two of the world's most highly valued companies, were trading sharply lower on Monday, weighing on the broader market. Technically, Amazon is classified as a consumer-discretionary company and not tech in major b\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": -0.033177, "explanation": "The actual 21-day forward return for VLUE starting 2018-09-18 was -3.32%, which classifies as 'negative'.", "metadata": {"future_return": -0.033177, "horizon_days": 21, "hist_return": 0.039726, "annualized_vol": 0.088288, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20191127_0830", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2019-11-27", "context_summary": "IWM over past 60 days: cumulative return +9.8%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=135.85, end=149.10, cumulative_return=+9.8%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 257.879, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.16, 't10y3m_spread': 0.14, 'breakeven_10y': 1.62, 'hy_oas': 4.05, 'ig_oas': 1.12, 'ted_spread': 0.34, 'mortgage_30y': 3.66, 'vix': 11.539999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-26] 5 Momentum Stocks to Buy on the Rebound In early September, we saw an unprecedented shift in the investment landscape from momentum stocks to value stocks. This came amid a recovery in economic fundamentals and a sharp rise in interest rates. By mid-September, the the iShares Momentum Factor ETF (BATS:) was down more than 1%, while the iShares Value Factor ETF (BATS:) was up more than 7%. This big divergence prompted me to write a piece on InvestorPlace outlining . The logic was simple. These sharp momentum-to-value shifts don\u2019t happen often. But, when they do, it\u2019s when the things are getting better. See late 2016. It is investors voting with their money that the coast is clear to buy stocks that require a good economy to head higher. As such, these shifts are normally temporary, and a harbinger of a broader market rally. When they end, both value and momentum stocks power higher alongside a rising economy. Thus, I reasoned that the September weakness in momentum stocks presented a solid buying opportunity into 2020, when all stocks would power higher supported by easing trade tensions, re-accelerated global capital investment and economic activity, revamped corporate profit growth, healthy labor markets and supportive central bank policy. Fast forward two months. Since then, both the Momentum Factor ETF and Value Factor ETF are up more than 3%, five of the seven momentum stocks I recommended are up more than 8%, and three of them are up more than 20%. I think this momentum stock rebound will continue. As such, let\u2019s take a deeper look at five of my favorite momentum stocks that have shown impressive strength since mid-September. Momentum Stocks to Buy on the Rebound: The Trade Desk (TTD) Source: Shutterstock % Gain Since Sept. 16: 20% At one point in time, programmatic advertising leader The Trade Desk (NASDAQ:) was one of the biggest losers in the mid-2019 momentum-to-value shift. Shares had shed almost a quarter of their value by mid-September. But, since then, shares have soared 20%. This big rebound in TTD stock will persist for a few reasons. First, the long-term fundamentals are favorable here. Programmatic advertising is \u201csmart\u201d advertising, which leverages algorithms, data and machine learning to transform ad transactions and ad spend allocations from a guess-and-check process, to an automated and optimized process. The whole ad industry is pivoting into programmatic advertising, yet only a small portion of global ad dollars are transacted programmatically today. The Trade Desk is at the center of this pivot. Thus, as more ad dollars flow into the programmatic channel over the next few years, TTD\u2019s revenues and profits will continue to roar higher. Second, the valuation remains reasonable. By my numbers, The Trade Desk will net $12 in earnings per share by fiscal 2025, behind 20%-plus annual revenue growth, steady profit margin expansion and 25%-plus profit growth. Based on an exit multiple of 35-times forward earnings (which is average\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": 0.022345, "explanation": "The actual 21-day forward return for IWM starting 2019-11-27 was +2.23%, which classifies as 'positive'.", "metadata": {"future_return": 0.022345, "horizon_days": 21, "hist_return": 0.097527, "annualized_vol": 0.134791, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210210_0832", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2021-02-10", "context_summary": "LINK-USD over past 60 days: cumulative return +126.0%, annualized vol 124.3%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=12.21, end=27.59, cumulative_return=+126.0%, annualized_volatility=124.3%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 263.579, 'unemployment': 6.2, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.07, 't10y3m_spread': 1.14, 'breakeven_10y': 2.22, 'hy_oas': 3.51, 'ig_oas': 0.98, 'ted_spread': 0.16, 'mortgage_30y': 2.73, 'vix': 21.6299991607666}\nMarket regime: sideways\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": 0.116548, "explanation": "The actual 21-day forward return for LINK-USD starting 2021-02-10 was +11.65%, which classifies as 'positive'.", "metadata": {"future_return": 0.116548, "horizon_days": 21, "hist_return": 1.260125, "annualized_vol": 1.242656, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181115_0834", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2018-11-15", "context_summary": "ADA-USD over past 60 days: cumulative return -7.3%, annualized vol 74.1%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.07, end=0.06, cumulative_return=-7.3%, annualized_volatility=74.1%\nMacro context: {'fed_funds_rate': 2.2, 'cpi_yoy': 252.594, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.26, 't10y3m_spread': 0.74, 'breakeven_10y': 2.0, 'hy_oas': 3.99, 'ig_oas': 1.29, 'ted_spread': 0.3, 'mortgage_30y': 4.94, 'vix': 21.25}\nMarket regime: sideways\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": -0.51532, "explanation": "The actual 21-day forward return for ADA-USD starting 2018-11-15 was -51.53%, which classifies as 'negative'.", "metadata": {"future_return": -0.51532, "horizon_days": 21, "hist_return": -0.073453, "annualized_vol": 0.740702, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20170413_0836", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2017-04-13", "context_summary": "SCHH over past 60 days: cumulative return +1.3%, annualized vol 11.2%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=15.92, end=16.13, cumulative_return=+1.3%, annualized_volatility=11.2%\nMacro context: {'fed_funds_rate': 0.91, 'cpi_yoy': 244.193, 'unemployment': 4.4, 'gdp_growth_qoq': 19506.949, 't10y2y_spread': 1.04, 't10y3m_spread': 1.47, 'breakeven_10y': 1.9, 'hy_oas': 3.96, 'ig_oas': 1.24, 'ted_spread': 0.36, 'mortgage_30y': 4.1, 'vix': 15.770000457763672}\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": -0.036806, "explanation": "The actual 21-day forward return for SCHH starting 2017-04-13 was -3.68%, which classifies as 'negative'.", "metadata": {"future_return": -0.036806, "horizon_days": 21, "hist_return": 0.013437, "annualized_vol": 0.111556, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190329_0839", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2019-03-29", "context_summary": "EEM over past 60 days: cumulative return +8.5%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=33.32, end=36.14, cumulative_return=+8.5%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 2.41, 'cpi_yoy': 254.277, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.16, 't10y3m_spread': -0.04, 'breakeven_10y': 1.83, 'hy_oas': 4.08, 'ig_oas': 1.25, 'ted_spread': 0.21, 'mortgage_30y': 4.06, 'vix': 14.43000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-03-28] The New Microsoft Partnership Underscores Why Adobe Stock Is a Winner Adobe (NASDAQ:) really is as strong as it has been for awhile. But when you think about it it makes perfect sense that and Adobe stock is so solid. Source: Shutterstock In the stock market, amid all the numbers and stochastic price movements, it\u2019s sometimes best to keep things simple. As such, here\u2019s my best attempt at a simple, three box check-list for identifying winning stocks. The company has to have winning and distinct features. The company has to be in a secular growth market. And, the stock has to trade at a reasonable valuation that leaves room for upside. A lot of stocks check off those boxes. But, few check them off as convincingly as Adobe. Adobe has winning and distinct features (the company dominates in delivering visual-oriented digital solutions). The company is also immersed in the secular growth cloud services market. And, ADBE has consistently traded at a reasonable 30-times forward price-to-earnings multiple. Consequently, Adobe stock has been a winning stock for a long time. Over the past five years, Adobe has risen more than 300%. Adobe will have similar success over the next five years, largely because the stock continues to check off all the right boxes. Of recent importance, Adobe just partnered with Microsoft (NASDAQ:) in a move that only emphasizes Adobe\u2019s winning features and expands the company\u2019s reach in the secular growth cloud services market. So long as these catalysts keep popping up, ADBE will remain in the winner\u2019s column. As such, it remains the sort of stock you buy now and hold for the long haul. Microsoft Partnership Reinforces Strong Fundamentals Adobe stock is supported by strong big picture growth fundamentals. Those big picture fundamentals include that this is a company unparalleled in its ability to deliver visual-oriented solutions, and that is leveraging that unique ability to create unique and highly valuable visual-focused cloud solutions. Those solutions include Document Cloud, Creative Cloud, and Experience Cloud, and have increasing value today, in a world that is rapidly pivoting to visual-heavy consumption and interaction. As such, as this pivot continues for the foreseeable future, Adobe projects to win dollars and share in the huge growth cloud market. This healthy big picture narrative is getting even healthier, mostly thanks to Adobe\u2019s continued expansion into the commerce and enterprise marketing side of the cloud market. Specifically, Adobe last year acquired two companies. The first, Magneto, is a commerce platform. The second, Marketo, is a B2B marketing engagement company. The sum of these acquisitions expanded Adobe\u2019s reach in the cloud services market, to include commerce and B2B enterprise marketing. Building on those acquisitions, Adobe recently announced a partnership with Microsoft that further expands Adobe\u2019s reach in new markets. Specifically, Adobe\u2019s customers can now tap into the Microsoft-owned LinkedIn \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": 0.024464, "explanation": "The actual 21-day forward return for EEM starting 2019-03-29 was +2.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.024464, "horizon_days": 21, "hist_return": 0.084781, "annualized_vol": 0.171731, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20161005_0841", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2016-10-05", "context_summary": "IWM over past 60 days: cumulative return +3.2%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=105.87, end=109.26, cumulative_return=+3.2%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 241.741, 'unemployment': 4.9, 'gdp_growth_qoq': 19304.352, 't10y2y_spread': 0.87, 't10y3m_spread': 1.36, 'breakeven_10y': 1.62, 'hy_oas': 4.85, 'ig_oas': 1.41, 'ted_spread': 0.53, 'mortgage_30y': 3.42, 'vix': 13.630000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-10-04] [\"Software-As-A-Service Competition Heats Up For Microsoft\", \"Software-As-A-Service Competition Heats Up For Microsoft\", \"Tech Stock Roundup: MSFT Deals, CRM Objections, TWTR Buy It was an eventful week for tech stocks in general and Microsoft MSFT in particular. The software giant entered into important alliances with Adobe ADBE , Workday WDAY , Dell, HP Enterprise HPE and got attacked by Salesforce CRM . Here's a quick look at the top stories: Microsoft Deal Week: Adobe, Workday, Renault Microsoft's alliances last week were notable. HP Enterprise and Dell, which officially joined Azure last week at its Ignite Conference in Atlanta, have everything to gain from the alliance. That's because Microsoft is the only one of the top cloud infrastructure providers that continues to bet on the hybrid cloud. Unlike Amazon AMZN and Alphabet's GOOGL Google, Microsoft expects companies to initially (and perhaps also later) use the public cloud for some operations while housing some sensitive operations on owned hardware. Therefore an alliance with Microsoft brings together the companies that can make this happen. Also at Ignite, the company announced a major collaboration with Adobe that will have the PDF software maker run its Adobe Marketing Cloud, Adobe Creative Cloud and Adobe Document Cloud on Azure. In return, Microsoft will make Adobe's marketing cloud the preferred marketing service for Dynamics 365, its own CRM solution. The combination of sales software from Microsoft and marketing software from Adobe will help users run Microsoft analytics on Adobe-stored data, thus putting up some solid competition for Salesforce's Sales Cloud and Marketing Cloud. What's more, the companies will cross-promote products. While Adobe will continue to work with Amazon's AWS for customers that want it, Adobe CEO Shantanu Narayen has said, \\\"We're going to be focusing our innovation and efforts on Azure.\\\" The company's alliance with Workday, intended to roll out this quarter, is intended to integrate Workdays' HR and finance software with Microsoft's Office 365 productivity solutions. The combined resources are expected to help customers \\\"simplify their business processes, enhance collaboration, and infuse more intelligence into their organizations,\\\" according to Microsoft CEO Nadella. There will also be employee-related analytics, such as how employee time is used. Renault and Nissan, that have gotten together to develop self driving car technology have now chosen Microsoft's Azure to provide advanced navigation, predictive maintenance and vehicle centric services, remote monitoring of car features, external mobile experiences and over-the-air updates. They also intend to collaborate on next-generation connected services for cars that will be powered by Azure services. SalesForce Opposes Microsoft-LinkedIn Deal After losing out in the bidding war to acquire LinkedIn, Salesforce is now trying to do what's second best. The main concern for the company is LinkedIn's d\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": -0.072207, "explanation": "The actual 21-day forward return for IWM starting 2016-10-05 was -7.22%, which classifies as 'negative'.", "metadata": {"future_return": -0.072207, "horizon_days": 21, "hist_return": 0.031996, "annualized_vol": 0.134635, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220729_0844", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2022-07-29", "context_summary": "EWJ over past 60 days: cumulative return -1.5%, annualized vol 18.8%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=51.60, end=50.81, cumulative_return=-1.5%, annualized_volatility=18.8%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 294.913, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.17, 't10y3m_spread': 0.26, 'breakeven_10y': 2.48, 'hy_oas': 4.98, 'ig_oas': 1.54, 'ted_spread': 0.09, 'mortgage_30y': 5.3, 'vix': 22.32999992370605}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K MSFT 2022-07-28] msft-10k_20220630.htm false FY 0000789019 --06-30 P10Y http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member 0000789019 2021-07-01 2022-06-30 0000789019 us-gaap:CommonStockMember 2021-07-01 2022-06-30 xbrli:shares 0000789019 2022-07-25 iso4217:USD 0000789019 2021-12-31 iso4217:USD xbrli:shares 0000789019 msft:NotesThreePointOneTwoFivePercentDueDecemberSixTwentyTwentyEightMember 2021-07-01 2022-06-30 0000789019 msft:NotesTwoPointSixTwoFivePercentDueMayTwoTwentyThirtyThreeMember 2021-07-01 2022-06-30 0000789019 us-gaap:ProductMember 2021-07-01 2022-06-30 0000789019 us-gaap:ProductMember 2020-07-01 2021-06-30 0000789019 us-gaap:ProductMember 2019-07-01 2020-06-30 0000789019 us-gaap:ServiceOtherMember 2021-07-01 2022-06-30 0000789019 us-gaap:ServiceOtherMember 2020-07-01 2021-06-30 0000789019 us-gaap:ServiceOtherMember 2019-07-01 2020-06-30 0000789019 2020-07-01 2021-06-30 0000789019 2019-07-01 2020-06-30 0000789019 2022-06-30 0000789019 2021-06-30 0000789019 2020-06-30 0000789019 2019-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2021-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2020-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2019-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2021-07-01 2022-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2020-07-01 2021-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2019-07-01 2020-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2022-06-30 0000789019 us-gaap:RetainedEarningsMember 2021-06-30 0000789019 us-gaap:RetainedEarningsMember 2020-06-30 0000789019 us-gaap:RetainedEarningsMember 2019-06-30 0000789019 us-gaap:RetainedEarningsMember 2021-07-01 2022-06-30 0000789019 us-gaap:RetainedEarningsMember 2020-07-01 2021-06-30 0000789019 us-gaap:RetainedEarningsMember 2019-07-01 2020-06-30 0000789019 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2021-06-30 0000789019 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2020-06-30 0000789019 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2019-06-30 0000789019 us-gaap:RetainedEarningsMember 2022-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-07-01 2022-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-07-01 2021-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-07-01 2020-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2021-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2020-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2019-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-06-30 0000789019 us-gaap:DebtSecuritiesMember 2021-07-01 2022-06-30 0000789019 us-gaap:EquitySecuritiesMember 2021-07-01 2022-06-30 0000789019 us-gaap:CashFlowHedgingMember us-gaap:OtherComprehensiveIncomeMember 2021-07-01 2022-06-30 0000789019 msft:NuanceCommunicationsIncMember 2021-07-01 2022-06-30 0000789019 msft:ZeniMaxMediaIncMember 2021-07-01 2022-06-30 0000789019 msft:ServerEquipmentMember us-gaap:ServiceLifeMember 2021-07-01 2022-06-30 0000789019 msft:ServerEquipmentMember us-gaap:ServiceLifeMember us-gaap:SubsequentEventMember 2022-07-01 2022-07-01 0000789019 msft:NetworkEquipmentMember us-gaap:ServiceLifeMember 2021-07-01 2022-06-30 0000789019 msft:NetworkEquipmentMember us-gaap:ServiceLifeMember us-gaap:SubsequentEventMember 2022-07-01 2022-07-01 0000789019 us-gaap:AllowanceForCreditLossMember 2021-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2020-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2019-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2021-07-01 2022-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2020-07-01 2021-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2019-07-01 2020-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2022-06-30 0000789019 msft:AccountsReceivableNetMember us-gaap:AllowanceForCreditLossMember 2022-06-30 0000789019 msft:AccountsReceivableNetMember us-gaap:AllowanceForCreditLossMember 2021-06-30 0000789019 msft:AccountsReceivableNetMember us-gaap:AllowanceForCreditLossMember 2020-06-30 0000789019 us-gaap:OtherNoncurrentAssetsMember us-gaap:AllowanceForCreditLossMember 2022-06-30 0000789019 us-gaap:OtherNoncurrentAssetsMember us-gaap:AllowanceForCreditLossMember 2021-06-30 0000789019 us-gaap:OtherNoncurrentAssetsMember us-gaap:AllowanceForCreditLossMember 2020-06-30 0000789019 srt:MinimumMember us-gaap:SoftwareAndSoftwareDevelopmentCostsMember 2021-07-01 2022-06-30 0000789019 us-gaap:SoftwareAndSoftwareDevelopmentCostsMember srt:MaximumMember 2021-07-01 2022-06-30 0000789019 srt:MinimumMember us-gaap:ComputerEquipmentMember 2021-07-01 2022-06-30 0000789019 us-gaap:ComputerEquipmentMember srt:MaximumMember 2021-07-01 2022-06-30 0000789019 srt:MinimumMember us-gaap:BuildingAndBuildingImprovementsMember 2021-07-0 [...TRUNCATED...] 60; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; 104 &#160; Cover page formatted as Inline XBRL and contained in Exhibit 101 &#160; X &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; * Indicates a management contract or compensatory plan or arrangement. ** Furnished, not filed. &#160; &#160; 107 PART IV Item 16 &#160; &#160; ITEM&#160;16. FORM 10-K SUMMARY None. &#160; &#160; 108 &#160; &#160; SIGNATURES Pursuant to the requirements of Section&#160;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&#59; thereunto duly authorized, in the City of Redmond, State of Washington, on July 28, 2022. &#160; M ICROSOFT C ORPORATION &#160; /s/ A LICE L. J OLLA Alice L. Jolla Corporate&#160;Vice&#160;President and Chief Accounting Officer (Principal Accounting Officer) &#160; 109 &#160; &#160; 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 28, 2022. &#160; Signature &#160; Title &#160; &#160; &#160; /s/&#160;S ATYA N ADELLA&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Satya Nadella &#160; Chairman and Chief Executive Officer (Principal Executive Officer) &#160; &#160; /s/&#160;R EID H OFFMAN &#160; &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Reid Hoffman &#160; Director &#160; &#160; /s/&#160;H UGH F. J OHNSTON &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Hugh F. Johnston &#160; Director &#160; &#160; /s/&#160; T ERI L. L IST &#160; Teri L. List &#160; Director &#160; &#160; /s/&#160; S ANDRA E. P ETERSON &#160; Sandra E. Peterson &#160; Director &#160; &#160; &#160; /s/&#160;P ENNY S. P RITZKER &#160; Penny S. Pritzker &#160; Director &#160; &#160; /s/&#160;C ARLOS A. R ODRIGUEZ &#160; Director Carlos A. Rodriguez &#160; &#160; &#160; &#160; /s/&#160; C HARLES W. S CHARF&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Charles W. Scharf &#160; Director &#160; &#160; /s/&#160; J OHN W. S TANTON&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; John W. Stanton &#160; Director &#160; &#160; &#160; /s/&#160;J OHN W. T HOMPSON&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Lead Independent Director John W. Thompson &#160; &#160; &#160; &#160; /s/&#160;E MMA N. W ALMSLEY&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Emma N. Walmsley &#160; Director &#160; &#160; /s/&#160; P ADMASREE W ARRIOR &#160; Padmasree Warrior &#160; Director &#160; &#160; /s/&#160;A MY E. H OOD&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Amy E. Hood &#160; Executive Vice President and Chief Financial Officer (Principal Financial Officer) &#160; &#160; /s/&#160;A LICE L. J OLLA &#160; Alice L. Jolla &#160; Corporate&#160;Vice&#160;President and Chief Accounting Officer (Principal Accounting Officer) &#160; &#160; 110\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": -0.040249, "explanation": "The actual 21-day forward return for EWJ starting 2022-07-29 was -4.02%, which classifies as 'negative'.", "metadata": {"future_return": -0.040249, "horizon_days": 21, "hist_return": -0.015418, "annualized_vol": 0.187713, "has_text": true, "text_chars": 9046}}
{"id": "T1_all_20170124_0846", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2017-01-24", "context_summary": "XLK over past 60 days: cumulative return +5.4%, annualized vol 12.2%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=21.52, end=22.67, cumulative_return=+5.4%, annualized_volatility=12.2%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 243.618, 'unemployment': 4.7, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.25, 't10y3m_spread': 1.9, 'breakeven_10y': 2.02, 'hy_oas': 4.1, 'ig_oas': 1.28, 'ted_spread': 0.53, 'mortgage_30y': 4.09, 'vix': 11.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-23] [\"Will Foxconn Build Its Next Multi-Billion Display Factory In The U.S. Or China? Apple's (AAPL) assembly supplier Hon Hai Precision Industry (2317.Taiwan), known as Foxconn, is considering investing $7 billion to build a display factory in the U.S., according to CEO Terry Gou in an interview on Sunday, a day after Donald Trump became the US President. Guo's interview contradicts an earlier one in which he said he would build an $8.8 billion factory in China.Foxconn would plan this factory with its subsidiary Sharp (6753.Japan), which has the LCD display technology.READ MORE.\", \"Goldman: Trump Trade Risk Not Priced In; 5 Stocks To Sell Financial markets have not priced in a protectionist Donald Trump presidency, according to Goldman Sachs.Look at how quickly Asia's export-oriented companies have bounced back, \\\"suggesting the market may not have priced in much trade risk\\\", wrote Goldman.READ MORE.\", \"Taiwan, Apple\\u2019s Manufacturing Backyard, Rallies As Trump Pledges \\u201cAmerica First\\u201d Irony kicks in on the first trading day after Donald Trump was sworn in as the 45th U.S. President.Emerging Asia's stock markets broadly gained as currency traders pared back their bullish bets on the U.S. dollar. Last week, in an interview with the Wall Street Journal, Trump broke the long-held tradition of presidents not commenting on the greenback and said the dollar was \\\"too strong\\\" and \\\"it's killing us.\\\" The South Korean won rose 0.6%, the new Taiwan dollar gained 0.3% and the offshore yuan was up 0.3%.Taiwan's stock markets gained the most today, with the TAIEX Index up 0.8% recently.So why Taiwan?READ MORE.\", \"Foxconn may team with Apple to build $7 billion manufacturing facility in U.S. Factory could create up to 50,000 new jobs, Foxconn chairman says Foxconn Technology Group is considering building a display-panel manufacturing facility in the United States in a joint venture with Apple Inc. that could create up to 50,000 jobs, the company\\u2019s chairman said Sunday.\", \"10 popular stocks at risk from Trump\\u2019s \\u2018America first\\u2019 inauguration speech The new president\\u2019s protectionist policies could damage the earnings of highly regarded companies doing business overseas The new president\\u2019s protectionist policies could damage the earnings of highly regarded companies doing business overseas.\", \"6 tech stocks that could move big on earnings Buy Alphabet and Microsoft, but sell Intel; Apple is a hold Earnings so far look mixed, but that could all change when Big Tech reports.\", \"Tech Today: Qualcomm\\u2019s Apple Risk, Apple\\u2019s iPhone Risk, Twilio, Oracle Prospects Here are some things going on today in your world of tech:Shares of Qualcomm (QCOM) are down $2.93, or almost 5%, at $59.95, in pre-market trading, after multiple outlets reported on Friday that Apple (AAPL), one of its largest customers, has filed suit against Qualcomm for withholding $1 billion in rebates owed Apple, in a move to punish Apple for helping South \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": 0.046016, "explanation": "The actual 21-day forward return for XLK starting 2017-01-24 was +4.60%, which classifies as 'positive'.", "metadata": {"future_return": 0.046016, "horizon_days": 21, "hist_return": 0.053841, "annualized_vol": 0.122211, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20170911_0848", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2017-09-11", "context_summary": "PALL over past 60 days: cumulative return +7.2%, annualized vol 22.0%. Market regime: sideways.", "question": "Asset: PALL\nHistorical prices (past 60 trading days): start=83.46, end=89.45, cumulative_return=+7.2%, annualized_volatility=22.0%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 246.435, 'unemployment': 4.3, 'gdp_growth_qoq': 19660.766, 't10y2y_spread': 0.79, 't10y3m_spread': 1.02, 'breakeven_10y': 1.81, 'hy_oas': 3.92, 'ig_oas': 1.17, 'ted_spread': 0.29, 'mortgage_30y': 3.78, 'vix': 12.119999885559082}\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": "flat", "answer_numeric": -0.008604, "explanation": "The actual 21-day forward return for PALL starting 2017-09-11 was -0.86%, which classifies as 'flat'.", "metadata": {"future_return": -0.008604, "horizon_days": 21, "hist_return": 0.071771, "annualized_vol": 0.220483, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190715_0851", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-07-15", "context_summary": "LINK-USD over past 60 days: cumulative return +201.0%, annualized vol 133.6%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=0.93, end=2.79, cumulative_return=+201.0%, annualized_volatility=133.6%\nMacro context: {'fed_funds_rate': 2.38, 'cpi_yoy': 255.802, 'unemployment': 3.7, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.28, 't10y3m_spread': -0.02, 'breakeven_10y': 1.77, 'hy_oas': 4.02, 'ig_oas': 1.18, 'ted_spread': 0.22, 'mortgage_30y': 3.75, 'vix': 12.390000343322754}\nMarket regime: sideways\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": -0.08947, "explanation": "The actual 21-day forward return for LINK-USD starting 2019-07-15 was -8.95%, which classifies as 'negative'.", "metadata": {"future_return": -0.08947, "horizon_days": 21, "hist_return": 2.009723, "annualized_vol": 1.335883, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220314_0854", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["GLD"], "decision_date": "2022-03-14", "context_summary": "GLD over past 60 days: cumulative return +10.8%, annualized vol 14.3%. Market regime: sideways.", "question": "Asset: GLD\nHistorical prices (past 60 trading days): start=167.09, end=185.09, cumulative_return=+10.8%, annualized_volatility=14.3%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 287.674, 'unemployment': 3.7, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.25, 't10y3m_spread': 1.6, 'breakeven_10y': 2.86, 'hy_oas': 4.05, 'ig_oas': 1.5, 'ted_spread': 0.09, 'mortgage_30y': 3.85, 'vix': 30.75}\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": "flat", "answer_numeric": 0.008064, "explanation": "The actual 21-day forward return for GLD starting 2022-03-14 was +0.81%, which classifies as 'flat'.", "metadata": {"future_return": 0.008064, "horizon_days": 21, "hist_return": 0.107726, "annualized_vol": 0.142844, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180112_0856", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2018-01-12", "context_summary": "BTC-USD over past 60 days: cumulative return +104.4%, annualized vol 100.1%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=6559.49, end=13405.80, cumulative_return=+104.4%, annualized_volatility=100.1%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 248.859, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.56, 't10y3m_spread': 1.11, 'breakeven_10y': 2.0, 'hy_oas': 3.4, 'ig_oas': 0.95, 'ted_spread': 0.31, 'mortgage_30y': 3.99, 'vix': 9.880000114440918}\nMarket regime: sideways\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": -0.368357, "explanation": "The actual 21-day forward return for BTC-USD starting 2018-01-12 was -36.84%, which classifies as 'negative'.", "metadata": {"future_return": -0.368357, "horizon_days": 21, "hist_return": 1.043726, "annualized_vol": 1.001012, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20171026_0859", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2017-10-26", "context_summary": "VEA over past 60 days: cumulative return +2.8%, annualized vol 7.1%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=32.86, end=33.79, cumulative_return=+2.8%, annualized_volatility=7.1%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 246.626, 'unemployment': 4.2, 'gdp_growth_qoq': 19882.352, 't10y2y_spread': 0.83, 't10y3m_spread': 1.32, 'breakeven_10y': 1.88, 'hy_oas': 3.42, 'ig_oas': 1.0, 'ted_spread': 0.27, 'mortgage_30y': 3.88, 'vix': 11.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-10-25] [\"Chip company earnings could be driven by new iPhones, data centers Broadcom and Texas Instruments cited by analysts as top picks High-profile smartphone releases and the growth of data centers are expected to drive another strong earnings quarter for chip makers and related companies, which would put a cap on a strong year for semiconductor stocks.\", \"Tech earnings: The iPhone X and other new gadgets that will matter this holiday season Apple\\u2019s expensive new smartphone, Fitbit Ionic among devices investors will focus on as companies release important forecasts Gadget companies and Silicon Valley tech titans alike have unveiled a swath of new toys leading up to the holiday shopping season and as earnings approach, investors can learn a great deal about what\\u2019s been successful\\u2014if they know what to look for.\", \"Apple bets on 'wireless future' with New Zealand takeover Apple Inc. is buying New Zealand company PowerbyProxi for an undisclosed sum in an effort to step deeper into the wireless tech market, media reports said on Wednesday. The takeover was first reported by New Zealand news site Stuff, while Reuters said an Apple spokesperson also confirmed the deal. Dan Riccio, senior vice president of hardware engineering at the California company, told Stuff the team at PowerbyProxi will be \\\"a great addition as Apple works to create a wireless future.\\\" The company recently said it was including wireless charging in its new iPhone X and iPhone 8 smartphones. Apple shares were down 0.2% in premarket trade on Wednesday.\", \"Apple initiated at buy at HSBC\", \"Apple initiated with a buy rating at HSBC HSBC initiated coverage of Apple Inc. stock on Wednesday with a buy rating and a $193 price target with analysts saying a large and loyal user base is eager to get hold of the iPhone X. Analysts led by Steven Pelayo said they are trying to take a unique look at Apple by embracing its marketing slogan and trying to 'think different,' using the perspectives of its analysts from around the world. The bank's consumer team says Apple is not just a tech company, but also competes with luxury brands for talent, wallet share and locations. The telecom team says the U.S. is a key market and that technologies like AI, AR and foldable phones will drive demand. The internet team believes China competition is not just with handset makers, but also with Tencent in services and with super apps like WeChat as a platform for mobile payments. \\\"The Automotive team expects heavy competition between current and future entrants around electrification, automation, entertainment and connectivity over the next few years,\\\" said Pelayo. \\\"The question is what level of vertical integration is required from an OEM perspective.\\\" Apple shares were flat in premarket trade, but have gained 35.6% in 2017, while the Dow Jones Industrial Average has gained about 19% and the S&P 500 has gained 15%.\", \"Shell Trims Tesla Stake; Buys PayPal, Adobe, FedEx A unit of the oil giant th\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": 0.023106, "explanation": "The actual 21-day forward return for VEA starting 2017-10-26 was +2.31%, which classifies as 'positive'.", "metadata": {"future_return": 0.023106, "horizon_days": 21, "hist_return": 0.02833, "annualized_vol": 0.071162, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190704_0861", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2019-07-04", "context_summary": "EWJ over past 60 days: cumulative return +2.3%, annualized vol 12.4%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=47.12, end=48.20, cumulative_return=+2.3%, annualized_volatility=12.4%\nMacro context: {'fed_funds_rate': 2.41, 'cpi_yoy': 255.802, 'unemployment': 3.7, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.19, 't10y3m_spread': -0.25, 'breakeven_10y': 1.65, 'hy_oas': 4.02, 'ig_oas': 1.2, 'ted_spread': 0.13, 'mortgage_30y': 3.75, 'vix': 12.56999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-03] [\"Why Microsoft Stock Owners Shouldn\\u2019t Worry About Linux Normally, a competitor\\u2019s increased presence, especially in one\\u2019s own turf, represents serious trouble. And under this context, consumer technology giant Microsoft (NASDAQ:) should be worried. Recently, a developer for the open-source platform Linux accidentally revealed that Linux-based operating systems had greater presence in Microsoft\\u2019s Azure cloud network than Microsoft-based OS\\u2019. Does this signal a dumping opportunity for Microsoft stock? Source: Shutterstock At first glance, the suddenly of Linux may startle stakeholders of Microsoft stock. After all, Linux is a free and open-source collaboration, meaning that it\\u2019s impossible to profit from its mere existence. Of course, that philosophy runs counter to Microsoft\\u2019s legacy revenue channels, where it sold programs and updates to those programs. By all accounts, it was an extremely profitable venture. But this latest bit of Microsoft news demonstrates that we\\u2019re no longer in the 20th century. And despite the optics, the Linux development is a long-term positive for MSFT stock. How so? Because MSFT is, when it comes to software-related ventures, moving firmly toward the Software as a Solution (SaaS) model. Not only that, but the rise of Linux helps shift the narrative to the concept that Microsoft stock will now trade on the fundamentals of service offerings, not standalone products. For management, it doesn\\u2019t really matter that Linux is the go-to choice for Azure users. For one thing, there\\u2019s the fact that Azure is cheaper to run on Linux than on any other platform. Even Microsoft benefited from Linux\\u2019s streamlined and efficient architecture to power its Internet of Things (IoT) devices. In other words, MSFT stock wins as long as Microsoft is somehow involved in the process. Office 2019 Offers Insight Into \\u201cNew\\u201d MSFT Stock When Microsoft 2019 launched during last year\\u2019s fall season, it many observers. By that time, the tech firm had decisively entered the SaaS arena, and for good reasons. Namely, SaaS makes perfect sense for MSFT stock on multiple levels. First, subscription-based models utilize an ongoing contractual relationship. While the subscriber has to pay constantly, they also have access to the SaaS entity\\u2019s service umbrella. Thus, when the need for updates arise \\u2014 and that need perpetually exists \\u2014 the platform automatically refreshes with relevant features. Second, the subscription model can quickly convert prospective buyers due to their much cheaper initial cost outlay. Once subs are on board, companies have greater chances to convert them to higher-margin services. Such strategies have rejuvenated Microsoft stock in the past. They\\u2019ve also done wonders for Adobe (NASDAQ:). So when MSFT launched Office 2019, the computing public viewed it as one of the strangest pieces of Microsoft news. Unlike Office 365, Office 2019 was not an SaaS plat\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": -0.025068, "explanation": "The actual 21-day forward return for EWJ starting 2019-07-04 was -2.51%, which classifies as 'negative'.", "metadata": {"future_return": -0.025068, "horizon_days": 21, "hist_return": 0.022876, "annualized_vol": 0.124211, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180627_0863", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2018-06-27", "context_summary": "PALL over past 60 days: cumulative return +3.4%, annualized vol 22.9%. Market regime: sideways.", "question": "Asset: PALL\nHistorical prices (past 60 trading days): start=88.25, end=91.29, cumulative_return=+3.4%, annualized_volatility=22.9%\nMacro context: {'fed_funds_rate': 1.92, 'cpi_yoy': 251.018, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.35, 't10y3m_spread': 0.95, 'breakeven_10y': 2.12, 'hy_oas': 3.48, 'ig_oas': 1.29, 'ted_spread': 0.44, 'mortgage_30y': 4.57, 'vix': 15.920000076293944}\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": "negative", "answer_numeric": -0.014722, "explanation": "The actual 21-day forward return for PALL starting 2018-06-27 was -1.47%, which classifies as 'negative'.", "metadata": {"future_return": -0.014722, "horizon_days": 21, "hist_return": 0.034448, "annualized_vol": 0.228912, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180629_0865", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2018-06-29", "context_summary": "EWJ over past 60 days: cumulative return -3.3%, annualized vol 8.8%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=51.15, end=49.45, cumulative_return=-3.3%, annualized_volatility=8.8%\nMacro context: {'fed_funds_rate': 1.91, 'cpi_yoy': 251.018, 'unemployment': 4.0, 'gdp_growth_qoq': 20150.476, 't10y2y_spread': 0.32, 't10y3m_spread': 0.91, 'breakeven_10y': 2.1, 'hy_oas': 3.64, 'ig_oas': 1.3, 'ted_spread': 0.45, 'mortgage_30y': 4.55, 'vix': 16.850000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-06-28] [\"These top-rated funds reveal some of the world\\u2019s hottest tech stocks All have beaten the S&P 500 tech sector for five years, and the holdings include less well-known companies such as Walsin Technology and Sino-American Silicon Products All have beaten the S&P 500 tech sector for five years, and the holdings include less well-known companies such as Walsin Technology and Sino-American Silicon Products.\", \"Ocasio-Cortez withholds support of Pelosi as House speaker | Trump to officiate at Foxconn groundbreaking McConnell vows vote on Supreme Court nominee before midterm elections Alexandria Ocasio-Cortez withholds support for Nancy Pelosi as House speaker; President Trump will officiate at a Foxconn facility groundbreaking on Thursday; and more.\", \"Here\\u2019s how much stock investors could lose in a \\u2018zero-sum\\u2019 trade war Critical information for the U.S. trading day The trade-war talk isn\\u2019t slowing down and our call of the day says global stocks could be set back years if this spat blows up.\", \"Cody Willard: I have more cash and hedges today than at any time in the past decade A trade war will knock the economy off-kilter A trade war will knock the economy off-kilter.\", \"DC Entertainment to launch digital subscription service in August DC Entertainment has begun accepting sign-ups for a beta version of its digital subscription service, dubbed DC Universe, the company announced Thursday. The beta version will launch in August, and a full launch will follow later in the fall. DC Entertainment is a subsidiary of Time Warner Inc., which was recently acquired by AT&T and renamed WarnerMedia. The subscription service will give fans access to new live-action and animated series, previously-released TV series and films and a curated, rotating selection of digital comic books, the company said. The platform will feature a social-media element where fans can connect with each other, earn rewards and participate in sweepstakes and contests. There will be shopping opportunities, as well. DC has not announced pricing yet, but is planning to launch DC Universe on iOS, Android, Roku, Apple TV, Amazon Fire TV, Android TV and the web, the company said. Shares of AT&T have fallen 18.3% so far this year, while the S&P 500 has gained 1.3%.\", \"Tech Today: Google vs Amazon, Buying Tesla, Lattice\\u2019s Turnaround Amazon's acquisition of pharmacy startup PillPack freaks out pharmacy stocks while its offer to help start small delivery businesses could be key to Whole Foods' expansion, Alphabet's Google needs to give away its home speaker to combat Amazon according to Morgan Stanley analyst Brian Nowak, now is the time to buy Tesla stock ahead of next week's Model 3 numbers according to Baird's Brian Kallo, T-Mobile's chances of getting Sprint are looking a little better to Wells Fargo's Jennifer Fritzsche, Lattice semiconductor may bounce back with new management and activist input thinks Dougherty's Charles Anderson, Square is no Amazon so says SunT\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.018477, "explanation": "The actual 21-day forward return for EWJ starting 2018-06-29 was +1.85%, which classifies as 'positive'.", "metadata": {"future_return": 0.018477, "horizon_days": 21, "hist_return": -0.033354, "annualized_vol": 0.088406, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160512_0867", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2016-05-12", "context_summary": "ACWI over past 60 days: cumulative return +7.5%, annualized vol 13.7%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=43.19, end=46.42, cumulative_return=+7.5%, annualized_volatility=13.7%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 239.557, 'unemployment': 4.8, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 0.99, 't10y3m_spread': 1.47, 'breakeven_10y': 1.59, 'hy_oas': 6.4, 'ig_oas': 1.57, 'ted_spread': 0.37, 'mortgage_30y': 3.61, 'vix': 14.6899995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-11] [\"WhatsApp launches desktop version for Mac, Windows Popular mobile messaging app rivals Skype, Apple\\u2019s iMessage WhatsApp, the massively popular smartphone messaging app owned by Facebook Inc., is now available in a familiar place: your computer\\u2019s desktop.\", \"Justice Inquiry Reveals Wall Street\\u2019s Dirty Secret Firms profit by trading against individual investors, who they consider \\u201cdumb money.\\u201d\", \"Neither Trump nor Clinton can do much for the job market Technology and demographics are driving change, and the best that politicians can do is help retrain displaced workers Technology and demographics are driving change, and the best that politicians can do is help retrain displaced workers, says Howard Gold.\", \"Axel Springer looks to U.S. for digital growth BERLIN--German media giant Axel Springer SE says its U.S.-focused push into digital media is starting to pay off. One of Europe's biggest digital publishers, the old-line tabloid giant was once known for its Bild and Die Welt newspapers. It has worked for years to shed its reliance on print and boost online revenue.\", \"Apple: iPhone Upgrades Slowing, Stock is \\u2018Range Bound,\\u2019 Says UBS UBS\\u2019s Steve Milunovich today reiterates a Buy rating on Apple (AAPL) shares, while trimming his price target to $115 from $120, writing that he\\u2019s trimming his estimates for Apple\\u2019s iPhone sales and profit after accepting the device is going to see longer upgrade cycles for the foreseeable future.His verdict on the shares: \\u201cThe stock is likely range bound for now with low multiples acting as downside support and lack of demand catalysts an upper ceiling.\\\"The company will benefit from some increase in upgrade sales in 2017, but only to match what happened in 2015:We now expect iPhone unit growth of about 4% in F17 with upgrade growth offsetting a decline in new users. Strong sales in F15 stole from F16 but upgrades should hit in F17 or F18. Earnings only get back to the F15 level in our model, so new products may be required to excite investors beyond a trade. Apple has both annuity and hardware hits aspects, but we think the best way to understand the company is as a platform deserving of valuation b\", \"Apple suppliers in Taiwan struggling amid weaker iPhone demand Taiwan Semiconductor faces slowdown due to weak demand for premium phones like the iPhone: Nikkei Apple\\u2019s A10 chip supplier Taiwan Semiconductor Manufacturing Co. faces a slowdown in the second-half of the year\", \"Apple: \\u2018Value Trap\\u2019 as Margins Come Under Pressure, Says Former Berenberg Analyst Adnaan Ahmad, who used to be a stock analyst with Berenberg Bank covering Apple (AAPL), until last year, today issues a missive to \\u2014 well, I\\u2019m not sure if he has clients at this point, but to anyone out there, in which he continues to press the deeply negative view of Apple shares, for which he offers a Sell rating and an $80 price target.Although the stock below $100 \\u2014 it\\u2019s at $\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.008536, "explanation": "The actual 21-day forward return for ACWI starting 2016-05-12 was +0.85%, which classifies as 'flat'.", "metadata": {"future_return": 0.008536, "horizon_days": 21, "hist_return": 0.074718, "annualized_vol": 0.137049, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20181015_0869", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2018-10-15", "context_summary": "XLP over past 60 days: cumulative return -0.2%, annualized vol 11.3%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=42.93, end=42.84, cumulative_return=-0.2%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 2.18, 'cpi_yoy': 252.772, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.3, 't10y3m_spread': 0.87, 'breakeven_10y': 2.12, 'hy_oas': 3.54, 'ig_oas': 1.16, 'ted_spread': 0.21, 'mortgage_30y': 4.9, 'vix': 21.309999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-12] [\"Here\\u2019s a dividend-investment strategy designed to outperform in down markets The Reality Shares DIVCON Leaders Dividend ETF screens for quality, based on the likelihood of large-cap companies raising payouts to shareholders The Reality Shares DIVCON Leaders Dividend ETF screens for quality, based on the likelihood of large-cap companies raising payouts to shareholders.\", \"All 30 Dow stocks rally premarket, led by Microsoft The 257-point rally in Dow Jones Industrial Average futures is unanimous early Friday, as all 30 components are trading higher in the premarket. Among the biggest gainers, shares of Microsoft Corp. ran up 2.9%, Visa Inc. climbed 2.6% and Cisco Systems Inc. rose 2.5%. The most active stock was Apple Inc.'s , which gained 2.3%. The Dow's bounce follows a 1,378-point drubbing the past two sessions. Microsoft's stock had shed 5.7% the past two sessions, as part of a sharp pullback in technology stocks.\", \"JPMorgan Jumps, Netflix Flies as Dow Steps Away From the Abyss The Nasdaq was up 1.7% as stocks like Microsoft, Fitbit and others got upgraded.\", \"How one investor sidestepped this week\\u2019s stock-market decline Holding cash and hedges protects you from losing money Holding cash and hedges protects you from losing money.\", \"Cody Willard: I\\u2019m adding Snap to the portfolio The shares have been hit so hard, it\\u2019s time to bite The shares have been hit so hard, it\\u2019s time to bite.\", \"Charting a dead-cat bounce, S&P 500 retests 200-day average from underneath Focus: 10-year yield tags 200-month moving average, Gold and gold miners take flight, Apple weathers the October downdraft, General Electric\\u2019s backdrop strengthens? U.S. stocks are higher early Friday, rising from deeply oversold conditions amid the damaging October market downdraft.\", \"Flanked by musicians, Trump signs music copyright bill into law Joined by Kid Rock, original Beach Boys member Mike Love, and other stars, President Trump signed the Music Modernization Act on Thursday to close loopholes in existing copyright legislation.\", \"Netflix Earnings Are Coming. Here\\u2019s What Matters As positive as the outlook for streaming video is, with tech stocks under fire investors will still focus on Netflix\\u2019s quarterly subscriber growth\", \"Netflix and PayPal Execs Brace for Earnings After Market Tumble A more candid earnings season looms. First up: Netflix, PayPal, and Lam Research.\", \"Stocks rally to close higher but log worst week since March S&P 500 snaps 6-day losing streak U.S. stock market rallies on Friday, with equities rising broadly in a partial rebound from a multiday rout that slashed about 1,400 points from the Dow Jones Industrial Average and left the Nasdaq on the precipice of a correction.\", \"Tech Stocks Could Rebound Again but the Risks Are Growing Tech stocks are likely to rebound after their latest drubbing, but the selloff suggests that investors are paying more attention to the sector\\u2019s challenges.\", \"The Momentum Trade Is D\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": 0.070019, "explanation": "The actual 21-day forward return for XLP starting 2018-10-15 was +7.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.070019, "horizon_days": 21, "hist_return": -0.002082, "annualized_vol": 0.11322, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20150306_0873", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2015-03-06", "context_summary": "VTI over past 60 days: cumulative return +2.9%, annualized vol 13.6%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=87.82, end=90.35, cumulative_return=+2.9%, annualized_volatility=13.6%\nMacro context: {'fed_funds_rate': 0.11, 'cpi_yoy': 235.976, 'unemployment': 5.4, 'gdp_growth_qoq': 18666.621, 't10y2y_spread': 1.46, 't10y3m_spread': 2.09, 'breakeven_10y': 1.84, 'hy_oas': 4.46, 'ig_oas': 1.31, 'ted_spread': 0.24, 'mortgage_30y': 3.75, 'vix': 14.039999961853027}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-03-05] [\"Apple delays production of larger iPad HONG KONG- Apple Inc. suppliers have been told to start production of a larger-screen iPad in the second half of this year as the U.S. tech giant wrestles with new designs and features for the enterprise market, people familiar with the matter say.\", \"Six reasons you should invest in the Wearables Revolution Wearables are a can't-miss growth market. The same kids (and adults) today who take selfies with their smartphones are going to be doing 10 times more of that using wearables, but how do investors make money?\", \"Why you should quit the QQQ in your IRA If you wouldn\\u2019t buy an index fund that tracks the NYSE or the Amex, why would you buy into the Nasdaq?\", \"Apple Watch could be $26 billion business by 2018 NEW YORK (MarketWatch) - The Apple Watch may be a $26 billion business by 2018, Deutsche Bank analyst Sherri Scribner predicted in a note Thursday. However, she only reiterated a hold rating on Apple Inc.'s stock, saying a limited impact from the Watch and Apple's heavy reliance on the iPhone offer \\\"limited catalysts\\\" to drive shares higher over the next few quarters. Her $110 price target implies a 14% share-price decline from Apple's $128.54 closing price on Wednesday. To be fair, Scribner is one of the most bearish Apple analysts on Wall Street. The average rating on Apple's stock among more than 40 analysts is overweight, and the average price target is $134.92, according to FactSet. While Apple will undoubtedly outsell all rival smartwatches this year, according to Scribner, she expects the Watch to remain a minor product category in relation to the iPhone, comprising 10% or less of sales and EPS by 2018. Shares of Apple traded up 0.3% in premarket trade.\", \"Apple to control 55% of smartwatch market by year end NEW YORK (MarketWatch) - Apple Inc. could sell as many as 15 million units of Apple Watch worldwide this year, according to new data from intelligence company Strategy Analytics. This comes in just shy of forecasts released earlier on Thursday by Deutsche Bank analyst Sherri Scribner, who is projecting 17.6 million watches. At that number, Apple, expected to launch the watch in early April, would be the world's biggest smartwatch vendor, holding a 55% share of the global market this year, according to Strategy Analytics. While the market for smartwatches has yet to be proven given the lack of blockbuster sales from Apple Watch predecessors, analysts believe the watch will help spark interest in the category. Total global smartwatch shipments are predicted to grow 511% to 28.1 million units this year from just 4.6 million in 2014, according to Strategy Analytics. Earlier on Thursday, Deutsche Bank predicted that the Apple Watch would become a $26 billion business by 2018. Shares of Apple fell 1.3% to $126.83 in recent trade.\", \"U.S. company earnings point to stock-market correction The price-to-earnings ratio hasn\\u2019t been so high since early 2010 The price-to-earnings ratio hasn\\u\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": 0.010947, "explanation": "The actual 21-day forward return for VTI starting 2015-03-06 was +1.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.010947, "horizon_days": 21, "hist_return": 0.028795, "annualized_vol": 0.136066, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20150918_0875", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2015-09-18", "context_summary": "XLP over past 60 days: cumulative return -0.8%, annualized vol 15.9%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=36.36, end=36.08, cumulative_return=-0.8%, annualized_volatility=15.9%\nMacro context: {'fed_funds_rate': 0.14, 'cpi_yoy': 237.498, 'unemployment': 5.0, 'gdp_growth_qoq': 18857.418, 't10y2y_spread': 1.51, 't10y3m_spread': 2.2, 'breakeven_10y': 1.58, 'hy_oas': 5.71, 'ig_oas': 1.66, 'ted_spread': 0.34, 'mortgage_30y': 3.91, 'vix': 21.13999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-09-17] [\"Foxconn Gets A Good Deal Out Of SPIL: Bernstein\", \"Demand for Apple's iPhone 6S may actually be lower than for the iPhone 6--Pacific Crest Analyst Andy Hargreaves at Pacific Crest said he believes demand for Apple Inc.'s iPhone 6S is actually lower than it was for the iPhone 6, \\\"possibly meaningfully so.\\\" He said Apple's statement that iPhone 6S sales are tracking at a record pace appears more a reflection of supply, and not demand. Hargreaves said evidence of lower demand comes from Google search data, device shipment times, third-party surveys, a lack of comments from carriers and a lack of quantitative comment on pre-orders in Apple's statement. He wrote in a note to clients that Apple's iPhone upgrade program isn't likely to drive the change that some expect, as \\\"the potential benefits are likely to be muted by likely financing costs, deflation in used iPhone pricing from increasing supply and cannibalization of people that already bought phones every year or already purchased AppleCare.\\\" He reiterated his sector weight rating on the stock, saying it remains \\\"attractive over the long term, but high iPhone expectations remain a near-term risk.\\\" The stock slipped 0.5% in premarket trade, putting it on track to snap a five-session win streak. It has dropped 8.6% over the past three months, while the Dow Jones Industrial Average has lost 6.7%.\", \"EU widens corporate tax investigation All countries agree to cooperate in probe of \\u2018sweetheart\\u2019 tax deals High-profile probe into alleged sweetheart tax deals broadened after all EU countries agree to cooperate.\", \"Judgment day for markets as Fed\\u2019s trigger finger gets itchier Critical intelligence before the U.S. market opens The Janet Yellen-led Federal Reserve could blast markets with the first U.S. rate hike in nearly a decade. If the Fed frenzy is too much for you, perhaps try stocks in Italy or France.\", \"Amazon introduces its answer to Apple TV Amazon.com Inc. launched an answer to Apple Inc.'s smart TV on Thursday - and it's much cheaper. The e-commerce giant introduced its latest-generation Amazon FireTV with 4K Ultra HD, which will sell for $99.99, versus $149 for Apple TV. It comes with a remote with voice control, and compatibility with Echo, its voice-assistance technology that competes with Apple's Siri. The company will also sell a higher-tier gaming edition, which comes with a new Amazon-designed game controller and a 32 GB microSD card. The gaming edition will sell for $139.99. Amazon began taking preorders for both devices on Tuesday. Apple is expected to open up preorders its new TV for preorders next month. Shares of Amazon climbed 1% to $532.45 in recent trade, while those of Apple slumped 0.9% to $115.40.\", \"Apple: Pac Crest Sees \\u2018Several Signs\\u2019 Demand for iPhone 6s is Weaker\", \"Amazon launches cheap tablet, offers six-pack deal for $250 Amazon.com Inc. launched a new 7-inch tablet on Thursday that it is offering for $49.99 - or a six pack for $249.95\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": 0.054025, "explanation": "The actual 21-day forward return for XLP starting 2015-09-18 was +5.40%, which classifies as 'positive'.", "metadata": {"future_return": 0.054025, "horizon_days": 21, "hist_return": -0.007642, "annualized_vol": 0.158958, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20201130_0877", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2020-11-30", "context_summary": "DBC over past 60 days: cumulative return +9.4%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: DBC\nHistorical prices (past 60 trading days): start=11.16, end=12.20, cumulative_return=+9.4%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 260.911, 'unemployment': 6.7, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.68, 't10y3m_spread': 0.75, 'breakeven_10y': 1.75, 'hy_oas': 4.35, 'ig_oas': 1.13, 'ted_spread': 0.14, 'mortgage_30y': 2.72, 'vix': 20.84000015258789}\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": "positive", "answer_numeric": 0.050215, "explanation": "The actual 21-day forward return for DBC starting 2020-11-30 was +5.02%, which classifies as 'positive'.", "metadata": {"future_return": 0.050215, "horizon_days": 21, "hist_return": 0.093604, "annualized_vol": 0.172254, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210924_0879", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2021-09-24", "context_summary": "EEM over past 60 days: cumulative return -6.8%, annualized vol 17.5%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=49.29, end=45.93, cumulative_return=-6.8%, annualized_volatility=17.5%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 273.91, 'unemployment': 4.7, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.14, 't10y3m_spread': 1.38, 'breakeven_10y': 2.31, 'hy_oas': 3.03, 'ig_oas': 0.89, 'ted_spread': 0.1, 'mortgage_30y': 2.88, 'vix': 18.6299991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-23] Interesting ADBE Put And Call Options For November 5th Investors in Adobe Inc (Symbol: ADBE) saw new options become available today, for the November 5th expiration. At Stock Options Channel, our YieldBoost formula has looked up and down the ADBE options chain for the new November 5th contracts and identified one put and one call contract of particular interest. The put contract at the $595.00 strike price has a current bid of $7.85. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $595.00, but will also collect the premium, putting the cost basis of the shares at $587.15 (before broker commissions). To an investor already interested in purchasing shares of ADBE, that could represent an attractive alternative to paying $629.52/share today. Because the $595.00 strike represents an approximate 5% 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 100%. 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 1.32% return on the cash commitment, or 11.20% annualized \u2014 at Stock Options Channel we call this the YieldBoost. Below is a chart showing the trailing twelve month trading history for Adobe Inc, and highlighting in green where the $595.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $640.00 strike price has a current bid of $13.20. If an investor was to purchase shares of ADBE stock at the current price level of $629.52/share, and then sell-to-open that call contract as a \"covered call,\" they are committing to sell the stock at $640.00. Considering the call seller will also collect the premium, that would drive a total return (excluding dividends, if any) of 3.76% if the stock gets called away at the November 5th expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if ADBE shares really soar, which is why looking at the trailing twelve month trading history for Adobe Inc, as well as studying the business fundamentals becomes important. Below is a chart showing ADBE's trailing twelve month trading history, with the $640.00 strike highlighted in red: Considering the fact that the $640.00 strike represents an approximate 2% premium 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 covered call contract would expire worthless, in which case the investor would keep both their shares of stock and the premium collected. The current analytical data (including g\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": 0.03013, "explanation": "The actual 21-day forward return for EEM starting 2021-09-24 was +3.01%, which classifies as 'positive'.", "metadata": {"future_return": 0.03013, "horizon_days": 21, "hist_return": -0.068178, "annualized_vol": 0.174918, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160908_0880", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2016-09-08", "context_summary": "IWM over past 60 days: cumulative return +10.1%, annualized vol 16.5%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=100.69, end=110.90, cumulative_return=+10.1%, annualized_volatility=16.5%\nMacro context: {'fed_funds_rate': 0.4, 'cpi_yoy': 241.176, 'unemployment': 5.0, 'gdp_growth_qoq': 19197.938, 't10y2y_spread': 0.8, 't10y3m_spread': 1.2, 'breakeven_10y': 1.51, 'hy_oas': 5.07, 'ig_oas': 1.4, 'ted_spread': 0.49, 'mortgage_30y': 3.46, 'vix': 11.9399995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-09-07] [\"7 Under-the-Radar Small-Cap Growth Stocks The Hood River Small-Cap Growth fund is trouncing its benchmark this year by finding mispriced companies.\", \"How Apple\\u2019s stock tends to trade around its September event Apple\\u2019s stock has historically risen 4% in the weeks after the event Apple\\u2019s shares tend to be on a rollercoaster ride in the weeks leading up to and following its product launches.\", \"Apple\\u2019s global wearables share halves to 7% Consumers opt for basic fitness bands over smart watches Apple\\u2019s share of the global wearables market has fallen to 7% as consumers opt for fitness bands instead of smart watches.\", \"All the iPhone buzz isn\\u2019t getting Apple over this hurdle Critical information before the U.S. market\\u2019s open There\\u2019s something for everyone today on iPhone day \\u2014 bulls, bears, haters, fanboys. Today\\u2019s chart comes from the Apple bears camp, flagging a level that has tripped up the stock all year. Our call is Apple-free, talking up energy stocks.\", \"Apple shares steady at $107.91 ahead of product announcement in early trade\", \"Apple: iPhone Failing as Fashion, More Like a Microwave Oven, Says BGC Ahead of Apple\\u2019s (AAPL) media event kicking off at 1 pm Eastern today, 10 am Pacific, Colin Gillis with BGC joins his voice to the chorus pontificating about the event, predicting that the iPhone is failing to meet the mark as a \\u201cfashion\\u201d device, imperiling Apple\\u2019s revenue growth.\\\"If Apple is positioning the iPhone as a fashion device,\\u201d writes Gillis, \\\"a reasonable point (and one supported by the fact that the SVP of retail is Angela Ahrendts, the former CEO of fashion brand Burberry), then issuing a flagship product with minimal style changes for a third straight year could cause a muted desire for its customer base to upgrade.\\\"Gillis, who has a Sell rating on Apple shares, and an $85 price target, quips that that buying one of the things will \\u201csoon be like buying a microwave \\u2014 something people do, but not a major event.\\\"Gillis sees the iPhone franchise in 2017 suffering revenue declines thanks to both share losses and price declines:\", \"Apple \\u2018Monitor\\u2019 Suggests Better-Than-Average FYQ4, Says Drexel\", \"The iPhone headset jack and Apple\\u2019s history of addition by subtraction Speculation has been in the air for months, but now that the day of the long-awaited Apple event is actually here, it\\u2019s time to, as the Wall Street Journal notes, \\u201clet the grumbling begin\\u201d over the company\\u2019s expected removal of the headphone jack from its next iPhone model.\", \"Apple: Nintendo Brings New Game \\u2018Super Mario Run\\u2019 to iPhone\", \"Amazon, Apple leak iPhone 7 photos ahead of Apple\\u2019s event Amazon product and accessories page has gone live An Amazon.com accessories page went live before Apple\\u2019s product event, revealing some photos and Bluetooth accessories for the next-generation iPhone.\", \"Apple Unveils Watch Series 2 with Water\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": -0.015904, "explanation": "The actual 21-day forward return for IWM starting 2016-09-08 was -1.59%, which classifies as 'negative'.", "metadata": {"future_return": -0.015904, "horizon_days": 21, "hist_return": 0.101492, "annualized_vol": 0.165072, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20170116_0882", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2017-01-16", "context_summary": "^VIX over past 60 days: cumulative return -22.1%, annualized vol 94.7%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=14.41, end=11.23, cumulative_return=-22.1%, annualized_volatility=94.7%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 243.618, 'unemployment': 4.7, 'gdp_growth_qoq': 19398.343, 't10y2y_spread': 1.19, 't10y3m_spread': 1.87, 'breakeven_10y': 1.99, 'hy_oas': 4.02, 'ig_oas': 1.28, 'ted_spread': 0.5, 'mortgage_30y': 4.12, 'vix': 11.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-13] [\"Nintendo, Sony Investors Can Expect Gains of 50% Nintendo\\u2019s Switch gaming console and a turnaround at Sony can send shares of both companies surging.\", \"Why this winner of a retail stock will keep on delivering Critical information for the U.S. trading day It\\u2019s retail sales day and a perfect opportunity to highlight the call of the day that involves one of the biggest players on the retail landscape. Here\\u2019s why it belongs in your portfolio to stay.\", \"Broadcom, IDT To Ride Apple\\u2019s iPhone Promotions, Says Pac Crest if you\\u2019re a chip investor holding Broadcom (AVGO), Integrated Device Technology (IDTI), or Analog Devices (ADI), don\\u2019t worry, writes Pacific Crest\\u2019s John Vinh, this morning, the companies should be okay given the pace of promotions on Apple\\u2019s (AAPL) iPhone 7.Vinh sees \\u201climited risk\\u201d for AVGO, ADI and IDTI, which are his \\u201cfavorite names\\u201d among Apple suppliers.\\\"Our December carrier surveys in North America and Western Europe indicate the return of holiday promotions at AT&T, T-Mobile and Verizon were effective in keeping inventories at healthy levels,\\u201d writes Vinh.That bodes well for sales of iPhone into the channel, he writes,Holiday promotions keep iPhone 7 inventories at very healthy levels. We observed that generous carrier promotions at AT&T and Verizon were effective in keeping inventory levels in check. AT&T was offering a \\\"buy one, get one free\\\" (BOGO) promotion on the iPhone 7, while Verizon was offering up to $400 trade- in credit towards the purchase of an iPhone 7. As a result, iPhone 7 inventories (DOI and absolute) declined m/m to just over 2 days and remain well below targeted levels of 6-10 days, while sell-through was roughly flat y/y. On the iPhone 7 Plus front, we are seeing supply gradually catching up with demand, though some stores are still experiencing shortages.\", \"Videogame Sales Are Fading and It\\u2019s Crushing GameStop It wasn\\u2019t a happy holiday season for GameStop. Sales fell 16% in the last nine weeks of the year.\", \"Apple: Not Clear It\\u2019s Investible for Five-Year Periods, Says Bernstein People continue to mull the negative remarks about Apple (AAPL) made by investor Peter Thiel to The New York Times on Wednesday.In case you missed it, Thiel was asked to \\u201cconfirm\\u201d or \\u201cdeny\\u201d statements put to him by Times columnist Maureen Dowd.Down posed the statement \\\"The age of Apple is over.\\\"Said Thiel,Confirm. We know what a smartphone looks like and does. It\\u2019s not the fault of Tim Cook, but it\\u2019s not an area where there will be any more innovation.Today\\u2019s pondering of that brief item comes from Toni Sacconaghi, a bull on the stock, with Bernstein, who was interviewed a short while ago by Scott Wapner, the host of CNBC\\u2019s \\u201cFast Money: Halftime Report.\\\"Asked by Wapner if he agreed, Sacconaghi replied,\", \"Tech Today: Pandora Zooms, GrubHub Up, Apple\\u2019s Debt Leverage Here are some things going on t\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": 0.008425, "explanation": "The actual 21-day forward return for ^VIX starting 2017-01-16 was +0.84%, which classifies as 'flat'.", "metadata": {"future_return": 0.008425, "horizon_days": 21, "hist_return": -0.22068, "annualized_vol": 0.947358, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190912_0884", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2019-09-12", "context_summary": "FXI over past 60 days: cumulative return -0.6%, annualized vol 19.4%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=35.61, end=35.38, cumulative_return=-0.6%, annualized_volatility=19.4%\nMacro context: {'fed_funds_rate': 2.13, 'cpi_yoy': 256.43, 'unemployment': 3.5, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.07, 't10y3m_spread': -0.21, 'breakeven_10y': 1.6, 'hy_oas': 3.92, 'ig_oas': 1.24, 'ted_spread': 0.21, 'mortgage_30y': 3.49, 'vix': 14.609999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-09-11] [\"Asian markets gain ahead of ECB meeting Nikkei, Hang Seng edge up as stocks in mainland China dip Asian markets mostly gained in early trading Wednesday, ahead of expected further monetary easing by the European Central Bank.\", \"Welcome to Borrower\\u2019s Paradise. How Long Can It Last? Stocks have returned to within a percent or two of their record highs, while bond yields have fallen to near-record lows, making equities\\u2019 valuations more attractive while also helping to fund share buybacks.\", \"Podcast: Apple Goes Head-to-Head With Netflix 3 numbers to help you navigate the market\\u2014in just two minutes.\", \"It\\u2019s \\u2018Too Soon to Bail\\u2019 on Apple, Amazon, and Other Top Tech Stocks For investors interested in the big FAANG tech stocks, it\\u2019s late in the game\\u2014but not too late to benefit, an analyst says.\", \"Apple iPhone event reveals a dramatic change in strategy Apple is now competing on price, after years of focusing on high margins One of the most surprising elements of Apple Inc.\\u2019s September iPhone launch was its aggressive pricing on many products, especially its new streaming service.\", \"Apple drops price on new iPhone 11, undercuts Netflix and Disney on streaming At annual event, Apple unveils three new iPhones, prices for streaming services Apple Inc. tried to make cameras the focus of its iPhone launch event on Tuesday, but the company\\u2019s most striking announcements concerned the prices of its phones and streaming offerings.\", \"Apple's stock gains 0.4% premarket after rising 1.2% on Tuesday\", \"Shift into value stocks could fuel a solid rally, says J.P. Morgan Critical information for the U.S. trading day J.P. Morgan quant strategists Marko Kolanovic and Bram Kaplan say this switch to value stocks seen lately could be promising.\", \"Apple stock price target raised to $250 from $240 at BofA Merrill Lynch\", \"Dow's nearly 75-point jump highlighted by gains for Apple Inc., Walgreens Boots shares\", \"Apple on the verge of reaching $1 trillion in market cap for first time in 10 months Shares of Apple Inc. rallied 1.7% toward a 10-month high in morning trading Wednesday, after rising 1.2% the previous sessions on the back of the technology behemoth's iPhone launch event. With the stock's recent rally, Apple is on the verge of getting back to being a trillion dollar company, something it hasn't been since Nov. 1, 2018; Apple's market capitalization is currently $995.4 billion. The stock only needs to rise another 0.5% to close at or above $221.28 for Apple's market cap to top $1 trillion, based on the latest disclosed 4.52 billion shares outstanding as of July 19. Getting back to being a trillion-dollar company would complete a recovery from a market-cap low of about $672.5 billion on Jan. 3, when the stock closed at a 21-month low of $142.19. Since then, Apple's stock has run up 55%, while the Dow Jones Industrial Average has gained 19%. Apple's market cap is still behind first-place Microsoft Corp. at $1.04 trilli\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": -0.003616, "explanation": "The actual 21-day forward return for FXI starting 2019-09-12 was -0.36%, which classifies as 'flat'.", "metadata": {"future_return": -0.003616, "horizon_days": 21, "hist_return": -0.00649, "annualized_vol": 0.194399, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200203_0887", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2020-02-03", "context_summary": "XRP-USD over past 60 days: cumulative return +12.5%, annualized vol 55.3%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.22, end=0.25, cumulative_return=+12.5%, annualized_volatility=55.3%\nMacro context: {'fed_funds_rate': 1.59, 'cpi_yoy': 259.25, 'unemployment': 3.5, 'gdp_growth_qoq': 20709.212, 't10y2y_spread': 0.18, 't10y3m_spread': -0.04, 'breakeven_10y': 1.65, 'hy_oas': 4.03, 'ig_oas': 1.09, 'ted_spread': 0.23, 'mortgage_30y': 3.51, 'vix': 18.84000015258789}\nMarket regime: sideways\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": 0.062837, "explanation": "The actual 21-day forward return for XRP-USD starting 2020-02-03 was +6.28%, which classifies as 'positive'.", "metadata": {"future_return": 0.062837, "horizon_days": 21, "hist_return": 0.124731, "annualized_vol": 0.553298, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200601_0890", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2020-06-01", "context_summary": "ITB over past 60 days: cumulative return -5.5%, annualized vol 56.1%. Market regime: sideways.", "question": "Asset: ITB\nHistorical prices (past 60 trading days): start=43.70, end=41.30, cumulative_return=-5.5%, annualized_volatility=56.1%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 255.802, 'unemployment': 13.2, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.49, 't10y3m_spread': 0.51, 'breakeven_10y': 1.15, 'hy_oas': 6.54, 'ig_oas': 1.87, 'ted_spread': 0.2, 'mortgage_30y': 3.15, 'vix': 27.51000022888184}\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": 0.019961, "explanation": "The actual 21-day forward return for ITB starting 2020-06-01 was +2.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.019961, "horizon_days": 21, "hist_return": -0.054945, "annualized_vol": 0.561133, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20151028_0892", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2015-10-28", "context_summary": "EWJ over past 60 days: cumulative return -3.6%, annualized vol 24.6%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=41.75, end=40.26, cumulative_return=-3.6%, annualized_volatility=24.6%\nMacro context: {'fed_funds_rate': 0.12, 'cpi_yoy': 237.733, 'unemployment': 5.0, 'gdp_growth_qoq': 18892.206, 't10y2y_spread': 1.4, 't10y3m_spread': 2.02, 'breakeven_10y': 1.48, 'hy_oas': 6.07, 'ig_oas': 1.67, 'ted_spread': 0.29, 'mortgage_30y': 3.79, 'vix': 15.43000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-10-27] [\"Risk Aversion Returns As China Stocks Dip: Apple Suppliers Retreat\", \"How JPMorgan Could Leapfrog Apple Pay JPMorgan\\u2019s Chase Pay has the scale out of the gate to become the most viable PayPal competitor.\", \"Broadcom Boosted by Supplying Apple Broadcom is ramping parts for the iPhone 6s ahead of a fourth-quarter push for its new data-center switching chipset.\", \"J.P. Morgan retooling Chase Pay product to better compete with Apple Pay Bank plans to partner with merchants to make service easier to use.\", \"This is the scare investors should be bracing for Critical intelligence before the U.S. market opens You\\u2019ve got oil prices and Apple for this stock market. One is pulling it one way, and the other another. Then you\\u2019ve got a key decision at the end of the week. Could be a rough ride for markets.\", \"IBM Adds $4B to Share Buyback\", \"Apple: Are the Best Days Over?\", \"J.P. Morgan Chase is latest to invest in future of mobile payments Mobile payment systems are emerging at a dizzying pace Pulling out a wad of cash, or writing a check at the Whole Foods checkout counter, are already outmoded ways of paying for goods. And as mobile payment systems continue to evolve, plastic credit cards could be on their way out the door as well.\", \"In one chart: How Microsoft has trumped Apple since Steve Jobs\\u2019s death Microsoft\\u2019s taken a bite out of Apple since 2011 Returns on Apple\\u2019s stock over the past four years haven\\u2019t been as good as those in one of its rivals: Microsoft.\", \"Think you know a lot about Apple? Our quiz thinks different Before you start wading through the numbers and the conference call, let\\u2019s see how well you really know the most valuable company in the world.\", \"What to watch for in Apple\\u2019s earnings Apple could be on track for 12th straight quarter of EPS beats Apple is expected to report earnings after the market\\u2019s close on Tuesday.\", \"Apple Q4 EPS $1.96 vs. FactSet consensus $1.88\", \"Apple Q4 revenue $51.5 bln vs. FactSet consensus $50.1 billion\", \"Apple stock up more than 2% after-hours following results\", \"Apple Up 3%: FYQ4 Rev $51.5B, EPS $1.96/Sh Beat; Q1 Rev View Light\", \"U.S. stocks slide for second day ahead of Fed policy statement Apple loses ground ahead of quarterly earnings U.S. stocks slip for the second day in a row Tuesday, as slumping oil prices and soft economic data weigh. Mixed earnings reports also prompt investors to take a cautious stance a day ahead of the Federal Reserve\\u2019s policy statement.\", \"Apple earnings lifted by iPhone sales in China Apple Inc. said its quarterly profit rose 31%, sparked by strong demand for iPhones in China. Booming iPhone sales have propelled the company to a string of strong results while withstanding a slowdown in the global smartphone market. Apple followed up its first large-screen iPhones with a pair of new releases in late September, but the company faces questions about whether it can maintain its sales momentum of the past year.\", \"Apple\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.003195, "explanation": "The actual 21-day forward return for EWJ starting 2015-10-28 was -0.32%, which classifies as 'flat'.", "metadata": {"future_return": -0.003195, "horizon_days": 21, "hist_return": -0.03577, "annualized_vol": 0.245542, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220531_0894", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2022-05-31", "context_summary": "IWM over past 60 days: cumulative return -5.4%, annualized vol 29.9%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=188.25, end=178.16, cumulative_return=-5.4%, annualized_volatility=29.9%\nMacro context: {'fed_funds_rate': 0.83, 'cpi_yoy': 291.298, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.27, 't10y3m_spread': 1.66, 'breakeven_10y': 2.63, 'hy_oas': 4.19, 'ig_oas': 1.41, 'ted_spread': 0.09, 'mortgage_30y': 5.1, 'vix': 25.71999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-05-27] [\"5 Growth Stocks For Your June 2022 Watchlist Are These The Best Growth Stocks To Buy Right Now? There\\u2019s no question that the stock market has taken quite a beating in recent months. And many of the top growth stocks are down along with it. Thus, some may find investing in these growth names less appealing compared to when the pandemic first started. Now, with the Fed taking a more aggressive stance on both interest rate hikes and tapering, it\\u2019s natural that investors are bearish on these stocks. But that doesn\\u2019t mean these are not great investments. Perhaps, what you need is a longer investment horizon. Investing in growth stocks involves having a long-term mindset. And adopting a long-term mindset will help you sift through the noise in the stock market and focus on the underlying business instead of the volatility of stock prices. With so much uncertainty continuing to loom over the stock market today, finding the best growth stocks to buy can be challenging. With the Nasdaq solidly in bear market territory and the S&P 500 dipping more than 15% from its record high, would now be a good time to put money into these stocks? If you believe so, here are five growth stocks to watch right now. Growth Stocks To Watch In June 2022 NVIDIA Corporation (NASDAQ: NVDA) Shopify Inc. (NYSE: SHOP) Sea Ltd. (NYSE: SE) Upstart Holdings Inc. (NASDAQ: UPST) Adobe Inc. (NASDAQ: ADBE) Nvidia When looking for top growth stocks to buy, graphics specialist Nvidia would often come to mind. The semiconductor giant reported better-than-expected figures earlier this week. From the latest quarterly report, revenue came in 46% higher at $8.29 billion. While the growth rate is lower than the previous quarter\\u2019s 53%, revenue still beat expectations of $8.1 billion. All in all, the company cites continuous strength in its gaming section. In detail, sales were driven by the GeForce RTX 30 Series, which remains the company\\u2019s best gaming product cycle in history. What\\u2019s more, reports said Cathie Wood purchased nearly 250,000 shares of NVDA stock across three ETFs, with the bulk of shares going towards her flagship fund. If anything, her latest investment in Nvidia may signal that this may be a good time to initiate a position for a long-term hold. Considering the upbeat quarter and Wood\\u2019s latest investment, would you be doing the same? [Read More] Best Stocks To Invest In Right Now? 5 Value Stocks To Watch This Week Shopify E-commerce innovator Shopify emerged as the pandemic darling, but its first-quarter report sent its shares falling. But before we give this stock a pass, let\\u2019s take a closer look at the most recent fiscal report. For the quarter, revenue came in 22% higher year-over-year to $1.2 billion. Additionally, its monthly recurring revenue also improved to $105.2 million, up 17% year-over-year. Admittedly, these figures may not be as exhilarating as those during the early stages of the pandemic. However, it does not change the fa\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": -0.083663, "explanation": "The actual 21-day forward return for IWM starting 2022-05-31 was -8.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.083663, "horizon_days": 21, "hist_return": -0.053615, "annualized_vol": 0.298552, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200427_0898", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2020-04-27", "context_summary": "VLUE over past 60 days: cumulative return -23.0%, annualized vol 37.8%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=74.38, end=57.26, cumulative_return=-23.0%, annualized_volatility=37.8%\nMacro context: {'fed_funds_rate': 0.05, 'cpi_yoy': 256.032, 'unemployment': 14.8, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.38, 't10y3m_spread': 0.48, 'breakeven_10y': 1.11, 'hy_oas': 8.03, 'ig_oas': 2.34, 'ted_spread': 0.77, 'mortgage_30y': 3.33, 'vix': 35.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-04-24] [\"The Zacks Analyst Blog Highlights: Microsoft, Apple, Adobe, Nvidia and Salesforce\", \"Adobe Stock Gets A Handle On Coronavirus Market Recovery\", \"Adobe Stock Gets A Handle On Coronavirus Market Recovery\", \"The Zacks Analyst Blog Highlights: Microsoft, Apple, Adobe, Nvidia and Salesforce\", \"3 Stocks You Can Set and Forget Capitalism is brutally competitive. To thrive over the long term, a company must do something special to protect itself from the opposition. Adobe Systems (NASDAQ: ADBE), Intuitive Surgical (NASDAQ: ISRG), and Visa (NYSE: V) all boast enviable track records of success. Each of these businesses is protected by a wide economic moat that shelters it from the forces of capitalism. All three of these businesses are major components in my portfolio. Here's why I believe that all of them are built to last. Image source: Getty Images. Adobe Systems Photoshop. Illustrator. After Effects. Acrobat. Premiere. Lightroom. Dreamweaver. If you are a creative professional, then the odds are very good that you are familiar with many -- if not all -- of these products. Adobe has been the top dog in digital media software for decades. The company's products are often viewed as the industry standard in their category. They're used by millions of consumers, creative professionals, designers, and enterprises around the world. Learning how to use software can take a long time, so once a user becomes comfortable with a product, they tend to stick with it for years. At the same time, Adobe's brand name has become synonymous with quality software. When combined, these attributes keep Adobe protected from the competition. A few years ago, Adobe transitioned to a software-as-a-service business model, which helps make its revenue (and profits) far more predictable than ever before. Wall Street has responded to the move by bidding up the share price to new highs. With lots of growth runway left ahead, I could see this trend continuing for many years. Meanwhile, Adobe has plenty of financial assets to weather the COVID-19 pandemic. With more than $4 billion in cash and equivalents and consistent cash flow coming in (more than $1.2 billion last quarter), there's no doubt in my mind that this company has staying power. Intuitive Surgical Intuitive Surgical pioneered the concept of robotic surgery. Its da Vinci system enabled surgeons to perform more than 1.25 million minimally invasive surgical procedures last year. Intuitive has had this market all to itself for two decades. That has allowed it to build up a global install base of more than 5,600 systems. That's important, as once healthcare providers become trained on how to use the da Vinci, they become resistant to switching. The training and time costs of learning something new are simply too high. The beauty of Intuitive's model is that it makes most of its money off disposable instruments and accessories, as well as through service contracts. This razor and blade business model is a big reason why the com\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": 0.080868, "explanation": "The actual 21-day forward return for VLUE starting 2020-04-27 was +8.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.080868, "horizon_days": 21, "hist_return": -0.230202, "annualized_vol": 0.378312, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220215_0900", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2022-02-15", "context_summary": "BTC-USD over past 60 days: cumulative return -7.8%, annualized vol 47.1%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=46202.14, end=42586.92, cumulative_return=-7.8%, annualized_volatility=47.1%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 284.5, 'unemployment': 3.9, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.4, 't10y3m_spread': 1.55, 'breakeven_10y': 2.48, 'hy_oas': 3.74, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 3.69, 'vix': 28.32999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-02-14] \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": -0.130968, "explanation": "The actual 21-day forward return for BTC-USD starting 2022-02-15 was -13.10%, which classifies as 'negative'.", "metadata": {"future_return": -0.130968, "horizon_days": 21, "hist_return": -0.078248, "annualized_vol": 0.471263, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20161228_0902", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2016-12-28", "context_summary": "VEA over past 60 days: cumulative return -1.7%, annualized vol 9.3%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=28.05, end=27.57, cumulative_return=-1.7%, annualized_volatility=9.3%\nMacro context: {'fed_funds_rate': 0.66, 'cpi_yoy': 242.637, 'unemployment': 4.7, 'gdp_growth_qoq': 19304.352, 't10y2y_spread': 1.29, 't10y3m_spread': 2.06, 'breakeven_10y': 1.99, 'hy_oas': 4.11, 'ig_oas': 1.28, 'ted_spread': 0.49, 'mortgage_30y': 4.3, 'vix': 11.989999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-12-27] The Zacks Analyst Blog Highlights: IBM, BP, Disney, Adobe and Cisco For Immediate Release Chicago, IL - December 27, 2016 - 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 IBM (NYSE: IBM - Free Report ), BP (NYSE: BP - Free Report ), Disney (NYSE: DIS - Free Report ), Adobe (NASDAQ: ADBE - Free Report ) and Cisco (NASDAQ: CSCO - Free Report ). Today, Zacks is promoting its ''Buy'' stock recommendations. Get #1Stock of the Day pick for free. Here are highlights from Friday's Analyst Blog: Stock Research Reports for Tuesday: IBM, BP, DIS Today's Research Daily features new research reports on 16 major stocks, including IBM (NYSE: IBM - Free Report ), BP (NYSE: BP - Free Report ) and Disney (NYSE: DIS - Free Report ). IBM shares lagged the technology space and the S&P 500 index over the last few years as the company struggled to reposition its business to the evolving business landscape. But the stock turned around this year (up +21.4% in the year-to-date period vs. +9.3% for the Zacks Technology sector) on greater appreciation for the company's outlook. The Zacks analyst likes IBM's strategic growth initiatives, including its Big Data & business analytics, cloud computing, mobile and social business. The company is expected to report Q4 results on January 17th. (You can read the full research report on IBM here >>> ) The turnaround in oil prices this year has benefited all oil players, BP included. BP shares have gained in excess of +18% this year, modestly below the Zacks Oil Integrated industry's +19.1% gain. The Zacks analyst likes the company's major expense reductions over the last four quarters, which is expected to remain a focus in the coming quarters as well. BP is scheduled to report Q4 results on February 7th, with the oil giant expected to report $0.50 per share on $52.2 billion in revenues. While upstream volumes are expected to be modestly up from the Q3 level, the refining business could be under pressure. (You can read the full research report on BP here >>> ) Disney shares have struggled this year, weighed down by concerns about ESPN whose future growth has been clouded by the evolving media landscape as a result of 'cord cutting' and the steady migration of subscribers to online and digital platforms. However, management anticipates reporting modest earnings growth in fiscal 2017 and a \"more robust growth\" in fiscal 2018. The Zacks analyst likes Disney's movie business and the parks & resorts division. The company is expected to report Q4 results on February 14th. (You can read the full research report on Disney here >>> ) Other noteworthy reports we are featuring today include Adobe (NASDAQ: ADBE - Free Report ) and Cisco (NASDAQ: CSCO - Free Report ). You can check all of today's research reports here >>> Today's Long-Term Buys & Sells Today \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": 0.04623, "explanation": "The actual 21-day forward return for VEA starting 2016-12-28 was +4.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.04623, "horizon_days": 21, "hist_return": -0.016888, "annualized_vol": 0.093353, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20200603_0904", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2020-06-03", "context_summary": "QQQ over past 60 days: cumulative return +22.0%, annualized vol 36.1%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=186.55, end=227.57, cumulative_return=+22.0%, annualized_volatility=36.1%\nMacro context: {'fed_funds_rate': 0.06, 'cpi_yoy': 257.042, 'unemployment': 11.0, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.51, 't10y3m_spread': 0.53, 'breakeven_10y': 1.18, 'hy_oas': 6.18, 'ig_oas': 1.81, 'ted_spread': 0.18, 'mortgage_30y': 3.15, 'vix': 26.84000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-02] [\"American Pie\", \"Tech Giants Dare Antitrust Deal Watchdogs\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Apple Cuts iPhone Prices in China To Push Sales As Country Reopens Economy\", \"Pepper Spray, Books On Racism, 'I Can't Breathe' Merchandise Are Top Sellers On Amazon As Protests Rage\", \"A Peek Into The Markets: US Stock Futures Up; Crude Oil Rises Over 2%\", \"Tesla CEO Musk Says Other Three Officers Should Be Charged In Floyd's Murder Case\", \"Hearing Susquehanna Check Suggests Total iPhone 12 Builds Tracking To 10M, Below Firm's Expectation Of 25M; Unconfirmed\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"'Apple is tracking iPhones stolen by looters' -Earlier NY Post Article\", \"'Apple is tracking iPhones stolen by looters' -Earlier NY Post Article\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Hearing Susquehanna Check Suggests Total iPhone 12 Builds Tracking To 10M, Below Firm's Expectation Of 25M; Unconfirmed\", \"Tesla CEO Musk Says Other Three Officers Should Be Charged In Floyd's Murder Case\", \"A Peek Into The Markets: US Stock Futures Up; Crude Oil Rises Over 2%\", \"Pepper Spray, Books On Racism, 'I Can't Breathe' Merchandise Are Top Sellers On Amazon As Protests Rage\", \"American Pie\", \"Tech Giants Dare Antitrust Deal Watchdogs\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"'Apple is tracking iPhones stolen by looters' -Earlier NY Post Article\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Hearing Susquehanna Check Suggests Total iPhone 12 Builds Tracking To 10M, Below Firm's Expectation Of 25M; Unconfirmed\", \"Tesla CEO Musk Says Other Three Officers Should Be Charged In Floyd's Murder Case\", \"A Peek Into The Markets: US Stock Futures Up; Crude Oil Rises Over 2%\", \"Pepper Spray, Books On Racism, 'I Can't Breathe' Merchandise Are Top Sellers On Amazon As Protests Rage\", \"American Pie\", \"Tech Giants Dare Antitrust Deal Watchdogs\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Here\\u2019s why the \\u2018unloved but welcome\\u2019 U.S. stock market rally from March lows won\\u2019t last, Goldman says Brief hopes that U.S.-China trade tensions may subside appear to have been dashed.\", \"Apple's stock slips 0.3% premarket, reversing earlier gains of as much as 0.7%\", \"How Apple Could Soar to a Valuation of $2 Trillion Apple is the world\\u2019s most highly valued company, with a market capitalization of $1.389 trillion. It is near the record closing level of $327.20 it hit in February, but Evercore ISI analyst Amit Daryanani thinks the stock can go higher.\", \"A semiconductor \\u2018cold war\\u2019 is heating up between the U.S. and China The world runs on semiconductors, most of which pass through Taiwan The world runs on semiconductors, most of which pass through Taiwan.\", \"Why Protests Rarely Rattle Markets The U.S. is experiencing painful civil\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": 0.067339, "explanation": "The actual 21-day forward return for QQQ starting 2020-06-03 was +6.73%, which classifies as 'positive'.", "metadata": {"future_return": 0.067339, "horizon_days": 21, "hist_return": 0.21988, "annualized_vol": 0.360567, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220606_0908", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2022-06-06", "context_summary": "QQQ over past 60 days: cumulative return -7.5%, annualized vol 34.8%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=322.62, end=298.57, cumulative_return=-7.5%, annualized_volatility=34.8%\nMacro context: {'fed_funds_rate': 0.83, 'cpi_yoy': 294.957, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.3, 't10y3m_spread': 1.75, 'breakeven_10y': 2.74, 'hy_oas': 4.21, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 5.09, 'vix': 24.790000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-03] [\"Apple Was the Worst Stock in the Dow Friday The Dow Jones Industrial Average dropped close to 350 points on Friday, despite a better-than-expected jobs report. For the week, however, the Dow Jones finished higher by nearly 165 points as volatile trading continued. No stock in the Dow saw a bigger percentage drop than Apple (NASDAQ: AAPL), which fell nearly 4% today after several analysts warned about slowing App Store revenue growth. Intel (NASDAQ: INTC) was the day's second-biggest loser on a percentage basis, finishing the day more than 3% down. Although ADP reported yesterday that private payrolls in May added the smallest number of new jobs since the COVID-19 recovery began, the U.S. Bureau of Labor Statistics reported today that nonfarm payrolls added 390,000 jobs last month. That was much stronger than the 328,000 jobs that most economists had been expecting. The conflicting data is nothing new, as investors struggle to try and figure out where the economy could land over the next six to 18 months. Slowing App Store growth at Apple Morgan Stanley analyst Katy Huberty warned today that App Store revenue growth may have started to slow in May, hinting that services revenue at Apple could come in weaker for the current quarter than many had initially thought. Huberty pointed to data from a company called Sensor Tower that showed just 4% revenue growth in May on a year-over-year basis. \\\"While we believe Apple user spending is more resilient at all stages of the economic cycle, which positions Apple better than other consumer hardware peers, a deceleration in App Store growth likely points to fading consumer spending on goods/services that accelerated during the pandemic,\\\" Huberty wrote in a research note. Image source: Getty Images. App Store revenue is a big component of the company's services revenue, which made up more than 20% of net sales in the tech giant's most recent quarter. Huberty projects that App Store revenue could fall by as much as $560 million from her initial forecast, which could hit her services revenue forecast for the current quarter by more than 3%. Huberty's note is the second warning this week from analysts. Evercore analyst Amit Daryanani also noted yesterday that the 4% growth is weaker than the 9% year-over-year App Store revenue growth Apple saw in April. \\\"We had expected growth to accelerate as comps became easier, so the slowdown is somewhat surprising, especially as China saw a large deceleration when we were anticipating some uplift from the ongoing lockdowns,\\\" Daryanani wrote in a research note. Still, even though App Store revenue growth might be slowing, both Huberty and Daryanani are bullish on the stock. Huberty has an \\\"overweight\\\" rating on Apple and a price target of $195. Daryanani also has an \\\"overweight\\\" rating and price target of $210. Apple closed the day at $145 per share, implying substantial upside to both of the analysts' price targets. Why Apple could bounce back The analysts are right\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.037995, "explanation": "The actual 21-day forward return for QQQ starting 2022-06-06 was -3.80%, which classifies as 'negative'.", "metadata": {"future_return": -0.037995, "horizon_days": 21, "hist_return": -0.074536, "annualized_vol": 0.347922, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20191211_0910", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-12-11", "context_summary": "LINK-USD over past 60 days: cumulative return -12.9%, annualized vol 54.6%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=2.61, end=2.27, cumulative_return=-12.9%, annualized_volatility=54.6%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 258.63, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.2, 't10y3m_spread': 0.29, 'breakeven_10y': 1.71, 'hy_oas': 3.84, 'ig_oas': 1.07, 'ted_spread': 0.36, 'mortgage_30y': 3.68, 'vix': 15.68000030517578}\nMarket regime: sideways\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": -0.170524, "explanation": "The actual 21-day forward return for LINK-USD starting 2019-12-11 was -17.05%, which classifies as 'negative'.", "metadata": {"future_return": -0.170524, "horizon_days": 21, "hist_return": -0.129056, "annualized_vol": 0.545546, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181106_0913", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2018-11-06", "context_summary": "MTUM over past 60 days: cumulative return -3.6%, annualized vol 20.7%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=103.60, end=99.88, cumulative_return=-3.6%, annualized_volatility=20.7%\nMacro context: {'fed_funds_rate': 2.2, 'cpi_yoy': 252.594, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.29, 't10y3m_spread': 0.84, 'breakeven_10y': 2.06, 'hy_oas': 3.72, 'ig_oas': 1.25, 'ted_spread': 0.27, 'mortgage_30y': 4.83, 'vix': 19.959999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-11-05] [\"When the going gets tough, Apple hides its numbers Apple will stop reporting unit sales for its largest businesses as iPhone sales stall Apple Inc. dropped a bomb on Thursday, but it wasn\\u2019t the weak forecast for the holiday quarter: It was the fact that it will no longer disclose unit sales of its products for investors, as it has for more than a decade.\", \"Apple predicts record holiday sales, but that isn\\u2019t enough to save stock Apple falls in late trading despite earnings beat, thanks to forecast that appears cautious for several reasons Apple Inc. revealed a blockbuster September quarter Thursday and predicted record revenue for the holiday season. That wasn\\u2019t good enough for investors, though.\", \"Apple stock suffers worst day in more than four years after \\u2018Houdini-like move\\u2019 with earnings \\u2018The uncertainty that speculation breeds is rarely positive,\\u2019 BTIG writes of decision to eliminate unit-sales disclosures Apple shares dropped Friday, after the smartphone manufacturer beat expectations with its latest results but delivered a disappointing forecast and announced that it would no longer be providing unit-sales figures for the iPhone and other hardware products.\", \"Apple's stock falls 0.9% premarket, after tumbling 6.6% on Friday\", \"In sweeping interview, Elon Musk says Tesla will be cash-flow positive \\u2018all quarters going forward\\u2019 \\u2018Some people use their hair to express themselves; I use Twitter,\\u2019 Musk says Up until September, it was do or die for Silicon Valley car maker, Elon Musk says.\", \"Apple curbs plans for additional iPhone XR production lines: report Apple Inc. has told companies that assemble its smartphones to halt plans for new production lines that would add iPhone XR capacity, the Nikkei Asian Review reported Monday. The report, which cites multiple unnamed sources, said that Apple has given these instructions to Hon Hai Precision Industry Co. Ltd. , better known as Foxconn, and Pegatron. Apple increased orders for the iPhone 8 and iPhone 8 Plus, two cheaper devices that launched a year ago, according to sources. The report comes a few days after Apple delivered a disappointing December-quarter earnings outlook and disclosed that it would stop reporting unit-sales figures for its various product lines. The company didn't immediately respond to a MarketWatch request for comment. Apple shares are off 1.6% in premarket trading, and they're down 7.5% over the past month. The Dow Jones Industrial Average has slipped 4.5% in that time.\", \"Berkshire Hathaway Climbs, but Dow Slips Because Even Warren Buffett Can\\u2019t Lift the Market by Himself U.S. stocks weakened ahead of the open as jitters continue despite an earnings season that is turning out to be more or less as good as in the second quarter.\", \"Amazon discussions fuel speculation that northern Virginia is \\u2018HQ2\\u2019 front runner Sources say detailed talks have focused on Crystal City, Va. Sources tell the Washington Pos\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": -0.047131, "explanation": "The actual 21-day forward return for MTUM starting 2018-11-06 was -4.71%, which classifies as 'negative'.", "metadata": {"future_return": -0.047131, "horizon_days": 21, "hist_return": -0.03589, "annualized_vol": 0.206895, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180330_0915", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2018-03-30", "context_summary": "EEM over past 60 days: cumulative return -0.4%, annualized vol 24.6%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=40.37, end=40.21, cumulative_return=-0.4%, annualized_volatility=24.6%\nMacro context: {'fed_funds_rate': 1.68, 'cpi_yoy': 249.577, 'unemployment': 4.0, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.47, 't10y3m_spread': 1.01, 'breakeven_10y': 2.05, 'hy_oas': 3.79, 'ig_oas': 1.16, 'ted_spread': 0.61, 'mortgage_30y': 4.44, 'vix': 19.96999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-03-29] [\"Can the stock market stand up to the tech wreck? Bull market loses its leader The key question for investors is whether a sharp selloff in tech shares puts the broader bull market in danger.\", \"How to know when to buy, sell or hold popular tech stocks today Amid increasing volatility, investors need to understand position size, time horizon and diversification Amid increasing volatility, investors need to understand position size, time horizon and diversification.\", \"Smart Home Devices: These Categories Are Growing the Fastest As new categories emerge, smart speakers are still expected to grow quickly.\", \"Spotify initiated at outperform by RBC ahead of trading debut RBC Capital Markets analyst Mark Mahaney initiated shares of Spotify Technology with an outperform rating and $220 price target, ahead of the stock's expected public debut in early April. Mahaney's target price represents \\\"70%+ upside vs. recent private transaction price of $127.50,\\\" he wrote. He likes the large total addressable market for music-streaming services and Spotify's leading position in the market. The Consumer Technology Association believes consumers will spend $6.6 billion on music streaming services in 2018. Spotify has nearly twice as many paid subscribers as Apple Inc.'s Apple Music does. \\\"Very high global aided brand awareness, relatively high customer satisfaction scores, and superior data-driven personalization all combine to help Spotify maintain its leadership position,\\\" Mahaney wrote. As for Spotify's financials, he believes gross margin can expand from 21% in 2017 to upwards of 30% by 2022. He also points to declining churn rates.\", \"Will a robot care for you in your old age? The great potential\\u2014and challenges\\u2014 of artificial intelligence for an aging population Realizing AI\\u2019s possibilities will require businesses to make it less expensive and for health care providers to embrace it.\", \"Nearly a billion smart home devices will ship in 2022, says IDC Market research firm IDC said Thursday that it expected shipments of smart home devices to grow at an 18.5% annual clip over the next five years, ultimately reaching 940 million devices shipped by 2022. Shipments of smart speakers will grow even faster over that period, IDC said, at a 32% annual rate. \\\"While it's still early days for the smart home market - and the wider consumer IoT ecosystem in general - we expect to see considerable growth over the next few years, especially as consumers become more aware of and increasingly interact with smart assistant platforms like Amazon's Alexa and [Alphabet Inc.'s ] Google Assistant,\\\" IDC senior research analyst Adam Wright said in a release. Amazon's Echo family of speakers is thought to be the market leader. Apple Inc. recently came out with its $349 HomePod speaker and will look to capture share of the market. Apple shares are up 18% over the past 12 months, while the Dow Jones Industrial Average has gained 17%.\", \"Apple\\u2019s Cook Has Pointed Ad\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": -0.010335, "explanation": "The actual 21-day forward return for EEM starting 2018-03-30 was -1.03%, which classifies as 'negative'.", "metadata": {"future_return": -0.010335, "horizon_days": 21, "hist_return": -0.00392, "annualized_vol": 0.246352, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20160426_0918", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2016-04-26", "context_summary": "VLUE over past 60 days: cumulative return +8.4%, annualized vol 18.2%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=44.66, end=48.41, cumulative_return=+8.4%, annualized_volatility=18.2%\nMacro context: {'fed_funds_rate': 0.37, 'cpi_yoy': 238.992, 'unemployment': 5.1, 'gdp_growth_qoq': 19062.709, 't10y2y_spread': 1.06, 't10y3m_spread': 1.66, 'breakeven_10y': 1.65, 'hy_oas': 6.32, 'ig_oas': 1.54, 'ted_spread': 0.38, 'mortgage_30y': 3.59, 'vix': 14.079999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-04-25] [\"3 Things Not To Like About Sony Apple (AAPL) camera components supplier Sony Corp. (6758.Japan/SNE) tumbled 6.3% today after the electronics maker said it would postpone its financial forecasts for the current fiscal year while assessing the damage from recent earthquakes that shut down its camera plants.Sony's stock faces 3 near-term headwinds, according to Citi Research's Kota Ezawa.READ MORE.\", \"Three Chip Stocks to be Wary of This Earnings Season Micron Technology has structural issues. Nvidia and Silicon Labs look overvalued on limited earnings upside.\", \"Don\\u2019t have Tidal? Beyonc\\u00e9\\u2019s \\u2018Lemonade\\u2019 coming to Apple\\u2019s iTunes Album headed for wide release after just 24 hours of exclusivity on Tidal Beyonc\\u00e9\\u2019s new album, \\u201cLemonade,\\u201d is expected to be released to the masses Sunday night, just 24 hours after its exclusive debut on the Tidal streaming service.\", \"\\u2018The efficient market is dead today just as sound banking died in 1999\\u2019 Critical intelligence before the U.S. market opens A mere 38% of money managers in Barron\\u2019s latest Big Money poll are bullish about the state of all things market. And this is a group, in general, that tends to put a smile on everything. At least for the clients they\\u2019re perpetually trying to woo.\", \"The market in a minute: Fed's tone, words will matter more than action While we agree that the Fed is unlikely to raise rates this go around, we believe that the risks are in what Chairwoman Yellen says, not what the committee does. So far, Dr. Yellen has been on the Dovish side, a trend that is sure to end at some point.\", \"Snapchat Must Be Reckoned With, Says SunTrust; Use Surpasses Twitter SunTrust Robinson Humphrey\\u2019s Robert Peck, who covers Facebook (FB), Twitter (TWTR) and other Internet stocks, today takes a deep dive into \\u201cThe Rise of Snapchat,\\u201d arguing of the privately held messaging service that \\\"digital media investors must pay attention to it for several reasons.\\\"Those reasons include the fact that it\\u2019s growing fast, it\\u2019s taking users away from other social media, and it\\u2019s also luring away advertisers and software talent.Digital media history is littered with companies that had early leads that eroded as new, innovative companies entered the industry (Friendster, MySpace, Yahoo, Alta Vista, etc). We are not proclaiming that Snapchat will unseat other digital media properties; however, it is paramount that digital media investors and the industry are mindful of Snapchat. This report is the first in a series of Snapchat reports that will aim to help investors understand Snapchat and its potential impact. It is important to understand that there is very limited publicly available information on Snapchat and we look forward to any feedback from the industry and investors, making the topic a living discussion.\", \"Goldman Ups Tesla Target, Potential For \\u2018Disruptive\\u2019 iPhone-Like Upside Goldman Sachs took a closer \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": -0.01031, "explanation": "The actual 21-day forward return for VLUE starting 2016-04-26 was -1.03%, which classifies as 'negative'.", "metadata": {"future_return": -0.01031, "horizon_days": 21, "hist_return": 0.083981, "annualized_vol": 0.181678, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20211027_0920", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2021-10-27", "context_summary": "XLRE over past 60 days: cumulative return +3.7%, annualized vol 13.2%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=39.76, end=41.24, cumulative_return=+3.7%, annualized_volatility=13.2%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.16, 't10y3m_spread': 1.57, 'breakeven_10y': 2.69, 'hy_oas': 3.09, 'ig_oas': 0.89, 'ted_spread': 0.08, 'mortgage_30y': 3.09, 'vix': 15.979999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-26] [\"Notable Tuesday Option Activity: PEP, ADBE, MPC Looking at options trading activity among components of the S&P 500 index, there is noteworthy activity today in PepsiCo Inc (Symbol: PEP), where a total volume of 33,015 contracts has been traded thus far today, a contract volume which is representative of approximately 3.3 million underlying shares (given that every 1 contract represents 100 underlying shares). That number works out to 80% of PEP's average daily trading volume over the past month, of 4.1 million shares. Particularly high volume was seen for the $165 strike call option expiring November 05, 2021, with 23,106 contracts trading so far today, representing approximately 2.3 million underlying shares of PEP. Below is a chart showing PEP's trailing twelve month trading history, with the $165 strike highlighted in orange: Adobe Inc (Symbol: ADBE) options are showing a volume of 18,513 contracts thus far today. That number of contracts represents approximately 1.9 million underlying shares, working out to a sizeable 78.5% of ADBE's average daily trading volume over the past month, of 2.4 million shares. Particularly high volume was seen for the $670 strike call option expiring October 29, 2021, with 2,768 contracts trading so far today, representing approximately 276,800 underlying shares of ADBE. Below is a chart showing ADBE's trailing twelve month trading history, with the $670 strike highlighted in orange: And Marathon Petroleum Corp. (Symbol: MPC) saw options trading volume of 45,113 contracts, representing approximately 4.5 million underlying shares or approximately 74% of MPC's average daily trading volume over the past month, of 6.1 million shares. Particularly high volume was seen for the $72.50 strike call option expiring December 17, 2021, with 25,269 contracts trading so far today, representing approximately 2.5 million underlying shares of MPC. Below is a chart showing MPC's trailing twelve month trading history, with the $72.50 strike highlighted in orange: For the various different available expirations for PEP options, ADBE options, or MPC options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe Is a Free Cash Flow Powerhouse That Will Move Significantly Higher InvestorPlace - Stock Market News, Stock Advice & Trading Tips Adobe (NASDAQ:ADBE) is the type of free cash flow (FCF) powerhouse company that I love to analyze since ADBE stock is likely to move much higher. This is based 0n the company\\u2019s consistently high FCF margins which seem to be sustainable. Moreover, the market is willing to value the stock appropriately based on its huge FCF production. ADBE) logo on wall of corporate building.\\\" width=\\\"300\\\" height=\\\"169\\\"> Source: r.classen / Shutterstock.com As a result, ADBE stock has skyrocketed this year. On Dec. 31, it was tra\n\nPredict whether the return of XLRE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002096, "explanation": "The actual 21-day forward return for XLRE starting 2021-10-27 was +0.21%, which classifies as 'flat'.", "metadata": {"future_return": 0.002096, "horizon_days": 21, "hist_return": 0.037115, "annualized_vol": 0.131988, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20181205_0924", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2018-12-05", "context_summary": "ADA-USD over past 60 days: cumulative return -53.6%, annualized vol 85.1%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.08, end=0.04, cumulative_return=-53.6%, annualized_volatility=85.1%\nMacro context: {'fed_funds_rate': 2.2, 'cpi_yoy': 252.767, 'unemployment': 3.9, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.11, 't10y3m_spread': 0.49, 'breakeven_10y': 1.94, 'hy_oas': 4.29, 'ig_oas': 1.46, 'ted_spread': 0.36, 'mortgage_30y': 4.81, 'vix': 20.739999771118164}\nMarket regime: sideways\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": 0.202826, "explanation": "The actual 21-day forward return for ADA-USD starting 2018-12-05 was +20.28%, which classifies as 'positive'.", "metadata": {"future_return": 0.202826, "horizon_days": 21, "hist_return": -0.536315, "annualized_vol": 0.850704, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160119_0926", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2016-01-19", "context_summary": "VTI over past 60 days: cumulative return -5.0%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=87.18, end=82.84, cumulative_return=-5.0%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 0.36, 'cpi_yoy': 237.652, 'unemployment': 4.8, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.18, 't10y3m_spread': 1.79, 'breakeven_10y': 1.36, 'hy_oas': 7.9, 'ig_oas': 1.89, 'ted_spread': 0.39, 'mortgage_30y': 3.92, 'vix': 27.020000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-15] [\"TSMC: Modesty Is Virtue, Bear Maybank Raises To Hold Analysts have been questioning Apple (AAPL) foundry Taiwan Semiconductor Manufacturing Corp.'s (2330.Taiwan/TSM) ambition lately, saying TSMC is unrealistic with its outlook.TSMC had a long-term goal of 10% annualized growth in revenue and profit. How can it be, when the overall smartphone growth is expected to dip to single-digit this year, they ask.After the market close on Thursday, TSMC reported fourth-quarter earnings per share of 2.81 new Taiwan dollars, above the consensus expectation of NT$2.65.But more importantly, TSMC guided its revenue growth outlook lower, expecting only 5-10% growth.READ MORE.\", \"Apple\\u2019s iPhone slowdown starting to take toll on suppliers Some Asian component makers warn of lower first-half revenues Companies that make parts for Apple Inc. are warning of lower first-half revenue this year, in a sign of slowing sales of the latest iPhones.\", \"Analog Devices Bruised by Apple The supplier is the latest hurt by lower iPhone demand. Consolation: more content in the new Apple Watch and iPhone 7.\", \"All Dow stocks trading premarket are down, led by Intel and Apple shares Bears are getting an early start Friday, as 26 of the 30 stocks in the Dow Jones Industrial Average are trading in the premarket, and they are all down. The biggest loser is Intel Corp.'s stock , which shed 5.9% after reporting disappointing fourth-quarter results late Thursday. The most active is Apple Inc.'s stock , which is down 2% on volume of about 105,000 shares. Among other more-active components, shares of Walt Disney Co. slid 2.7%, of Exxon Mobil Corp. fell 2.7%, of Microsoft Corp. dropped 2.3% and of General Electric Co. gave up 1.6%. Dow futures were last down around 268 points.\", \"This tech company hopes to help Hollywood through biometric analysis Lightwave measured 15 audience fight-or-flight responses in \\u2018The Revenant\\u2019 Biometric tech company Lightwave partnered with 20th Century Fox to track audiences response to \\u201cThe Revenant.\\u201d\", \"Analog Devices Slips Although Street Largely Yawns at the Apple Debacle Shares of chip maker Analog Devices (ADI) are down $1.03, or 2%, at $49.47, after the company yesterday afternoon cut its revenue outlook for its January-ending fiscal Q1, noting weakness in its \\u201cportable\\u201d products division, which most on the Street take as equating to the company\\u2019s sales to smartphones, and especially Apple's (AAPL) iPhone.Although there are price target and estimate cuts at all shops today, the sell side is largely yawning at this development.Although the impact from what appears to be some reduction in orders for parts from ADI by Apple is somewhat greater than many expected; and although the pain may last into next quarter as well, most seem to believe the problem is understood by investors and that it\\u2019s time to move on.The stock has gotten one upgrade today, that I can see, from Nomura\\u2019s Romit Shah, who raised his ratin\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": 0.0, "explanation": "The actual 21-day forward return for VTI starting 2016-01-19 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": -0.049781, "annualized_vol": 0.172214, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210112_0928", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2021-01-12", "context_summary": "XLE over past 60 days: cumulative return +38.0%, annualized vol 39.1%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=12.53, end=17.30, cumulative_return=+38.0%, annualized_volatility=39.1%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 262.687, 'unemployment': 6.4, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.01, 't10y3m_spread': 1.07, 'breakeven_10y': 2.06, 'hy_oas': 3.82, 'ig_oas': 1.01, 'ted_spread': 0.14, 'mortgage_30y': 2.71, 'vix': 24.07999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-01-11] [\"Royal Mail to name Simon Thompson as CEO: report --Royal Mail PLC will name nonexecutive director Simon Thompson as its next chief executive, Sky News reports, citing unnamed sources. --Mr. Thompson has previously worked for companies including Apple Inc., Honda Motor Co., Lastminute.com NV and Wm. Morrison Supermarkets PLC. Full story: https://bit.\", \"Watch for these trends in credit cards this year Expect changes in everything from rewards, cash back and bonuses to payment methods and more.\", \"Barron\\u2019s Daily: Bitcoin Is Tumbling Because Regulators Are Paying Attention Pelosi lays out plan for impeachment of President Trump, Amazon stops hosting social media network Parler, slow vaccine rollout could speed up in coming days, and other news to start your day.\", \"Baidu Is Entering the EV Industry. Tesla Bulls Beware. The Chinese tech giant is working with a Chinese auto maker to build a smart electric vehicle. Investors should expect more partnerships between tech companies and auto makers in the future.\", \"I\\u2019ve pulled out all the stops for Tesla \\u2014 but can\\u2019t find the upside on the stock This fund manager can't get to a stock price beyond $300, even with the best possible case of $1.2 trillion of sales in 2035.\", \"Dow drops 182 points on losses for Boeing, Apple Inc. stocks\", \"This fund manager says Amazon and other large-cap tech companies will make lots of money for investors for years to come Scott Berg of T. Rowe Price has been successful following a 'durable quality growth' strategy.\", \"The antitrust case against Facebook is bad economic policy The lawsuits against Facebook are without merit and are bad economic policy, writes Peter Morici.\", \"Amazon Stops Hosting Social-Media Site Parler The move came after both Google and Apple removed Parler\\u2019s app from their respective app stores earlier in the weekend.\", \"Dow down 100 points on losses in American Express, Apple Inc. stocks\", \"Twitter\\u2019s Trump ban could hurt user engagement but appeal to advertisers, analysts say Twitter Inc. is leading social-media stocks lower Monday as investors digest a new reality for the services after Twitter permanently banned President Donald Trump from its platform and Facebook Inc. said it would restrict him at least until the end of his term.\", \"Dow flat in spite of losses for shares of Boeing, Coca-Cola\", \"Robotaxis and Self-Driving Cars Are Coming. This Company Will Be the Brains Behind Them. Aptiv unveiled new technology that makes robotaxis and consumer autonomous-car models feasible. It supplies Tesla and other auto makers.\", \"Coca-Cola, Apple Inc. share losses lead Dow's 110-point drop\", \"Dow flat in spite of losses in shares of Apple Inc., Coca-Cola\", \"Report: FBI Warns of Armed Protests Ahead of Inauguration Day Democrats say they have a majority to impeach the president but plan to first bring a resolution calling on the vice president and cabinet members to remove Trump using the 25th Amendment for a full vote.\", \"The Dow\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": 0.011024, "explanation": "The actual 21-day forward return for XLE starting 2021-01-12 was +1.10%, which classifies as 'positive'.", "metadata": {"future_return": 0.011024, "horizon_days": 21, "hist_return": 0.380144, "annualized_vol": 0.391338, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190705_0930", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-07-05", "context_summary": "BTC-USD over past 60 days: cumulative return +95.2%, annualized vol 81.2%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=5746.81, end=11215.44, cumulative_return=+95.2%, annualized_volatility=81.2%\nMacro context: {'fed_funds_rate': 2.41, 'cpi_yoy': 255.802, 'unemployment': 3.7, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.19, 't10y3m_spread': -0.25, 'breakeven_10y': 1.65, 'hy_oas': 4.02, 'ig_oas': 1.2, 'ted_spread': 0.13, 'mortgage_30y': 3.75, 'vix': 12.56999969482422}\nMarket regime: sideways\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": -0.100939, "explanation": "The actual 21-day forward return for BTC-USD starting 2019-07-05 was -10.09%, which classifies as 'negative'.", "metadata": {"future_return": -0.100939, "horizon_days": 21, "hist_return": 0.951595, "annualized_vol": 0.811978, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20150507_0932", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2015-05-07", "context_summary": "IVV over past 60 days: cumulative return +1.0%, annualized vol 11.0%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=171.93, end=173.73, cumulative_return=+1.0%, annualized_volatility=11.0%\nMacro context: {'fed_funds_rate': 0.13, 'cpi_yoy': 237.001, 'unemployment': 5.6, 'gdp_growth_qoq': 18782.243, 't10y2y_spread': 1.6, 't10y3m_spread': 2.23, 'breakeven_10y': 1.91, 'hy_oas': 4.5, 'ig_oas': 1.33, 'ted_spread': 0.26, 'mortgage_30y': 3.68, 'vix': 15.149999618530272}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-05-06] [\"Itron (ITRI) Q1 Earnings Trail on Adverse Forex Impact - Analyst Blog\", \"Itron (ITRI) Q1 Earnings Trail on Adverse Forex Impact - Analyst Blog\", \"Itron (ITRI) Q1 Earnings Trail on Adverse Forex Impact - Analyst Blog Shares of Itron, Inc.ITRI lost around 1.2% and closed at $35.27, a day after the company reported disappointing first-quarter 2015 results on May 4. Adjusted earnings per share slumped 35.5% to 20 cents in the quarter from 31 cents in the prior-year quarter, mainly due to unfavorable impact of foreign currency exchange rates. Earnings also trailed the Zacks Consensus Estimate of 30 cents. Including one-time items, such as amortization, restructuring and acquisition-related expenses, the company reported earnings of 13 cents per share, contrary to a loss of 1 cent in the year-ago quarter. Itron Inc. - Earnings Surprise | FindTheCompany Operational Update Total revenue declined 5.6% to $448 million from $474.8 million in the year-ago quarter. Revenues, however, beat the Zacks Consensus Estimate of $429 million. Changes in foreign currency exchange rates unfavorably impacted revenues for the quarter. Excluding the impact of foreign currency, revenues increased 4% year over year. Improvement was driven by growth in the Electricity segment, which offset a decrease in the Gas segment. The Water segment was consistent with the prior-year period. Cost of goods sold went down to $310 million from $320 million in the prior-year quarter. Gross profit also decreased 10.6% year over year to $138 million. Gross margin decreased 170 basis points (bps) to 30.8%, primarily due to unfavorable product mix and increased warranty expense in the Gas and Water segments, partially offset by improved performance in Electricity. Adjusted operating expenses declined to $119.8 million from $131.9 million in the year-ago quarter. Adjusted operating profit decreased 21.7% year over year to $18 million. Including one-time items, Itron's operating income increased to $13.5 million in the quarter from $4.5 million in the year-ago quarter. Segment Performance Electricity Segment: Net sales at the Electricity Segment increased 7.6% year over year to $193.8 million. The segment reported adjusted operating income of $6 million unlike an operating loss of $15.9 million in the year-ago quarter. Gas Segment: The segment's sales went down 14.4% year over year to $125 million. Adjusted operating income for the quarter was $16 million, down 42.8% from $28 million in the year-ago quarter. Water Segment: The Water Segment reported sales of $129 million in the quarter, down 13% from $148.5 million in the prior-year quarter. Adjusted operating income for the quarter was $9.8 million, which plunged 58% from $23 million in the year-ago quarter. Financial Position Itron ended the quarter with cash and cash equivalents of $118 million versus $112.4 million as of 2014-end. The company reported cash used in operating activities of $3.9 million during first-quarter 2015 compared to cas\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": 0.00428, "explanation": "The actual 21-day forward return for IVV starting 2015-05-07 was +0.43%, which classifies as 'flat'.", "metadata": {"future_return": 0.00428, "horizon_days": 21, "hist_return": 0.010459, "annualized_vol": 0.10957, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180214_0934", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2018-02-14", "context_summary": "EMB over past 60 days: cumulative return -2.3%, annualized vol 4.4%. Market regime: sideways.", "question": "Asset: EMB\nHistorical prices (past 60 trading days): start=77.03, end=75.27, cumulative_return=-2.3%, annualized_volatility=4.4%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 249.529, 'unemployment': 4.1, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.73, 't10y3m_spread': 1.24, 'breakeven_10y': 2.05, 'hy_oas': 3.78, 'ig_oas': 1.0, 'ted_spread': 0.27, 'mortgage_30y': 4.32, 'vix': 24.96999931335449}\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": 0.010775, "explanation": "The actual 21-day forward return for EMB starting 2018-02-14 was +1.08%, which classifies as 'positive'.", "metadata": {"future_return": 0.010775, "horizon_days": 21, "hist_return": -0.022891, "annualized_vol": 0.04408, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191028_0936", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2019-10-28", "context_summary": "VLUE over past 60 days: cumulative return +5.4%, annualized vol 19.5%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=67.19, end=70.81, cumulative_return=+5.4%, annualized_volatility=19.5%\nMacro context: {'fed_funds_rate': 1.83, 'cpi_yoy': 257.155, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.17, 't10y3m_spread': 0.14, 'breakeven_10y': 1.65, 'hy_oas': 3.89, 'ig_oas': 1.14, 'ted_spread': 0.3, 'mortgage_30y': 3.75, 'vix': 12.649999618530272}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-10-25] [\"'Fast Money Halftime Report' Give Their View On Bristol-Myers, Adobe And More\", \"'Fast Money Halftime Report' Give Their View On Bristol-Myers, Adobe And More\", \"3 Stocks to Build Your Portfolio Around Revered investor Peter Lynch wrote in One Up On Wall Street that \\\"To come out ahead, you don't have to be right all the time, or even a majority of the time.\\\" He famously stated that an investor really only has to be right 60% of the time to beat the market in the long run. Since all investors will have losers in their portfolio, what matters more than anything is centering your portfolio around solid core holdings in a variety of different sectors. Adobe (NASDAQ: ADBE), Disney (NYSE: DIS), and McDonald's (NYSE: MCD) are three completely different companies that together offer the building blocks for growth and value. Source: Getty Images. Adobe One of the first tips you'll hear in investing is to find a company whose operations are resilient, if not impenetrable, to the competition. Look no further than Adobe. Seven years ago, CEO Shantanu Narayen repackaged Adobe's products into an all-encompassing suite called Adobe Creative Cloud. For $80 a month or $360 per year, Creative Cloud is the industry standard for graphic design. Adobe's subscription model is used by over 12 million paying subscribers. The stock recently blasted through an all-time high of $310 per share before falling to around $270, where is trades today. In the company's recent third quarter 2019, it reported record revenue of $2.83 billion, for 24% year-over-year growth. That 24% figure for a $130 billion (by market cap) tech titan isn't bad, especially when that company has a 2020 forward P/E of 28.50. Adobe benefits from many of the tailwinds driving the economy. The rise of software as a service, the gig economy, and increased use of digital design, digital media, and digital marketing are all reasons its total addressable market is essentially unlimited. The company caters to the largest corporations, creative college students, and everyone in between. It's incredibly efficient as well, with operating margins at 28% and minimal debt of $4.1 billion almost entirely offset by $3.6 billion in cash. Disney Lately, everyone's been talking about Disney+, the company's streaming service that's being launched Nov. 12 starting at $6.99 a month. But what about Disney's films? It is dominant at the box office. Disney's Avengers: Endgame, the live-action Lion King, Toy Story 4, and Captain Marvel, in that order, are the four top-grossing movies year-to-date in 2019. Its Aladdin ranks sixth. Together, the five movies have raked in over $2.6 billion in sales. Disney has built what is quite possibly the most dominant and influential entertainment powerhouse of the 21st century. It owns ABC, Marvel, Lucasfilm, Twenty-First Century Fox, Touchstone Pictures, an 80% stake in ESPN, and more. Between entertainment and its famous theme parks across the globe, the company makes so much profit th\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": 0.028997, "explanation": "The actual 21-day forward return for VLUE starting 2019-10-28 was +2.90%, which classifies as 'positive'.", "metadata": {"future_return": 0.028997, "horizon_days": 21, "hist_return": 0.053854, "annualized_vol": 0.19488, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190204_0938", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2019-02-04", "context_summary": "XRP-USD over past 60 days: cumulative return -2.8%, annualized vol 71.5%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.31, end=0.30, cumulative_return=-2.8%, annualized_volatility=71.5%\nMacro context: {'fed_funds_rate': 2.4, 'cpi_yoy': 253.319, 'unemployment': 3.8, 'gdp_growth_qoq': 20431.641, 't10y2y_spread': 0.18, 't10y3m_spread': 0.3, 'breakeven_10y': 1.88, 'hy_oas': 4.29, 'ig_oas': 1.36, 'ted_spread': 0.38, 'mortgage_30y': 4.46, 'vix': 16.139999389648438}\nMarket regime: sideways\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": 0.094311, "explanation": "The actual 21-day forward return for XRP-USD starting 2019-02-04 was +9.43%, which classifies as 'positive'.", "metadata": {"future_return": 0.094311, "horizon_days": 21, "hist_return": -0.027607, "annualized_vol": 0.714644, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20170913_0940", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2017-09-13", "context_summary": "EEM over past 60 days: cumulative return +9.7%, annualized vol 12.5%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=33.99, end=37.28, cumulative_return=+9.7%, annualized_volatility=12.5%\nMacro context: {'fed_funds_rate': 1.16, 'cpi_yoy': 246.435, 'unemployment': 4.3, 'gdp_growth_qoq': 19660.766, 't10y2y_spread': 0.84, 't10y3m_spread': 1.14, 'breakeven_10y': 1.84, 'hy_oas': 3.81, 'ig_oas': 1.16, 'ted_spread': 0.3, 'mortgage_30y': 3.78, 'vix': 10.579999923706056}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-09-12] [\"3 Must Read Stories: UN North Korea Sanctions, Why China\\u2019s Party Congress Matters, Xiaomi vs Apple\", \"Thinking of Buying Nike Shares? Just Don\\u2019t As Adidas picks up the pace, Nike is losing ground in the sneaker race. Its stumbling stock could fall another 10%.\", \"Nikkei scores one-month closing high, but global rally slows in Asia Japanese stocks boosted by falling yen Investors continued to buy risk assets and sell havens Tuesday, as Asian stocks extended gains while the yen and gold fell further.\", \"Should you buy Apple stock ahead of the iPhone 8 launch? Jeff Reeves considers 5 reasons to buy \\u2014 and five reasons to sell Jeff Reeves considers 5 reasons to buy \\u2014 and five reasons to sell.\", \"Tired of the FANG gang? These 2 tech stocks look like they\\u2019re in the same class ASML Holding and SAP are leaders with room to run, says fund manager who also advises avoiding Nokia and Ericsson ASML Holding and SAP are pacesetters with room to run, according to Benjamin Segal, portfolio manager for the Neuberger Berman International Equity fund.\", \"New Apple iPhone\\u2019s key feature is its price tag Apple is expected to debut 10th-anniversary iPhone lineup Tuesday, including model reportedly being priced at $1,000 At Apple Inc.\\u2019s event Tuesday, executives will boast about new iPhone wizardry to much applause, but the most important feature will likely be tucked in at the end and met with little audience response: The price.\", \"Apple shares climb premarket ahead of iPhone 8 launch Stock faces short-term risks, but is still a buy: UBS Apple shares are cautiously moving higher before Tuesday\\u2019s opening bell, ahead of the highly anticipated iPhone 8 launch that could put the tech giant closer to becoming a $1 trillion company.\", \"Single iPhone users don\\u2019t want to date someone with an Android Online daters judge each other by the kind of smartphone they own Online daters judge each other by the kind of smartphone they own.\", \"It\\u2019s nutty that Apple is rallying into its super-hyped iPhone launch, strategist says Critical information for the U.S. trading day It\\u2019s time for the umpteenth iPhone, and plenty of fans are shouting, \\u201cShut up and take my money!\\u201d But our call of the day says the stock market is acting a bit how it did before 2000\\u2019s dot-com bust, and that should worry investors.\", \"What time is the iPhone launch event? Apple will host event for the first time at its Steve Jobs Theater The tech giant confirmed a Sept. 12 date for an event expected to include the launch of a new iPhone.\", \"Apple's stock up 0.4% in morning trade,\", \"Apple\\u2019s Next: It\\u2019s All Priced into Component Makers, Says Summit Redstone Chip content in the various new models of iPhone will be good for suppliers such as Broadcom and Qorvo, although it is mostly priced into their stocks, says Summit Redstone chip analyst Jagadish Iyer. He likes memory-chip makers Micron and Western Digital, given the rising memory content\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": 0.023009, "explanation": "The actual 21-day forward return for EEM starting 2017-09-13 was +2.30%, which classifies as 'positive'.", "metadata": {"future_return": 0.023009, "horizon_days": 21, "hist_return": 0.096578, "annualized_vol": 0.124925, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210416_0942", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2021-04-16", "context_summary": "ADA-USD over past 60 days: cumulative return +72.1%, annualized vol 100.2%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.86, end=1.48, cumulative_return=+72.1%, annualized_volatility=100.2%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 266.614, 'unemployment': 6.1, 'gdp_growth_qoq': 21440.929, 't10y2y_spread': 1.4, 't10y3m_spread': 1.54, 'breakeven_10y': 2.33, 'hy_oas': 3.25, 'ig_oas': 0.94, 'ted_spread': 0.17, 'mortgage_30y': 3.04, 'vix': 16.56999969482422}\nMarket regime: sideways\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": 0.166911, "explanation": "The actual 21-day forward return for ADA-USD starting 2021-04-16 was +16.69%, which classifies as 'positive'.", "metadata": {"future_return": 0.166911, "horizon_days": 21, "hist_return": 0.720752, "annualized_vol": 1.001765, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20191216_0944", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2019-12-16", "context_summary": "XLE over past 60 days: cumulative return -1.6%, annualized vol 19.0%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=22.72, end=22.36, cumulative_return=-1.6%, annualized_volatility=19.0%\nMacro context: {'fed_funds_rate': 1.55, 'cpi_yoy': 258.63, 'unemployment': 3.6, 'gdp_growth_qoq': 20985.448, 't10y2y_spread': 0.21, 't10y3m_spread': 0.25, 'breakeven_10y': 1.7, 'hy_oas': 3.71, 'ig_oas': 1.05, 'ted_spread': 0.36, 'mortgage_30y': 3.73, 'vix': 12.630000114440918}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-13] [\"5 Stocks To Watch For December 13, 2019\", \"A Peek Into The Markets: US Stock Futures Climb Ahead Of Economic Reports\", \"20 Stocks Moving in Friday's Pre-Market Session\", \"Credit Suisse Reiterates Outperform on Adobe, Raises Price Target to $350\", \"Wells Fargo Reiterates Equal-Weight on Adobe, Raises Price Target to $315\", \"Barclays Maintains Overweight on Adobe, Raises Price Target to $350\", \"Adobe shares are trading higher after the company reported better-than-expected Q4 EPS and sales results.\", \"PiperJaffray Maintains Overweight on Adobe, Raises Price Target to $360\", \"Wedbush Maintains Neutral on Adobe, Raises Price Target to $315\", \"Stifel Maintains Buy on Adobe, Raises Price Target to $350\", \"10 Biggest Price Target Changes For Friday\", \"Adobe Did Good \\u2013 And Stock Is Headed To A Record High\", \"Nomura Maintains Buy on Adobe, Raises Price Target to $318\", \"Stifel Nicolaus Maintains Buy on Adobe, Raises Price Target to $350\", \"Canaccord Genuity Maintains Buy on Adobe, Raises Price Target to $350\", \"UPDATE: Credit Suisse Maintains Outperform On Adobe, Raises Target To $350 Notes 'While some may harp on the F1Q20 guide, we believe the outperformance in F4Q19 and reiteration of FY20 net new ARR likely signals upside to Digital Media'\", \"Mid-Morning Market Update: Markets Mixed; Adobe Earnings Beat Estimates\", \"Stocks That Hit 52-Week Highs On Friday\", \"UPDATE: Wells Fargo Maintains Outperform On Adobe, Raises Target To $315 As Firm Believes Believes The Stock's Current Valuation Reflects Co's 'successful transition to subscription and ability to increase its total addressable market'\", \"UPDATE: Nomura Maintains Buy On Adobe, Raises Target To $318 Notes 'After underwhelming bookings momentum around both Marketo (mid-market) and Analytics Cloud subscriptions in 3Q, things seem to have gained some positive traction in the quarter'\", \"36 Stocks Moving In Friday's Mid-Day Session\", \"Mid-Day Market Update: Crude Oil Rises Over 1%; Sarepta Therapeutics Shares Spike Higher\", \"The Street Reviews Adobe's 2019: 'Record Year'\", \"The Street Reviews Adobe's 2019: 'Record Year'\", \"Mid-Day Market Update: Crude Oil Rises Over 1%; Sarepta Therapeutics Shares Spike Higher\", \"36 Stocks Moving In Friday's Mid-Day Session\", \"UPDATE: Nomura Maintains Buy On Adobe, Raises Target To $318 Notes 'After underwhelming bookings momentum around both Marketo (mid-market) and Analytics Cloud subscriptions in 3Q, things seem to have gained some positive traction in the quarter'\", \"UPDATE: Wells Fargo Maintains Outperform On Adobe, Raises Target To $315 As Firm Believes Believes The Stock's Current Valuation Reflects Co's 'successful transition to subscription and ability to increase its total addressable market'\", \"Stocks That Hit 52-Week Highs On Friday\", \"Mid-Morning Market Update: Markets Mixed; Adobe Earnings Beat Estimates\", \"UPDATE: Credit Suisse Maintains Outperform On Adobe, Raises Target To $350 Notes 'While some may harp on the F1Q20 guide, we believe the outper\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": 0.01239, "explanation": "The actual 21-day forward return for XLE starting 2019-12-16 was +1.24%, which classifies as 'positive'.", "metadata": {"future_return": 0.01239, "horizon_days": 21, "hist_return": -0.015829, "annualized_vol": 0.190265, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210726_0946", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2021-07-26", "context_summary": "XLY over past 60 days: cumulative return +3.0%, annualized vol 14.1%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=85.56, end=88.11, cumulative_return=+3.0%, annualized_volatility=14.1%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 271.903, 'unemployment': 5.4, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.08, 't10y3m_spread': 1.25, 'breakeven_10y': 2.35, 'hy_oas': 3.22, 'ig_oas': 0.92, 'ted_spread': 0.08, 'mortgage_30y': 2.78, 'vix': 17.200000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-07-23] [\"This Is My #1 Secret to Scoring 10X Returns in the Stock Market InvestorPlace - Stock Market News, Stock Advice & Trading Tips Hey, Luke Lango here. Source: Freedom365day / Shutterstock.com I know, I\\u2019m a new face and name to some of you folks. So, in order to get to know each other better, I figured a great place to start our journey in MoneyWire is for me to tell you about my investment philosophy and how we will build on what you are accustomed to. Fortunately, it\\u2019s very simple \\u2014 and very profitable. And if you follow just one big secret, I\\u2019m positive you\\u2019ll be able to score 10X returns in the stock market \\u2014 not just once, but time and time again. But\\u2026 before I get to sharing that big secret with you\\u2026 let me tell you a story so we can get better acquainted\\u2026 Three months ago, shares of space tourism pioneer Virgin Galactic (NYSE:SPCE) were reeling. 7 Value Stocks to Buy Ahead of Possible Interest Rate Hikes Insiders were selling the stock in droves \\u2014 the company\\u2019s founder (Richard Branson), the venture capital investor who took the company public (Chamath Palihapitiya), and the fund manager who focuses on growth stocks like Virgin Galactic (Cathie Wood \\u2014 many of you may recognize her as the CEO of ARK Invest) collectively sold about $400 million worth of stock over the course of a month \\u2014 and competitor Blue Origin had just announced it was going to start selling tickets for rides on its own space tourism rocket. Virgin Galactic stock collapsed from over $60 in February, to a low of $14 in mid-May. Everyone was bearish on the stock\\u2026 well, everyone except me. I wrote around that time that Wall Street was being unnecessarily short-sighted, and that insider sales and increased competition in an early-stage company on the cusp of doing something no one has ever done before \\u2014 commercially flying people into space \\u2014 were non-news. I told investors to take a step back, look at things from the 400-foot-view, and understand that over the next decade, Virgin Galactic is going to create a huge, one-of-a-kind, never-seen-before space tourism business that will generate billions of dollars in annual revenue and hundreds of millions of dollars in net profits. And so, I told folks to buy the dip. A few weeks later, Virgin Galactic successfully completed a flawless test flight into space. Days after that, Virgin won FAA approval to commercially fly paying customers into space. A month after, the company flew Richard Branson into space in a flight that has been 15 years delayed. And, amid all those developments, Virgin Galactic stock soared from $15 to over $50, more than tripling the money of investors who listened to me and bought the dip in May. OK\\u2026 but why am I telling you all of this? Because the secret to scoring 10X returns and unlocking generational wealth in the stock market lies in the lesson of the Virgin Galactic story. You have to understand: This is not an isolat\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": -0.018686, "explanation": "The actual 21-day forward return for XLY starting 2021-07-26 was -1.87%, which classifies as 'negative'.", "metadata": {"future_return": -0.018686, "horizon_days": 21, "hist_return": 0.029803, "annualized_vol": 0.140695, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220524_0948", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2022-05-24", "context_summary": "ADA-USD over past 60 days: cumulative return -53.3%, annualized vol 96.4%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=1.10, end=0.51, cumulative_return=-53.3%, annualized_volatility=96.4%\nMacro context: {'fed_funds_rate': 0.83, 'cpi_yoy': 291.298, 'unemployment': 3.6, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.21, 't10y3m_spread': 1.79, 'breakeven_10y': 2.6, 'hy_oas': 4.82, 'ig_oas': 1.53, 'ted_spread': 0.09, 'mortgage_30y': 5.25, 'vix': 28.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-05-23] \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": -0.070676, "explanation": "The actual 21-day forward return for ADA-USD starting 2022-05-24 was -7.07%, which classifies as 'negative'.", "metadata": {"future_return": -0.070676, "horizon_days": 21, "hist_return": -0.533099, "annualized_vol": 0.96368, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20180202_0950", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2018-02-02", "context_summary": "JNK over past 60 days: cumulative return +1.2%, annualized vol 3.7%. Market regime: sideways.", "question": "Asset: JNK\nHistorical prices (past 60 trading days): start=67.19, end=67.98, cumulative_return=+1.2%, annualized_volatility=3.7%\nMacro context: {'fed_funds_rate': 1.42, 'cpi_yoy': 249.529, 'unemployment': 4.1, 'gdp_growth_qoq': 20044.077, 't10y2y_spread': 0.62, 't10y3m_spread': 1.3, 'breakeven_10y': 2.11, 'hy_oas': 3.29, 'ig_oas': 0.9, 'ted_spread': 0.33, 'mortgage_30y': 4.22, 'vix': 13.470000267028809}\nMarket regime: sideways\n\nPredict whether the return of JNK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.00351, "explanation": "The actual 21-day forward return for JNK starting 2018-02-02 was -0.35%, which classifies as 'flat'.", "metadata": {"future_return": -0.00351, "horizon_days": 21, "hist_return": 0.011743, "annualized_vol": 0.037264, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20180706_0953", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2018-07-06", "context_summary": "XLE over past 60 days: cumulative return +7.2%, annualized vol 17.4%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=24.94, end=26.73, cumulative_return=+7.2%, annualized_volatility=17.4%\nMacro context: {'fed_funds_rate': 1.91, 'cpi_yoy': 251.214, 'unemployment': 3.8, 'gdp_growth_qoq': 20276.154, 't10y2y_spread': 0.29, 't10y3m_spread': 0.88, 'breakeven_10y': 2.13, 'hy_oas': 3.74, 'ig_oas': 1.29, 'ted_spread': 0.42, 'mortgage_30y': 4.52, 'vix': 14.970000267028809}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-05] [\"PreMarket Prep Recap For July 5: Trading The Range In The S&P 500; Sean Udall Joins The Show\", \"PreMarket Prep Recap For July 5: Trading The Range In The S&P 500; Sean Udall Joins The Show\", \"Synopsys, Siemens Join Forces on EDA Interoperability Effort SynopsysSNPS is collaborating with Siemens PLM Software to jointly develop a wide range of electronic design automation (EDA) product interoperability projects. EDA is a category of tools used to analyze semiconductor devices. Many chip designers and manufacturers are opting for EDA, attracted by the reduced cost, errors and design time associated with its adoption. The increasing demand for EDA solutions are driven by growth in fast growing fields of cloud computing, Artificial Intelligence (AI), Internet of Things (IoT) and smart wearable devices. Collaboration to Boost Customer Base The synergistic collaboration between Synopsys and Siemens encompasses EDA domains from design to verification. The latest collaboration will help Synopsys address the needs of semiconductor and system-on-chip (SoC) manufacturing firms, which comprises the majority of its clientele. Moreover, the joint solution will enhance customers' digitization efforts. Further, the collaboration will ensure more effective EDA solutions for mutual customers. Notably, one major competitor of Synopsys was Mentor Graphics, which was recently acquired by Siemens. The companies have also settled all outstanding patent litigations Hence, we believe the collaboration with Siemens on EDA product interoperability solutions bodes well for Synopsys, as it will expand its penetration in the market. Synopsys, Inc. Revenue (TTM) Synopsys, Inc. Revenue (TTM) | Synopsys, Inc. Quote Extended Partner Base, New Solutions to Drive Growth We believe Synopsys will benefit from its expanding partner base. The company's extended relationships with the likes of AMD, Juniper, Realtek, Teradici, NetLogic Microsystems, Toshiba and Wolfson will continue to boost its top-line growth. Synopsys also collaborated with ARM Holdings plc which is expected to optimize the performance of its processors. The company is positive about its EDA design solutions which are helping in designing of new AI engines. The newly launched Fusion Technology has gained accolades from the Samsung, STMicroelectronics, Toshiba, and ANSYS. Further, strategic acquisitions have expanded the company's presence in the intensely competitive EDA market. Zacks Rank and Stocks to Consider Synopsys currently carries a Zacks Rank #3 (Hold). Some stocks worth considering in the broader Computer and Technology sector are Adobe ADBE , YY YY , and Verint VRNT . All three stocks sport a Zacks Rank #1 (Strong Buy). You can see the complete list of today's Zacks #1 Rank stocks here . Long-term earnings growth for Adobe, YY and Verint is projected to be 16.20%, 26.43% and 10%, respectively. Today's Stocks from Zacks' Hottest Strategies It's hard to believe, even for us at Zacks. But while the market gai\n\nPredict whether the return of XLE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.001982, "explanation": "The actual 21-day forward return for XLE starting 2018-07-06 was -0.20%, which classifies as 'flat'.", "metadata": {"future_return": -0.001982, "horizon_days": 21, "hist_return": 0.071886, "annualized_vol": 0.173541, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20221209_0955", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2022-12-09", "context_summary": "XLU over past 60 days: cumulative return -4.1%, annualized vol 26.2%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=33.34, end=31.98, cumulative_return=-4.1%, annualized_volatility=26.2%\nMacro context: {'fed_funds_rate': 3.83, 'cpi_yoy': 298.832, 'unemployment': 3.5, 'gdp_growth_qoq': 22278.345, 't10y2y_spread': -0.83, 't10y3m_spread': -0.8, 'breakeven_10y': 2.28, 'hy_oas': 4.55, 'ig_oas': 1.38, 'ted_spread': 0.09, 'mortgage_30y': 6.33, 'vix': 22.290000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-08] [\"US STOCKS-S&P 500, Nasdaq snap losing streaks after jobless claims rise By David French Dec 8 (Reuters) - The S&P 500 .SPXended higher on Thursday, snapping a five-session losing streak, as investors interpreted data showing a rise in weekly jobless claims as a sign the pace of interest rate hikes could soon slow. Wall Street's main indexes had come under pressure in recent days, with the S&P 500 shedding 3.6% since the beginning of December on expectations of a longer rate-hike cycle and downbeat economic views from some top company executives. Such thinking had also weighed on the Nasdaq Composite .IXIC, which had posted four straight losing sessions prior to Thursday's advance on the tech-heavy index. Stocks rose as investors cheered data showing the number of Americans filing claims for jobless benefits increased moderately last week, while unemployment rolls hit a 10-month high toward the end of November. The report follows data last Friday that showed U.S. employers hired more workers than expected in November and increased wages, spurring fears that the Fed might stick to its aggressive stance to tame decades-high inflation. Markets have been swayed by data releases in recent days, with investors lacking certainty ahead of Federal Reserve guidance next week on interest rates. Such behavior means Friday's producer price index and the University of Michigan's consumer sentiment survey will likely dictate whether Wall Street can build on Thursday's rally. \\\"The market has to adjust to the fact that we're moving from a stimulus-based economy - both fiscal and monetary - into a fundamentals-based economy, and that's what we're grappling with right now,\\\" said Wiley Angell, chief market strategist at Ziegler Capital Management. The Dow Jones Industrial Average .DJI rose 183.56 points, or 0.55%, to close at 33,781.48; the S&P 500 .SPX gained 29.59 points, or 0.75%, to finish at 3,963.51; and the Nasdaq Composite .IXIC added 123.45 points, or 1.13%, at 11,082.00. Nine of the 11 major S&P 500 sectors rose, led by a 1.6% gain in technology stocks .SPLRCT. Most mega-cap technology and growth stocks gained. Apple Inc AAPL.O, Nvidia Corp NVDA.O and Amazon.com Inc AMZN.O rose between 1.2% and 6.5%. Microsoft Corp MSFT.O ended 1.2% higher, despite giving up some intraday gains after the Federal Trade Commission filed a complaint aimed at blocking the tech giant's $69 billion bid to buy Activision Blizzard Inc ATVI.O. The \\\"Call of Duty\\\" games maker closed 1.5% lower. The energy index .SPNY was an exception, slipping 0.5%, despite Exxon Mobil Corp XOM.N gaining 0.7% after announcing it would expand its $30-billion share repurchase program. The sector had been under pressure in recent sessions as commodity prices slipped: U.S. crude CLc1 is now hovering near its level at the start of 2022. Meanwhile, Moderna Inc MRNA.O advanced 3.2% after the U.S. Food and Drug Administration authorized COVID-19 shots from the vaccine maker that target both the original\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": 0.017434, "explanation": "The actual 21-day forward return for XLU starting 2022-12-09 was +1.74%, which classifies as 'positive'.", "metadata": {"future_return": 0.017434, "horizon_days": 21, "hist_return": -0.04104, "annualized_vol": 0.26199, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210128_0957", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2021-01-28", "context_summary": "ACWI over past 60 days: cumulative return +18.0%, annualized vol 13.7%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=71.03, end=83.80, cumulative_return=+18.0%, annualized_volatility=13.7%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 262.687, 'unemployment': 6.4, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 0.92, 't10y3m_spread': 0.96, 'breakeven_10y': 2.08, 'hy_oas': 3.85, 'ig_oas': 1.03, 'ted_spread': 0.13, 'mortgage_30y': 2.77, 'vix': 37.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-01-27] [\"AT&T Reports Earnings Wednesday. Here\\u2019s What to Expect. Dividend plans, 5G and HBO Max updates, and 2021 guidance will be the highlights of AT&T\\u2019s fourth-quarter earnings report Wednesday.\", \"European stocks track Wall Street lower with investors focused on Fed and big tech earnings European stocks struggled on Wednesday, as investors look to the Federal Reserve meeting later, coronavirus updates and a batch of big U.S. earnings.\", \"London stocks under pressure led by miners amid grim COVID-19 headlines Investors were steeped in gloom for Wednesday as the U.K. faces the worst death toll in Europe and potentially more restrictions.\", \"AT&T Just Reported Earnings. Here Are the Numbers You Need to Know. AT&T saw a huge net gain in wireless subscribers, but it also offered guidance that was likely much softer than investors had expected.\", \"Accelerating Growth for Microsoft Azure Bodes Well for Cloud Software Sector Even as the S&P 500 sells off this morning, down about 1.8%, Microsoft shares have rallied 1.5%, to $235.81. The stock is on track for another record close.\", \"GameStop\\u2019s surge is making it one of the most traded stocks in the U.S. The parabolic ride higher for GameStop, driven by a klatch of investors congregating on sites like Reddit's WallStreetBest forum, has made the company the most traded stock in the U.S., according to Deutsche Bank data.\", \"Even Reddit is beginning to discuss the endgame for the wild GameStop ride When are the meteoric gains for videogames retailer GameStop going to stop? Perhaps one sign is that there is a discussion of the subject on the Reddit message board that fueled the run.\", \"Apple overtakes Amazon to become world\\u2019s most valuable brand, while Tesla is the fastest-growing Apple has overtaken Amazon to become the world\\u2019s most valuable brand for the first time in five years, according to a global report.\", \"Stocks Close Down Sharply on Fed News, Disappointing Earnings Investors reacted to the central bank\\u2019s comments on slowing recovery plus big losses from Boeing and AT&T.\", \"Apple posts record revenue of $111.4 billion, up 21%\", \"U.S. stocks book worst daily losses since October as Powell stresses long road to recovery and short squeeze drama plays out Dow, S&P 500 both flipped negative for the year Wednesday, as stocks tumbled and Federal Reserve Chair Jerome Powell underscored how far the economy is from a full recovery.\", \"Facebook beats expectations but warns of \\u2018cross currents\\u2019 in 2021 Facebook Inc. shares initially tumbled 5% in extended trading, then quickly rallied, Wednesday after it announced better-than-expected fourth-quarter results, but warned of \\\"significant uncertainty as we manage through a number of cross currents in 2021.\\\"\", \"Apple Earnings Crush Estimates as iPhone Scores Again Wall Street had been looking for a potentially spectacular quarter for iPhone sales following the recent launch of Apple's first 5G phones. The company delivered.\", \"Gam\n\nPredict whether the return of ACWI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002818, "explanation": "The actual 21-day forward return for ACWI starting 2021-01-28 was +0.28%, which classifies as 'flat'.", "metadata": {"future_return": 0.002818, "horizon_days": 21, "hist_return": 0.179796, "annualized_vol": 0.13728, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210813_0959", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2021-08-13", "context_summary": "XLP over past 60 days: cumulative return +2.9%, annualized vol 9.2%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=61.68, end=63.45, cumulative_return=+2.9%, annualized_volatility=9.2%\nMacro context: {'fed_funds_rate': 0.1, 'cpi_yoy': 272.676, 'unemployment': 5.1, 'gdp_growth_qoq': 21617.828, 't10y2y_spread': 1.13, 't10y3m_spread': 1.3, 'breakeven_10y': 2.41, 'hy_oas': 3.34, 'ig_oas': 0.93, 'ted_spread': 0.07, 'mortgage_30y': 2.87, 'vix': 15.59000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-08-12] [\"6 Stocks to Buy as Delta Variant Cases Surge There's been an alarming rise in COVID-19 cases in recent weeks, due in large part to the delta variant. While worries over this strain of COVID-19 has created market volatility alongside the spike in infection rates, it's also created some potential buying opportunities in stocks. The delta variant, also known as B.1.617.2, was first identified in India late last year, but has spread to over 85 countries. It now accounts for over 90% of known COVID-19 cases in the U.S., according to the Centers for Disease Control and Prevention (CDC). The Delta variant is problematic as it is more infectious and more effective at evading vaccines. Even in vaccinated individuals, the variant is highly contagious, which allows it to spread quite easily. While most experts don't expect a repeat of the 2020 lockdowns, the delta variant could affect the economy and the equities market \\u2013 especially considering several of the best stocks to buy in 2021 are directly tied to the recovery. Individuals may spend more time at home and away from offices and social gatherings, which could slow the recovery in the job market and the amount consumers spend. This, in turn, could impact certain sectors, including consumer discretionary and consumer staples. Also, the global supply chain could become even more strained, which could affect a variety of industries, like semiconductors and automakers. Investors should consider these six delta variant stocks that could thrive if the spread of the strain intensifies. We looked at stocks tracked by the Stock News POWR Ratings System, and focused on only those that received a Buy or Strong Buy rating from the pros based on the company's current financial situation and future prospects. We then homed in on companies best suited for another prolonged COVID flare-up. Check them out. SEE MORE 32 Bankruptcy Filings Chalked Up to COVID-19 Data is as of Aug. 11. POWR Ratings work on an A-B-C-D-F system. Stocks are listed in order of lowest to highest overall rating, and then alphabetically. Getty Images Adobe Market value: $298.2 billion POWR Ratings overall rating: B (Buy) POWR Ratings average broker rating: 1.35 Cloud company Adobe (ADBE, $626.03) provides content creation, document management and digital marketing and advertising software and services to creative professionals. With more people working at home during the pandemic, the need for ADBE's offerings has skyrocketed. As cases soar and workers remain home for the time being, this demand for its cloud products \\u2013 Creative Cloud, Document Cloud and Adobe Experience Cloud \\u2013 should continue, which should drive top-line growth. The company is also expected to benefit from growth in emerging markets, online video creation demand and improving average revenue per user. ADBE has an overall grade of B, which translates into a Buy rating in our POWR Ratings system. The company has a Stability grade of B, which means it has a histor\n\nPredict whether the return of XLP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.006206, "explanation": "The actual 21-day forward return for XLP starting 2021-08-13 was -0.62%, which classifies as 'flat'.", "metadata": {"future_return": -0.006206, "horizon_days": 21, "hist_return": 0.028668, "annualized_vol": 0.092242, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220715_0961", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2022-07-15", "context_summary": "IWM over past 60 days: cumulative return -15.7%, annualized vol 30.8%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=191.38, end=161.42, cumulative_return=-15.7%, annualized_volatility=30.8%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.913, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.19, 't10y3m_spread': 0.56, 'breakeven_10y': 2.34, 'hy_oas': 5.53, 'ig_oas': 1.6, 'ted_spread': 0.09, 'mortgage_30y': 5.51, 'vix': 26.39999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-14] [\"5 Stocks to Outrun the Housing Market InvestorPlace - Stock Market News, Stock Advice & Trading Tips This article is excerpted from Tom Yeung\\u2019s Profit & Protection newsletter. To make sure you don\\u2019t miss any of Tom\\u2019s picks, subscribe to his mailing list here. CPI Hits 9.1%\\u2026 And Other Bad News On Tuesday, I wrote that exorbitant home prices are driving even relatively well-off professionals out of top markets. No matter how successful a doctor, lawyer or programmer you become, it\\u2019s hard to make $450,000 per year \\u2014 Fidelity Bank\\u2019s estimated buying price for the average apartment in New York\\u2019s Upper East Side. Right on cue, the Bureau of Labor Statistics (BLS) released even more bad news: Inflation hit 9.1% in the month of June. And as shocking as the figure might be, it actually understates the problem. According to data from Zillow, the average cost to rent has risen 14.7% in the past 12 months. But because only one-third of Americans rent (and making some adjustments for homeowners), the BLS only recorded a 5.6% increase in real estate spending among all Americans. But jumping into real estate today is also risky at best. Rising mortgage rates, slackening commodity prices and unaffordable prices point to prolonged stagnation in house values. Real estate prices cannot go to the moon unless wages do too. Instead, investors need to buy companies that benefit from real estate markets without the pricing risk. And today, we will cover five of these fast-growing tech firms that are upending the traditional real estate market. Source: Shutterstock / Unicode Vector 5 Stocks to Outrun the Housing Market Earlier this month, Zillow revealed housing prices have risen 19.4% over the past year. Many homeowners are nervously asking themselves how they\\u2019ll afford a new house if they ever need to move. Meanwhile, renters are in even worse shape. Wages have risen at just one-third the rate of rent increases. And Google\\u2019s 30 million results for the question \\u201chow much does a cardboard box cost to live in\\u201d yield very little helpful advice. At first glance, homebuilder stocks seem like a natural winner. As I mentioned on Tuesday, companies like America\\u2019s largest home builder D.H. Horton (DHI) are earning 4x their operating income compared to five years ago. If home prices are going up, shouldn\\u2019t homebuilder stocks too? But such conclusions fall into the trap of \\u201cfirst-level thinking,\\u201d a term coined by Oaktree Capital co-founder Howard Marks. First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in \\u201cThe outlook for the company is favorable, meaning the stock will go up.\\u201d Second-level thinking is deep, complex and convoluted. That\\u2019s because homebuilding is a low-margin business with virtually no barriers to entry. \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": 0.16165, "explanation": "The actual 21-day forward return for IWM starting 2022-07-15 was +16.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.16165, "horizon_days": 21, "hist_return": -0.156545, "annualized_vol": 0.308436, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20190524_0963", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2019-05-24", "context_summary": "VEA over past 60 days: cumulative return -1.0%, annualized vol 11.1%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=32.80, end=32.45, cumulative_return=-1.0%, annualized_volatility=11.1%\nMacro context: {'fed_funds_rate': 2.38, 'cpi_yoy': 255.296, 'unemployment': 3.6, 'gdp_growth_qoq': 20602.275, 't10y2y_spread': 0.19, 't10y3m_spread': -0.06, 'breakeven_10y': 1.73, 'hy_oas': 4.22, 'ig_oas': 1.28, 'ted_spread': 0.2, 'mortgage_30y': 4.06, 'vix': 16.920000076293945}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-05-23] [\"Huawei feels U.S. squeeze in U.K. and Japan The peril to Huawei Technologies Co.'s global business is growing as foreign partners back away from the Chinese maker of networking equipment and smartphones in the face of U.S. restrictions. U.K.-based chip design company Arm Holdings PLC is suspending its business with Huawei following Washington's blacklisting of the Chinese technology giant, according to a person familiar with the matter.\", \"Podcast: Target Stock Rallies 8% After Strong Earnings 3 numbers to help you navigate the market\\u2014in just two minutes.\", \"Apple Could Take a Huge Earnings Hit if China Retaliates Over Huawei, Goldman Says Apple faces a large risk to its annual profits if China decides to retaliate over the U.S. government\\u2019s decision to restrict sales to Huawei, according to Goldman Sachs.\", \"Qualcomm Stock Plunged After an Antitrust Ruling Qualcomm stock was dropping sharply Wednesday after a U.S. district court ruled in favor of the Federal Trade Commission in its antitrust lawsuit against the chipmaker.\", \"Apple earnings at risk of 29% hit if China retaliates to Huawei ban, Goldman says HSBC has also warned of fallout if Chinese consumers accelerate adoption of local iPhone substitutes amid trade tensions Apple Inc.\\u2019s per-share earnings are at risk of a 29% hit if its products are banned in China in retaliation for measures taken by the U.S. government against Huawei Technologies Co., Goldman Sachs said Wednesday.\", \"Apple stock price target cut to $225 from $235 at UBS\", \"Apple's stock falls 1.6% premarket, after dropping 2.1% on Wednesday\", \"Tesla stock\\u2019s mini \\u2018bullish divergence\\u2019 provides glimmer of hope as prices plunge Aggressive selling, historically oversold conditions increase risk of short squeeze, analyst says A mini \\u201cbullish technical divergence\\u201d pattern in Tesla\\u2019s stock chart suggests bulls still have some hope, at a time that many on Wall Street appear to have thrown in the towel on the electric car maker\\u2019s prospects.\", \"Trade tensions could last well into the 2020 U.S. election campaign, says Nomura Critical information for the U.S. trading day Grab some popcorn and settle in for what could be a long summer, autumn, and winter of trade tensions, says Nomura, in our call of the day.\", \"Apple's stock now down 15.6% from May 3 record close of $211.75\", \"Apple's stock fall 2.3% to lowest level since March 11\", \"Why the Democrats\\u2019 long game on impeachment is working Trump\\u2019s numbers are getting worse, as boost from economy fades House Democrats are wise to play out President Donald Trump\\u2019s drama, rather than rush toward impeachment, writes Tim Mullaney.\", \"Qualcomm stock downgraded at Mizuho amid FTC 'overhang' Mizuho analyst Vijay Rakesh cut his rating on Qualcomm Inc. shares to neutral from buy on Thursday, after a federal judge sided with the Federal Trade Commission and ruled that the company violated antitrust law with its patent royalties. \\\"The l\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": 0.034284, "explanation": "The actual 21-day forward return for VEA starting 2019-05-24 was +3.43%, which classifies as 'positive'.", "metadata": {"future_return": 0.034284, "horizon_days": 21, "hist_return": -0.010475, "annualized_vol": 0.111316, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20180702_0965", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2018-07-02", "context_summary": "IWM over past 60 days: cumulative return +8.9%, annualized vol 11.6%. Market regime: sideways.", "question": "Asset: IWM\nHistorical prices (past 60 trading days): start=136.00, end=148.13, cumulative_return=+8.9%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 1.91, 'cpi_yoy': 251.214, 'unemployment': 3.8, 'gdp_growth_qoq': 20276.154, 't10y2y_spread': 0.33, 't10y3m_spread': 0.92, 'breakeven_10y': 2.11, 'hy_oas': 3.71, 'ig_oas': 1.3, 'ted_spread': 0.45, 'mortgage_30y': 4.55, 'vix': 16.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-06-29] [\"4 Cloud Computing Stocks to Consider InvestorPlace - Stock Market News, Stock Advice & Trading Tips Cloud computing truly has revolutionized American business. The ability to deliver top-level performance anywhere - to a customer of nearly any size - has leveled the playing field for small and medium-sized businesses. And growth is only going to rise going forward. That would seem to create a huge opportunity in cloud computing stocks. But the problem is that the trend isn't exactly hidden - or new. Investors already are pricing many cloud plays at exceedingly high multiples to earnings - and in the cases of many companies that remain unprofitable, to sales. The 10 Fastest-Growing Stocks to Invest In Right Now But there are still opportunities to play the cloud computing trends with stocks whose valuations still allow for strong upside going forward. These four stocks all will benefit from cloud computing - and all are priced reasonably enough to satisfy investors looking for attractive entry points. Cloud Computing Stocks to Consider: Micron (MU) Source: Shutterstock I've admittedly been pushing Micron (NASDAQ: MU ) pretty hard lately , but there really isn't a better cloud play right now than MU stock. And in my defense, I'm not alone in saying that. Luke Lango pointed to cloud computing last week in arguing that MU should trade above $70. Stifel analyst Kevin Cassidy made a similar point after earnings this month, and gave Micron stock a $108 price target . JP Morgan (NYSE: JPM ) has cited the cloud tailwind , and so hasMorgan Stanley (NYSE: MS ). The core argument is rather simple. Micron trades at a seemingly ridiculous valuation (barely 5x forward EPS) because investors are worried that always-cyclical memory pricing eventually will decline. But the memory - particularly on the DRAM side - required for cloud computing should provide years of demand that can help offset any supply expansion. If cloud computing continues to grow, Micron's pricing should hold - and so should its earnings. And at some point in that scenario, Micron will be trading for a lot more than 5x EPS and its current price of $53. Cloud Computing Stocks to Consider: Adobe (ADBE) Source: Shutterstock The story at Adobe (NASDAQ: ADBE ) is a faster-growing version of that of Microsoft (NASDAQ: MSFT ). In both cases, the shift from \\\"on-premise\\\" software to cloud-based offerings hasn't just been a case of selling the same product in a different medium. Rather, the move to the cloud has opened up new cross-selling and revenue opportunities \\u2026 and benefited margins as well. Indeed, Adobe's fantastic growth story often seems a bit lost in the shuffle in terms of tech coverage, despite a $120 billion market capitalization and hugely impressive performance. In fiscal Q2, revenue rose 24% and EPS jumped an impressive 77% year-over-year . Adobe once again beat analyst estimates; it hasn't missed consensus on either revenue or EPS since September 2014. 7 Stocks to Buy That Are\n\nPredict whether the return of IWM over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.008855, "explanation": "The actual 21-day forward return for IWM starting 2018-07-02 was +0.89%, which classifies as 'flat'.", "metadata": {"future_return": 0.008855, "horizon_days": 21, "hist_return": 0.089186, "annualized_vol": 0.116098, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20151013_0967", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2015-10-13", "context_summary": "SCHH over past 60 days: cumulative return +3.3%, annualized vol 18.8%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=14.13, end=14.59, cumulative_return=+3.3%, annualized_volatility=18.8%\nMacro context: {'fed_funds_rate': 0.13, 'cpi_yoy': 237.733, 'unemployment': 5.0, 'gdp_growth_qoq': 18892.206, 't10y2y_spread': 1.47, 't10y3m_spread': 2.11, 'breakeven_10y': 1.54, 'hy_oas': 6.13, 'ig_oas': 1.73, 'ted_spread': 0.31, 'mortgage_30y': 3.76, 'vix': 16.170000076293945}\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": -0.014132, "explanation": "The actual 21-day forward return for SCHH starting 2015-10-13 was -1.41%, which classifies as 'negative'.", "metadata": {"future_return": -0.014132, "horizon_days": 21, "hist_return": 0.032592, "annualized_vol": 0.187797, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20190717_0969", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2019-07-17", "context_summary": "XLP over past 60 days: cumulative return +6.3%, annualized vol 11.0%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=47.22, end=50.17, cumulative_return=+6.3%, annualized_volatility=11.0%\nMacro context: {'fed_funds_rate': 2.41, 'cpi_yoy': 255.802, 'unemployment': 3.7, 'gdp_growth_qoq': 20843.322, 't10y2y_spread': 0.26, 't10y3m_spread': -0.02, 'breakeven_10y': 1.8, 'hy_oas': 3.96, 'ig_oas': 1.18, 'ted_spread': 0.2, 'mortgage_30y': 3.75, 'vix': 12.859999656677246}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-16] [\"Notable Tuesday Option Activity: UVE, AMD, WDC Among the underlying components of the Russell 3000 index, we saw noteworthy options trading volume today in Universal Insurance Holdings Inc (Symbol: UVE), where a total of 1,150 contracts have traded so far, representing approximately 115,000 underlying shares. That amounts to about 52.3% of UVE's average daily trading volume over the past month of 219,995 shares. Especially high volume was seen for the $25 strike call option expiring August 16, 2019, with 1,125 contracts trading so far today, representing approximately 112,500 underlying shares of UVE. Below is a chart showing UVE's trailing twelve month trading history, with the $25 strike highlighted in orange: Advanced Micro Devices Inc (Symbol: AMD) options are showing a volume of 294,746 contracts thus far today. That number of contracts represents approximately 29.5 million underlying shares, working out to a sizeable 50.7% of AMD's average daily trading volume over the past month, of 58.1 million shares. Particularly high volume was seen for the $35 strike call option expiring July 19, 2019, with 36,309 contracts trading so far today, representing approximately 3.6 million underlying shares of AMD. Below is a chart showing AMD's trailing twelve month trading history, with the $35 strike highlighted in orange: And Western Digital Corp (Symbol: WDC) options are showing a volume of 37,907 contracts thus far today. That number of contracts represents approximately 3.8 million underlying shares, working out to a sizeable 49.6% of WDC's average daily trading volume over the past month, of 7.6 million shares. Particularly high volume was seen for the $50 strike put option expiring July 19, 2019, with 4,169 contracts trading so far today, representing approximately 416,900 underlying shares of WDC. Below is a chart showing WDC's trailing twelve month trading history, with the $50 strike highlighted in orange: For the various different available expirations for UVE options, AMD options, or WDC options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The AMD Stock Rally Has Gotten Way Too Advanced in Front of Earnings Shraes of Advanced Micro Devices (NASDAQ:) broke out to fresh multi-year highs yesterday. AMD stock finally closed above the $34 level after three previous failed tries. Momentum traders rejoiced, although shares did finish slightly off the highs of the day. Advanced Micro Devices has now added on over 30% since the lows near $26.50 in late May. All good things must come to an end, though. The red-hot rally in an overbought and overvalued AMD has come too far, too fast. Time to take some chips off the table. InvestorPlace contributor Jay Yao both the bullish and bearish case for AMD stock. He noted that AMD stock price was comparatively expensive, trading a\n\nPredict whether the return of XLP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.006509, "explanation": "The actual 21-day forward return for XLP starting 2019-07-17 was -0.65%, which classifies as 'flat'.", "metadata": {"future_return": -0.006509, "horizon_days": 21, "hist_return": 0.062528, "annualized_vol": 0.109992, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220912_0971", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2022-09-12", "context_summary": "XHB over past 60 days: cumulative return +11.7%, annualized vol 28.4%. Market regime: sideways.", "question": "Asset: XHB\nHistorical prices (past 60 trading days): start=53.81, end=60.11, cumulative_return=+11.7%, annualized_volatility=28.4%\nMacro context: {'fed_funds_rate': 2.33, 'cpi_yoy': 296.349, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.23, 't10y3m_spread': 0.25, 'breakeven_10y': 2.42, 'hy_oas': 4.57, 'ig_oas': 1.47, 'ted_spread': 0.09, 'mortgage_30y': 5.89, 'vix': 22.790000915527344}\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": -0.080977, "explanation": "The actual 21-day forward return for XHB starting 2022-09-12 was -8.10%, which classifies as 'negative'.", "metadata": {"future_return": -0.080977, "horizon_days": 21, "hist_return": 0.116932, "annualized_vol": 0.284288, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20181010_0974", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2018-10-10", "context_summary": "BTC-USD over past 60 days: cumulative return +5.5%, annualized vol 32.2%. Market regime: sideways.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=6295.73, end=6642.64, cumulative_return=+5.5%, annualized_volatility=32.2%\nMacro context: {'fed_funds_rate': 2.18, 'cpi_yoy': 252.772, 'unemployment': 3.8, 'gdp_growth_qoq': 20304.874, 't10y2y_spread': 0.33, 't10y3m_spread': 0.96, 'breakeven_10y': 2.17, 'hy_oas': 3.41, 'ig_oas': 1.13, 'ted_spread': 0.21, 'mortgage_30y': 4.71, 'vix': 15.949999809265137}\nMarket regime: sideways\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": -0.040683, "explanation": "The actual 21-day forward return for BTC-USD starting 2018-10-10 was -4.07%, which classifies as 'negative'.", "metadata": {"future_return": -0.040683, "horizon_days": 21, "hist_return": 0.055102, "annualized_vol": 0.321807, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20160114_0976", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2016-01-14", "context_summary": "VTI over past 60 days: cumulative return -5.8%, annualized vol 16.4%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=87.97, end=82.84, cumulative_return=-5.8%, annualized_volatility=16.4%\nMacro context: {'fed_funds_rate': 0.36, 'cpi_yoy': 237.652, 'unemployment': 4.8, 'gdp_growth_qoq': 19001.69, 't10y2y_spread': 1.17, 't10y3m_spread': 1.86, 'breakeven_10y': 1.43, 'hy_oas': 7.5, 'ig_oas': 1.8, 'ted_spread': 0.4, 'mortgage_30y': 3.97, 'vix': 25.21999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-13] [\"CLSA Survey: China\\u2019s iPhone Demand Remains Firm Smartphone hardware stocks are sold off this year. Apple (AAPL) has fallen 5%, while Samsung Electronics (005930.Korea/SSNLF) has retreated 9.1% on concerns over a sharp smartphone growth slowdown.After conducting a consumer intent survey in December, Asia-based broker CLSA continues to feel bullish about Apple, but has cooled towards its competitors Huawei, Xiaomi and Samsung.READ MORE.\", \"Oversold Apple Stocks Apple's (AAPL) supply chain in Asia has sank with its patron this year. In Taiwan, casing supplier Catcher Technology (2474.Taiwan) lost a quarter of its market value in 7 trading days, while Apple's foundry Taiwan Semiconductor Manufacturing Corp., or TSMC (2330.Taiwan/TSM) retreated 7.6%.Some of the setback is media reports that Apple would cut its iPhone production by a third in the March quarter, but the weaker yuan, which has rattled stocks, commodities, and currencies worldwide, is also to blame.As yuan calms and dust settles, we may find some Apple suppliers oversold. \\\"On valuation, we find a few Apple names trading near book value, but still generating respectable free cash flow, ROE and dividend yields,\\\" noted HSBC's Steven Pelayo this morning.READ MORE.\", \"Qualcomm Teams with TDK in RF Assault on Skyworks, Qorvo Wireless chip giant Qualcomm (QCOM) early Wednesday morning announced it would team with Japan\\u2019s TDK (TTDKY) to produce more complete radio frequency chips, a move that could bring the company into closer competition with RF leaders Skyworks Solutions (SWKS) and Qorvo (QRVO).Qualcomm said it will form a joint venture with TDK, called RF360 Holdings, 51% owned by Qualcomm, to make what are known as \\u201cRF front-end modules,\\u201d combining parts from Qualcomm, such as power amplifiers,\\u201d with parts in which TDK specializes, such as radio-frequency filters.Qualcomm has long dominated the the baseband modem in smartphones such as Apple's (AAPL) iPhone and most other major devices. From the modem it has built a growing business supplying application processors, but also, increasingly, more of the radio-frequency chips that tune a phone to the particular electromagnetic frequency by which they must send and receive signals.TDK, founded in 1935, is best known for its magnetic recording media, especially the cassette tape. But it also has an extensive microelectronics business. That business includes parts of wireless equation that Qualcomm lacks, such as surface acoustic wave, or SAW, filters.Qualcomm has an option to buy out TDK\\u2019s share in the venture, after 30 months have passed from the closing of the deal. In a phone call I had with the company, Qualcomm\\u2019s chief financial officer, George Davis, said \\\"we would anticipate that being exercised\\u201d ultimately.\", \"Steer clear of Saudi Aramco\\u2019s initial public offering It would be world\\u2019s biggest listed company, but it\\u2019d come with lots of unknowns The initial public offering for Saudi \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": 0.0, "explanation": "The actual 21-day forward return for VTI starting 2016-01-14 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": -0.058318, "annualized_vol": 0.163785, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20211012_0978", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2021-10-12", "context_summary": "XLE over past 60 days: cumulative return +21.5%, annualized vol 29.7%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=19.72, end=23.95, cumulative_return=+21.5%, annualized_volatility=29.7%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 276.55, 'unemployment': 4.5, 'gdp_growth_qoq': 21988.737, 't10y2y_spread': 1.29, 't10y3m_spread': 1.56, 'breakeven_10y': 2.5, 'hy_oas': 3.2, 'ig_oas': 0.9, 'ted_spread': 0.07, 'mortgage_30y': 2.99, 'vix': 20.0}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-11] [\"Loci Cycle Crypto Training Course 2021 by Chris Munch - Price And Bonuses Review The Loci Cycle system will be perfect for all those entrepreneurs interested in launching their own crypto ventures. Chris Munch equips users with the expert knowledge, proven strategies, and software tools to create a very sustainable source of income.London, United Kingdom, Oct. 10, 2021 (GLOBE NEWSWIRE) -- Chris Munch, the founder and CEO of AmpiFire, is launching the Loci Cycle. This comprehensive digital marketing training program can help entrepreneurs build a 6, even 7-figure income onlin\", \"Apple's AirPods Max headphones are $100 off at Amazon Apple's AirPods Max headphones are on sale in all colors $449 at Amazon.\", \"The Morning After: Google might offer a Pixel Phone subscription bundle Today\\u2019s headlines: Google might offer a subscription bundle with its next Pixel phone, Burger King\\u2019s Impossible Nuggets go on sale this week, Sony and TSMC may team up to tackle global chip shortages.\", \"Apple's MacBook Air M1 returns to record low of $850 at Amazon Amazon knocks the MacBook Air M1 down to a record low of $850.\", \"Apple appeals the Epic Games ruling and asks to put ordered App Store changes on hold A federal judge declared last month that Apple was not a monopoly when issuing the court's decision on California\\u2019s Epic Games v. Apple case. On this point, the judge sided with Epic Games, saying that Apple can no longer prohibit developers from pointing to other means of payment beyond Apple's own payment systems. Now, Apple is appealing that decision and asking for a stay on the injunction the judge had put into place.\", \"Apple releases iOS 15.0.2 with a security fix for a bug 'under active exploitation' Apple today released its second minor update to iOS 15 and iPadOS 15, which includes an \\\"important security update\\\" for a zero-day bug under active exploitation. While details on the bug remain thin, Apple warns that it \\\"may have been actively exploited\\\" \\u2014 so it's probably a good idea to update your devices right away. The updates also address a number of other glitches in iOS 15 and iPadOS 15, including an issue that caused the iPhone Leather Wallet and with MagSafe and not to connect to Find My, a bug that could cause AirTags not to appear in the \\u200cFind My\\u200c Items tab, and another that caused CarPlay to fail to open audio apps or to disconnect during playback.\", \"LiveOne To Present At The LD Micro Main Event On October 12th At 1:00 PM PT/4:00 PM ET LiveOne (Nasdaq: LVO) (\\\"LiveOne\\\"), a global platform for livestream and on-demand audio, video, and podcast/vodcast content in music, comedy, and pop culture, and owner of LiveXLive, PodcastOne, Slacker Radio, React Presents and Custom Personalization Solutions, announced today that its Chairman & CEO, Robert Ellin, will present at the LD Micro Main Event investor conference on Tuesday, October 12th at 1:00 pm PT/4:00 pm ET. The event will be held in-person at the Luxe Sunset Bel\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": 0.018791, "explanation": "The actual 21-day forward return for XLE starting 2021-10-12 was +1.88%, which classifies as 'positive'.", "metadata": {"future_return": 0.018791, "horizon_days": 21, "hist_return": 0.214751, "annualized_vol": 0.296687, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20210118_0980", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2021-01-18", "context_summary": "DBA over past 60 days: cumulative return +11.2%, annualized vol 9.9%. Market regime: sideways.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=13.14, end=14.61, cumulative_return=+11.2%, annualized_volatility=9.9%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 262.687, 'unemployment': 6.4, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 0.98, 't10y3m_spread': 1.02, 'breakeven_10y': 2.1, 'hy_oas': 3.74, 'ig_oas': 1.0, 'ted_spread': 0.13, 'mortgage_30y': 2.79, 'vix': 24.34000015258789}\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": 0.024155, "explanation": "The actual 21-day forward return for DBA starting 2021-01-18 was +2.42%, which classifies as 'positive'.", "metadata": {"future_return": 0.024155, "horizon_days": 21, "hist_return": 0.112156, "annualized_vol": 0.09926, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20210223_0982", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-02-23", "context_summary": "MATIC-USD over past 60 days: cumulative return +814.5%, annualized vol 188.6%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.02, end=0.15, cumulative_return=+814.5%, annualized_volatility=188.6%\nMacro context: {'fed_funds_rate': 0.07, 'cpi_yoy': 263.579, 'unemployment': 6.2, 'gdp_growth_qoq': 21082.134, 't10y2y_spread': 1.26, 't10y3m_spread': 1.34, 'breakeven_10y': 2.16, 'hy_oas': 3.44, 'ig_oas': 0.95, 'ted_spread': 0.15, 'mortgage_30y': 2.81, 'vix': 23.450000762939453}\nMarket regime: sideways\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": 1.724149, "explanation": "The actual 21-day forward return for MATIC-USD starting 2021-02-23 was +172.41%, which classifies as 'positive'.", "metadata": {"future_return": 1.724149, "horizon_days": 21, "hist_return": 8.145359, "annualized_vol": 1.886186, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20201026_0986", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2020-10-26", "context_summary": "DBB over past 60 days: cumulative return +6.7%, annualized vol 18.5%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=12.72, end=13.57, cumulative_return=+6.7%, annualized_volatility=18.5%\nMacro context: {'fed_funds_rate': 0.09, 'cpi_yoy': 260.319, 'unemployment': 6.9, 'gdp_growth_qoq': 20791.917, 't10y2y_spread': 0.67, 't10y3m_spread': 0.75, 'breakeven_10y': 1.75, 'hy_oas': 4.87, 'ig_oas': 1.3, 'ted_spread': 0.12, 'mortgage_30y': 2.8, 'vix': 27.549999237060547}\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": 0.066411, "explanation": "The actual 21-day forward return for DBB starting 2020-10-26 was +6.64%, which classifies as 'positive'.", "metadata": {"future_return": 0.066411, "horizon_days": 21, "hist_return": 0.066667, "annualized_vol": 0.184958, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20200701_0988", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2020-07-01", "context_summary": "BNB-USD over past 60 days: cumulative return -12.3%, annualized vol 41.4%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=17.58, end=15.41, cumulative_return=-12.3%, annualized_volatility=41.4%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 257.042, 'unemployment': 11.0, 'gdp_growth_qoq': 19077.992, 't10y2y_spread': 0.5, 't10y3m_spread': 0.5, 'breakeven_10y': 1.34, 'hy_oas': 6.44, 'ig_oas': 1.6, 'ted_spread': 0.14, 'mortgage_30y': 3.13, 'vix': 30.43000030517578}\nMarket regime: sideways\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": 0.142926, "explanation": "The actual 21-day forward return for BNB-USD starting 2020-07-01 was +14.29%, which classifies as 'positive'.", "metadata": {"future_return": 0.142926, "horizon_days": 21, "hist_return": -0.123476, "annualized_vol": 0.413967, "has_text": false, "text_chars": 0}}
{"id": "T1_all_20220203_0992", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2022-02-03", "context_summary": "MATIC-USD over past 60 days: cumulative return -23.9%, annualized vol 101.2%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=2.03, end=1.54, cumulative_return=-23.9%, annualized_volatility=101.2%\nMacro context: {'fed_funds_rate': 0.08, 'cpi_yoy': 284.5, 'unemployment': 3.9, 'gdp_growth_qoq': 21932.71, 't10y2y_spread': 0.62, 't10y3m_spread': 1.59, 'breakeven_10y': 2.41, 'hy_oas': 3.45, 'ig_oas': 1.08, 'ted_spread': 0.09, 'mortgage_30y': 3.55, 'vix': 22.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-02-02] \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": -0.071378, "explanation": "The actual 21-day forward return for MATIC-USD starting 2022-02-03 was -7.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.071378, "horizon_days": 21, "hist_return": -0.239231, "annualized_vol": 1.012061, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20220426_0994", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2022-04-26", "context_summary": "XLI over past 60 days: cumulative return -0.9%, annualized vol 18.5%. Market regime: sideways.", "question": "Asset: XLI\nHistorical prices (past 60 trading days): start=93.33, end=92.44, cumulative_return=-0.9%, annualized_volatility=18.5%\nMacro context: {'fed_funds_rate': 0.33, 'cpi_yoy': 288.561, 'unemployment': 3.7, 'gdp_growth_qoq': 21967.045, 't10y2y_spread': 0.18, 't10y3m_spread': 1.9, 'breakeven_10y': 2.86, 'hy_oas': 3.8, 'ig_oas': 1.35, 'ted_spread': 0.09, 'mortgage_30y': 5.11, 'vix': 27.020000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-25] [\"Adobe Systems (ADBE) Outpaces Stock Market Gains: What You Should Know Adobe Systems (ADBE) closed at $413.95 in the latest trading session, marking a +1.29% move from the prior day. The stock outpaced the S&P 500's daily gain of 0.57%. Meanwhile, the Dow gained 0.7%, and the Nasdaq, a tech-heavy index, lost 0.1%. Prior to today's trading, shares of the software maker had lost 5.32% over the past month. This has was narrower than the Computer and Technology sector's loss of 11.12% and lagged the S&P 500's loss of 5.26% in that time. Adobe Systems will be looking to display strength as it nears its next earnings release. In that report, analysts expect Adobe Systems to post earnings of $3.30 per share. This would mark year-over-year growth of 8.91%. Our most recent consensus estimate is calling for quarterly revenue of $4.34 billion, up 13.12% from the year-ago period. For the full year, our Zacks Consensus Estimates are projecting earnings of $13.58 per share and revenue of $17.83 billion, which would represent changes of +8.81% and +12.93%, respectively, from the prior year. Investors might also notice recent changes to analyst estimates for Adobe Systems. These revisions help to show the ever-changing nature of near-term business trends. As a result, we can interpret positive estimate revisions as a good sign for the company's business outlook. Research indicates that these estimate revisions are directly correlated with near-term share price momentum. We developed the Zacks Rank to capitalize on this phenomenon. Our system takes these estimate changes into account and delivers a clear, actionable rating model. 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. Within the past 30 days, our consensus EPS projection has moved 0.01% higher. Adobe Systems is currently a Zacks Rank #3 (Hold). In terms of valuation, Adobe Systems is currently trading at a Forward P/E ratio of 30.09. Its industry sports an average Forward P/E of 28.39, so we one might conclude that Adobe Systems is trading at a premium comparatively. Meanwhile, ADBE's PEG ratio is currently 1.73. The PEG ratio is similar to the widely-used P/E ratio, but this metric also takes the company's expected earnings growth rate into account. The Computer - Software industry currently had an average PEG ratio of 2.37 as of yesterday's close. The Computer - Software industry is part of the Computer and Technology sector. This industry currently has a Zacks Industry Rank of 160, which puts it in the bottom 37% of all 250+ industries. The Zacks Industry Rank includes is listed in order 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. To follow ADBE in the coming trading sessions, b\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": -0.047673, "explanation": "The actual 21-day forward return for XLI starting 2022-04-26 was -4.77%, which classifies as 'negative'.", "metadata": {"future_return": -0.047673, "horizon_days": 21, "hist_return": -0.009454, "annualized_vol": 0.185028, "has_text": true, "text_chars": 3020}}
{"id": "T1_all_20220923_0996", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2022-09-23", "context_summary": "MATIC-USD over past 60 days: cumulative return -3.0%, annualized vol 74.7%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.78, end=0.75, cumulative_return=-3.0%, annualized_volatility=74.7%\nMacro context: {'fed_funds_rate': 3.08, 'cpi_yoy': 296.349, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.41, 't10y3m_spread': 0.41, 'breakeven_10y': 2.41, 'hy_oas': 4.91, 'ig_oas': 1.48, 'ted_spread': 0.09, 'mortgage_30y': 6.29, 'vix': 27.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-22] \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": 0.017995, "explanation": "The actual 21-day forward return for MATIC-USD starting 2022-09-23 was +1.80%, which classifies as 'positive'.", "metadata": {"future_return": 0.017995, "horizon_days": 21, "hist_return": -0.029514, "annualized_vol": 0.747104, "has_text": true, "text_chars": 20}}
{"id": "T1_all_20220718_0998", "template": "T1", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2022-07-18", "context_summary": "XRP-USD over past 60 days: cumulative return -18.2%, annualized vol 60.0%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=0.42, end=0.34, cumulative_return=-18.2%, annualized_volatility=60.0%\nMacro context: {'fed_funds_rate': 1.58, 'cpi_yoy': 294.913, 'unemployment': 3.5, 'gdp_growth_qoq': 22125.625, 't10y2y_spread': -0.2, 't10y3m_spread': 0.56, 'breakeven_10y': 2.36, 'hy_oas': 5.39, 'ig_oas': 1.58, 'ted_spread': 0.09, 'mortgage_30y': 5.51, 'vix': 24.229999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-17] \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": "positive", "answer_numeric": 0.034347, "explanation": "The actual 21-day forward return for XRP-USD starting 2022-07-18 was +3.43%, which classifies as 'positive'.", "metadata": {"future_return": 0.034347, "horizon_days": 21, "hist_return": -0.182306, "annualized_vol": 0.600231, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20171211_0000", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2017-12-11", "context_summary": "XLV: 60-day return history, mean=0.0000, std=0.0053.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0000, std=0.0053, min=-0.0123, max=0.0133\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-12-08] [\"A tale of two bubbles \\u2014 the dot-coms and bitcoin The internet paid off in the end because it solved a real problem; bitcoin doesn\\u2019t Bitcoin is the biggest bubble since the dot-com era but, unlike bitcoin, the dot-com companies actually solved a real problem, writes Tim Mullaney.\", \"We\\u2019re still only in the early stages of stock-market euphoria Bitcoin and FAANGs excepted, of course Well, with the exception of bitcoin and FAANG stocks, says Howard Gold.\", \"YouTube plans to launch new streaming music offering: report Alphabet Inc.'s YouTube is planning to debut a new streaming music service in March to compete with Spotify and Apple Inc., according to a Bloomberg report from Thursday night. The service, called Remix, would feature streaming music as well as video clips, Bloomberg said, citing sources familiar with YouTube's plans. YouTube has reportedly inked a deal with Warner Music Group and is talking with other major labels, including Universal Music Group and Sony Corp.'s Sony Music Entertainment. Prior subscription music offerings from YouTube, including YouTube Red, have failed to generate the same interest as Apple Music or Spotify. Alphabet shares are up 0.1% in premarket trading Friday and up 32% so far in 2017. The S&P 500 has gained 18% in that time. (This replaces an earlier item that incorrectly reported the date of the Bloomberg report.)\", \"Apple stock rises after analyst points to supply-chain strength Apple Inc. shares gained 0.5% in Friday morning trading after an analyst at Drexel Hamilton penned an upbeat note on the Apple supply chain. Drexel's Brian White wrote that sales for his \\\"Apple Monitor,\\\" a basket of Apple suppliers, rose 7% in November, ahead of the season average of 6%. White is also optimistic that Apple will have a good holiday season and benefit from the iPhone X over the long term. \\\"We believe this is a durable iPhone cycle that will pay dividends for years to come given that the iPhone X pushes Apple deep into the ultra-luxury smartphone market with the highest-priced iPhone in the company's history,\\\" he wrote. Apple shares have gained 46% so far in 2017, compared with a 23% gain for the Dow Jones Industrial Average .\", \"Finisar stock gains after Apple hopes outweigh disappointing earnings Shares of Finisar Corp. gained 3.7% in Friday morning trade even though the company's earnings fell short of expectations and several analysts slashed their price targets. The company, which reported fiscal second-quarter earnings late Thursday, also delivered a lower-than-expected earnings outlook for the current quarter. Finisar, which makes products that help enable 3D-sensing technology, said on its earnings conference call that it had acquired a new plant in Texas and would expand manufacturing capacity. \\\"This was a mixed quarter, with gross margin weakness from the low 3D utilization, but with shipments ramping, the trajectory suggests Finisar received certification to sell to Apple ,\\\" wrote Raymond\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": "-0.0080", "answer_numeric": -0.008011, "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%) = -0.0110.", "metadata": {"var": -0.008011, "cvar": -0.011048, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180613_0004", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-06-13", "context_summary": "XRP-USD: 60-day return history, mean=-0.0006, std=0.0551.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0006, std=0.0551, min=-0.1435, max=0.1673\nMarket regime: sideways\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": "-0.0917", "answer_numeric": -0.091697, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0917 (i.e., on a bad day with 5% probability, the loss exceeds 9.17%). CVaR(95%) = -0.1163.", "metadata": {"var": -0.091697, "cvar": -0.116254, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160127_0007", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2016-01-27", "context_summary": "EEM: 60-day return history, mean=-0.0027, std=0.0142.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0027, std=0.0142, min=-0.0341, max=0.0317\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-26] [\"Skyworks, Cirrus: Apple \\u2018Capitulation\\u2019 Will Be the Buy Sign, Says Pac Crest When Apple (AAPL) files fiscal Q1 results tomorrow, Tuesday, after the closing bell, it\\u2019ll be time to buy shares of SkyworksSolutions (SWKS) and Cirrus Logic (CRUS), according to John Vinh with Pacific Crest Securities in a note to clients today.Apple\\u2019s numbers, after months of hand-wringing about the volume of iPhone shipments that may happen in March \\u2014 something that carried right through to today \\u2014 is expected by Vinh to lead to a \\\"reset in expectations\\u201d that \\\"would be viewed as a positive catalyst for suppliers CRUS and SWKS.\\\"The stocks already probably reflect the worst for Cirrus and Skyworks, he writes:Read further...\", \"Apple Q1 Capitulation to Boost Cirrus, Skyworks Weaker-than-expected results and guidance from Apple is anticipated and would prove a catalyst to suppliers.\", \"Apple Earnings: 3 Supply Chain Stocks to Watch Asian suppliers are down 30% but don\\u2019t rush in: Market share gainers with strong cash flows are best bets.\", \"Can Tim Cook solve Apple\\u2019s China challenge? Chinese market holds the key to Apple\\u2019s earnings China, powered by a swelling middle class, last year became Apple Inc.\\u2019s biggest market after the Americas.\", \"10 stock market \\u2018darlings\\u2019 you may want to break up with Credit Suisse has identified the stocks most commonly held by funds \\u2014 and recommends selling a lot of them Credit Suisse has identified the stocks most commonly held by funds \\u2014 and recommends selling a lot of them.\", \"Here\\u2019s the chart that predicts Apple shares are headed for the $70s Critical intelligence before the U.S. stock market opens Apple reports Tuesday and a lot is on the line, both for investors in the stock and those in the S&P 500. The gloomsters won\\u2019t be silenced. Here\\u2019s one call that says the stock is headed to $70.\", \"The turning point in the stock market starts now Company earnings and economic reports support a rebound in equities Company earnings and economic reports support a rebound in equities, writes Tim Mullaney.\", \"Apple: Ahead of FYQ1 Report, Estimates Still Coming Down Shares of Apple (AAPL) are up 13 cents at $99.57, reversing losses at the open, as the company heads toward its fiscal Q1 report this afternoon, after the closing bell.Analysts are, on average, are modeling $76.6 billion and $3.23 per share. That includes an estimate for Apple to have sold 75 million iPhones, according to FactSet.For the March forecast, the Street is currently modeling $55.41 billion and $2.21 per share. That includes an iPhone number of 54 million units.There\\u2019s still time for analysts to get their vote in for tonight\\u2019s report. A couple are also still cutting their iPhone numbers for the full year that ends in September.Read further...\", \"Apple investors bracing for first decline in iPhone sales What to expect from Apple earnings, planned for Tuesday afternoon Apple is p\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": "-0.0278", "answer_numeric": -0.027754, "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%) = -0.0313.", "metadata": {"var": -0.027754, "cvar": -0.0313, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210326_0010", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2021-03-26", "context_summary": "ETH-USD: 60-day return history, mean=0.0035, std=0.0489.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0035, std=0.0489, min=-0.1188, max=0.1068\nMarket regime: sideways\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": "-0.0767", "answer_numeric": -0.076682, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0767 (i.e., on a bad day with 5% probability, the loss exceeds 7.67%). CVaR(95%) = -0.0970.", "metadata": {"var": -0.076682, "cvar": -0.096988, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210520_0013", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2021-05-20", "context_summary": "XRP-USD: 60-day return history, mean=0.0186, std=0.1097.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0186, std=0.1097, min=-0.2138, max=0.3257\nMarket regime: sideways\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": "-0.1234", "answer_numeric": -0.123426, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1234 (i.e., on a bad day with 5% probability, the loss exceeds 12.34%). CVaR(95%) = -0.1774.", "metadata": {"var": -0.123426, "cvar": -0.177441, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220127_0016", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-01-27", "context_summary": "ETH-USD: 60-day return history, mean=-0.0076, std=0.0399.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0076, std=0.0399, min=-0.1477, max=0.0729\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-26] \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": "-0.0662", "answer_numeric": -0.066183, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0662 (i.e., on a bad day with 5% probability, the loss exceeds 6.62%). CVaR(95%) = -0.1015.", "metadata": {"var": -0.066183, "cvar": -0.101454, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20210218_0019", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2021-02-18", "context_summary": "QUAL: 60-day return history, mean=0.0013, std=0.0078.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0013, std=0.0078, min=-0.0232, max=0.0160\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-02-17] [\"Martin Scorsese laments the rise of \\u2018content\\u2019 and streaming\\u2019s lack of curation Oscar-winning director Martin Scorsese took a shot at streaming services Tuesday for devaluing cinema to mere \\\"content,\\\" and said algorithms are ruining discovery.\", \"The 2021 BMW 8 Series is a formidable blend of power and suppleness These large luxury grand touring machines offer brilliant handling and a luxurious interior, but can get a little pricey compared with the competition.\", \"This is how the great chip shortage happened \\u2014 and how it gets solved Car companies and smartphone makers don't have enough semiconductors to meet demand for their products. The crunch should let up by mid-year, but there's a greater concern that the U.S. doesn't control enough manufacturing.\", \"Bitcoin\\u2019s Run Doesn\\u2019t Make Sense Berkshire Hathaway\\u2019s mystery investments are Verizon and Chevron, major winter storm slows U.S. vaccination effort, Epic Games takes Apple battle to Brussels, and other news to start your day.\", \"Michael B. Jordan gave his girlfriend Herm\\u00e8s stock for Valentine\\u2019s Day The 'Black Panther' star gave Lori Harvey a gift that could keep on giving.\", \"Dow drops 84 points on losses in shares of Apple Inc., Walt Disney\", \"Dow flat in spite of losses for Apple Inc., American Express shares\", \"Looking to avoid an obscenely overpriced U.S. stock market? Here\\u2019s one strategist\\u2019s advice on how to ride the inflation wave If inflation is coming, where should investors go? How about Latin America, says one strategist.\", \"Moore Kuehn Encourages Investors of TSN, SPLK or CLOV to Contact Law Firm Moore Kuehn, PLLC, a securities law firm located on Wall Street, is investigating potential claims involving directors and officers regarding possible breaches of fiduciary duties related to whether insiders caused their companies to make false and/or misleading statements and/or failed to disclose, among other things, that:\", \"Dublin Attic And Wall Insulation Specialists Home Energy Assessment Launched Usher Insulations announced that their new Home Energy Assessment service is now available for clients in Dublin and surrounding areas, who are looking to reduce their energy billsDublin, Ireland , Feb. 16, 2021 (GLOBE NEWSWIRE) -- Usher Insulations, a leading home insulation contractor in Dublin, Ireland, announced the launch of their new Home Energy Assessment service. The company can help homeowners to identify their building\\u2019s energy efficiency. More information can be found at https://www.usherinsulations.com The newly launched Home Energy Assessment service at Usher Insulations aims to identify the right steps to improve energy efficiency in each client\\u2019s home, in locations across the greater Dublin area including counties Louth, Meath, Kildare and Wicklow. For homeowners looking to save heat and make their home warmer, more comfortable and energy efficient, getting a professional energy assessment can be an excellent s\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": "-0.0079", "answer_numeric": -0.007914, "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%) = -0.0202.", "metadata": {"var": -0.007914, "cvar": -0.020243, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200715_0022", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2020-07-15", "context_summary": "VEA: 60-day return history, mean=0.0025, std=0.0136.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0025, std=0.0136, min=-0.0276, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-07-14] [\"S&P 500, Dow rise after mixed bank earnings; tech-heavy Nasdaq falls By Medha Singh and Devik Jain July 14 (Reuters) - The S&P 500 and Dow indexes edged higher in volatile trading on Tuesday as investors digested a mixed bag of quarterly earnings reports from U.S. lenders but technology stocks fell on worries over new business restrictions in California. JPMorgan Chase & Co JPM.N, the largest U.S. lender, was up 0.2% after it posted a smaller-than-expected 51% drop in second-quarter profit. Wells Fargo & Co WFC.N, however, fell 5.5% after booking a quarterly loss for the first time since the 2008 financial crisis. Citigroup Inc C.N was also down 2.5% as it reported a steep fall in quarterly profit. The S&P 500 banks index .SPXBK slumped 1.6% as the three banks set aside a combined $28 billion to cover potential losses on loans to borrowers hurt by the coronavirus pandemic. \\\"The choppiness is very natural as we've had our fair share of gains over the last two or three weeks now,\\\" said Luis Strohmeier, wealth advisor at Octavia in Los Angeles, California. \\\"There's a level of uncertainty due to California temporary shutting down indoors ... because we weren't prepared for a reversal in the opening.\\\" Wall Street has reclaimed most of its coronavirus-driven losses since March as a raft of monetary and fiscal stimulus and upbeat economic data raised hopes of a swift post-pandemic recovery. But a recent record surge in COVID-19 cases and new business restrictions, particularly in California, have sparked a selloff in tech stocks, with the Nasdaq pulling back about 6% from its intraday record high on Monday. Investors are bracing for what could be the sharpest drop in quarterly earnings for S&P 500 firms since the 2008 financial crisis, according to Refinitiv IBES data. At 12:55 p.m. ET, the Dow Jones Industrial Average .DJI was up 257.51 points, or 0.99%, at 26,343.31, the S&P 500 .SPX was up 7.03 points, or 0.22%, at 3,162.25. The Nasdaq Composite .IXIC was down 41.96 points, or 0.40%, at 10,348.88. Amazon.com Inc AMZN.O, Adobe Inc ADBE.O and Facebook Inc FB.O, all three of which hit record highs in intraday trading on Monday, were some of the biggest drags on the Nasdaq. Delta Air Lines Inc DAL.N fell 2.5% as it warned it will be more than two years before the industry sees a sustainable recovery from the \\\"staggering\\\" impact of the coronavirus pandemic, with demand largely tracking the curve of infections in different places. Moderna Inc MRNA.O rose 3.7% as it plans to start a late-stage clinical trial for its COVID-19 vaccine candidate on or around July 27. Advancing issues outnumbered decliners by a 1.41-to-1 ratio on the NYSE and for a 1.01-to-1 ratio on the Nasdaq. The S&P index recorded three new 52-week highs and no new low, while the Nasdaq recorded 23 new highs and 27 new lows. COVID-19's growing potential economic impacthttps://tmsnrt.rs/307zCt5 (Reporting by Medha Singh and Devik Jain in Bengaluru; Editing by Shounak Dasgupta and Ani\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": "-0.0209", "answer_numeric": -0.020892, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0209 (i.e., on a bad day with 5% probability, the loss exceeds 2.09%). CVaR(95%) = -0.0250.", "metadata": {"var": -0.020892, "cvar": -0.024965, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200624_0025", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-06-24", "context_summary": "MATIC-USD: 60-day return history, mean=0.0089, std=0.0594.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0089, std=0.0594, min=-0.1465, max=0.2137\nMarket regime: sideways\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": "-0.0743", "answer_numeric": -0.074297, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0743 (i.e., on a bad day with 5% probability, the loss exceeds 7.43%). CVaR(95%) = -0.1113.", "metadata": {"var": -0.074297, "cvar": -0.111276, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170817_0028", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2017-08-17", "context_summary": "REZ: 60-day return history, mean=0.0001, std=0.0071.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0001, std=0.0071, min=-0.0249, max=0.0164\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": "-0.0117", "answer_numeric": -0.011746, "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": -0.011746, "cvar": -0.01669, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20171123_0033", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2017-11-23", "context_summary": "IYR: 60-day return history, mean=0.0006, std=0.0049.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0006, std=0.0049, min=-0.0101, max=0.0116\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": "-0.0077", "answer_numeric": -0.007732, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0077 (i.e., on a bad day with 5% probability, the loss exceeds 0.77%). CVaR(95%) = -0.0089.", "metadata": {"var": -0.007732, "cvar": -0.008893, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180727_0036", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2018-07-27", "context_summary": "XLP: 60-day return history, mean=0.0012, std=0.0070.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0012, std=0.0070, min=-0.0198, max=0.0144\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-26] [\"This reversal shows there\\u2019s risk in the bullish stock market \\u2014 and Facebook is further proof Big tech stocks are faltering, so make sure to hold cash and maintain hedges Big tech stocks are faltering, so make sure to hold cash and maintain hedges, says Nigam Arora.\", \"This FAANG stock looks like the next Berkshire Hathaway \\u2014 a smart bet for the next 25 years Critical information for the U.S. trading day Tough day out there for tech stocks, but our call of the day says if you\\u2019ve got an eye on the future, then this superstar in that sector could be big like Berkshire in the next 25 years.\", \"Qualcomm drops NXP acquisition, leaves analysts concerned about Apple business Several price-target hikes follow better-than-expected earnings Nearly two years after Qualcomm Inc. announced its intent to acquire NXP Semiconductors NV, investors are pleased that the company is moving on.\", \"Is Facebook\\u2019s thud a bad omen for FAANG stocks? Simon Maierhofer looks at technical indicators that suggest the fundamentals are deteriorating Simon Maierhofer looks at technical indicators that suggest the fundamentals are deteriorating.\", \"Wall Street veteran who flagged Apple at $1.14 a share says these 5 overlooked stocks are buys \\u2018Turnaround Letter\\u2019 editor\\u2019s picks include Blue Apron, AMC Entertainment \\u2018Turnaround Letter\\u2019 editor\\u2019s picks include Blue Apron, AMC Entertainment, writes Mark Hulbert.\", \"Amazon earnings: Prime Day isn\\u2019t the only thing giving business a boost Amazon shares are up 25.3% for the last three months and the e-commerce giant is on the road to a $1 trillion market cap Amazon is expected to report earnings that reflect growth across advertising and cloud services as well as e-commerce.\", \"Intel earnings: After CEO departure, chip maker needs a win Data-center and PC revenue will be closely watched as Intel looks for a new leader Intel Corp. needs strong gains in its core personal-computer business as well as its server segment to overcome uncertainties about management succession and its manufacturing processes in the wake of a sudden shake-up.\", \"Why Facebook\\u2019s stock plunge may gather steam When stocks open 15% or lower after earnings, they tend to close even weaker by the end of session It is an ugly day for Facebook, but an unsightly tumble for the social-media giant may get worse before it gets better.\", \"Facebook Investors Want to Strip Zuckerberg of Chairman Title Trillium, which filed a shareholder proposal asking the company to remove Zuckerberg as chairman before the company announced disappointing results Wednesday, is the latest group of investors who want a change.\", \"Tech Today: Facebook\\u2019s Fall, AMD\\u2019s New High, an Apple Beat? Facebook's got a credibility gap to deal with, AMD is heading for its highest level in over a decade, and some see nice trends for Apple heading into its earnings report next Tuesday.\", \"\\u2018Oh sh-t!\\u2019 Facebook\\u2019s historic plunge, as\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": -0.008481, "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%) = -0.0169.", "metadata": {"var": -0.008481, "cvar": -0.016876, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20191016_0041", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-10-16", "context_summary": "LINK-USD: 60-day return history, mean=0.0016, std=0.0467.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0016, std=0.0467, min=-0.0981, max=0.1130\nMarket regime: sideways\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": "-0.0619", "answer_numeric": -0.061913, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0619 (i.e., on a bad day with 5% probability, the loss exceeds 6.19%). CVaR(95%) = -0.0804.", "metadata": {"var": -0.061913, "cvar": -0.080431, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160802_0044", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2016-08-02", "context_summary": "^VIX: 60-day return history, mean=-0.0053, std=0.0761.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0053, std=0.0761, min=-0.1825, max=0.2508\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-08-01] [\"Tech Turbocharged By Earnings, Chart Breakouts Last week\\u2019s killer earnings from Facebook, Alphabet and Apple paced an already energized tech sector.\", \"The drive behind Uber and Didi\\u2019s odd billions Ride-hailing services battle for China with cash that isn\\u2019t coming from venture capital Two ride-hailing giants are bringing in billions of dollars from untraditional sources, and the goals seem clear.\", \"The complicated web of companies that will determine the future of cars Race with tech giants to autonomous services pushes partnerships between carmakers and ride-hailing startups Auto makers, ride-hailing companies and tech companies are all part of an intricate web of partnerships and investments working toward an autonomous future.\", \"Sony: Could Have 54% Upside; Four Reasons to Be Bullish Japanese electronics giant Sony (6758.JP) is making investors believe in the stock again. Shares are up 2.2% this morning following the company\\u2019s stunning June quarter earnings beat last Friday. The stock has rebounded 12% this year after having plummeted 35% in the second half ofSony unveiled a JPY56 billion operating profit for the June quarter, which is well above the JPY3 billion operating loss analysts were expecting. Revenues of JPY1.6 trillion were down 11% year-on-year although the fall narrows to 3% after adjusting for the stronger yen.READ MORE>>\", \"Didi Chuxing reaches deal to buy Uber\\u2019s China operations Uber, investors in UberChina unit will own 20% of Didi; Chinese ride-hailing company will invest $1 billion in Uber Global ride-hailing giant Uber Technologies Inc. has given up its costly battle for China\\u2019s riders, swapping its local operations there for a minority stake in the country\\u2019s homegrown champion, Didi Chuxing Technology Co.\", \"Earnings signal a bear market: \\u2018Sell the house, sell the car, sell the kids\\u2019 Critical intelligence before the U.S. market opens Investors are certainly looking for something to light a fire under this market, considering the S&P 500 over the past 11 days has been stuck in the narrowest range in 45 years.\", \"Worldwide tablet shipments plunge 12% in second quarter: IDC\", \"VirnetX's stock plunges 46% premarket after disappointing court ruling on Apple patent suits\", \"Apple grows share of total tablet market despite sales decline Worldwide shipments of tablets fell 12% in the second quarter, according to a new report from IDC. Roughly 65% of tablets shipped this past quarter were run on Alphabet Inc.'s Android operating system, followed by Apple Inc.'s ioS, which captured 26% of the market. Apple's shipments fell by 9% year-over-year, but the launch of a new iPad Pro earlier this year helped to increase average selling prices for iPads, lifting Apple's total share of the market from 25% last year. Samsung Electronics Co.'s share decreased to 15.6% from 18.2% a year ago, as its shipments plunged 25% during the quarter. Lenovo, Huawei and Amazon.com Inc. rounded out the top fi\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": "-0.1121", "answer_numeric": -0.112088, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1121 (i.e., on a bad day with 5% probability, the loss exceeds 11.21%). CVaR(95%) = -0.1614.", "metadata": {"var": -0.112088, "cvar": -0.161442, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20171107_0047", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2017-11-07", "context_summary": "SHV: 60-day return history, mean=0.0000, std=0.0002.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0000, 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": "-0.0002", "answer_numeric": -0.000186, "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%) = -0.0003.", "metadata": {"var": -0.000186, "cvar": -0.000272, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20211130_0050", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2021-11-30", "context_summary": "ETH-USD: 60-day return history, mean=0.0072, std=0.0369.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0072, std=0.0369, min=-0.0749, max=0.1019\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-11-29] \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": "-0.0490", "answer_numeric": -0.049039, "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%) = -0.0663.", "metadata": {"var": -0.049039, "cvar": -0.066272, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20221006_0053", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2022-10-06", "context_summary": "^VIX: 60-day return history, mean=0.0008, std=0.0542.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0008, std=0.0542, min=-0.0979, max=0.1600\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-05] [\"After Hours Most Active for Oct 5, 2022 : DKNG, BTRS, X, AAPL, TQQQ, FDX, QQQ, SHY, STOR, C, TMX, T The NASDAQ 100 After Hours Indicator is down -5.07 to 11,568.11. The total After hours volume is currently 56,919,551 shares traded. The following are the most active stocks for the after hours session: DraftKings Inc. (DKNG) is +0.02 at $16.72, with 4,538,767 shares traded. As reported by Zacks, the current mean recommendation for DKNG is in the \\\"buy range\\\". BTRS Holdings Inc. (BTRS) is unchanged at $9.30, with 3,054,891 shares traded. As reported in the last short interest update the days to cover for BTRS is 7.073858; this calculation is based on the average trading volume of the stock. United States Steel Corporation (X) is -0.04 at $20.15, with 2,353,442 shares traded. X's current last sale is 79.02% of the target price of $25.5. Apple Inc. (AAPL) is -0.03 at $146.37, with 1,812,454 shares traded. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". ProShares UltraPro QQQ (TQQQ) is -0.02 at $22.56, with 1,517,812 shares traded. This represents a 17.01% increase from its 52 Week Low. FedEx Corporation (FDX) is +0.01 at $156.88, with 1,504,179 shares traded. FDX's current last sale is 78.83% of the target price of $199. Invesco QQQ Trust, Series 1 (QQQ) is +0.09 at $282.07, with 1,464,731 shares traded. This represents a 5.6% increase from its 52 Week Low. iShares 1-3 Year Treasury Bond ETF (SHY) is +0.03 at $81.26, with 1,197,338 shares traded. This represents a .32% increase from its 52 Week Low. STORE Capital Corporation (STOR) is +0.05 at $31.48, with 1,160,148 shares traded. STOR's current last sale is 97.61% of the target price of $32.25. Citigroup Inc. (C) is unchanged at $43.84, with 1,073,662 shares traded. C's current last sale is 73.07% of the target price of $60. Terminix Global Holdings, Inc. (TMX) is -0.05 at $40.34, with 986,921 shares traded. TMX's current last sale is 91.68% of the target price of $44. AT&T Inc. (T) is +0.03 at $15.96, with 892,397 shares traded. T's current last sale is 71.73% of the target price of $22.25. 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 slides as Fed's hawkish talk snuffs two-day rally By Herbert Lash, Ankika Biswas and Bansari Mayur Kamdar Oct 5 (Reuters) - Wall Street stocks slid on Wednesday, ending the biggest two-day rally since 2020, after data showed U.S. labor demand remained strong and as Federal Reserve officials stuck to their hawkish message that interest rates will stay higher for longer. U.S. private employers stepped up hiring in September, the ADP National Employment report on Wednesday showed, suggesting rising rates and tighter financial conditions have yet to curb labor demand as the Fed battles high inflation. The Institute for Supply Management's services industry employment gauge shot up in another sign labor remains strong as t\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": "-0.0858", "answer_numeric": -0.085802, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0858 (i.e., on a bad day with 5% probability, the loss exceeds 8.58%). CVaR(95%) = -0.0908.", "metadata": {"var": -0.085802, "cvar": -0.090793, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210503_0056", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2021-05-03", "context_summary": "SHV: 60-day return history, mean=0.0000, std=0.0001.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0000, std=0.0001, min=-0.0001, max=0.0002\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": "-0.0001", "answer_numeric": -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%) = -0.0001.", "metadata": {"var": -9e-05, "cvar": -9e-05, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181008_0061", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2018-10-08", "context_summary": "BNB-USD: 60-day return history, mean=-0.0015, std=0.0423.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0015, std=0.0423, min=-0.1289, max=0.1087\nMarket regime: sideways\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": "-0.0795", "answer_numeric": -0.079474, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0795 (i.e., on a bad day with 5% probability, the loss exceeds 7.95%). CVaR(95%) = -0.1098.", "metadata": {"var": -0.079474, "cvar": -0.109765, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20211029_0064", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2021-10-29", "context_summary": "FXI: 60-day return history, mean=-0.0001, std=0.0159.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0001, std=0.0159, min=-0.0438, max=0.0400\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-28] [\"The Morning After: Android 12L is Google's latest tablet effort Today\\u2019s headlines: Google gives Android on tablets another shot with Android 12L, Intel's hybrid 12th-gen chips are a major strike against AMD and iOS 15\\u2019s SharePlay is finally here.\", \"Fleksy raises Series A to expand its keyboard SDK biz after 10x growth Barcelona-based mobile keyboard software maker, Fleksy, has bagged a $1.6 million Series A to cement a pivot to b2b for its white-label SDK for Android and iOS. The AI keyboard maker has been a long time player in the third party smartphone keyboard space, initially developing a productivity-focused keyboard called ThingThing -- before acquiring the assets of better known US-based custom keyboard Fleksy (which had gone into stasis after its dev team got acquired by Pinterest) and making developing Fleksy the full focus. Tech giants like Apple and Google also throw their weight around in peculiar ways.\", \"Stock market news live updates: Stock futures as investors eye weaker-than-expected Q3 GDP, drop in jobless claims Stock futures rose Thursday morning, with the S&P 500 and Dow looking to resume advances after a pause on Wednesday. Traders looked ahead to more key earnings and economic data reports.\", \"Apple is the first public partner to join sustainable chip initiative With the Sustainable Semiconductor Technologies and Systems program, Imec wants to help chipmakers reduce their carbon footprint.\", \"Apple TV+ is coming to Comcast devices The Apple TV app will be available on Comcast devices in the months ahead, including its X1 boxes and XClass TVs.\", \"Apple's App Privacy Report launches into beta to show you what your apps are up to Apple has now launched a beta version of its \\\"App Privacy Report,\\\" a new feature that aims to provide iOS users with details about how often their everyday apps are requesting access to sensitive information, and where that information is being shared. The feature was first introduced at Apple's Worldwide Developer Conference in June, amid other privacy-focused improvements, including tools to block tracking pixels in emails, a private VPN, and more. Apple explained at the time the new report would include details about an app's access to user data and sensors, including the user's location, photos, contacts, and more, as well as a list of domains that the app contacts.\", \"Affirm founder Max Levchin on American Airlines deal, crypto Yahoo Finance Live chats with Affirm founder and CEO Max Levchin about his new deal with American Airlines and the outlook for crypto.\", \"Apple to report earnings amid chip shortage and supply crunch Apple will report its Q4 earnings after the bell on Thursday, with analysts looking to the potential impact of the chip shortage.\", \"Mark Zuckerberg takes thinly veiled shots at Apple for 'stifling innovation' via its platform policies Facebook (aka \\\"Meta\\\") CEO Mark Zuckerberg today took several thinly veiled shots at Apple and the overall app ecosystem when d\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": "-0.0230", "answer_numeric": -0.023035, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0230 (i.e., on a bad day with 5% probability, the loss exceeds 2.30%). CVaR(95%) = -0.0325.", "metadata": {"var": -0.023035, "cvar": -0.032483, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20211008_0067", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2021-10-08", "context_summary": "QUAL: 60-day return history, mean=-0.0001, std=0.0075.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=-0.0001, std=0.0075, min=-0.0216, max=0.0141\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-07] November 26th Options Now Available For Analog Devices (ADI) Investors in Analog Devices Inc (Symbol: ADI) saw new options become available today, for the November 26th expiration. At Stock Options Channel, our YieldBoost formula has looked up and down the ADI options chain for the new November 26th contracts and identified one put and one call contract of particular interest. The put contract at the $165.00 strike price has a current bid of $4.80. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $165.00, but will also collect the premium, putting the cost basis of the shares at $160.20 (before broker commissions). To an investor already interested in purchasing shares of ADI, that could represent an attractive alternative to paying $168.30/share today. Because the $165.00 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 100%. 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 2.91% return on the cash commitment, or 21.22% annualized \u2014 at Stock Options Channel we call this the YieldBoost. Below is a chart showing the trailing twelve month trading history for Analog Devices Inc, and highlighting in green where the $165.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $170.00 strike price has a current bid of $4.60. If an investor was to purchase shares of ADI stock at the current price level of $168.30/share, and then sell-to-open that call contract as a \"covered call,\" they are committing to sell the stock at $170.00. Considering the call seller will also collect the premium, that would drive a total return (excluding dividends, if any) of 3.74% if the stock gets called away at the November 26th expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if ADI shares really soar, which is why looking at the trailing twelve month trading history for Analog Devices Inc, as well as studying the business fundamentals becomes important. Below is a chart showing ADI's trailing twelve month trading history, with the $170.00 strike highlighted in red: Considering the fact that the $170.00 strike represents an approximate 1% premium 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 covered call contract would expire worthless, in which case the investor would keep both their shares of stock and the premium collected. The current\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": "-0.0130", "answer_numeric": -0.012983, "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%) = -0.0181.", "metadata": {"var": -0.012983, "cvar": -0.018082, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160804_0070", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2016-08-04", "context_summary": "PDBC: 60-day return history, mean=0.0006, std=0.0117.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=0.0006, std=0.0117, min=-0.0300, max=0.0243\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": "-0.0171", "answer_numeric": -0.017139, "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%) = -0.0265.", "metadata": {"var": -0.017139, "cvar": -0.026521, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220915_0074", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2022-09-15", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0005, std=0.0510.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0510, min=-0.1211, max=0.1691\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-14] \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": "-0.0832", "answer_numeric": -0.083209, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0832 (i.e., on a bad day with 5% probability, the loss exceeds 8.32%). CVaR(95%) = -0.1110.", "metadata": {"var": -0.083209, "cvar": -0.111044, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20200106_0077", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2020-01-06", "context_summary": "LQD: 60-day return history, mean=0.0002, std=0.0031.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0002, std=0.0031, min=-0.0078, max=0.0077\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": "-0.0048", "answer_numeric": -0.004759, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0048 (i.e., on a bad day with 5% probability, the loss exceeds 0.48%). CVaR(95%) = -0.0065.", "metadata": {"var": -0.004759, "cvar": -0.006478, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20161101_0080", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2016-11-01", "context_summary": "VLUE: 60-day return history, mean=0.0001, std=0.0065.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0001, std=0.0065, min=-0.0228, max=0.0152\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-10-31] [\"Music industry still plagued by pirated CDs Even in the digital era there are plenty of music fans who still buy old-fashioned compact discs for more than $10 a pop. But the money that shoppers have been spending on CDs lately hasn't necessarily been going to the artists and record labels who created the music.\", \"Apple hikes U.K. prices 20% \\u2014 blame Brexit Consumer confidence in the U.K. slides in October Apple becomes the latest corporate giant to raise prices in the U.K. to address the pound plunge and the moves are starting to squeeze British households.\", \"Apple\\u2019s underwhelming Mac event was lacking in innovation Opinion: Incremental improvements and annoying changes Apple Inc. hosted one of its most boring product launch events in recent years, one that is not likely to give investors confidence that innovation is alive and well at Apple\", \"Apple demolished by Microsoft at their respective PC events Microsoft hailed as the winner over Apple following back-to-back events Apple\\u2019s PC event was underwhelming compared with Microsoft\\u2019s, and many designers are for the first time turning to Windows over iOS.\", \"\\u2018Game changer\\u2019 could derail a traditionally great stretch for stocks Critical information ahead of the U.S. market\\u2019s open Thanks to the FBI\\u2019s fresh probe into Hillary\\u2019s emails, it looks like that volatility traders have been missing is back, and there\\u2019s nothing to suggest we won\\u2019t see more of the same as we careen toward Election Day\", \"Nomura Ups Qualcomm To Buy, Praises NXP Semi Deal Qualcomm (QCOM) is rising Monday, after Nomura analyst Romit Shah gave the NXP Semi (NXPI) deal his blessing and upgraded the stockShah raised his rating on the stock from Neutral to Buy and boosted his price target from $55 to $80, writing that NXP is a good business that will add \\u201ca ton\\u201d of scale for Qualcomm, expanding its total addressable market and creating new opportunities for its Snapdragon suite of chips.\", \"Four Key Takeaways From Apple\\u2019s 10K RBC Capital Markets\\u2019 Amit Daryanani reviewed Apple\\u2019s (AAPL) recently released 10K filing, and reiterated an Outperform rating and $125 price target on the stock Monday.He writes that there are a number of key findings from the stock, including the fact that initial fiscal 2017 capex spending is forecast up 26% year over year and total manufacturing and purchase commitments are up 3% year over year. The company has already spent some $133 billion of its $175 billion share repurchase authorization as well.\", \"Is buying a pair of Ivanka Trump shoes a political endorsement? A new survey found more than half of millennial women would still buy her shoes A new survey found more than half of millennial women would still buy shoes from the daughter of current Republican presidential candidate.\", \"Has Apple become a value play? In the wake of its earnings report, the stock may be flashing a buy signal.\", \"Could Apple Buy Time Warner? Would \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": "-0.0116", "answer_numeric": -0.011586, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0116 (i.e., on a bad day with 5% probability, the loss exceeds 1.16%). CVaR(95%) = -0.0159.", "metadata": {"var": -0.011586, "cvar": -0.01589, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190619_0083", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2019-06-19", "context_summary": "XLV: 60-day return history, mean=0.0003, std=0.0086.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0003, std=0.0086, min=-0.0292, max=0.0164\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-06-18] [\"Earnings Scheduled For June 18, 2019\", \"7 Stocks To Watch For June 18, 2019\", \"Adobe Systems Q2 Earnings Preview\", \"Tuesday's Market Minute: What To Watch For Today, 6/18\", \"Adobe To Report Q2 Earnings After The Closing Bell, Co. Historically Issues Its Report Between 4:05 And 4:10 p.m. ET; Watch For Sympathy Movement In Co.'s Peer Companies In The Software Space Following Earnings\", \"Adobe Q2 Adj. EPS $1.83 Beats $1.78 Estimate, Sales $2.74B Beat $2.7B Estimate\", \"Adobe Sees Q3 Adj. EPS ~$1.95 vs $2.05 Est., Sales ~$2.80B vs $2.83B Est.\", \"Adobe shares are trading higher after the company reported better-than-expected Q2 EPS and sales results.\", \"Adobe Shares Trade Higher After Record Q2 Sales\", \"Adobe Shares Trade Higher After Record Q2 Sales\", \"Adobe shares are trading higher after the company reported better-than-expected Q2 EPS and sales results.\", \"Adobe Sees Q3 Adj. EPS ~$1.95 vs $2.05 Est., Sales ~$2.80B vs $2.83B Est.\", \"Adobe Q2 Adj. EPS $1.83 Beats $1.78 Estimate, Sales $2.74B Beat $2.7B Estimate\", \"Adobe To Report Q2 Earnings After The Closing Bell, Co. Historically Issues Its Report Between 4:05 And 4:10 p.m. ET; Watch For Sympathy Movement In Co.'s Peer Companies In The Software Space Following Earnings\", \"Tuesday's Market Minute: What To Watch For Today, 6/18\", \"Adobe Systems Q2 Earnings Preview\", \"7 Stocks To Watch For June 18, 2019\", \"Earnings Scheduled For June 18, 2019\", \"After Hours: Adobe Beats on Cloud Performance, CBS Reportedly Making a New Play for Viacom We're seeing plenty of trading action across various sectors in the after market this evening. One particularly hot stock is IT sector mainstay Adobe (NASDAQ: ADBE), which just released its latest set of quarterly figures. In the media sphere, it looks as if CBS (NYSE: CBS) is about to open its wallet for a big buy... although this is hardly the first episode in that particular soap opera. Image source: Adobe. Adobe's awesome quarter Adobe is one of the most actively traded issues in the post-market space tonight, and it's no wonder -- it released Q2 of fiscal 2019 figures after market close that were not only above expectations, they set new records. For its Q2, the company drew revenue of $2.74 billion. This was 25% higher on a year-over-year basis, and set a new record for Adobe. Net income came in at just over $900 million ($1.83 per share), against $825 million ($1.66) in the same period a year ago. On average, analysts had been projecting $2.70 billion on the top line and per-share earnings of $1.78. Adobe has enjoyed success with its shift to a cloud-based subscription model, as opposed to the classical method of charging high \\\"one and done\\\" prices for boxed software. The company believes it can continue to grow through a combination of price raises and the addition of new customers. Adobe proffered guidance for Q3. It believes it will post revenue of around $2.8 billion for the quarter and EPS of $1.95. These numbers, alas, are a bit below the analyst consens\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": "-0.0190", "answer_numeric": -0.018983, "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%) = -0.0231.", "metadata": {"var": -0.018983, "cvar": -0.0231, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20151223_0086", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2015-12-23", "context_summary": "ACWI: 60-day return history, mean=0.0011, std=0.0092.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0011, std=0.0092, min=-0.0195, max=0.0208\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-12-22] [\"7 Stock Picks From the Top Tech Fund Since 2001 Kyle Weaver\\u2019s Fidelity IT Services fund is No. 1 tech portfolio since dot-com crash, without owning FANGs.\", \"Apple and Tesla could blow away a boring stock market with 20% gains Two of Wall Street\\u2019s biggest stocks may be your best way forward in beating the S&P 500 next year, says this analyst.\", \"Apple: Cowen Sees Street Too Bearish, But Not Ready to Buy the Stock The Street may finally be too bearish about Apple's (AAPL) iPhone prospects, writes Cowen & Co.\\u2019s Timothy Arcuri this morning, while reiterating a Market Perform rating on shares of Apple and cutting his price target to $130 from $135.Arcuri, you\\u2019ll recall, cut the stock from Outperform back in July, writing that supply-chain data was suggesting to him \\u201cbuilds are tracking down cycle/cycle for the first time.\\\"Today he writes, \\\"At the end of the day, we think near-term investor expectations around the Q may finally be too bearish, creating some potential to be tactical - if only slightly - in the near-term,\\u201d writes Arcuri, reflecting on the spate of estimate cuts for Apple in recent weeks.Read further...\", \"Still a F.A.N.G. Year in \\u201916, Says Morgan Stanley; Maybe Qualcomm, Apple Is there anything to own in 2016 besides FANG \\u2014 Facebook (FB), Amazon.com (AMZN), Netflix (NFLX), and Alphabet/Google (GOOGL)?That\\u2019s one question tackled today by Morgan Stanley\\u2019s Adam Parker in a think piece about what to do after the first Fed hike in years, last week.Parker notes investors are obsessed with the FANG question: \\u201cIn nearly every investor meeting we have been in over the past few weeks, the issue of breadth has surfaced. Facebook, Amazon, Netflix, and GOOGL, a.k.a. F.A.N.G., have performed incredibly well, but market breadth has been pretty narrow.\\\"Parker goes on to rephrase this: \\\"Will growth and momentum keep working to predict things at the stock level, or will value start working in 2016?\\\"His view is \\\"growth will probably still work. Why? Our house view is that we are in a world described by slow growth, slow reflation, and slow retrenchment from the Fed. Hence, it is likely we remain in a backdrop where stocks that can deliver growth maintain or even increase their premium valuations.\\\"\", \"Kim Kardashian\\u2019s \\u2018Kimoji\\u2019 app already No. 1 on its first day in the App Store \\u2018Kimoji\\u2019 is already the highest grossing app in Apple\\u2019s iOS entertainment category Kim Kardashian\\u2019s \\u2018Kimoji\\u2019 app launched Monday and is already the highest grossing entertainment app on Apple\\u2019s App Store.\", \"Apple changes bylaws to let certain stockholders nominate directors\", \"Apple reverses course, will let investors nominate directors Apple Inc. said in a federal filing Tuesday that it will allow certain stockholders to nominate directors for its board, after arguing against a similar proposal for proxy access at its last annual meeting. Apple said that investors who \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": "-0.0123", "answer_numeric": -0.012291, "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%) = -0.0159.", "metadata": {"var": -0.012291, "cvar": -0.015898, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190729_0089", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2019-07-29", "context_summary": "VTI: 60-day return history, mean=0.0006, std=0.0078.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0006, std=0.0078, min=-0.0256, max=0.0222\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-26] [\"SoftBank launches another tech megafund, backed by Apple, Microsoft Second Vision Fund, with about $108 billion secured, will invest in AI SoftBank Group Corp. said it would start a second technology megafund and has secured $108 billion in commitments from investors including Apple Inc., Japanese banks, Taiwanese investors and Kazakhstan\\u2019s sovereign-wealth fund.\", \"SoftBank Unveils Plans For $108 Billion Vision Fund 2 The Japanese holding company said investors in the new fund include Apple, Microsoft, Foxconn, and others.\", \"Asian markets pull back as Japan-South Korea trade tensions escalate Japan reportedly will diminish South Korea\\u2019s trade status Asian shares were lower Friday as investors continued to watch the brewing trade conflict between China and the U.S., and any signs of what\\u2019s in store from central banks.\", \"Tesla\\u2019s key executive departures, in one handy list News that Tesla\\u2019s Chief Technology Officer J.B. Straubel is stepping down from that role is just the latest move in a long list The departure of Tesla Inc.\\u2019s J.B. Straubel is a song Tesla has heard before \\u2014 numerous times.\", \"Even Intel doesn\\u2019t seem to know what\\u2019s going to happen with Intel Amid sale of modem-chip business to Apple and a forecast flip-flop, Intel seems to be unsure of path for it, or the chip industry, in second half In the semiconductor industry, \\u201cmixed signal\\u201d usually refers to chips that combine digital and analog circuitry. When referring to Intel Corp. right now, though, the standard definition of that phrase is more apt.\", \"Alphabet earnings show Google revenue growth rebounding, stock pops higher Profit and revenue beat expectations amid reported antitrust scrutiny Alphabet Inc. shares jumped 7% in after-hours trading Thursday after the online giant announced better-than-expected financial results.\", \"Facebook tops Amazon and Google in second-quarter lobbying spending Partisan split means \\u2018we see little room for any legislation to actually materialize in the near term,\\u2019 analysts say Facebook spent $4.1 million on lobbying Washington in the second quarter, topping the outlays by other so-called FAANG companies and keeping the tech giant on pace for another record year of spending to influence lawmakers and regulators.\", \"Google Needs to Buy Back Even More Stock Wall Street cheered the latest numbers, but Alphabet\\u2019s repurchase program barely exceed its stock-based compensation, which totaled $5.5 billion in the first half of 2019.\", \"Are you a \\u2018zombie eater\\u2019? It could be bad for your health Distracted diners who stare at screens tend to eat more calories and choose fattier foods Distracted diners who stare at screens tend to eat more calories and choose fattier foods.\", \"Intel\\u2019s earnings beat gets fairly cold reception from analysts Surprise rise in PC sales overshadowed by new chip rollout pace, AMD challenges Intel Corp. shares slip Friday following a big earnings beat\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": "-0.0129", "answer_numeric": -0.012851, "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%) = -0.0189.", "metadata": {"var": -0.012851, "cvar": -0.018854, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160303_0092", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2016-03-03", "context_summary": "SCHP: 60-day return history, mean=0.0004, std=0.0028.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0004, std=0.0028, min=-0.0071, max=0.0048\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": "-0.0042", "answer_numeric": -0.004168, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0042 (i.e., on a bad day with 5% probability, the loss exceeds 0.42%). CVaR(95%) = -0.0059.", "metadata": {"var": -0.004168, "cvar": -0.0059, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190620_0095", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-06-20", "context_summary": "BTC-USD: 60-day return history, mean=0.0095, std=0.0378.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0095, std=0.0378, min=-0.0686, max=0.1157\nMarket regime: sideways\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": "-0.0473", "answer_numeric": -0.047269, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0473 (i.e., on a bad day with 5% probability, the loss exceeds 4.73%). CVaR(95%) = -0.0636.", "metadata": {"var": -0.047269, "cvar": -0.063582, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210913_0098", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2021-09-13", "context_summary": "INDS: 60-day return history, mean=0.0009, std=0.0095.", "question": "Asset: INDS\nDaily returns (past 60 days): mean=0.0009, std=0.0095, min=-0.0240, max=0.0233\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for INDS. Express as a decimal (e.g., -0.02).", "answer": "-0.0115", "answer_numeric": -0.011463, "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%) = -0.0203.", "metadata": {"var": -0.011463, "cvar": -0.020325, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180406_0101", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2018-04-06", "context_summary": "ETH-USD: 60-day return history, mean=-0.0113, std=0.0548.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0113, std=0.0548, min=-0.1593, max=0.1364\nMarket regime: sideways\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": "-0.0884", "answer_numeric": -0.088372, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0884 (i.e., on a bad day with 5% probability, the loss exceeds 8.84%). CVaR(95%) = -0.1351.", "metadata": {"var": -0.088372, "cvar": -0.135088, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160111_0104", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2016-01-11", "context_summary": "BTC-USD: 60-day return history, mean=0.0066, std=0.0308.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0066, std=0.0308, min=-0.0842, max=0.0878\nMarket regime: sideways\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": "-0.0383", "answer_numeric": -0.038321, "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%) = -0.0553.", "metadata": {"var": -0.038321, "cvar": -0.055338, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180703_0107", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2018-07-03", "context_summary": "QUAL: 60-day return history, mean=0.0005, std=0.0065.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0005, std=0.0065, min=-0.0128, max=0.0169\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-02] [\"Why there may never be a Netflix of videogames Years into parallel efforts to deliver videogame streams from the cloud, latency \\u2014 and doubts \\u2014 persist Plenty of companies, from multibillion-dollar tech titans to startups, are trying to develop a streaming service for videogames that could do to consoles and individual videogame sales what Netflix did to DVDs and the cable bundle. But the issues that stand in the way could keep it from ever happening as imagined.\", \"Tech Today: Can Tesla Keep It Up? Dell Going Public, Facebook\\u2019s Instagram Numbers Tesla says it hit its goal of 5,000 Model 3s per week although some wonder if it's sustainable, Dell is going public again via a stock swap and CEO Michael Dell says the company will exploit a broad IT infrastructure spending trend, Lumentum is set to ride the expansion of \\\"augmented reality\\\" in Apple iPhones and other devices, and Facebook can see a big boost in revenue as its Instagram unit closes the pricing gap with other properties according to Ken Sena of Wells Fargo.\", \"Nasdaq supported by rebound in tech stocks; Apple up 0.8%\", \"NBA Veteran Jason Kidd Takes a Swing at Tech Investing Basketball legend Jason Kidd, like a growing number of other retired and current professional athletes, has invested in a tech startup. The appeal of making a bet on tech is proving to be irresistible. He cites the two-time defending NBA champion Golden State Warriors, whose players are dabbling in tech startups while lending star brand recognition to those companies.\", \"Taiwan Semi to Ride Wave of Custom AI Chips, Says Susquehanna Taiwan Semi has been the contract manufacturer to Apple and Qualcomm and Nvidia and others for a long time, but it has a new opportunity to make revenue off of the emerging industry of artificial intelligence chips, says Susquehanna's Mehdi Hosseini.\", \"U.S. stocks end higher as tech shares stage late-session rally U.S. stocks ended higher on Monday, reversing an early decline as a rebound in technology shares helped to offset ongoing uncertainty surrounding trade policy. The Dow Jones Industrial Average rose 0.1%. The S&P 500 ended 0.3% higher. The Nasdaq Composite Index gained 0.8%. Major indexes had opened lower in a broad decline, but equities improved throughout the session, and seven of the 11 primary S&P 500 sectors ended in positive territory. Leading the move higher was technology stocks, which rose 1% as the top-performing industry group of the day. Among the notable gainers, Apple Inc. added 1.1% while Microsoft Corp. was up 1.4%. Nvidia Corp. popped 2.3%.\", \"Tech sector contributed all of the stock market gains so far in 2018 Amazon.com accounted for more than a third of S&P 500 gains The equity markets\\u2019 story of 2018, much like last year, was and still is the one of FAANGs\\u2014high-flying large technology companies\", \"Why Apple stock is still a buy \\u2014 even at $200 a share Three key valuation measures prove the stock\\u2019s long-term value Three key v\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": "-0.0100", "answer_numeric": -0.009982, "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%) = -0.0120.", "metadata": {"var": -0.009982, "cvar": -0.012038, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150714_0110", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2015-07-14", "context_summary": "PALL: 60-day return history, mean=-0.0027, std=0.0133.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=-0.0027, std=0.0133, min=-0.0436, max=0.0355\nMarket regime: sideways\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": "-0.0217", "answer_numeric": -0.021668, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0217 (i.e., on a bad day with 5% probability, the loss exceeds 2.17%). CVaR(95%) = -0.0311.", "metadata": {"var": -0.021668, "cvar": -0.031124, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180402_0113", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-04-02", "context_summary": "XRP-USD: 60-day return history, mean=-0.0120, std=0.0710.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0120, std=0.0710, min=-0.1719, max=0.1852\nMarket regime: sideways\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": "-0.1151", "answer_numeric": -0.115146, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1151 (i.e., on a bad day with 5% probability, the loss exceeds 11.51%). CVaR(95%) = -0.1470.", "metadata": {"var": -0.115146, "cvar": -0.147028, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180607_0116", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2018-06-07", "context_summary": "QQQ: 60-day return history, mean=0.0002, std=0.0135.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0002, std=0.0135, min=-0.0329, max=0.0340\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-06-06] The 3 Rules of a Bull Market When I talk to investors about the stock market, I still hear all the reasons that it's time to be cautious and the end is near. But all my experience tells me differently. And while I have often thought this year that the market must be in its 6th or 7th inning, I have few fundamental reasons to believe that it couldn't keep making new highs for another two to three years. So as I look back at the portfolios and the body of content I've created over the years to help investors profit, I wondered if I could simplify the message even further. I often prefer not to over-simplify, leaning instead toward parsing out the complexities and nuances of economic matters. But my work does have the same persistent themes. And so I realized, I could very easily crystallize them into 3 rules, and just ten words total. In the video that accompanies this article, I go back over some of those messages from the past nine years of this bull market. Then I summarize them all with my \"3 Rules.\" My hope is that this video becomes teaching tool for investors age 8 to 88 because its lessons will certainly stand the test of time in the next bull market, and the one after that too. In the video, I also promise some useful links... For a review of my latest fundamental update on BABA in case you missed it, here was my May ZU Strategy Session presentation. It's the last clip at minute 44:20... May ZUSS: Top Stock Pick BABA at 44:20 Even then after awesome earnings and growth guidance, I reminded investors \"If you can get in under $200, do it!\" The Moral of the Bull's Story Got a minute? I can think of no better way to sum up the moral of this story than with a 1-minute video I recorded last year over at the CBOE. TV host Angela Miles asked me for my favorite \"trader's tip\" and I knew instantly that if I only had a minute to share with thousands of investors, I would choose this one core idea... Follow the Smart Money Finally, here was the message I offered on Tracey Ryniec's MarketEdge podcast back in January... Cooker's Melt-Up Recipe Three ingredients for a \"melt-up recipe\" that investors can profit from. 1. Multiple Expansion Is Under Control: We may be in the 6th inning of this bull market, but multiple expansion isn't yet as high as it was at the peak of other bull rallies like 1999-2000. There could still be more upside to go. 2. Competition: There's less stock and more investors. Additionally, Wall Street, unlike most retail investors, has to buy, but doesn't have to sell. 3. No global macro worries: Whatever happened to the Eurozone crisis or China having a hard landing? For the first time in a decade, the global economy is in sync and growing at the same time with virtually no economic crises looming. (end of excerpt from MarketEdge podcast) Granted, the market headed into a 10% correction right after that. But I also warned Zacks Ultimate members about that 2 weeks prior. Despite my long-term bullishness, I'm always ready with \"dry pow\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": "-0.0254", "answer_numeric": -0.02541, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0254 (i.e., on a bad day with 5% probability, the loss exceeds 2.54%). CVaR(95%) = -0.0296.", "metadata": {"var": -0.02541, "cvar": -0.029625, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20171218_0123", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2017-12-18", "context_summary": "PDBC: 60-day return history, mean=0.0002, std=0.0070.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=0.0002, std=0.0070, min=-0.0160, max=0.0181\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": "-0.0124", "answer_numeric": -0.012386, "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%) = -0.0148.", "metadata": {"var": -0.012386, "cvar": -0.014848, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20191126_0126", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2019-11-26", "context_summary": "XRP-USD: 60-day return history, mean=-0.0014, std=0.0296.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0014, std=0.0296, min=-0.0599, max=0.0706\nMarket regime: sideways\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": "-0.0530", "answer_numeric": -0.053035, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0530 (i.e., on a bad day with 5% probability, the loss exceeds 5.30%). CVaR(95%) = -0.0573.", "metadata": {"var": -0.053035, "cvar": -0.057294, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160107_0129", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2016-01-07", "context_summary": "MTUM: 60-day return history, mean=0.0003, std=0.0095.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0003, std=0.0095, min=-0.0204, max=0.0217\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-06] [\"Apple iPhone Production Cuts? Suppliers Largan, Catcher Miss December Sales\", \"Bad day for Fitbit and its jittery investors Opinion: Lower price should expand reach, but margins may suffer Fitbit Inc. investors headed for the exits on Tuesday after the company unveiled the Blaze, a wearable device with many smartwatch features that fueled immediate comparisons with the Apple Watch and a looming battle with the consumer electronics juggernaut.\", \"AAC Tech Tumbles On Apple iPhone Production Cut: Not A Reason To Sell, Says Jefferies Along with other Apple (AAPL) iPhone suppliers, AAC Technologies (2018.Hong Kong) slipped 5.2% in Hong Kong after a Nikkei report that Apple would cut its iPhone production by a third in the March quarter.Jefferies' Ken Hui is pounding the table this morning saying iPhone's weakness is an opportunity to buy - not a reason to sell, because Apple is not AAC's only customers. Hui wrote:READ MORE.\", \"Samsung\\u2019s new smartwatch to be compatible with Apple\\u2019s iOS Gear 2 announcement may signal more inclusive approach Samsung Electronics Co. said it would make its latest smartwatch compatible with rival Apple Inc.\\u2019s operating system, marking the latest wrinkle in a complex relationship between the world\\u2019s two biggest smartphone makers.\", \"Apple scaling back iPhone production Reduction in orders likely reflects lower-than-expected sales Apple Inc. is scaling back orders for its iPhones, sending ripples throughout the multibillion-dollar industry that supplies and builds the company\\u2019s phones.\", \"Fears About North Korea, Apple Are Overstated Several financial writers make a case for taking a chill pill about recent troubling news.\", \"Self-driving cars will kill the auto industry Europe has the most to lose if its companies can\\u2019t adapt to disruptive technology Self-driving cars will disrupt the auto industry, creating lots of new winners and losers. The biggest losers will be in Europe, says Matthew Lynn.\", \"Asian markets mostly slip as North Korea bomb test sends shivers China shares bucks trend with 2.3% rise The yen reaches a near-three-month high and most shares in Asia trade lower, though Shanghai bucks the trend, on news of a possible nuclear test in North Korea and lingering worries about China.\", \"Apple shares down 2.2% premarket\", \"Apple reports biggest holiday season for app store Apple Inc. reported record-breaking sales for the holiday season, with customers spending more than $1.1 billion on apps and in-app purchases. This was the biggest holiday season for the App Store and Jan. 1, 2016 broke the store's single-day record with customers spending more than $144 million. The most popular purchase categories were gaming, social networking and entertainment, including apps such as Minecraft, Snapchat and Clash of Clans as well as Netflix. \\\"We are excited that our customers downloaded and enjoyed so many incredible apps for iPhone, iPad, Mac, Apple Watch and Apple TV, spending over $20 billion\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": -0.016472, "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%) = -0.0181.", "metadata": {"var": -0.016472, "cvar": -0.018077, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170317_0132", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2017-03-17", "context_summary": "XHB: 60-day return history, mean=0.0014, std=0.0089.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0014, std=0.0089, min=-0.0194, max=0.0294\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": "-0.0107", "answer_numeric": -0.010737, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0107 (i.e., on a bad day with 5% probability, the loss exceeds 1.07%). CVaR(95%) = -0.0144.", "metadata": {"var": -0.010737, "cvar": -0.014412, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20150205_0137", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2015-02-05", "context_summary": "ICSH: 31-day return history, mean=-0.0001, std=0.0010.", "question": "Asset: ICSH\nDaily returns (past 31 days): mean=-0.0001, std=0.0010, min=-0.0020, max=0.0028\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": "-0.0016", "answer_numeric": -0.001599, "explanation": "Historical simulation VaR at 95%: sort the 31 daily returns and take the 5th percentile. VaR(95%) = -0.0016 (i.e., on a bad day with 5% probability, the loss exceeds 0.16%). CVaR(95%) = -0.0017.", "metadata": {"var": -0.001599, "cvar": -0.001699, "confidence": 0.95, "n_returns": 31, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181121_0140", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2018-11-21", "context_summary": "TIP: 60-day return history, mean=-0.0001, std=0.0007.", "question": "Asset: TIP\nDaily returns (past 60 days): mean=-0.0001, std=0.0007, min=-0.0015, max=0.0022\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": "-0.0012", "answer_numeric": -0.001216, "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%) = -0.0014.", "metadata": {"var": -0.001216, "cvar": -0.001356, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20201021_0143", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2020-10-21", "context_summary": "SOL-USD: 60-day return history, mean=-0.0052, std=0.0889.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0052, std=0.0889, min=-0.2453, max=0.2870\nMarket regime: sideways\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": "-0.1532", "answer_numeric": -0.153189, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1532 (i.e., on a bad day with 5% probability, the loss exceeds 15.32%). CVaR(95%) = -0.1945.", "metadata": {"var": -0.153189, "cvar": -0.194454, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20211022_0148", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2021-10-22", "context_summary": "XLB: 60-day return history, mean=0.0005, std=0.0095.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0005, std=0.0095, min=-0.0208, max=0.0240\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-21] [\"Customer engagement platform Batch raises $23 million after years of bootstrapping If you\\u2019ve been working in the French tech ecosystem, you may remember a startup called AppGratis. From the team that brought you AppGratis, Batch is a customer engagement platform that has been operating under the radar for many years. It\\u2019s a customer engagement platform that competes with Braze as well as big enterprise solutions from Salesforce, Adobe, Oracle, IBM and Microsoft.\", \"Apple will require unvaccinated employees to test for COVID-19 daily Apple will require all unvaccinated corporate employees to be tested for COVID-19 every time they have to work in the office.\", \"The Morning After: Will Facebook change its name? Today\\u2019s headlines: Some Windows 11 users can start testing Android apps, Netflix CEO says he 'screwed up' on Dave Chappelle as employees walk out, \\u2018Cyberpunk 2077' PS5 and Xbox Series X/S upgrades delayed until 2022.\", \"Apple will require unvaccinated employees to test for COVID-19 daily Apple has yet to issue a mandate similar to Google's that would require all employees to be vaccinated, but it's tightening its COVID-19 protocols nonetheless. According to Bloomberg, the tech giant will start requiring all unvaccinated corporate employees to be tested for COVID-19 every time they have to work in the office instead of working from home. Back in September, Bloomberg reported that Apple asked employees to share their vaccination status voluntarily.\", \"Apple's AirTags are 10 percent off at Woot today Apple's AirTags are down to $26 each when you buy them from Woot today only.\", \"Meet the 2021 Women in Technology Hall of Fame Inductees Female Executives and Leaders to be Honored for Their Impact and Achievements Featured Image for WITI - Women in Technology International Featured Image for WITI - Women in Technology International LOS ANGELES, Oct. 21, 2021 (GLOBE NEWSWIRE) -- Women in Technology International (WITI), the leading organization for the advancement and inclusion of women in business and technology, today announced its eight inductees into the 2021 Women in Technology Hall of Fame. The honorees will be inducted dur\", \"Product Marketing Alliance: From $0 to $1M+ ARR in 12 months: product marketing is the world's fastest-growing job role The role of product marketing is on the rise. It's no longer seen as a nice-to-have, it's a company commodity for forward-thinking, fast-growing, market-dominating organizations worldwide.\", \"Google lowers Play Store fees to 15% on subscription apps, as low as 10% for media apps Google is lowering commissions on all subscription-based businesses on the Google Play Store, the company announced today. Previously, the company had followed Apple's move by reducing commissions from 30% to 15% on the first $1 million of developer earnings. Instead of charging them 30% in the first year, which lowers to 15% in year two and beyond, Google says developers will only be charged 15% from day o\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": "-0.0126", "answer_numeric": -0.012601, "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%) = -0.0186.", "metadata": {"var": -0.012601, "cvar": -0.018629, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180530_0151", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2018-05-30", "context_summary": "LQD: 60-day return history, mean=0.0002, std=0.0027.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0002, std=0.0027, min=-0.0076, max=0.0053\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": "-0.0038", "answer_numeric": -0.003794, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0038 (i.e., on a bad day with 5% probability, the loss exceeds 0.38%). CVaR(95%) = -0.0056.", "metadata": {"var": -0.003794, "cvar": -0.005581, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20201110_0154", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-11-10", "context_summary": "LINK-USD: 60-day return history, mean=0.0002, std=0.0563.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0563, min=-0.1212, max=0.1799\nMarket regime: sideways\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": "-0.0926", "answer_numeric": -0.092646, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0926 (i.e., on a bad day with 5% probability, the loss exceeds 9.26%). CVaR(95%) = -0.1062.", "metadata": {"var": -0.092646, "cvar": -0.106186, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20201229_0157", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2020-12-29", "context_summary": "MTUM: 60-day return history, mean=0.0011, std=0.0123.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0011, std=0.0123, min=-0.0341, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-12-28] [\"Stand By Chip Champ Advanced Micro Devices Even at Higher Price Points InvestorPlace - Stock Market News, Stock Advice & Trading Tips For investors in Advanced Micro Devices (NASDAQ:AMD), the temptation to take profits is understandable. Anyone who bought AMD stock early in 2020 can easily declare himself/herself a winner and cash out. AMD) logo outside of a corporate building\\\" width=\\\"300\\\" height=\\\"169\\\"> Source: Sundry Photography / Shutterstock.com After all, AMD is a stock that more than doubled from mid-March to December. Skeptics might wonder how much further AMD stock can possibly go after a run like that. As we\\u2019ll discover, the concerns over valuation are understandable. An argument can be made in favor of taking some chips off the table when it comes to AMD stock. On the other hand, it\\u2019s also possible to assess the company\\u2019s progress and choose to hold on to one\\u2019s AMD shares. Perhaps the bull run can continue into 2021. So, let\\u2019s home in on the AMD stock price and consider whether the stock\\u2019s valuation is a deal breaker. A Closer Look at AMD Stock At its lowest point in March of 2020, AMD stock bottomed out at $36.75. Even a tech stock like AMD wasn\\u2019t impervious to the Covid-19 crisis at that time. 7 Undervalued Stocks That Could Soar in 2021 Yet, by the middle of April, AMD stock had already returned to its pre-pandemic price. The swift recovery was likely due to the market\\u2019s belief that the technology sector could thrive during lockdowns. AMD stock took another big leg up during the summer of 2020. During that time, the stock quickly rocketed to the $85 level. Then the bulls took a much-needed breather for a couple of months. In December, the AMD stock bulls came back and began to push the share price beyond the $90 level. In fact, on Dec. 23, AMD shares hovered near $92 or $93. At that time, however, the trailing 12-month price-to-earnings ratio reached 125. Meanwhile, the trailing 12-month price-to-earnings ratio of rival Intel\\u2019s (NASDAQ:INTC) stock was around 9. Therefore, value-focused investors will need to be convinced that AMD stock is worth its price tag. Undeniable Revenue Growth If any AMD shareholders have been concerned about the stock\\u2019s valuation, a glance at the company\\u2019s fiscal stats should help to put them at ease. Suffice it to say that Advanced Micro Devices\\u2019 third quarter was an absolute blockbuster. Even the most optimistic commentators might not have expected the quarterly results that the company posted. Here are the bullet points for Advanced Micro Devices\\u2019 third quarter: $2.8 billion in revenues, up 56% year-over-year and 45% quarter-over-quarter Revenues from the computing and graphics segment totaled $1.67 billion, up 31% year-over-year and 22% quarter-over-quarter Net income was $390 million, a huge improvement over the $120 million posted a year ago and $157 million recorded in the prior quarter Diluted earnings per share came to 32 cents, \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": "-0.0235", "answer_numeric": -0.023456, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0235 (i.e., on a bad day with 5% probability, the loss exceeds 2.35%). CVaR(95%) = -0.0294.", "metadata": {"var": -0.023456, "cvar": -0.029428, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201117_0162", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2020-11-17", "context_summary": "USMV: 60-day return history, mean=0.0011, std=0.0103.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0011, std=0.0103, min=-0.0253, max=0.0190\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-11-16] [\"A Covid Vaccine Is Coming. Here\\u2019s What It Means for the Stock Market. After years of disappointment, a rotation into value-oriented investments from growth could gain traction. International stocks, small-caps, and gold could also climb.\", \"What GM Recall of the Bolt Electric Vehicle Means for the Stock The recall is tied to a battery charging issue. Recalls don\\u2019t usually hit auto maker shares, but this one is worth watching.\", \"Intel Can Shine Again Repeated manufacturing delays have dented Intel\\u2019s reputation. Why the stock is down but not out.\", \"Facebook Stock Will Continue to Benefit from Online Advertising\\u2019s Rebound The online advertising market appears on pace for continued acceleration through the fourth quarter, a J.P. Morgan analyst says.\", \"Dow, S&P 500 end at record highs Monday as stock market rallies amid further vaccine progress U.S. stocks book a round of fresh records Monday, as a rally fueled by optimism on the COVID-19 vaccine front overshadowed skyrocketing case numbers.\", \"Warren Buffett\\u2019s Berkshire Hathaway Confirms Apple Stock Sale, Buys of Pfizer, Merck Warren Buffett\\u2019s Berkshire Hathaway trimmed holdings in Apple, in line with our estimate. It also initiated positions in drug giants AbbVie, Pfizer, and Merck. Berkshire Hathaway also slashed its JPMorgan investment.\", \"Samsung's latest monitor is a smart TV with PC features It\\u2019s the brand\\u2019s first smart TV with built-in WiFi, Bluetooth and Wireless DeX capability.\", \"Ambu A/S: Reporting of transactions made by persons discharging managerial responsibilities Please see attached file. Attachment * 16_11_2020_Michael H\\u00f8jgaard II\", \"How FlyBy Auto Transport Rises to the Top of Its Competitive Industry LOS ANGELES, CA / ACCESSWIRE / November 16, 2020 / Amid the heavily competitive and saturated auto transport market, it all boils down to a company's reliability and performance, leading people to give their trust.\", \"Moderna reports its COVID-19 vaccine is 94.5% effective in first data from Phase 3 trial Following fast on the heels of Pfizer's announcement of its COVID-19 vaccine efficacy, Moderna is also sharing positive results from its Phase 3 trial on Monday. The biotech company says that its COVID-19 vaccine candidate has shown efficacy of 94.5% in its first interim data analysis, which covers 95 confirmed COVID cases among its study participants, of which 90 were given the placebo, and only 5 received Moderna's mRNA-based vaccine. Further, of 11 severe cases of COVID-19, none were found among those who received the actual vaccine candidate.\", \"The Morning After: Updating to macOS Big Sur is messing up some MacBook Pros Engadget's daily tech news bulletin.\", \"Techfugees non-profit brings on new CEO to engage tech industry with refugee issues Techfugees, the global non-profit which advocates the use of technology to aid refugees and displaced people, has appointed tech entrepreneur and Raj Burman as its new CEO. Burman succeeds Jo\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": "-0.0163", "answer_numeric": -0.016304, "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%) = -0.0231.", "metadata": {"var": -0.016304, "cvar": -0.023053, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150916_0165", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2015-09-16", "context_summary": "EEM: 60-day return history, mean=-0.0027, std=0.0163.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0027, std=0.0163, min=-0.0341, max=0.0317\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-09-15] [\"Chip Stocks Up Despite Falling Semiconductor Billings\", \"Chip Stocks Up Despite Falling Semiconductor Billings\", \"Is Apple, Inc.'s \\\"3D Touch\\\" Supplier a Buy? As expected, the headline selling feature in Apple 's new iPhone 6s and 6s Plus models will be 3D Touch, the rebranded technology that integrates pressure sensitivity into the display to unlock a whole new slew of interface interactions. Seeing as how investing in Apple component suppliers is a popular investing trend these days, investors can't help wondering if Analog Devices is worth looking at, since the smaller analog-chip maker is reportedly the exclusive supplier of the microcontroller that drives the 3D Touch display. Is Analog Devices a buy? The Street has been busy tackling this very question. Last month before earnings, BlueFin Research Partners estimated that overall Force/3D Touch revenues could add up to an additional $500 million in fiscal 2016. The firm notes that Analog Devices has had some trouble finding customers willing to pay for its superior performance, but Apple fits the bill quite nicely. Seeing as how the iPhone 6s and 6s Plus production ramp likely started a few months ago, it was no surprise when Analog then reported record revenues of $863 million in its fiscal third quarter. It was also pretty obvious where the strength was coming from as well. Source: SEC filings. In no uncertain terms, the consumer segment stole the show. Naturally, Analog Devices has to speak vaguely when referring to Apple on the conference all, but it's pretty clear who it is. Here's CFO David Zinsner: Not only were the quarter's results better than expected, but Analog Devices also issued upbeat guidance. In the coming quarter, revenue is expected in the range of $880 million to $940 million, which utterly crushed the consensus forecast of $876 million. There's more where that came from Following the strong results, SunTrust Robinson Humphrey boosted its rating on Analog Devices to \\\"buy\\\" while increasing its price target from $68 to $71. The firm believes that Apple Force/3D Touch will proliferate throughout Apple's lineup in the coming quarters, and Analog Devices will be a key beneficiary as the incremental revenue adds up. This is an entirely reasonable conjecture, since Apple tends to introduce innovative new technologies in one major product before bringing it to the rest of the product portfolio. Usually, Apple does this with the iPhone first, but this time around it introduced Force Touch first in Apple Watch and the new MacBooks before the iPhone (Analog Devices supplies the chips in both of these devices). That being said, I fully expect the iPad to get 3D Touch next, although it'll take more time to implement the technology on such large displays. RBC Capital also rates Analog Devices \\\"outperform\\\" with a $70 price target. It seems that the Street is mostly bullish on Analog Devices as Apple ramps up Force/3D Touch. Even though Apple is contributing heavily to the near-te\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": "-0.0314", "answer_numeric": -0.031405, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0314 (i.e., on a bad day with 5% probability, the loss exceeds 3.14%). CVaR(95%) = -0.0341.", "metadata": {"var": -0.031405, "cvar": -0.034114, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190312_0168", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2019-03-12", "context_summary": "FXI: 60-day return history, mean=0.0013, std=0.0123.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0013, std=0.0123, min=-0.0225, max=0.0333\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-03-11] [\"Apple\\u2019s iPhone Woes Could Hurt Supplier Credit Ratings S&P Ratings predicts that Apple\\u2019s iPhone revenue will drop by around 15% in fiscal 2019, and a continuing decline continues, it would hurt the creditworthiness of its suppliers.\", \"The folly of Elizabeth Warren\\u2019s wealth tax Most fortunes are the earned by entrepreneurs cashing in on their great ideas, not the idle rich of Democrats\\u2019 fantasies Democrats like Sanders and Warren want to tax the goose that lays the golden eggs.\", \"Apple Investors Are \\u2018Too Pessimistic\\u2019 About Its Hardware \\u2014 and Its Stock \\u2014 Analyst Says Bank of America Merrill Lynch upgraded the tech giant\\u2019s stock Monday.\", \"The Dow Bounces Back Because Stock Trading Isn\\u2019t Just About Boeing The Dow Jones Industrial Average moved into positive territory despite a loss for Boeing. The S&P 500 and Nasdaq Composite achieved larger gains.\", \"Trump Today: President reopens border-wall fight with new budget, endorses permanent daylight-saving time Trump tweets explanation of \\u2018Tim Apple\\u2019 President Donald Trump renewed a fight for border-wall funding as he released his 2020 budget on Monday, and endorsed making daylight-saving time permanent a day after most Americans set their clocks ahead an hour.\", \"Stocks snap 5-day losing streak as tech shares rally Boeing stock has worst day in nearly 5 months after Ethiopian Airlines crash U.S. stocks snap a five-day losing streak to close higher Monday as technology shares rallied, offsetting some of the gloom from Boeing Co.\\u2019s woes after the second deadly crash in about six months involving the company\\u2019s 737 Max 8 aircraft.\", \"The \\u2018smart money\\u2019 prefers Alibaba over Amazon, Intel over AMD, and Google over Apple The change came after popular tech stocks were sold short late last year The change came after popular tech stocks were sold short late last year.\", \"This is why Trump now says he called Apple CEO Tim Cook \\u2018Tim Apple\\u2019 Trump says he didn't slip up and was trying to \\u2018save time & words\\u2019 Trump says he didn't slip up and was trying to \\u2018save time & words.\\u2019\", \"Dow Gains 200 Points to Break Five-Day Losing Streak U.S. stocks reversed some of last week\\u2019s losses and closed in the solid black on Monday\", \"Apple Sets March 25 to Announce Its Next Big Thing The company\\u2019s annual spring product announcement is likely to reflect a shift to services with a new streaming TV offering and a revamped Apple News.\", \"Amazon\\u2019s Alexa has 80,000 Apps-and No Runaway Hit Deakin and his coworkers at the U.K.\\u2019s Musicplode Media Ltd. created a version of their music trivia game for Alexa, chasing the opportunity to hitch a ride on what they correctly predicted would be one of the hottest trends in consumer technology. Like many developers, they found working with voice\", \"Why people think their phones are listening to them A surprising number of people falsely think their smartphones, smart spe\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": "-0.0175", "answer_numeric": -0.017469, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0175 (i.e., on a bad day with 5% probability, the loss exceeds 1.75%). CVaR(95%) = -0.0204.", "metadata": {"var": -0.017469, "cvar": -0.020443, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190819_0175", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2019-08-19", "context_summary": "XRP-USD: 60-day return history, mean=-0.0064, std=0.0398.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0064, std=0.0398, min=-0.1256, max=0.0712\nMarket regime: sideways\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": "-0.0782", "answer_numeric": -0.078247, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0782 (i.e., on a bad day with 5% probability, the loss exceeds 7.82%). CVaR(95%) = -0.1099.", "metadata": {"var": -0.078247, "cvar": -0.109912, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181004_0178", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2018-10-04", "context_summary": "IVV: 60-day return history, mean=0.0008, std=0.0043.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0008, std=0.0043, min=-0.0080, max=0.0092\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-03] Adobe Unveils Major Document Updates, Enhances PDF Experience Adobe Systems IncorporatedADBE is firing on all cylinders to enhance presence in the document management system market on the back of its robust tools and software. The company has recently added useful updates to its Adobe Document Cloud, enabling the users to share and edit portable document format (PDF) files seamlessly and securely. Adobe aims to enrich the PDF user experience with its latest advances in order to gain further traction in this data driven world where e-documentation is of primary importance. Coming to the price performance, shares of Adobe have returned 55.3% on a year-to-date basis, outperforming the industry 's rally of 28.6%. New Updates to Drive Growth The company has introduced central document hub and home view in Acrobat DC which will allow the users of Acrobat DC desktop app, Acrobat Reader mobile app and the new Adobe Document Cloud web app to access the files and documents from one single point. Further, the new updates will offer cross-platform capabilities which will enable the users of Acrobat Pro DC to edit their documents on tablets with touch sensor of the devices similar to desktops. Additionally, the combination of Adobe's Sensei, Adobe Scan and Acrobat DC will aid in filling forms and scanning business cards. Further, with the help of modified Adobe Sign, people can electronically sign PDFs in Acrobat DC. Furthermore, an improvised content review process will help in tracking the activities related to a PDF file such as info on who is sharing the file with how many reviewers. This will ease the collection of feedbacks. Moreover, the new updates will assist in solving the feedbacks within the PDF itself. All these new useful features are likely to strengthen the company's product portfolio. Further, they will attract more users to the company's platform, thus expanding the adoption rate of Adobe Document Cloud. This will aid the subscription revenues, consequently aiding the company's top- line. Adobe Systems Incorporated Revenue (TTM) Adobe Systems Incorporated Revenue (TTM) | Adobe Systems Incorporated Quote Market Opportunities Per a report from MarketsandMarkets, the global document management system market is expected to reach $6.78 billion by 2023 at a CAGR of 11.17% between 2017 and 2023. Adobe's latest updates in Acrobat which offers a set of a cloud-based document and collaboration subscription services, supports centralized online file sharing and contract signing solutions, will aid it in reaping benefits from this potential market. Further, the company's robust Document Cloud will aid the company to rapidly penetrate the document-centric collaboration software market which as per a report from Technavio, is projected to witness a CAGR of more than 10% between 2017 and 2021. Notably, all these will help Adobe to fortify its presence in the rapidly growing cloud market in today's world. Zacks Rank & Stocks to Consider Currently, Adobe car\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": "-0.0065", "answer_numeric": -0.006472, "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%) = -0.0075.", "metadata": {"var": -0.006472, "cvar": -0.007536, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220707_0181", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2022-07-07", "context_summary": "EWJ: 60-day return history, mean=-0.0019, std=0.0120.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=-0.0019, std=0.0120, min=-0.0286, max=0.0204\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-06] [\"Beyond Crypto: This Is the Secret Sauce to Retiring a Millionaire While many would agree that the stock market has been the best tool historically to building long-term wealth, cryptocurrencies have taken that title in the past several years. Bitcoin and Ethereum, for example, have produced trailing five-year returns of 700% and 310%, respectively, compared with the S&P 500's total return of only 73% during that time. But with cryptocurrencies getting absolutely hammered over the past few months, now is a good time to reassess your investment philosophy and the path you want to take to achieve adequate financial returns. And if you want to retire a millionaire, a valid argument can be made that avoiding crypto altogether might be the right course of action now. Image source: Getty Images. Don't chase the shiny object With stories of individuals becoming millionaires virtually overnight by trading digital assets, a fear of missing out can no doubt be the feeling many non-crypto investors have been experiencing. It's human nature. We see others having incredible success doing something and we immediately want to copy that behavior. The problem, however, is that it completely goes against what a rational person should do. What really matters is how much a person is consistently saving, the time until retirement, and their risk tolerance. Building a financial plan that helps one achieve personal goals is the ultimate objective. While some cryptocurrencies have crushed stocks in recent years, they are not the right investment for everyone. For starters, digital assets are ridiculously volatile with daily moves greater than 10% a normal occurrence. And because the sector as a whole just started its teenage years -- Bitcoin was launched in January 2009 -- the potential range of outcomes for the still-nascent asset class is extremely wide. This is too much uncertainty for most to stomach. Furthermore, the lack of regulation with cryptocurrencies, something that is not an issue in the traditional financial system, adds to the level of risk. There are countless stories of scams. And even with legitimate projects, the total risk involved with different crypto enterprises is simply unknown. We're seeing this play out right now, with major crypto hedge fund Three Arrows Capital filing for bankruptcy protection and Voyager Digital, a large crypto brokerage, suspending all trading because of market conditions. It can certainly be tempting to buy into the hype of cryptocurrencies, especially given the monster returns some speculators have achieved by buying digital assets, but a safer approach is to just focus on owning stocks for the long haul. Do this instead There really is no secret to retiring a millionaire. It's actually quite simple. People should start investing at a young age and let compounding take care of the rest. But what's the right way to invest? If you have the time to study and research different businesses, then actively picking stocks might\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": "-0.0217", "answer_numeric": -0.021679, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0217 (i.e., on a bad day with 5% probability, the loss exceeds 2.17%). CVaR(95%) = -0.0282.", "metadata": {"var": -0.021679, "cvar": -0.02824, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180829_0184", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2018-08-29", "context_summary": "ACWI: 60-day return history, mean=0.0003, std=0.0058.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0003, std=0.0058, min=-0.0143, max=0.0098\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-08-28] [\"Here\\u2019s What Blockchain Technology Means for IBM Stock InvestorPlace - Stock Market News, Stock Advice & Trading Tips IBM (NYSE: IBM ) has been in a prolonged restructuring, and the results have been mixed at best. This is particularly aggravating since various other old-line tech giants like Microsoft (NASDAQ: MSFT ), Cisco (NASDAQ: CSCO ) and Adobe (NASDAQ: ADBE ), have staged strong turnarounds. But I think investors should not give up on IBM stock. The fact is that the company is making progress. More important, it has been investing heavily in next-generation technologies. Just look at the blockchain category. The roots of this technology go back to 2009, with the creation of the bitcoin cryptocurrency. The blockchain technology was the foundation of it, acting as a powerful ledger system. This meant that the transactions were stored in a decentralized database and only accessible by private key cryptography - making it highly secure. 21 Beverage Stocks to Buy for the Contrarian-Minded Since then, the interest in blockchain has certainly gotten more and more intense. But the applications are much wider than just cryptocurrency. Blockchain really represents a new way of storing any kind of critical information. And this is ideal for a company like IBM. In fact, the company has already made significant strides. IBM Stock and the Blockchain An example of this is TradeLens, which involves an alliance with Maersk, a major integrated container logistics company. The platform leverages blockchain technology to track transactions across the shipping supply chain. So far, there are 94 organizations in the program that account for 234 marine gateways worldwide. TradeLens provides transparency, which is often lacking in global trade. But there is also the use of sophisticated IoT (Internet-of-Things) sensor data to provide real-time access. To get a sense of the power of this platform, it has helped reduce the transit times of shipments of packing materials to the U.S. by as much as 40% . Keep in mind that global shipping represents about four trillion dollars in goods every year. But TradeLens is not the only initiative. For example, there is LedgerConnect , which helps financial institutions to create their own blockchain apps. Some of the partners include Barclays (NYSE: BCS ) and Citigroup (NYSE: C ). Some of the core functions of LedgerConnect include collateral management, sanctions screening and derivatives processing. Although, the technology should also help promote standards in the financial industry and also make it easier to develop new innovations. And as the system gets more traction, there is likely to be the benefit of network effects, which should lead to strong barriers to entry. The Bottom Line on IBM Stock When it comes to IBM stock, blockchain technology is still in the early stages, but it should have a pervasive impact in the coming years. What's more, IBM's efforts show that the company is focused on innovation and taking \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": "-0.0119", "answer_numeric": -0.011895, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0119 (i.e., on a bad day with 5% probability, the loss exceeds 1.19%). CVaR(95%) = -0.0127.", "metadata": {"var": -0.011895, "cvar": -0.012698, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210914_0189", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2021-09-14", "context_summary": "XRP-USD: 60-day return history, mean=0.0116, std=0.0633.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0116, std=0.0633, min=-0.1902, max=0.1895\nMarket regime: sideways\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": "-0.0782", "answer_numeric": -0.078165, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0782 (i.e., on a bad day with 5% probability, the loss exceeds 7.82%). CVaR(95%) = -0.1204.", "metadata": {"var": -0.078165, "cvar": -0.120438, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181126_0192", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2018-11-26", "context_summary": "VLUE: 60-day return history, mean=-0.0019, std=0.0108.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0019, std=0.0108, min=-0.0356, max=0.0205\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-11-23] [\"50 Biggest Movers From Wednesday\", \"Argus Upgrades Autodesk to Buy, Announces $160 Price Target\", \"Argus Upgrades Autodesk to Buy, Announces $160 Price Target\", \"50 Biggest Movers From Wednesday\", \"Company News For Nov 23, 2018 Foot Locker Inc.'s FL shares jumped 14.9% after the company posted fiscal third-quarter 2018 adjusted earnings per share of $0.95, surpassing the Zacks Consensus Estimate of $0.92 Shares of Autodesk Inc. ADSK surged 9.7% after reporting third quarter fiscal 2019 adjusted earnings per share of $0.29, outpacing the Zacks Consensus Estimate of $0.26 LATAM Airlines Group S.A. LTM shares climbed 5.9% after the company reported third-quarter adjusted earnings per share of $0.09, beating the Zacks Consensus Estimate by 1 cent. Shares of BJ's Wholesale Club Holdings Inc. BJ soared 11.2% after posting fiscal third-quarter 2018 adjusted earnings per share of $0.39, surpassing the Zacks Consensus Estimate of $0.34 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 Autodesk, Inc. (ADSK): Free Stock Analysis Report LATAM Airlines Group S.A. (LTM): Free Stock Analysis Report Foot Locker, Inc. (FL): Free Stock Analysis Report BJ's Wholesale Club Holdings, Inc. (BJ): Free Stock Analysis Report To read this article on Zacks.com 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. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Autodesk (ADSK) Soars: Stock Adds 9.7% in Session Autodesk, Inc.ADSK was a big mover last session, as the company saw its shares rise nearly 10% on the day. The move came on solid volume too with far more shares changing hands than in a normal session. This stock, which remained volatile and traded within the range of $123.05 -$140.61 in the past one-month time frame, witnessed a sharp increase on Wednesday. The move came after the company announced that it will acquire PlanGrid for $875 million. The company has seen a mixed track record when it comes to estimate revision of one increase and no decrease over the past few weeks, while the Zacks Consensus Estimate for the current quarter remained unchanged. The recent price action is encouraging though, so make sure to keep a close watch on this firm in the near future. Autodesk currently has a Zacks Rank #3 (Hold) while its Earnings ESP is positive. Autodesk, Inc. Price Autodesk, Inc. Price | Autodesk, Inc. Quote Investors interested in the Computer - Software industry may consider ACI Worldwide, Inc. ACIW , which has a Zacks Rank #1 (Strong Buy). You can see the complete list of today's Zacks #1 Rank stocks here. Is ADSK going up? Or down? Predict to see what others think: Up or Down Will You Make a Fortune on the Shift to Electric Cars? Here's another stock idea to consider. Much like\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": "-0.0235", "answer_numeric": -0.023513, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0235 (i.e., on a bad day with 5% probability, the loss exceeds 2.35%). CVaR(95%) = -0.0289.", "metadata": {"var": -0.023513, "cvar": -0.02891, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220110_0197", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2022-01-10", "context_summary": "XHB: 60-day return history, mean=0.0016, std=0.0143.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0016, std=0.0143, min=-0.0344, max=0.0343\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": -0.023316, "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%) = -0.0289.", "metadata": {"var": -0.023316, "cvar": -0.028891, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220117_0200", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2022-01-17", "context_summary": "IWM: 60-day return history, mean=-0.0009, std=0.0141.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0009, std=0.0141, min=-0.0371, max=0.0282\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-14] [\"3 Downtrodden Stocks to Sell Before It Gets Worse InvestorPlace - Stock Market News, Stock Advice & Trading Tips Downtrends are multiplying across the land, and bears\\u2019 ranks are swelling. Despite the fact that the Nasdaq Composite still sitting a stone\\u2019s throw from its peak, some 40% of the index has been cut in half. There\\u2019s trouble beneath the surface, making for narrowing leadership and, ultimately, more vulnerability. I scanned my watchlist of the downtrodden and discovered three ugly stocks to sell before they get worse. And you don\\u2019t need to perform any mental gymnastics to grasp why lower prices are in the offing. The stocks below are stuck in nasty downtrends. And that matters greatly because trend direction is the most important of all technical signals. It sits atop the hierarchy of charting, demanding deference from all who employ technical analysis. In short, you\\u2019re far better off betting with the trend than against it. 7 Undervalued Stocks to Buy Before Wall Street Catches On That said, here are three struggling stocks that are poised for lower prices. PayPal (NASDAQ:PYPL) Snapchat (NYSE:SNAP) Adobe (NASDAQ:ADBE) Let\\u2019s review each chart in greater detail and map out a smart options trade you can use to bank on further weakness. Downtrodden Stocks to Sell: PayPal (PYPL) Source: The thinkorswim\\u00ae platform from TD Ameritrade Distance from Peak: -43% PayPal could still fall a great distance despite getting cut nearly in half. Going into the 2020 pandemic, PYPL was sitting at $125, another $50 lower from here. Over the past six weeks, the daily downtrend has slowed and formed a sideways trading range. But instead of powering to the top side and building a compelling bullish breakout, it\\u2019s knocking heavily on the lower-end. The $177 support shelf has held long enough to where its failure would prove a significant breakdown. If previous support breaks are any indication, we could see a swift move down to $160 if sellers press their bets. Given the higher volatility of the stock, I suggest using a spread trade over buying puts outright. The Trade: Buy the Feb $175/$160 put vertical for $4.75. You\\u2019re risking $4.75 to make $10.25 if PYPL stock falls to $160 by expiration. Snap (SNAP) Source: The thinkorswim\\u00ae platform from TD Ameritrade Distance from Peak: -56% Snap\\u2019s unraveling following last quarter\\u2019s earnings report has been deathly. For a single announcement to cause the stock to drop over 50% within a single quarter is horrific and speaks to just how much the Street hated the numbers. Prices are now submerged deep beneath all major moving averages. Once again, it\\u2019s tempting to argue SNAP stock is down so much that it can\\u2019t go lower. But like PayPal, it was way, way lower before the pandemic. Shareholders are hoping the quarterly report on Feb. 3 saves them. For now, I think the downtrend continues. Prices are down big over the past three days, so if you want to wait for\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": "-0.0228", "answer_numeric": -0.02277, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0228 (i.e., on a bad day with 5% probability, the loss exceeds 2.28%). CVaR(95%) = -0.0315.", "metadata": {"var": -0.02277, "cvar": -0.031477, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160816_0203", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2016-08-16", "context_summary": "XLK: 60-day return history, mean=0.0020, std=0.0089.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0020, std=0.0089, min=-0.0392, max=0.0196\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-08-15] [\"Two Chip Picks to Play iPhone, Galaxy Demand Broadcom and InvenSense both could benefit with the launch of the iPhone 7 and Galaxy Note 7.\", \"Stock bulls keep making it look easy \\u2014 which is getting hard to fathom Critical information ahead of the U.S. market\\u2019s open Another week, another slew of record highs splashed across the major indexes. This whole stock market thing ... pretty easy, right? Don\\u2019t tell that to hedge funder Crispin Odey, the one-time billionaire who has seen his fortunes gutted.\", \"Twitter shares trading at 7-month high after report of potential deal with Apple Shares of Twitter Inc. were up 4% Monday, trading at a seven-month high, after a New York Times report that the company has been talking with Apple Inc about putting a Twitter app on Apple TV. The move would add to Twitter's recent partnership with the National Football League. Shares of Apple were up 1%. In the past month to date, shares of Twitter have gained 23% compared to the S&P 500's gain of 1%.\", \"Apple CEO Tim Cook: \\u2018We\\u2019re not a tax dodger\\u2019 The amount of money stashed abroad by U.S. multinationals doubled between 2008 and 2014 to more than $2 trillion Apple leads the way, but the amount of money stashed overseas by U.S. multinationals has exploded in recent years, doubling into the trillions between 2008 and 2014. For some perspective on the numbers, cost-estimating website HowMuch.net crunched the most recent data and created a telling interactive chart.\", \"Tiger Global: Sells 18M Shares of Netflix, Continues to Cut Apple Netflix (NFLX) lost a friend today. Tiger Global Management disclosed in a 13F filing today that it no longer owns the tech giant in its portfolio as of June 30 after selling almost 18 million shares during the second quarter. The hedge fund also continued to slash its exposure to Apple (AAPL).\", \"Twitter shares soar after report of Apple TV talks Beleaguered social stock reaches highest prices since January Shares of Twitter Inc. jumped more than 7% in midday trading Monday, hitting a seven-month high after an unconfirmed report in the New York Times that the company was in talks with Apple Inc. to put its app on Apple TV.\", \"Twitter\\u2019s \\u2018Live Streams\\u2019 Can Ride TV\\u2019s Fleeing Ad Budgets, Says Boenning & Scattergood\", \"Apple: Despite iPhone Decline, Smartphones to Rise in 2016, says Canalys There are a couple of upbeat tidbits for the beleaguered smartphone market today, in particular, the report of research firm Canalys that phone shipments will rise this year, even though Apple (AAPL) is projected to see its first-ever annual decline in iPhone shipments.Canalys projects shipments this calendar year of 1.4 billion units, a 5% year-over-year increase. Apple is expected by Wall Street to see a 9% decline in unit shipments of the iPhone in the fiscal year ending in September, being seeing its sales lift again in fiscal \\u201917 by 5%.Given that outlook, the market get a little lift from a forthcomi\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": "-0.0079", "answer_numeric": -0.00788, "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%) = -0.0236.", "metadata": {"var": -0.00788, "cvar": -0.02357, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210316_0206", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-03-16", "context_summary": "DOT-USD: 60-day return history, mean=0.0158, std=0.0743.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0158, std=0.0743, min=-0.1117, max=0.2810\nMarket regime: sideways\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": "-0.0900", "answer_numeric": -0.089978, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0900 (i.e., on a bad day with 5% probability, the loss exceeds 9.00%). CVaR(95%) = -0.0990.", "metadata": {"var": -0.089978, "cvar": -0.099043, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160805_0211", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2016-08-05", "context_summary": "VTI: 60-day return history, mean=0.0008, std=0.0083.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0008, std=0.0083, min=-0.0335, max=0.0182\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-08-04] [\"Top Dogs (And Stocks In The Dog House) - Cramer's Mad Money (8/3/16)\", \"Tracking William Von Mueffling's Cantillon Capital Management Portfolio - Q2 2016 Update\", \"Tracking William Von Mueffling's Cantillon Capital Management Portfolio - Q2 2016 Update\", \"Top Dogs (And Stocks In The Dog House) - Cramer's Mad Money (8/3/16)\", \"Vipshop Holdings (VIPS) Q2 Earnings: What's in the Cards? Vipshop Holdings LimitedVIPS ) is set to report second-quarter 2016 results on Aug 8, after the market closes . Last quarter, this Chinese online lifestyle product retailer posted a negative surprise of 6.67%. In the last four quarters, the company missed estimates in two, posted in-line results in one and topped expectations in one with an average positive surprise 1.86%. Let's see how things are shaping up for this announcement. VIPSHOP HOLDNGS Price and EPS Surprise VIPSHOP HOLDNGS Price and EPS Surprise | VIPSHOP HOLDNGS Quote Factors at Play Vipshop Holdings ramped up its marketing efforts and started offering substantial discounts in 2015. This helped the company expand and target new users across a wide age group. We expect the trend to continue in the to-be-reported quarter, thereby boosting the company's top line. Moreover, the company enhanced its logistics to improve customers' shopping experience. It also expanded the product assortment at its stores during the first half of 2016, which should aid top-line growth in the to-be-reported quarter. The financing program for customers launched during the first quarter is expected to boost customer spending. This should help the company increase consumer loyalty and enhance the overall consumer experience, while boosting the average spend per customer. Such an initiative is expected to increase the company's market share as well as boost revenues in the second quarter. However, the discounts offered by the company are expected to adversely impact margins. Further, the ongoing macroeconomic slowdown in China and increasing competition in the retail space are headwinds. Earnings Whispers Our proven model does not conclusively show that Vipshop Holdings will beat earnings this quarter. That is because a stock needs to have both a positive Earnings ESP and a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold) for this to happen. That is not the case here as you will see below. Zacks ESP : Both the Most Accurate estimate and the Zacks Consensus Estimate stand at 14 cents per share. Hence, the difference is 0.00%. Zacks Rank : Vipshop Holdings carries a Zacks Rank #4 (Sell). We caution against stocks with a Zacks Rank #4 or 5 (Sell-rated stocks) going into the earnings announcement, especially when the company is seeing negative estimate revisions momentum. Stocks to Consider Here are some computer and technology stocks with a positive Earnings ESP and a favorable Zacks Rank: Analog Devices ADI with an Earnings ESP of +2.63% and a Zacks Rank #2. Digital Turbine APPS with an Earnings ESP of +12.50% and a Zacks Rank #3. Di\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": "-0.0092", "answer_numeric": -0.009224, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0092 (i.e., on a bad day with 5% probability, the loss exceeds 0.92%). CVaR(95%) = -0.0213.", "metadata": {"var": -0.009224, "cvar": -0.021306, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201006_0214", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2020-10-06", "context_summary": "SOYB: 60-day return history, mean=0.0022, std=0.0083.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=0.0022, std=0.0083, min=-0.0210, max=0.0272\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": "-0.0114", "answer_numeric": -0.011389, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0114 (i.e., on a bad day with 5% probability, the loss exceeds 1.14%). CVaR(95%) = -0.0154.", "metadata": {"var": -0.011389, "cvar": -0.015422, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20191114_0217", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PPLT"], "decision_date": "2019-11-14", "context_summary": "PPLT: 60-day return history, mean=0.0011, std=0.0151.", "question": "Asset: PPLT\nDaily returns (past 60 days): mean=0.0011, std=0.0151, min=-0.0436, max=0.0399\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": "-0.0247", "answer_numeric": -0.024674, "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%) = -0.0342.", "metadata": {"var": -0.024674, "cvar": -0.034227, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170104_0224", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2017-01-04", "context_summary": "QQQ: 60-day return history, mean=0.0002, std=0.0078.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0002, std=0.0078, min=-0.0174, max=0.0235\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-03] [\"Seven highly valued tech startups that could IPO in 2017 Unicorns like Snap and Spotify are expected to reach Wall Street in 2017, but what about Uber, Lyft, Airbnb, Dropbox and Palantir? After a dismal year for IPOs, investors expects to see more billion dollar startups test the public market or at least make moves in that direction.\", \"Go after these long-term stock plays in 2017 \\u2014 don\\u2019t chase what already happened Critical information for the U.S. trading day The new year has kicked off with what looks like a bright start for stocks, but investors should check their desire to chase the market at the door. Our call of the day offers these ideas for investing in some themes that will deliver.\", \"Intel seeks German digital-map venture stake BERLIN-- Intel Corp. is positioning itself to join BMW AG, Daimler AG and Volkswagen AG's Audi unit in developing navigation technology for self-driving cars. The U.S. tech bellwether filed a request for regulatory approval in Germany to make a strategic acquisition of a minority stake in the digital-mapping service Here International B.V., the Berlin-based company that Germany's big-three car makers bought from Nokia in 2015 for about EUR2.5 billion ($2.6 billion).\", \"CES 2017: Can Virtual Reality Finally Go Mainstream? For VR, 2016 was supposed to be the year when everything came together. But VR headsets remain bulky, expensive, and nausea inducing. What to expect in 2017.\", \"Virtual Reality Fertile Ground for Loup Ventures Despite Failures Thus Far A couple weeks ago I spoke by phone with former analyst , who left the firm after many years being a star analyst on (AAPL) to become a venture capitalist, along with colleagues and .Their firm, , will invest in four areas, , , , and , which they sees as among the most promising tech trends of the next several years. They want to combin investment with dissemination of research notes like they have done as sell-side analysts.More info is available on their Web site.I was interested to talk with the trio because my own experience with virtual reality, related in this space, is that it's at best immature as a consumer product, and at worst, it just plain sucks.\", \"As India Investment Slumps, Will GDP Follow? Announcements about new investments in India declined in the quarter ending December 30, continuing a stubborn quarterly trend.Add demonetization to the mix, and one has to ask if expectations for India's economy are too elevated. Read More>>\", \"Intel buys 15% stake in German digital-map co. Intel Corp. is acquiring a 15% stake in Here International B.V. for an undisclosed sum, joining the digital mapmaker's core shareholders BMW AG, Daimler AG and Volkswagen AG's Audi unit in developing navigation technology for self-driving cars.\", \"Apple\\u2019s Key Risk: Nokia Litigation The beginning of the year will likely be quiet in terms of legal outcomes, but the second half could bring volatility.\", \"Meet the world\\u2019s friendliest home robot Kuri, deve\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": "-0.0123", "answer_numeric": -0.01229, "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%) = -0.0160.", "metadata": {"var": -0.01229, "cvar": -0.016024, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20161010_0227", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2016-10-10", "context_summary": "XLY: 60-day return history, mean=-0.0003, std=0.0064.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0003, std=0.0064, min=-0.0244, max=0.0139\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-10-07] What's Next for Alnylam Pharmaceuticals, Inc. After Its Phase 3 Failure? Image source: Getty Images. Another once-promising drug has failed. Alnylam Pharmaceuticals (NASDAQ: ALNY) announced on Oct. 5 that it was discontinuing development of revusiran in treating hereditary ATTR amyloidosis with cardiomyopathy (hATTR-CM). The drug had been in a late-stage study and mid-stage study. The company said that its independent committee monitoring the late-stage study recommended that the benefits of the drug didn't outweigh the risks after several patients died and other patients experienced worsening nerve damage in the phase 2 study. The market reacted immediately to the bad news. Alnylam's stock plunged more than 46% in early trading the morning after the announcement. What's next for the biotech after this huge setback? What could have been Analysts had been projecting that revusiran could reach peak annual sales of more than $1 billion. Alnylam wouldn't have received all of the revenue had things gone better, though; the company licensed the rights for the drug outside of North America and Western Europe to Sanofi . Still, Alnylam would have potentially raked in hundreds of millions of dollars per year if revusiran had been successful. All of this theoretical revenue has now gone up in smoke. The market sell-off after Alnylam's announcement wiped out around $3 billion of the biotech's market cap. That doesn't seem overblown considering the peak sales projections for revusiran. Alnylam CEO John Maraganore said that the company would continue to analyze the data from the late-stage study to try to determine the potential cause for the safety issues. However, the bottom line is that the game is over for revusiran -- and Alnylam must deal with the financial repercussions. Next in line Probably the biggest question on investors' minds was: How does this affect Alnylam's other hereditary ATTR amyloidosis drug, patisiran? The company stated that the decision to discontinue development for revusiran won't change anything for plans related to patisiran, which is in a late-stage study for the treatment of hereditary ATTR amyloidosis with polyneuropathy (hATTR-PN). Both revusiran and patisiran use RNA interference, a revolutionary method of turning genes off and on. Through RNA interference, the drugs attempt to silence specific messenger RNA and prevent proteins that cause hATTR from being made. While the two drugs use the same underlying approach, there are key differences in how they are administered and accomplish RNA interference in the liver. Alnylam conducted a review of the safety data for patisiran and found no evidence of drug-related nerve dysfunction. That's at least a sliver of good news for the biotech. Analysts estimate that patisiran could achieve peak annual sales of over $750 million. As with revusiran, though, Alnylam must split any revenue with Sanofi. The French drugmaker has commercialization rights for patisiran outside of North America \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": "-0.0113", "answer_numeric": -0.011267, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0113 (i.e., on a bad day with 5% probability, the loss exceeds 1.13%). CVaR(95%) = -0.0179.", "metadata": {"var": -0.011267, "cvar": -0.017927, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20171215_0230", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2017-12-15", "context_summary": "SCHP: 60-day return history, mean=0.0001, std=0.0019.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0001, std=0.0019, min=-0.0047, max=0.0042\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": "-0.0031", "answer_numeric": -0.003057, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0031 (i.e., on a bad day with 5% probability, the loss exceeds 0.31%). CVaR(95%) = -0.0036.", "metadata": {"var": -0.003057, "cvar": -0.003606, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20150622_0233", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2015-06-22", "context_summary": "EEM: 60-day return history, mean=0.0001, std=0.0092.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0001, std=0.0092, min=-0.0176, max=0.0207\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-06-19] [\"Maxim Integrated, others named as potential Texas Instruments target\", \"Maxim Integrated, others named as potential Texas Instruments target\", \"Analog Devices Inc. Reportedly Wins a Design Inside the Next Apple Inc. iPhone According to Barron's , Citigroup analyst Chris Danely said chipmaker Analog Devices has \\\"likely won a slot in Apple 's next iPhone.\\\" This win could positively impact Analog Devices' revenue and profit in 2016, according to the report. Let's take a closer look at what Danely had to say. What's this design win worth? Danely said this win could be worth $160 million in revenue to Analog Devices in 2016, adding about 4% to the company's expected top line for the year. The analyst estimated the deal's operating margin at 23.5%, lower than the 32.4% company-wide operating profit margin he expects for the full year. To explain his relatively low margin expectation for the deal, Danely said margins from \\\"high volume consumer products and large customers such as Apple\\\" are generally lower than \\\"high-performance analog products for industrial applications.\\\" At any rate, the deal is still expected to be accretive to both revenue and earnings. Concordant with that view, Danely raised his 2016 earnings-per-share estimate for Analog by about 2.7%, from $2.98 to $3.06. A \\\"low-quality\\\" win? Danely noted that although the iPhone win should \\\"boost revenue and [earnings per share] in a meaningful and material way\\\" for Analog, that Citi has \\\"a lot of concern on the long-term quality\\\" of this new revenue. \\\"Apple is notorious for giving and taking away large design wins,\\\" Danely wrote in his research note. He added that Analog Devices has previously had \\\"large design wins\\\" with Apple that \\\"ended abruptly.\\\" Those design-outs eventually led to \\\"downside to Consensus estimates and the stock selling off,\\\" he noted. This isn't the first time we've heard of this win, though Analog Devices is up \\\"just\\\" 1.44% following the publication of this research note as of this writing. The Nasdaq index is up 1.35% and the iShares PHLX Semiconductor ETF is up 1.5%, meaning Analog Devices shares aren't outperforming the relevant indices due to this news. This is likely because the Apple win for future iPhones -- and possibly also iPads -- was already reported by analysts at Barclays (via MarketWatch) back in March. Analog Devices shares rallied by about 10% following that initial report. Additionally, at that time the Barclays analyst claimed that the wins at Apple for \\\"high accuracy\\\" analog-to-digital converters inside next-generation iPhones and iPads to enable Force Touch would add \\\"at least\\\" $0.80 to the company's 2016 earnings per share. It's not surprising, then, that a separate confirmation of news that is already \\\"known\\\" wouldn't move the stock much, if at all. Investment takeaway It seems as though Analog Devices has won a spot inside the next-generation iPhone. I'd argue that winning this spot is good, although the company will \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": "-0.0153", "answer_numeric": -0.015271, "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%) = -0.0163.", "metadata": {"var": -0.015271, "cvar": -0.016318, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200819_0238", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2020-08-19", "context_summary": "XLB: 60-day return history, mean=0.0037, std=0.0131.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0037, std=0.0131, min=-0.0337, max=0.0270\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-08-18] [\"How Companies Are Working To Reduce The Size of Their Carbon Footprint \\u201cScientific evidence for warming of the climate system is unequivocal.\\u201d ~ Intergovernmental Panel on Climate Change The Earth\\u2019s natural greenhouse continues to change. Over the years, the concentration of greenhouse gases (GHG) in the atmosphere has increased, resulting in catastrophic changes in the climate. July 2019 was the warmest month in recorded history for the globe. The GHG emissions are traced in the form of a carbon footprint, which is the total amount of GHG generated by human activities. Here\\u2019s a look at how these GHG emissions are at the country level and how are corporates are committing to lower their carbon footprint. At the country level, China is the largest contributor to CO2 emissions with 28% (10.06GT) followed by the U.S. at 15% (5.41GT), India at 7% (2.65GT), and Russia at 5% (1.71GT). However, in terms of per capita emissions, Saudi Arabia is the largest emitter with 18.48T of per capital emissions, followed by Kazakhstan, Australia, the U.S., Canada, and South Korea at 17.6T, 16.92T, 16.56T, 15.32T, and 12.89T, respectively. According to the U.S. Energy Information Administration, the burning of fossil fuels was responsible for 76% of U.S. greenhouse gas emissions. Fossil fuels were the source of about 75% of total U.S. anthropogenic greenhouse gas emissions in 2018. One landmark environmental accord towards cutting emissions was the Paris Agreement signed by nearly every nation to address climate change and its negative impacts. The deal aims to substantially reduce global greenhouse gas emissions and includes commitments from all major emitting countries to cut their climate-altering pollution. As climate change and sustainability take center stage, many companies have set emission reduction targets for the next five, ten, twenty, and thirty years. For the last ten years, Microsoft (MSFT) has made significant investments to reduce its historic carbon footprint. In January 2020, they announced their goal to be carbon negative by 2030, and ultimately remove its carbon footprint (has emitted either directly or by electrical consumption) since it was founded in 1975 by 2050. BMW has been making efforts to reduce CO2 emissions and ensure sustainability over the years. The company has recently set new targets for the phase up to 2030. It includes the first-ever CO2 goals for full lifecycle up to 2030 and lowering of carbon emissions from production and sites by 80% per vehicle. In July 2020, Apple (AAPL) unveiled its plan to become carbon neutral across its entire business, which will ensure that every Apple device sold by 2030 will have a net zero climate impact. Apple has set a target to reduce emissions by 75% by 2030 while developing innovative carbon removal solutions for the remaining 25% of its footprint. In June, Cisco (CSCO) signed its first long-term wind energy power purchase agreement (PPA) as a part of its overall strate\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": "-0.0197", "answer_numeric": -0.019676, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0197 (i.e., on a bad day with 5% probability, the loss exceeds 1.97%). CVaR(95%) = -0.0285.", "metadata": {"var": -0.019676, "cvar": -0.028514, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20211015_0241", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLT"], "decision_date": "2021-10-15", "context_summary": "TLT: 60-day return history, mean=-0.0003, std=0.0080.", "question": "Asset: TLT\nDaily returns (past 60 days): mean=-0.0003, std=0.0080, min=-0.0226, max=0.0171\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for TLT. Express as a decimal (e.g., -0.02).", "answer": "-0.0107", "answer_numeric": -0.010714, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0107 (i.e., on a bad day with 5% probability, the loss exceeds 1.07%). CVaR(95%) = -0.0183.", "metadata": {"var": -0.010714, "cvar": -0.018292, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20211018_0244", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2021-10-18", "context_summary": "VNQI: 60-day return history, mean=-0.0001, std=0.0077.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=-0.0001, std=0.0077, min=-0.0246, max=0.0169\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": "-0.0123", "answer_numeric": -0.012308, "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%) = -0.0167.", "metadata": {"var": -0.012308, "cvar": -0.01674, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160129_0247", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2016-01-29", "context_summary": "SCHH: 60-day return history, mean=-0.0007, std=0.0124.", "question": "Asset: SCHH\nDaily returns (past 60 days): mean=-0.0007, std=0.0124, min=-0.0302, max=0.0263\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SCHH. Express as a decimal (e.g., -0.02).", "answer": "-0.0198", "answer_numeric": -0.019793, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0198 (i.e., on a bad day with 5% probability, the loss exceeds 1.98%). CVaR(95%) = -0.0268.", "metadata": {"var": -0.019793, "cvar": -0.026827, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160718_0250", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2016-07-18", "context_summary": "QUAL: 60-day return history, mean=0.0003, std=0.0083.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0003, std=0.0083, min=-0.0339, max=0.0164\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-07-15] [\"Apple Supplier Largan Precision Soars 8% On Profit Beat, Dual-Cam Outlook Apple (AAPL) lens supplier Largan Precision (3008.Taiwan) has no plans to stop outperforming.Largan Precision already rallied 37% this year on expectation that Apple will adopt dual cameras for its high-end iPhone 7 models this fall. This morning, Largan jumped another 8.5% as its second-quarter profit beat analysts' forecasts and its management painted a sunny outlook on its sales in the second-half.READ MORE.\", \"Big Pharma Q2 Earnings Preview Johnson & Johnson will report on July 19 with Lilly, Bristol-Myers, Merck and AbbVie to follow.\", \"Samsung vs LG: There\\u2019s Only One Stock to Buy Analysts see 20% upside for Samsung on demand for the Galaxy Note 7, while LG shares may fall 20%.\", \"Tech industry bashes Donald Trump in open letter Letter signed by Qualcomm, Box, Yelp CEOs, and dozens more The technology industry said it opposes Donald Trump because of its immigration policies.\", \"BMO Says Qualcomm Can Fall To $50 On Negative Catalysts Qualcomm (QCOM) is up nearly 10% so far in 2016, but BMO Capital Markets doesn\\u2019t expect the rally to last.Analyst Tim Long cut his rating on the stock from Market Perform to Underperform, with a $50 target price. He writes that although the company\\u2019s dividend and cash flow yields are providing support at the moment for the stock, he\\u2019s concerned about negative catalysts on the horizon.\", \"Raymond James Up Jabil To Strong Buy, Inflection Points Overshadowed Jabil Circuit (JBL) is climbing Friday, thanks to a bullish endorsement from Raymond James.Analyst Brian Alexander raised his rating on the stock to Strong Buy from Outperform, with a $26 price target. He writes that there is \\u201cmeaningful\\u201d cash flow and capital return inflection at the firm, but that the market hasn\\u2019t taken notice because it\\u2019s focused on volatility with its top customer\\u2014Apple (AAPL), which accounts for nearly a quarter of sales\\u2014that\\u2019s been driving subpar earnings. However, Alexander writes that with fundamentals hitting a trough, sentiment should improve going into the company\\u2019s analyst day in September, where investors could be heartened by messages about diversification and discipline.\", \"Barclays Trims Apple Target, Calls Smartphone Demand \\u2018Tenuous\\u2019 Barclays\\u2019 Mark Moskowitz cut his estimates for Apple (AAPL) again Friday, the third cut ahead of the company\\u2019s earnings report later this month.He\\u2019s still an Apple bull, reiterating an Overweight rating on the stock, but he lowered his price target from $121 to $115, a process he calls \\u201ctedious\\u201d but necessary, as it\\u2019s larger than his previous cuts. Nonetheless he writes that Apple can still work after any post-earnings weakness, given the iPhone 7 launch is expected this fall. Still, he expects 2017 to be Apple\\u2019s big year, when it skips to the iPhone 8 to reveal major changes, so volatility for the rest of this year coul\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": "-0.0095", "answer_numeric": -0.009501, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0095 (i.e., on a bad day with 5% probability, the loss exceeds 0.95%). CVaR(95%) = -0.0200.", "metadata": {"var": -0.009501, "cvar": -0.019994, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190104_0253", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-01-04", "context_summary": "LINK-USD: 60-day return history, mean=-0.0017, std=0.0800.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0017, std=0.0800, min=-0.1934, max=0.1577\nMarket regime: sideways\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": "-0.1322", "answer_numeric": -0.132228, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1322 (i.e., on a bad day with 5% probability, the loss exceeds 13.22%). CVaR(95%) = -0.1661.", "metadata": {"var": -0.132228, "cvar": -0.166083, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20221028_0256", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2022-10-28", "context_summary": "IWM: 60-day return history, mean=-0.0009, std=0.0174.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0009, std=0.0174, min=-0.0371, max=0.0349\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-27] [\"Apple (AAPL) Q4 2022 Earnings Call Transcript Image source: The Motley Fool. Apple (NASDAQ: AAPL) Q4 2022 Earnings Call Oct 27, 2022, 5:00 p.m. ET Contents: Prepared Remarks Questions and Answers Call Participants Prepared Remarks: Operator Good day, and welcome to the Apple Q4 fiscal year 2022earnings conference call For your information, today's call is being recorded. At this time, for opening remarks and introductions, I would like to turn the call over to Tejas Gala, director of investor relations and corporate finance. Please go ahead. Tejas Gala -- Director of Investor Relations and Corporate Finance Speaking first today is Apple's CEO, Tim Cook; and he'll be followed by CFO, Luca Maestri. After that, we'll open the call to questions from analysts. Before turning the call over to Tim, I would like to remind you that approximately once every six years, we add a week to the December quarter to realign our fiscal periods with the December calendar. So this December quarter will span 14 weeks rather than the usual 13 and will end on December 31. Please note that some of the information you'll hear during our discussion today will consist of forward-looking statements, including, without limitation, those regarding revenue, gross margin, operating expense, other income and expense, taxes, capital allocation, and future business outlook, including the potential impact of COVID-19 on the company's business and results of operations. These statements involve risks and uncertainties that may cause actual results or trends to differ materially from our forecast. For more information, please refer to the risk factors discussed in Apple's most recently filed annual report on Form 10-K and the Form 8-K filed with the SEC today, along with the associated press release. Apple assumes no obligation to update any forward-looking statements or information, which speak as of their respective dates. 10 stocks we like better than Apple When our award-winning 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 September 30, 2022 I'd now like to turn the call over to Tim for introductory remarks. Tim Cook -- Chief Executive Officer Thank you, Tejas. Good afternoon, everyone, and thank you for joining the call today. Over the past year, despite a range of challenges facing the world, our teams have come together in incredible ways to drive unparalleled innovation and deliver again and again for our customers.For the September quarter, we reported record revenue of $90.1 billion, which was better than we anticipated despite stronger-than-expected foreign currency headwinds. We set an all-time revenue record for Mac and S\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": "-0.0273", "answer_numeric": -0.02728, "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%) = -0.0334.", "metadata": {"var": -0.02728, "cvar": -0.033444, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200729_0263", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2020-07-29", "context_summary": "BIL: 60-day return history, mean=0.0000, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0000, std=0.0001, min=-0.0002, max=0.0002\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": "-0.0002", "answer_numeric": -0.000218, "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": -0.000218, "cvar": -0.000218, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210705_0265", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2021-07-05", "context_summary": "STIP: 60-day return history, mean=0.0003, std=0.0013.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0003, std=0.0013, min=-0.0039, max=0.0031\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": "-0.0015", "answer_numeric": -0.00152, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0015 (i.e., on a bad day with 5% probability, the loss exceeds 0.15%). CVaR(95%) = -0.0032.", "metadata": {"var": -0.00152, "cvar": -0.003158, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20171201_0270", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2017-12-01", "context_summary": "^VIX: 60-day return history, mean=-0.0005, std=0.0503.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0005, std=0.0503, min=-0.1424, max=0.1248\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-11-30] [\"High-flying tech stocks fall back toward earth, chip makers suffer worst day of year Tech stocks lead S&P 500 to a loss despite gains for nine of 11 sectors Tech stocks, admittedly the best performers of the year, took a big step back Wednesday to close sharply lower, led by a selloff of chip makers.\", \"Apple's stock gains as analyst sees 'super-long cycle' of iPhone X upgrades Apple Inc. shares rose 0.5% in premarket trading Thursday, after an analyst suggested that the latest iPhone technology will drive a multi-year wave of device upgrades. Piper Jaffray analyst Michael Olson wrote Thursday that Apple could come out with slightly enhanced version of the iPhone X next fall, including a larger-screen option, and cut the price of the original model that was released in early November. The combination of these factors could drive a \\\"super-long cycle\\\" of upgrades, beyond the single-year \\\"super-cycle\\\" investors were hoping for. \\\"We believe an elongated iPhone cycle in FY18, followed by a wider array of iPhone X 'offspring' in Fall 2018, along with growing awareness and interest in augmented reality (fueled by developers populating the App Store with new use cases and, longer-term, addition of rear facing 3D sensor), will all push out the need for Apple to answer the question of 'what's next?'\\\" Olson wrote. With overall global smartphone sales expanding slowly, Apple has been under some pressure to find new avenues for growth. Apple's stock is up 46% so far in 2017, compared with a 21% rise for the Dow Jones Industrial Average .\", \"Apple\\u2019s Delayed \\u2018Super-Long Cycle\\u2019 Will Be All the Better, Says Piper Apple's \\\"super cycle,\\\" the focus of investors for most of this year, hasn't quite lived up to the hype, thanks to delays in the iPhone X. But that's going to lead to a \\\"super-long cycle\\\" in subsequent years, according to Piper Jaffray's Michael Olson, who advises clients to stick with the stock as Apple's OLED-based iPhones lead to rising prices.\", \"Fitbit, Xiaomi knock Apple down to 3rd in wearables shipments Fitbit Inc. and China-based Xiaomi Inc. led the pack in terms of wearables shipments for the latest quarter, according to research firm IDC, knocking Apple Inc. down to third place from second. Both Fitbit and Xiaomi shipped 3.6 million devices in the quarter, IDC said, while overall shipments rose 7.3%, to 26.3 million units. Fitbit released its first full-fledged smartwatch, the Ionic, earlier this fall, and hopes the device will reinvigorate its fortunes as consumers gravitate away from simple fitness tracking bands. Fitbit's shares have lost two thirds of their value since the company's 2015 IPO, and its shipments for the third quarter declined 33% relative to a year earlier, according to IDC. The firm wrote that Apple's shipments of 2.7 million devices reflect the fact that the company launched its new cellular-enabled Apple Watch 3 late in the quarter. \\\"The introduction of a cellular-connected version should spur i\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": "-0.0913", "answer_numeric": -0.091338, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0913 (i.e., on a bad day with 5% probability, the loss exceeds 9.13%). CVaR(95%) = -0.1248.", "metadata": {"var": -0.091338, "cvar": -0.12481, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170406_0273", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2017-04-06", "context_summary": "QQQ: 60-day return history, mean=0.0013, std=0.0041.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0013, std=0.0041, min=-0.0153, max=0.0109\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-04-05] [\"ADP Posts Another Blowout Jobs Number to 263K Wednesday, April 5, 2017 For the second straight month, Automated Data Processing ADP private-sector jobs numbers blew the doors off expectations. A total of 263K new jobs were created for the month of March, a gain of 18,000 jobs from last month's (revised lower) ADP figure of 245K. And, for the second month in a row, Construction and Manufacturing jobs outperformed expectations, helping overall totals in the non-government labor market. The top industries in new job growth were Professional/Business Services (57K) and Leisure/Hospitality (55K), which is not surprising. But the 49K new jobs in Construction and the 30K in Manufacturing are far stronger than the historical average during this entire resurgence in U.S. jobs, which has been going on for the past 7-8 years. Confidence not only with the consumer (which we've seen in other recent econ data) but with the goods-producing sectors has led the way, at least partially due to expectations from the Trump administration's goals to bring back jobs in these categories. Small-sized companies (fewer than 50 employees) grew the most last month at 118K, Medium companies (50-499 employees) grew by 100K and Large firms added 45K jobs. Services still far outweighed Goods, 181K to 82K respectively, but to reiterate - goods-producing is much higher than it's been in the recent past, and for the second straight month. Projections for Friday's comprehensive non-farm payroll report from the Bureau of Labor Statistics (BLS) remain at 175K following today's ADP report, though last month we saw analysts ratchet up their estimates in the wake of the strong ADP numbers. Historically, ADP and BLS jobs figures do tend to align (considering they track differently; ADP does not include government jobs, for instance), but usually only after a month or two of revisions from initial figures. In any case, this has been one of the strongest three-month averages we have seen in a long time regarding jobs growth. This points to what several economists had predicted going back to last year, which is employment traction finally taking hold after a stubborn low-growth market in labor and elsewhere. Pre-markets jumped higher on the ADP data, though the 2-year and 10-year T-notes remain rangebound at this hour. Equities remain the place to be invested. Mark Vickery Senior Editor Questions or comments about this article and/or its author? Click here>> 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 SPDR-DJ IND AVG (DIA): ETF Research Reports NASDAQ-100 SHRS (QQQ): ETF Research Reports SPDR-SP 500 TR (SPY): ETF Research Reports Automatic Data Processing, Inc. (ADP): Free Stock Analysis Report To read this article on Zacks.com 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. The views \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": "-0.0041", "answer_numeric": -0.004131, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0041 (i.e., on a bad day with 5% probability, the loss exceeds 0.41%). CVaR(95%) = -0.0094.", "metadata": {"var": -0.004131, "cvar": -0.009382, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180620_0276", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2018-06-20", "context_summary": "USMV: 60-day return history, mean=0.0009, std=0.0069.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0009, std=0.0069, min=-0.0173, max=0.0197\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-06-19] [\"Beyonc\\u00e9 and Jay-Z\\u2019s new album goes to multiple streaming platforms, and is already a hit \\u2018Everything Is Love\\u2019 album available more places than just Tidal Beyonc\\u00e9 and Jay-Z have made their new album available for streaming across all major music services \\u2014 as long as listeners are paying for it.\", \"Trump reportedly told Apple that tariffs against China would spare iPhones Tech giant worries China will retaliate as trade tensions heat up Apple Inc. iPhones assembled in China will not be subject to U.S. tariffs, according to a report Monday, but the tech giant may get punished by a possible trade war.\", \"Chinese stocks end at 2-year low, Apple suppliers sink on trade-war worries iPhone component-makers\\u2019 shares hit hard in Hong Kong, Taiwan Asian exporters took a heavy hit Tuesday, with China stocks suffering their lowest close in two years, following President Donald Trump\\u2019s announcement of potentially $400 billion in additional tariffs against imports from that country.\", \"Beware the \\u2018perpetual-motion machine\\u2019 driving this market, warns billionaire Howard Marks Critical information for the U.S. trading day President Trump and China just keep ramping up their trade battle, sending stocks worldwide into the woodchipper. But it\\u2019s billionaire investor Howard Marks\\u2019s memo on another hot topic that provides our call of the day.\", \"Apple fined as Australian customers win right-to-repair court fight Apple Inc. was fined in Australia for refusing to offer free fixes for iPhones and iPads that were previously serviced by non-Apple stores, the latest episode in a global dispute between companies and consumers about the right to repair.\", \"Trump\\u2019s latest trade-war threat wreaks havoc for markets \\u2014 here\\u2019s how, in five charts iPhone suppliers, copper, yen China-related markets were taking some heat on Tuesday as a fresh chapter in the trade war with the U.S. threatened to blow up. Here are five charts showing how dramatic a day it has been for global markets.\", \"Universal Display stock slides for sixth straight day, on track to close at 52-week low Shares of Universal Display Corp. are down 3.4% in Tuesday morning trading, marking the sixth straight day that the stock is down and the ninth day out of the last 10 trading sessions. UDC's stock recently changed hands at $87. and is on pace to close at a 52-week low. Shares closed at $87.55 on April 25. The stock has been hammered in recent days amid concerns about Apple Inc.'s plans for its next iPhone lineup. The Wall Street Journal reported last week that Apple expects more than half of iPhones sold this fall to have liquid-crystal-display screens rather than organic-light-emitting-diode screens. Universal Display makes OLED technology. The stock is off 27% over the past 12 months, while the S&P 500 has gained 12%.\", \"China can\\u2019t match Trump in a tariff fight, but it does have other weapons Widening trade dispute is already hurting \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": "-0.0087", "answer_numeric": -0.008701, "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%) = -0.0147.", "metadata": {"var": -0.008701, "cvar": -0.014696, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160108_0279", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2016-01-08", "context_summary": "XLY: 60-day return history, mean=-0.0007, std=0.0103.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0007, std=0.0103, min=-0.0267, max=0.0191\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-07] [\"Sony Dips On Apple Weakness, Credit Suisse Warns Asia Tech Profit Tumble Sony Corp. (6758.Japan/SNE) tumbles 5% in Tokyo this morning after customer Apple (AAPL) at one point fell through $100 per share, ending down 2% to $100.70 on Wednesday. The market is worried that Apple will dramatically cut its iPhone production in the March quarter.Separately, Nitto Denko (6988.Japan), rumored to supply OLED screens for future generation iPhones, dipped 4.8% as well.READ MORE.\", \"With smartphone sales booming, Huawei eyes U.S. market Fast-growing Chinese manufacturer introduces new phone at CES Huawei Technologies Co. boasted of dramatic gains in the global smartphone market as it launched a new flagship handset that signals its ambitions in the lucrative U.S. market.\", \"Apple Casing Supplier Catcher Tech Sees No Sales Growth In First-Half So Apple (AAPL) is cutting its production orders in the March quarter for real?After releasing disappointing December sales numbers yesterday, Apple metal casing supplier Catcher Technology (2474.Taiwan) told analysts that it expected 2016 first-half sales to be flattish year-on-year and we should not see growth till the second-half. Catcher also said capital expenditure this year would be lower than the previous two.READ MORE.\", \"5 black swans that could rock markets in 2016 What if Apple failed the next iPhone launch, or peace broke out in Syria? Matthew Lynn lists five potential black swans -- inherently unpredictable events -- that could rock financial markets in 2016.\", \"Apple stock price tumbles 3% premarket, now trades well below $100\", \"Market bears roar as $2.5 trillion gets wiped out Critical information before the U.S. market\\u2019s open Our chart of the day shows why analysts expect a lot of pain for the S&P 500 in the near term. Our suggests the Shanghai index could plunge below the low it hit during last summer\\u2019s swoon.\", \"Apple: RBC Slashes iPhone Numbers; \\u2018Higher Than Optimal Inventory\\u2019 Apple (AAPL) this morning gets yet another in a string of estimate cuts following speculation this week that the company cut its iPhone production for the March quarter, this note being from RBC Capital Markets\\u2019s Amit Daryanani, who cut his estimate for March to 45 million units from what he had thought would be 54 million, citing \\\"incremental softness and recent production cuts.\\\"Writes Daryanani, who has an Outperform rating on the stock, but who cuts his price target from $140 to $130, Apple is sitting on \\\"higher than optimal inventory across multiple geographies\\u201d:Our discussions with a host of supply chain companies and recent results from Catcher lead us to think Mar- EPS, Ops Diluted 2014A qtr iPhone units could come in well below current buyside and Street Prev. expectations (50\\u201358M).Read further...\", \"Apple just bought a startup that reads people\\u2019s emotions Emotient technology is used to assess emotions by reading facial expressions Apple Inc. has purchased Emotient Inc., a s\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": "-0.0175", "answer_numeric": -0.017465, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0175 (i.e., on a bad day with 5% probability, the loss exceeds 1.75%). CVaR(95%) = -0.0235.", "metadata": {"var": -0.017465, "cvar": -0.023485, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190314_0282", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2019-03-14", "context_summary": "VLUE: 60-day return history, mean=0.0005, std=0.0109.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0005, std=0.0109, min=-0.0256, max=0.0296\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-03-13] [\"How your internet surfing could make you money in the coming blockchain revolution Decentralized internet will give people online privacy and data ownership A decentralized internet will give people online privacy and data ownership, writes Michael Edesess.\", \"Spotify shares aren't trading in the premarket\", \"Apple's stock adds 0.3% before the opening bell\", \"Spotify files antitrust complaint against Apple in European Union: reports\", \"Spotify files EU antitrust complaint over Apple\\u2019s App store Complaint alleges Apple abused its control over which apps appear in its App Store Music-streaming service Spotify Technology SA has filed an antitrust complaint in Europe against Apple Inc., a new salvo in the broader battle over how and whether to rein in alleged wrongdoing by tech giants.\", \"Spotify Is Hitting Apple With an Antitrust Complaint Over the \\u2018Unfair Advantage\\u2019 of the App Store Spotify CEO Daniel Elk said the App Store gives Apple\\u2019s own applications and services \\u201can unfair advantage at every turn.\\u201d\", \"Apple\\u2019s China Problems May Be Getting Even Worse Analysts expect Apple to report earnings of $2.38 per share on revenue of $57.54 billion, indicating declines of 13% and 5.9%, respectively, from the year-ago period.\", \"Charting a headline breakout attempt, S&P 500 challenges major resistance (2,817) Focus: Apple confirms its uptrend, Real estate sector tags 11-year highs, Utilities finally knife to record territory, AAPL, IYR, XLU, PANW, DDS, NRG U.S. stocks are firmly higher early Wednesday, rising amid distinctly bullish price action ahead of a key Brexit vote. Against this backdrop, the S&P 500 and Nasdaq Composite are challenging their five-month range top \\u2014 S&P 2,817 and Nasdaq 7,670 \\u2014 areas defining the immediate bull-bear tension. An eventual breakout opens the path to less-charted territory, and potentially material follow-through.\", \"Should stock-market investors watch out for a volatility pickup? \\u2018The cost of being wrong using options has seldom been lower,\\u2019 says BTIG\\u2019s Emanuel A 2019 stock-market rally comes alongside a fall in volatility. One analyst says investors can\\u2019t go wrong buying protection against a potential pickup.\", \"Podcast: Microsoft\\u2019s Surprising Comeback This week on The Readback, Alex Eule is joined by associate editor Jack Hough to talk about the surprising comeback of Microsoft.\", \"Apple, Amazon, Google, Facebook cast in Europe as harmful monopolies Spotify claims antitrust against Apple as U.K. report recommends new rules, oversight of big tech firms Facebook, Google, Amazon and Apple are once again being cast as monopolies that have become too powerful for society\\u2019s good, a recurring theme that\\u2019s increasing the pressure to rein them in.\", \"Apple Courts HBO and Showtime for Service to Challenge Netflix The company will host A-list celebrities and media executives on March 25 to outline how it will take on competitors like Amazon.com Inc\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": "-0.0186", "answer_numeric": -0.018621, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0186 (i.e., on a bad day with 5% probability, the loss exceeds 1.86%). CVaR(95%) = -0.0221.", "metadata": {"var": -0.018621, "cvar": -0.022059, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220315_0285", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2022-03-15", "context_summary": "BNB-USD: 60-day return history, mean=-0.0032, std=0.0409.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0032, std=0.0409, min=-0.1294, max=0.0973\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-03-14] \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": "-0.0635", "answer_numeric": -0.063541, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0635 (i.e., on a bad day with 5% probability, the loss exceeds 6.35%). CVaR(95%) = -0.0883.", "metadata": {"var": -0.063541, "cvar": -0.088273, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20190117_0288", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2019-01-17", "context_summary": "XLY: 60-day return history, mean=-0.0008, std=0.0170.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0008, std=0.0170, min=-0.0367, max=0.0338\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-16] [\"Great things are expected for (most) FAANG stocks in 2019 The recent price declines and expected growth ahead could create big opportunities The recent price declines and expected growth ahead could create big opportunities.\", \"Chipmakers look poised for a weak earnings season, KeyBanc says KeyBanc Capital Markets analyst John Vinh delivered a downbeat view of the upcoming earnings season for the chipmakers in his coverage, writing of several concerning trends in a note to clients Wednesday. \\\"We expect 4Q18 earnings season to be challenging given weakening end-demand trends, particularly in China, across multiple sectors including autos, industrials, consumer, and white goods,\\\" he wrote. \\\"With lead times beginning to ease and inventory levels higher, we anticipate a cyclical correction should result in below-seasonal outlooks for broad-based semiconductor companies.\\\" Vinh is also concerned about the impact of weak iPhone demand in what could be \\\"one of the most disappointing iPhone cycles since the 6s.\\\" He sees risk to forward estimates for Cirrus Logic Inc. , Qorvo Inc. , Skyworks Solutions Inc. , and Synaptics Inc. due to ongoing issues with Apple Inc.'s iPhone. He deems wireless infrastructure, including around 5G, \\\"one of the few areas of strength within semiconductors.\\\" Vinh recommends buying Xilinx Inc. shares heading into earnings season and sees room for upside due to \\\"healthy wireless infrastructure demand including 4G and initial 5G pulls.\\\" The PHLX Semiconductor Index is down 6.7% over the past three months, while the S&P 500 has dropped 7.1%.\", \"Roku to remove Infowars from its platform, stock extends gains Shares of Roku Inc. hiked up 1.2% in morning trade Wednesday, adding to the previous session's 2.6% surge. The streaming platform said late Tuesday that it has decided to remove the controversial channel Infowars from its platform. \\\"After the InfoWars channel became available, we heard from concerned parties and have determined that the channel should be removed from our platform,\\\" the company said in an emailed statement to MarketWatch late Tuesday. \\\"Deletion from the channel store and platform has begun and will be completed shortly.\\\" Roku faced a public backlash after the it added the far-right conspiracy-theory promoting channel Infowars, although a number of companies, including Apple Inc. , Twitter Inc. , Facebook Inc. and Google parent Alphabet Inc. , banned the channel. Roku's stock has tumbled 36% over the past three months, while the S&P 500 has slipped 6.8%.\", \"The Dow Rises 123 Points Because Strong Earnings Trump Everything The Dow Jones Industrial Average is up 0.51% to 24,188.11. The S&P 500 and Nasdaq Composite are both 0.24% higher in recent trading.\", \"Sen. Marco Rubio rolls out online-privacy legislation Big Tech wants federal legislation that would preempt California\\u2019s tough new rules Florida Republican Sen. Marco Rubio on Wednesday introduced legislation that would deliver a national consum\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": "-0.0303", "answer_numeric": -0.03033, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0303 (i.e., on a bad day with 5% probability, the loss exceeds 3.03%). CVaR(95%) = -0.0329.", "metadata": {"var": -0.03033, "cvar": -0.032885, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160505_0291", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2016-05-05", "context_summary": "IWM: 60-day return history, mean=0.0024, std=0.0111.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0024, std=0.0111, min=-0.0244, max=0.0274\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-04] [\"Fitbit wins ruling in Jawbone patent dispute Patents invalidated, but trade-secret claims may continue A fight between two of the largest makers of fitness trackers just got smaller.\", \"Apple shares gain 0.7% to $95.85 to lead Dow gainers in early trade\", \"A.M. Funds Roundup: The ETF World\\u2019s Apple Conundrum\", \"Apple hires Google X\\u2019s co-founder for its health projects Apple hires Yoky Matsuoka, formally of Nest Labs and Quanttus Apple has hired Yoky Matsuoka, a Google X founder, who will report directly to COO Jeff Williams\", \"Fitbit Sold 21 Million Activity Trackers Last Year and No One Seems to Care; Plus, a Month with the Blaze Smartwatch\", \"European stocks end lower for 4th session in a row Eurozone PMI confirms flash reading European stock markets finished sharply lower on Wednesday, as investors assessed a mixed bag of corporate news, with shares in Dialog Semiconductor PLC and London Stock Exchange Group PLC dropping.\", \"Welcome to your Smart Future Investors need to open their minds to the possibilities of what future tech will bring, and along with it, great investment opportunities.\", \"Apple: Survey Says iPhone Demand to Recover, But Huawei, Oppo More \\u2018Aspirational,\\u2019 Says UBS UBS\\u2019s Steve Milunovich today offers up evidence from the firm\\u2019s \\u201cEvidence Lab\\u201d that there\\u2019s hope for a rise in Apple\\u2019s (AAPL) iPhone sales when it produces the next model of the device, presumably an \\u201ciPhone 7.\\\"Milunovich, who has a Buy rating on the shares, and a $120 price target, writes that his survey of 6,336 smartphone users in the U.S., U.K., Japan, Germany, and Mainland China, conducted online in March, found some improvement in sentiment for Apple\\u2019s wares.Milunovich\\u2019s report is actually contained in two notes.In the Apple-specific note, he writes of an improvement in the upgrade \\u201ccycle\\\" for the iPhone versus what many see as a lengthening of the time between when people buy a new iPhone, writing \\u201cin our fall survey we should have taken more seriously the two negatives: demand for the 6s was weaker than for the 6 and upgrade cycles slightly lengthened.\\\"The latest data \\\"finds a reversal,\\u201d he writes. \\\"interest in the iPhone 7 is better than for the 6s though not as strong as for the 6 and upgrade cycles appear shorter in the US and China though not in other countries.\\\"In the companion report on the survey itself, the intent of consumers has actually improved from that survey back in the fall, at least in the U.S. and China:\", \"Fitbit\\u2019s new products should propel the company through earnings Fitbit Blaze and Alta are big sellers Fitbit reports first-quarter earnings Wednesday, and analysts expect an easy beat.\", \"Apple CEO Cook: Bloomberg, Kass Explore the Credibility Gap (Update) A couple of individuals in the last 24 hours have offered some rebuttal to Apple (AAPL) CEO Tim Cook\\u2019s upbeat appearance Monday evening with Jim Cramer of CNBC on his \\u201cMad Money\\u201\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": "-0.0157", "answer_numeric": -0.015731, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0157 (i.e., on a bad day with 5% probability, the loss exceeds 1.57%). CVaR(95%) = -0.0199.", "metadata": {"var": -0.015731, "cvar": -0.019878, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20221214_0298", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2022-12-14", "context_summary": "QQQ: 60-day return history, mean=-0.0009, std=0.0179.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0009, std=0.0179, min=-0.0388, max=0.0340\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-13] [\"After Hours Most Active for Dec 13, 2022 : INTC, DIS, AMZN, AAPL, T, VZ, MSFT, HBAN, V, GOOGL, NIO, BEKE The NASDAQ 100 After Hours Indicator is down -5.33 to 11,828.88. The total After hours volume is currently 167,541,844 shares traded. The following are the most active stocks for the after hours session: Intel Corporation (INTC) is unchanged at $28.73, with 8,045,958 shares traded. INTC's current last sale is 95.77% of the target price of $30. Walt Disney Company (The) (DIS) is unchanged at $94.70, with 6,567,501 shares traded. As reported by Zacks, the current mean recommendation for DIS is in the \\\"buy range\\\". Amazon.com, Inc. (AMZN) is unchanged at $92.49, with 5,464,912 shares traded. As reported by Zacks, the current mean recommendation for AMZN is in the \\\"buy range\\\". Apple Inc. (AAPL) is unchanged at $145.47, with 5,404,084 shares traded. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". AT&T Inc. (T) is -0.01 at $19.11, with 5,064,573 shares traded. T's current last sale is 84% of the target price of $22.75. Verizon Communications Inc. (VZ) is unchanged at $37.86, with 4,827,699 shares traded. VZ's current last sale is 75.72% of the target price of $50. Microsoft Corporation (MSFT) is unchanged at $256.92, with 4,442,117 shares traded. As reported by Zacks, the current mean recommendation for MSFT is in the \\\"buy range\\\". Huntington Bancshares Incorporated (HBAN) is +0.02 at $14.23, with 3,910,414 shares traded. HBAN's current last sale is 91.81% of the target price of $15.5. Visa Inc. (V) is unchanged at $213.04, with 3,853,339 shares traded. As reported by Zacks, the current mean recommendation for V is in the \\\"buy range\\\". Alphabet Inc. (GOOGL) is -0.12 at $95.51, with 3,771,241 shares traded. As reported by Zacks, the current mean recommendation for GOOGL is in the \\\"buy range\\\". NIO Inc. (NIO) is +0.03 at $12.34, with 3,691,025 shares traded. As reported by Zacks, the current mean recommendation for NIO is in the \\\"buy range\\\". KE Holdings Inc (BEKE) is unchanged at $14.62, with 3,290,915 shares traded. As reported by Zacks, the current mean recommendation for BEKE 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.\", \"Apple prepares to allow alternative app stores on iPhones, iPads - Bloomberg News Dec 13 (Reuters) - Apple Inc AAPL.O is preparing to allow alternative app stores on its iPhones and iPads, Bloomberg News reported on Tuesday, citing sources familiar with the matter. Apple did not immediately respond to a Reuters request for comment. (Reporting by Eva Mathews in Bengaluru; Editing by Shounak Dasgupta) ((Eva.Mathews@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.\", \"Why Investors Cranked Spotify Stock Higher Today What happened A report indicated that the companies b\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": "-0.0293", "answer_numeric": -0.029315, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0293 (i.e., on a bad day with 5% probability, the loss exceeds 2.93%). CVaR(95%) = -0.0347.", "metadata": {"var": -0.029315, "cvar": -0.034748, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170824_0301", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2017-08-24", "context_summary": "FXI: 60-day return history, mean=0.0013, std=0.0092.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0013, std=0.0092, min=-0.0290, max=0.0209\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-08-23] [\"Apple\\u2019s $1 billion TV move pits company against Spotify, not Netflix Apple\\u2019s investment in producing and acquiring TV content should help it achieve plan to double its services business by 2020 Apple\\u2019s $1 billion investment to buy and produce original TV programming pits the technology giant against Spotify, not Netflix Inc. and Amazon.com Inc., according to analysts at RBC Capital Markets \\u2014 at least for now.\", \"Koch Stock Buys: Cisco, BlackBerry, Qualcomm A unit of Koch Industries also bought Alphabet shares, and initiated large positions in Vistra Energy and BKLN.\", \"Income Reading List: How Investors View Venezuelan, European Debt; Companies Paying Big Dividends A few headlines that might interest income investors.\", \"A Tech Crash Isn\\u2019t Coming, But You Should Expect A Pullback There are a number of problems with comparing today to the dot com meltdown, but markets could still fall back a bit.\", \"Factors to Favor: What the Technicals Say Ned Davis Research Group says lower volatility and higher quality are factors exhibiting favorable technicals.\", \"Samsung Seeks to Redeem, Renew With \\u2018Note 8\\u2032 Ahead of Apple\\u2019s iPhone Event Samsung's set to unveil its \\\"Note 8,\\\" a replacement of the infamous Note 7 that got banned on airplanes last year for exploding batteries.\", \"Apple phone sales appear to be steady ahead of September launch Sales of Apple's iPhones appear to have been \\\"resilient\\\" and sell through share appears steady last month, even as many consumers seem to be waiting for the new iPhone release in September, Canaccord Genuity analysts said Wednesday. They estimate that Apple Inc. brought in 64% of industry profits in July, helped by carrier promotions, but down from 84% in its March quarter. Apple's sales took a hit from Samsung's launch of the Galaxy S8 phone and steady results from Chinese phone companies. However, they see Apple's new cycle of iPhones in September bringing Apple to 46.5 million iPhone units sold and leading Apple to increase its market share in calendar year 2018. In addition to strong sales of Apple's iPhone 8, they expect strong sales of 7S Plus models. They maintained a buy rating and $180 price target. Shares of Apple have gained 6.4% in the past month, while the S&P 500 has lost 1%.\", \"Why Amazon Should Sweat Google\\u2019s Wal-Mart Deal While Amazon is still well ahead of its rivals, Google is ramping up efforts to gain share in retail and voice-activated devices.\", \"Investors Favor Facebook, Amazon, Alphabet Recent feedback indicates that bullish viewers of Facebook expect over 35% year-over-year growth in ad revenue.\", \"Apple\\u2019s Share of Smartphone Profits Dives The new iPhones are likely to reverse the trend, however, one analyst predicts.\", \"Samsung Redemption: \\u2018Note 8\\u2032 Its Most Elegant Device Yet Samsung Electronics unveils \\\"Note 8,\\\" a sleeker version of the phablet computer, which last year was a black mark for the company when the Note 7 model had i\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": "-0.0116", "answer_numeric": -0.011579, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0116 (i.e., on a bad day with 5% probability, the loss exceeds 1.16%). CVaR(95%) = -0.0198.", "metadata": {"var": -0.011579, "cvar": -0.019845, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150429_0304", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2015-04-29", "context_summary": "XLP: 60-day return history, mean=0.0004, std=0.0068.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0004, std=0.0068, min=-0.0197, max=0.0145\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-04-28] [\"5 Cheap Stocks James Hunt of Tocqueville Intl. has returned almost double his benchmark over 15 years. He sees better deals for investors overseas.\", \"Orange profit falls, but buoyed by iPhone sales Orange nevertheless reiterated its guidance of a slower drop in Ebitda in 2015, to between EUR11.9 billion and EUR12.1 billion from EUR12.19 billion for all of 2014.(\\\"IPhone Sales Help Orange Slow Revenue Slide,\\\" published at 0629 GMT, mistakenly said that guidance was for revenue in the ninth paragraph.\", \"Morgan Stanley raises Apple price target to $166 from $160\", \"Morgan Stanley says Apple is among its \\\"best idea\\\" stocks\", \"Mizuho lifts Apple price target to $125 from $115\", \"Susquehanna raises Apple price target to $155 from $150\", \"Apple stock price target raised to $195 from $180 at Cantor Fitzgerald\", \"Apple stock price target raised to $150 from $142 at RBC Capital\", \"Apple stock price target raised to $160 from $150 at BTIG\", \"Apple's stock up 1.4% premarket after Q2 results late Monday\", \"Apple's stock set to open at record highs Apple Inc.'s stock is rising 1.4% in premarket trade Monday, putting them on track to open at a fresh record high. The stock has traded within a range of up 1% at $134 to up 2.7% at $136.20 ahead of the open, after the technology giant reported better-than-expected fiscal second-quarter results after Monday's close. Apple's previous record highs were $133 on a closing basis on Feb. 23 and $133.60 on an intraday basis on Feb. 24. An open at current premarket levels would lift Apple's market capitalization to $783.72 billion, more than double the second-biggest U.S. company Microsoft at $388.5 billion.\", \"Here\\u2019s how much more Apple earns than everyone else The iPhone maker blew out its fiscal second quarter, with a profit of $13.6 billion The iPhone maker blew out its fiscal second quarter, with a profit of $13.6 billion, says Phil van Doorn.\", \"Why some are saying \\u2018Correction? Make my day\\u2019 Critical information ahead of the market\\u2019s open Apple may not be able to do the heavy lifting, and perhaps a correction should be welcomed. That\\u2019s in our Call of the Day.\", \"Apple shares rise 0.5% day after earnings release\", \"Apple's stock turns lower, down 0.3% in morning trade\", \"Apple's stock was up 1.4% at record intraday high of $134.54 earlier Tuesday\", \"Who else is miffed about Apple\\u2019s \\u2018very modest\\u2019 watch launch? CEO Tim Cook offers few details on biggest product rollout in five years CEO Tim Cook gave few details on the biggest product rollout in five years, writes Therese Poletti.\", \"Carl Icahn's $100 million profit on Apple may have turned into an $90 million loss Billionaire investor Carl Icahn may have watched the near $100 million one-day profit he could have been making on his Apple Inc. investment disappear into thin air, as the technology giant's stock erased an earlier rally to record highs. Icahn's New York hedge fund Icahn Associates is Apple's seventh-largest share\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": "-0.0093", "answer_numeric": -0.009335, "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%) = -0.0145.", "metadata": {"var": -0.009335, "cvar": -0.01449, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150511_0307", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2015-05-11", "context_summary": "USMV: 60-day return history, mean=0.0002, std=0.0065.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0002, std=0.0065, min=-0.0179, max=0.0136\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-05-08] Dow 30 Stock Roundup: Disney, Visa Beat, Chevron Reports Mixed Results - Analyst Blog The Dow went through another volatile week, losing for two consecutive days, while it moved up during other sessions. Stocks ended in the green for the second straight session on Monday boosted by a handful of upbeat earnings results. The Dow declined on Tuesday, dragged down by losses in technology, biotechnology and small-cap stocks. Markets ended in the red for the second consecutive day on Wednesday following Fed Chair Janet Yellen's comments that stock valuations are \"quite high.\" The Dow rebounded on Thursday following easing in bond yields and gains in technology stocks. The Dow has lost 0.5% during the first four trading days. LastWeek's Performance Last Friday, the Dow gained more than 1% as investors added beaten down stocks to their portfolios. Stocks from the health and technology sectors found favor. Apple Inc. AAPL boosted the tech sector and also the broader markets after gaining almost 3.1%. It was the biggest daily percentage gain since Jan this year. Investors also cheered positive US auto sales numbers. According to Autodata, April auto sales were at an annual rate of 16.45 million, better than 16.05 million in the year-ago period. ISM's April PMI was flat month on month at 51.5%. March's construction spending dropped 0.6% from February. However, April consumer sentiment rose to the second best level since 2007. Friday's robust gains could limit weekly losses. The Dow declined 0.3% over the week. Benchmarks ended in the red on Monday, Wednesday and Thursday, and were mixed on Tuesday. Each of the benchmarks had lost over 1% on Thursday, dragged by losses in technology and biotechnology stocks. The major disappointment last week was the weaker-than-expected GDP data. According to the \"advance\" estimate, first quarter GDP increased at an annual rate of 0.2%, less than the consensus estimate of an increase by 1%. On the other hand, Fed officials gave no clear guidance on the timing of interest rate hike, which did little to boost investor sentiment. Among other data, investors received discouraging report on consumer confidence. However, personal income improved marginally in April. Some major companies reported encouraging earnings numbers. The DowThisWeek Stocks ended in the green for the second straight session on Monday boosted by a handful of upbeat earnings results. New orders for manufactured goods increased 2.1% in March, its biggest rise in eight months. Meanwhile, president of the Federal Reserve Bank of Chicago, Charles Evans, said hiking federal funds rate won't be appropriate until next year due to weak first quarter economic reports. This increase in factory orders for March was in line with the consensus estimate. However, the underlying trend remains weak as the increase in new orders for manufactured goods was due to a 13.5% jump in transportation orders. Positive news emanating from Europe also added to the bullish sentiment. Th\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": "-0.0110", "answer_numeric": -0.011001, "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%) = -0.0145.", "metadata": {"var": -0.011001, "cvar": -0.014496, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200217_0312", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-02-17", "context_summary": "LINK-USD: 60-day return history, mean=0.0157, std=0.0471.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0157, std=0.0471, min=-0.0694, max=0.1653\nMarket regime: sideways\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": "-0.0375", "answer_numeric": -0.037454, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0375 (i.e., on a bad day with 5% probability, the loss exceeds 3.75%). CVaR(95%) = -0.0544.", "metadata": {"var": -0.037454, "cvar": -0.054358, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210512_0315", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-05-12", "context_summary": "DOT-USD: 60-day return history, mean=0.0027, std=0.0564.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0027, std=0.0564, min=-0.1220, max=0.1619\nMarket regime: sideways\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": "-0.0940", "answer_numeric": -0.09398, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0940 (i.e., on a bad day with 5% probability, the loss exceeds 9.40%). CVaR(95%) = -0.1137.", "metadata": {"var": -0.09398, "cvar": -0.113666, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20201013_0318", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2020-10-13", "context_summary": "XLK: 60-day return history, mean=0.0028, std=0.0172.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0028, std=0.0172, min=-0.0427, max=0.0321\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-10-12] [\"The American Dream: Bringing Factories Back to the U.S. Restoring the nation\\u2019s production prowess will be a long, hard slog. But it can be done, if companies, politicians, and investors get behind the effort.\", \"Apple's stock surges 2.9% premarket, ahead of iPhone launch event on Tuesday\", \"Dow jumps 114 points on gains for Apple Inc., Walgreens Boots shares\", \"Dow's 188-point climb highlighted by gains for Apple Inc., Goldman Sachs shares\", \"The earnings recession is back, and the pandemic has made it bigger The S&P 500 officially returned to an earnings recession with last quarter's results, and there does not seem to be much hope for a turnaround amid a world-wide pandemic.\", \"\\u2018HIPAA does not give you a get-out-of-jail-free card\\u2019: What the health-privacy law does (and doesn\\u2019t) protect Because President Donald Trump is receiving health care from a 'covered entity,' his information would be protected under the law, experts said.\", \"Dow climbs 262 points on gains for shares of Apple Inc., Walgreens Boots\", \"Dow up 337 points on gains in Apple Inc., Microsoft stocks\", \"Apple\\u2019s 5G iPhone launch has investors hoping for \\u2018unprecedented upgrade cycle\\u2019 Apple Inc. has pulled off a few product virtual launches during the COVID-19 crisis, and now the company is gearing up for the most important one yet.\", \"Nasdaq Composite stands less than 1% from exiting correction territory Monday afternoon The Nasdaq Composite Index on Monday afternoon was surging more than 3% higher, putting the technology-laden index within striking distance of exiting a plunge into correction territory produced back on Sept. 8. A drop of at least 10% for an asset from a recent peak is the commonly used definition on Wall Street for a correction, while putting in a new high after that decline is often viewed as that asset exiting that bearish phase of trading. The Nasdaq Composite sank into correction--after putting in its most recent record high on Sept. 2--early last month but is now nearing a new record peak above 12,056.44, putting the benchmark about 0.8% from its all-time high, according to FactSet data. The Nasdaq has been powered higher by a handful of stocks in its resurgence from its March lows and Monday's trade was no different, with Facebook Inc. Apple Inc. , Amazon.com [: AMZN], Netflix and Google parent Alphabet Inc. all rising sharply on the day. The contingent of stocks, known informally as FAANG (and sometimes including Microsoft Cor. , has helped to lift the broader market by dint of the market value those handful of those companies. The Nasdaq Composite was recently trading up 3.2% at 11,955, coming after brisk run-up for the index on Friday. The broader market also was gaining altitude briskly, with the Dow Jones Industrial Average [: DJIA] rising 1.1% and the S&P 500 index climbing 2% to 3,547. The S&P 500 had threatened to fall into correction, with a drop to 3,222.76 from its recent September peak, but managed to avoid a cl\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": "-0.0266", "answer_numeric": -0.026587, "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%) = -0.0390.", "metadata": {"var": -0.026587, "cvar": -0.039032, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210309_0321", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-03-09", "context_summary": "MATIC-USD: 60-day return history, mean=0.0373, std=0.1095.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0373, std=0.1095, min=-0.1717, max=0.3873\nMarket regime: sideways\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": "-0.0990", "answer_numeric": -0.099003, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0990 (i.e., on a bad day with 5% probability, the loss exceeds 9.90%). CVaR(95%) = -0.1393.", "metadata": {"var": -0.099003, "cvar": -0.13926, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190211_0324", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2019-02-11", "context_summary": "VLUE: 60-day return history, mean=-0.0012, std=0.0132.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0012, std=0.0132, min=-0.0356, max=0.0296\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-08] [\"If you own Apple, Amazon, Facebook or AMD, look out below Those shares have been bid up by the average investor, but buying could slow or even reverse Those shares have been bid up by the average investor, but buying could slow or even reverse.\", \"Hasbro Falls, Trade Worries Worsen, and Dow Is in Line for Another Loss U.S. stock markets were poised to open lower for a third consecutive day.\", \"The stock market dip? Keep buying, says Bank of America Merrill Lynch Critical information for the U.S. trading day Stocks are on track to end the week on a sour note. If you\\u2019re a fan of the \\u2018buy-the-dip\\u2019 strategy, our call of the day from Bank of America Merrill Lynch, along with our chart of a stoic S&P says now is not the time to give up.\", \"Cody Willard: I\\u2019m most bullish on Apple, Alphabet and Verizon Also reviewed today: Amazon, Intel, Palo Alto Networks, Facebook and Nvidia Also reviewed today: Amazon, Intel, Palo Alto Networks, Facebook and Nvidia.\", \"Amazon Investors Are Worried About Bezos Blackmail Case Shares of the e-commerce giant are down nearly 3% on Friday, in the wake of CEO Jeff Bezos\\u2019 startling revelations.\", \"GoPro predicts profit, thanks to years of massive layoffs Company expects to flip to profit in 2019 despite single-digit revenue growth, after chopping expenses with layoffs in 2017 and 2018 GoPro Inc. executives have been sounding bullish in the last two months, and Wednesday\\u2019s fourth quarter conference call was no exception, with a forecast for profitability in 2019 for the action camera maker, but its results were helped by past cost cutting and company layoffs.\", \"3 Stocks Bucking the Earnings Slowdown Most companies these days seem to beat earnings estimates. This is a screen for stocks whose earnings estimates have been rising in the first quarter. Boeing and two more favorites.\", \"AT&T\\u2019s 5G Act Is Bad for Everyone Wireless phone service is full of confusing labels, but AT&T\\u2019s latest \\u201c5GE\\u201d is raising new ire from consumers and industry rivals.\", \"Apple Gives New Retail Head Stock Grants Worth About $8 Million The Cupertino, California-based technology giant gave O\\u2019Brien two sets of 23,922 restricted stock units -- one group that will vest across three years beginning Aug. 5, 2021, and the other based on the company\\u2019s performance that may vest on Oct. 1, 2021, according to a regulatory filing. Each set is\", \"Apple isn't too happy about apps that secretly record your phone's screen Following TechCrunch's report that certain iOS apps are using technology from a company called Glassbox to record everything a user does within the app, Apple has started telling app developers that they either need to disclose this to users or face getting banned from the App Store. \\\"Our App\", \"Dow Jones Rout: The Cat is in the Bag, the Bag is in Trump\\u2019s Hand Friday started off badly for the Dow Jones industrial average, with all major stock indexes trading markedly lower right out o\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": "-0.0245", "answer_numeric": -0.024521, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0245 (i.e., on a bad day with 5% probability, the loss exceeds 2.45%). CVaR(95%) = -0.0292.", "metadata": {"var": -0.024521, "cvar": -0.02919, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190201_0327", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2019-02-01", "context_summary": "ADA-USD: 60-day return history, mean=0.0003, std=0.0583.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0003, std=0.0583, min=-0.1464, max=0.1406\nMarket regime: sideways\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": "-0.0924", "answer_numeric": -0.092423, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0924 (i.e., on a bad day with 5% probability, the loss exceeds 9.24%). CVaR(95%) = -0.1168.", "metadata": {"var": -0.092423, "cvar": -0.11684, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20171019_0330", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2017-10-19", "context_summary": "EEM: 60-day return history, mean=0.0011, std=0.0073.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0011, std=0.0073, min=-0.0240, max=0.0157\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-10-18] [\"Qualcomm CEO still expects NXP deal to close later this year Mollenkopf says of Apple dispute: \\u2018We\\u2019ll get through it\\u2019 Qualcomm Inc. said its $39 billion acquisition of NXP Semiconductors NV is on schedule to close by the end of the year, paving the way for it to be a major player in autonomous driving.\", \"Mizuho hikes Apple price target to $160 from $150, backs neutral rating\", \"Apple stock price target raised to $160 from $150 at Mizuho\", \"Apple's stock gains after Mizuho raises stock price target Apple Inc.'s stock edged up 0.2% in premarket trade Wednesday, putting them on track for a fourth-straight gain, after Mizuho analyst Abhey Lamba raised his stock price target to current levels, citing an improved outlook for average selling prices. Lamba boosted his target to $160, which is 0.3% below Tuesday's closing price, from $150, while keeping his rating at neutral. He expects Apple to report fiscal fourth-quarter results on Nov. 2 that are in line with expectations, but he raised his fiscal 2018 earnings estimates to account for higher ASPs associated with iPhone X shipments, and the shift of shipments from Q1 2018 to Q2 2018. His 2018 EPS estimate was raised to $10.67 from $9.60, while his revenue estimate was lifted to $267.9 billion from $238.5 billion. In June, Lamba had downgraded Apple to neutral and cut his target to $150 from $160, citing concerns that enthusiasm around the upcoming product cycle was fully captured by the stock's rally, with limited upside to estimates. Apple's stock has run up 6.9% over the past three months through Tuesday, while the tech-heavy Nasdaq 100 has gained 4.1% and the Dow Jones Industrial Average has climbed 6.6%.\", \"Apple partners with GE to bring predictive data and analytics to GE's IOT platform Predix\", \"GE to promote Apple's Mac as a choice for global workworce\", \"Apple to promote GE's Predix as the industrial IoT platform of choice\", \"Invest Like ExxonMobil: Sell Apple; Buy Walgreens The energy giant\\u2019s investment unit has trimmed nearly all of its 506 holdings. Here\\u2019s what it\\u2019s buying.\", \"GE and Apple partner on industrial Internet-of-Things platform General Electric Co. and Apple Inc. announced Wednesday a partnership aimed at bringing GE's industrial Internet of Things (IoT) platform Predix to Apple's iPhones and iPads. The companies will provide developers a new software development kit to make industrial IoT apps for Apple's operating system iOS. As part of the partnership, GE will standardize on iPhone and iPad for mobile devices, and promote Mac as a choice for its global workforce, while Apple will promote Predix as the industrial IoT analytics platform of choice for its customers and developers. \\\"Working together, GE and Apple are giving industrial companies access to powerful apps that help them tap into the predictive data and analytics of Predix right on their iPhone or iPad,\\\" said GE Chief Executive John Flannery. GE's stock edged up less than 0.1% in pre\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": "-0.0129", "answer_numeric": -0.012865, "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%) = -0.0181.", "metadata": {"var": -0.012865, "cvar": -0.018087, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210907_0333", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2021-09-07", "context_summary": "PDBC: 60-day return history, mean=0.0004, std=0.0122.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=0.0004, std=0.0122, min=-0.0309, max=0.0278\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": "-0.0236", "answer_numeric": -0.023565, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0236 (i.e., on a bad day with 5% probability, the loss exceeds 2.36%). CVaR(95%) = -0.0273.", "metadata": {"var": -0.023565, "cvar": -0.027254, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190130_0336", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2019-01-30", "context_summary": "FXI: 60-day return history, mean=0.0014, std=0.0147.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0014, std=0.0147, min=-0.0274, max=0.0411\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-29] [\"Apple Reports Earnings Today. Here\\u2019s What to Expect. Apple has said the quarter will be the first in which it stops reporting unit sales for the iPhone, iPad, and Mac, a decision some investors criticized.\", \"Today Is Apple\\u2019s Most Important Earnings Announcement in Years Apple opened a can of worms during its last earnings call. The stock is down 30% since then.\", \"Apple scrambles to fix eavesdropping FaceTime bug Feature linked to bug has been disabled The glitch, which was flagged on social media Monday, allows one FaceTime user calling another to listen in while the recipient\\u2019s Apple device is still ringing\\u2014even if the person never accepts the call.\", \"An Apple Videogame Subscription Service Makes Sense. Will It Happen? The notion got some fresh coverage just as the company is preparing to announce its latest quarterly financial results.\", \"Dow Futures Drop 29 Points Because Tensions With China Are Heating Up The U.S. formally charged Huawei late Monday. The market is also waiting for earnings from Apple and the Federal Reserve.\", \"Applied Materials Stock Gains, Square Drops and 3 More Tuesday Morning Movers Whirlpool and AK Steel were also in play.\", \"An earnings tsunami \\u2014 with 113 S&P 500 components \\u2014 marks \\u2018pivot point\\u2019 for stock market 13 Dow components are set to report this busy week Stock-market investors are bracing for the busiest week of the earnings season, in what could be a crucial stage in what has been a potent recovery from last year\\u2019s lows.\", \"Apple's stock gains 0.2% ahead of Q1 results after the close\", \"The global dominators you invest in when Apple and the chips are down Critical information for the U.S. trading day It\\u2019s a big earnings day for investors and the anxiety is running high. But even if Apple manages to disappoint investors further with results due later, these are your hip pocket backup stocks for when the chips are down.\", \"It\\u2019s time to \\u2018dismount\\u2019 from this stock-market rodeo, says Morgan Stanley\\u2019s Wilson The Fed abandoning its tightening regime could be a game changer, strategist writes Timing is everything and Morgan Stanley\\u2019s chief equity strategist Mike Wilson is telling investors that they need to get out of stocks right now even if the market still has some upside potential.\", \"Unpopular take: Giant tech companies should pay taxes The world needs a corporate tax system that is fit for the digital economy The world needs a corporate tax system that is fit for the digital economy and benefits developing and developed countries alike.\", \"Harley-Davidson hits rough road, and now all eyes move to Apple Earnings Watch: Verizon and Pfizer take impairment hits, AMD to report in Apple\\u2019s shadow Harley-Davidson Inc. expects a slow start to the year, and didn\\u2019t do so well last year either. In the afternoon, all eyes will be on Apple\\u2019s results, though some of the suspense is gone.\", \"Al Gore Bulks Up on Apple Stock The former \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": "-0.0208", "answer_numeric": -0.020783, "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%) = -0.0240.", "metadata": {"var": -0.020783, "cvar": -0.024014, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180503_0339", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2018-05-03", "context_summary": "LINK-USD: 60-day return history, mean=0.0017, std=0.0751.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0017, std=0.0751, min=-0.1934, max=0.1422\nMarket regime: sideways\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": "-0.1227", "answer_numeric": -0.122712, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1227 (i.e., on a bad day with 5% probability, the loss exceeds 12.27%). CVaR(95%) = -0.1925.", "metadata": {"var": -0.122712, "cvar": -0.192533, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220114_0342", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2022-01-14", "context_summary": "XLK: 60-day return history, mean=0.0006, std=0.0136.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0006, std=0.0136, min=-0.0312, max=0.0343\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-13] [\"Server Storage Market to grow by USD 54.68 bn from 2021 to 2026 | Evolving Opportunities with Citrix Systems Inc. and DataCore Software Corp. |17000+ Technavio Reports 43% of the growth will originate from North America for the server storage market. The US is a key market for server storage in North America. Market growth in this region will be faster than the growth of the market in Europe, MEA, and South America. The rising adoption of high-performance computing (HPC) systems in industry verticals, such as government, BFSI, and healthcare will facilitate the server storage market growth in North America over the forecast period. The server storage market is\", \"Turnip raises $12.5 million for its mobile-first gaming community platform Turnip, an Indian startup that is building a mobile-first gaming community platform, has raised $12.5 million in a new financing round to deepen its footprints in India and dozens of other countries and dabble with web3 as it looks to broaden its product offerings. Greenoaks and Elevation Capital co-led the one-and-a-half-year-old startup\\u2019s Series A round. SEA Capital, Vibe Capital and scores of entrepreneurs including Andrew Chen of Andreessen Horowitz, Sujeet Kumar of Udaan, Harshil Mathur and Shashank Kumar of Razorpay, Gaurav Munjal and Roman Saini of Unacademy, Lalit Keshre, Harsh Jain and Ishan Bansal of Groww, and Akshay Kothari of Notion also participated in the round.\", \"Apple details $30 million settlement for off-the-clock bag search lawsuit The long-running lawsuit Apple faced over off-the-clock bag searches of its employees in California is almost over.\", \"Apple's updated iCloud Private Relay notice clarifies why it might not work for some users After a previous iOS 15.2 update, some users found that they couldn't use Private Relay while on a cellular network.\", \"Changing How We Think about Difficult Patients: A Guide for Physicians and Healthcare Professionals Physicians enter their professions with the highest of hopes and ideals for compassionate and efficient patient care. Along the way, however, consistent problems arise in their interactions with difficult patients\\u2014some studies relate that physicians identify 15% or more of their patients as \\\"difficult.\\\" What's to be done about this widespread problem?\", \"'Fortnite' is returning to iPhone and iPad via NVIDIA GeForce Now A cloud version of the game for iOS and Android goes into closed beta next week.\", \"Copycats not allowed: Apple yanks knockoffs of viral puzzle game Wordle from App Store Apple said it has removed several apps ripping off the viral puzzle game Wordle. The tech giant did not say which apps were removed.\", \"Apple's third-gen AirPods drop to $140 at Amazon Amazon's latest sale knocks $40 off Apple's third-generation AirPods, bringing them down to a record low of $140.\", \"PUBG Mobile maker Krafton sues Apple, Google and rival game developer Garena over clones The lawsuit alleges Garena's games copy numerous aspects of i\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": "-0.0253", "answer_numeric": -0.02533, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0253 (i.e., on a bad day with 5% probability, the loss exceeds 2.53%). CVaR(95%) = -0.0287.", "metadata": {"var": -0.02533, "cvar": -0.028742, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200228_0345", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2020-02-28", "context_summary": "XLP: 60-day return history, mean=-0.0004, std=0.0067.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0004, std=0.0067, min=-0.0250, max=0.0118\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-02-27] [\"Apple's stock drops 2.8% premarket, after rising 1.6% Wednesday to snap 4-day losing streak\", \"With Microsoft\\u2019s coronavirus warning, PC and hardware makers are probably next The refrain about a \\u2018better second half\\u2019 will probably start up again Now that Microsoft, the world\\u2019s most valuable tech giant, has warned investors that its PC business will not meet its recent guidance because of the impact of the coronavirus on the supply chain, the rest of the PC universe will likely follow suit.\", \"Tesla crash report may lack enforcement power, but implications are real, analysts say Lawsuits, temporary Autopilot halt some of the possibilities, Evercore says Tesla Autopilot is often misused, and recent report by a government agency on a fatal crash involving the feature may lack real enforcement power, but the implications for Tesla Inc. could be far reaching, analysts at Evercore ISI said in a note Wednesday.\", \"Why the Fed can\\u2019t defend the economy against the coronavirus outbreak Rate cuts are effective against weak demand \\u2014 not shocks to global supply When people can\\u2019t go to work, the goods and services they normally produce can\\u2019t be supplied to a global market. The Fed can\\u2019t do a lot about that.\", \"Dow Inc., Walt Disney share losses lead Dow's nearly 550-point fall\", \"There\\u2019s not a lot the Fed can do about a coronavirus recession Lowering interest rates here won\\u2019t get factories back to work in China Calls for the Federal Reserve to cut interest rates in response to the coronavirus epidemic are misplaced at best and more likely downright dangerous.\", \"Coronavirus Is Slamming Stocks. The Jury Is Still Out on M&A Activity. Coronavirus fears are clearly weighing on the broad market, but it is still too soon to tell whether the disease will affect mergers and acquisitions, bankers said.\", \"Dow's 720-point drop led by losses for Boeing, Apple Inc. stocks\", \"U.S. economy grew a mild 2.1% in 4th quarter, but coronavirus threatens to reduce GDP even further Business investment was already weak before viral outbreak The economy expanded at a 2.1% pace at the end of 2019, but the U.S. might struggle to achieve even that modest rate of growth in the months ahead if a new strain of coronavirus isn\\u2019t contained.\", \"Nokia Stock Gives Back Gains as Skepticism Over Deal Talk Grows Nokia shares spiked 6.1% yesterday after Bloomberg reported that Nokia could consider merging or joining with Ericsson. Analysts who follow the company find the deal implausible.\", \"Dow down 618 points on losses in shares of Apple Inc., Dow Inc.\", \"Dow Inc., Apple Inc. share losses contribute to Dow's 237-point fall\", \"Dow's 560-point fall led by losses in Dow Inc., Apple Inc. shares\", \"Here\\u2019s why you\\u2019ll never see a bad guy with an iPhone in the movies \\u2018Knives Out\\u2019 director Rian Johnson alleges Apple has strict product placement standards \\u2018Knives Out\\u2019 director Rian Johnson alleges Apple has strict pro\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": "-0.0117", "answer_numeric": -0.011676, "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%) = -0.0222.", "metadata": {"var": -0.011676, "cvar": -0.022185, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20221010_0348", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2022-10-10", "context_summary": "PDBC: 60-day return history, mean=0.0003, std=0.0145.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=0.0003, std=0.0145, min=-0.0309, max=0.0278\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": "-0.0236", "answer_numeric": -0.023601, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0236 (i.e., on a bad day with 5% probability, the loss exceeds 2.36%). CVaR(95%) = -0.0279.", "metadata": {"var": -0.023601, "cvar": -0.027919, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220418_0351", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2022-04-18", "context_summary": "SOL-USD: 60-day return history, mean=0.0011, std=0.0517.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0011, std=0.0517, min=-0.1110, max=0.1637\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-17] \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": "-0.0837", "answer_numeric": -0.083707, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0837 (i.e., on a bad day with 5% probability, the loss exceeds 8.37%). CVaR(95%) = -0.1023.", "metadata": {"var": -0.083707, "cvar": -0.102252, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20201005_0354", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2020-10-05", "context_summary": "ETH-USD: 60-day return history, mean=-0.0011, std=0.0460.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0011, std=0.0460, min=-0.1365, max=0.0965\nMarket regime: sideways\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": "-0.0776", "answer_numeric": -0.077648, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0776 (i.e., on a bad day with 5% probability, the loss exceeds 7.76%). CVaR(95%) = -0.1130.", "metadata": {"var": -0.077648, "cvar": -0.112964, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170103_0359", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2017-01-03", "context_summary": "XLF: 60-day return history, mean=0.0028, std=0.0103.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0028, std=0.0103, min=-0.0145, max=0.0362\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-12-30] [\"Which Wall Street Firm Made The Best Stock Picks Of 2016?\", \"Which Wall Street Firm Made The Best Stock Picks Of 2016?\", \"7 Stocks Near 52 Week-High with More Room to Run The year 2016 will likely be remembered as one of the most eventful ones. An unexpected regime change, a long overdue interest rate hike and one of the fastest economic growth in recent times have surely made a mark. With President-elect Donald Trump taking office in 2017, the year is slated to be one wild roller coaster ride that can reward some and punish others. Meanwhile, the growing presence of high-valued stocks has made the market overvalued. In such a scenario, it may be na\\u00efve to invest in value stocks. Also, the prolonged slowdown in the global economy restricts the chances of further growth in the near term. At this point, it would be prudent to stack up on great momentum stocks. One such trend is spotting stocks that are at or above the 52-week high mark. The 52-week investment strategy is one of the relatively new entries in the investing rulebook. Borrowing from the basics of Momentum investing, this technique bets on the principle of buying high and selling higher. A wide group of investors today favor winning stocks with prospects of scaling higher. These investors have mastered the art of finding stocks that have strong upside potential and are still undervalued. Clubbing 52-week high stocks with the correct set of parameters is all you need to turn the tide in your favor. How Does it Work? Stocks near 52-week highs often instill the presumptive \\\"adjustment and anchoring bias\\\" in the minds of investors. This principle works on the belief that investors use the 52-week high price as a reference point and value stocks against this anchor. Many a times such stocks are prevented from scaling higher despite robust potential, due to the psychological bias of investors who fear that the stocks are overvalued and a price crash is impending. A few of the stocks remain undervalued due to prolonged under reaction on part of investors despite bullish growth drivers. Meanwhile, news pertaining to robust sales, surging profit levels, bullish earnings prospects and strategic acquisitions can drive the stock higher. However, when a string of positive developments start dominating the market, investors find their under-reaction unwarranted and the renewed interest might drive stocks beyond the 52-week high bar. Wall Street's fast paced trading makes it imperative for investors to step in before the market gets a whiff of it. Meanwhile, market gurus believe that the current price level rather than past changes in prices better reflect a stock's momentum. This implies that if a stock is trading close to its 52-week high range, chances are that it will perform better in the subsequent period. The Parameters to Rely on Our diligent screening technique has been deployed to find 52-week high stocks that hold tremendous potential compared to their respective industries. The add\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": "-0.0103", "answer_numeric": -0.010256, "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%) = -0.0124.", "metadata": {"var": -0.010256, "cvar": -0.012393, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20221202_0364", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2022-12-02", "context_summary": "DBA: 60-day return history, mean=-0.0008, std=0.0064.", "question": "Asset: DBA\nDaily returns (past 60 days): mean=-0.0008, std=0.0064, min=-0.0194, max=0.0132\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DBA. Express as a decimal (e.g., -0.02).", "answer": "-0.0079", "answer_numeric": -0.007922, "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%) = -0.0149.", "metadata": {"var": -0.007922, "cvar": -0.014874, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181212_0367", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-12-12", "context_summary": "XRP-USD: 60-day return history, mean=-0.0046, std=0.0417.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0046, std=0.0417, min=-0.0908, max=0.1092\nMarket regime: sideways\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": "-0.0788", "answer_numeric": -0.078768, "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%) = -0.0834.", "metadata": {"var": -0.078768, "cvar": -0.08345, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20201203_0370", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2020-12-03", "context_summary": "QUAL: 60-day return history, mean=0.0018, std=0.0120.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0018, std=0.0120, min=-0.0339, max=0.0240\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-12-02] [\"Are Microsoft And Adobe Coming For Salesforce's Market Share? Adobe (NASDAQ: ADBE) and Microsoft (NASDAQ: MSFT) have teamed up to take on customer relationship management (CRM), which has historically been Salesforce's (NYSE: CRM) domain. ProShares' Executive Director of Thematic Investing Scott Helfstein shares what investors need to know about how the COVID-19 pandemic has accelerated market trends in the cloud and how their new ETF ProShares MSCI Transformational Changes ETF (NYSEMKT: ANEW) is capitalizing on these transformations. 10 stocks we like better than Salesforce.com When investing geniuses David and Tom Gardner have 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.* David and Tom just revealed what they believe are the ten best stocks for investors to buy right now... and Salesforce.com 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 November 20, 2020 Corinne Cardina: Awesome. There are also a couple of more traditional tech stocks in the future of work part of the basket. Adobe, I think a lot of people, what comes to mind is Photoshop, Illustrator, InDesign. Microsoft people tend to think about their Office Suite, and Windows. What are some of the ways that these older tech companies are really transforming and how the pandemic has spurred that along? Scott Helfstein: Microsoft is a juggernaut. It's one that's hard for people to wrap their brain around, because it is so prominent. We work with the Office Suite, and Word, Excel, and our operating system. But they've taken a lot of their revenue into the cloud with subscription service. We see that cloud and productivity tools make up about two-thirds. It's really interesting that you talk about Microsoft and Adobe because they've actually announced a partnership a little while ago to take on customer relationship management. So CRM is a new segment, the two of them working in conjunction. By the way, Microsoft, as I think you were implying, also has a big gaming division with Xbox. As we think about virtualizing work, it's a little crazy to think about this. But what about the virtual reality coffee break? Or the virtual reality water cooler? There are some companies that are uniquely positioned to be able to facilitate a new and different remote working environment. Microsoft I think is one that investors should continue to pay attention to. Really important from a productivity standpoint, and Adobe as well. My 11-year-old wanted a subscription to Illustrator for his birthday this year. They are not just talking about PDFs, but they are important in secure document management. However, we've got Photoshop, we've got Illustrator, they also have an artificial intelligence product called Sensei, which actually helps people to do their graphic and document management. They're on the cutting edge of artificial\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": -0.016597, "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%) = -0.0242.", "metadata": {"var": -0.016597, "cvar": -0.024204, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210420_0373", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2021-04-20", "context_summary": "BTC-USD: 60-day return history, mean=0.0019, std=0.0373.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0373, min=-0.0993, max=0.0996\nMarket regime: sideways\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": "-0.0573", "answer_numeric": -0.057284, "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%) = -0.0769.", "metadata": {"var": -0.057284, "cvar": -0.076947, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20150409_0376", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2015-04-09", "context_summary": "HAUZ: 60-day return history, mean=0.0016, std=0.0100.", "question": "Asset: HAUZ\nDaily returns (past 60 days): mean=0.0016, std=0.0100, min=-0.0200, max=0.0268\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for HAUZ. Express as a decimal (e.g., -0.02).", "answer": "-0.0151", "answer_numeric": -0.015124, "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%) = -0.0166.", "metadata": {"var": -0.015124, "cvar": -0.016614, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210430_0379", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2021-04-30", "context_summary": "VLUE: 60-day return history, mean=0.0024, std=0.0104.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0024, std=0.0104, min=-0.0292, max=0.0261\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-04-29] [\"The SPAC boom isn't just here to stay, it's changing consumer tech Consumer technology is an inherently risky investment sector: even the best idea can fall flat if the story of the product is not sold properly to the end user. Traditionally, companies that have successfully told their story and become market leaders have taken the initial public offering route \\u2014 pitching their story to institutional investors on banker-led roadshows rather than to the people that buy their products. For the right consumer technology companies \\u2014 for which the story is often just as, if not more, important than the financial figures \\u2014 a SPAC deal offers a more direct access to public capital.\", \"All-New 11th Generation Civic Sedan Fully Revealed in Production Form with Sporty Design, Advanced Technology, Cutting-Edge Safety Features Honda today revealed the most fun-to-drive and technologically advanced Civic Sedan in the model's nearly 50-year history. The all-new 2022 Honda Civic boasts a clean, modern design paired with a high-tech, human-centered interior, and equipped with advanced active and passive safety systems. Previewed in November 2020 in prototype form, the 11th-generation Civic continues the tradition of innovation, design leadership and class-leading driving dynamics.\", \"China's Baidu to launch paid driverless ride-hailing services in Beijing China's tech giant Baidu will launch paid driverless robotaxi services in Beijing from May 2, the company said on Thursday, making it the first Chinese company to offer autonomous driving robotaxi services to paying users. Baidu's driverless Apollo Robotaxi, to be first launched in the Chinese capital's Shougang Park, will operate without a safety driver behind the steering wheel, Baidu said in a statement.\", \"FanDuel President expects to see more betting engagement during NFL Draft FanDuel president Amy Howe previewed NFL Draft gambling and the Kentucky Derby with Yahoo Finance.\", \"Amazon made more profit during the pandemic than in the past three years Amazon made more profit during the pandemic than in the past three years combined.\", \"Apple AirTags: Why they\\u2019re an easy sell for iPhone users who lose their keys Apple's AirTags are impressive little pieces of tech that are worth it for iPhone owners who frequently misplace things.\", \"Statement by the Prime Minister on the death of Thomas Berger The Prime Minister, Justin Trudeau, today issued the following statement on the death of former B.C. Supreme Court Justice Thomas Berger:\", \"Important Investor Reminder: Kessler Topaz Meltzer & Check, LLP Reminds 3D Systems Corp. Investors of Deadline in Securities Fraud Class Action Lawsuit The law firm of Kessler Topaz Meltzer & Check, LLP reminds investors that a securities fraud class action lawsuit has been filed against 3D Systems Corp. (NYSE: DDD) (\\\"3D Systems\\\") on behalf of those who purchased or acquired 3D Systems securities between May 6, 2020 and March 1, 2021, inclusive (the \\\"Class\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": "-0.0133", "answer_numeric": -0.013334, "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%) = -0.0231.", "metadata": {"var": -0.013334, "cvar": -0.023061, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20221124_0384", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-11-24", "context_summary": "ETH-USD: 60-day return history, mean=-0.0009, std=0.0445.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0445, min=-0.1593, max=0.1560\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-23] \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": "-0.0392", "answer_numeric": -0.039196, "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%) = -0.1240.", "metadata": {"var": -0.039196, "cvar": -0.123991, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20221107_0391", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2022-11-07", "context_summary": "IYR: 60-day return history, mean=-0.0033, std=0.0161.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=-0.0033, std=0.0161, min=-0.0339, 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": "-0.0271", "answer_numeric": -0.027113, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0271 (i.e., on a bad day with 5% probability, the loss exceeds 2.71%). CVaR(95%) = -0.0302.", "metadata": {"var": -0.027113, "cvar": -0.030245, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20221026_0394", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-10-26", "context_summary": "ETH-USD: 60-day return history, mean=0.0001, std=0.0349.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0001, std=0.0349, min=-0.0997, max=0.0867\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-25] \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": "-0.0554", "answer_numeric": -0.055369, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0554 (i.e., on a bad day with 5% probability, the loss exceeds 5.54%). CVaR(95%) = -0.0896.", "metadata": {"var": -0.055369, "cvar": -0.089598, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20220628_0399", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2022-06-28", "context_summary": "IWM: 60-day return history, mean=-0.0022, std=0.0193.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0022, std=0.0193, min=-0.0371, max=0.0312\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-27] [\"CEOs will look past abortion bans, too Reuters Reuters NEW YORK (Reuters Breakingviews) - The demolition of the constitutionally protected right to an abortion in the United States is historic. But for companies doing business in America, the cost-benefit analysis it provokes will feel familiar. Corporate bosses will end up viewing America\\u2019s illiberal states the way they do any emerging market. Each state will be left to decide how and whether to regulate abortion after the Supreme Court on Friday decided that protections of \\u201clife, liberty, or property\\u201d don\\u2019t include ending a pregnancy as a right. At least eight states had already banned the procedure by Monday, and around half of the 50 are primed to outlaw it under statutes already in place. Removing access to abortion could increase maternal deaths https://read.dukeupress.edu/demography/article/58/6/2019/265968/The-Pregnancy-Related-Mortality-Impact-of-a-Total by over one-fifth, according to Duke University, and Black maternal deaths by one-third. Recognizing the anxiety, companies have moved to reassure their staff: Facebook owner Meta Platforms and Goldman Sachs are among those offering to fund travel costs for employees who need to go out of state for healthcare and reproductive services. But if the majority of Americans https://www.cbsnews.com/news/americans-react-to-roe-v-wade-overturn-opinion-poll-2022-06-26 who oppose the overturning of Roe vs. Wade hope their large, powerful employers will do more, they will be disappointed. Multinationals long ago made peace with setting up shop in locations where freedoms taken for granted in some countries are limited in the name of stability or ideology. Foreign direct investment into China surged by a third to $344 billion last year, according to Peterson Institute for International Economics. Net foreign investment in Saudi Arabia jumped more than threefold in 2021, according to state media. China and states like Texas are in that way somewhat similar. The Lone Star state offers low taxes, good universities, rich natural resources, and scale. Accepting bans on abortion is simply the cost of doing business for companies like Goldman Sachs and Apple. So is turning a blind eye to the governing Texas Republican Party\\u2019s recent declaration that \\u201chomosexuality\\u201d is \\u201can abnormal lifestyle choice https://texasgop.org/wp-content/uploads/2022/06/6-Permanent-Platform-Committee-FINAL-REPORT-6-16-2022.pdf,\\u201d an awkward reality for companies that trumpet their commitment to diversity. Emerging-market attitudes don\\u2019t always create economic success for nations \\u2013 or states. Mississippi, for example, has no Fortune 500 companies headquartered within its borders. It\\u2019s also the state with the least well-functioning healthcare system https://www.commonwealthfund.org/publications/scorecard/2022/jun/2022-scorecard-state-health-system-performance in the country, according to the Commonwealth Fund. Even then, the\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": "-0.0371", "answer_numeric": -0.037067, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0371 (i.e., on a bad day with 5% probability, the loss exceeds 3.71%). CVaR(95%) = -0.0371.", "metadata": {"var": -0.037067, "cvar": -0.037067, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200904_0402", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2020-09-04", "context_summary": "BNO: 60-day return history, mean=0.0023, std=0.0157.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=0.0023, std=0.0157, min=-0.0504, max=0.0293\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": "-0.0205", "answer_numeric": -0.020486, "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%) = -0.0339.", "metadata": {"var": -0.020486, "cvar": -0.033879, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210922_0407", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2021-09-22", "context_summary": "IVV: 60-day return history, mean=0.0003, std=0.0062.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0003, std=0.0062, min=-0.0170, max=0.0144\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-21] [\"Over 2 Billion Devices Will be Shipped with a Dedicated Chipset for Ambient Sound or Natural Language Processing By 2026 Natural Language Processing (NLP) and ambient sound processing are traditionally considered exclusive cloud technologies and this has restricted their adoption in markets where security, privacy, and service continuity are critical elements for deployment. However, the advancements in deep learning compression technologies and edge Artificial Intelligence (AI) chipsets are now enabling these technologies to be integrated at the end-device level, which could mitigate security and privacy concerns\", \"PDMR Shareholding Notification of Transactions by Persons Discharging Managerial Responsibilities and Persons Closely Associated with them [This form is required for disclosure of transactions under Article 19 of Regulation (EU) No 596/2014 of the European Parliament and of the Council of 16 April 2014 on market abuse (Market Abuse Regulation)] 1Details of the person discharging managerial responsibilities/person closely associated a)NameAndrew Sheen 2Reason for the notification a)Position/statusPDMR / Managing D\", \"Apple adds new personalized recommendations in Podcasts' Listen Now page Apple has introduced new sharing and personalized recommendation features for Podcasts on iOS 15.\", \"Google\\u2019s updated iOS 15 apps support Focus Mode and iPad widgets One of those is Google, which detailed today the iOS 15-related enhancements you can expect from its apps. The biggest change involves how Gmail, Meet, Tasks, Maps, Home and many of Google's other applications will handle notifications. Should you have iOS 15\\u2019s new Focus Mode enabled, Google says prompts that don\\u2019t require your immediate attention will go to the Notifications Center where you can deal with them later.\", \"iPhone 13 and 13 mini review Should you get the iPhone 13 and 13 mini? Depends on how badly you want the new camera features and upgraded battery.\", \"Marvel shows are now available through Apple Podcast subscriptions Marvel and SiriusXM have opened a new Apple Podcasts channel, which includes a paid tier. The free Marvel channel includes Marvel's Wolverine: The Long Night and the sequel, Marvel's Wolverine: The Lost Trail. You'll be able to listen to Marvel/Method, in which Method Man interviews celebrities about Marvel, and This Week in Marvel, a weekly show about the latest news in the company's ecosystem.\", \"The iPhone 13 Pro goes to Disneyland This year\\u2019s iPhone review goes back to Disneyland for the first time in a couple of years for, uh, obvious reasons. One of the major reasons I keep bringing these iPhones back to Disneyland is that it\\u2019s pretty much the perfect place to test the improvements Apple claims it is making in an intense real-world setting. In my testing, most of Apple\\u2019s improvements actually had a visible impact on the quality of life of my trip, though in some cases not massive.\", \"Dynamic head tracking is now availabl\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": -0.009747, "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%) = -0.0143.", "metadata": {"var": -0.009747, "cvar": -0.014299, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201027_0410", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2020-10-27", "context_summary": "DOT-USD: 60-day return history, mean=-0.0012, std=0.0590.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0012, std=0.0590, min=-0.1989, max=0.1643\nMarket regime: sideways\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": "-0.1001", "answer_numeric": -0.100069, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1001 (i.e., on a bad day with 5% probability, the loss exceeds 10.01%). CVaR(95%) = -0.1424.", "metadata": {"var": -0.100069, "cvar": -0.142437, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190926_0413", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2019-09-26", "context_summary": "XLB: 60-day return history, mean=-0.0002, std=0.0104.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0002, std=0.0104, min=-0.0322, max=0.0204\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-09-25] [\"Google apologizes, promises to give users more control over how and when it stores voice recordings \\u2018It\\u2019s clear that we fell short of our high standards in making it easy for you to understand how your data is used, and we apologize,\\u2019 the company said \\u2018It\\u2019s clear that we fell short of our high standards in making it easy for you to understand how your data is used, and we apologize,\\u2019 the company said.\", \"McDonald\\u2019s enlists Alexa and Google to help with its hiring Starting Wednesday, McDonald\\u2019s Corp. will let job seekers start an application by using voice commands with Amazon\\u2019s Alexa or Google\\u2019s Assistant.\", \"Netflix stock falls again as the previous most-bullish analyst slashes price target Shares have turned negative this year, and have broken below a long-term uptrend line Shares of Netflix Inc. sank again Tuesday, enough to turn negative for this year, after the previously most-bullish analyst slashed his price target to below the Wall Street average, citing expectations that the path to profitability will take longer than expected.\", \"How to know which retailers will take the biggest hit from a trade war The trade war between the U.S. and China continues, so here are three tips to prepare and secure your portfolio.\", \"Amazon pilots health care program with virtual, in-home options; Teladoc's stock falls Amazon.com Inc. has launched recently its Amazon Care pilot program for employees in the Seattle area, allowing for virtual and in-home care and prescription deliveries. Employees who are at least 18 years old, are currently enrolled in an Amazon health insurance plan and live and work within current service locations are eligible for the program, the e-commerce and cloud giant said. Shares of telehealthcare provider Teladoc Health Inc. dropped 7.0% in premarket trading, after shedding 1.7% on Tuesday. The company said employees who are enrolled in Kaiser Permanente are unable to participate at this time. Amazon Care options include Care Chat, which connects users with a nurse; Video Care, which provides a \\\"video visit\\\" with a doctor or nurse practitioner; Mobile Care, in which a nurse can be dispatched to the user's home or office; and Care Courier, in which prescriptions can be delivered to a user's home or office. Amazon's stock, which slipped 0.3% in premarket trading, has gained 16.0% year to date through Tuesday. In comparison, the SPDR Health Care Select Sector ETF has tacked on 4.8% this year and the S&P 500 has advanced 18.3%.\", \"Teladoc's stock sinks but analyst says buy, as Amazon Care seen as a 'major long-term tailwind' Shares of Teladoc Health Inc. sank 7.0% in premarket trading Wednesday, in the wake of Amazon.com Inc. launching a pilot health care program that includes virtual and in-home care options. SVB Leerink analyst Daniel Grosslight said that while Amazon's new program may be perceived as a negative, he believes it is actually a \\\"major [long-term] tailwind\\\" for Tel\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": "-0.0167", "answer_numeric": -0.016662, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0167 (i.e., on a bad day with 5% probability, the loss exceeds 1.67%). CVaR(95%) = -0.0252.", "metadata": {"var": -0.016662, "cvar": -0.025222, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20171117_0420", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2017-11-17", "context_summary": "XLE: 60-day return history, mean=0.0014, std=0.0066.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0014, std=0.0066, min=-0.0163, max=0.0226\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-11-16] [\"Will New Technologies Help Agilent (A) Beat on Q4 Earnings? Agilent Technologies A is set to report fiscal fourth-quarter 2017 results on Nov 20. Last quarter, it delivered a positive earnings surprise of 13.46%. The company's surprise history has been pretty impressive. It beat estimates in each of the trailing four quarters, with an average positive earnings surprise of 13.98%. Notably, on a year-to-date basis, Agilent's shares have returned 47.8%, underperforming the industry 's gain of 49.6%. Strength in ACG Segment to Drive Revenues In the last reported fiscal third quarter, the Agilent Cross Lab Group (ACG) segment contributed 35% of total third-quarter revenues, reflecting an increase of 7% year over year. The figure is expected to further increase in the upcoming quarter, driven by strength in services and consumables across all geographical regions. The Zacks Consensus Estimate for the upcoming quarter is pegged at $392 million. Strength in DGG & LSAG a Big Positive In the last quarter, revenues from Diagnostics and Genomics Group (DGG) came in at $197 million. The segment was up 9% year over year, driven by strength in pharma, diagnostic and clinical end-markets. All businesses under this group (Dako, Genomics and Nucleic Acid Solutions) performed well. The segment is expected to perform well in the upcoming quarter too. The Zacks Consensus Estimate for the fiscal fourth quarter is pegged at $207 million. Also, the Life Sciences & Applied Markets Group (LSAG) segment is expected to perform well in the upcoming quarter driven by strong performances in chemical and energy, pharma and environmental markets. The Zacks Consensus Estimate for the fiscal fourth quarter is pegged at $569 million. Other Growth Drivers Agilent Technologies is a broad-based OEM of test and measurement equipment. The company has shifted its focus to life sciences, genomics, diagnostics and wireless test markets, in which it has made a few important acquisitions and alliances. Agilent's broad-based portfolio and increased focus on segments offer higher growth potential. The company's decision to divest/wind up underperforming businesses has enhanced its focus on the new Agilent, while enabling expansion of a solid recurring revenue base and diversification of geographic and industrial operations for growth. Also, the company's focus on aligning investments toward more attractive growth avenues and innovative product launches is a positive. The company's solid market position, acquisition strategy and increased focus on segments with growth potential remain major growth drivers. What Our Model Suggests According to the Zacks model, a company with a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold) has a good chance of beating estimates if it also has a positive Earnings ESP . Zacks Rank #4 (Sell) or 5 (Strong Sell) stocks are best avoided, especially if these have a negative Earnings ESP. You can uncover the best stocks to buy or sell before they're reported with our\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": "-0.0086", "answer_numeric": -0.008593, "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%) = -0.0128.", "metadata": {"var": -0.008593, "cvar": -0.012775, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220126_0423", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["STIP"], "decision_date": "2022-01-26", "context_summary": "STIP: 60-day return history, mean=0.0000, std=0.0015.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0000, std=0.0015, min=-0.0038, max=0.0034\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": "-0.0026", "answer_numeric": -0.002574, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0026 (i.e., on a bad day with 5% probability, the loss exceeds 0.26%). CVaR(95%) = -0.0034.", "metadata": {"var": -0.002574, "cvar": -0.003375, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170207_0426", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2017-02-07", "context_summary": "IAU: 60-day return history, mean=-0.0007, std=0.0086.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=-0.0007, std=0.0086, min=-0.0223, max=0.0152\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": "-0.0146", "answer_numeric": -0.014648, "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%) = -0.0211.", "metadata": {"var": -0.014648, "cvar": -0.021148, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220721_0429", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2022-07-21", "context_summary": "BNDX: 60-day return history, mean=-0.0001, std=0.0041.", "question": "Asset: BNDX\nDaily returns (past 60 days): mean=-0.0001, std=0.0041, min=-0.0064, 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": "-0.0063", "answer_numeric": -0.006339, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0063 (i.e., on a bad day with 5% probability, the loss exceeds 0.63%). CVaR(95%) = -0.0064.", "metadata": {"var": -0.006339, "cvar": -0.006363, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20221020_0432", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2022-10-20", "context_summary": "DOT-USD: 60-day return history, mean=-0.0024, std=0.0305.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0305, min=-0.0875, max=0.0642\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-19] \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": "-0.0660", "answer_numeric": -0.066037, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0660 (i.e., on a bad day with 5% probability, the loss exceeds 6.60%). CVaR(95%) = -0.0813.", "metadata": {"var": -0.066037, "cvar": -0.081282, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20210810_0435", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-08-10", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0007, std=0.0707.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0007, std=0.0707, min=-0.2144, max=0.2868\nMarket regime: sideways\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": "-0.0863", "answer_numeric": -0.086269, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0863 (i.e., on a bad day with 5% probability, the loss exceeds 8.63%). CVaR(95%) = -0.1572.", "metadata": {"var": -0.086269, "cvar": -0.157184, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20151006_0439", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2015-10-06", "context_summary": "ICSH: 60-day return history, mean=-0.0001, std=0.0008.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=-0.0001, std=0.0008, min=-0.0020, max=0.0034\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": "-0.0016", "answer_numeric": -0.001599, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0016 (i.e., on a bad day with 5% probability, the loss exceeds 0.16%). CVaR(95%) = -0.0018.", "metadata": {"var": -0.001599, "cvar": -0.001759, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190809_0442", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2019-08-09", "context_summary": "MTUM: 60-day return history, mean=0.0012, std=0.0087.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0012, std=0.0087, min=-0.0312, max=0.0206\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-08-08] 4 Safe Stocks to Buy Amid Trade War Turbulence The U.S.-China trade war is on and that makes finding good, safe stocks to buy much more difficult than before. Over the past few months there was a semantics debate over what exactly the trade tensions between the U.S. and China should be labeled as. Is it a full blown trade war? Or is it just a trade dispute, or trade skirmish? Today, that question seems fully answered. U.S. President Donald Trump upped the ante in early August by promising to introduce a 10% tariff on $300 billion worth of Chinese goods by September. China responded in force, suspending the purchase of new U.S. agricultural products and devaluing its own currency to decade lows against the U.S. Dollar. As such, there\u2019s no question about it. With both sides upping the ante to much more serious levels than before, the U.S.-China trade war is fully here. Stocks dropped in response. Big time. In just a few trading days, the S&P 500 dropped more than 5%. As of this writing, it looks likely that the market\u2019s decline will run into 10%-plus territory within the next few trading days. Thus, in a matter of a few trading days, stocks have gone from making new all-time highs, to being in correction territory. That is the definition of volatility. And when volatility comes roaring back into markets, investors flock to safety. Common financial safe havens included Treasuries (which have been rally in mode) and gold (which just made a six year high). Another financial safe haven is the class of high quality, high moat, big that won\u2019t be hit hard by this trade war drama. As such, I fully expect those \u201csafe stocks\u201d to out-perform so long as trade war drama hangs around. Which stocks fall into the safety stocks category? Let\u2019s take a closer look at four safe stocks to buy amid the recent trade war turbulence. Safe Stocks to Buy Amid Trade Turbulence: AT&T (T) Source: Shutterstock The first safety stock on this list is a telecom giant with a big yield, stable operations, minimal trade war exposure and huge forthcoming catalysts on the horizon. AT&T (NYSE:) is one of America\u2019s largest telecom companies. As a U.S. telecom giant, AT&T\u2019s operations won\u2019t be disrupted by a trade war. Consumers will still need internet service and mobile coverage, and will be willing to pay up for it so long as labor conditions remain favorable (which they do). Furthermore, T stock has a 6% yield which: 1) is pretty much higher than every other blue-chip yield in the market, and 2) looks really attractive next to a 10-Year Treasury yield that is below 2%. Also of note, AT&T has huge catalysts on the horizon that could breathe life back into this sluggish stock. First, AT&T is set to launch HBO Max soon, and this streaming service has enough content firepower from the Time Warner acquisition to make noise in the streaming landscape. If so, AT&T could pivot its negative cord-cutting narrative, into a positive streaming sub growth narrative. That will put upward pressure on \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": "-0.0105", "answer_numeric": -0.010482, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0105 (i.e., on a bad day with 5% probability, the loss exceeds 1.05%). CVaR(95%) = -0.0194.", "metadata": {"var": -0.010482, "cvar": -0.019403, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200625_0445", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2020-06-25", "context_summary": "XLRE: 60-day return history, mean=0.0002, std=0.0217.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0002, std=0.0217, min=-0.0375, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-24] [\"European stocks in the red as investors fret about rising U.S. Covid-19 infections Cluster of M&A news and weakness by drug groups marks trading European stocks traded lower on Wednesday, as markets struggled to gain traction against a backdrop of rising coronavirus cases in the U.S. Technology stocks were a bright spot after another record session for the Nasdaq Composite\", \"Apple's stock slips 0.7% premarket, after rallying 4.8% the past 2 days to Tuesday's record close\", \"Apple Chip Supplier Upgrades Outlook on Lockdown Demand Apple chip supplier Dialog Semiconductor raised its revenue outlook on Wednesday, citing strong demand for tablets and wearable products\", \"Barron\\u2019s Daily: Even the Nasdaq Is Falling as Covid Spike Spurs Demand for Stay-at-Home Stocks A new stimulus bill could pass in July, Covid-19 testing will increase in the U.S., tech stocks reach new highs, and other news to start your day.\", \"Apple stock falls after report says Justice Department looking at App Store investigation Apple Inc. could face heightened antitrust scrutiny in the U.S. as the Department of Justice and state attorneys general are looking at an investigation that would focus on the company's App Store, according to a Politico report. European regulators also have investigations underway that look into Apple's App Store and Apple Pay practices. Apple takes a cut of revenue when users make in-app purchases of digital services through third-party apps, which some developers have criticized as anticompetitive and arbitrary. The European investigation of Apple Pay will examine Apple's control over the NFC reader on iPhones, which enables contactless payments. The company has restricted the way third parties can tap into this technology. Apple shares are off 0.6% in premarket trading Wednesday. The stock has gained 48% over the past three months as the Dow Jones Industrial Average has risen 26%.\", \"Facebook, Microsoft, Zoom, More Software Stocks Get a Lift Goldman Sachs technology analyst Heather Bellini does a deep dive on valuation for the stocks she covers, in the process lifting her targets for a slew of familiar software names.\", \"Apple acquires security company Fleetsmith Apple Inc. has acquired security company Fleetsmith, according to a blog post on the Fleetsmith website. Fleetsmith helps with device setup and security patching for Apple devices including Macs and iPhones that are used in enterprise settings. The company's tools help businesses automatically set up Apple devices for new employees and manage fleet-wide issues in a single place. \\\"Our shared values of putting the customer at the center of everything we do without sacrificing privacy and security, means we can truly meet our mission, delivering Fleetsmith to businesses and institutions of all sizes, around the world,\\\" Fleetsmith said of the Apple deal. Apple didn't immediately respond to a MarketWatch request for comment. Terms of the deal weren't disclosed in the Fleetsmith post. App\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": "-0.0375", "answer_numeric": -0.037529, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0375 (i.e., on a bad day with 5% probability, the loss exceeds 3.75%). CVaR(95%) = -0.0375.", "metadata": {"var": -0.037529, "cvar": -0.037529, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20221116_0447", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2022-11-16", "context_summary": "VLUE: 60-day return history, mean=-0.0000, std=0.0158.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0000, std=0.0158, min=-0.0356, max=0.0296\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-15] [\"US STOCKS-Wall Street jumps on growing evidence of easing inflation By Amruta Khandekar and Ankika Biswas Nov 15 (Reuters) - Wall Street's main indexes jumped on Tuesday as growing evidence of cooling inflation bolstered hopes of smaller rate hikes by the Federal Reserve, while Walmart's upbeat forecast powered gains in retail sector. Data showed U.S. producer prices increased less than expected, rising 8% in the 12 months through October against an estimated 8.3% rise, according to a Reuters poll of economists. The report follows a softer-than-expected consumer prices reading late last week, which sparked a massive rally on hopes that the Fed would tone down its aggressive monetary policy approach that has roiled markets this year. Following the latest data, traders' bets of a 50-basis points rate hike in December surged to 91% compared with 71.5% last week. FEDWATCH \\\"Going into the final months of the year, this (the inflation data) gives the Fed a chance to go from at least 75 to 50 basis points and potentially even further,\\\" said Phil Blancato, chief executive of Ladenburg Thalmann Asset Management in New York. Shares of Walmart Inc WMT.N jumped 7% after the top U.S. retailer lifted its annual sales and profit forecasts, benefiting from a steady demand for groceries despite higher prices. Its results boosted stocks of other major retailers, including Target Corp TGT.N and Costco COST.O. Target will report results on Wednesday. Home Depot Inc HD.Nleft its annual forecasts unchanged, but the home improvement chain's results exceeded Wall Street expectations and shares rose 1.6% amid a jump in shares of retailers. Among the S&P 500 sectors, consumer staples was up .SPLRCS 1.2%, while the consumer discretionary .SPLRCD index jumped 1.9%. Boosting the Nasdaq .IXIC, shares of megacap technology and other growth stocks such as Apple AAPL.O, Microsoft Corp MSFT.O and Alphabet GOOGL.O rose between 1% and 3%. Focus was also on comments from policymakers, after Fed Vice Chair Lael Brainard and Governor Christoper Waller in recent days emphasized on the need to keep raising rates to rein in inflation. Atlanta President Raphael Bostic echoed the views, saying he sees little evidence that the central bank's aggressive monetary policy tightening is slowing inflation. At 12:41 a.m. ET, the Dow Jones Industrial Average .DJI was up 164.48 points, or 0.49%, at 33,701.18, the S&P 500 .SPX was up 51.46 points, or 1.30%, at 4,008.71, and the Nasdaq Composite .IXIC was up 253.48 points, or 2.26%, at 11,449.70. U.S.-listed shares of Chinese firms including JD.Com JD.O, Alibaba Group Holding BABA.N rose between 7% and 12% after President Joe Biden and Chinese leader Xi Jinping's meeting on Monday where they pledged more frequent communications. U.S.-listed shares of Taiwan Semiconductor Manufacturing TSM.N jumped 12.2% after Warren Buffett's Berkshire Hathaway BRKa.Nbought more than $4.1 billion of stock in the company. Advancing issues outnumbered decliners by a\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": "-0.0217", "answer_numeric": -0.021657, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0217 (i.e., on a bad day with 5% probability, the loss exceeds 2.17%). CVaR(95%) = -0.0306.", "metadata": {"var": -0.021657, "cvar": -0.030568, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210217_0450", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2021-02-17", "context_summary": "BTC-USD: 60-day return history, mean=0.0127, std=0.0470.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0127, std=0.0470, min=-0.1328, max=0.1157\nMarket regime: sideways\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": "-0.0605", "answer_numeric": -0.060541, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0605 (i.e., on a bad day with 5% probability, the loss exceeds 6.05%). CVaR(95%) = -0.0904.", "metadata": {"var": -0.060541, "cvar": -0.090397, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200128_0453", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2020-01-28", "context_summary": "USMV: 60-day return history, mean=0.0010, std=0.0037.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0010, std=0.0037, min=-0.0072, max=0.0079\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-01-27] [\"All 30 Dow stocks are falling, with Apple and Boeing the biggest drags All 30 of the Dow Jones Industrial Average's components are falling in premarket trading Monday, as the anxiety grows over the spreading of the corovnavirus that originated from China. Dow future tumbled 424 points. The biggest drags on the Dow, which is a price-weighted index, are the selloffs in the shares of Apple Inc. and Boeing Co. . Apple's stock fell 2.5%, while the implied price decline was shaving about 54 points off the Dow's price. Boeing's stock dropped 2.2%, and was reducing the Dow's price by about 48 points. There have been reports about events surrounding a Boeing-built plane in Afghanistan, but the company has not immediately responded to a request for comment.\", \"Apple stock price target raised to $290 from $280 at Deutsche Bank\", \"Apple's price target raised at Deutsche Bank, but it implies a 9% decline Apple Inc.'s stock price target was raised to $290 from $280 at Deutsche Bank, but that new target is still 8.9% below Friday's closing price of $318.31, as analyst Jeriel Ong reiterated his hold rating. Ong said he raised his price target because he expects iPhone unit demand to be better than Wall Street currently expects. \\\"However, the significant intra-quarter stock price move...is unlikely to be matched commensurately by the improved fundamentals, and we expect [Apple] to normalize at a higher valuation,\\\" Ong wrote in a note to clients. \\\"In our view, such a setup bodes poorly for investors who consider what to do with their [Apple] holdings from present levels.\\\" He said the recent sharp run up in the stock creates a setup where risks remain balanced with the potential reward. Apple shares have run up 29.1% over the past three months through Friday, while the Dow Jones Industrial Average has gained 7.5%. Apple's stock fell 2.0% in premarket trading, amida sharp selloff in the broader market, with Dow futures down set to open down over 400 points.\", \"This money manager says growth stocks are still your best play, and he has the math to back it up Tom Plumb of Wisconsin Capital Management says growth-stock valuations aren\\u2019t overly high and expects investors to keep paying up for the most successful companies Tom Plumb of Wisconsin Capital Management says growth-stock valuations aren\\u2019t overly high and expects investors to keep paying up for the most successful companies.\", \"Apple stock price target raised to $300 from $296 at J.P. Morgan\", \"Dow down 414 points on losses for American Express, UnitedHealth stocks\", \"Coronavirus Fears Are Hitting the Dow Hard. Travel Stocks, Chip Makers Are Plunging. U.S. stocks slumped as investors evaluate the latest news about China\\u2019s coronavirus outbreak. Haven investments such as gold are getting a boost.\", \"Your 6-point plan to navigating a choppy stock market Investors have been excessively bullish and overconfident Investors have been excessively bullish and overconfident, so when bad news surprises\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": "-0.0050", "answer_numeric": -0.004996, "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%) = -0.0071.", "metadata": {"var": -0.004996, "cvar": -0.007097, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220809_0456", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2022-08-09", "context_summary": "QUAL: 60-day return history, mean=0.0011, std=0.0158.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0011, std=0.0158, min=-0.0339, max=0.0266\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-08-08] [\"US STOCKS-Wall St set for higher open after selloff on jobs data By Bansari Mayur Kamdar and Aniruddha Ghosh Aug 8 (Reuters) - U.S. stock indexes were set to open higher on Monday after last week's blockbuster jobs data soothed some fears about an economic slowdown, but investors remained cautious as it also added to expectations of a hawkish Federal Reserve. The focus this week will be on consumer prices data on Wednesday. The S&P 500 has bounced back 13% from its mid-June lows, but investors fear that signs of persistent inflation this week could further bolster the Fed's case for aggressive monetary policy tightening. \\\"While it's clear the Fed needs to continue tightening policy, there are still about six weeks until the next meeting and we remind investors that economic data can change very quickly,\\\" said Robert Schein, chief investment officer, Blanke Schein Wealth Management. \\\"The CPI data will help to confirm if the Fed's tightening efforts have been successful in starting to tame inflation or if continued Fed tightening is needed.\\\" U.S. rate futures have priced in a 68.5% chance of a 75-basis-point hike at the Fed's September meeting, up from about 41% before payrolls data on Friday beat market expectations. IRPR Banks that tend to benefit from a higher interest rate environment extended their gains in trading before the bell. Megacap growth and technology stocks edged higher, with Tesla TSLA.O up 2.3%. The U.S. electric-car maker signed contracts worth about $5 billion to buy materials for their batteries from nickel processing companies in Indonesia, according to a CNBC report. Other high-growth stocks such as Apple Inc AAPL.O and Amazon.com Inc AMZN.O gained as U.S. Treasury yields pulled back from sharp highs in the previous session. The benchmark 10-year yield declined 1.6% in early trading. Meanwhile, the U.S. Senate on Sunday passed a sweeping $430 billion bill intended to fight climate change, lower drug prices and raise some corporate taxes. \\\"All in all, it's a net positive. Biotech and pharma should rebound after some uncertainty because it (the bill) is less onerous than initially anticipated as it relates to negotiating drug prices,\\\" said Thomas Hayes, managing member, Great Hill Capital LLC, New York. Hayes added that a lot of companies might accelerate their stock buybacks as they now have incentive to aggressively initiate buybacks before the 1% tax kicks in, helping the equity markets overall. Nvidia Corp NVDA.O fell 7% on saying it expects second-quarter revenue of about $6.70 billion, down 19% from the prior quarter, largely hurt by weakness in its gaming business. Signify Health Inc SGFY.N jumped 15.1% on a media report that CVS Health Corp CVS.N was looking to buy the health technology company. Global Blood Therapeutics climbed 4.6% on Pfizer's PFE.N $5.4 billion deal for the blood disorder drugmaker. At 08:50 a.m. ET, Dow e-minis 1YMcv1 were up 164 points, or 0.50%, S&P 500 e-minis EScv1 were up 25.75 points, \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": "-0.0309", "answer_numeric": -0.030887, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0309 (i.e., on a bad day with 5% probability, the loss exceeds 3.09%). CVaR(95%) = -0.0339.", "metadata": {"var": -0.030887, "cvar": -0.033883, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20151221_0459", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2015-12-21", "context_summary": "XLB: 60-day return history, mean=0.0009, std=0.0130.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0009, std=0.0130, min=-0.0316, max=0.0297\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-12-18] Adobe (ADBE) Attains a New 52-Week High on Solid Earnings Shares of Adobe Systems Inc.ADBE attained a new 52-week high of $96.42 on Dec 17, eventually closing at $94.20. The company returned 26.5% in the past one year and approximately 29.6% year-to-date. Average volume of shares traded over the last three months was roughly 3,453K. What is Driving Adobe Systems? One of the largest software companies in the world, Adobe Systems' massive customer base provides it with a distinct competitive edge. We believe that the company is being driven by continuous innovation in the Creative Cloud and Marketing Cloud businesses. The price appreciation may be attributed to Adobe's strong fundamentals, solid adoption of creative cloud and better-than-expected fourth-quarter fiscal 2015 results reported on Dec 10. Since then, the stock has gained 5.9%. In the fourth quarter, Adobe reported earnings of 47 cents per share, surpassing the Zacks Consensus Estimate of 45 cents. The growth was backed by strong adoption of creative cloud that led to a record sequential Creative Cloud ARR (Annualized Recurring Revenue) growth and strong revenues in the Creative product family. Adobe's revenues jumped 9.4% sequentially and 23.2% year over year to $1.31 billion. Revenues were at the higher end of the guidance range and in line with our expectations. We believe that the company will continue to be driven by innovation in its Creative suite businesses. In addition, the consistent adoption of the Adobe marketing cloud could serve as a potential catalyst, going forward. We expect significant synergies over the long term from the integration of Fotolia. Moreover, the solid adoption of Document Cloud, a new subscription package that enables users to sign documents on the cloud, will boost revenues. Additionally, Adobe Systems delivered an average positive earnings surprise of nearly 6.39% over the trailing four quarters. The company's solid market position, compelling product lines (including CS cloud initiative and digital media products), strong revenue growth, continued innovation and strong long-term growth potential position it favorably. Adobe Systems currently has a Zacks Rank #3 (Hold). Stocks to Consider Some well-ranked stocks in the same space are Citrix Systems, Inc. CTXS , Datawatch Corporation DWCH and Fleetmatics Group PLC FLTX , all sporting a Zacks Rank #1 (Strong Buy). 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 >> 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 CITRIX SYS INC (CTXS): Free Stock Analysis Report ADOBE SYSTEMS (ADBE): Free Stock Analysis Report FLEETMATICS GRP (FLTX): Free Stock Analysis Report DATAWATCH CORP (DWCH): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Research The views and opin\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": "-0.0202", "answer_numeric": -0.020187, "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%) = -0.0263.", "metadata": {"var": -0.020187, "cvar": -0.026285, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20191112_0464", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2019-11-12", "context_summary": "XLRE: 60-day return history, mean=-0.0002, std=0.0074.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0002, std=0.0074, min=-0.0174, max=0.0142\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-11] [\"Goldman Sachs and Apple Face Criticism Over Card, While Trade and Hong Kong Protest Drag Down Stock Futures Macroeconomic news is dominating early on Veterans Day. More back and forth on trade as well as continuing protests in Hong Kong are putting pressure on Asian stock markets.\", \"Big Tech can avoid a real crackdown because of Congress\\u2019s chaotic efforts, analysts say \\u2018The existence of so many disparate critiques complicates making progress on any one issue\\u2019 While Congress has Big Tech in its crosshairs, that doesn\\u2019t mean any of the bills targeting Silicon Valley actually will become law soon, according Capital Alpha analysts, who suggest there are just too many measures coming at once.\", \"Apple, Facebook, Google and Amazon are putting billions of dollars toward affordable housing \\u2014 but that money may be too little, too late Housing prices have skyrocketed in cities like San Francisco and Seattle, and tech companies are scrambling to ensure there\\u2019s an affordable place to live for their workforces Housing prices have skyrocketed in cities like San Francisco and Seattle, and tech companies are scrambling to ensure there\\u2019s an affordable place to live for their workforces.\", \"Apple co-founder Steve Wozniak also alleges that the Apple Card discriminated against his wife Wozniak says his Apple Card limit is 10x higher than his wife\\u2019s, despite their finances being identical Wozniak says his Apple Card limit is 10 times higher than his wife\\u2019s, despite their finances being identical.\", \"Qualcomm Stock Gets Downgraded on Potential 5G Risks A Morgan Stanley analyst says a recent rally by the chip maker makes its shares look less appealing.\", \"Regulator Will Investigate Goldman Sachs After Apple Card Controversy The New York State Department of Financial Services said it would investigate whether the algorithm used by Goldman Sachs to make credit-limit decisions for the Apple card violated state laws against discrimination.\", \"Netflix's stock surges as Disney's rival service set to launch; Apple's stock hits record high Shares of Netflix Inc. rallied 1.5% toward an 8-week high, as investors appear to be taking Tuesday's launch of Walt Disney Co.'s rival Disney+ streaming service in stride. Netflix's stock has now gained 3.0% this month, which also included the launch of Apple Inc.'s rival service Apple TV+ on Nov. 1. Apple's stock rallied 0.6%, putting them on track to close at a record high, and has climbed 5.2% this month. Disney's stock fell 1.1%, but had run up 3.8% on Friday on the back of upbeat third-quarter results. Disney shares have tacked on 5.0% this month.\", \"Dow closes at record after Boeing surges on report of 737 Max early return Treasury markets are closed in observance of Veterans Day but the stock market stays open U.S. stock market benchmarks came off intraday lows on Monday after Boeing said its grounded 737 Max fleet could see a return to service early next year\", \"Secret Google project i\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": "-0.0123", "answer_numeric": -0.012346, "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%) = -0.0149.", "metadata": {"var": -0.012346, "cvar": -0.014946, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150327_0467", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2015-03-27", "context_summary": "VTI: 57-day return history, mean=0.0002, std=0.0088.", "question": "Asset: VTI\nDaily returns (past 57 days): mean=0.0002, std=0.0088, min=-0.0173, max=0.0175\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-03-26] [\"The Zacks Analyst Blog Highlights: Biogen, Prothena, Vertex, Gilead and Amgen - Press Releases For Immediate Release Chicago, IL - March 26, 2015 - 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 the Biogen ( BIIB - Free Report ), Prothena ( PRTA - Free Report ), Vertex ( VRTX - Free Report ), Gilead ( GILD - Free Report ) and Amgen ( AMGN - Free Report ). Today, Zacks is promoting its ''Buy'' stock recommendations. Get #1Stock of the Day pick for free. Here are highlights from Wednesday's Analyst Blog: Biotech Stock Roundup: Biogen Soars It's been an eventful week on the pipeline front with companies like Biogen ( BIIB - Free Report ), Prothena ( PRTA - Free Report ) and Vertex ( VRTX - Free Report ) coming out with data. Meanwhile, Gilead ( GILD - Free Report ) was back in the news once again due to its hepatitis C virus (HCV) franchise. Recap of the Week's Most Important Stories 1. Hopes for a new Alzheimer's treatment are up with Biogen reporting positive data from a pre-specified interim analysis of a phase Ib study on aducanumab (BIIB037). Aducanumab was found to have an acceptable safety profile and the candidate delivered positive results on radiologic and clinical measurements in patients with prodromal or mild Alzheimer's disease (AD). Aducanumab showed a statistically significant reduction on amyloid plaque as well as a statistically significant slowing of clinical impairment in patients with prodromal or mild disease - this is promising news in the field of Alzheimer's disease. While Biogen's shares were up on the data and the news resulted in a lot of excitement among the investor and medical community, we note that the data is from an early-stage study. Moreover, developing treatments for Alzheimer's is pretty challenging with quite a few companies failing in late-stages of development (read more: Biogen Gains on Positive Alzheimer's Drug Interim Results ). 2. It's been a mixed week for Vertex - the company gained FDA approval for yet another label expansion for Kalydeco (read more: Vertex's Kalydeco Gets FDA Nod for Additional Indication ) but failed to impress the investment community with phase II data on its Kalydeco-VX-661 combination (read more: Vertex Falls on Disappointing Kalydeco+VX-661 Combo Data ). 3. Amgen's ( AMGN - Free Report ) efforts to block the entry of Novartis' Zarxio, a biosimilar of the former's blockbuster drug Neupogen, were hit by a roadblock with a judge in the U.S. denying the company's motion. Sandoz, Novartis' generic arm, gained FDA approval for Zarxio earlier this month in what was a landmark decision marking the approval of the first biosimilar in the U.S. It remains to be seen when Novartis will launch its biosimilar and what the impact on the launch on Neupogen sales will be. Meanwhile, Amgen is now looking t\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": "-0.0142", "answer_numeric": -0.014228, "explanation": "Historical simulation VaR at 95%: sort the 57 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%) = -0.0161.", "metadata": {"var": -0.014228, "cvar": -0.016125, "confidence": 0.95, "n_returns": 57, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20191231_0470", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2019-12-31", "context_summary": "XLK: 60-day return history, mean=0.0024, std=0.0077.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0024, std=0.0077, min=-0.0185, max=0.0164\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-30] Is North America Contribution To Amazon's Total Revenue 60%, 70%, Or 80%? Amazon\u2018s (NASDAQ:AMZN) North America business, consisting primarily of retail sales in the region, is expected to contribute $177.6 billion to Amazon\u2019s 2019 revenues, making up 61.2% of Amazon\u2019s $290.4 billion in expected revenues for 2019. The North America segment contribution is more than twice that from International business. Amazon is expected to add $154 billion in revenue between 2016 to 2019, out of which the North America segment is expected to provide $97 billion, that is 63% of the total expected increase. This North America revenue growth has been key to Amazon\u2019s 160% price appreciation since 2016, further helped by increasing margins. We discuss Amazon\u2019s valuation analysis in full, separately. Below we discuss Amazon\u2019s business model, followed by sections that review past performance and 2019 expectations for Amazon\u2019s revenue drivers and competitive comparisons of its Retail revenue with Walmart and Target. You can look at our interactive dashboard analysis ~ Amazon\u2019s Revenues: How Does Amazon Make Money? ~ for more details. Amazon Business Model: What does Amazon offer: Amazon.com, Inc. was incorporated in 1994 in the state of Washington. The company is one of the largest online retailers, and also dabbles in a broad range of businesses including its core e-commerce operations, cloud services, digital advertising, groceries, and prescription drugs. They also sell products such as the Alexa personal assistant and ecosystem, and also gives access to content through subscription on its Amazon Prime platform. Has 3 major Operating Segments: North America: The North America segment primarily consists of amounts earned from retail sales of consumer products (including from sellers) and subscriptions through North America-focused online and physical stores. This segment includes export sales from these online stores. International: The International segment primarily consists of amounts earned from retail sales of consumer products (including from sellers) and subscriptions through internationally-focused online stores. This segment includes export sales from these internationally-focused online stores (including export sales from these online stores to customers in the U.S., Mexico, and Canada), but excludes export sales from the North America-focused online stores. AWS: The AWS segment consists of amounts earned from global sales of computing, storage, database, and other service offerings for start-ups, enterprises, government agencies, and academic institutions. What Are The Alternatives? Major competitors are Walmart, eBay, Alibaba, Google, Facebook, and Apple. What Is The Basis of Competition? The principal competitive factors in the retail businesses include selection, price, and convenience, including fast and reliable fulfillment. Additional competitive factors for the seller and enterprise services include the quality, speed, and reliability of their servi\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": "-0.0098", "answer_numeric": -0.009792, "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%) = -0.0155.", "metadata": {"var": -0.009792, "cvar": -0.015478, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190702_0473", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-07-02", "context_summary": "ETH-USD: 60-day return history, mean=0.0112, std=0.0501.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0112, std=0.0501, min=-0.1262, max=0.1382\nMarket regime: sideways\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": "-0.0658", "answer_numeric": -0.06577, "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%) = -0.0982.", "metadata": {"var": -0.06577, "cvar": -0.098196, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200521_0476", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-05-21", "context_summary": "MATIC-USD: 60-day return history, mean=0.0120, std=0.0564.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0120, std=0.0564, min=-0.1130, max=0.1666\nMarket regime: sideways\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": -0.074001, "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%) = -0.1086.", "metadata": {"var": -0.074001, "cvar": -0.108583, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190111_0481", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-01-11", "context_summary": "ETH-USD: 60-day return history, mean=-0.0063, std=0.0680.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0063, std=0.0680, min=-0.1575, max=0.1560\nMarket regime: sideways\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": "-0.1231", "answer_numeric": -0.123115, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1231 (i.e., on a bad day with 5% probability, the loss exceeds 12.31%). CVaR(95%) = -0.1436.", "metadata": {"var": -0.123115, "cvar": -0.143619, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210203_0484", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2021-02-03", "context_summary": "VNQI: 60-day return history, mean=0.0017, std=0.0096.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=0.0017, std=0.0096, min=-0.0212, 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": "-0.0133", "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%) = -0.0186.", "metadata": {"var": -0.013273, "cvar": -0.018637, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210614_0487", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2021-06-14", "context_summary": "XHB: 60-day return history, mean=0.0014, std=0.0154.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0014, std=0.0154, min=-0.0411, max=0.0364\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": "-0.0231", "answer_numeric": -0.023113, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0231 (i.e., on a bad day with 5% probability, the loss exceeds 2.31%). CVaR(95%) = -0.0335.", "metadata": {"var": -0.023113, "cvar": -0.033542, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210514_0490", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2021-05-14", "context_summary": "XLK: 60-day return history, mean=-0.0004, std=0.0156.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=-0.0004, std=0.0156, min=-0.0356, max=0.0334\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-05-13] Can DocuSign Fend Off Adobe's E-Signature Product? There's plenty of competition for DocuSign's (NASDAQ: DOCU) flagship e-signature product, but the digital agreement software continues to lead in the market. On a Fool Live episode recorded on April 28, Fool contributors Brian Feroldi and Brian Withers discuss the e-signature specialist's biggest competitor and how investors should think about this rivalry. 10 stocks we like better than DocuSign When investing geniuses David and Tom Gardner have 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.* David and Tom just revealed what they believe are the ten best stocks for investors to buy right now... and DocuSign 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 February 24, 2021 Brian Feroldi: I do see a question here that I do want to take. It's from MS Regular saying, \"Is there any competitor for DocuSign?\" Yes. There's a lot of competitors for DocuSign. The number one competitor is a little company called Adobe. Adobe is not a company that should be overlooked because they have deep relationships, and they have a growing marketing and sales business that is focused on business services and it is winning. Their e-signature solution is part of their product. But look at the results, what are the results clearly say? Clearly, there's plenty of customers that are choosing DocuSign, and DocuSign is the top dog, and first mover in this space. Moreover, DocuSign has hundreds upon hundreds of integrations directly with some of the leading products that are out there. DocuSign works directly with Microsoft's products, with salesforce.com, etc. Don't overlook that as a competitive advantage. Finally, I always think about what is the value of this thing compared to the costs to a company. The productivity gains that you get from using an e-signature solution are just so massive compared to the costs of it. I don't think once you adopt DocuSign that you're going to be going away from it. Competition is something to watch, but DocuSign is basically a verb at this point and they have clearly done a great job about staying the lead husky. Brian Withers: Yeah. I wanted to tag onto that, Brian. DocuSign has got like 70 percent-plus market share, Adobe is in the single digits. But do you have to remember and I think you stated it well, is people don't necessarily go to Adobe to buy the e-signature product they go to buy more of a holistic solution. Recently there was an announcement that I saw that \"Adobe partners with all 50 states to modernize digital experience for citizens\", and really if you read through the documentation what they're doing is they're putting together websites and experiences for customers and some small part of that is a signature process. Maybe they're building online forms for people, or questionnaires to allow the\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": "-0.0257", "answer_numeric": -0.025699, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0257 (i.e., on a bad day with 5% probability, the loss exceeds 2.57%). CVaR(95%) = -0.0308.", "metadata": {"var": -0.025699, "cvar": -0.030753, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210216_0493", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2021-02-16", "context_summary": "ETH-USD: 60-day return history, mean=0.0180, std=0.0599.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0180, std=0.0599, min=-0.1593, max=0.1560\nMarket regime: sideways\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": "-0.0767", "answer_numeric": -0.076742, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0767 (i.e., on a bad day with 5% probability, the loss exceeds 7.67%). CVaR(95%) = -0.1254.", "metadata": {"var": -0.076742, "cvar": -0.12541, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180914_0496", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-09-14", "context_summary": "XRP-USD: 60-day return history, mean=-0.0061, std=0.0568.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0061, std=0.0568, min=-0.1449, max=0.2539\nMarket regime: sideways\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": "-0.0813", "answer_numeric": -0.081278, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0813 (i.e., on a bad day with 5% probability, the loss exceeds 8.13%). CVaR(95%) = -0.1272.", "metadata": {"var": -0.081278, "cvar": -0.127195, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181123_0499", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2018-11-23", "context_summary": "^VIX: 60-day return history, mean=0.0069, std=0.0856.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0069, std=0.0856, min=-0.1825, max=0.2508\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-11-21] [\"Apple could provide veterans with access to electronic medical records Partnership with VA could streamline veterans\\u2019 hospital visits Apple Inc. is in discussions with the Department of Veterans Affairs to provide portable electronic health records to military veterans, a partnership that would simplify patients\\u2019 hospital visits and allow the technology giant to tap millions of new customers, according to people familiar with the effort and emails reviewed by The Wall Street Journal.\", \"Asian markets mixed, retreating then recovering as tech and energy stocks lead Nikkei nears 1-month low Asian stock markets mostly fell early but improved from the worst levels of the day, as the region\\u2019s trading tracked the drubbing Tuesday for U.S. stocks and oil futures. Both equities and oil markets indicated a Wednesday rebound was in order.\", \"Apple's stock gains 1.1% premarket, after falling 4.8% Tuesday to close in bear-market territory\", \"Corporate America Is Ready to Pay Down Its Debt. That\\u2019s Bad News for Stocks. Companies have borrowed record amounts of debt in recent years, in part to buy back record amounts of stock. These borrowers are now starting to pay down debt and reduce leverage.\", \"The tech-stock selloff is a golden opportunity to buy Amazon, Apple, Netflix and Tesla If a technology is fundamentally disruptive enough, that fact will always overwhelm the noise of the day about valuation If a technology is fundamentally disruptive enough, that fact will always overwhelm the noise of the day about valuation.\", \"This Apple true believer just sold all of his firm\\u2019s shares Slower growth, mature products, and faster competition pressure the stock Slower growth, mature products, and faster competition pressure Apple stock, writes Vitaliy Katsenelson.\", \"There\\u2019s a darker message for investors in the FAANG selloff Gloom for Facebook, Amazon, Apple, Netflix and Google parent Alphabet Big Tech is facing the kind of scrutiny it hasn\\u2019t had since the Microsoft Monopoly era.\", \"Misguided share buybacks are hollowing out companies\\u2019 balance sheets and will lead to even bigger stock-market trouble GE\\u2019s troubles are a reliable signal of trouble ahead for U.S. companies No bubble in today\\u2019s stock market is as overblown and as unjustified as the one in share buybacks.\", \"Apple's stock and the other FAANGs bounce after previous session's drubbing Shares of Apple Inc. rallied 1.3% in premarket trade Wednesday, bouncing from the previous session's tumble that kicked off what many chart watchers define as a bear market. The stock fell 4.8% Tuesday, to close 23.7% below its Oct. 3 record close of $232.07. Many on Wall Street define a bear market as a decline of 20% or more from a bull-market high. The new bear market started Tuesday is the first since it came out of the last bear market on Aug. 9, 2016. The other FAANG stocks, which were already in bear markets, were also bouncing ahead of the open. Shares of Facebook \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": "-0.0997", "answer_numeric": -0.099727, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0997 (i.e., on a bad day with 5% probability, the loss exceeds 9.97%). CVaR(95%) = -0.1746.", "metadata": {"var": -0.099727, "cvar": -0.174614, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160318_0504", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2016-03-18", "context_summary": "XLF: 60-day return history, mean=-0.0006, std=0.0152.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=-0.0006, std=0.0152, min=-0.0310, max=0.0362\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-03-17] [\"Progress is being made in the war on \\u2018St. Patty\\u2019s Day\\u2019 The likes of Google and Apple have been conscripted On the one hand, St. Patrick\\u2019s Day is a patriotic celebration of Irish heritage. On the other hand, alas, are the clovers masquerading as shamrocks; the unbridled commercialization; the beer that looks like lime Jell-O; and, of particular significance to the Northern Ireland\\u2013raised web developer Marcus Campbell, the saint\\u2019s name being corrupted as \\u201cPatty.\\u201d\", \"Apple will lead surge in wearable shipments through 2020 Shipments of wearable devices are expected to jump by more than 38% this year to 110 million, and surpass 200 million by 2019, according to new data from industry tracker IDC. The industry's growth is expected to be led by smartwatches, as manufacturers advance their capabilities and they become operational on their own without the need to be tethered to third-party devices like smartphones. Smartwatches like Apple Inc.'s watch and Alphabet Inc.'s Android Wear are expected to account for one-third of all of all wearables by 2020. The market is also expected to be lifted by the emergence of higher-end smartwatch brands from luxury designers, which could slightly eat into Apple's share, though Apple is expected to remain the dominant brand for the foreseeable future, IDC said. The proliferation of new and different types of wearable product categories, such as connected clothes and eyewear, are also expected to contribute to the industry's growth.\", \"Apple Switching to Google Cloud? Market Big Enough for All, Says Pac Crest Shares of Alphabet (GOOGL) are up $4.07, or half a percent, at $761.43, while Amazon.com (AMZN) is down $11.56, or 2%, at $562.71, after Kevin McLaughlin and Joseph Tsidulko late yesterday wrote that Alphabet has signed up Apple (AAPL) as a customer for its \\u201cGoogle Cloud Platform\\u201d computing service, citing multiple unnamed sources.The move means Apple has \\u201csignificantly reduced its reliance on Amazon Web Services,\\u201d the authors write, perhaps giving Google $500 million to $600 million with Google Cloud.However, Mark Bergen with Re/code, reinforcing the speculation with another set of unnamed sources, wrote later in the day that Apple has a team building out data centers of its own to store its various media libraries, again citing an unnamed source:Apple already has a team working on this; it\\u2019s known internally as \\u201cMcQueen,\\u201d as in Steve. It\\u2019s unclear if that project will materialize or when. But a source tells Re/code that the codename refers to Apple\\u2019s intent sometime in the next few years to break its reliance on all three outside cloud providers in favor of its own soup-to-nuts infrastructure.In a note to clients this morning, Evan Wilson of Pacific Crest, citing the CRN report,\", \"Intel: Taking Qualcomm Apple Biz at Zero Profit Means Nothing, Says Citi Citigroup\\u2019s chip analyst, Christopher Danely, is the latest to weigh\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": "-0.0264", "answer_numeric": -0.026442, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0264 (i.e., on a bad day with 5% probability, the loss exceeds 2.64%). CVaR(95%) = -0.0292.", "metadata": {"var": -0.026442, "cvar": -0.029241, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160223_0511", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2016-02-23", "context_summary": "IWM: 60-day return history, mean=-0.0023, std=0.0143.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0023, std=0.0143, min=-0.0326, max=0.0323\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-02-22] [\"China bans foreign publishing content online All online content must be on servers hosted within China China has issued broad new rules for online publishing that formalize the government\\u2019s already strict control of the Internet and seek to expand the scope of online content stored inside its borders.\", \"Samsung\\u2019s Flagship Galaxy S7 Disappoints At the annual Mobile World Congress in Barcelona, whereas LG Electronics (066570.Korea) got good reviews for its new module smartphone G5, Samsung Electronics' (005930.Korea/SSNLF) flagship Galaxy S7 turns out lackluster.Year-to-date, Samsung fell 6.3%, broadly in line with competitor Apple's (AAPL) 8.8% decline.Galaxy S7 offers few new bells and whistles, reviewedThe Wall Street Journal colleagues Jonathan Cheng and Min-Jeong Lee:The high-end Galaxy S7 and its curved-screen companion, the Galaxy S7 Edge, released on the sidelines of the Mobile World Congress trade show Sunday, look strikingly similar to their predecessors and lack fresh features to set them apart in a crowded field of Android handsets.The smartphones come with an improved camera and longer battery life, in addition to two features that had been dropped from the Galaxy S6 last year: removable memory storage and water resistance.Morgan Stanley's Shawn Kim agrees:READ MORE.\", \"FBI boss to Apple backers: \\u2018Stop saying the world is ending\\u2019 James Comey argues agency won\\u2019t \\u2018set a master key loose\\u2019 Protesters worldwide plan to blast the FBI for trying to break into a terror suspect\\u2019s iPhone, and the public looks like it\\u2019s mostly with Apple in this fight. Meanwhile, the FBI\\u2019s director, James Comey, says everyone should essentially chill out.\", \"Samsung\\u2019s Faster Charging without Wires\", \"Looking for bottoms in oil prices and the stock market? Keep looking Critical intelligence before the U.S. market opens The final dispatches of an already-dead earnings season and another batch of Fed blather may sway investors\\u2019 mood in the week ahead. But perhaps even more relevant to the stock market\\u2019s odds of building on last week\\u2019s big push \\u2014 the best of the year so far \\u2014 is oil\\u2019s next move.\", \"Apple holds firm against FBI, calls for expert panel to discuss encryption Tim Cook posts his own Q&A over San Bernardino phone Apple renews its defense for why it has refused to help law enforcement unlock the phone of a shooter in the San Bernardino terror attack and suggests the government form a commission to address the thorny problems posed by the growing use of encryption.\", \"Apple still giving the FBI advice on how to crack San Bernardino shooter\\u2019s phone The tech giant says it\\u2019s done everything within its power to help The tech giant says it\\u2019s done everything within its power to help.\", \"What Apple and the head of the FBI agree on The tech giant and authorities have some common ground The tech giant and authorities have some common ground.\", \"Read the letter Tim C\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": "-0.0236", "answer_numeric": -0.023629, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0236 (i.e., on a bad day with 5% probability, the loss exceeds 2.36%). CVaR(95%) = -0.0292.", "metadata": {"var": -0.023629, "cvar": -0.029158, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200206_0514", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2020-02-06", "context_summary": "QQQ: 60-day return history, mean=0.0022, std=0.0075.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0022, std=0.0075, min=-0.0209, max=0.0226\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-02-05] [\"Stocks That Hit 52-Week Highs On Wednesday\", \"Stocks That Hit 52-Week Highs On Wednesday\", \"Adobe Stock Could Head Higher, but Tread Carefully With shares up 31% since Nov. 1, is Adobe (NASDAQ:) stock a buy at the current price level? After December\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s earning beat, the company could see its impressive level of growth continue \\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0094 and push ADBE stock even higher. Source: r.classen / Shutterstock.com Currently sitting at , Adobe shares sell at a rich valuation. In this runaway bull market, that hardly seems to matter. So, with the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s growth story continuing, shares could reach new highs in the near-term. Furthermore, it\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s safe to say that with ADBE stock, you are buying a business with a tremendous economic moat. The company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s software offerings are invaluable assets. Whether we are talking about the unit, Document Cloud unit or , the company plays a heavy role in the new economy. However, is buying Adobe stock today a smart play long term? It may pay to be patient, and wait for a dip to accumulate shares. That said, let\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s dive in, and see why buying later is the best call for ADBE stock. ADBE Stock Has Gotten Ahead of Itself As InvestorPlace\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s Luke Lango discussed Dec. 19, the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s revenue growth justified a price target of . But now, shares trade above that price target and are closer to the $365 level. It\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s tough to say the recent rise of ADBE stock is due to fundamentals. After December\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s earnings beat, much of Adobe\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s future upside was priced into shares. So, what\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s driving the recent run-up? Mr. Market, or specifically, Mr. Broad Market. Major indices are even after the coronavirus panic, so it\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s no mystery why ADBE stock keeps climbing higher. With its de facto monopoly on digital design, Adobe should be christened a Nasdaq Composite blue chip. Given major tech names like Microsoft (NASDAQ:) are ripping to new highs, there\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s no reason to leave out Adobe shares from the fun. However, outside of the broad market, what could send ADBE stock lower? How about the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s projected revenue growth slowdown? As this Seeking Alpha contributor discussed, it\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s hard to justify Adobe\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s high forward price-to-earnings (P/E) ratio when the company\\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0099s growth rate is expected to drop below the . Once investors get back to using fundamentals \\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0094 not momentum \\u00c3\\u00a2\\u00c2\\u0080\\u00c2\\u0094 to\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": "-0.0093", "answer_numeric": -0.009257, "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%) = -0.0157.", "metadata": {"var": -0.009257, "cvar": -0.015716, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220810_0519", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2022-08-10", "context_summary": "XLY: 60-day return history, mean=0.0021, std=0.0221.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0021, std=0.0221, min=-0.0388, max=0.0338\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-08-09] [\"Down 47% in a Year, Time to Buy This Growth Stock? With a market cap of $8.3 billion, Cognex Corporation (NASDAQ: CGNX) is not a small-cap company. However, it's still a growth company trying to build out the adoption of technology with explosive growth potential. As the leader in machine vision, Cognex's strategic aim is to grow into a served market (estimated as being worth $4.2 billion in 2018) that management sees as growing at a 12% annual rate. The good news from 2022 is Cognex is achieving many of its strategic aims; the bad news is almost everything seems to be working against the company right now. Here's the lowdown. What a growth company needs If you are going to make up an informal list of objectives for a growth company, it will include the following: Win over some highly prominent and visible customers to demonstrate your technology's efficacy, expand revenue, win follow-up business, and sell to lower-tier players as they follow their industry leaders in adopting machine vision. Ensure you satisfy high-profile customers by investing in a high level of service. Continue establishing your technology in new growth markets. As alluded to earlier, Cognex is doing all three things. The company's three major machine vision markets are automotive, consumer electronics, and logistics/e-commerce. The biggest names in two of those three industries are Apple (named as a significant customer in a previous Cognex SEC filing) and Amazon.com (NASDAQ: AMZN). The latter was not named on Cognex's recentearnings call Still, Cognex's last 10-K filing referred to a large customer in the logistics industry that represented approximately 17% of their total revenue. When an analyst refers to \\\"the world's largest e-commerce customer,\\\" it's a reasonable bet that it's Amazon. One clear thing is that Cognex has won some very high-profile customers in the last five years, so you can tick off the first box on the checklist. Servicing customers and establishing new markets The other two boxes can be ticked off as well. Three sources indicate that Cognex is very careful in servicing its customers (an excellent quality in a growing company). First, back in 2014, when Cognex started working on Apple orders (its machine vision solutions help smartphone manufacturers fit screens), management significantly ramped its operating expenses to support the orders. Second, it was the same in 2021, with Cognex incurring an extra cost in providing a \\\"higher level of support on a large deployment by a customer in logistics.\\\" Third, back on the fourth-quarterearnings callin February, CEO Robert Willett disclosed Cognex had \\\"been prioritizing delivery during this time of global chip shortages that added incremental costs in 2021, due to the significant premiums we've paid to procure components through brokers, and for expedited freight.\\\" As for establishing new markets, the logistics market is a relatively new one for Cognex that's grown at a compound annual growth rate of \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": "-0.0388", "answer_numeric": -0.038816, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0388 (i.e., on a bad day with 5% probability, the loss exceeds 3.88%). CVaR(95%) = -0.0388.", "metadata": {"var": -0.038816, "cvar": -0.038816, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190521_0522", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2019-05-21", "context_summary": "SOYB: 60-day return history, mean=-0.0018, std=0.0077.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=-0.0018, std=0.0077, min=-0.0221, 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": "-0.0124", "answer_numeric": -0.012351, "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%) = -0.0170.", "metadata": {"var": -0.012351, "cvar": -0.017047, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200311_0525", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2020-03-11", "context_summary": "MTUM: 60-day return history, mean=-0.0003, std=0.0134.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0003, std=0.0134, min=-0.0383, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-03-10] [\"123 Biggest Movers From Yesterday\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Morning Market Stats In 5 Minutes\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Morning Market Stats In 5 Minutes\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"123 Biggest Movers From Yesterday\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Morning Market Stats In 5 Minutes\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"123 Biggest Movers From Yesterday\", \"Has the coronavirus selloff created a stock-buying opportunity, or is it too early? Here\\u2019s what analysts and strategists are advising Is it safe to go back into the water after stocks have been rocked by the COVID-19 outbreak?\", \"These 3 EVs are the lowest cost to own over 5 years The 5-Year Cost to Own equation includes insurance, fuel economy, interest rates, and depreciation\\u2014the Nissan Leaf comes out on top The Nissan Leaf takes home KBB\\u2019s Best EV 5-Year Cost to Own Award for the third year in a row.\", \"After markets plunge on fears of OPEC \\u2018price war\\u2019 and coronavirus \\u2014 5 questions to ask your financial adviser right now Advisers say this is a \\u2018great litmus test\\u2019 to evaluate your risk tolerance, but they say retail investors should proceed cautiously Advisers say this is a \\u2018great litmus test\\u2019 to evaluate your risk tolerance, but they say retail investors should proceed ca\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": "-0.0281", "answer_numeric": -0.028144, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0281 (i.e., on a bad day with 5% probability, the loss exceeds 2.81%). CVaR(95%) = -0.0349.", "metadata": {"var": -0.028144, "cvar": -0.034926, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190225_0530", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2019-02-25", "context_summary": "FXI: 60-day return history, mean=0.0017, std=0.0123.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0017, std=0.0123, min=-0.0212, max=0.0333\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-22] [\"Pinnacle West's (PNW) Q4 Earnings Beat Estimates, Up Y/Y Pinnacle West Capital CorporationPNW delivered adjusted earnings per share of 23 cents in the fourth quarter of 2018, beating the Zacks Consensus Estimate of 17 cents by 35.3%. In the year-ago quarter, the company had reported adjusted earnings of 19 cents. Impressive operational performance and favorable Arizona economy supported the quarterly numbers. In 2018, Pinnacle West Capital generated earnings of $4.54 per share, up from $4.35 in 2017. Total Revenues In the quarter under review, total revenues of $756.4 million fell 0.4% on a year-over-year basis. In 2018, the company delivered revenues of $3.69 billion, up from $3.57 billion in 2017. Pinnacle West Capital Corporation Price, Consensus and EPS Surprise Pinnacle West Capital Corporation Price, Consensus and EPS Surprise | Pinnacle West Capital Corporation Quote Operational Highlights In fourth-quarter 2018, total Operating Expenses were $689.5 million, up 2.3% from the year-ago quarter's tally. Operating income declined 21.8% year over year to $66.9 million. Interest expenses rose to $55.9 million from $50.6 million in the year-ago quarter. Courtesy of the improving Arizona economy, customer volumes improved 1.7% year over year in 2018, resulting in an increase of 16 cents in the company's earnings compared with 2017. Guidance Management projects 2019 EPS in the range of $4.75-$4.95, whose mid-point of $4.85 is higher than the current Zacks Consensus Estimate of $4.84. Zacks Rank Pinnacle West currently carries a Zacks Rank #2 (Buy). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here . Other Utility Releases NextEra Energy, Inc. NEE delivered fourth-quarter 2018 adjusted earnings of $1.49 per share, which lagged the Zacks Consensus Estimate of $1.51 by 1.3%. American Electric Power Co., Inc. AEP generated fourth-quarter 2018 operating EPS of 72 cents, in line with the Zacks Consensus Estimate. Xcel Energy Inc. XEL posted fourth-quarter 2018 operating earnings of 42 cents per share, in line with the Zacks Consensus Estimate. Wall Street's Next Amazon Zacks EVP Kevin Matras believes this familiar stock has only just begun its climb to become one of the greatest investments of all time. It's a once-in-a-generation opportunity to invest in pure genius. Click for details >> 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 NextEra Energy, Inc. (NEE): Free Stock Analysis Report Pinnacle West Capital Corporation (PNW): Free Stock Analysis Report American Electric Power Company, Inc. (AEP): Free Stock Analysis Report Xcel Energy Inc. (XEL): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Research The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein \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": "-0.0167", "answer_numeric": -0.01669, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0167 (i.e., on a bad day with 5% probability, the loss exceeds 1.67%). CVaR(95%) = -0.0198.", "metadata": {"var": -0.01669, "cvar": -0.019803, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220706_0533", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2022-07-06", "context_summary": "XLV: 60-day return history, mean=-0.0011, std=0.0141.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0011, std=0.0141, min=-0.0294, max=0.0244\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-05] [\"EU lawmakers pass landmark tech rules, but enforcement a worry By Foo Yun Chee BRUSSELS, July 5 (Reuters) - EU lawmakers gave the thumbs up on Tuesday to landmark rules to rein in tech giants such as Alphabet GOOGL.O unit Google, Amazon AMZN.O, Apple AAPL.O, Facebook FB.O and Microsoft MSFT.O, but enforcement could be hampered by regulators' limited resources. In addition to the rules known as the Digital Markets Act (DMA), lawmakers also approved the Digital Services Act (DSA), which requires online platforms to do more to police the internet for illegal content. Companies face fines of up to 10% of annual global turnover for DMA violations and 6% for DSA breaches. Lawmakers and EU states had reached a political deal on both rule books earlier this year, leaving some details to be ironed out. The European Commission has set up a taskforce, with about 80 officials expected to join up, which critics say is inadequate. Last month it put out a 12 million euro ($12.3 million) tender for experts to help in investigations and compliance enforcement over a four-year period. EU industry chief Thierry Breton sought to address enforcement concerns, saying various teams would focus on different issues such as risk assessments, interoperability of messenger services and data access during implementation of the rules. Regulators will also set up a European Centre for Algorithmic Transparency to attract data science and algorithm scientists to help with enforcement. \\\"We have started to gear the internal organisation to this new role, including by shifting existing resources, and we also expect to ramp up recruitment next year and in 2024 to staff the dedicated DG CONNECT team with over 100 full time staff,\\\" Breton said in a blogpost. DEEP POCKETS Lawmaker Andreas Schwab, who steered the issue through the European Parliament, has called for a bigger taskforce to counter Big Tech's deep pockets and array of lawyers. European Consumer Organisation (BEUC) echoed the same worries. \\\"We raised the alarm last week with other civil society groups that if the Commission does not hire the experts it needs to monitor Big Tech's practices in the market, the legislation could be hamstrung by ineffective enforcement,\\\" BEUC Deputy Director General Ursula Pachl said in a statement. The DMA is set to force changes in companies' businesses, requiring them to make their messaging services interoperable and provide business users access to their data. Business users would be able to promote competing products and services on a platform and reach deals with customers off the platforms. Companies will not be allow to favour their own services over rivals' or prevent users from removing pre-installed software or apps, two rules that will hit Google and Apple hard. The DSA bans targeted advertising aimed at children or based on sensitive data such as religion, gender, race and political opinions. Dark patterns, which are tactics that mislead people into giving personal data to c\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": "-0.0262", "answer_numeric": -0.026156, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0262 (i.e., on a bad day with 5% probability, the loss exceeds 2.62%). CVaR(95%) = -0.0284.", "metadata": {"var": -0.026156, "cvar": -0.028363, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210824_0538", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2021-08-24", "context_summary": "QUAL: 60-day return history, mean=0.0015, std=0.0061.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0015, std=0.0061, min=-0.0130, max=0.0141\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-08-23] [\"Global Cider Market Report 2021-2027: Market to Reach $16.6 Billion - Heineken Revels in Cider Business while C&C Languishes Dublin, Aug. 23, 2021 (GLOBE NEWSWIRE) -- The \\\"Cider - Global Market Trajectory & Analytics\\\" report has been added to ResearchAndMarkets.com's offering. Global Cider Market to Reach $16.6 Billion by 2027Amid the COVID-19 crisis, the global market for Cider estimated at US$12.2 Billion in the year 2020, is projected to reach a revised size of US$16.6 Billion by 2027, growing at a CAGR of 4.4% over the analysis period 2020-2027. Apple Flavored, one of the segments analyzed in the report, is projec\", \"The Morning After: WhatsApp might finally launch an iPad app Today\\u2019s headlines: Google has already discontinued the Pixel 5 and Pixel 4a with 5G, A more powerful Apple Mac mini might land this fall and four new games come to the... Atari Lynx.\", \"Water Ways Announces Its Shares Being Quoted for Trading on the Frankfurt Stock Exchange NOT FOR DISTRIBUTION TO U.S. NEWSWIRE SERVICES OR DISSEMINATION IN THE UNITED STATES TORONTO, Aug. 23, 2021 (GLOBE NEWSWIRE) -- Water Ways Technologies Inc. (TSXV: WWT) (\\\"Water Ways\\\" or the \\\"Company\\\"), a global provider of Israeli-based agriculture technology, providing water irrigation solutions to agricultural producers, is pleased to announce its shares being quoted for trade on the Frankfurt Stock Exchange (FSE) under the symbol 977. Ohad Haber Water Ways' CEO and Chairman, commented: \\\"We ar\", \"T-Mobile is giving customers a free year of Apple TV+ For a few years now, wireless carriers in the US have offered their customers all manner of video and music freebies. Verizon (Engadget's parent company) has offered free subscriptions to Disney+, Apple Music and AMC+ recently, while T-Mobile has long offered its customers free Netflix access. Today, T-Mobile is adding another freebie to its offerings: Apple TV+. Starting on August 25th, customers on the carrier's Magenta or Magenta Max plans (as well as some Sprint legacy plans) will get one year of free Apple TV+ access.\", \"Video: Jamie Windsor Shares the Truth on Being Successful on YouTube ly concerned about views and popularity, some industry members reject their credibility as skilled photographers. But that can hardly be fair. Surely there's more depth to a photographer who makes YouTube content? I was eager to find out. So I invited popular YouTuber Jamie Windsor on to The Phoblographer's official podcast: Inside The Photographers Mind.\", \"Apple employees are organizing to push for 'real change' at the company A group of current and former Apple employees are calling on their colleagues to publicly share stories of discrimination, harassment and retaliation they experienced while working at the company.\", \"Enjoy Technology Announces Second Quarter and First Half 2021 Financial Results Enjoy Technology, Inc., (\\\"Enjoy\\\"), a technology-powered service platform reinventing \\\"Commerce at Home,\\\" today reported its financial results for\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": "-0.0086", "answer_numeric": -0.008615, "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%) = -0.0126.", "metadata": {"var": -0.008615, "cvar": -0.012618, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150312_0541", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2015-03-12", "context_summary": "FXI: 46-day return history, mean=-0.0004, std=0.0135.", "question": "Asset: FXI\nDaily returns (past 46 days): mean=-0.0004, std=0.0135, min=-0.0275, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-03-11] [\"How to Get a 6.2% Yield On a Blue Chip Stock Enhance AT&T\\u2019s already juicy yield by selling puts while waiting to see how market reacts to Dow ejection.\", \"It would take 2.5 years of Foxconn wages to afford $10,000 Apple Watch $10,000 watch underscores gap between suppliers, customers While Apple has pledged to improve supply-chain working conditions, China Labor Watch says problems persist\", \"Elon Musk wants you to know that Tesla\\u2019s priciest Model S is a badass on ice In Norway, the pricey P85D is a winner on the ice Could a Tesla Model S race across a frozen Norwegian lake help put the sexy back into shares? Can\\u2019t blame Elon Musk for trying.\", \"Which is the better value play, Qualcomm or Apple? By forgetting about the actual price of the stock and focusing on both trailing and forward earnings when trying to determine whether or a stock is properly priced brings a much clearer picture when making such a choice.\", \"This 15-year-old bear market will be around a while longer A generation comes of age learning that stocks have miserable returns Major stock market indexes are finally back to 2000 levels, but the psychological bear market is likely to be with us for a long time to come, writes Matthew Lynn.\", \"A stock market versus a market of stocks The latest issue of Hulbert On Markets One of the longest-lived debates on Wall Street is between those who think it\\u2019s a \\u201cstock market\\u201d and those who consider it to be a \\u201cmarket of stocks.\\u201d Mark Hulbert discusses who\\u2019s winning this debate right now, and what it means for your investments.\", \"Apple\\u2019s app stores are knocked out of commission iTunes store is temporarily out of commission.\", \"Apple\\u2019s App Stores Out of Order\", \"Ericsson to cut 2,200 jobs Telecom-equipment giant Ericsson AB said Wednesday it will shed 2,200 jobs, the latest move by Chief Executive Hans Vestberg to transition the company from a hardware provider into a global leader in mobile-network software.\", \"Apple's stock falls behind AT&T since Dow changes announced NEW YORK (MarketWatch) -- The curse of new Dow Jones Industrial Average components may be taking a bite out of Apple Inc.'s shares , as they have fallen behind AT&T since it was announced that the technology giant will replace the telecom company within the blue-chip index . Apple's stock dropped 1.8% on Wednesday to close at a one-month low. It has now lost 3.4% since Friday, the day S&P S&P Dow Jones Indices said Apple would join the Dow after the March 18 close. Meanwhile, AT&T's stock has lost just 2.6% this week. The last three stocks to be booted from the Dow have outperformed their respective replacements since those changes went into effect. Separately, Apple's stock now suffered the biggest two-session drop--3.9%--since it fell 4.6% in the two days ending Sept. 25, when reports of bending iPhones made the rounds.\", \"Drug dealer in China says he only did it to buy an Apple Watch The high price tag of the Apple Wat\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": "-0.0233", "answer_numeric": -0.023338, "explanation": "Historical simulation VaR at 95%: sort the 46 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%) = -0.0259.", "metadata": {"var": -0.023338, "cvar": -0.025864, "confidence": 0.95, "n_returns": 46, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160510_0544", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2016-05-10", "context_summary": "EWJ: 60-day return history, mean=0.0019, std=0.0132.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0019, std=0.0132, min=-0.0325, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-09] Drug Stocks Reporting on May 10: XON, ARIA, CPRX & More How is the Earnings Picture Evolving now that a large part of the first-quarter 2016 earnings season has come through with 87.2% (as of May 6) of the S&P 500 members having already reported results? This season is likely to finish as the fourth straight quarter of earnings declines for the S&P 500 index. Moreover, this trend of earnings declines is expected to continue into the second quarter as well. With several pharma and major biotech companies having released their earnings results, our Q1 scorecard shows that 92.5% of the Medical sector has reported results with a blended beat of 65.3% (the percentage of companies that have beaten both EPS as well as revenue estimates). Notably, the Medical sector is anticipated to be one of the seven sectors to record earnings growth in the first quarter of 2016, as per our Earnings Trends report. The earnings picture for both the pharma and the biotech sector looks pretty mixed with beats and misses. While in the biotech sector, Amgen Inc. AMGN topped first-quarter earnings and revenues and even raised the outlook for the year, another well-known biotech name Gilead lagged both earnings and revenue estimates even though it kept its outlook for the year intact. Among the other biotech stocks, Biogen, Celgene, Alexion and AbbVie managed to post mixed results, while some others came up with disappointing results and outlook for the year. Pharma giants like Johnson & Johnson JNJ , Pfizer and Bristol-Myers Squibb surpassed first-quarter earnings and revenue expectations and also raised the outlook for the year. Eli Lilly raised its outlook for the year despite an earnings miss while Glaxo expects core earnings growth of 10-12% at constant exchange rate in 2016. With several medium and small-sized drug companies still to report first-quarter 2016 results, let's see what awaits these drug stocks when they report their first-quarter results on May 10. What Awaits these Drug Stocks? Jazz Pharmaceuticals plcJAZZ , a biopharmaceutical company, has a portfolio of offerings targeting sleep and hematology/oncology disorders. Focus will be on the performance of marketed products including Xyrem, Defitelio and Erwinaze among others along with that of commercialization plans for Defitelio in the U.S., and the company's business development plans. Jazz's Earnings ESP of +6.11% and a Zacks Rank #3 (Hold) make us confident of an earnings beat this quarter (read more: Jazz Q1 Earnings: A Beat in the Cards for the Stock ). Palo Alto, CA-based Anacor Pharmaceuticals, Inc.ANAC is a biopharmaceutical company focused on the discovery, development and commercialization of small-molecule therapeutics derived from its boron chemistry platform. Anacor's track record so far has been mixed with the company missing estimates in two of the trailing four quarters with an average negative surprise of 16.68%. The company's Zacks Rank #4 (Sell) when combined with an ESP -32.35% makes a b\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": "-0.0168", "answer_numeric": -0.016779, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0168 (i.e., on a bad day with 5% probability, the loss exceeds 1.68%). CVaR(95%) = -0.0264.", "metadata": {"var": -0.016779, "cvar": -0.026385, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160628_0549", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2016-06-28", "context_summary": "VLUE: 60-day return history, mean=-0.0006, std=0.0095.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0006, std=0.0095, min=-0.0356, max=0.0158\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-06-27] [\"FedEx, Oracle, Adobe and Alcoa are part of Zacks Earnings Preview: For Immediate Release Chicago, IL -June 27, 2016 - Zacks.com releases the list of companies likely to issue earnings surprises. This week's list includes FedEx ( FDX ), Oracle ( ORCL ), Adobe ( ADBE ) and Alcoa ( AA ). To see more earnings analysis, visit https://at.zacks.com/?id=3207 . Every day, Zacks.com makes their Bull Stock of the Day available, free of charge. To see it, click here . Q2 Earnings Season Gets Underway No one is expected to pay attention to earnings given the unexpected Brexit vote, but the Q2 earnings season has gotten underway, with results from 10 S&P 500 members already out. All of these early reporters, which includes major operators like FedEx ( FDX ), Oracle ( ORCL ) and Adobe ( ADBE ), have fiscal quarters ending in May, but get clubbed as part of the June quarter tally. We have another 11 index members with fiscal quarters ending in May on deck to report results this week. All in all, we will have seen Q2 results from almost two dozen S&P 500 members by the time Alcoa ( AA ) comes out with its results on July 11 th . We are about three weeks away from the reporting cycle really ramping up. Expectations for the Quarter Total earnings for the 10 index members that have reported results are up +4.1% on +4.2% higher revenues, with 60% beating EPS estimates and equal proportion coming ahead of top-line expectations. Comparison of the Q2 results thus far with prior periods offers a mixed picture. But it's likely too small a sample to draw any conclusions from in any case. For Q2 as a whole, total earnings for the S&P 500 are expected to be down -6.1% on -0.7% lower revenues, with growth in negative territory for 9 of the 16 Zacks sectors. As has been the pattern in other recent periods, the Energy sector remains the biggest drag on the aggregate growth picture, with total earnings for the sector expected to be down -78.9% on -27.1% lower revenues. Excluding the Energy sector, earnings for the rest of the index would be down -2.7%. Estimates for Q2 faithfully followed the well-trodden path of previous quarters. As negative as this revisions trend looks, it is nevertheless an improvement over what we had seen in the comparable period(s) in other recent quarters. The improved commodity-price backdrop and the reduced dollar drag are some of the explanations for this development. It will be interesting to see if this trend of decelerated negative revisions will continue this earnings season. But we will have to wait a few more weeks to get a better read on this development after companies start reporting June quarter results and guide towards Q3 estimates. Current estimates for Q3 are showing flat growth from the year-earlier level. Expectations Beyond Q2 Growth is expected to be negative in 2016 Q2 and flat in the following quarter. The only meaningful positive earnings growth this year is expected to come from the last quarter of the year, which is then expe\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": "-0.0142", "answer_numeric": -0.014194, "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%) = -0.0256.", "metadata": {"var": -0.014194, "cvar": -0.025564, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160517_0552", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2016-05-17", "context_summary": "IVV: 60-day return history, mean=0.0012, std=0.0075.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0012, std=0.0075, min=-0.0122, max=0.0238\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-16] [\"Uber China Rival Didi Targets New York IPO In 2017\", \"With Buffett Betting Big, Is Apple\\u2019s Stock a Buy? With Warren Buffett\\u2019s Berkshire Hathaway buying $1 billion in stock, see what the charts recommend.\", \"Japanese firms expect more strong-yen headwinds TOKYO--Faced with a stronger yen, Japanese companies are reporting lower annual profits for the first time in four years, and projecting tepid earnings growth for the current year. The results for the financial year ended in March underscore how the record profits that many companies enjoyed in recent years depended on a weaker currency.\", \"Warren Buffett's Berkshire Hathaway took new 9.8 mln share stake in Apple in Q1\", \"Apple shares up 2.2% in premarket trade\", \"Apple's stock surges after Warren Buffett discloses new share stake Apple Inc.'s stock surged 2% in premarket trade Monday, after Warren Buffett's Berkshire Hathaway Inc. disclosed in a regulatory filing that it took a new 9.8 million share stake in the technology giant during the first quarter. That would represent about 0.2% of Apple's shares outstanding, according to FactSet data. Other moves Berkshire made include selling 99% of its stake in Procter & Gamble Co. to just 315,400 shares, trimming its stake in Wal-Mart Stores Inc. by 1.7% to 55.2 million shares. Berkshire also boosted its stake in Phillips 66 by 23% to 75.6 million shares, increased its stake in Liberty Media Corp. to 30 million shares, and slightly raised its stake in Deere & Co. and International Business Machines Corp. .\", \"Warren Buffett's Apple shares could be down $181 million since March Warren Buffett's investment vehicle Berkshire Hathaway Inc.'s new investment in Apple Inc. could be worth about $181.2 million less than it was 6 1/2 weeks ago, at the end of the first quarter. Berkshire's 13F filing showed that it owned a new 9,811,747 stake in Apple as of March 31, when the stock closed at $108.99, or 20% above Friday's closing price of $90.52. The filing did not disclose at what prices the shares were bought. The volume-weighted average price of Apple's stock during the quarter was $99.59. At that price, if its position in Apple was unchanged, Berkshire could have lost about $89 million on its Apple stake through Friday.\", \"A.M. Funds Roundup: How Are Your Mad Money Picks Doing?\", \"Warren Buffett\\u2019s Berkshire took new $1 billion Apple stake Legendary investor also sold entire AT&T position Warren Buffett\\u2019s Berkshire Hathaway took a new stake in Apple during the first quarter, valued at about $1 billion as of March 31.\", \"Apple Inc. jumps 1.4% to $91.67 in early trade after Berkshire Hathaway reveals stake\", \"Berkshire Bought Apple, Dumped AT&T in 1Q Berkshire Hathaway (BRK.B) disclosed a new, roughly $1.1 billion stake in Apple in documents filed Monday morning with securities regulators. The filings show that Berkshire added 9.8 million Apple shares that were valued at $1.069 billion as of the end of March, when Apple's stock traded at $\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": "-0.0115", "answer_numeric": -0.011492, "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%) = -0.0121.", "metadata": {"var": -0.011492, "cvar": -0.012109, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190213_0555", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2019-02-13", "context_summary": "BNB-USD: 60-day return history, mean=0.0134, std=0.0518.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0134, std=0.0518, min=-0.1244, max=0.1396\nMarket regime: sideways\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": "-0.0776", "answer_numeric": -0.077636, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0776 (i.e., on a bad day with 5% probability, the loss exceeds 7.76%). CVaR(95%) = -0.1103.", "metadata": {"var": -0.077636, "cvar": -0.1103, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200724_0558", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IEF"], "decision_date": "2020-07-24", "context_summary": "IEF: 60-day return history, mean=0.0002, std=0.0026.", "question": "Asset: IEF\nDaily returns (past 60 days): mean=0.0002, std=0.0026, min=-0.0062, max=0.0075\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": "-0.0040", "answer_numeric": -0.004023, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0040 (i.e., on a bad day with 5% probability, the loss exceeds 0.40%). CVaR(95%) = -0.0057.", "metadata": {"var": -0.004023, "cvar": -0.005686, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220930_0561", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2022-09-30", "context_summary": "XLE: 60-day return history, mean=0.0015, std=0.0213.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0015, std=0.0213, min=-0.0481, max=0.0434\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-29] [\"After Hours Most Active for Sep 29, 2022 : MCHI, MU, QQQ, AMZN, AAPL, BEKE, FDMT, FE, NKE, GE, T, DIS The NASDAQ 100 After Hours Indicator is down -7.41 to 11,157.37. The total After hours volume is currently 80,336,294 shares traded. The following are the most active stocks for the after hours session: iShares MSCI China ETF (MCHI) is -0.1142 at $42.77, with 4,285,006 shares traded., following a 52-week high recorded in today's regular session. Micron Technology, Inc. (MU) is +0.1 at $50.11, with 3,651,914 shares traded. Smarter Analyst Reports: Micron to Unveil Memory Design Center in Atlanta Invesco QQQ Trust, Series 1 (QQQ) is +0.27 at $272.14, with 3,310,772 shares traded. This represents a 1.06% increase from its 52 Week Low. Amazon.com, Inc. (AMZN) is +0.1 at $114.90, with 2,292,612 shares traded. As reported by Zacks, the current mean recommendation for AMZN is in the \\\"buy range\\\". Apple Inc. (AAPL) is -0.18 at $142.30, with 2,280,068 shares traded. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". KE Holdings Inc (BEKE) is unchanged at $16.26, with 2,243,117 shares traded. As reported by Zacks, the current mean recommendation for BEKE is in the \\\"buy range\\\". 4D Molecular Therapeutics, Inc. (FDMT) is unchanged at $8.22, with 1,998,543 shares traded. As reported in the last short interest update the days to cover for FDMT is 7.734705; this calculation is based on the average trading volume of the stock. FirstEnergy Corp. (FE) is unchanged at $37.18, with 1,597,393 shares traded. FE's current last sale is 83.55% of the target price of $44.5. Nike, Inc. (NKE) is -3.18 at $92.15, with 1,143,383 shares traded. As reported by Zacks, the current mean recommendation for NKE is in the \\\"buy range\\\". General Electric Company (GE) is -0.39 at $62.34, with 1,119,674 shares traded. As reported by Zacks, the current mean recommendation for GE is in the \\\"buy range\\\". AT&T Inc. (T) is -0.02 at $15.51, with 1,021,939 shares traded., following a 52-week high recorded in today's regular session. Walt Disney Company (The) (DIS) is -0.0501 at $97.40, with 1,013,168 shares traded. As reported by Zacks, the current mean recommendation for DIS 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.\", \"Lions Gate (LGF.A) Set to Rebrand Starzplay as Lionsgate+ Lions Gate Entertainment (LGF.A) recently announced that it is going to be rebranding Starzplay as Lionsgate+ in 35 countries outside the United States and Canada. The new brand look with a graphics package, color palette and design elements is expected to bring a differentiated identity and build on the brand equity for Lionsgate. Though Lions Gate retains its Starz brand in the United States and Canada along with Starzplay Arabia and south and southeast Asia's Lionsgate Play. Strong Portfolio of Movies & Shows to Boost Subscriber Growth Lionsgate benefits from th\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": "-0.0294", "answer_numeric": -0.029401, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0294 (i.e., on a bad day with 5% probability, the loss exceeds 2.94%). CVaR(95%) = -0.0401.", "metadata": {"var": -0.029401, "cvar": -0.040126, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20221220_0564", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2022-12-20", "context_summary": "XLV: 60-day return history, mean=0.0016, std=0.0118.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0016, std=0.0118, min=-0.0214, max=0.0244\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-19] [\"US STOCKS-Wall Street falls fourth straight day as recession worries nag By Sin\\u00e9ad Carew and Sruthi Shankar Dec 19 (Reuters) - Wall Street closed lower on Monday for a fourth straight session with Nasdaq leading declines as investors shied away from riskier bets, worried the Federal Reserve's tightening campaign could push the U.S. economy into a recession. The three major U.S. stock indexes have been under pressure since Wednesday, when Fed Chair Jerome Powell took a hawkish tone while the central bank raised interest rates. Powell promised further rate increases even as data showed signs of a weakening economy. The S&P 500 .SPX, the Dow Jones industrials .DJI and the Nasdaq have sold off sharply for December and are on track for their biggest annual declines since the 2008 financial crisis. While U.S. Treasury yields gained, investors ran from stocks, eyeing prospects of safer bets as they worried about the likelihood of a recession in 2023 according to Brian Overby, senior markets strategist at Ally. \\\"Investors are asking why do I want to take those risks going into 2023 with the Fed's stance still aggressive when I can get such a good yield on the fixed income market place,\\\" he said. The Dow Jones Industrial Average .DJI fell 162.92 points, or 0.49%, to 32,757.54, the S&P 500 .SPX lost 34.7 points, or 0.90%, to 3,817.66 and the Nasdaq Composite .IXIC dropped 159.38 points, or 1.49%, to 10,546.03. The biggest decliners among S&P industry sectors were communications services .SPLRCL, which fell 2.2%, consumer discretionary .SPLRCD, down 1.7% and technology .SPLRCT, which lost 1.4%. Energy .SPNY outperformed, closing up 0.13% as the sole industry out of 11 to manage a gain. Market heavyweights such as Apple Inc AAPL.O, Microsoft Corp MSFT.O and Amazon.com Inc AMZN.O created some of the biggest drags on the market. Trading in Tesla Inc TSLA.Owas volatile with the electric carmaker closing down 0.24% after falling as much as 2.8% during the session. This was after a Twitter poll that showed a majority of respondents want Tesla Chief Executive Elon Musk to step down as CEO of the social media platform. Meta Platforms META.O shares finished down 4.1% after the European Commission said it could impose a fine of up to 10% of the tech conglomerate's annual global turnover if evidence showed an infringement of the EU's antitrust laws. L3Harris Technologies Inc LHX.N lost 3.6% after the U.S. defense contractor said it would buy hypersonic engine manufacturer Aerojet Rocketdyne Holdings Inc AJRD.N for $4.7 billion. Aerojet added 1.3%. Shares of casino operatorsMelco Resorts & EntertainmentMLCO.O tumbled just under 8% and Wynn Resorts WYNN.O lost 5.2% while Las Vegas Sands Corp LVS.Nfell 2.3% after Macau said on Friday that six casino firms will invest around $15 billion as part of new 10-year contracts they signed to operate in the world's biggest gambling hub. Declining issues outnumbered advancing ones on the NYSE by a 2.80-to-1 ratio; on Nasda\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": -0.014775, "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": -0.014775, "cvar": -0.019019, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20161114_0567", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2016-11-14", "context_summary": "ACWI: 60-day return history, mean=-0.0004, std=0.0073.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0004, std=0.0073, min=-0.0235, max=0.0202\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-11-11] [\"Trumped: Apple, Home Depot, Nike\\u2019s Asian Suppliers Tumble\", \"Why the Nasdaq was alone among stock markets in sliding lower The weakness in the Nasdaq on Thursday is important to understand. There are two major factors at play, in explaining both the isolated weakness and the broader strength.\", \"Apple and Trump: Can a tax cut for overseas cash heal wounds? Cook to employees: we must move forward together Apple could benefit from repatriation-tax holiday president-elect Donald Trump has proposed, but it may have to fight the new White House on immigration.\", \"U.S. stocks open lower as post-election rally stalls U.S. stocks retreated on Friday as a dramatic postelection rally ran out of steam. The S&P 500 index fell 5 points, or 0.2%, to 2,163. The Dow Jones Industrial Average , which surged to record highs on Thursday, slid 18 points, or 0.1%, to 18,793. The Nasdaq Composite Index shed 21 points, or 0.3%, to 5,193. Oil prices moved sharply lower, weighing on energy shares. Amazon.con Inc. weighed on the technology sector as the tech giant was on track for a fifth straight weekly loss. Other big tech losers were Chinese e-commerce giant Baidu Inc. and Apple Inc. . The S&P was on track for its best week since October 2014, while the Dow was on track for its best week since December 2011.\", \"Foxconn profit declines on Sharp Corp. losses HONG KONG -- Foxconn Technology Group, the world's biggest assembler of Apple Inc. gadgets, reported a decline in third-quarter net profit, weighed by losses at recently acquired Japanese electronics maker Sharp Corp.\", \"A.M. Funds Roundup: Buffett Bullish On Stocks; Loeb Buys Big Apple Stake; Trumping Gold\", \"Dan Loeb\\u2019s Third Point: In With AAPL, BABA; Out With ATVI Billionaire hedge fund manager Dan Loeb has snapped up large stakes in Apple (AAPL) and Alibaba (BABA), and continued to expand his stake in Facebook (FB). But he has turned his back on Activision Blizzard (ATVI).\", \"Dow knifes to uncharted territory, Nasdaq treads water amid post-election volatility Focus: Technology sector treads water, Retail comes to life, Steel and industrial metals take flight, Apple violates major support From a strictly technical standpoint, the U.S. benchmarks\\u2019 post-election price action remains firmly bullish. On a headline basis, the Dow Jones Industrial Average has spiked 990 points across five sessions, reaching all-time highs, while the S&P 500 has extended its breakout, rising within striking distance of record territory.\", \"UPDATED: Why Alibaba Singles Day Could Boost Revenue 48% Alibaba Group Holdings (BABA) declared another sales record on its biggest shopping day of the year, Singles Day on Nov. 11.But the Chinese internet retailer's shares were down more than 2% in Friday. Read More>>\", \"Apple\\u2019s Tax Holiday, Western\\u2019s Trump Risk, Per Morgan Stanley Apple (AAPL) stands to benefit the most from any U.S. tax holiday on overseas cash, writes Morgan Stanley\\u2019s Katy Huberty, while disk drive 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": "-0.0107", "answer_numeric": -0.010683, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0107 (i.e., on a bad day with 5% probability, the loss exceeds 1.07%). CVaR(95%) = -0.0184.", "metadata": {"var": -0.010683, "cvar": -0.018445, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160714_0570", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2016-07-14", "context_summary": "TIP: 60-day return history, mean=0.0002, std=0.0010.", "question": "Asset: TIP\nDaily returns (past 60 days): mean=0.0002, std=0.0010, min=-0.0031, max=0.0032\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": "-0.0014", "answer_numeric": -0.001382, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0014 (i.e., on a bad day with 5% probability, the loss exceeds 0.14%). CVaR(95%) = -0.0020.", "metadata": {"var": -0.001382, "cvar": -0.002013, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200914_0573", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2020-09-14", "context_summary": "QUAL: 60-day return history, mean=0.0010, std=0.0110.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0010, std=0.0110, min=-0.0339, max=0.0167\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-11] Ambarella Stock Could See Further Downside Ambarella Incorporated stock (NASDAQ: AMBA) is down 22% since the beginning of this year, but at the current price of $47 per share, we believe that Ambarella stock has a significant downside. Why is that? Our belief stems from the fact that Ambarella\u2019s stock has risen almost 35% from the low seen in early 2019. Our dashboard What Factors Drove 34% Change In Ambarella Inc. Stock Between 2018 And Now? provides the key numbers behind our thinking, and we explain more below. Ambarella is a semiconductor design company, manufacturing processors used across a variety of applications such as video compression, image processing, and computer vision. The stock rise over the past 2 years came despite a 22% drop in Ambarella\u2019s revenues, which combined with a roughly unchanged outstanding share count, led to a 22% fall in revenue per share (RPS) from 2018 to 2020. However, Ambarella\u2019s P/S ratio rose from about 3.9x at the end of 2018 to 8.7x at the end of 2019, but has dropped to 6.8x now. This fall came due to a drop in the company\u2019s profitability, with EPS falling from $0.57 in 2018 to -$1.35 in 2020, on the back of falling revenues and gross margins. Also, given the volatility of the current situation, there is further possible downside for Ambarella\u2019s multiple when compared to levels seen in the past years \u2013 P/S of 5.9x at the start of 2018, and 3.9x as recently as early 2019. So what\u2019s the likely trigger and timing to this downside? The global spread of coronavirus, and the resulting lockdowns and quarantine has led to a drop in demand for computing devices. Further, the rise in competitors in the video compression and computer vision markets has led to a drop in selling prices, weighing down company revenue. Ambarella\u2019s revenue for Q2 2021 came in at $50.1 million vs $56.4 million for the same period last year, and with expenses not dropping at the same rate, EPS came in at -$0.43 vs -$0.31. We expect this revenue drop to continue in the medium term. We believe Ambarella\u2019s Q3 results in December will confirm this and will also likely accompany a lower 2021 guidance. Regardless, if there isn\u2019t clear evidence of containment of the virus anytime soon, we believe the stock will see its P/S multiple decline from the current level of 6.8x to around 6x, which combined with a slight reduction in revenues and margins could result in the stock price shrinking to as low as $40. Want a more balanced portfolio instead? Here\u2019s a top quality portfolio to outperform the market, with over 100% return since 2016, versus 55% for the S&P 500. Comprised of companies with strong revenue growth, healthy profits, lots of cash, and low risk. It has outperformed the broader market year after year, consistently. See all Trefis Price Estimates and Download Trefis Data here What\u2019s behind Trefis? See How It\u2019s Powering New Collaboration and What-Ifs For CFOs and Finance Teams | Product, R&D, and Marketing Teams The views and opinions expre\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": "-0.0243", "answer_numeric": -0.024265, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0243 (i.e., on a bad day with 5% probability, the loss exceeds 2.43%). CVaR(95%) = -0.0291.", "metadata": {"var": -0.024265, "cvar": -0.02909, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200609_0576", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2020-06-09", "context_summary": "USMV: 60-day return history, mean=0.0012, std=0.0170.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0012, std=0.0170, min=-0.0253, max=0.0221\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-08] [\"UBS Maintains Buy on Adobe, Raises Price Target to $450\", \"UBS Maintains Buy on Adobe, Raises Price Target to $450\", \"3 Top E-Commerce Stocks to Watch in June Many e-commerce businesses have seen tailwinds this year as conditions created by the novel coronavirus pandemic resulted in stores closing and spending migrating to digital channels. With many brick-and-mortar businesses beginning to reopen in conjunction with coronavirus restrictions being eased, June could provide valuable data about what the future of retail looks like. Investors interested in e-commerce stocks should keep an eye on Shopify (NYSE: SHOP), Baozun (NASDAQ: BZUN), and Adobe Systems (NASDAQ: ADBE) this month. Image source: Getty Images. 1. Shopify Shopify provides software that allows businesses to easily create and manage online-retail websites, and it's one of the e-commerce space's hottest stocks. Shares are crushing the market in 2020, climbing roughly 89.5% year to date after rallying 187% in 2019. SHOP data by YCharts. Shopify has posted torrid growth as it's brought more large companies on board its platform and become solidified as the category-leading e-commerce services provider for small-and-medium-size enterprises. The company saw heightened merchant-customer additions and shopper engagement as the novel coronavirus began disrupting brick-and-mortar retail operations in mid-March. Shopify stock hit a lifetime high in May, but shares have actually pulled back over the last couple of weeks despite the S&P 500 index climbing roughly 8% across the same stretch. The e-commerce company's valuation is currently down roughly 13% from the lifetime high it hit in May. With brick-and-mortar retail businesses beginning to reopen in the U.S. and other territories, Shopify's coronavirus-related momentum could be tested in June. Despite the potential for near-term volatility, the company's long-term growth outlook remains promising. E-commerce will only become more important for businesses, and pullback on the stock could present an entry point for long-term investors. 2. Baozun Baozun is sometimes referred to as \\\"the Shopify of China\\\" because it also provides website-creation tools and other e-commerce services. However, most of Baozun's customers are large companies, and its core business hinges on providing services for Western brands aiming to expand their presence in China's fast-growing e-commerce market. The stock is up roughly 4% year to date following Baozun's first-quarter earnings beat and encouraging Q2 guidance it published on June 2. Even with shares now in positive territory across 2020's trading, they're still down roughly 48% from their lifetime high two years ago due to slowing growth and tensions between the U.S. and China. Baozun is seeing business pick back up as the Chinese economy recovers from coronavirus-related conditions, but the country's increasingly fraught relationship with the U.S. could create obstacles to a sustained stock rebound. Phase on\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": "-0.0253", "answer_numeric": -0.025309, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0253 (i.e., on a bad day with 5% probability, the loss exceeds 2.53%). CVaR(95%) = -0.0253.", "metadata": {"var": -0.025309, "cvar": -0.025309, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190920_0579", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-09-20", "context_summary": "LINK-USD: 60-day return history, mean=-0.0043, std=0.0407.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0043, std=0.0407, min=-0.0981, max=0.1107\nMarket regime: sideways\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": "-0.0619", "answer_numeric": -0.061913, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0619 (i.e., on a bad day with 5% probability, the loss exceeds 6.19%). CVaR(95%) = -0.0804.", "metadata": {"var": -0.061913, "cvar": -0.080431, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190902_0582", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2019-09-02", "context_summary": "VEA: 60-day return history, mean=-0.0001, std=0.0079.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=-0.0001, std=0.0079, min=-0.0274, max=0.0137\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-08-30] [\"Nvidia Stock Is a Long-Term Winner Predicting what technologies will be prevalent in ten years is difficult. Who\\u2019s to say whether the dominant smartphone will be Apple\\u2019s (NASDAQ:) iPhone or Alphabet\\u2019s (NASDAQ:, NASDAQ:GOOG) Pixel? But Nvidia (NASDAQ:), and Nvidia stock are easier to bet on because the company is powering the technological pillars of tomorrow. Source: Hairem / Shutterstock.com Many sectors, including agriculture, transportation, drones and cloud computing, are turning to artificial intelligence. Often referred to as A.I., this technology requires an insane amount of computing power. The company best suited to provide that computing power is Nvidia. As a result, NVDA and Nvidia stock are in prime position to be long-term winners. Earlier this year, I took a very . I suggest reading the column if you are curious about the company\\u2019s long-term outlook. I would not necessarily say that the company\\u2019s catalysts make NVDA stock a screaming buy, but they do make the shares worth considering for long-term investors. Valuing Nvidia Stock Nvidia stock was on an unsustainable flight path, rallying hundreds of percent in just a few years. In Oct. 2015, NVDA was changing hands in the $16 range. Now in the mid-$160s, NVDA is still up ten-fold from those levels. At its high near $300, NVDA stock had jumped almost 18 times from its late 2015 levels. Despite the pullback of Nvidia stock, Nvidia\\u2019s core business hasn\\u2019t been knocked off course. Previously, crypto miners were inflating demand for the company\\u2019s products, but that trend has since slowed greatly, hurting Nvidia\\u2019s results, Advanced Micro Devices (NASDAQ:) experienced a similar phenomenon, although that company has done a better job of sidestepping the pain. As it stands, AMD is forecast to have positive earnings and revenue growth this year and explosive growth next year. Unfortunately for Nvidia, it\\u2019s not in the same boat. Analysts, on average, expect its sales to slump 8% this year and predict that its earnings will tumble 18.8% in 2019. Investors are already aware that this is a down year for NVDA and that there\\u2019s not much to be done about it. But NVDA stock is treading higher in recent weeks, even as the trade war continues. The biggest risk facing Nvidia stock, in my view, is estimates for next year, Nvidia\\u2019s fiscal 2021. Analysts, on average, expect its top line to jump nearly 20% to $12.91 billion and predict that its earnings per share will surge about 31% to $7.08. Those figures would surpass Nvidia\\u2019s fiscal 2019 results and put it back on the path of growth. They would also makes its forward price-earnings ratio, which currently trading at 23.6, more reasonable. If the average estimates materialize, and the trailing 12 month P/E ratio of Nvidia stock stays around its current level of 38, its price would reach roughly $270. Trading NVDA Stock $270 does not seem like a great price for many investors, given that NVDA \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": "-0.0107", "answer_numeric": -0.010732, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0107 (i.e., on a bad day with 5% probability, the loss exceeds 1.07%). CVaR(95%) = -0.0219.", "metadata": {"var": -0.010732, "cvar": -0.021885, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200828_0585", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2020-08-28", "context_summary": "VTI: 60-day return history, mean=0.0023, std=0.0107.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0023, std=0.0107, min=-0.0335, max=0.0253\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-08-27] [\"Tesla\\u2019s Market Cap Hits $400 Billion The world\\u2019s most valuable car company just hit another huge milestone.\", \"Podcast: Rental Prices Drop 1.7% Between First and Second Quarters U.S. manufacturers\\u2019 inventories of civilian aircrafts and parts are up 6% since the beginning of the year. The impact of the pandemic has landlords lowering prices to keep tenants. And Salesforce\\u2019s shares are on the rise.\", \"Which is better, the Honda Pilot or VW Atlas? One thing is for sure, they\\u2019ve both got plenty of room for people and stuff Let\\u2019s take a closer look at how these two people-haulers compare.\", \"Why Chinese Social Media Apps Are Increasingly Vital to Luxury Goods Makers If you\\u2019re a luxury goods company, you want affluent, young Chinese consumers to share their love for your product. Here\\u2019s who\\u2019s winning.\", \"The stock market\\u2019s rebound is nowhere near over, and midcap exposure is probably what you need Research into stock-market disruptions and recoveries shows conventional wisdom about large-cap stocks is wrong Research into stock market disruptions and recoveries shows conventional wisdom about large-cap stocks is wrong.\", \"Interest Rates Will Remain Low for Years. These High-Quality Stocks Might Offer the Income You Need. Stocks with ample and secure dividends could benefit as investors search for yield.\", \"Salesforce\\u2019s 30% stock rally this week is a possible \\u2018nightmare\\u2019 scenario for the Dow committee As part of a shake-up in the stocks comprising the Dow Jones Industrial Average announced earlier this week, Salesforce.com Inc. was among a trio of companies included in the venerable benchmark, but now its stock is soaring.\", \"HP and Dell Report Earnings Thursday. Here\\u2019s What To Expect. PC sales have been boosted by the stay-at-home trend. Why that might not be enough to lift Dell and HP shares.\", \"Smartphone shipments could drop almost 10% this year, says IDC Worldwide smartphone shipments could fall 9.5% this year given pressures from the pandemic, according to market-research company IDC. Shipments fell 17% from a year earlier in the second quarter, with the market showing \\\"visible signs of economic concerns.\\\" IDC said in a release that before the pandemic, analysts expected a return to growth in smartphone sales that is \\\"obviously not going to happen.\\\" While analysts predict a 9% year-over-year increase in volumes for 2021, \\\"that is only due to the large drop in 2020,\\\" said IDC research director Nabila Popal in the release. \\\"The real recovery won't happen until 2022 when smartphone volumes return to pre-COVID levels.\\\" Though there's some hype around 5G devices especially with Apple Inc. expected to introduce its first 5G-enabled iPhones later this year, IDC program vice president Ryan Reith said in the release that IDC analysts \\\"still believe that consumer demand for 5G is very low and when that is combined with the economic headwinds facing the market, the pressure to dr\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": "-0.0116", "answer_numeric": -0.011607, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0116 (i.e., on a bad day with 5% probability, the loss exceeds 1.16%). CVaR(95%) = -0.0282.", "metadata": {"var": -0.011607, "cvar": -0.02817, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160125_0588", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-01-25", "context_summary": "QQQ: 60-day return history, mean=-0.0013, std=0.0130.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0013, std=0.0130, min=-0.0351, max=0.0285\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-22] [\"Apple Pay Use Low, Says Piper, But It\\u2019s Expected to Grow Apple\\u2019s (AAPL) Apple Pay electronic payments system is the \\u201cshare leader,\\u201d writes Piper Jaffray\\u2019s Gene Munster in a note to clients this evening, although usage in total \\u201ccontinues to be low.\\\"Apple\\u2019s Apple Pay lets a customer transaction at a retail point-of-sale by pressing the home button of the iPhone, or passing an Apple Watch by a contactless card reader at the register.Munster, who has an Overweight rating on Apple stock, and a $179 price target, writes that 2015 was the \\u201cyear of adoption,\\u201d and he\\u2019s seen a surge in banks accepting Apple Pay even lately from 515 as of September of last year to 930 presently, 913 of which are in the U.S., with one in Canada and 1 in Australia.2016, he writes, will be a year of new features:\", \"Apple Looks Dirt Cheap; Why Stock Can Rise 50% With shares down 25% from last year\\u2019s peak and its valuation \\u201cnear a historical low\\u201d Apple is priced to buy.\", \"Google shelling out $1 billion just to stay on Apple\\u2019s iPhone: report Android generates $31 billion in revenue, says court transcript The search engine paid $1 billion to Apple in 2014 just to keep its Google search on iPhones, say court documents seen by Bloomberg News.\", \"Stressed out by this market? Why it\\u2019s giving you a great opportunity \\u2014 really Critical information before the U.S. market opens It\\u2019s been an awful start to the year for markets, but there could be a silver lining, argues one financial blogger. Meanwhile, today\\u2019s call suggests selling rallies and buying dips. Our chart shows the beating that the ruble\\u2019s getting.\", \"Apple: Buy Side Too Pessimistic on iPhone, Says Stifel Stifel Nicolaus\\u2019s Aaron Rakers this morning is the latest to weigh in with his thoughts on the debate over shipments of Apple\\u2019s (AAPL) iPhone, which have received one after another markdown in recent weeks.The flashpoint has been the March-ending fiscal Q2 for Apple, where there have been the most cuts in estimates of late. Rakers thinks investors have become too pessimistic.Writes Rakers, who has a Buy rating on Apple stock, and a $140 price target, \\\"Given the continued debate on how investors are thinking about iPhone shipments into the March '16 quarter (we believe buy-side sentiment has moved into the mid-40M range) we wanted to provide a more thorough review / analysis of iPhone shipment trends on a geographical basis (utilizing Gartner\\u2019s historical sell-thru estimates).\\\"\", \"It\\u2019s not yet time to sell, but it is time to get defensive Many investors have been bailing on this market as quickly as they possibly could, but the best thing to do here is not panic.\", \"Apple\\u2019s new massive underground auditorium, as seen in drone footage Drone footage takes you flying above the Apple Campus 2 Construction for Apple Inc.\\u2019s new campus, dubbed Apple Campus 2, is well under way, as evidenced by the latest \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": "-0.0237", "answer_numeric": -0.023697, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0237 (i.e., on a bad day with 5% probability, the loss exceeds 2.37%). CVaR(95%) = -0.0328.", "metadata": {"var": -0.023697, "cvar": -0.032813, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160121_0597", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2016-01-21", "context_summary": "IWM: 60-day return history, mean=-0.0024, std=0.0125.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0024, std=0.0125, min=-0.0326, max=0.0288\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-20] Commit To Buy American Electric Power Company At $45, Earn 5.7% Using Options Investors considering a purchase of American Electric Power Company, Inc. (Symbol: AEP) shares, but tentative about paying the going market price of $58.07/share, might benefit from considering selling puts among the alternative strategies at their disposal. One interesting put contract in particular, is the January 2018 put at the $45 strike, which has a bid at the time of this writing of $2.55. Collecting that bid as the premium represents a 5.7% return against the $45 commitment, or a 2.8% annualized rate of return (at Stock Options Channel we call this the YieldBoost ). Selling a put does not give an investor access to AEP's upside potential the way owning shares would, because the put seller only ends up owning shares in the scenario where the contract is exercised. And the person on the other side of the contract would only benefit from exercising at the $45 strike if doing so produced a better outcome than selling at the going market price. ( Do options carry counterparty risk? This and six other common options myths debunked ). So unless American Electric Power Company, Inc. sees its shares decline 23% and the contract is exercised (resulting in a cost basis of $42.45 per share before broker commissions, subtracting the $2.55 from $45), the only upside to the put seller is from collecting that premium for the 2.8% annualized rate of return. Below is a chart showing the trailing twelve month trading history for American Electric Power Company, Inc., and highlighting in green where the $45 strike is located relative to that history: The chart above, and the stock's historical volatility, can be a helpful guide in combination with fundamental analysis to judge whether selling the January 2018 put at the $45 strike for the 2.8% annualized rate of return represents good reward for the risks. We calculate the trailing twelve month volatility for American Electric Power Company, Inc. (considering the last 253 trading day closing values as well as today's price of $58.07) to be 20%. For other put options contract ideas at the various different available expirations, visit the AEP Stock Options page of StockOptionsChannel.com. In mid-afternoon trading on Wednesday, the put volume among S&P 500 components was 1.33M contracts, with call volume at 1.62M, for a put:call ratio of 0.82 so far for the day, which is unusually high compared to the long-term median put:call ratio of .65. In other words, there are lots more put buyers out there in options trading so far today than would normally be seen, as compared to call buyers. Find out which 15 call and put options traders are talking about today . Top YieldBoost Puts of the S&P 500 \u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect \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": "-0.0226", "answer_numeric": -0.022576, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0226 (i.e., on a bad day with 5% probability, the loss exceeds 2.26%). CVaR(95%) = -0.0277.", "metadata": {"var": -0.022576, "cvar": -0.027719, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150217_0600", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2015-02-17", "context_summary": "XLP: 29-day return history, mean=0.0008, std=0.0088.", "question": "Asset: XLP\nDaily returns (past 29 days): mean=0.0008, std=0.0088, min=-0.0182, max=0.0170\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-02-13] [\"London wants a piece of New York\\u2019s startups U.K. led startup funding in Europe last month, raising $294 million The U.K. government launched a new initiative called HQUK this week to try and lure foreign businesses to the British isles.\", \"Goldman traded its reputation for quick profits It was once known as an investment bank but now it\\u2019s a hedge fund It was once known as an investment bank but now it\\u2019s a hedge fund, says David Weidner.\", \"Apple price target raised to $135 at BMO Capital Markets\", \"Apple price target raised to $150 at UBS\", \"Apple developing 'mega-ecosystem' as target raised to $150 NEW YORK (MarketWatch) - Apple Inc.'s price target was raised to $150 at UBS and to $135 at BMO Capital Markets on Friday, as analysts continue to grow more bullish on the iPhone maker's product line. On Thursday, Apple's stock closed at a record split-adjusted high of $126.46, valuing the company at more than $736 billion, the highest valuation of any U.S. company in history. UBS analyst Steven Milunovich, who rates Apple a buy, said Apple is creating a \\\"mega-ecosystem\\\" that is quickly turning the company into a platform, rather than just a device, company. \\\"Apple the platform company may take it to $1 trillion,\\\" he said. At $150, UBS is one of the most bullish brokerages on Apple's stock, behind just Cantor Fitzgerald, which has a $160 target on Apple. Meanwhile, BMO analyst Keith Bachman, who has an outperform rating on the stock, said he thinks Apple is adding \\\"far more users than are leaving the brand\\\" and that its fiscal 2015 iPhone unit forecast may be conservative. Shares of Apple edged 0.4% higher to $126.98 in premarket trade. To get to a $1 trillion market valuation, shares of Apple will have to reach $172.\", \"Apple\\u2019s expanding \\u2018Appleverse\\u2019 will lure you in Apple creating mega-ecosystem as target raised to $150 at UBS Apple wants iOS to permeate all aspects of consumers\\u2019 lives, more than it already does.\", \"Lovelorn single people should move to these cities Some singletons this Valentine\\u2019s Day may be looking for love in all the wrong places (or cities).\", \"Week in Review: Musk, Holocaust Chic and Homer go into \\u2018insane mode\\u2019 Marek Fuchs reviews the top events of the week, including news from Elon Musk, Holocaust Chic and Homer Simpson.\", \"American Express: After Costco, the Deluge\", \"10 biggest financial-market events this week Rising oil prices, energy stocks, Greece and Ukraine led the news Rising oil prices, energy stocks, Greece and Ukraine led the news.\", \"Groupon rallies as Zynga sinks; Tesla struggles Apple shrugs off analysts\\u2019 price target hikes Groupon, Zynga, Tesla, and Apple are among notable movers in Friday\\u2019s session.\", \"David Tepper's Appaloosa slashes equity holdings; closes Apple, Facebook positions NEW YORK (MarketWatch) -- David Tepper's hedge fund Appaloosa Management disclosed that the value of its equity holdings were reduced by 40% late last year, accor\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": "-0.0116", "answer_numeric": -0.011628, "explanation": "Historical simulation VaR at 95%: sort the 29 daily returns and take the 5th percentile. VaR(95%) = -0.0116 (i.e., on a bad day with 5% probability, the loss exceeds 1.16%). CVaR(95%) = -0.0149.", "metadata": {"var": -0.011628, "cvar": -0.014921, "confidence": 0.95, "n_returns": 29, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20191011_0604", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2019-10-11", "context_summary": "PALL: 60-day return history, mean=0.0034, std=0.0163.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=0.0034, std=0.0163, min=-0.0606, max=0.0381\nMarket regime: sideways\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": "-0.0191", "answer_numeric": -0.01914, "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%) = -0.0363.", "metadata": {"var": -0.01914, "cvar": -0.036295, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181016_0609", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2018-10-16", "context_summary": "XLP: 60-day return history, mean=0.0001, std=0.0071.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0001, std=0.0071, min=-0.0250, max=0.0142\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-15] [\"GoPro to Sell Curated Video Clips to the Adobe Stock Marketplace\", \"Adobe Sees FY19 Total Adobe Sales Growth ~20% Year Over Year, Sees Digital Media Annualized Recurring Sales ~$1.4B Of Net New ARR\", \"Adobe Reaffirms Q4 Sales, EPS Guidance\", \"UPDATE: Adobe Reaffirms Q4 Guidance: Sales ~$2.42B vs $2.43B Estimate, Adj. EPS $1.87 vs $1.89 Est.\", \"Adobe To Host Call Mon., Oct. 15, 2018 At 5 p.m. EDT To Discuss Numerous Drivers For Growth Of Total Addressable Market To Expand From ~$83M In 2020 To ~$108M By 2021\", \"Adobe shares are up 5.8% after the company reaffirmed Q4 guidance; The company sees 20% year-over-year sales growth in FY19.\", \"5 Stocks Moving In Tuesday's After-Hours Session\", \"5 Stocks Moving In Tuesday's After-Hours Session\", \"Adobe shares are up 5.8% after the company reaffirmed Q4 guidance; The company sees 20% year-over-year sales growth in FY19.\", \"Adobe To Host Call Mon., Oct. 15, 2018 At 5 p.m. EDT To Discuss Numerous Drivers For Growth Of Total Addressable Market To Expand From ~$83M In 2020 To ~$108M By 2021\", \"UPDATE: Adobe Reaffirms Q4 Guidance: Sales ~$2.42B vs $2.43B Estimate, Adj. EPS $1.87 vs $1.89 Est.\", \"Adobe Sees FY19 Total Adobe Sales Growth ~20% Year Over Year, Sees Digital Media Annualized Recurring Sales ~$1.4B Of Net New ARR\", \"Adobe Reaffirms Q4 Sales, EPS Guidance\", \"GoPro to Sell Curated Video Clips to the Adobe Stock Marketplace\", \"Factors Setting the Tone for SAP SE (SAP) in Q3 Earnings SAP SESAP is scheduled to report third-quarter 2018 results on Oct 18. Notably, the company has a mixed record of earnings surprises in the trailing four quarters, with an average beat of 5.6%. The company reported second-quarter 2018 non-IFRS earnings of \\u20ac0.98 ($1.17) per share, up 4.3% on a year-over-year basis. However, the bottom line fell short of the Zacks Consensus Estimate of $1.18 per share. Total revenues, on non-IFRS basis, were \\u20ac6.01 billion ($7.15 billion), up 4% year over year (up 10% at constant currency), exceeding the Zacks Consensus Estimate of $7.11 billion. A flourishing cloud business and strong growth of support revenues aided top-line growth in the last reported quarter. What to Expect? The Zacks Consensus Estimate for third-quarter earnings is pegged at $1.26 per share, indicating an increase of 5.9% on a year-over-year basis. Revenues are estimated to be around $6.97 billion, indicating a rise of 6.1% from the year-ago quarter. Let's see how things are shaping up for this announcement. Factor Influencing Q3 Results SAP's Cloud and Software business have been consistent growth drivers for quite some time. In fact, Cloud and software business revenues came in at \\u20ac5.25 billion in the second quarter, up 4% year over year driven by Cloud subscriptions & support revenues of \\u20ac1.30 billion, which surged 40% from the year-ago quarter. Further, the company's human capital management (''HCM'') applications continue to boost the top line, including the likes of SuccessFactors and SAP Fieldgl\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": -0.010826, "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%) = -0.0175.", "metadata": {"var": -0.010826, "cvar": -0.017502, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20191202_0612", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2019-12-02", "context_summary": "IYR: 60-day return history, mean=0.0001, std=0.0064.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0001, std=0.0064, min=-0.0163, max=0.0121\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": "-0.0107", "answer_numeric": -0.010688, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0107 (i.e., on a bad day with 5% probability, the loss exceeds 1.07%). CVaR(95%) = -0.0139.", "metadata": {"var": -0.010688, "cvar": -0.013883, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220720_0615", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2022-07-20", "context_summary": "IAU: 60-day return history, mean=-0.0017, std=0.0086.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=-0.0017, std=0.0086, min=-0.0238, max=0.0151\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": "-0.0159", "answer_numeric": -0.015924, "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%) = -0.0211.", "metadata": {"var": -0.015924, "cvar": -0.021116, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210728_0617", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2021-07-28", "context_summary": "EEM: 60-day return history, mean=-0.0010, std=0.0103.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0010, std=0.0103, min=-0.0280, max=0.0204\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-07-27] [\"Advanced Micro Devices Q2 21 Earnings Conference Call At 5:00 PM ET (RTTNews) - Advanced Micro Devices Inc. (AMD) will host a conference call at 5:00 PM ET on July 27, 2021, to discuss Q2 21 earnings results. Advanced Micro Devices is scheduled to report results on Tuesday, July 27, after market close. To access the live webcast, log on to http://ir.amd.com The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Advanced Micro Devices (AMD) Q2 2021 Earnings Call Transcript Image source: The Motley Fool. Advanced Micro Devices (NASDAQ: AMD) Q2 2021 Earnings Call Jul 27, 2021, 5:00 p.m. ET Contents: Prepared Remarks Questions and Answers Call Participants Prepared Remarks: Operator Hello, and welcome to the AMD second-quarter 2021earnings conference call [Operator instructions] As a reminder, this conference is being recorded. It's now my pleasure to turn the call over to Laura Graves, corporate vice president of investor relations. Laura, please go ahead. Laura Graves -- Corporate Vice President of Investor Relations Thank you, and welcome to AMD's second-quarter 2021 financial results conference call. By now, we hope you have had the opportunity to review a copy of our earnings press release and slides. If you have not reviewed these documents yet, they can be found on the Investor Relations page of amd.com. Participants on today's conference call are Dr. Lisa Su, our president and chief executive officer; and Devinder Kumar, our executive vice president, chief financial officer, and treasurer. This is a live call and will be replayed via webcast on our website. Before we begin, I would like to note that Saeid Moshkelani, senior vice president and general manager of our client business; and Ruth Cotter, senior vice president of worldwide marketing, human resources, investor relations and strategy, will attend the Jefferies semiconductor and hardware summit on Tuesday, August 31. Devinder Kumar will attend the Deutsche Bank technology conference on Friday, September 10. 10 stocks we like better than Advanced Micro Devices When our award-winning 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 Advanced Micro Devices 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 June 7, 2021 And our third-quarter 2021 quiet time is expected to begin at the close of business on Friday, September 10. Today's discussion contains forward-looking statements based on current beliefs, assumptions and expectations, speak only as of today and as such, involve risks and uncertainties that could cause actual results to differ materially from our current expectations. We refer to the cautionary statemen\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": -0.019286, "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%) = -0.0232.", "metadata": {"var": -0.019286, "cvar": -0.023157, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160623_0620", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["CORN"], "decision_date": "2016-06-23", "context_summary": "CORN: 60-day return history, mean=0.0010, std=0.0161.", "question": "Asset: CORN\nDaily returns (past 60 days): mean=0.0010, std=0.0161, min=-0.0326, max=0.0305\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": "-0.0311", "answer_numeric": -0.031087, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0311 (i.e., on a bad day with 5% probability, the loss exceeds 3.11%). CVaR(95%) = -0.0326.", "metadata": {"var": -0.031087, "cvar": -0.0326, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210929_0625", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2021-09-29", "context_summary": "MTUM: 60-day return history, mean=0.0005, std=0.0105.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0005, std=0.0105, min=-0.0270, max=0.0228\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-28] [\"Logitech's MX Keys Mini is a compact keyboard for minimalists Logitech has unveiled the MX Keys Mini, a compact keyboard for minimalists who don't want mechanical switches.\", \"Ableton Live 11.1 beta available now with Apple M1 support Ableton Live 11.1 beta available now with Apple M1 support, a new pitch shifting device and more.\", \"How to Buy Used and Refurbished Cameras and Lenses \\\"But it's so expensive,\\\" is what everyone says when a new camera or lens goes on sale. And so I'd like to welcome you to the world of photography that Leica camera users have known about for years. There is a massive benefit to the used and refurbished market for this reason. Don't want to pay $3,000 for that new Sony lens? Do you think that the Canon R5 is way too much money? Well, hyper-focusing on the original price point, I think, is sometimes excessive. It gets in the way of you getting tha\", \"United States Natural Language Processing Market Report 2021 Featuring Google, IBM, Microsoft, Intel, Apple, AWS, Facebook, Inbenta Technologies, Veritone, SAS Institute Dublin, Sept. 28, 2021 (GLOBE NEWSWIRE) -- The \\\"United States Natural Language Processing Market, By Component (Solution and Services), By Deployment (On-Premise, Cloud), By Organization Size (SME's Vs Large Enterprises), By Type, By Application, By End User, By Region, Competition, Forecast & Opportunities, 2026\\\" report has been added to ResearchAndMarkets.com's offering. United States natural language processing market is expected to grow at an impressive rate over the forecast period Growing\", \"1Password can now randomly generate email addresses for logins The Masked Email feature allows you to create unique email addresses for your logins.\", \"1Password can now randomly generate email addresses for logins Since 2019, Sign in with Apple has allowed iPhone and Mac users to protect their privacy by allowing them to generate random email addresses when they need to access a new website, service or app. It\\u2019s one of those small features that can have an outsized impact, and now something similar is coming to 1Password. Like its Apple counterpart, the tool allows you to create unique email addresses for your logins.\", \"Highnote emerges from stealth with $54M and a plan to take on Marqeta in the world of card issuing as a service Fintech startups have thrown a curve ball into the world of financial services, by building more flexible, cheaper and user-friendly tools to businesses and consumers, who in turn are walking away from older incumbents and taking their custom to newer providers. In the latest development, a startup called Highnote is launching with ambitions to make waves in the world of card issuing, by making it easy for any company of any size to provide virtual payment cards to their customers. Founded by PayPal alums, the company is exiting stealth mode today and also announcing $54 million in funding to take its first steps.\", \"IIROC Trading Resumption - STUV Trading resumes in:\", \"Wit\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": "-0.0124", "answer_numeric": -0.01245, "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%) = -0.0219.", "metadata": {"var": -0.01245, "cvar": -0.021895, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220204_0628", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2022-02-04", "context_summary": "SOL-USD: 60-day return history, mean=-0.0094, std=0.0555.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0094, std=0.0555, min=-0.1589, max=0.1630\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-02-03] \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": "-0.0938", "answer_numeric": -0.093845, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0938 (i.e., on a bad day with 5% probability, the loss exceeds 9.38%). CVaR(95%) = -0.1279.", "metadata": {"var": -0.093845, "cvar": -0.127905, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20200306_0631", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2020-03-06", "context_summary": "XLRE: 60-day return history, mean=0.0004, std=0.0121.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0004, std=0.0121, min=-0.0375, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-03-05] [\"Apple, Netflix are latest to pull out of SXSW over outbreak: reports Apple Inc. and Netflix Inc. are reportedly the latest tech companies to pull out of the upcoming South by Southwest festival and conference over coronavirus fears. Multiple news outlets, including Variety and the Hollywood Reporter, said the tech giants have canceled their plans for the giant Austin, Texas, gathering set to start next week. Apple had been scheduled to premiere three Apple TV+ originals at the 2020 SXSW Film Festival, Variety said, and Netflix was to show five new films, according to the Hollywood Reporter. On Sunday, SXSW lost one of its featured speakers, Twitter CEO Jack Dorsey, when the social-media company suspended all non-essential business travel. Amazon.com Inc. and Facebook Inc. have also pulled out of SXSW. The festival, which last year drew more than 400,000 visitors, is still scheduled to go on, despite a number of other tech conferences canceling their events due to the global coronavirus outbreak.\", \"These stocks soared the most after Biden burned Bernie on Super Tuesday Health-care stocks led the market rally after Biden took 10 of 14 states, becoming the Democratic front runner Health-care stocks led the market rally after Biden took 10 of 14 states, becoming the Democratic front runner.\", \"All 30 Dow stocks fall premarket, led by Goldman Sachs; only 1 stock is down less than 1% Shares of all 30 components of the Dow Jones Industrial Average are falling in premarket trading Thursday, with 29 losing more than 1%. The unanimous selloff comes as Dow futures tumbled 363 points, or 2.1%. The biggest decliner was Goldman Sachs Group Inc.'s stock, which dropped 3.2%, while the most-active stock was Apple Inc.'s , which fell 2.4%. The best performer was Johnson & Johnson's stock which slipped 0.8%.\", \"Will Coronavirus Push the World Into Recession? Sonal Desai Isn\\u2019t Convinced. Sonal Desai, chief investment officer of Franklin Templeton\\u2019s fixed income group, isn\\u2019t convinced a global recession is inevitable.\", \"Coronavirus brings opportunities in gold \\u2014 just like in the good, old days The conditions for gold are optimal The conditions for gold are optimal, says Nigam Arora.\", \"Apple price target trimmed at Deutsche Bank Apple Inc. could see a hit of nearly $5 billion due to COVID-19's spread in China, but signs point to supply issues easing next month, according to analysts at Deutsch Bank. In a note Thursday afternoon, analysts reduced their estimate for Apple's fiscal second quarter, which now stand at earnings of $2.69 a share on sales of $60.4 billion, down from $2.99 a share on sales of $65.1 billion. The reduction was due to the effects of the new coronavirus spreading through China and the resulting inaction in an important country for Apple's manufacturing and sales, but analysts said that reports from iPhone manufacturer Foxconn Technology Co. Ltd. suggest effects should decline after March. \\\"There has been an increasing flo\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": "-0.0233", "answer_numeric": -0.023303, "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%) = -0.0293.", "metadata": {"var": -0.023303, "cvar": -0.029318, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200409_0634", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2020-04-09", "context_summary": "MTUM: 60-day return history, mean=-0.0026, std=0.0222.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0026, std=0.0222, min=-0.0383, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-04-08] [\"iPhone Maker Foxconn To Produce Ventilators In US\", \"Hearing Piper Sandler Raised Apple Price Target From $260 To $300; Unconfirmed\", \"JP Morgan Maintains Overweight on Apple, Lowers Price Target to $335\", \"10 Biggest Price Target Changes For Wednesday\", \"Shares of several technology companies are trading higher amid overall market strength on optimism that US coronavirus cases could soon leveling off. NOTE: Some names in the sector have potentially benefited from recent work-at-home trends.\", \"Watching Apple Shares; Hearing Traders Circulating Word Of Earlier Article From China Publication Suggesting Apple Cut Orders From China Suppliers\", \"Global Payments Firm Papaya Global Publishes International COVID-19 Crisis Guides For Employers\", \"The Show Must Go On \\u2013 Event Industry Rising To The Challenge Of COVID-19\", \"Netflix, YouTube, Disney+: Which Video Streaming Platform Do Teens Watch The Most?\", \"Disney Shares Climb 7% As Video On Demand Service Crosses 50M Subscribers\", \"Netflix, YouTube, Disney+: Which Video Streaming Platform Do Teens Watch The Most?\", \"The Show Must Go On \\u2013 Event Industry Rising To The Challenge Of COVID-19\", \"Global Payments Firm Papaya Global Publishes International COVID-19 Crisis Guides For Employers\", \"Watching Apple Shares; Hearing Traders Circulating Word Of Earlier Article From China Publication Suggesting Apple Cut Orders From China Suppliers\", \"Shares of several technology companies are trading higher amid overall market strength on optimism that US coronavirus cases could soon leveling off. NOTE: Some names in the sector have potentially benefited from recent work-at-home trends.\", \"10 Biggest Price Target Changes For Wednesday\", \"JP Morgan Maintains Overweight on Apple, Lowers Price Target to $335\", \"Hearing Piper Sandler Raised Apple Price Target From $260 To $300; Unconfirmed\", \"iPhone Maker Foxconn To Produce Ventilators In US\", \"Disney Shares Climb 7% As Video On Demand Service Crosses 50M Subscribers\", \"Netflix, YouTube, Disney+: Which Video Streaming Platform Do Teens Watch The Most?\", \"The Show Must Go On \\u2013 Event Industry Rising To The Challenge Of COVID-19\", \"Global Payments Firm Papaya Global Publishes International COVID-19 Crisis Guides For Employers\", \"Watching Apple Shares; Hearing Traders Circulating Word Of Earlier Article From China Publication Suggesting Apple Cut Orders From China Suppliers\", \"Shares of several technology companies are trading higher amid overall market strength on optimism that US coronavirus cases could soon leveling off. NOTE: Some names in the sector have potentially benefited from recent work-at-home trends.\", \"10 Biggest Price Target Changes For Wednesday\", \"JP Morgan Maintains Overweight on Apple, Lowers Price Target to $335\", \"Hearing Piper Sandler Raised Apple Price Target From $260 To $300; Unconfirmed\", \"iPhone Maker Foxconn To Produce Ventilators In US\", \"Mercedes-Benz GLS-Class: New full-size luxury SUV fits the bill A review of the all-new 2020 SUV\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": "-0.0383", "answer_numeric": -0.038264, "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%) = -0.0383.", "metadata": {"var": -0.038264, "cvar": -0.038264, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220921_0637", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2022-09-21", "context_summary": "XLRE: 60-day return history, mean=-0.0011, std=0.0128.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0011, std=0.0128, min=-0.0375, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-20] [\"Why Investors Found Apple Stock Tempting Today What happened Most investors are cool on tech stocks these days, but enough of them warmed to Apple (NASDAQ: AAPL) Tuesday to give an encouraging little rise to its share price. Thanks to some news about its global operations and positive comments from an analyst, the company's stock closed nearly 2% higher on the day, in contrast to the over 1% decline of the S&P 500 index. So what In an official company blog post, Apple revealed that will soon start raising prices in its App Store for certain regions and countries. These include all countries that use the euro as a currency, plus a clutch of other large and small markets in Europe, Asia, and South America. Non-eurozone countries that will see increases include Egypt, Chile, Japan, and South Korea. The hikes will start to take effect on Wednesday, Oct. 5, Apple said. The move comes as the U.S. dollar continues to be a strong currency when matched against peers like the euro or the Japanese yen. A strong dollar reduces the take for U.S.-based Apple from such currencies, hence the need to make adjustments. It should be noted that this isn't a unique, one-off move by the company. It periodically makes pricing adjustments based on factors like this. Meanwhile, noted Apple tracker Daniel Ives from Wedbush reiterated his outperform (read: buy) recommendation on Apple stock, at a $220 per share price target. In a new analyst note, Ives cited the \\\"brisk sales\\\" and lengthening customer wait times for the new iPhone 14 as a key reason for his continued optimism. Now what Apple's services business -- which includes the App Store and its massive inventory of titles -- has become increasingly important to the company. Compared to Apple's other revenue stream (products), it's growing more robustly, to the point where it comprised nearly $20 billion in revenue in the tech giant's most recently reported quarter. Meanwhile, Apple device owners tend to be relatively affluent and fond of their apps, so there shouldn't be too much resistance to the price hikes. 10 stocks we like better than Apple When our award-winning 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 17, 2022 Eric Volkman has positions in Apple. The Motley Fool has positions in and recommends Apple. The Motley Fool recommends the following options: long March 2023 $120 calls on Apple and short March 2023 $130 calls on Apple. The Motley Fool has a disclosure policy. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The 7 Best Biotech Stocks to Buy InvestorPlace -\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": "-0.0222", "answer_numeric": -0.022248, "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%) = -0.0300.", "metadata": {"var": -0.022248, "cvar": -0.029972, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190813_0642", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-08-13", "context_summary": "ETH-USD: 60-day return history, mean=-0.0020, std=0.0481.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0481, min=-0.1554, max=0.0854\nMarket regime: sideways\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": "-0.0935", "answer_numeric": -0.093463, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0935 (i.e., on a bad day with 5% probability, the loss exceeds 9.35%). CVaR(95%) = -0.1382.", "metadata": {"var": -0.093463, "cvar": -0.138235, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160715_0645", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2016-07-15", "context_summary": "EMB: 60-day return history, mean=0.0010, std=0.0037.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0010, std=0.0037, min=-0.0097, max=0.0100\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": "-0.0041", "answer_numeric": -0.004066, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0041 (i.e., on a bad day with 5% probability, the loss exceeds 0.41%). CVaR(95%) = -0.0076.", "metadata": {"var": -0.004066, "cvar": -0.007562, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20191107_0648", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2019-11-07", "context_summary": "XLI: 60-day return history, mean=0.0014, std=0.0106.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0014, std=0.0106, min=-0.0310, max=0.0215\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-06] [\"Robinhood glitch is letting users trade with unlimited amounts of borrowed cash Bug gives traders infinite leverage \\u2014 but it\\u2019s also a very bad idea to try A glitch in the stock-trading app Robinhood is allowing investors to trade with apparently unlimited amounts of borrowed money.\", \"Why Warren Buffett Should Buy Walgreens The Berkshire Hathaway CEO has been searching in vain for a large acquisition that could absorb a chunk of Berkshire\\u2019s growing cash balance. Walgreens Boots Alliance could be it.\", \"Roku remains a promising stock even after this year\\u2019s surge Roku is the most fairly valued pure play in the over-the-top space Roku is the most fairly valued pure play in the over-the-top space, writes Beth Kindig.\", \"Sonos could be the next hardware acquisition after Fitbit, says analyst D.A. Davidson analyst Tom Forte said Wednesday that Sonos Inc. looks well positioned to see its stock appreciate either due to improved investor perception or an acquisition, in the wake of Alphabet Inc.'s plans to purchase Fitbit Inc. \\\"On the bad block of hardware companies, we consider Sonos to be: 1) the best house on the block and 2) the one adjacent to the mansion on the neighboring block, Apple ,\\\" Forte wrote. He sees Sonos as similar to Apple due to his view that both companies make superior products with a focus on design and are able to charge more than competitors. \\\"We see Sonos as a natural acquisition target for Apple, given the similarities in: 1) product quality, 2) design acumen, and 3) premium brands,\\\" Forte wrote. \\\"Just as Fitbit fills a void for Google when it comes to healthcare-related data, acquiring Sonos could materially advance Apple's connected home efforts (an area we believe it needs improvement and where its own product, the HomePod, was a disappointment).\\\" Forte rates Sonos shares at buy with a $20 target price. The stock is up 37% so far this year as the S&P 500 has risen 23%, but it remains below its $15 initial-public-offering price from August 2018.\", \"Corporate tax avoidance demands a global solution The world should tax multinationals based on the destination of sales Multinational corporations have long avoided paying their full share of taxes, and time is running out to agree on a fair global solution.\", \"Apple Stock Is Up 65% This Year. More Gains Could Be Coming. The move has lifted the company\\u2019s market valuation by $450 billion, to $1.114 trillion. Bank of America Merrill Lynch says the move can continue.\", \"How the Saudi Aramco IPO Will Affect Other Oil Giants When the world\\u2019s largest oil producer goes public, it will surely mean a new dynamic for all the players in the oil industry.\", \"Apple expands privacy explanations on website, but actual policy remains unchanged The site updates are part of Apple\\u2019s push to distinguish itself from data-hungry rivals Google and Facebook The site updates are part of Apple\\u2019s push to distinguish itself from data-hungry rivals Google and Faceb\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": "-0.0193", "answer_numeric": -0.019313, "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%) = -0.0275.", "metadata": {"var": -0.019313, "cvar": -0.027467, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170110_0651", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2017-01-10", "context_summary": "IWM: 60-day return history, mean=0.0017, std=0.0097.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0017, std=0.0097, min=-0.0131, max=0.0303\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-09] [\"The Medicines Co LDL-Lowering Drug Positive in Phase II The Medicines CompanyMDCO announced positive top-line results from a Day 180 interim analysis of the ongoing ORION-1 phase II study on its pipeline candidate, Inclisiran (formerly PCSK9si), for the treatment of hypercholesterolemia. The Medicines Company is developing Inclisiran under a collaboration agreement with Alnylam Pharmaceuticals, Inc. ALNY , which was inked in early 2013. The Medicines Company is solely responsible for the development and commercialization of the candidate. The Medicines Company's three-month share price movement shows that the stock has outperformed the Zacks classified Medical - Biomedical and Genetics industry. Specifically, the company lost 1.7%, while the industry lost 3.7%. ORION-1 is a placebo-controlled, double-blinded, randomized, dose-finding phase II study. It compares and evaluates the effect of various doses of single or multiple subcutaneous injections of Inclisiran. The study was conducted in a total of 501 patients with atherosclerotic cardiovascular disease (ASCVD) or ASCVD-risk equivalents (hypercholesterolemia). Interim data demonstrated that Inclisiran led to a significant and durable reduction of LDL (low-density lipoprotein) cholesterol up to Day 210. Inclisiran was well tolerated throughout the study, with infrequent and mild or moderate injection site reactions. Data from the study will be presented at the annual meeting of the American College of Cardiology, scheduled to be held in Mar 2017. The company expects to move Inclisiran into phase III development (OROPN-4 study) after discussions with regulatory authorities. Meanwhile, the company announced the initiation of ORION-2 for evaluating the efficacy, safety and tolerability of Inclisiran in patients with homozygous familial hypercholesterolemia (HoFH). Moreover, the company commenced enrollment of ORION-1 patients in the phase II ORION-3 extension study, which will evaluate the efficacy, safety and tolerability of long-term dosing of Inclisiran. Note that, apart from Inclisiran, The Medicines Company has several interesting pipeline candidates targeting key focus areas. Three of these candidates - MDCO-216 (atherosclerotic plaque burden), ABP-700 (general anesthesia for surgical care) and Carbavance (treatment of hospitalized patients with serious gram-negative bacterial infections) - have blockbuster potential. The Medicines Company Price The Medicines Company Price | The Medicines Company Quote Zacks Rank & Other Key Picks The Medicines Company currently carries a Zacks Rank #2 (Buy). A couple of other favorably placed stocks in the health care sector include Orexigen Therapeutics, Inc. OREX and Arbutus Biopharma Corporation ABUS . Both the stocks sport a Zacks Rank #1 (Strong Buy). You can see the complete list of today's Zacks #1 Rank stocks here . Orexigen's loss estimates widened from $8.93 to $8.17 for 2016 and from $5.19 to $2.17 for 2017 over the last 60 days. The company pos\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": "-0.0123", "answer_numeric": -0.012324, "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%) = -0.0128.", "metadata": {"var": -0.012324, "cvar": -0.012816, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201111_0656", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-11-11", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0021, std=0.0516.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0021, std=0.0516, min=-0.1372, max=0.1508\nMarket regime: sideways\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": "-0.0806", "answer_numeric": -0.080581, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0806 (i.e., on a bad day with 5% probability, the loss exceeds 8.06%). CVaR(95%) = -0.1083.", "metadata": {"var": -0.080581, "cvar": -0.108267, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210908_0659", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2021-09-08", "context_summary": "XLV: 60-day return history, mean=0.0015, std=0.0063.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0015, std=0.0063, min=-0.0153, max=0.0138\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-07] [\"3 Top Stocks to Buy in September It's been a topsy-turvy summer for investors, but things don't cool down just because fall is around the corner. September is often a sleepy period, but there are some interesting companies that are still expected to make waves this month. Adobe (NASDAQ: ADBE), fuboTV (NYSE: FUBO), and Walt Disney (NYSE: DIS) are three companies that have some potential catalysts kicking in this month. Let's take a closer look to see why they are some of the top stocks to buy in September. Image source: Getty Images. Adobe Earnings season has come and gone, but some companies like Adobe march to the beat of a different fiscal drummer. The desktop publishing giant reports fresh financials for its fiscal third quarter in two weeks. Adobe isn't just the company behind Photoshop and PDF files. Its Creative Cloud suite of digital publishing tools is the cloud-based standard for more than just creative types. Adobe is also also a major player in the booming e-signature market. This is also a far more consistent growth stock than you might think, with steady and growing subscription revenue now accounting for 92% of the top-line mix. It has rattled off six consecutive fiscal years of revenue growth of 15% or better. It's a strong bet to stretch that streak to seven after posting 26% and 23% top-line growth in its first two fiscal quarters. A master of the \\\"beat and raise\\\" game that is so rewarding to shareholders, it would be a shock if Adobe doesn't land ahead of Wall Street targets again in two weeks. It's also helping make its own luck on a per-share basis by perpetually buying back more shares than its prints out. Adobe's fiscal year-end share count has declined for five years. fuboTV The fastest-growing live TV streaming service has had a wild first year of trading. fuboTV stock has more than tripled since going public at $10 just 11 months ago, but it's trading for less than half of its late-December peak. The sports-heavy platform has seen its revenue accelerate throughout its brief tenure on the market, soaring 196% in its latest quarter. fuboTV isn't one of the handful of companies reporting financial results this month, but it is putting one important component of its master plan into action in September. Last week, fuboTV rolled real-time sporting event stats and free-to-play games out of beta, coinciding with the new round of South American Qatar World Cup 2022 qualifying matches. Subscribers can now opt to have their game screens resized to make room for its FanView stats. There are also predictive games that are free to play but with real cash prizes for the best prognosticators. With a small yet fast-growing sports-centric subscriber base of more than 680,000 premium accounts, all of this month's new toys are just the beginning. The real star will come later this year when fuboTV launches its own sportsbook through a dedicated smartphone app. fuboTV viewers already trust the platform for their programming and with thei\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": "-0.0100", "answer_numeric": -0.009993, "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%) = -0.0125.", "metadata": {"var": -0.009993, "cvar": -0.012454, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220811_0662", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2022-08-11", "context_summary": "BNB-USD: 60-day return history, mean=0.0042, std=0.0416.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0042, std=0.0416, min=-0.1307, max=0.0907\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-08-10] \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": "-0.0650", "answer_numeric": -0.065009, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0650 (i.e., on a bad day with 5% probability, the loss exceeds 6.50%). CVaR(95%) = -0.1067.", "metadata": {"var": -0.065009, "cvar": -0.106732, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20190614_0665", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-06-14", "context_summary": "ETH-USD: 60-day return history, mean=0.0080, std=0.0451.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0080, std=0.0451, min=-0.0767, max=0.1382\nMarket regime: sideways\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": "-0.0522", "answer_numeric": -0.052169, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0522 (i.e., on a bad day with 5% probability, the loss exceeds 5.22%). CVaR(95%) = -0.0701.", "metadata": {"var": -0.052169, "cvar": -0.070142, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180130_0673", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2018-01-30", "context_summary": "VTI: 60-day return history, mean=0.0017, std=0.0042.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0017, std=0.0042, min=-0.0066, max=0.0104\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-01-29] [\"Alibaba, Foxconn lead big investment in Chinese electric-car maker Tech companies branch out into burgeoning industry Chinese e-commerce giant Alibaba Group Holding Ltd. and Foxconn Technology Group have co-led a 2.2 billion yuan ($348 million) funding round into Chinese electric-vehicle manufacturer Xiaopeng Motors, marking Alibaba\\u2019s first big investment in a car maker\", \"Immersion enters settlement and license deal with Apple\", \"Immersion settles with Apple, reaches license agreements Immersion Corp. said Monday it has entered into settlement and license deals with Apple Inc. . Immersion, which develops touch feedback technology, had filed patent infringement lawsuits against Apple for technology used in iPhones and the trackpads used in MacBooks. Immersion said the terms of the agreements reached with Apple are confidential. The stock, which was still inactive in premarket trade, has tumbled 30% over the past 12 months, while the S&P 500 has gained 25%.\", \"Apple stock drops after report of iPhone X production cut Apple Inc. shares are down 0.5% in premarket trading Monday after a report in the Nikkei Asia Review said that the company planned to trim its iPhone X production target to 20 million for the March quarter, half of what it expected a few months ago. The Nikkei Asian Review attributes the production cut to lower-than-anticipated sales of the device. The phone's price tag of at least $999 could be a key reason for the demand issues, the publication said. Wall Street analysts have also been weighing in on the prospect of significantly weaker-than-expected iPhone X sales, with analysts at JP Morgan predicting last week that Apple would cut its build orders for the device by 50% in the March quarter, causing them to take a more cautious stance on a number of Apple suppliers. Apple shares are up 41% over the past 12 months, while the Dow Jones Industrial Average is up 30%.\", \"Robinhood\\u2019s crypto biz has drawn nearly 1 million in user interest: Watch out Coinbase! Coinbase is the No. 1\\u2013ranked U.S. crypto exchange platform over the past six months. Can Robinhood give it a run for its money in bitcoin, Ethereum trading? New-age brokerage platform Robinhood is jumping in on the cryptocurrency craze, declaring that it will allow trading in bitcoin and Ethereum\\u2019s currency starting in February, with more virtual currencies expected to be added soon.\", \"This \\u2018parabolic\\u2019 move for stocks has some investors nervous, but should it? Critical information for the U.S. trading day Is this bull market finally starting to feel a bit top-heavy? According to official MarketWatch records, this marks the 698th time that very question has been asked in this space since Trump took office.\", \"\\u2018Get Out\\u2019 is headed back to theaters after its 4 Oscar nominations \\u2018Get Out\\u2019 grossed $254.7 million at box offices worldwide on just a $4.5 million production budget It has been almost a year since \\u201cGet Out\\u201d opened i\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": "-0.0044", "answer_numeric": -0.004436, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0044 (i.e., on a bad day with 5% probability, the loss exceeds 0.44%). CVaR(95%) = -0.0055.", "metadata": {"var": -0.004436, "cvar": -0.005464, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200520_0678", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2020-05-20", "context_summary": "ITB: 60-day return history, mean=-0.0007, std=0.0357.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=-0.0007, std=0.0357, min=-0.0460, 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": "-0.0460", "answer_numeric": -0.04596, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0460 (i.e., on a bad day with 5% probability, the loss exceeds 4.60%). CVaR(95%) = -0.0460.", "metadata": {"var": -0.04596, "cvar": -0.04596, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200806_0681", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2020-08-06", "context_summary": "EEM: 60-day return history, mean=0.0035, std=0.0140.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0035, std=0.0140, min=-0.0341, max=0.0317\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-08-05] Why MongoDB Stock Is Cheaper Than It Looks MongoDB, Inc. (NASDAQ: MDB) stock has climbed over 65% since the beginning of the year, trouncing the S&P 500's single-digit gains, and has attracted the attention of tech investors. MDB data by YCharts Along with the stock gains, the price-to-sales ratio has run up over 40%, causing some to flinch at its lofty valuation. But this cloud database specialist is worth the price. Let's take a deeper look at its business, the growth plans, and its valuation to see why this stock could be cheaper than it looks. The business of a cloud database MongoDB was founded in 2007 to create a database that could address the shortcomings of legacy relational databases in powering high-performance cloud-based applications. Since then, it has become a developer favorite, consistently ranked as the top non-relational database according to DB-Engines. This popularity has helped it reach $462 million in trailing 12-month revenues and serve more than 18,000 customers in 100 countries. Image source: Getty Images. Over the last three years, the company has had explosive growth, increasing its top line by a 61% compound annual growth rate from fiscal 2017 to its most recent fiscal year ending Jan. 31, 2020. This impressive trend continued into last quarter's 46% year-over-year top-line gain, but the company isn't profitable, as it's pouring its profits into growth efforts. A $977 million pile of cash and marketable securities provide the company with plenty of flexibility to operate this way for years. The company has two core products: MongoDB Enterprise Advanced (EA), its on-premise solution, and Atlas, its cloud-based offering. Atlas only made up 42% of its revenue last quarter, but it's growing faster at 75% year over year and is an important element in driving overall growth. Atlas is key to growth Atlas was released in 2016 as a way for software developers to experience the benefits of its product more easily. As a cloud-based subscription platform, developers just need a sign-on and a credit card to get started. This simple on-ramp allows information technology teams to experiment with the platform in non-mission-critical applications before committing to the technology to take over larger portions of the enterprise. This approach has been highly successful. Atlas customers have almost tripled from 5,700 in January 2018 to 16,800 in its most recent quarter ending April 30, 2020. What's even more exciting is that as a cloud product, the company can keep tabs on what developers are doing. This enables the company to better understand how the product is used, make improvements, and call on customers who've increased usage to discuss upselling opportunities. Although Atlas customers only average around $6,000 to $7,000 in revenue per year, it can be a path to its EA product that typically exceeds $100,000 annually. In its most recent quarter, MongoDB reported 780 customers spending more than $100,000 annually, up from 598 a ye\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": "-0.0144", "answer_numeric": -0.014371, "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%) = -0.0240.", "metadata": {"var": -0.014371, "cvar": -0.023953, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190924_0684", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2019-09-24", "context_summary": "BNB-USD: 60-day return history, mean=-0.0061, std=0.0311.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0061, std=0.0311, min=-0.0801, max=0.0621\nMarket regime: sideways\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": "-0.0520", "answer_numeric": -0.051964, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0520 (i.e., on a bad day with 5% probability, the loss exceeds 5.20%). CVaR(95%) = -0.0780.", "metadata": {"var": -0.051964, "cvar": -0.077976, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190606_0687", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2019-06-06", "context_summary": "LQD: 60-day return history, mean=0.0008, std=0.0024.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0008, std=0.0024, min=-0.0039, max=0.0068\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": "-0.0034", "answer_numeric": -0.003372, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0034 (i.e., on a bad day with 5% probability, the loss exceeds 0.34%). CVaR(95%) = -0.0038.", "metadata": {"var": -0.003372, "cvar": -0.003757, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170111_0690", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2017-01-11", "context_summary": "XLRE: 60-day return history, mean=-0.0000, std=0.0104.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0000, std=0.0104, min=-0.0240, max=0.0206\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-10] [\"Snapchat to set up international HQ in London Snapchat owner Snap Inc. will make London its international headquarters and start booking overseas revenue in all the countries where it has offices, breaking from other tech firms whose headquarters in smaller European countries help them shift profit and lower their taxes.\", \"Here\\u2019s how much ETFs are dominating on the trading floor Of the 15 most active securities in 2016, 14 were ETFs Only one of the 15 most heavily traded issues on the stock market in 2016 was actually a stock. The rest were ETFs,\", \"Charting a slow-motion breakout attempt: Dow back for another crack at 20,000 Focus: Apple\\u2019s breakout attempt, Telecom pulls in to support, IYZ, AAPL, AGCO, VG, ON Technically speaking, the U.S. benchmarks\\u2019 strong bull trend is firmly intact. Consider that the S&P 500 continues to press record territory, after briefly reaching all-time highs last week. Meanwhile, the Nasdaq Composite has broken out, confirming its uptrend, while the Dow Jones Industrial Average remains within striking distance of the marquee 20,000 mark.\", \"Tech Today: Trouble for T-Mo, Buy Twilio, Nvidia A Must-Have? Here are some things going on today in your world of tech:Craig Moffett of the eponymous MoffettNathanson, who has long been a bullish defender of T-Mobile US (TMUS), today cut his rating on the stock to Neutral from Buy, writing that there has been a return of subsidies, and that T-Mo\\u2019s \\u201cAll in\\u201d pricing plan \\u201copens yet another front in the battle over service plan pricing.\\\"\\u201cTo be sure, we still see T-Mobile as the best-positioned operator,\\u201d writes Moffett, \\u201cbut after factoring in the impacts of T-Mobile\\u2019s new pricing, our estimates for T-Mobile are now below consensus for the first time in four years.\\\"T-Mobile shares are up 91 cents, or 1.6%, at $57.58.Canaccord Genuity\\u2019s Richard Davis writes \\u201cthe time has come\\u201d to raise his rating on Internet cloud services vendor Twilio (TWLO) to Buy from Hold, with a $35 price target.\\\"While you can never know where a precise bottom for a stock is,\\u201d observes Davis, \\\"we believe the odds are in our favor that TWLO shares will be higher, perhaps materially so, by the end of this year.\\\"Twilio shares are up 24 cents, or 0.9%, at $28.34.\", \"Charting a slow-motion breakout attempt: Dow back for another crack at 20,000 Focus: Apple\\u2019s breakout attempt, Telecom pulls in to support, IYZ, AAPL, AGCO, VG, ON Technically speaking, the U.S. benchmarks\\u2019 strong bull trend is firmly intact. Consider that the S&P 500 continues to press record territory, after briefly reaching all-time highs last week. Meanwhile, the Nasdaq Composite has broken out, confirming its uptrend, while the Dow Jones Industrial Average remains within striking distance of the marquee 20,000 mark.\", \"Himax: Craig Hallum Cuts to Hold as Microsoft HoloLens Fails to Deliver Shares of display technology vendor Himax Technologies (HIMX) are own\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": "-0.0178", "answer_numeric": -0.017799, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0178 (i.e., on a bad day with 5% probability, the loss exceeds 1.78%). CVaR(95%) = -0.0222.", "metadata": {"var": -0.017799, "cvar": -0.022221, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180119_0693", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2018-01-19", "context_summary": "IAU: 60-day return history, mean=0.0011, std=0.0059.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=0.0011, std=0.0059, min=-0.0132, max=0.0134\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": "-0.0082", "answer_numeric": -0.00819, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0082 (i.e., on a bad day with 5% probability, the loss exceeds 0.82%). CVaR(95%) = -0.0114.", "metadata": {"var": -0.00819, "cvar": -0.011396, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170308_0696", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2017-03-08", "context_summary": "XLE: 60-day return history, mean=-0.0009, std=0.0083.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0009, std=0.0083, min=-0.0202, max=0.0198\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-03-07] [\"LG Electronics Soars On Firm LCD Pricing, But Smartphone Business Drags LG Electronics (066570.Korea) soared 4.2% on Tuesday amid heavy buying after the latest LCD panel prices data alleviated market fears that the LCD panel cycle is peaking out soon.In the first week of March, LCD panel prices across different screen sizes stayed firm and the large-screen 65 inch TVs actually saw an increase in sales price.READ MORE.\", \"Go Long China, Short US: 5 Smart Stock Trades Concerns that U.S. stocks are overvalued may mean it\\u2019s time to buy their cheaper Chinese rivals.\", \"Most Investors Already Bullish On Apple\\u2019s iPhone 8: Any Upside Left? After meeting with over 150 investors globally, JP Morgan concluded that most investors are already on board with the Apple (AAPL) iPhone 8 super cycle trade.\\\"We agree that street expectations of ~100M units of new iPhone builds in 2H17 are now hard to exceed, but upside is likely to come from OLED iPhone mix and much higher ASPs. We have been advising investors to position into explicit OLED iPhone plays like Hon Hai, Samsung SDI or content gainers like WinSemi,LG Innotek and Lens Tech,\\\" reports JP Morgan.READ MORE.\", \"Which Tech Companies Will Win The Augmented Reality Race? Plenty of people have been wary of Snap Inc.'s (SNAP) worth as a social media company, but some may be buying the stock for its future as a camera company, and as a player in augmented reality (AR).Former Piper Jaffray analyst Gene Munster, who now works at AR and VR-focused venture capital firm writes that the question is broader than just Snap, however: With AR primed to come online in the next few years through existing operating systems, Munster has a new report out ranking how major tech players fare in the race to the new reality.\", \"House Republican Jason Chaffetz dangles Sophie\\u2019s choice: Your iPhone or your health? \\u2018Good morning to everyone except Jason Chaffetz\\u2019 Republicans unveiled new legislation this week to replace Obamacare and fix what President Trump describes as \\u201ca complete and total disaster.\\u201d Some sacrifices may be required, says Jason Chaffetz.\", \"Wall Street is at the very heart of American innovation: author Top politicians, says writer William D. Cohan, have bipolar relationships with Wall Street \\u2014 at best We need to understand Wall Street better, focusing not only on uncovering abuses but on the larger picture, placing even those probes into problem areas, which he said are often merited, into a broader context that includes Wall Street\\u2019s manifold services and innovations, argues William D. Cohan, author of \\u201cWhy Wall Street Matters.\\u201d\", \"Threat Of US Protectionism Not Fully Priced Into Tech Markets: Morgan Stanley Morgan Stanley\\u2019s Shawn Kim and team recently took a look at Asian technology companies, arguing that the risk of US protectionism isn\\u2019t fully priced into markets.They write that the tech sector is very exposed to the risk that policies will punis\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": "-0.0146", "answer_numeric": -0.014636, "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%) = -0.0180.", "metadata": {"var": -0.014636, "cvar": -0.018012, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210715_0699", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2021-07-15", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0103, std=0.0804.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0103, std=0.0804, min=-0.1912, max=0.2320\nMarket regime: sideways\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": "-0.1368", "answer_numeric": -0.136781, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1368 (i.e., on a bad day with 5% probability, the loss exceeds 13.68%). CVaR(95%) = -0.1822.", "metadata": {"var": -0.136781, "cvar": -0.182187, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181017_0702", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2018-10-17", "context_summary": "LINK-USD: 60-day return history, mean=0.0048, std=0.0518.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0048, std=0.0518, min=-0.1284, max=0.1304\nMarket regime: sideways\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": "-0.0724", "answer_numeric": -0.072386, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0724 (i.e., on a bad day with 5% probability, the loss exceeds 7.24%). CVaR(95%) = -0.1042.", "metadata": {"var": -0.072386, "cvar": -0.104179, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181011_0704", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2018-10-11", "context_summary": "VTI: 60-day return history, mean=-0.0002, std=0.0060.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0002, std=0.0060, min=-0.0324, max=0.0085\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-10] [\"Stocks Which Set New 52-Week Low Yesterday, October 9th\", \"Applied Materials Option Alert: Nov 23 $37 Calls Sweep (41) near the Ask: 2165 @ $0.991 vs 60 OI; Earnings 11/15 After Close [est] Ref=$34.55\", \"Stocks That Made New 52-Week Lows So Far Today Include: Goldman Sachs, Morgan Stanley, eBay, International Paper, WestRock, Quanta Services, PPG Industries, Vulcan Materials, Illinois Tool Works, Pentair, Affiliated Managers Group, and Goodyear Tire\", \"Stocks That Made New 52-Week Lows So Far Today Include: Goldman Sachs, Morgan Stanley, eBay, International Paper, WestRock, Quanta Services, PPG Industries, Vulcan Materials, Illinois Tool Works, Pentair, Affiliated Managers Group, and Goodyear Tire\", \"Applied Materials Option Alert: Nov 23 $37 Calls Sweep (41) near the Ask: 2165 @ $0.991 vs 60 OI; Earnings 11/15 After Close [est] Ref=$34.55\", \"Stocks Which Set New 52-Week Low Yesterday, October 9th\", \"Why Applied Materials, Inc. Lost 10.2% in September What happened Applied Materials (NASDAQ: AMAT) stock fell 10.2% in September, according to data provided by S&P Global Market Intelligence . Shares lost ground amid a broader sell-off for chip stocks. AMAT data by YCharts Comments from Micron Technology 's chief financial officer indicating continued declines for NAND memory prices and a bearish note on the outlook for the memory-chip industry from Morgan Stanley analyst Shawn Kim resulted in steep sell-offs for Applied Materials and other related semiconductor companies on Sept. 6. The iShares Philadelphia Semiconductor ETF closed the month down 2.8%. So what Applied Materials' semiconductor systems segment accounted for 61% of the company's sales in its July quarter, and combined flash and DRAM memory business accounted for 60% of that revenue. The company has benefited from strong demand for memory chips over the last several years, with its earnings and stock price hitting record highs earlier this year; a downturn for the memory chip market is likely to have a significant, negative impact on performance. Now what Applied Materials' stock has continued to lose ground in October, with continued impact from the market's bearish shift on memory chips and combining with broader market sell-offs to push shares down roughly 11.4% in the month as of this writing. The stock now trades at roughly 7.5 times this year's expected earnings, but the company's profits have historically been tied to cyclical swings in the memory chip and data storage markets -- so investors shouldn't rely on that seemingly low multiple as an indication that the stock is near a bottom. AMAT data by YCharts Applied Materials is expected to report third-quarter earnings in mid-November and is guiding for earnings per share of $0.96 on sales of $4 billion -- targets that underwhelmed the market and led to double-digit sell-offs in August. 10 stocks we like better than Applied Materials When investing geniuses David and Tom Gardner have a stock tip, it can pay to listen. After all\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": -0.007946, "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%) = -0.0163.", "metadata": {"var": -0.007946, "cvar": -0.016301, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220328_0707", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2022-03-28", "context_summary": "BNB-USD: 60-day return history, mean=0.0028, std=0.0341.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0028, std=0.0341, min=-0.0702, max=0.0973\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-03-27] \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": "-0.0566", "answer_numeric": -0.056596, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0566 (i.e., on a bad day with 5% probability, the loss exceeds 5.66%). CVaR(95%) = -0.0644.", "metadata": {"var": -0.056596, "cvar": -0.064399, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20210603_0710", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2021-06-03", "context_summary": "AVAX-USD: 60-day return history, mean=0.0015, std=0.0946.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0015, std=0.0946, min=-0.1912, max=0.2320\nMarket regime: sideways\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": "-0.1485", "answer_numeric": -0.148513, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1485 (i.e., on a bad day with 5% probability, the loss exceeds 14.85%). CVaR(95%) = -0.1701.", "metadata": {"var": -0.148513, "cvar": -0.170136, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160428_0713", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2016-04-28", "context_summary": "ICSH: 60-day return history, mean=0.0001, std=0.0006.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0001, std=0.0006, min=-0.0016, max=0.0016\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": "-0.0008", "answer_numeric": -0.000831, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0008 (i.e., on a bad day with 5% probability, the loss exceeds 0.08%). CVaR(95%) = -0.0015.", "metadata": {"var": -0.000831, "cvar": -0.001535, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20211103_0717", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2021-11-03", "context_summary": "XLV: 60-day return history, mean=0.0002, std=0.0079.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0002, std=0.0079, min=-0.0173, max=0.0142\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-11-02] Got $5,000? 3 Tech Stocks to Buy and Hold For the Long Term $5,000 might not seem like much in the tech sector, where stocks often cost hundreds or thousands of dollars per share. However, the best tech stocks can still transform a modest investment into a small fortune. To identify those long-term winners, investors should focus on companies that are led by visionary CEOs, routinely generate robust growth, and exercise killer competitive advantages. These three tech stocks check all three boxes: Adobe (NASDAQ: ADBE), Microsoft (NASDAQ: MSFT), and AMD (NASDAQ: AMD). 1. Adobe A decade ago, Adobe generated most of its revenue from desktop software. Today, nearly all of its revenue comes from cloud-based services. Adobe's entire business model evolved because CEO Shantanu Narayen pushed the company to transform all of its desktop-based creative software products -- including Photoshop, Illustrator, and Premiere Pro -- into subscription-based cloud services. Adobe also launched new cloud-based e-commerce, marketing, and analytics services for enterprise customers. Image source: Getty Images. This bold transformation locked in Adobe's customers, generated predictable recurring revenue, and widened its moat. As a result, Adobe's annual revenue surged from $4.1 billion in 2013 to $12.9 billion in 2020, while its adjusted earnings per share (EPS) soared from $1.34 to $10.10 per share. Those long-term returns are impressive, but Adobe hasn't run out of room to grow yet. Analysts expect Adobe's revenue to rise 22.5% this year and grow another 15% next year as its Digital Media (creative software) and Digital Experience (enterprise software) clouds continue to expand. Adobe doesn't face many meaningful competitors in the creative software market, its ecosystem is very sticky, and its enterprise-facing businesses should continue to benefit from the ongoing digitization and automation of older businesses. All those qualities make it a solid long-term investment. 2. Microsoft Microsoft also underwent a dramatic cloud-based transformation under a visionary CEO over the past seven years. Satya Nadella, who took over as Microsoft's third CEO in 2014, aggressively expanded the aging tech giant's cloud services with a \"mobile first, cloud first\" mantra. In 2015, Microsoft set a goal to grow its annualized cloud revenue from $6.3 billion to $20 billion by 2018. It hit that target in 2017, then went on to generate a whopping $69 billion in cloud revenue in fiscal 2021. That growth was led by Azure, which competes against Amazon's (NASDAQ: AMZN) Amazon Web Services (AWS) in the cloud platform market, as well as Office 365, Dynamics in the customer relationship management (CRM) market, and enterprise-oriented social network LinkedIn. Microsoft also continued to broaden its hardware portfolio with new Xbox consoles and Surface devices. Between fiscal 2014 and 2021, Microsoft's annual revenue soared from $86.8 billion to $168.1 billion, while its EPS jumped from $2.63 to\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": "-0.0144", "answer_numeric": -0.014396, "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%) = -0.0160.", "metadata": {"var": -0.014396, "cvar": -0.015988, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210720_0719", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-07-20", "context_summary": "DOT-USD: 60-day return history, mean=-0.0115, std=0.0814.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0115, std=0.0814, min=-0.1989, max=0.2810\nMarket regime: sideways\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": "-0.1124", "answer_numeric": -0.112425, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1124 (i.e., on a bad day with 5% probability, the loss exceeds 11.24%). CVaR(95%) = -0.1802.", "metadata": {"var": -0.112425, "cvar": -0.180242, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190718_0721", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2019-07-18", "context_summary": "BNB-USD: 60-day return history, mean=0.0001, std=0.0411.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0001, std=0.0411, min=-0.1010, max=0.0922\nMarket regime: sideways\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": "-0.0650", "answer_numeric": -0.064967, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0650 (i.e., on a bad day with 5% probability, the loss exceeds 6.50%). CVaR(95%) = -0.0885.", "metadata": {"var": -0.064967, "cvar": -0.088502, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210701_0723", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2021-07-01", "context_summary": "XLP: 60-day return history, mean=0.0003, std=0.0066.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0003, std=0.0066, min=-0.0179, max=0.0140\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-06-30] [\"Ably raises $70 million for its developer platform that enables realtime features Ably is a Pub/Sub messaging platform that companies can use to develop realtime features in their products. The company just raised a $70 million Series B funding round co-led by Insight Partners and Dawn Capital. A popular system that lets you create realtime features is called Pub/Sub, as in publish-subscribe.\", \"LG's 'QNED' Mini LED TVs are coming to the US in July LG's lineup of QNED 4K and 8K TVs unveiled late last year will arrive in the US in July, the company has announced.\", \"Amazon\\u2019s Halo app gets better with Movement Health update Amazon is rolling out its smartphone camera-driven service called Movement Health, which it announced earlier this month.\", \"Microsoft says a third of its government data requests have secrecy orders Microsoft's customer security chief says as many as one-third of all government demands that the company receives for customer data are issued with secrecy clauses that prevents it from disclosing the search to the subject of the warrant. The figure was disclosed in testimony by Microsoft's Tom Burt ahead of a House Judiciary Committee on Wednesday, as lawmakers weigh a legislative response to efforts by the Justice Department under the Trump administration to secretly obtain call and email records as part of an investigation into the leaks of classified information to reporters at The New York Times, The Washington Post, and CNN. Burt said that such secrecy orders \\\"have unfortunately become commonplace,\\\" and that Microsoft regularly receives \\\"boilerplate secrecy orders unsupported by any meaningful legal or factual analysis.\\\"\", \"Apple\\u2019s developer problems are much bigger than Epic and \\u2018Fortnite\\u2019 The Epic v. Apple trial exacerbated the company's developer relations problem, and it could still get worse.\", \"Facebook\\u2019s early antitrust win doesn't let it or Big Tech off the hook Facebook may have scored and early win in its antitrust battle with the FTC, but the war is far from over for the social networking giant, or the rest of Big Tech.\", \"The iOS 15, iPadOS 15 and watchOS 8 public betas are here The iOS 15 public beta is rolling out today. Here's how to get it.\", \"iOS 15 beta hands-on: A surprisingly complete preview iOS 15 features like SharePlay, Focus modes and Live Text are ready for testing.\", \"AT&T will soon enable RCS messaging for all Android phones Google Messages will be the default chat app for AT&T customers.\", \"watchOS 8 beta hands-on: Subtle but useful changes The watchOS 8 public beta might not be as big a change as iOS 15, but it still promises better integration with your iPhone, along with health and fitness updates.\", \"Lego should snap up this rapid-fire brick-finding iOS app Lego has worked extremely closely with Apple over the years, experimenting with unreleased iOS tech and demoing it onstage at launch events like WWDC; this has included some pretty heavy tinkering on the augmen\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": "-0.0114", "answer_numeric": -0.01138, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0114 (i.e., on a bad day with 5% probability, the loss exceeds 1.14%). CVaR(95%) = -0.0149.", "metadata": {"var": -0.01138, "cvar": -0.014884, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190122_0725", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHY"], "decision_date": "2019-01-22", "context_summary": "SHY: 60-day return history, mean=0.0002, std=0.0007.", "question": "Asset: SHY\nDaily returns (past 60 days): mean=0.0002, std=0.0007, min=-0.0021, max=0.0020\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SHY. Express as a decimal (e.g., -0.02).", "answer": "-0.0010", "answer_numeric": -0.000959, "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%) = -0.0014.", "metadata": {"var": -0.000959, "cvar": -0.001438, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210215_0727", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2021-02-15", "context_summary": "BTC-USD: 60-day return history, mean=0.0139, std=0.0474.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0139, std=0.0474, min=-0.1328, max=0.1157\nMarket regime: sideways\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": "-0.0605", "answer_numeric": -0.060541, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0605 (i.e., on a bad day with 5% probability, the loss exceeds 6.05%). CVaR(95%) = -0.0904.", "metadata": {"var": -0.060541, "cvar": -0.090397, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220623_0731", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2022-06-23", "context_summary": "ADA-USD: 60-day return history, mean=-0.0081, std=0.0734.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0081, std=0.0734, min=-0.1761, max=0.1849\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-22] \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": "-0.1183", "answer_numeric": -0.118315, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1183 (i.e., on a bad day with 5% probability, the loss exceeds 11.83%). CVaR(95%) = -0.1588.", "metadata": {"var": -0.118315, "cvar": -0.158846, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20200709_0733", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2020-07-09", "context_summary": "QUAL: 60-day return history, mean=0.0025, std=0.0153.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0025, std=0.0153, min=-0.0339, max=0.0266\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-07-08] These 3 Tech Stocks Are Absurdly Overvalued Right Now Many of the most sought-after stocks on the market come from the tech sector. Over the last few decades, the tech industry has remained on the cutting edge, bringing new and innovative technologies to society. This has generated heavy demand in the market for some tech stocks. Consequently, some tech names have risen to absurd valuations. While these companies may prosper for years to come, their stock prices have increased to levels that could make earning long-term gains more difficult. In this respect, investors need to weigh the valuations of companies such as Bill.com Holdings (NYSE: BILL), Datadog, Inc. (NASDAQ: DDOG), and Shopify, Inc. (NYSE: SHOP) carefully before taking a chance on such stocks. Bill.com Bill.com is a software-as-a-service (SaaS) company that provides back-office financial services to small and medium-sized businesses (SMBs). It streamlines and automates billing and payment processes that most SMBs still perform manually. This work happens through Intuit's QuickBooks Online and other popular software packages that integrate with Bill.com's Simple Bill Pay. Image source: Getty Images. SMBs continue to increasingly embrace this service. In the most recent quarter, quarterly revenue growth increased by 46% year over year. Subscriptions and transactions revenue rose by 63% over the same period. Investors have taken notice. The stock's initial run-up following its December IPO came down amid the stock market swoon related to COVID-19. However, Bill.com moved higher as tech stocks bounced back, and it has almost quadrupled in value since the March lows. BILL data by YCharts Nonetheless, this could indicate the stock price has moved ahead of growth. With losses projected for the foreseeable future, Bill.com does not have a P/E ratio for now. Still, it trades at a price-to-sales (P/S) ratio of over 52. In comparison, Square, a high-growth company offering a wider array of financial services, trades at a sales multiple of 10.9. While Bill.com should continue to offer value to businesses, the stock could struggle to compete with Square or other fintech stocks. Datadog Datadog monitors cloud platforms on a high-level basis. It oversees the entire data stack, including the parts that come from third-party vendors. This allows IT departments to isolate potential issues. It also prevents and minimizes downtimes, helping to provide a smoother user experience. This value proposition helped send revenue higher in the previous quarter by 87% from year-ago levels and resulted in a quarterly profit of $0.02 per diluted share for that period. The company also reported a positive free cash flow of $19.31 million. However, this story has begun to capture more investor attention. Datadog stock began trading last September. It saw little upward movement in the stock price until right after tech stocks began their recovery in March. Since that time, it has more than tripled in value. DDOG data \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": "-0.0261", "answer_numeric": -0.026149, "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%) = -0.0304.", "metadata": {"var": -0.026149, "cvar": -0.030419, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180316_0736", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2018-03-16", "context_summary": "MORT: 60-day return history, mean=-0.0010, std=0.0091.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=-0.0010, std=0.0091, min=-0.0214, max=0.0171\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": "-0.0169", "answer_numeric": -0.016895, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0169 (i.e., on a bad day with 5% probability, the loss exceeds 1.69%). CVaR(95%) = -0.0195.", "metadata": {"var": -0.016895, "cvar": -0.019518, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190801_0738", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2019-08-01", "context_summary": "VLUE: 60-day return history, mean=0.0001, std=0.0091.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0001, std=0.0091, min=-0.0282, max=0.0288\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-31] [\"Asian markets fall on diminished hopes of U.S.-China trade deal Nikkei, Hang Seng slump as investors await possible Fed rate cut Asian markets fell in early trading Wednesday, after President Donald Trump poured cold water over optimism for a trade deal as negotiations between the U.S. and China resumed.\", \"Apple heads back toward $1 trillion territory after earnings beat, optimistic forecast China revenue falls while Americas revenue ticks up Apple Inc. shares gained in late trading Tuesday after the company gave an upbeat forecast for the current quarter, putting the stock is on pace to notch a $1 trillion valuation once again.\", \"Apple surges toward trillion-dollar status again after an unlikely performer saves the day Wearables category extends its lead on the iPad business, which analysts say underscores success in diversification strategy Even as Apple Inc.\\u2019s iPhone revenue once again disappointed, the company was able to lean on an unexpected star.\", \"The Dow Is Gaining as Apple and GE Get a Lift After Earnings Hope that the Federal Reserve will lower interest rates this afternoon is boosting spirits, along with strong earnings from some high-profile companies.\", \"Stocks open slightly higher as investors await Fed decision Stocks opened slightly higher on Wednesday, with investors focused on the outcome of a Federal Reserve policy meeting later in the session that's widely expected to produce the central bank's first rate cut in more than a decade. The Dow Jones Industrial Average rose 47 points or 0.2%, to 27,245, while the S&P 500 rose 2 points, or 0.1%, to 3,015. The Nasdaq Composite advanced 13 points, or 0.2%, to 8,287. Traders view a quarter-point rate cut as virtually assured when the Fed releases its decision at 2 p.m. Eastern, but investors will focus closely on the language in the statement and in Fed Chairman Jerome Powell's subsequent news conference for indications about the scope for further easing. Meanwhile, the Dow was lifted by shares of iPhone maker Apple Inc. , which rose 4.3% after it reported results late Tuesday that topped consensus forecasts for both earnings and revenue.\", \"Apple Inc., Travelers share gains lead Dow's 68-point jump\", \"Here\\u2019s how the Fed could rattle the market instead of calm it down Critical information for the U.S. trading day All eyes on the Fed. Well, and Apple. And a raft of economic data too.\", \"Alphabet Should Take Note of Apple\\u2019s Stock Buyback The massive Apple stock-buyback program ought to be a model for the Google parent, whose tepid share repurchases barely make a dent in its total shares outstanding.\", \"Apple stock price target raised to $240 from $230 at BofA Merrill Lynch\", \"Spotify goes back to school on student plans, Qualcomm earnings come with another legal cloud Earnings Watch: Even a raised outlook couldn\\u2019t help GE\\u2019s stock Spotify Technology SA has learned that students need things spelled out for them.\", \"15 Takeaways From Apple Earnings and Guidanc\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": "-0.0137", "answer_numeric": -0.013701, "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%) = -0.0215.", "metadata": {"var": -0.013701, "cvar": -0.021548, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200402_0741", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-04-02", "context_summary": "MATIC-USD: 60-day return history, mean=0.0034, std=0.0857.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0034, std=0.0857, min=-0.2144, max=0.2701\nMarket regime: sideways\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": "-0.1080", "answer_numeric": -0.107982, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1080 (i.e., on a bad day with 5% probability, the loss exceeds 10.80%). CVaR(95%) = -0.1992.", "metadata": {"var": -0.107982, "cvar": -0.199198, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20201211_0743", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2020-12-11", "context_summary": "XLI: 60-day return history, mean=0.0018, std=0.0143.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0018, std=0.0143, min=-0.0336, max=0.0303\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-12-10] [\"Adobe Guides Q1, FY21 Above Estimates - Quick Facts (RTTNews) - While reporting financial results for the fourth quarter and fiscal 2020 on Thursday, software company Adobe, Inc. (ADBE) initiated earnings and revenue guidance for the first quarter and full-year 2021. For the first quarter, the company expects earnings of about $2.19 per share and adjusted earnings about $2.78 per share on revenues about $3.75 billion. On average, analysts polled by Thomson Reuters expect the company to report earnings of $2.59 per share on revenues of $3.50 billion for the quarter. Analysts' estimates typically exclude special items. For the fiscal 2021, the company now projects earnings of about $8.57 per share and adjusted earnings about $11.20 per share on revenues about $15.15 billion. The Street is looking for earnings of $11.17 per share on revenues of $14.78 billion for the year. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe Approves Repurchase Of Up To $15 Billion In Common Stock Through 2024 - Quick Facts (RTTNews) - Ahead of its virtual financial analyst meeting with investors and financial analysts on Thursday, software company Adobe, Inc. (ADBE) announced that its board of directors has approved a new stock repurchase authority, granting the company additional authority to repurchase up to $15 billion in common stock through its fiscal year 2024. The previous program authorizing the repurchase of up to $8 billion in common stock through fiscal year 2021 is expected to be exhausted in the first half of 2021. The new program is expected to be funded from Adobe's future cash flows from operations and is incorporated into the company's fiscal year 2021 financial targets. Adobe also said its total addressable market has expanded to approximately $147 billion by 2023. This is based on its proven ability to create new categories and consistently innovate across our creativity, digital documents and customer experience management businesses. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe Systems Inc. Q4 adjusted earnings Beat Estimates (RTTNews) - Adobe Systems Inc. (ADBE) released earnings for its fourth quarter that advanced from the same period last year. The company's bottom line came in at $2.25 billion, or $4.64 per share. This compares with $0.85 billion, or $1.74 per share, in last year's fourth quarter. Excluding items, Adobe Systems Inc. reported adjusted earnings of $1.36 billion or $2.81 per share for the period. Analysts had expected the company to earn $2.66 per share, according to figures compiled by Thomson Reuters. Analysts' estimates typically exclude special items. The company's revenue for the quarter rose 14.4% to $3.42 billion from $2.99 billion last year. Adobe Systems Inc. earnings at a glance: -Earnings (Q4): $1.36 Bln. vs. $1.12 Bln. last yea\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": "-0.0223", "answer_numeric": -0.022263, "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%) = -0.0308.", "metadata": {"var": -0.022263, "cvar": -0.030753, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160624_0746", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2016-06-24", "context_summary": "HYG: 60-day return history, mean=0.0009, std=0.0038.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0009, std=0.0038, min=-0.0067, max=0.0085\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": "-0.0049", "answer_numeric": -0.004869, "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%) = -0.0060.", "metadata": {"var": -0.004869, "cvar": -0.006018, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20191218_0748", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2019-12-18", "context_summary": "REZ: 60-day return history, mean=-0.0011, std=0.0081.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=-0.0011, std=0.0081, min=-0.0231, max=0.0165\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": "-0.0173", "answer_numeric": -0.017294, "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%) = -0.0197.", "metadata": {"var": -0.017294, "cvar": -0.019652, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200224_0750", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2020-02-24", "context_summary": "XRP-USD: 60-day return history, mean=0.0072, std=0.0369.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0072, std=0.0369, min=-0.0854, max=0.1328\nMarket regime: sideways\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": "-0.0369", "answer_numeric": -0.036859, "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%) = -0.0652.", "metadata": {"var": -0.036859, "cvar": -0.065238, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220607_0752", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2022-06-07", "context_summary": "BIL: 60-day return history, mean=-0.0000, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=-0.0000, std=0.0001, min=-0.0002, max=0.0002\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": "-0.0002", "answer_numeric": -0.000219, "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": -0.000219, "cvar": -0.000219, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20221122_0754", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2022-11-22", "context_summary": "SOL-USD: 60-day return history, mean=-0.0099, std=0.0681.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0099, std=0.0681, min=-0.2453, max=0.2683\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-21] \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": "-0.1096", "answer_numeric": -0.109575, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1096 (i.e., on a bad day with 5% probability, the loss exceeds 10.96%). CVaR(95%) = -0.1801.", "metadata": {"var": -0.109575, "cvar": -0.180132, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20200908_0757", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-09-08", "context_summary": "LINK-USD: 60-day return history, mean=0.0120, std=0.0802.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0120, std=0.0802, min=-0.1934, max=0.1799\nMarket regime: sideways\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": "-0.1131", "answer_numeric": -0.113142, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1131 (i.e., on a bad day with 5% probability, the loss exceeds 11.31%). CVaR(95%) = -0.1621.", "metadata": {"var": -0.113142, "cvar": -0.162103, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180907_0759", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2018-09-07", "context_summary": "IVV: 60-day return history, mean=0.0006, std=0.0051.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0006, std=0.0051, min=-0.0137, max=0.0093\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-09-06] [\"7 Lucrative Biotech Stocks With Up to 300% Upside InvestorPlace - Stock Market News, Stock Advice & Trading Tips Forget market dynamics. These biotechs are playing to their own tune. According to the Street's top analysts this can be a very lucrative path. Biotech stocks can spike massively on positive news - be it key trial results or regulatory approvals. Of course, the opposite is also true and the biotech sector can crash just as quickly on unexpected disappointments. But the key point remains: Biotechs provide an outlet away from the rest of the market to potentially make serious money. That's especially welcome in the month of September - a notoriously tricky time for the markets. Indeed, September has been the worst performing month of the year for the Dow Jones Industrial Average and the S&P 500 since 1950. Your Chance to Cash In With Legal Sports Betting With that in mind, let's now turn to these seven strong buy biotechs now. I used TipRanks to ensure two crucial points: 1) big support from the Street, especially from top-performing analysts and 2) eye-watering upside potential ahead. Now let's see how these stocks tick these two boxes: Biotech Stocks to Buy: ObsEva (OBSV) ObsEva (NASDAQ: OBSV ) is developing best-in-class drug candidates to improve women's reproductive health. The lead is Linzagolix (OBE2109), a potentially best-in-class orally-dosed GnRH antagonist to treat symptoms of endometriosis (Ph2b) and uterine fibroids (Ph3). Top HC Wainwright analyst Ram Selvaraju ( Profile & Recommendations ) is very bullish on the stock's potential. He has just reiterated his \\\"buy\\\" rating with a $44 price target. From current levels that indicates massive upside potential of 237%! He notes that just-released data from AbbVie Inc (NYSE: ABBV ) reduces the risk for OBSV's Linzagolix. \\\"In our view, the long-term efficacy for elagolix should bode well for future development of linzagolix in uterine fibroids, since both drugs are GnRH receptor antagonists and have shown comparable potency in clinical studies.\\\" However, one of the key advantages for Linzagolix is the potential to be administered in certain patients without needing add-back therapy (ABT). This is the addition of a small amount of the hormones estrogen and/or progesterone to reduce undesirable effects of GnRH. Overall, six analysts have published back-to-back buy ratings on OBSV stock. This is with a $32 price target (147% upside potential). See what other Top Analysts are saying about OBSV . Biotech Stocks to Buy: Tocagen Inc (TOCA) This cutting-edge biotech stock is at the forefront of cancer therapy. Tocagen Inc (NASDAQ: TOCA ) is developing an RRV platform that can selectively deliver therapeutic genes into the DNA of cancer cells. Right now, all eyes are on Toca 511 and Toca FC. These drugs are in pivotal Phase 3 trials for recurrent high-grade gliomas (HGGs), with data due in 1H19. These are extremely difficult to treat cancers. \\\"Given the robustness of overall dataset\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": "-0.0075", "answer_numeric": -0.007497, "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%) = -0.0101.", "metadata": {"var": -0.007497, "cvar": -0.010123, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220902_0762", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2022-09-02", "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=-0.1203, max=0.1010\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-01] \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": "-0.0605", "answer_numeric": -0.060464, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0605 (i.e., on a bad day with 5% probability, the loss exceeds 6.05%). CVaR(95%) = -0.0889.", "metadata": {"var": -0.060464, "cvar": -0.088929, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20200417_0765", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2020-04-17", "context_summary": "^VIX: 60-day return history, mean=0.0131, std=0.1145.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0131, std=0.1145, min=-0.1825, max=0.2508\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-04-16] [\"Software Rises Above Semiconductors And Hardware As Tech Heads Into Earnings Season\", \"'Apple's only retail store in South Korea reopening April 18' -9to5Mac\", \"Morgan Stanley Misses On EPS, But Shows Strong Trading Results For Q1 As Banks Wrap Up\", \"Deutsche Bank Maintains Buy on Apple, Raises Price Target to $285\", \"Apple shares are trading higher after Deutsche Bank maintained its Buy rating on the stock and raised its price target from $270 to $285 per share.\", \"Comcast's Peacock Takes Well-Timed Flight\", \"Apple's Tim Cook Tells Staff Mgmt. Is Unclear When Employees Will Be Able To Return To Offices, Says Offices Will Likely Have Temperature Checks, Social Distancing Efforts\", \"S&P 500 Futures Up 3.2% After Hours; Many Other Stocks Moving Higher With Futures; Investors Reacting Favorably To White Phase Guidelines On Reopening Economy\", \"Big Stocks Moving After Hours As Market Cheers Gilead, 'Reopening' Updates\", \"Big Stocks Moving After Hours As Market Cheers Gilead, 'Reopening' Updates\", \"S&P 500 Futures Up 3.2% After Hours; Many Other Stocks Moving Higher With Futures; Investors Reacting Favorably To White Phase Guidelines On Reopening Economy\", \"Apple's Tim Cook Tells Staff Mgmt. Is Unclear When Employees Will Be Able To Return To Offices, Says Offices Will Likely Have Temperature Checks, Social Distancing Efforts\", \"Comcast's Peacock Takes Well-Timed Flight\", \"Apple shares are trading higher after Deutsche Bank maintained its Buy rating on the stock and raised its price target from $270 to $285 per share.\", \"Deutsche Bank Maintains Buy on Apple, Raises Price Target to $285\", \"Morgan Stanley Misses On EPS, But Shows Strong Trading Results For Q1 As Banks Wrap Up\", \"'Apple's only retail store in South Korea reopening April 18' -9to5Mac\", \"Big Stocks Moving After Hours As Market Cheers Gilead, 'Reopening' Updates\", \"S&P 500 Futures Up 3.2% After Hours; Many Other Stocks Moving Higher With Futures; Investors Reacting Favorably To White Phase Guidelines On Reopening Economy\", \"Apple's Tim Cook Tells Staff Mgmt. Is Unclear When Employees Will Be Able To Return To Offices, Says Offices Will Likely Have Temperature Checks, Social Distancing Efforts\", \"Comcast's Peacock Takes Well-Timed Flight\", \"Apple shares are trading higher after Deutsche Bank maintained its Buy rating on the stock and raised its price target from $270 to $285 per share.\", \"Deutsche Bank Maintains Buy on Apple, Raises Price Target to $285\", \"Morgan Stanley Misses On EPS, But Shows Strong Trading Results For Q1 As Banks Wrap Up\", \"'Apple's only retail store in South Korea reopening April 18' -9to5Mac\", \"Apple stock price target raised to $285 from $270 at Deutsche Bank\", \"Apple is working on high-end over-the-ear headphones: report Apple Inc. has seen considerable success with its AirPods earphones and now the company is looking to make high-end over-the-ear wireless headphones to add to its product lineup, according to a Bloomberg report Thursday. The story, which cites mult\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": "-0.1406", "answer_numeric": -0.140635, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1406 (i.e., on a bad day with 5% probability, the loss exceeds 14.06%). CVaR(95%) = -0.1686.", "metadata": {"var": -0.140635, "cvar": -0.168633, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210817_0767", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2021-08-17", "context_summary": "ICSH: 60-day return history, mean=0.0000, std=0.0001.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0000, std=0.0001, min=-0.0003, max=0.0004\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": -0.000218, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220701_0769", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2022-07-01", "context_summary": "EFA: 60-day return history, mean=-0.0025, std=0.0139.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=-0.0025, std=0.0139, min=-0.0289, max=0.0259\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-30] [\"Apple Allows App Developers To Use 3rd-party Payment Systems In South Korea (RTTNews) - Tech giant Apple Inc. (AAPL) on Thursday announced that it will allow developers in South Korea to use a third-party payment system. \\\"To comply with the new South Korean law, developers can use the StoreKit External Purchase Entitlement,\\\" the company said in a developer update. \\\"This entitlement allows apps distributed on the App Store solely in South Korea the ability to provide an alternative in-app payment processing option\\\". Last year, the South Korean National Assembly passed a bill that restricted tech giants like Google (GOOG) and Apple from forcing developers to make use of only their in-app billing systems, while developing applications for their flagship app stores. Meanwhile, the new provision from Apple comes with few riders, as few features like Ask to Buy and Family Sharing will not be available. \\\"If you're considering using this entitlement, it's important to understand that some App Store features, such as Ask to Buy and Family Sharing, will not be available to your users, in part because we cannot validate payments that take place outside of the App Store's private and secure payment system,\\\" the company said. The benefit to qualifying developers is that instead of paying Apple 30% of every transaction, Apple will now only charge 26%. \\\"Apple will charge a 26% commission on the price paid by the user, gross of any value-added taxes,\\\" says the further detailed developer documentation. \\\"This is a reduced rate that excludes value related to payment processing and related activities.\\\" Developers will have to report all sales monthly. \\\"Please note that Apple has audit rights pursuant to the entitlement's terms and conditions,\\\" says Apple's documentation. \\\"Failure to pay Apple's commission could result in the offset of proceeds owed to you in other markets,\\\" it continues, \\\"removal of your app from the App Store or removal from the Apple Developer program.\\\" The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"After Hours Most Active for Jun 30, 2022 : MU, TAL, AAPL, IUSV, MRK, QQQ, EQT, AMZN, GSK, MSFT, WFC, ZYME The NASDAQ 100 After Hours Indicator is down -8.1 to 11,495.62. The total After hours volume is currently 96,787,908 shares traded. The following are the most active stocks for the after hours session: Micron Technology, Inc. (MU) is -1.51 at $53.77, with 4,341,269 shares traded. Smarter Analyst Reports: Micron to Unveil Memory Design Center in Atlanta TAL Education Group (TAL) is unchanged at $4.87, with 4,100,757 shares traded. TAL's current last sale is 90.19% of the target price of $5.4. Apple Inc. (AAPL) is +0.06 at $136.78, with 4,048,733 shares traded. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". iShares Core S&P U.S. Value ETF (IUSV) is -0.0259 at $66.85, with 3,840,000 shares traded. This re\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": "-0.0284", "answer_numeric": -0.028374, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0284 (i.e., on a bad day with 5% probability, the loss exceeds 2.84%). CVaR(95%) = -0.0289.", "metadata": {"var": -0.028374, "cvar": -0.028901, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180302_0771", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2018-03-02", "context_summary": "LINK-USD: 60-day return history, mean=0.0003, std=0.1065.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0003, std=0.1065, min=-0.1934, max=0.1799\nMarket regime: sideways\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": "-0.1610", "answer_numeric": -0.160999, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1610 (i.e., on a bad day with 5% probability, the loss exceeds 16.10%). CVaR(95%) = -0.1830.", "metadata": {"var": -0.160999, "cvar": -0.18303, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210201_0773", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2021-02-01", "context_summary": "^VIX: 60-day return history, mean=-0.0053, std=0.0736.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0053, std=0.0736, min=-0.1825, max=0.2508\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-01-29] Dolby Laboratories Stock Could Drop To $75 Dolby Laboratories stock (NYSE: DLB) is up around 35% since the beginning of 2020, and at the current price around $90 per share, we believe that Dolby Laboratories stock has over 15% potential downside. Why is that? Our belief stems from the fact that DLB stock is up 2x its low in March this year, while the S&P has moved a little over 70% in comparison. Further, after posting weak Q4 2020 numbers, and with demand struggling to rise to pre-Covid levels, we believe Dolby stock could slide lower. Our dashboard What Factors Drove 51% Change In Dolby Laboratories Stock Between 2018 And Now? provides the key numbers behind our thinking, and we explain more below. Dolby Laboratories specializes in audio noise reduction and audio encoding/compression software and hardware, licensing its technology to sound system manufacturers. Dolby\u2019s price rise since 2018 came due to a 13% rise in revenue per share (RPS), driven by a 10% rise in revenue combined with a 3% drop in the outstanding share count. Further, DLB\u2019s P/S (price-to-sales) ratio shrank from 6.1x in 2018 to 5.6x in 2019, but has since jumped to 8.1x, riding the rally in technology stocks. We believe that given Dolby\u2019s weak Q4 \u201920 performance, there is a possible downside risk for the P/S multiple. So what\u2019s the likely trigger and timing to this downside? The global spread of coronavirus and the resulting lockdowns have led to a drop in demand for medium to large scale sound systems, as theaters have remained closed and large-scale events are not as frequent, due to the pandemic. This has led to a drop in demand for Dolby\u2019s products, which is evident from their Q4 2020 results, where revenue came in at $1.16 billion vs $1.24 billion in 2019. Products and services revenue dropped almost 40% from $134 million to $83 million over this period. Further, as operating expenses didn\u2019t drop at the same rate as revenue, operating margins fell to 18.8% in FY\u201920 vs 20.7% in FY \u201919. Despite a lower effective tax rate, EPS came in lower at $2.30 vs $2.51 in 2019. Going forward, we expect revenues to stay weak in the near to medium term, and if the company is not able to control expenses, we believe the stock will see its P/S multiple decline from the current level of 8.1x to around 7x, which combined with a reduction in revenues and margins could result in the stock price shrinking to as low as $75, a downside of more than 15% from the current price near $90. may have moved, 2020 has created many pricing discontinuities which can offer attractive trading opportunities. For example, you'll be surprised how counter-intuitive the stock valuation is for Intel vs Cisco. \\n\\nBased on article theme, variations to \\\"While may have moved\\\" can be (a) While may be overvalued (or undervalued) (b) While can move (c) Although may not be attractive (d) While is worth considering\"}\" data-sheets-userformat=\"{\"2\":1049345,\"3\":{\"1\":0},\"11\":4,\"12\":0,\"23\":1}\" data-sheets-textstyleruns=\"{\"1\":\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": "-0.1043", "answer_numeric": -0.104337, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1043 (i.e., on a bad day with 5% probability, the loss exceeds 10.43%). CVaR(95%) = -0.1596.", "metadata": {"var": -0.104337, "cvar": -0.159631, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220125_0775", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2022-01-25", "context_summary": "MTUM: 60-day return history, mean=-0.0025, std=0.0136.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0025, std=0.0136, min=-0.0341, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-24] [\"Buy Smart With Software Stocks on the Dip InvestorPlace - Stock Market News, Stock Advice & Trading Tips Technology stocks are getting crushed right now, and software stocks in particular are bearing the brunt of the selling. Year-to-date, the tech-heavy Nasdaq is off 12% \\u2014 marking its fourth worst start to a year ever. Worse yet, the Invesco Dynamic Software ETF (NYSEARCA:PSJ) is down nearly 18% in just three weeks. Source: Shutterstock Ouch! But as the old saying goes, it\\u2019s often best to be greedy when others are fearful. This time around, that saying is especially true because the stocks getting hit the hardest \\u2014 software stocks \\u2014 are the market\\u2019s best. Technology is taking over the world. You know that. I know that. We all know that. New tech products and services are redefining every aspect of our personal and professional lives. This trend won\\u2019t stop anytime soon. By 2030, the world will be run by tech. And these days, most of that tech is software \\u2014 not hardware. That\\u2019s because from a single piece of hardware, like a phone or computer, you can access an infinite number of software applications. Big picture: Software will inevitably run the world one day. That\\u2019s just a fact. And consequently, software stocks will be the market\\u2019s biggest winners. So\\u2026 when faced with a short-term pullback in a group of long-term winners \\u2014 like we\\u2019re seeing today in software stocks \\u2014 the best thing to do is buy the dip. But be careful \\u2014 because while some software stocks look like they\\u2019ve bottomed and are ready to rocket higher, the ones you\\u2019re probably thinking about buying have further yet to fall. Avoid Overvaluation The biggest software growth stocks in the market \\u2014 household companies making software that you and I use every day, with businesses growing at 10%-plus every year and gross margins above 60% \\u2014 are still overvalued. I\\u2019m talking Microsoft (NASDAQ:MSFT), Adobe (NASDAQ:ADBE), Intuit (NASDAQ:INTU), Autodesk (NASDAQ:ADSK), Fortinet (NASDAQ:FTNT), Illumina (NASDAQ:ILMN) and more. I\\u2019ve put together an index of the 10 most important software growth stocks in the market and tracked their price-to-sales multiples over the past five years. Before the pandemic \\u2014 before interest rates got cut to zero, before Treasury yields plunged and before enormous globs of fiscal stimulus hit the economy \\u2014 these stocks were trading around 10 to 12 times trailing sales. That should be considered a \\u201cnormal\\u201d valuation for high-margin software growth stocks. During the pandemic, though, those multiples ballooned to record highs. Now, even after the recent tech meltdown, the \\u201cBig Software 10\\u201d (as I like to call them) are still trading at 16 times trailing sales \\u2014 a huge premium to their valuations prior to the pandemic. Source: InvestorPlace In other words, those stocks still have a lot of room to fall if the Fed does hike interest rat\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": "-0.0256", "answer_numeric": -0.025589, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0256 (i.e., on a bad day with 5% probability, the loss exceeds 2.56%). CVaR(95%) = -0.0296.", "metadata": {"var": -0.025589, "cvar": -0.029573, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201002_0777", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2020-10-02", "context_summary": "ETH-USD: 60-day return history, mean=0.0003, std=0.0464.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0003, std=0.0464, min=-0.1365, max=0.0965\nMarket regime: sideways\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": "-0.0776", "answer_numeric": -0.077648, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0776 (i.e., on a bad day with 5% probability, the loss exceeds 7.76%). CVaR(95%) = -0.1130.", "metadata": {"var": -0.077648, "cvar": -0.112964, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220412_0779", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2022-04-12", "context_summary": "LINK-USD: 60-day return history, mean=-0.0030, std=0.0466.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0030, std=0.0466, min=-0.1040, max=0.1071\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-11] \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": "-0.0794", "answer_numeric": -0.079404, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0794 (i.e., on a bad day with 5% probability, the loss exceeds 7.94%). CVaR(95%) = -0.0925.", "metadata": {"var": -0.079404, "cvar": -0.092499, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20211101_0781", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2021-11-01", "context_summary": "BNB-USD: 60-day return history, mean=0.0022, std=0.0472.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0022, std=0.0472, min=-0.1581, max=0.1050\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-29] \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": "-0.0614", "answer_numeric": -0.06138, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0614 (i.e., on a bad day with 5% probability, the loss exceeds 6.14%). CVaR(95%) = -0.1154.", "metadata": {"var": -0.06138, "cvar": -0.115413, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20220411_0784", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2022-04-11", "context_summary": "XLP: 60-day return history, mean=0.0003, std=0.0092.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0003, std=0.0092, min=-0.0250, max=0.0211\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-08] [\"Top Stock Reports for Costco, AstraZeneca & Medtronic Friday, April 8, 2022 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 Costco Wholesale Corporation (COST), AstraZeneca PLC (AZN), and Medtronic plc (MDT). 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 Costco have outperformed the Zacks Retail - Discount Stores industry over the past year (+69.5% vs. +23.7%), reflecting the company's growth strategies, better price management, decent membership trend, and increasing penetration of e-commerce business. The strategy to sell products at discounted prices has helped draw customers seeking both value and convenience. These factors have been aiding in registering impressive sales and earnings numbers. Costco put up a decent performance in second-quarter fiscal 2022, wherein both the top and the bottom lines improved year over year. Also, Costco has been witnessing stellar comps sales run. While the aforementioned factors raise optimism. However, supply chain bottlenecks and higher labor and freight costs remain concerns. Any deleverage in SG&A rate may hurt margins. (You can read the full research report on Costco here >>>) Shares of AstraZeneca have outperformed the Zacks Large Cap Pharmaceuticals industry over the past year (+47% vs. +38.5%). The Zacks analyst believes that the company\\u2019s newer drugs, mainly cancer medicines, Lynparza, Tagrisso and Imfinzi should keep driving revenues. Its pipeline is strong with several phase III data readouts lined up. AstraZeneca has also engaged in external acquisitions and strategic collaborations to boost its pipeline while investing in geographic areas of high growth like emerging markets. Cost-cutting efforts should drive earnings. The Alexion buyout strengthens its immunology franchise, adding several drugs that can boost its top line. However, AstraZeneca\\u2019s diabetes franchise faces stiff competition while pricing pressure is hurting sales in the respiratory unit. Sales of some medicines are being hurt due to COVID-19. Sales are slowing down in key markets, China, due to pricing pressure. (You can read the full research report on AstraZeneca here >>>) Shares of Medtronic have outperformed the Zacks Medical - Products industry over the year-to-date period (+9.3% vs. -7.3%). Medtronic has registered organic growth in the Cardiovascular, Neuroscience and Diabetes segments. The company claims share gains in 60% of its businesses. However, the sluggish top-line results reflect the unfavorable market impact of COVID-19 and health system labor shortages. CRDN sales decreased in the mid-single digits, given the impact of COVID-19 on PCI procedures. Also, there have been low double-digit organic declines in RGR with sales of ventilators declining in the high-fif\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": "-0.0147", "answer_numeric": -0.014659, "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%) = -0.0203.", "metadata": {"var": -0.014659, "cvar": -0.020257, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200916_0786", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2020-09-16", "context_summary": "ETH-USD: 60-day return history, mean=0.0087, std=0.0479.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0087, std=0.0479, min=-0.1365, max=0.1147\nMarket regime: sideways\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": "-0.0662", "answer_numeric": -0.066188, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0662 (i.e., on a bad day with 5% probability, the loss exceeds 6.62%). CVaR(95%) = -0.1125.", "metadata": {"var": -0.066188, "cvar": -0.112534, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220509_0788", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2022-05-09", "context_summary": "QQQ: 60-day return history, mean=-0.0026, std=0.0212.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0026, std=0.0212, min=-0.0399, max=0.0340\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-05-06] [\"The Technology Select Sector SPDR Fund Experiences Big Inflow Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel, one standout is the The Technology Select Sector SPDR Fund (Symbol: XLK) where we have detected an approximate $248.0 million dollar inflow -- that's a 0.6% increase week over week in outstanding units (from 300,610,000 to 302,360,000). Among the largest underlying components of XLK, in trading today Visa Inc (Symbol: V) is off about 1.5%, Mastercard Inc (Symbol: MA) is down about 2.6%, and Adobe Inc (Symbol: ADBE) is lower by about 2.2%. For a complete list of holdings, visit the XLK Holdings page \\u00bb The chart below shows the one year price performance of XLK, versus its 200 day moving average: Looking at the chart above, XLK's low point in its 52 week range is $130.958 per share, with $177.04 as the 52 week high point \\u2014 that compares with a last trade of $140.65. 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 The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Shopify Stock: Bull vs. Bear My fellow Texans know that Cinco de Mayo is one of the best holidays of the year. And for many of my neighbors, it's as important as July 4th. Filled with dancing, laughter, and history -- raising a Topo Chico mineral water in the heat of May is a nice reprieve from the scorching Texas sun. However, a much more serious event was hosted by our neighbors to the north on May 5. It was on that day when Ottawa-based Shopify (NYSE: SHOP) reported its first-quarter earnings. Shares were down nearly 20% in reaction the report, setting a bearish tone for the year as the young company weans off its pandemic-induced growth spurt and dives into the abyss of rising interest rates and a potential recession. Here's a breakdown that will give you a glimpse into the bull case and bear case for Shopify so you can better understand what's pressuring the stock right now. Image source: Getty Images. The bear case Shopify is a battleground stock \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": "-0.0376", "answer_numeric": -0.037623, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0376 (i.e., on a bad day with 5% probability, the loss exceeds 3.76%). CVaR(95%) = -0.0394.", "metadata": {"var": -0.037623, "cvar": -0.039434, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190220_0790", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2019-02-20", "context_summary": "^VIX: 59-day return history, mean=-0.0070, std=0.0768.", "question": "Asset: ^VIX\nDaily returns (past 59 days): mean=-0.0070, std=0.0768, min=-0.1743, max=0.2323\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-19] After Hours Most Active for Feb 19, 2019 : SIRI, PFE, CHK, MO, VER, FDC, ZAYO, WBA, PYPL, AGNC, ADBE, SHY The NASDAQ 100 After Hours Indicator is up 1.03 to 7,067.64. The total After hours volume is currently 51,827,821 shares traded. The following are the most active stocks for the after hours session : Sirius XM Holdings Inc. ( SIRI ) is unchanged at $6.00, with 3,769,562 shares traded. As reported in the last short interest update the days to cover for SIRI is 8.93504; this calculation is based on the average trading volume of the stock. Pfizer, Inc. ( PFE ) is -0.2 at $42.40, with 2,262,941 shares traded. PFE's current last sale is 94.22% of the target price of $45. Chesapeake Energy Corporation ( CHK ) is unchanged at $2.68, with 1,818,617 shares traded. Over the last four weeks they have had 5 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2018. The consensus EPS forecast is $0.17. CHK's current last sale is 89.33% of the target price of $3. Altria Group ( MO ) is +0.13 at $49.12, with 1,447,860 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Jun 2019. The consensus EPS forecast is $1.07. MO's current last sale is 83.97% of the target price of $58.5. VEREIT Inc. ( VER ) is unchanged at $8.26, with 1,314,873 shares traded.VER is scheduled to provide an earnings report on 2/21/2019, for the fiscal quarter ending Dec2018. The consensus earnings per share forecast is 0.17 per share, which represents a 18 percent increase over the EPS one Year Ago First Data Corporation ( FDC ) is +0.03 at $25.53, with 1,273,073 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2019. The consensus EPS forecast is $0.27. FDC's current last sale is 102.12% of the target price of $25. Zayo Group Holdings, Inc. ( ZAYO ) is +0.1198 at $25.57, with 1,218,521 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Mar 2019. The consensus EPS forecast is $0.18. As reported by Zacks, the current mean recommendation for ZAYO is in the \"buy range\". Walgreens Boots Alliance, Inc. ( WBA ) is +0.4 at $74.83, with 991,822 shares traded. WBA's current last sale is 99.77% of the target price of $75. PayPal Holdings, Inc. ( PYPL ) is -0.02 at $95.00, with 877,652 shares traded. As reported by Zacks, the current mean recommendation for PYPL is in the \"buy range\". AGNC Investment Corp. ( AGNC ) is +0.01 at $17.70, with 813,667 shares traded. AGNC's current last sale is 98.33% of the target price of $18. Adobe Inc. ( ADBE ) is -0.0077 at $257.80, with 795,058 shares traded. As reported by Zacks, the current mean recommendation for ADBE is in the \"buy range\". iShares 1-3 Year Treasury Bond ETF ( SHY ) is unchanged at $83.74, with 792,213 shares traded. This represents a 1.1% increase from its 52 Week Low. The views and opinions expre\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": "-0.1108", "answer_numeric": -0.110846, "explanation": "Historical simulation VaR at 95%: sort the 59 daily returns and take the 5th percentile. VaR(95%) = -0.1108 (i.e., on a bad day with 5% probability, the loss exceeds 11.08%). CVaR(95%) = -0.1583.", "metadata": {"var": -0.110846, "cvar": -0.158257, "confidence": 0.95, "n_returns": 59, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201113_0794", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2020-11-13", "context_summary": "MTUM: 60-day return history, mean=0.0007, std=0.0162.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0007, std=0.0162, min=-0.0383, max=0.0314\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-11-12] [\"Better Buy: Slack vs. Adobe Slack (NYSE: WORK) and Adobe (NASDAQ: ADBE) are both forward-thinking companies that are changing how people work. Slack's enterprise communication platform reduced the need for clumsy email chains and time-consuming phone calls. It also recently expanded its platform with Slack Connect, which allows companies to communicate and collaborate securely with external partners. Adobe transformed its desktop software into cloud-based services that locked in customers with subscriptions and eliminated the need for local software installations and periodic upgrades. Adobe also expanded its cloud ecosystem with additional services for enterprise customers. Slack went public via a direct listing in June 2019. But after a few wild swings, its stock is still hovering near its initial reference price of $26. Meanwhile, Adobe's stock has surged nearly 60% just since Slack's public debut. Let's see why Adobe outperformed Slack, and if it will remain the faster-growing stock for the foreseeable future. Image source: Getty Images. Slack: A first mover with a shrinking moat Slack operates a \\\"freemium\\\" business model. Paying businesses gain unlimited messages and integrated tools, better security, more cloud storage, automation services for repetitive tasks, and other services. Slack was founded seven years ago, and it enjoys a first mover's advantage in its disruptive niche. However, Microsoft's (NASDAQ: MSFT) Teams, which was launched in 2017, copied many of Slack's features and was subsequently bundled into Office 365 subscriptions as a free service. In response, Slack filed an antitrust complaint against Microsoft in Europe earlier this year, alleging the tech giant was \\\"force installing\\\" a \\\"weak, copycat product\\\" onto \\\"millions\\\" of users. Slack continued to grow as Microsoft expanded Teams, but that competitive threat cast a long shadow over the underdog's future. Adobe: An evolving tech giant with an expanding ecosystem Adobe splits its business into two main divisions: the Digital Media unit, which provides its creativity and productivity software as cloud-based services; and the Digital Experience unit, which hosts its enterprise tools. The Digital Media unit's Creative Cloud hosts industry-standard software like Adobe Photoshop, Premiere Pro, Illustrator, After Effects, and Acrobat. Most of these software products dominate their respective markets. The Digital Experience unit, which hosts cloud-based advertising, analytics, advertising, and e-commerce tools, faces much tougher competition. salesforce.com (NYSE: CRM) competes against most of Adobe's enterprise-oriented services, while Shopify competes against Adobe's Magento e-commerce services. Which company is growing faster? Slack's revenue grew 57% year over year to $630 million in fiscal 2020, which ended on Jan. 30. Its GAAP net loss widened from $141 million to $571 million last year, but its non-GAAP net loss narrowed slightly from $116 million to $113 million. \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": "-0.0297", "answer_numeric": -0.029653, "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%) = -0.0369.", "metadata": {"var": -0.029653, "cvar": -0.036874, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20171023_0796", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2017-10-23", "context_summary": "UNG: 60-day return history, mean=0.0004, std=0.0155.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=0.0004, std=0.0155, min=-0.0394, max=0.0356\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": "-0.0273", "answer_numeric": -0.027277, "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%) = -0.0326.", "metadata": {"var": -0.027277, "cvar": -0.032597, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20151113_0798", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2015-11-13", "context_summary": "BTC-USD: 60-day return history, mean=0.0070, std=0.0353.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0070, std=0.0353, min=-0.1142, max=0.1157\nMarket regime: sideways\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": "-0.0432", "answer_numeric": -0.043172, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0432 (i.e., on a bad day with 5% probability, the loss exceeds 4.32%). CVaR(95%) = -0.0840.", "metadata": {"var": -0.043172, "cvar": -0.083964, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170920_0800", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2017-09-20", "context_summary": "BTC-USD: 60-day return history, mean=0.0077, std=0.0480.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0077, std=0.0480, min=-0.1328, max=0.1157\nMarket regime: sideways\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": "-0.0653", "answer_numeric": -0.065295, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0653 (i.e., on a bad day with 5% probability, the loss exceeds 6.53%). CVaR(95%) = -0.0964.", "metadata": {"var": -0.065295, "cvar": -0.096386, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200529_0802", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2020-05-29", "context_summary": "BTC-USD: 60-day return history, mean=0.0084, std=0.0353.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0084, std=0.0353, min=-0.0873, max=0.1157\nMarket regime: sideways\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": "-0.0455", "answer_numeric": -0.045531, "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%) = -0.0645.", "metadata": {"var": -0.045531, "cvar": -0.064471, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200630_0804", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2020-06-30", "context_summary": "BTC-USD: 60-day return history, mean=0.0014, std=0.0294.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0014, std=0.0294, min=-0.0873, max=0.0746\nMarket regime: sideways\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": "-0.0468", "answer_numeric": -0.046793, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0468 (i.e., on a bad day with 5% probability, the loss exceeds 4.68%). CVaR(95%) = -0.0685.", "metadata": {"var": -0.046793, "cvar": -0.068514, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190114_0806", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2019-01-14", "context_summary": "ACWI: 60-day return history, mean=-0.0009, std=0.0127.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0009, std=0.0127, min=-0.0284, max=0.0250\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-11] [\"Friday's ETF with Unusual Volume: SIZE The iShares Edge MSCI USA Size Factor ETF is seeing unusually high volume in afternoon trading Friday, with over 314,000 shares traded versus three month average volume of about 32,000. Shares of SIZE were down about 0.2% on the day. Components of that ETF with the highest volume on Friday were General Electric, trading off about 0.1% with over 39.2 million shares changing hands so far this session, and Advanced Micro Devices, up about 0.5% on volume of over 37.5 million shares. General Motors is the component faring the best Friday, higher by about 8.3% on the day, while Vail Resorts is lagging other components of the iShares Edge MSCI USA Size Factor ETF, trading lower by about 13%. VIDEO: Friday's ETF with Unusual Volume: SIZE The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Noteworthy ETF Inflows: SOXX, NVDA, AMD, XLNX Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the iShares PHLX Semiconductor ETF (Symbol: SOXX) where we have detected an approximate $88.9 million dollar inflow -- that's a 8.2% increase week over week in outstanding units (from 6,700,000 to 7,250,000). Among the largest underlying components of SOXX, in trading today NVIDIA Corp (Symbol: NVDA) is off about 0.6%, Advanced Micro Devices Inc (Symbol: AMD) is off about 0.6%, and Xilinx, Inc. (Symbol: XLNX) is lower by about 0.3%. For a complete list of holdings, visit the SOXX Holdings page \\u00bb The chart below shows the one year price performance of SOXX, versus its 200 day moving average: Looking at the chart above, SOXX's low point in its 52 week range is $144.79 per share, with $198.84 as the 52 week high point - that compares with a last trade of $163.35. 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 The views and opinions expressed herein are the views and opi\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": "-0.0191", "answer_numeric": -0.019094, "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%) = -0.0253.", "metadata": {"var": -0.019094, "cvar": -0.025264, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210104_0808", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2021-01-04", "context_summary": "USO: 60-day return history, mean=0.0026, std=0.0193.", "question": "Asset: USO\nDaily returns (past 60 days): mean=0.0026, std=0.0193, min=-0.0498, max=0.0557\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": "-0.0270", "answer_numeric": -0.027018, "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%) = -0.0367.", "metadata": {"var": -0.027018, "cvar": -0.036719, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160222_0810", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2016-02-22", "context_summary": "MTUM: 60-day return history, mean=-0.0012, std=0.0129.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0012, std=0.0129, min=-0.0313, max=0.0217\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-02-19] [\"IDACORP (IDA) Misses on Q4 Earnings, Gives '16 Guidance IDACORP, Inc.IDA recorded operating earnings of 63 cents per share in the fourth quarter of 20Array5, lagging the Zacks Consensus Estimate of 64 cents by Array.56%. Quarterly earnings were down 8.7% year over year. Full-year 20Array5 operating earnings per share came in at $3.87, beating the Zacks Consensus Estimate of $3.86 and increasing from the year-ago figure of $3.85. Idacorp Inc. - Earnings Surprise | FindTheBest Total Revenue Quarterly revenues came in at $285.4 million, 22.7% lower than the year-ago level. IDACORP's 20Array5 revenues of $Array,270.3 million lagged year-ago revenues and the Zacks Consensus Estimate of $Array,282.5 million and $Array,286 million, respectively. Quarterly Highlights Total operating expenses decreased 3.9% year over year to $988.2 million in 20Array5. Costs shrunk primarily due to lower purchased power and fuel expenses compared with the prior year. Operating income increased ArrayArray.2% year over year to $282.Array million in 20Array5. Interest expenses increased 2.6% year over year to $8Array.9 million in 20Array5. Financial Update Cash & cash equivalents as of Dec 3Array, 20Array5, were $ArrayArray4.8 million compared with $56.8 million as of Dec 3Array, 20Array4. Long-term debt as of Dec 3Array, 20Array5, was $Array.73 billion compared with $Array.59 billion as of Dec 3Array, 20Array4. Cash from operating activities in 20Array5 was $353.2 million compared with $364.3 million in the year-ago period. 20Array6 Guidance IDACORP provided 20Array6 earnings guidance in the range of $3.80 to $3.95 per diluted share. The company also stated that its operating and maintenance expense guidance for 20Array6 is in the range of $350 million to $360 million. Other Utility Releases DTE Energy Company DTE reported fourth-quarter 20Array5 operating earnings per share of $Array.0Array, surpassing the Zacks Consensus Estimate of 97 cents by 4.Array%. NextEra Energy NEE announced fourth-quarter 20Array5 adjusted earnings of $Array.Array7 per share, lagging the Zacks Consensus Estimate of $Array.ArrayArray by 5.4%. American Electric Power Co., Inc. AEP reported fourth-quarter 20Array5 operating earnings of 48 cents per share, missing the Zacks Consensus Estimate of 50 cents by 4%. Zacks Rank IDACORP Corp. currently carries a Zacks Rank #2 (Buy). 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 >> 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 AMER ELEC PWR (AEP): Free Stock Analysis Report NEXTERA ENERGY (NEE): Free Stock Analysis Report DTE ENERGY CO (DTE): Free Stock Analysis Report IDACORP INC (IDA): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Research The views and opinions expressed herein are the views and opi\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": "-0.0226", "answer_numeric": -0.022569, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0226 (i.e., on a bad day with 5% probability, the loss exceeds 2.26%). CVaR(95%) = -0.0283.", "metadata": {"var": -0.022569, "cvar": -0.028251, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200212_0813", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-02-12", "context_summary": "LINK-USD: 60-day return history, mean=0.0120, std=0.0480.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0120, std=0.0480, min=-0.1137, max=0.1653\nMarket regime: sideways\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": "-0.0507", "answer_numeric": -0.050713, "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%) = -0.0796.", "metadata": {"var": -0.050713, "cvar": -0.079647, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20151222_0815", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2015-12-22", "context_summary": "VEA: 60-day return history, mean=0.0004, std=0.0092.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0004, std=0.0092, min=-0.0195, max=0.0201\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-12-21] [\"Ericsson shares up 6% after settling patent litigation with Apple\", \"Ericsson jumps 7% after settling mobile patent dispute with Apple Shares in L.M. Ericsson Telefon AB climbed 7% on Monday in Stockholm after the Swedish maker of telecom equipment said it had settled litigation with Apple Inc. , which has agreed to pay royalties for use of Ericsson's mobile technology patents. The two have signed a global patent license agreement that resolves \\\"all pendingpatent-infringement litigation between the companies\\\" and covers \\\"patents relating to both companies' standard-essential patents (includingthe GSM, UMTS and LTE cellular standards),\\\" Ericsson said in a news release. Apple will make an initial payment toEricsson and then make on-going royalties as part of the seven-year deal, Ericsson said, adding that other deal details are confidential.\", \"Why this \\u2018insane\\u2019 year in markets is poised for a wild finish Everything you need to know before the market opens So much for a relaxing market farewell to 2015. Last week was all over the place, with four days moving in excess of 1% in either direction on the S&P 500, while the Dow had three, including that nasty exclamation point on Friday.\", \"Fitbit's stock surges after Pacific Crest says sales have been 'exploding' Fitbit Inc.'s stock surged 3.4% in premarket trade Monday, after Pacific Crest Securities analyst Brad Erickson said the fitness-band maker's holiday sales have been \\\"exploding\\\" since a weak Black Friday performance. Erickson said his in-store checks suggest a \\\"substantial increase\\\" in sales volumes from a month ago, nearly a third of stores have seen temporary sell outs and market share remains dominant. \\\"We are obviously encouraged by seeing in-store demand come back so strongly as a proxy for overall demand,\\\" Erickson wrote in a note to clients. He said he was also encouraged that competitors, such as Garmin Ltd. and Apple Inc. , have been discounting their fitness products while Fitbit has not. Erikson said expected new products, to be introduced at the Consumer Electronics Show in Las Vegas in early January, could provide a sales boost. Fitbit's stock has tumbled 27% over the past three months through Friday, while the S&P 500 has gained 2%.\", \"Ericsson, Apple settle tech patent dispute STOCKHOLM--Swedish telecom company Ericsson and U.S. tech giant Apple Inc. have signed a global license agreement that puts an end to an almost year-long patent dispute between the two companies. Ericsson said that under the seven-year accord it will be paid an initial amount by Apple along with ongoing royalties.\", \"A new Apple iPhone and a Tesla rival mark the most anticipated products of 2016 Virtual reality, left for dead, might stage a big comeback Virtual reality, left for dead, might stage a big comeback, says Jurica Dujmovi\\u0107.\", \"Stocks: Is There Life After FANG? Morgan Stanley's Adam Parker and team argued there's life outside of Facebook (FB), Amazon.com (AMZN), Netflix \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": "-0.0122", "answer_numeric": -0.012173, "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%) = -0.0176.", "metadata": {"var": -0.012173, "cvar": -0.017627, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200925_0817", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2020-09-25", "context_summary": "ACWI: 60-day return history, mean=0.0009, std=0.0100.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0009, std=0.0100, min=-0.0309, max=0.0194\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-24] [\"AppFolio Deep Dive: Is This Real Estate SaaS Company Worth Buying? In this week's episode of Industry Focus: Financials, host Jason Moser and Fool.com contributor Matt Frankel, CFP, take a closer look at AppFolio (NASDAQ: APPF), a software-as-a-service company that offers a subscription-based solution for the property management industry. Plus, hear why Matt has Bank of America (NYSE: BAC) at the top of his watch list this week, while Jason is looking closely at Darden Restaurants (NYSE: DRI) ahead of earnings. 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\\u00c2 Walmart When investing geniuses David and Tom Gardner have 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.* David and Tom just revealed what they believe are the\\u00c2 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 2/1/20 This video was recorded on September 21, 2020. Jason Moser: It's Monday, September 21st. I'm your host Jason Moser. On this week's Financial show, we're going to dig a little bit deeper into a company called AppFolio. A software company targeting the real estate and legal markets. We've also got a couple of stocks for you to keep an eye on this week. As always, joining me this week, it's Certified Financial Planner, Mr. Matt Frankel. Matt, how's everything going? Matt Frankel: Just fine. I mean, it's not as great here as my sunny Florida background might suggest. But it's 70 and sunny in South Carolina; I can't go wrong. Moser: Yeah, I was going to say it, I mean, that doesn't sound like that's all that different. So, you know, hey, listen ... Frankel: There's no ocean right next to me. Moser: Now, well, yeah. Well, that just makes the ocean better for when you want to go visit, right? If you're around the ocean all-day every day, it kind of gets boring and mundane. Well, I guess people like to believe that, but I grew up on the water down in Charleston and I can verify that it never really got boring and mundane, I always really [laughs] enjoyed being on the water, so. [laughs] Hey, so, Matt, we're going to dig into a company today that you and I haven't really talked a whole heck of a lot about on the show. You know, I've seen it in passing and I've looked a little bit into it just because of the type of business that it is. But I'm excited about today, because we're going to learn a lot more about this business. And hopefully, our listeners as well will learn a lot more about it too. And this is a company called AppFolio. And, Matt, this company that IPO'd back in June 2015, so it's not one of these more recent IPOs that is still \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": "-0.0150", "answer_numeric": -0.01505, "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%) = -0.0245.", "metadata": {"var": -0.01505, "cvar": -0.02447, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170724_0819", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2017-07-24", "context_summary": "IWM: 60-day return history, mean=0.0003, std=0.0075.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0003, std=0.0075, min=-0.0273, max=0.0191\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-07-21] [\"XLU, EXC, PCG, AEP: Large Inflows Detected at ETF Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the Utilities Select Sector SPDR Fund (Symbol: XLU) where we have detected an approximate $156.0 million dollar inflow -- that's a 2.1% increase week over week in outstanding units (from 139,774,160 to 142,724,160). Among the largest underlying components of XLU, in trading today Exelon Corp (Symbol: EXC) is down about 0.2%, PG&E Corp (Symbol: PCG) is up about 0.1%, and American Electric Power Company, Inc. (Symbol: AEP) is higher by about 0.3%. For a complete list of holdings, visit the XLU Holdings page \\u00bb The chart below shows the one year price performance of XLU, versus its 200 day moving average: Looking at the chart above, XLU's low point in its 52 week range is $45.33 per share, with $54.63 as the 52 week high point - that compares with a last trade of $52.93. 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 The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Friday Sector Leaders: Utilities, Consumer Products Looking at the sectors faring best as of midday Friday, shares of Utilities companies are outperforming other sectors, up 0.3%. Within that group, FirstEnergy Corp (Symbol: FE) and American Electric Power Company, Inc. (Symbol: AEP) are two large stocks leading the way, showing a gain of 1.4% and 1.1%, respectively. Among utilities ETFs , one ETF following the sector is the Utilities Select Sector SPDR ETF (Symbol: XLU), which is up 0.2% on the day, and up 10.82% year-to-date. FirstEnergy Corp, meanwhile, is up 4.55% year-to-date, and American Electric Power Company, Inc. is up 12.17% year-to-date. Combined, FE and AEP make up approximately 7.2% of the underlying holdings of XLU. The next best performing sector is the Consumer Products sector, higher by 0.1%. Among l\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": "-0.0103", "answer_numeric": -0.010325, "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": -0.010325, "cvar": -0.017998, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201016_0821", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2020-10-16", "context_summary": "XLU: 60-day return history, mean=0.0008, std=0.0103.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0008, std=0.0103, min=-0.0219, max=0.0271\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-10-15] Adobe's Stock To Continue Growing? Despite more than a 63% rise from its March lows of this year, at the current price near $502 per share, we believe Adobe\u2019s stock (NASDAQ: ADBE) is still undervalued. ADBE stock has increased from $307 to $502 since March 23rd compared to the S&P 500 which increased almost 55% from its recent lows. The stock has outperformed the market and was at a 52 week high in early September. The company has benefited from a subscription-based business model which helps with continuous revenue flow. In the first nine months (ended August 2020) of FY 2020 Adobe saw revenue grow to $9.4 billion, up by 15% y-o-y while earnings were recorded at $6.25 compared to $4.31 in the same period of the previous year. Our dashboard What Factors Drove 179% Change In Adobe Systems Stock Between 2017 And Now? provides the key numbers behind our thinking. The 175% rise in ADBE stock price between FY 2017 to FY 2019 is justified by significant growth in earnings during those two years. Adobe\u2019s Revenue increased 53% from $7.2 billion in FY2017 to $11.2 billion in FY2020 (FY ends in November). This effect was amplified by margins increasing from 23.2% to 26.4% during this period. On a per share basis, earnings went up from $3.43 to $6.07. Higher revenue and margins were driven by overall industry growth and innovative solutions. During the same period, the P/E multiple declined slightly from 52x to 51x. This was because the rise in stock price was lower than the growth in EPS. The P/E jumped in 2020 following the outbreak of coronavirus pandemic as more and more organizations were switching to remote working and faster digital transformations. Currently the multiple stands at 83x and is likely to see a modest upside as the current crisis abates. Where Is The Stock Headed? The global spread of coronavirus led to lockdown in various cities across the globe, which affected industrial and economic activity. With the majority of people working from home, the demand for Adobe\u2019s solutions has increased. This was evident to a certain extent from the recently released Q3 2020 results of ADBE for the quarter ending August 2020. Revenue increased by 14% while earnings increased by 22% on a y-o-y basis. Remaining Performance obligation surpassed $10 billion at the end of the quarter. The actual recovery and its timing hinge on the broader containment of the coronavirus spread. Our dashboard Trends In U.S. Covid-19 Cases provides an overview of how the pandemic has been spreading in the U.S. and contrasts with trends in Brazil and Russia. With investors focusing their attention on 2021 results, the valuations become important in finding value. Expectations of revenue and earnings rising due to the continuous digital transformation initiatives and with investors\u2019 focus shifting to the 2021 numbers, Adobe\u2019s stock could see an upside in the near term. As per Adobe\u2019s valuation by Trefis, we have a price estimate of $554 per share for ADBE\u2019s stock, reflecting al\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": "-0.0156", "answer_numeric": -0.015554, "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%) = -0.0190.", "metadata": {"var": -0.015554, "cvar": -0.019009, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170320_0823", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2017-03-20", "context_summary": "VTI: 60-day return history, mean=0.0009, std=0.0043.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0009, std=0.0043, min=-0.0083, max=0.0134\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-03-17] [\"5 Stocks To Watch For March 17, 2017\", \"Wunderlich Upgrades Adobe Systems to Buy, Raises Price Target to $145.00\", \"A Peek Into The Markets: U.S. Stock Futures Edge Higher Ahead Of Consumer Sentiment Data\", \"Adobe's Premium Valuation Is Warranted; Wunderlich Upgrades To Buy\", \"20 Stocks Moving In Friday's Pre-Market Session\", \"The Market In 5 Minutes\", \"Benzinga's Top Upgrades, Downgrades For March 17, 2017\", \"This Is What Makes Adobe The Best Large-Cap Stock In Its Space\", \"Adobe Makes New All-Time High\", \"Success Stories With Facebook, T-Mobile And Others Keep Adobe Stock A Core Holding\", \"8 Biggest Price Target Changes For Friday\", \"15 Biggest Mid-Day Gainers For Friday\", \"Analyst: Good Q1 For Adobe, But Valuation Already Reflects Most Potential For Growth\", \"Analyst: Good Q1 For Adobe, But Valuation Already Reflects Most Potential For Growth\", \"15 Biggest Mid-Day Gainers For Friday\", \"8 Biggest Price Target Changes For Friday\", \"Success Stories With Facebook, T-Mobile And Others Keep Adobe Stock A Core Holding\", \"Adobe Makes New All-Time High\", \"This Is What Makes Adobe The Best Large-Cap Stock In Its Space\", \"Benzinga's Top Upgrades, Downgrades For March 17, 2017\", \"The Market In 5 Minutes\", \"20 Stocks Moving In Friday's Pre-Market Session\", \"Adobe's Premium Valuation Is Warranted; Wunderlich Upgrades To Buy\", \"A Peek Into The Markets: U.S. Stock Futures Edge Higher Ahead Of Consumer Sentiment Data\", \"Wunderlich Upgrades Adobe Systems to Buy, Raises Price Target to $145.00\", \"5 Stocks To Watch For March 17, 2017\", \"3 Big Stock Charts for Friday: Adobe Systems Incorporated (ADBE), Netflix, Inc. (NFLX) and International Business Machines Corp. (IBM) InvestorPlace - Stock Market News, Stock Advice & Trading Tips Earnings and upgrades are moving stocks in the technology sector today. Adobe Systems Incorporated (NASDAQ: ADBE ) announced better than expected earnings while Netflix, Inc. (NASDAQ: NFLX ) is seeing some cautious comments from the analyst community and International Business Machines Corp. (NYSE: IBM ) saw an upgrade to its price target from Morgan Stanley yesterday. All three of these stocks were already operating in strong bullish trends, but the recent price activity is signalling that the bulls are getting ready to engage these stocks again. Adobe Systems Incorporated (ADBE) Adobe announced earnings this morning, surprising the Street with better-than-expected results. ADBE shares are trading more than 5% higher after the news. Adobe shares have been trying to break into another volatility rally for the last week, but had failed to move above their top Bollinger Band. Today's news will change that as ADBE stock will open outside of the bands and likely see a further surge. 10 Monthly Dividend Stocks to Buy to Pay the Bills We saw a 9% reduction in the short interest on Adobe ahead of the earnings announcement, indicating that the short selling crowd has already started trying to get out of the way of ADBE shares breaking to new \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": "-0.0045", "answer_numeric": -0.004544, "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%) = -0.0072.", "metadata": {"var": -0.004544, "cvar": -0.007187, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200731_0826", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-07-31", "context_summary": "MATIC-USD: 60-day return history, mean=0.0005, std=0.0355.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0355, min=-0.0744, max=0.1246\nMarket regime: sideways\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": -0.053698, "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%) = -0.0670.", "metadata": {"var": -0.053698, "cvar": -0.066976, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20200310_0828", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2020-03-10", "context_summary": "BNB-USD: 60-day return history, mean=0.0033, std=0.0459.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0033, std=0.0459, min=-0.1588, max=0.1160\nMarket regime: sideways\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": "-0.0759", "answer_numeric": -0.075934, "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%) = -0.1059.", "metadata": {"var": -0.075934, "cvar": -0.105899, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181210_0831", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2018-12-10", "context_summary": "IWM: 60-day return history, mean=-0.0027, std=0.0139.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0027, std=0.0139, min=-0.0371, max=0.0286\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-12-07] [\"What the Arrest of a Chinese Executive Means for the Stock Market A massive drop in the Dow Jones Industrial Average was spurred by the arrest of Huawei CFO Meng Wanzhou. And it was a confirmation that tensions between the U.S. and China are about more than trade.\", \"These 5 stocks are surprising winners amid the market\\u2019s wild swings Scana, Newell Brands, McCormick, Spirit Airlines, Dr. Reddy\\u2019s Impressive gains for investors so far this quarter.\", \"Morgan Stanley gets less bullish on Apple due to China demand woes Morgan Stanley analyst Katy Huberty cut her price target on Apple Inc. shares to $236 from $253 on Friday, citing weakness in the China market. She said that her supply-chain conversations in Asia suggest that the smartphone market is weakening in China. The country is \\\"following in the footsteps of the U.S. with replacement cycles lengthening after a structurally shorter cycle over the last decade,\\\" Huberty wrote. Rising average selling prices and overall better smartphone quality are leading people to keep their current devices for longer, according to Huberty. She also sees \\\"some risk of churn\\\" at the low end of Apple's customer base in China, given that some local manufacturers are offering phones with new features such as a triple camera. Huberty kept her overweight rating on the stock and said that wearables and services revenues could help the company amid a weak stretch for iPhones. Apple's shares are off 0.2% in Friday morning trading, and they're down 21% over the past three months. The Dow Jones Industrial Average has dropped 3.4% in that time.\", \"Apple\\u2019s iPhone Sales in China Will Slip, Says Morgan Stanley Analyst Katy Huberty cut her price target on Apple to $236 from $253 but reiterated an Outperform rating for the services business.\", \"All 30 Dow industrials stocks and the 20 Dow transport stocks are falling As the Dow Jones Industrial Average tumbles 659 points, or 2.6%, in afternoon trade, all 30 of its components are losing ground. Of the biggest decliners, shares of Microsoft Corp. dropped 4.4%, Caterpillar Inc. shed 4.3% and Intel Corp. declined 4.3%. The most active Dow stock was Apple Inc. , which shed 3.5% toward the lowest close since April 30. Elsewhere, the Dow Jones Transportation Average lost 4.2%, with all 20 components falling. Meanwhile, the defensive Dow Jones Utility Average rose 0.5%, with 14 of 15 components gaining ground.\", \"Online Holiday Sales Are Soaring Adobe Analytics expects a record $124.1 billion in domestic online holiday sales through Dec. 31, up 15% from $108.2 billion a year ago.\", \"Apple iPhones Won\\u2019t See Major Redesigns in 2019, Says Analyst The new iPhones in the second half of fiscal 2019 will likely have the same body size and displays as the current iPhone XR, XS, and XS Max models, according to Nomura\\u2019s Anne Lee.\", \"Older Consumers Are a Lucrative Market By 2030, seniors will be one billion strong globally and account for half of all consumer spending\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": "-0.0222", "answer_numeric": -0.022205, "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%) = -0.0344.", "metadata": {"var": -0.022205, "cvar": -0.034426, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180918_0833", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-09-18", "context_summary": "XRP-USD: 60-day return history, mean=-0.0078, std=0.0552.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0078, std=0.0552, min=-0.1449, max=0.2539\nMarket regime: sideways\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": "-0.0813", "answer_numeric": -0.081278, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0813 (i.e., on a bad day with 5% probability, the loss exceeds 8.13%). CVaR(95%) = -0.1272.", "metadata": {"var": -0.081278, "cvar": -0.127195, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20191127_0835", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2019-11-27", "context_summary": "BIL: 60-day return history, mean=0.0000, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0000, std=0.0001, min=-0.0001, max=0.0003\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": "-0.0001", "answer_numeric": -0.000109, "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%) = -0.0001.", "metadata": {"var": -0.000109, "cvar": -0.000109, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210210_0837", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2021-02-10", "context_summary": "XRP-USD: 60-day return history, mean=0.0055, std=0.1017.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0055, std=0.1017, min=-0.2138, max=0.3257\nMarket regime: sideways\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": "-0.1244", "answer_numeric": -0.124372, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1244 (i.e., on a bad day with 5% probability, the loss exceeds 12.44%). CVaR(95%) = -0.1867.", "metadata": {"var": -0.124372, "cvar": -0.1867, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181115_0839", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2018-11-15", "context_summary": "QQQ: 60-day return history, mean=-0.0012, std=0.0150.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0012, std=0.0150, min=-0.0399, max=0.0340\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-11-14] [\"Apple stock swings lower after Goldman cuts target, another supplier slashes guidance Shares fall to 3 1/2-month low after seesaw session, suffer fourth straight decline Apple shares swung back to losses after a downbeat report from Goldman Sachs and another revenue warning from a supplier of smartphone components fueled concerns over deteriorating iPhone demand.\", \"Apple downgraded to neutral from buy at Guggenheim\", \"Apple's stock falls after Guggenheim downgrades, cuts earnings outlook Shares of Apple Inc. fell 0.4% in premarket trade Wednesday, which puts them in danger of a fifth-straight decline, after the technology giant was downgraded by analyst Rob Cihra at Guggenheim Securities, who said rising average selling prices (ASPs) was \\\"no longer enough\\\" to offset declining iPhone units. Cihra cut his fiscal 2019 earnings estimate to $12.97 a share from $13.41--the FactSet consensus is $13.44--and his revenue estimate to $273 billion from $281 billion. \\\"Over the past 10 years, Apple's iPhone ASP has increased a dramatic +$220, or 40%, reflecting its growing value to both consumer and business markets, but nearly half of all that just came in [fiscal year 2018] alone, making a period of digestion now likely,\\\" Cihra wrote in a note to clients. Apple's stock has tumbled 8.4% over the past four sessions to close at a 3 1/2-month low amid growing concerns over slowing iPhone demand. It was still up 13.6% year to date, while the Dow Jones Industrial Average has gained 2.3%.\", \"Oil, Apple, and More to Think About as the Dow Presses On Global equity markets are still under pressure. Worry over demand for Apple iPhones and the price of oil are dragging on stocks.\", \"Apple's stock turns higher, rallies 0.8% in premarket trade\", \"Apple\\u2019s iPhone Revenue Is Poised to Fall Next Year, Analyst Says Demand for iPhones is likely to fall next year, and Apple\\u2019s revenue from its key product is poised to decline, according to Guggenheim Securities.\", \"Here\\u2019s how to easily reduce your investment risk just at the right time Mike Loewengart of E-Trade discusses equal-weighted and bond ETFs, and actively managed funds for diversification Mike Loewengart of E-Trade discusses equal-weighted and bond ETFs, and actively managed funds for diversification.\", \"The Dow Sinks Because There\\u2019s More to Worry About Than Oil and Apple The Dow Jones Industrial Average was lower Wednesday as investors balanced largely positive news on inflation against Chinese data and worries about Brexit.\", \"Apple's stock falls 2.1%, as market-cap drops below $900 bln\", \"Podcast: PowerPoint Fatigue This week on The Readback, Alex Eule speaks with Al Root about the possible connection between the lenght of a company\\u2019s earnings presentation and its stock.\", \"These two chart patterns tell the real story of the stock market Bullish and bearish patterns are of low quality Bullish and bearish patterns are of low quality.\", \"Dow's 205-point drop marks longest skid for blue ch\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": "-0.0263", "answer_numeric": -0.026292, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0263 (i.e., on a bad day with 5% probability, the loss exceeds 2.63%). CVaR(95%) = -0.0369.", "metadata": {"var": -0.026292, "cvar": -0.036851, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170413_0841", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2017-04-13", "context_summary": "EEM: 60-day return history, mean=0.0012, std=0.0076.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0012, std=0.0076, min=-0.0178, max=0.0258\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-04-12] [\"Six Reasons Cirrus Won\\u2019t See Apple Insourcing It\\u2019s unlikely Apple will insource Cirrus\\u2019 audio codec or amplifier, based on a long relationship, for starters.\", \"BlackBerry Surges 17% on Award of $815M from Qualcomm Shares of BlackBerry (BBRY) are up $1.29, or 17%, at $8.99, in early trading the company announced it was awarded roughly $815 million from Qualcomm (QCOM) for having overpaid the latter in royalties, as a result of arbitration between the two. The final terms of the aware await a May 30th hearing. BlackBerry CEO John Chen said his company and Qualcomm are still \\u201cvalued technology partners.\\\"The award comes as Qualcomm is counter-suing Apple (AAPL) in a dispute over royalties.The refunds come because BlackBerry in recent years fell below the rate of smartphone shipments it had originally expected under its deal with Qualcomm.Mike Walkley of Raymond James, who has a Hold rating on BlackBerry stock, raises his price target today to $9.50 from $8.\", \"Apple May Have Consequences for Hampering Qualcomm Contracts, Says Wells The Street continues to assess Qualcomm\\u2019s (QCOM) 134-page brief in its countersuit against Apple (AAPL) yesterday.Today\\u2019s note comes from Maynard Um of Wells Fargo, who has a Market Perform rating on shares of Apple.Um deems something new in Qualcomm\\u2019s paperwork: Apple has put suppliers in a position where they may be breaching their own agreements with Qualcomm, which could have consequences for Apple:\", \"Apple: Whose Chips Will They Dump Next? Asks Pac Crest Pacific Crest semiconductor analyst John Vinh this morning reflects on rumors in recent weeks that Apple (AAPL) is looking to dump chips it uses from Dialog Semiconductor (DGLNF) and Imagination Technologies (IGZ), and ponders who might be next.He concludes the risk to wireless chip vendors such as Broadcom (AVGO), Skyworks Solutions (SWKS) and Qorvo (QRVO) is \\u201clow,\\u201d the risk to audio chip provider Cirrus Logic (CRUS) is \\u201clow to medium,\\u201d and the risk to Synaptics (SYNA) is \\u201cmedium to high.\\\"\\\"In light of concerns over Imagination Technologies graphics chips and Dialog Semiconductor power management chips being insourced at Apple, we believe the risk of Synaptics being displaced is medium to high,\\u201d writes Vinh.\", \"Apple: Rosenblatt, Needham Debate 3-D Sensing (Update) Yesterday, I wrote that Needham & Co. chip analyst Rajvindra Gill opined a technology called \\\"3-D sensing\\u201d might be missing from Apple's (AAPL) next iPhone, presumably the 10th anniversary \\u201ciPhone 8,\\u201d or \\u201ciPhone X.\\u201dAnother analyst, Jun Zhang, today calls that bunk.Gill in his note yesterday cited conversations with companies in the supply chain, in particular. In particular, Gill spoke with one James Wong, who is the COO of Truly Holdings, a company that does assembly work for a variety of smartphone makers.From those talks he learned there have been problems with incorporating 3-D sensing into the iPhone, whic\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": "-0.0098", "answer_numeric": -0.009761, "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%) = -0.0136.", "metadata": {"var": -0.009761, "cvar": -0.01358, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170718_0843", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2017-07-18", "context_summary": "TLH: 60-day return history, mean=0.0001, std=0.0032.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=0.0001, std=0.0032, min=-0.0069, max=0.0108\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": "-0.0039", "answer_numeric": -0.003857, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0039 (i.e., on a bad day with 5% probability, the loss exceeds 0.39%). CVaR(95%) = -0.0051.", "metadata": {"var": -0.003857, "cvar": -0.005112, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190329_0845", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2019-03-29", "context_summary": "ADA-USD: 60-day return history, mean=0.0088, std=0.0441.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0088, std=0.0441, min=-0.1263, max=0.1197\nMarket regime: sideways\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": "-0.0440", "answer_numeric": -0.043961, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0440 (i.e., on a bad day with 5% probability, the loss exceeds 4.40%). CVaR(95%) = -0.0796.", "metadata": {"var": -0.043961, "cvar": -0.079598, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20161005_0847", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SLV"], "decision_date": "2016-10-05", "context_summary": "SLV: 60-day return history, mean=-0.0017, std=0.0158.", "question": "Asset: SLV\nDaily returns (past 60 days): mean=-0.0017, std=0.0158, min=-0.0452, max=0.0380\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SLV. Express as a decimal (e.g., -0.02).", "answer": "-0.0265", "answer_numeric": -0.026475, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0265 (i.e., on a bad day with 5% probability, the loss exceeds 2.65%). CVaR(95%) = -0.0352.", "metadata": {"var": -0.026475, "cvar": -0.035232, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160526_0849", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2016-05-26", "context_summary": "XLU: 60-day return history, mean=0.0009, std=0.0085.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0009, std=0.0085, min=-0.0253, max=0.0152\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-25] [\"Today\\u2019s Top 5 Stock Picks: Bargains in U.S. and Asia Danton Goei, portfolio manager at Davis Advisors, explains how you can buy Tencent at a discount.\", \"Goldman Revives HTC: VR Is The Next Big Product And HTC Is The New Apple Will virtual reality toys be as dominant as smartphones today and HTC Corp. (2498.Taiwan) be the next Apple (AAPL)?Goldman Sachs thinks so.HTC soared 8.8% in Taipei after Goldman initiated its coverage with a \\\"conviction\\\" buy. Its price target of 95 new Taiwan dollars implies 41% upside (before the market open), \\\"the most in our coverage [of stocks],\\\" pumped the bank.READ MORE.\", \"LG Innotek Jumps On Sony Exit: Any Upside Left To The Dual Camera Story? Korea's LG Innotek (011070.Korea) jumped 6.8% to 87,800 won after Sony Corp. (6758.Japan/SNE) said at its earnings briefing yesterday that it would \\\"terminate the development and manufacturing of high-functionality camera modules for external sales.\\\" LG Innotek competes with Sony for Apple's (AAPL) camera module business.So now unless a third competitor appears, LG Innotek is poised to become the sole camera module supplier for Apple.READ MORE.\", \"Twitter\\u2019s stock tumble belies bullish chart patterns Shares fall, but momentum, RSI, MACD indicators trend higher Twitter\\u2019s stock hits all-time intraday low, but Class A \\u201cbullish divergence\\u201d in a number of momentum indicators suggest a sharp short-term bounce may be just around the corner.\", \"What it will take to get the S&P 500 above 2,100 again Critical information ahead of the U.S. market\\u2019s open Technical signals have been pointing to trouble for the S&P 500, but a turn of fortunes may be in the cards if gains keep up Wednesday. Plus, our chart of the day is on a commodity set to benefit from Tesla\\u2019s popularity\", \"Microsoft to cut 1,850 smartphone workers Microsoft Corp., struggling to restart its mobile strategy after multiple misfires, early on Wednesday morning announced a further step in dismantling the mobile-phone operations it acquired from Nokia Corp.\", \"Can India Steal iPhone Share From China, Taiwan? Just After Apple CEO Tim Cook visited India, now comes word that Apple (AAPL) must source components in India to expand there.The government is clearly digging in its heels through a very public negotiation.READ MORE>>\", \"Universal Display: Needham Ups Target to $69 on Expected Industry Acceleration Shares of organic light-emitting diode technology maker Universal Display (OLED) are up $1.35, or 2%, at $65.74, following yet another mention in the past few days, this time from Needham & Co.\\u2019s James Ricchiuti, who raised his price target on the stock to $69 from $62, and reiterated his Buy rating, after reaching greater confidence in his belief OLED technology will accelerate in displays for mobile phones and such.Ricchiuti writes of having met with management at Universal recently and attended the \\u201cSociety for Information Displays\\u201d conference in San Francisco, known a\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": "-0.0189", "answer_numeric": -0.018899, "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%) = -0.0218.", "metadata": {"var": -0.018899, "cvar": -0.021784, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170911_0853", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2017-09-11", "context_summary": "XLU: 60-day return history, mean=0.0006, std=0.0051.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0006, std=0.0051, min=-0.0113, max=0.0095\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-09-08] [\"Amazon headed for $1.6 trillion market cap, analyst suggests Predicted growth of retail, cloud-computing businesses would push Bezos\\u2019s stake to more than $250 billion Amazon.com Inc. could be worth $1.6 trillion in less than a decade, an investment analyst predicted Thursday, a move that would make Chief Executive Jeff Bezos\\u2019s stake worth more than $250 billion.\", \"Roku is launching its own free, ad-supported movie channel News comes after Roku unveiled plans for an IPO with the aim of raising up to $100 million Streaming device maker Roku Inc. on Wednesday said it has launched its own channel on the Roku platform.\", \"Fitbit shares close up 10% on diabetes-monitoring partnership in new smartwatch Fitness-tracker company shares hit highest prices since January after detailing collaboration with DexCom glucose monitors Fitbit Inc. shares rally Thursday to close at levels not seen since late January after the fitness-tracker company announces a collaboration with glucose-monitoring device company DexCom Inc. to allow diabetics to monitor their blood sugar through Fitbit\\u2019s new smartwatch.\", \"Facebook is ponying up to spend $1 billion in its push for video The social-media giant\\u2019s investment pits it against traditional broadcasters such as HBO and deep-pocketed tech companies such as Amazon and Netflix Facebook Inc. is loosening its purse strings in its drive to become a major hub for video.\", \"Media: Arms Race For Content Continues As Ad Sales Shrivel Skinny bundles are also still all the rage, while the NFL ad season has gotten off to a sluggish start.\", \"Finisar Falls: Big Apple iPhone Sensing Deal Delayed, Not Lost, Say Bulls Finisar shares are down 6% after it Thursday afternoon missed with its quarterly revenue outlook, saying it experienced a delay in selling parts for 3-D sensing, which most observers believe are destined for Apple's next iPhone. Finisar told analysts the shortfall is merely a delay, not a case of lost business, as it had to adjust its manufacturing techniques to improve the part. Analysts seemed to give CEO Jerry Rawls the benefit of the doubt, although they cut their price targets on Finisar.\", \"Get ready for the \\u2018voice revolution\\u2019 in stocks Cody Willard shares details of his new book Cody Willard shares details of his new book.\", \"Competition Ramps Up In Machine Learning Chips More companies are offering more options as the space heats up.\", \"Verizon's stock set to suffer longest losing streak in 12 years, but BTIG says it looks 'attractive' Shares of telecom giant Verizon Communications Inc. slumped 0.5% in afternoon trade, putting them on track to suffer a ninth-straight loss. That would be the longest losing streak since the nine-session stretch ending Oct. 13, 2005. There have been four eight-session losing streaks since then, in May 2017, October 2012, January 2012 and February 2009. Analyst Walter Piecyk at BTIG warned investors against selling into the weakness, saying the stock's rela\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": "-0.0081", "answer_numeric": -0.008108, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0081 (i.e., on a bad day with 5% probability, the loss exceeds 0.81%). CVaR(95%) = -0.0101.", "metadata": {"var": -0.008108, "cvar": -0.010122, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190715_0856", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2019-07-15", "context_summary": "XLRE: 60-day return history, mean=0.0010, std=0.0087.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0010, std=0.0087, min=-0.0196, max=0.0225\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-12] [\"Tlwm Buys Marathon Petroleum Corp, UnitedHealth Group Inc, HCP Inc, Sells Invesco S&P ...\", \"Will Hot Growth Stocks Break Out From These 5 Leading Industry Groups?\", \"Tigress Financial Analyst Ivan Feinseth Comments On Semiconductors Strength, Tell Benzinga 'Positive trends in US-China trade negotiations is lifting all the chip stocks.'\", \"UPDATE: Cassidy Also Tells Benzinga 'Japan / Korea trade issues may drive up the prices of memory devices following a year of memory prices in free fall. Prices for memory increased w/w for the first time in over a year.'\", \"Stifel Nicolaus Analyst Kevin Cassidy On Semiconductors Strength, Tells Benzinga 'The fed signaling lower interest rates and Trump loosening the ban on Huawei are both huge news for semiconductor companies.'\", \"Shares of several semiconductor companies are trading higher amid positive trends in US-China trade negotiations, Trump loosening the Huawei ban and the Fed signaling a rate cut. Japan/Korea trade tensions could also drive up memory prices.\", \"Shares of several semiconductor companies are trading higher amid positive trends in US-China trade negotiations, Trump loosening the Huawei ban and the Fed signaling a rate cut. Japan/Korea trade tensions could also drive up memory prices.\", \"UPDATE: Cassidy Also Tells Benzinga 'Japan / Korea trade issues may drive up the prices of memory devices following a year of memory prices in free fall. Prices for memory increased w/w for the first time in over a year.'\", \"Stifel Nicolaus Analyst Kevin Cassidy On Semiconductors Strength, Tells Benzinga 'The fed signaling lower interest rates and Trump loosening the ban on Huawei are both huge news for semiconductor companies.'\", \"Tigress Financial Analyst Ivan Feinseth Comments On Semiconductors Strength, Tell Benzinga 'Positive trends in US-China trade negotiations is lifting all the chip stocks.'\", \"Tlwm Buys Marathon Petroleum Corp, UnitedHealth Group Inc, HCP Inc, Sells Invesco S&P ...\", \"Will Hot Growth Stocks Break Out From These 5 Leading Industry Groups?\", \"Shares of several semiconductor companies are trading higher amid positive trends in US-China trade negotiations, Trump loosening the Huawei ban and the Fed signaling a rate cut. Japan/Korea trade tensions could also drive up memory prices.\", \"UPDATE: Cassidy Also Tells Benzinga 'Japan / Korea trade issues may drive up the prices of memory devices following a year of memory prices in free fall. Prices for memory increased w/w for the first time in over a year.'\", \"Stifel Nicolaus Analyst Kevin Cassidy On Semiconductors Strength, Tells Benzinga 'The fed signaling lower interest rates and Trump loosening the ban on Huawei are both huge news for semiconductor companies.'\", \"Tigress Financial Analyst Ivan Feinseth Comments On Semiconductors Strength, Tell Benzinga 'Positive trends in US-China trade negotiations is lifting all the chip stocks.'\", \"Tlwm Buys Marathon Petroleum Corp, UnitedHealth Group Inc, HCP Inc, Sells Invesco S&P ...\", \"Will H\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": "-0.0138", "answer_numeric": -0.013792, "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%) = -0.0177.", "metadata": {"var": -0.013792, "cvar": -0.017708, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220314_0859", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2022-03-14", "context_summary": "DOT-USD: 60-day return history, mean=-0.0065, std=0.0468.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0065, std=0.0468, min=-0.1453, max=0.0857\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-03-13] \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": "-0.0725", "answer_numeric": -0.072545, "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%) = -0.1039.", "metadata": {"var": -0.072545, "cvar": -0.103906, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20180112_0861", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2018-01-12", "context_summary": "XLF: 60-day return history, mean=0.0017, std=0.0069.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0017, std=0.0069, min=-0.0139, max=0.0256\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-01-11] [\"ADBE March 2nd Options Begin Trading Investors in Adobe Systems Inc (Symbol: ADBE) saw new options become available today, for the March 2nd expiration. At Stock Options Channel , our YieldBoost formula has looked up and down the ADBE options chain for the new March 2nd 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 $4.50. 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 $180.50 (before broker commissions). To an investor already interested in purchasing shares of ADBE, that could represent an attractive alternative to paying $187.01/share today. Because the $185.00 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 100%. 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 2.43% return on the cash commitment, or 17.76% annualized - at Stock Options Channel we call this the YieldBoost . Below is a chart showing the trailing twelve month trading history for Adobe Systems 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 $4.20. If an investor was to purchase shares of ADBE stock at the current price level of $187.01/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 3.84% if the stock gets called away at the March 2nd expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if ADBE shares really soar, which is why looking at the trailing twelve month trading history for Adobe Systems Inc, as well as studying the business fundamentals becomes important. Below is a chart showing ADBE'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 2% premium 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 covered call contract would expire worthless, in which case the investor would keep both their shares of stock and the premium collected. The current analytical data (includin\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": "-0.0065", "answer_numeric": -0.006512, "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%) = -0.0112.", "metadata": {"var": -0.006512, "cvar": -0.011183, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160728_0863", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2016-07-28", "context_summary": "EFA: 60-day return history, mean=0.0009, std=0.0118.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0009, std=0.0118, min=-0.0289, max=0.0259\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-07-27] [\"Apple CEO Cook: India Growing Fast, China Challenged Apple (AAPL) CEO Tim Cook said he\\u2019s excited about growth prospects in India and China, but noted that India is one of its fastest-growing markets.The comments came in the evening conference call on the company\\u2019s latest quarter, which outpaced analyst expectations. Read More>>\", \"Apple Stock Undervalued Even After Recent Rally With strong third-quarter results, a low valuation and a market-beating dividend yield, Apple remains a buy.\", \"Apple CEO Cook Explains to Slightly Perplexed Analysts \\u2018So Many Signs That Are Positive\\u2019 Following better-than-expected fiscal Q3 results from (AAPL), the company held a Tuesday night with analysts.I related the prepared portion of 's remarks in a previous post; here's a rundown of the There were some conflicting remarks about the better-than-expected outlook for this quarter, and and perhaps skeptical as to why the forecast is as strong as it is, or perhaps why it wouldn't be even stronger.They can't entirely reconcile the outlook with various aspects of Apple's business as they see it.Asked by of how the company sees , Cook declined to talk about possible new product, such as a rumored , instead saying the company was relying on its sense that several countries showed double-digit growth for Apple in Q3, including , , and .\\\",\\\" he said.Rebuffing the argument from 's that phone users worldwide are , Cook said he was encouraged by \\\"an installed base that has gotten incredibly large.\\\"\\\"I see a that is the highest ever,\\\" continued Cook. \\\"I see the smartphone itself, lead by iPhone, becoming even more instrumental and important to peoples lives. It's becoming essential.\\\"\\\",\\\" he said.\", \"Apple shares rally 6% premarket after earnings beat views\", \"Nikkei climbs on hopes for bigger-than-expected stimulus for Japan Apple earnings boost Taiwan stocks Shares close 1.7% higher in Tokyo on a report that planned Japanese economic stimulus will be more than double the amount expected by the market, though the talk fails to lift markets in the rest of Asia.\", \"iPhone SE, iPad Pro throw new wrinkle into Apple finances Opinion: Average selling prices go down for iPhones, up for iPads Apple reported slightly better than expected results on Tuesday, but investors were dismayed by one important but slightly esoteric measure in the quarter\\u2014average selling prices for iPhones. But the company\\u2019s comments around ASPs also provided a window into the next quarter.\", \"Apple stock price target cut raised to $107 from $105 at J.P. Morgan\", \"Apple stock price target set at $129 at Raymond James\", \"Apple's stock soars 7.5% premarket after Q3 results late Tuesday\", \"Apple's stock surge keeping Dow futures positive Apple Inc.'s stock soared 7.3% in premarket trade Wednesday, to keep the Dow Jones Industrial Average futures in positive territory ahead of the open. The $7.03 price gain in the stock would add about 48 points to the price of the Dow, which is \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": "-0.0194", "answer_numeric": -0.019389, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0194 (i.e., on a bad day with 5% probability, the loss exceeds 1.94%). CVaR(95%) = -0.0258.", "metadata": {"var": -0.019389, "cvar": -0.02578, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20171026_0865", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2017-10-26", "context_summary": "IWM: 60-day return history, mean=0.0008, std=0.0066.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0008, std=0.0066, min=-0.0184, max=0.0194\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-10-25] [\"Chip company earnings could be driven by new iPhones, data centers Broadcom and Texas Instruments cited by analysts as top picks High-profile smartphone releases and the growth of data centers are expected to drive another strong earnings quarter for chip makers and related companies, which would put a cap on a strong year for semiconductor stocks.\", \"Tech earnings: The iPhone X and other new gadgets that will matter this holiday season Apple\\u2019s expensive new smartphone, Fitbit Ionic among devices investors will focus on as companies release important forecasts Gadget companies and Silicon Valley tech titans alike have unveiled a swath of new toys leading up to the holiday shopping season and as earnings approach, investors can learn a great deal about what\\u2019s been successful\\u2014if they know what to look for.\", \"Apple bets on 'wireless future' with New Zealand takeover Apple Inc. is buying New Zealand company PowerbyProxi for an undisclosed sum in an effort to step deeper into the wireless tech market, media reports said on Wednesday. The takeover was first reported by New Zealand news site Stuff, while Reuters said an Apple spokesperson also confirmed the deal. Dan Riccio, senior vice president of hardware engineering at the California company, told Stuff the team at PowerbyProxi will be \\\"a great addition as Apple works to create a wireless future.\\\" The company recently said it was including wireless charging in its new iPhone X and iPhone 8 smartphones. Apple shares were down 0.2% in premarket trade on Wednesday.\", \"Apple initiated at buy at HSBC\", \"Apple initiated with a buy rating at HSBC HSBC initiated coverage of Apple Inc. stock on Wednesday with a buy rating and a $193 price target with analysts saying a large and loyal user base is eager to get hold of the iPhone X. Analysts led by Steven Pelayo said they are trying to take a unique look at Apple by embracing its marketing slogan and trying to 'think different,' using the perspectives of its analysts from around the world. The bank's consumer team says Apple is not just a tech company, but also competes with luxury brands for talent, wallet share and locations. The telecom team says the U.S. is a key market and that technologies like AI, AR and foldable phones will drive demand. The internet team believes China competition is not just with handset makers, but also with Tencent in services and with super apps like WeChat as a platform for mobile payments. \\\"The Automotive team expects heavy competition between current and future entrants around electrification, automation, entertainment and connectivity over the next few years,\\\" said Pelayo. \\\"The question is what level of vertical integration is required from an OEM perspective.\\\" Apple shares were flat in premarket trade, but have gained 35.6% in 2017, while the Dow Jones Industrial Average has gained about 19% and the S&P 500 has gained 15%.\", \"Shell Trims Tesla Stake; Buys PayPal, Adobe, FedEx A unit of the oil giant th\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": "-0.0097", "answer_numeric": -0.00972, "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%) = -0.0159.", "metadata": {"var": -0.00972, "cvar": -0.015916, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190704_0867", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-07-04", "context_summary": "ETH-USD: 60-day return history, mean=0.0115, std=0.0500.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0115, std=0.0500, min=-0.1262, max=0.1382\nMarket regime: sideways\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": "-0.0658", "answer_numeric": -0.06577, "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%) = -0.0982.", "metadata": {"var": -0.06577, "cvar": -0.098196, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160512_0871", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2016-05-12", "context_summary": "EEM: 60-day return history, mean=0.0015, std=0.0132.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0015, std=0.0132, min=-0.0287, max=0.0317\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-11] [\"WhatsApp launches desktop version for Mac, Windows Popular mobile messaging app rivals Skype, Apple\\u2019s iMessage WhatsApp, the massively popular smartphone messaging app owned by Facebook Inc., is now available in a familiar place: your computer\\u2019s desktop.\", \"Justice Inquiry Reveals Wall Street\\u2019s Dirty Secret Firms profit by trading against individual investors, who they consider \\u201cdumb money.\\u201d\", \"Neither Trump nor Clinton can do much for the job market Technology and demographics are driving change, and the best that politicians can do is help retrain displaced workers Technology and demographics are driving change, and the best that politicians can do is help retrain displaced workers, says Howard Gold.\", \"Axel Springer looks to U.S. for digital growth BERLIN--German media giant Axel Springer SE says its U.S.-focused push into digital media is starting to pay off. One of Europe's biggest digital publishers, the old-line tabloid giant was once known for its Bild and Die Welt newspapers. It has worked for years to shed its reliance on print and boost online revenue.\", \"Apple: iPhone Upgrades Slowing, Stock is \\u2018Range Bound,\\u2019 Says UBS UBS\\u2019s Steve Milunovich today reiterates a Buy rating on Apple (AAPL) shares, while trimming his price target to $115 from $120, writing that he\\u2019s trimming his estimates for Apple\\u2019s iPhone sales and profit after accepting the device is going to see longer upgrade cycles for the foreseeable future.His verdict on the shares: \\u201cThe stock is likely range bound for now with low multiples acting as downside support and lack of demand catalysts an upper ceiling.\\\"The company will benefit from some increase in upgrade sales in 2017, but only to match what happened in 2015:We now expect iPhone unit growth of about 4% in F17 with upgrade growth offsetting a decline in new users. Strong sales in F15 stole from F16 but upgrades should hit in F17 or F18. Earnings only get back to the F15 level in our model, so new products may be required to excite investors beyond a trade. Apple has both annuity and hardware hits aspects, but we think the best way to understand the company is as a platform deserving of valuation b\", \"Apple suppliers in Taiwan struggling amid weaker iPhone demand Taiwan Semiconductor faces slowdown due to weak demand for premium phones like the iPhone: Nikkei Apple\\u2019s A10 chip supplier Taiwan Semiconductor Manufacturing Co. faces a slowdown in the second-half of the year\", \"Apple: \\u2018Value Trap\\u2019 as Margins Come Under Pressure, Says Former Berenberg Analyst Adnaan Ahmad, who used to be a stock analyst with Berenberg Bank covering Apple (AAPL), until last year, today issues a missive to \\u2014 well, I\\u2019m not sure if he has clients at this point, but to anyone out there, in which he continues to press the deeply negative view of Apple shares, for which he offers a Sell rating and an $80 price target.Although the stock below $100 \\u2014 it\\u2019s at $\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": "-0.0198", "answer_numeric": -0.019778, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0198 (i.e., on a bad day with 5% probability, the loss exceeds 1.98%). CVaR(95%) = -0.0235.", "metadata": {"var": -0.019778, "cvar": -0.023477, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20181015_0873", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2018-10-15", "context_summary": "IYR: 60-day return history, mean=-0.0010, std=0.0082.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=-0.0010, std=0.0082, min=-0.0272, max=0.0172\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": "-0.0133", "answer_numeric": -0.013346, "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%) = -0.0200.", "metadata": {"var": -0.013346, "cvar": -0.019962, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20150319_0875", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2015-03-19", "context_summary": "VCIT: 55-day return history, mean=0.0004, std=0.0033.", "question": "Asset: VCIT\nDaily returns (past 55 days): mean=0.0004, std=0.0033, min=-0.0075, max=0.0096\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": "-0.0043", "answer_numeric": -0.004301, "explanation": "Historical simulation VaR at 95%: sort the 55 daily returns and take the 5th percentile. VaR(95%) = -0.0043 (i.e., on a bad day with 5% probability, the loss exceeds 0.43%). CVaR(95%) = -0.0063.", "metadata": {"var": -0.004301, "cvar": -0.006288, "confidence": 0.95, "n_returns": 55, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20150306_0878", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2015-03-06", "context_summary": "EEM: 42-day return history, mean=0.0007, std=0.0114.", "question": "Asset: EEM\nDaily returns (past 42 days): mean=0.0007, std=0.0114, min=-0.0278, max=0.0218\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-03-05] [\"Apple delays production of larger iPad HONG KONG- Apple Inc. suppliers have been told to start production of a larger-screen iPad in the second half of this year as the U.S. tech giant wrestles with new designs and features for the enterprise market, people familiar with the matter say.\", \"Six reasons you should invest in the Wearables Revolution Wearables are a can't-miss growth market. The same kids (and adults) today who take selfies with their smartphones are going to be doing 10 times more of that using wearables, but how do investors make money?\", \"Why you should quit the QQQ in your IRA If you wouldn\\u2019t buy an index fund that tracks the NYSE or the Amex, why would you buy into the Nasdaq?\", \"Apple Watch could be $26 billion business by 2018 NEW YORK (MarketWatch) - The Apple Watch may be a $26 billion business by 2018, Deutsche Bank analyst Sherri Scribner predicted in a note Thursday. However, she only reiterated a hold rating on Apple Inc.'s stock, saying a limited impact from the Watch and Apple's heavy reliance on the iPhone offer \\\"limited catalysts\\\" to drive shares higher over the next few quarters. Her $110 price target implies a 14% share-price decline from Apple's $128.54 closing price on Wednesday. To be fair, Scribner is one of the most bearish Apple analysts on Wall Street. The average rating on Apple's stock among more than 40 analysts is overweight, and the average price target is $134.92, according to FactSet. While Apple will undoubtedly outsell all rival smartwatches this year, according to Scribner, she expects the Watch to remain a minor product category in relation to the iPhone, comprising 10% or less of sales and EPS by 2018. Shares of Apple traded up 0.3% in premarket trade.\", \"Apple to control 55% of smartwatch market by year end NEW YORK (MarketWatch) - Apple Inc. could sell as many as 15 million units of Apple Watch worldwide this year, according to new data from intelligence company Strategy Analytics. This comes in just shy of forecasts released earlier on Thursday by Deutsche Bank analyst Sherri Scribner, who is projecting 17.6 million watches. At that number, Apple, expected to launch the watch in early April, would be the world's biggest smartwatch vendor, holding a 55% share of the global market this year, according to Strategy Analytics. While the market for smartwatches has yet to be proven given the lack of blockbuster sales from Apple Watch predecessors, analysts believe the watch will help spark interest in the category. Total global smartwatch shipments are predicted to grow 511% to 28.1 million units this year from just 4.6 million in 2014, according to Strategy Analytics. Earlier on Thursday, Deutsche Bank predicted that the Apple Watch would become a $26 billion business by 2018. Shares of Apple fell 1.3% to $126.83 in recent trade.\", \"U.S. company earnings point to stock-market correction The price-to-earnings ratio hasn\\u2019t been so high since early 2010 The price-to-earnings ratio hasn\\u\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": "-0.0169", "answer_numeric": -0.016868, "explanation": "Historical simulation VaR at 95%: sort the 42 daily returns and take the 5th percentile. VaR(95%) = -0.0169 (i.e., on a bad day with 5% probability, the loss exceeds 1.69%). CVaR(95%) = -0.0210.", "metadata": {"var": -0.016868, "cvar": -0.020979, "confidence": 0.95, "n_returns": 42, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150918_0880", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2015-09-18", "context_summary": "XLP: 60-day return history, mean=-0.0001, std=0.0100.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0001, std=0.0100, min=-0.0250, max=0.0211\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-09-17] [\"Foxconn Gets A Good Deal Out Of SPIL: Bernstein\", \"Demand for Apple's iPhone 6S may actually be lower than for the iPhone 6--Pacific Crest Analyst Andy Hargreaves at Pacific Crest said he believes demand for Apple Inc.'s iPhone 6S is actually lower than it was for the iPhone 6, \\\"possibly meaningfully so.\\\" He said Apple's statement that iPhone 6S sales are tracking at a record pace appears more a reflection of supply, and not demand. Hargreaves said evidence of lower demand comes from Google search data, device shipment times, third-party surveys, a lack of comments from carriers and a lack of quantitative comment on pre-orders in Apple's statement. He wrote in a note to clients that Apple's iPhone upgrade program isn't likely to drive the change that some expect, as \\\"the potential benefits are likely to be muted by likely financing costs, deflation in used iPhone pricing from increasing supply and cannibalization of people that already bought phones every year or already purchased AppleCare.\\\" He reiterated his sector weight rating on the stock, saying it remains \\\"attractive over the long term, but high iPhone expectations remain a near-term risk.\\\" The stock slipped 0.5% in premarket trade, putting it on track to snap a five-session win streak. It has dropped 8.6% over the past three months, while the Dow Jones Industrial Average has lost 6.7%.\", \"EU widens corporate tax investigation All countries agree to cooperate in probe of \\u2018sweetheart\\u2019 tax deals High-profile probe into alleged sweetheart tax deals broadened after all EU countries agree to cooperate.\", \"Judgment day for markets as Fed\\u2019s trigger finger gets itchier Critical intelligence before the U.S. market opens The Janet Yellen-led Federal Reserve could blast markets with the first U.S. rate hike in nearly a decade. If the Fed frenzy is too much for you, perhaps try stocks in Italy or France.\", \"Amazon introduces its answer to Apple TV Amazon.com Inc. launched an answer to Apple Inc.'s smart TV on Thursday - and it's much cheaper. The e-commerce giant introduced its latest-generation Amazon FireTV with 4K Ultra HD, which will sell for $99.99, versus $149 for Apple TV. It comes with a remote with voice control, and compatibility with Echo, its voice-assistance technology that competes with Apple's Siri. The company will also sell a higher-tier gaming edition, which comes with a new Amazon-designed game controller and a 32 GB microSD card. The gaming edition will sell for $139.99. Amazon began taking preorders for both devices on Tuesday. Apple is expected to open up preorders its new TV for preorders next month. Shares of Amazon climbed 1% to $532.45 in recent trade, while those of Apple slumped 0.9% to $115.40.\", \"Apple: Pac Crest Sees \\u2018Several Signs\\u2019 Demand for iPhone 6s is Weaker\", \"Amazon launches cheap tablet, offers six-pack deal for $250 Amazon.com Inc. launched a new 7-inch tablet on Thursday that it is offering for $49.99 - or a six pack for $249.95\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": "-0.0168", "answer_numeric": -0.016769, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0168 (i.e., on a bad day with 5% probability, the loss exceeds 1.68%). CVaR(95%) = -0.0236.", "metadata": {"var": -0.016769, "cvar": -0.023589, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20201130_0882", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2020-11-30", "context_summary": "ETH-USD: 60-day return history, mean=0.0085, std=0.0365.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0085, std=0.0365, min=-0.0909, max=0.0982\nMarket regime: sideways\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": "-0.0382", "answer_numeric": -0.038177, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0382 (i.e., on a bad day with 5% probability, the loss exceeds 3.82%). CVaR(95%) = -0.0626.", "metadata": {"var": -0.038177, "cvar": -0.06257, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210924_0884", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2021-09-24", "context_summary": "USMV: 60-day return history, mean=0.0005, std=0.0049.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0005, std=0.0049, min=-0.0115, max=0.0103\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-23] Interesting ADBE Put And Call Options For November 5th Investors in Adobe Inc (Symbol: ADBE) saw new options become available today, for the November 5th expiration. At Stock Options Channel, our YieldBoost formula has looked up and down the ADBE options chain for the new November 5th contracts and identified one put and one call contract of particular interest. The put contract at the $595.00 strike price has a current bid of $7.85. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $595.00, but will also collect the premium, putting the cost basis of the shares at $587.15 (before broker commissions). To an investor already interested in purchasing shares of ADBE, that could represent an attractive alternative to paying $629.52/share today. Because the $595.00 strike represents an approximate 5% 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 100%. 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 1.32% return on the cash commitment, or 11.20% annualized \u2014 at Stock Options Channel we call this the YieldBoost. Below is a chart showing the trailing twelve month trading history for Adobe Inc, and highlighting in green where the $595.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $640.00 strike price has a current bid of $13.20. If an investor was to purchase shares of ADBE stock at the current price level of $629.52/share, and then sell-to-open that call contract as a \"covered call,\" they are committing to sell the stock at $640.00. Considering the call seller will also collect the premium, that would drive a total return (excluding dividends, if any) of 3.76% if the stock gets called away at the November 5th expiration (before broker commissions). Of course, a lot of upside could potentially be left on the table if ADBE shares really soar, which is why looking at the trailing twelve month trading history for Adobe Inc, as well as studying the business fundamentals becomes important. Below is a chart showing ADBE's trailing twelve month trading history, with the $640.00 strike highlighted in red: Considering the fact that the $640.00 strike represents an approximate 2% premium 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 covered call contract would expire worthless, in which case the investor would keep both their shares of stock and the premium collected. The current analytical data (including g\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": "-0.0094", "answer_numeric": -0.009352, "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%) = -0.0106.", "metadata": {"var": -0.009352, "cvar": -0.010621, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20160908_0886", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2016-09-08", "context_summary": "VNQI: 60-day return history, mean=0.0019, std=0.0085.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=0.0019, std=0.0085, min=-0.0251, 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": "-0.0095", "answer_numeric": -0.009484, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0095 (i.e., on a bad day with 5% probability, the loss exceeds 0.95%). CVaR(95%) = -0.0172.", "metadata": {"var": -0.009484, "cvar": -0.017169, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170116_0887", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2017-01-16", "context_summary": "EWJ: 60-day return history, mean=0.0006, std=0.0071.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0006, std=0.0071, min=-0.0155, max=0.0199\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-13] [\"Nintendo, Sony Investors Can Expect Gains of 50% Nintendo\\u2019s Switch gaming console and a turnaround at Sony can send shares of both companies surging.\", \"Why this winner of a retail stock will keep on delivering Critical information for the U.S. trading day It\\u2019s retail sales day and a perfect opportunity to highlight the call of the day that involves one of the biggest players on the retail landscape. Here\\u2019s why it belongs in your portfolio to stay.\", \"Broadcom, IDT To Ride Apple\\u2019s iPhone Promotions, Says Pac Crest if you\\u2019re a chip investor holding Broadcom (AVGO), Integrated Device Technology (IDTI), or Analog Devices (ADI), don\\u2019t worry, writes Pacific Crest\\u2019s John Vinh, this morning, the companies should be okay given the pace of promotions on Apple\\u2019s (AAPL) iPhone 7.Vinh sees \\u201climited risk\\u201d for AVGO, ADI and IDTI, which are his \\u201cfavorite names\\u201d among Apple suppliers.\\\"Our December carrier surveys in North America and Western Europe indicate the return of holiday promotions at AT&T, T-Mobile and Verizon were effective in keeping inventories at healthy levels,\\u201d writes Vinh.That bodes well for sales of iPhone into the channel, he writes,Holiday promotions keep iPhone 7 inventories at very healthy levels. We observed that generous carrier promotions at AT&T and Verizon were effective in keeping inventory levels in check. AT&T was offering a \\\"buy one, get one free\\\" (BOGO) promotion on the iPhone 7, while Verizon was offering up to $400 trade- in credit towards the purchase of an iPhone 7. As a result, iPhone 7 inventories (DOI and absolute) declined m/m to just over 2 days and remain well below targeted levels of 6-10 days, while sell-through was roughly flat y/y. On the iPhone 7 Plus front, we are seeing supply gradually catching up with demand, though some stores are still experiencing shortages.\", \"Videogame Sales Are Fading and It\\u2019s Crushing GameStop It wasn\\u2019t a happy holiday season for GameStop. Sales fell 16% in the last nine weeks of the year.\", \"Apple: Not Clear It\\u2019s Investible for Five-Year Periods, Says Bernstein People continue to mull the negative remarks about Apple (AAPL) made by investor Peter Thiel to The New York Times on Wednesday.In case you missed it, Thiel was asked to \\u201cconfirm\\u201d or \\u201cdeny\\u201d statements put to him by Times columnist Maureen Dowd.Down posed the statement \\\"The age of Apple is over.\\\"Said Thiel,Confirm. We know what a smartphone looks like and does. It\\u2019s not the fault of Tim Cook, but it\\u2019s not an area where there will be any more innovation.Today\\u2019s pondering of that brief item comes from Toni Sacconaghi, a bull on the stock, with Bernstein, who was interviewed a short while ago by Scott Wapner, the host of CNBC\\u2019s \\u201cFast Money: Halftime Report.\\\"Asked by Wapner if he agreed, Sacconaghi replied,\", \"Tech Today: Pandora Zooms, GrubHub Up, Apple\\u2019s Debt Leverage Here are some things going on t\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": "-0.0103", "answer_numeric": -0.010271, "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%) = -0.0142.", "metadata": {"var": -0.010271, "cvar": -0.014206, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190912_0889", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2019-09-12", "context_summary": "XLF: 60-day return history, mean=0.0008, std=0.0120.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0008, std=0.0120, min=-0.0372, max=0.0202\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-09-11] [\"Asian markets gain ahead of ECB meeting Nikkei, Hang Seng edge up as stocks in mainland China dip Asian markets mostly gained in early trading Wednesday, ahead of expected further monetary easing by the European Central Bank.\", \"Welcome to Borrower\\u2019s Paradise. How Long Can It Last? Stocks have returned to within a percent or two of their record highs, while bond yields have fallen to near-record lows, making equities\\u2019 valuations more attractive while also helping to fund share buybacks.\", \"Podcast: Apple Goes Head-to-Head With Netflix 3 numbers to help you navigate the market\\u2014in just two minutes.\", \"It\\u2019s \\u2018Too Soon to Bail\\u2019 on Apple, Amazon, and Other Top Tech Stocks For investors interested in the big FAANG tech stocks, it\\u2019s late in the game\\u2014but not too late to benefit, an analyst says.\", \"Apple iPhone event reveals a dramatic change in strategy Apple is now competing on price, after years of focusing on high margins One of the most surprising elements of Apple Inc.\\u2019s September iPhone launch was its aggressive pricing on many products, especially its new streaming service.\", \"Apple drops price on new iPhone 11, undercuts Netflix and Disney on streaming At annual event, Apple unveils three new iPhones, prices for streaming services Apple Inc. tried to make cameras the focus of its iPhone launch event on Tuesday, but the company\\u2019s most striking announcements concerned the prices of its phones and streaming offerings.\", \"Apple's stock gains 0.4% premarket after rising 1.2% on Tuesday\", \"Shift into value stocks could fuel a solid rally, says J.P. Morgan Critical information for the U.S. trading day J.P. Morgan quant strategists Marko Kolanovic and Bram Kaplan say this switch to value stocks seen lately could be promising.\", \"Apple stock price target raised to $250 from $240 at BofA Merrill Lynch\", \"Dow's nearly 75-point jump highlighted by gains for Apple Inc., Walgreens Boots shares\", \"Apple on the verge of reaching $1 trillion in market cap for first time in 10 months Shares of Apple Inc. rallied 1.7% toward a 10-month high in morning trading Wednesday, after rising 1.2% the previous sessions on the back of the technology behemoth's iPhone launch event. With the stock's recent rally, Apple is on the verge of getting back to being a trillion dollar company, something it hasn't been since Nov. 1, 2018; Apple's market capitalization is currently $995.4 billion. The stock only needs to rise another 0.5% to close at or above $221.28 for Apple's market cap to top $1 trillion, based on the latest disclosed 4.52 billion shares outstanding as of July 19. Getting back to being a trillion-dollar company would complete a recovery from a market-cap low of about $672.5 billion on Jan. 3, when the stock closed at a 21-month low of $142.19. Since then, Apple's stock has run up 55%, while the Dow Jones Industrial Average has gained 19%. Apple's market cap is still behind first-place Microsoft Corp. at $1.04 trilli\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": "-0.0231", "answer_numeric": -0.023056, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0231 (i.e., on a bad day with 5% probability, the loss exceeds 2.31%). CVaR(95%) = -0.0323.", "metadata": {"var": -0.023056, "cvar": -0.032278, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200203_0892", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2020-02-03", "context_summary": "XLU: 60-day return history, mean=0.0016, std=0.0057.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0016, std=0.0057, min=-0.0136, max=0.0147\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-01-31] [\"Why it can pay to buy the stocks of companies you love to hate Start your search for diamonds in the rough by looking through the list of the most despised companies Start your search for diamonds in the rough by looking through the list of the most despised companies.\", \"Amazon\\u2019s record holiday sales send stock soaring toward $1 trillion valuation Amazon demolishes its own disappointing forecast and returns to earnings growth after previous quarter's decline Amazon.com Inc. defied its own disappointing forecast and returned to earnings growth in the holiday quarter with more than $3 billion in profit, sending shares soaring toward a $1 trillion valuation in the extended session Thursday.\", \"One Medical is going public: 5 things to know about the primary-care startup The pitch is convenience, as company looks to \\u2018delight\\u2019 working-age adults who get health insurance through their jobs and live in urban centers like New York City and San Francisco One Medical, a direct primary-care provider, has filed for its initial public offering, trading under the name 1Life Healthcare Inc.\", \"Amazon Soars to $1 Trillion Value After Earnings Crush Estimates Amazon reported fourth-quarter earnings $6.47 a share, versus analysts\\u2019 $4.03 estimate.\", \"McDonald\\u2019s is acting more like a FAANG, and investors should love it Here\\u2019s why the stock price should climb Here\\u2019s why the stock price should climb.\", \"Amazon's stock surges to set new all-time intraday high after blowout earnings Shares of Amazon.com Inc. rocketed to a new intraday record before paring some gains, but was still on track to leapfrog Google-parent Alphabet Inc. into third place as the largest U.S. company based on market capitalization after the e-commerce and cloud giant reported blowout fourth-quarter results. The was up as much as 9.9% to an intraday high of $2,055.72, above the previous intraday record of $2,050.50 on Sept. 4, 2018. The stock, now up 8.1%, is currently below the Sept. 4, 2018 record close of $2,039.51. The market cap is at $1.002 trillion, fractionally above Alphabet's, but still well below Microsoft Corp. at $1.306 trillion and Apple Inc. at $1.402 trillion.\", \"MedMen\\u2019s Colorful Pioneer of Cannabis, Adam Bierman, Resigns as CEO The chief executive\\u2019s lavish spending antagonized colleagues and torched bonfires of cash, dropping MedMen stock nearly 90% in the past year.\", \"Google-parent Alphabet's stock falls enough to knock market cap below the trillion-dollar mark Shares of Google-parent Alphabet Inc. dropped 1.4% in midday trading, putting the internet giant in danger of dropping out of the trillion-dollar club for the second time since it joined two weeks ago. Alphabet's market capitalization was now at $989.4 billion, which currently makes it the fourth-most valuable U.S. company. Amazon.com Inc. leapfrogged Alphabet to third place on Thursday, as the e-commerce and cloud giant's stock soared 8.9% to lift the market cap to $1.01 tri\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": "-0.0094", "answer_numeric": -0.009383, "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%) = -0.0122.", "metadata": {"var": -0.009383, "cvar": -0.012185, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180411_0894", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2018-04-11", "context_summary": "LQD: 60-day return history, mean=-0.0003, std=0.0029.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=-0.0003, std=0.0029, min=-0.0055, max=0.0051\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": "-0.0043", "answer_numeric": -0.004349, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0043 (i.e., on a bad day with 5% probability, the loss exceeds 0.43%). CVaR(95%) = -0.0050.", "metadata": {"var": -0.004349, "cvar": -0.004999, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220531_0898", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2022-05-31", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0160, std=0.0662.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0160, std=0.0662, min=-0.1912, max=0.1245\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-05-30] \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": "-0.1352", "answer_numeric": -0.135212, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1352 (i.e., on a bad day with 5% probability, the loss exceeds 13.52%). CVaR(95%) = -0.1719.", "metadata": {"var": -0.135212, "cvar": -0.171941, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20160525_0900", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2016-05-25", "context_summary": "IWM: 60-day return history, mean=0.0016, std=0.0111.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0016, std=0.0111, min=-0.0244, max=0.0274\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-24] [\"Taiwan Market Seen To Stabilize As Tsai Takes Office Among Asian markets, Taiwan has been sold off the most in May. In the first three weeks, foreigners net sold $3.6 billion as they turned sour on Apple (AAPL) and its manufacturing backyard and became wary of Taiwan's relations with China.But now that President Tsai Ing-wen has taken office, the TAIEX Index should stabilize, analysts say, because some of the recent sell-off catalysts are not related to Tsai's hawkish stance towards China. HSBC summarizes the factors:READ MORE.\", \"Apple shares find traction after Taiwan report notes increased iPhone7 production Shares of Apple are up some 0.6% in premarket action, off a gain of more than 1% overnight, after a report in Taiwan's Economic Daily said the smartphone giant has asked its mostly Asia-based suppliers to make more iPhone 7s. The Economic Daily report said Apple asked suppliers to produce between 72 million and 78 million iPhone 7s by the end of the year, above Wall Street analysts' current expectations for 65 million. The report was picked up by CNBC. AAPL shares are down about 8% so far this year and down about 29% from their February 2015 high of $133.\", \"How to start the \\u2018Uber of the next big thing\\u2019 Uber\\u2019s business model works, but copying it blindly can lead to spectacular failure Uber\\u2019s business model works, but copying it blindly can lead to spectacular failure, say David S. Evans and Richard Schmalensee.\", \"Apple admits iPhone prices are too high in India Tim Cook trying to convince government to allow sales of preowned phones Apple Inc. Chief Executive Tim Cook did something out of character this week in an effort to win more business in India: He admitted the iPhone might be too expensive.\", \"Global GDP: Is iPhone Inflation Overstated? Is economic data used to calculate hundreds of millions of dollars of pension payments unreliable? The truth may be politically unpalatable, Schroders economists say. They use Apple iPhone pricing as an example of how fundamental economic calculations -- used globally -- may be flawed.READ MORE>>\", \"Best Buy Drops 8%: Where Are the \\u2018Iconic\\u2019 Products? Asks Citi Shares of Best Buy (BBY) are down $2.57, or almost 8%, at $30.43, after the company this morning reported fiscal Q1 revenue and earnings per share that topped analysts\\u2019 expectations, but forecast this quarter\\u2019s earnings lower and said CFO Sharon Mccollumwill step down in June.This is the stock\\u2019s biggest drop since January 14th, when it fell 10%, according to Dow Jones index mavens.The stock has already gotten one downgrade, from Citigroup\\u2019s Kate McShane, who cut her rating shortly after the report to Neutral from Buy.McCollam\\u2019s replacement is Corie Bary, a 16-year Best Buy vet who has been serving as \\u201cchief strategic growth officer.\\\"Revenue in the three months ended in April declined by 1%, year over year, to $8.44 billion, yielding EPS of 44 cents, excluding some costs. Analysts \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": "-0.0160", "answer_numeric": -0.016006, "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%) = -0.0199.", "metadata": {"var": -0.016006, "cvar": -0.019878, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20151020_0902", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2015-10-20", "context_summary": "XLI: 60-day return history, mean=0.0000, std=0.0138.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0000, std=0.0138, min=-0.0336, max=0.0303\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-10-19] Equifax (EFX) to Report Q3 Earnings: What's in the Cards? Equifax Inc. EFX is scheduled to report third-quarter 2015 results on Oct 21. Last quarter, the company posted a positive earnings surprise of 4.55%. Let's see how things are shaping up for this announcement. Factors to Consider Equifax reported better-than-expected second-quarter 2015 results, which improved year over year as well. The year-over-year upside was supported by revenue growth across all its business segments, except International. Recently, Equifax made a non-binding offer to acquire Veda Group Limited, the leading Australian credit information provider, to broaden its global operations. If successful, this would be Equifax's biggest acquisition surpassing the $1 billion CSC Credit Services buyout in 2012. We believe that the recent move will give Equifax a substantial foothold in the country. Management's efforts such as strategic initiatives for product innovation, expansion of data assets through acquisitions and continuous share gains in North America raise optimism. Also, the company's strong correlation with the consumer and financial markets as well as its exposure in the U.S. and Europe are likely to propel growth, going ahead. However, competition from the likes of Automatic Data Processing Inc. ADP , Fiserv Inc., Moody's Corp. and uncertainty in the mortgage sector raise concern. Earnings Whispers Our proven model does not conclusively show that Equifax is likely to beat earnings estimates this quarter. This is because a stock needs to have both a positive Earnings ESP and a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold) for this to happen. This is not the case here, as you will see below. Zacks ESP: ESP for Equifax is 0.00% since the Most Accurate estimate of $1.10 per share stands in line with the Zacks Consensus Estimate. Zacks Rank: Equifax's Zacks Rank #2 when combined with a 0.00% ESP makes surprise prediction difficult. We caution against stocks with Zacks Rank #4 or 5 (Sell-rated stocks) going into the earnings announcement, especially when the company is seeing negative estimate revisions. Stocks to Consider Here are some other companies, which you may consider as our model shows that they have the right combination of elements to post an earnings beat this quarter: Fiserv, Inc. FISV with Earnings ESP of +3.09% and a Zacks Rank #2 Apple Inc. AAPL with Earnings ESP of +1.60% and a Zacks Rank #3 (Hold) 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 >> 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 EQUIFAX INC (EFX): Free Stock Analysis Report AUTOMATIC DATA (ADP): Free Stock Analysis Report FISERV INC (FISV): Free Stock Analysis Report APPLE INC (AAPL): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Researc\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": "-0.0226", "answer_numeric": -0.022567, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0226 (i.e., on a bad day with 5% probability, the loss exceeds 2.26%). CVaR(95%) = -0.0295.", "metadata": {"var": -0.022567, "cvar": -0.029473, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200427_0904", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2020-04-27", "context_summary": "ICSH: 60-day return history, mean=0.0003, std=0.0034.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0003, std=0.0034, min=-0.0147, max=0.0092\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": "-0.0057", "answer_numeric": -0.005695, "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%) = -0.0105.", "metadata": {"var": -0.005695, "cvar": -0.010498, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220215_0906", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-02-15", "context_summary": "ETH-USD: 60-day return history, mean=-0.0042, std=0.0387.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0042, std=0.0387, min=-0.1477, max=0.1136\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-02-14] \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": "-0.0599", "answer_numeric": -0.059942, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0599 (i.e., on a bad day with 5% probability, the loss exceeds 5.99%). CVaR(95%) = -0.0926.", "metadata": {"var": -0.059942, "cvar": -0.092592, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20161228_0908", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-12-28", "context_summary": "QQQ: 60-day return history, mean=0.0003, std=0.0075.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0003, std=0.0075, min=-0.0174, max=0.0235\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-12-27] The Zacks Analyst Blog Highlights: IBM, BP, Disney, Adobe and Cisco For Immediate Release Chicago, IL - December 27, 2016 - 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 IBM (NYSE: IBM - Free Report ), BP (NYSE: BP - Free Report ), Disney (NYSE: DIS - Free Report ), Adobe (NASDAQ: ADBE - Free Report ) and Cisco (NASDAQ: CSCO - Free Report ). Today, Zacks is promoting its ''Buy'' stock recommendations. Get #1Stock of the Day pick for free. Here are highlights from Friday's Analyst Blog: Stock Research Reports for Tuesday: IBM, BP, DIS Today's Research Daily features new research reports on 16 major stocks, including IBM (NYSE: IBM - Free Report ), BP (NYSE: BP - Free Report ) and Disney (NYSE: DIS - Free Report ). IBM shares lagged the technology space and the S&P 500 index over the last few years as the company struggled to reposition its business to the evolving business landscape. But the stock turned around this year (up +21.4% in the year-to-date period vs. +9.3% for the Zacks Technology sector) on greater appreciation for the company's outlook. The Zacks analyst likes IBM's strategic growth initiatives, including its Big Data & business analytics, cloud computing, mobile and social business. The company is expected to report Q4 results on January 17th. (You can read the full research report on IBM here >>> ) The turnaround in oil prices this year has benefited all oil players, BP included. BP shares have gained in excess of +18% this year, modestly below the Zacks Oil Integrated industry's +19.1% gain. The Zacks analyst likes the company's major expense reductions over the last four quarters, which is expected to remain a focus in the coming quarters as well. BP is scheduled to report Q4 results on February 7th, with the oil giant expected to report $0.50 per share on $52.2 billion in revenues. While upstream volumes are expected to be modestly up from the Q3 level, the refining business could be under pressure. (You can read the full research report on BP here >>> ) Disney shares have struggled this year, weighed down by concerns about ESPN whose future growth has been clouded by the evolving media landscape as a result of 'cord cutting' and the steady migration of subscribers to online and digital platforms. However, management anticipates reporting modest earnings growth in fiscal 2017 and a \"more robust growth\" in fiscal 2018. The Zacks analyst likes Disney's movie business and the parks & resorts division. The company is expected to report Q4 results on February 14th. (You can read the full research report on Disney here >>> ) Other noteworthy reports we are featuring today include Adobe (NASDAQ: ADBE - Free Report ) and Cisco (NASDAQ: CSCO - Free Report ). You can check all of today's research reports here >>> Today's Long-Term Buys & Sells Today \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": "-0.0123", "answer_numeric": -0.01229, "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%) = -0.0160.", "metadata": {"var": -0.01229, "cvar": -0.016024, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20150814_0910", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2015-08-14", "context_summary": "XLF: 60-day return history, mean=0.0001, std=0.0082.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0001, std=0.0082, min=-0.0244, max=0.0152\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-08-13] [\"Earnings Scheduled For August 13, 2015\", \"10 Stocks You Should Be Watching Today\", \"Option Alert: Applied Materials Sep $18 Call; 2000 Contracts @Ask @$0.32; Now $17.04\", \"Applied Materials Reports Q3 Adj. EPS $0.33, Inline, Sales $2.49B vs $2.54B Est.\", \"Applied Materials Expecting Q4 Adj. EPS $0.27-$0.31 vs $0.33 Est.\", \"UPDATE: Applied Materials Sees Q4 Sales Down 7% to Flat QoQ\", \"Nordstrom, El Pollo LoCo, King Digital Lead Thursday's After-Hours\", \"Applied Materials Posts In-Line Q3 Earnings, But Sales Miss Estimates\", \"Applied Materials Posts In-Line Q3 Earnings, But Sales Miss Estimates\", \"Nordstrom, El Pollo LoCo, King Digital Lead Thursday's After-Hours\", \"UPDATE: Applied Materials Sees Q4 Sales Down 7% to Flat QoQ\", \"Applied Materials Expecting Q4 Adj. EPS $0.27-$0.31 vs $0.33 Est.\", \"Applied Materials Reports Q3 Adj. EPS $0.33, Inline, Sales $2.49B vs $2.54B Est.\", \"Option Alert: Applied Materials Sep $18 Call; 2000 Contracts @Ask @$0.32; Now $17.04\", \"10 Stocks You Should Be Watching Today\", \"Earnings Scheduled For August 13, 2015\", \"Interesting AMAT Put And Call Options For October 2nd Investors in Applied Materials, Inc. (Symbol: AMAT) saw new options begin trading today, for the October 2nd expiration. At Stock Options Channel , our YieldBoost formula has looked up and down the AMAT options chain for the new October 2nd contracts and identified one put and one call contract of particular interest. The put contract at the $17.00 strike price has a current bid of 68 cents. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $17.00, but will also collect the premium, putting the cost basis of the shares at $16.32 (before broker commissions). To an investor already interested in purchasing shares of AMAT, that could represent an attractive alternative to paying $17.17/share today. Because the $17.00 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 55%. 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 4.00% return on the cash commitment, or 29.20% annualized - at Stock Options Channel we call this the YieldBoost . Below is a chart showing the trailing twelve month trading history for Applied Materials, Inc., and highlighting in green where the $17.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $17.50 strike price has a current bid of 55 cents. If an investor was to purchase shares of AMAT stock at the current price level of $17.17/share, and\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": "-0.0116", "answer_numeric": -0.011602, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0116 (i.e., on a bad day with 5% probability, the loss exceeds 1.16%). CVaR(95%) = -0.0196.", "metadata": {"var": -0.011602, "cvar": -0.019626, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20200603_0912", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2020-06-03", "context_summary": "IYR: 60-day return history, mean=0.0001, std=0.0239.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0001, std=0.0239, min=-0.0339, 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": "-0.0339", "answer_numeric": -0.033943, "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%) = -0.0339.", "metadata": {"var": -0.033943, "cvar": -0.033943, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20171120_0914", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2017-11-20", "context_summary": "BTC-USD: 60-day return history, mean=0.0127, std=0.0417.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0127, std=0.0417, min=-0.0736, max=0.1157\nMarket regime: sideways\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": "-0.0643", "answer_numeric": -0.0643, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0643 (i.e., on a bad day with 5% probability, the loss exceeds 6.43%). CVaR(95%) = -0.0707.", "metadata": {"var": -0.0643, "cvar": -0.070669, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180807_0916", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2018-08-07", "context_summary": "EWJ: 60-day return history, mean=-0.0006, std=0.0062.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=-0.0006, std=0.0062, min=-0.0160, max=0.0137\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-08-06] [\"Zacks.com highlights: Mellanox Technologies, Fortinet, Commvault Systems and Adobe Systems For Immediate Release Chicago, IL - August 6, 2018 - Stocks in this week's article include: Mellanox Technologies Ltd. MLNX , Fortinet Inc. FTNT , Commvault Systems, Inc. CVLT and Adobe Systems Inc. ADBE . Screen of the Week of Zacks Investment Research: Bet on These 4 Liquid Stocks for Solid Returns The liquidity of a stock is an important yardstick that many investors tend to ignore. It primarily indicates a company's capability to meet debt obligations by converting its assets into liquid cash and equivalents. Liquid stocks have always been in demand due to their potential to provide maximum returns. However, one should exercise caution before investing in such stocks. While a high liquidity level may imply that the company is meeting its obligations at a faster rate than its peers, it may also indicate that the company is failing to use its assets efficiently. Hence, one should consider the efficiency level of a company in addition to its liquidity to identify potential winners as this combination is indicative of underlying financial strength. Measures to Identify Liquid Stocks Current Ratio : It measures current assets relative to current liabilities. This ratio is used for measuring a company's potential to meet both short- and long-term debt obligations. Thus, a current ratio - also known as working capital ratio - below 1 indicates that the company has more liabilities than assets. However, a high current ratio does not always indicate that the company is in good financial shape. It may also mean that the company has failed to utilize its assets significantly. Hence, a range of 1 to 3 is considered ideal. Quick Ratio: Unlike current ratio, quick ratio - also called \\\"acid-test ratio\\\" or \\\"quick assets ratio\\\" - indicates a company's ability to pay short-term obligations. It considers inventory excluding current assets relative to current liabilities. Like the current ratio, a quick ratio of greater than 1 is desirable. Cash Ratio: This is the most conservative ratio among the three, as it takes into account only cash and cash equivalents, and invested funds relative to current liabilities. It measures a company's ability to meet its current debt obligations using the most liquid of assets. Though a cash ratio of more than 1 may point to sound financials, a higher number may indicate inefficiency in cash utilization. So, a ratio greater than 1 is desirable at all times but may not always appropriately represent a company's financial condition. And that's what we're screening for today\\u2026 For the rest of this Screen of the Week article please visit Zacks.com at:https://www.zacks.com/stock/news/297774/bet-on-these-4-liquid-stocks-for-solid-returns Get the remaining stocks on the list and start putting this and other ideas to the test. It can all be done with the Research Wizard stock picking and back testing software. The Research Wizard is a gr\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": "-0.0108", "answer_numeric": -0.01081, "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%) = -0.0145.", "metadata": {"var": -0.01081, "cvar": -0.014546, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220606_0918", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2022-06-06", "context_summary": "EFA: 60-day return history, mean=-0.0002, std=0.0131.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=-0.0002, std=0.0131, min=-0.0289, max=0.0259\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-03] [\"Apple Was the Worst Stock in the Dow Friday The Dow Jones Industrial Average dropped close to 350 points on Friday, despite a better-than-expected jobs report. For the week, however, the Dow Jones finished higher by nearly 165 points as volatile trading continued. No stock in the Dow saw a bigger percentage drop than Apple (NASDAQ: AAPL), which fell nearly 4% today after several analysts warned about slowing App Store revenue growth. Intel (NASDAQ: INTC) was the day's second-biggest loser on a percentage basis, finishing the day more than 3% down. Although ADP reported yesterday that private payrolls in May added the smallest number of new jobs since the COVID-19 recovery began, the U.S. Bureau of Labor Statistics reported today that nonfarm payrolls added 390,000 jobs last month. That was much stronger than the 328,000 jobs that most economists had been expecting. The conflicting data is nothing new, as investors struggle to try and figure out where the economy could land over the next six to 18 months. Slowing App Store growth at Apple Morgan Stanley analyst Katy Huberty warned today that App Store revenue growth may have started to slow in May, hinting that services revenue at Apple could come in weaker for the current quarter than many had initially thought. Huberty pointed to data from a company called Sensor Tower that showed just 4% revenue growth in May on a year-over-year basis. \\\"While we believe Apple user spending is more resilient at all stages of the economic cycle, which positions Apple better than other consumer hardware peers, a deceleration in App Store growth likely points to fading consumer spending on goods/services that accelerated during the pandemic,\\\" Huberty wrote in a research note. Image source: Getty Images. App Store revenue is a big component of the company's services revenue, which made up more than 20% of net sales in the tech giant's most recent quarter. Huberty projects that App Store revenue could fall by as much as $560 million from her initial forecast, which could hit her services revenue forecast for the current quarter by more than 3%. Huberty's note is the second warning this week from analysts. Evercore analyst Amit Daryanani also noted yesterday that the 4% growth is weaker than the 9% year-over-year App Store revenue growth Apple saw in April. \\\"We had expected growth to accelerate as comps became easier, so the slowdown is somewhat surprising, especially as China saw a large deceleration when we were anticipating some uplift from the ongoing lockdowns,\\\" Daryanani wrote in a research note. Still, even though App Store revenue growth might be slowing, both Huberty and Daryanani are bullish on the stock. Huberty has an \\\"overweight\\\" rating on Apple and a price target of $195. Daryanani also has an \\\"overweight\\\" rating and price target of $210. Apple closed the day at $145 per share, implying substantial upside to both of the analysts' price targets. Why Apple could bounce back The analysts are right\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": "-0.0244", "answer_numeric": -0.024364, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0244 (i.e., on a bad day with 5% probability, the loss exceeds 2.44%). CVaR(95%) = -0.0287.", "metadata": {"var": -0.024364, "cvar": -0.028716, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20191211_0920", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2019-12-11", "context_summary": "IWM: 60-day return history, mean=0.0005, std=0.0078.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0005, std=0.0078, min=-0.0198, max=0.0210\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-10] Beware the Valuation Risks of Red-Hot DocuSign Stock E-signature pioneer DocuSign (NASDAQ:) delivered strong third-quarter earnings in early December. In response, DOCU stock rallied to all-time highs. Source: Sundry Photography / Shutterstock.com Everything in the report looked great. The company\u2019s customer growth was robust, as more and more businesses around the globe start to digitize and automate their contracts. The company\u2019s revenue growth was even more robust, as DocuSign\u2019s \u201cfoot in the door and grow\u201d model is working, and current customers are spending more on DocuSign\u2019s suite of Cloud Agreement products. Its gross margins held steady at an impressive 80%, while its strong revenue growth increased its profitability. As a result, its third-quarter profit was sizable, versus its tiny profit during the same period a year earlier. On top of all that, the company provided healthy Q4 guidance which indicated that all of these positive dynamics will persist into the end of the year. In other words, the 7% pop of DOCU stock after the Q3 results made sense, right? After all, its numbers were great, its growth outlook is healthy, and all signs point to \u201cGO\u201d\u2026 right? Wrong. While DocuSign is a great company and DOCU stock is a long-term winner, there is one big red flag now which warrants caution. That red flag is the valuation of DocuSign stock. I understand DOCU is a growth company that deserves a premium valuation. But, even aggressively assuming that the company will grow rapidly for the next decade, it\u2019s still tough to justify the current price of DOCU stock. As a result, I think DOCU stock is riddled with valuation risks. The stock may brush off those risks in the near-term, thanks to the momentum from its earnings. But, at some point, these risks will rear their ugly head. DocuSign Is a Great Company To be clear, I think DocuSign is a great company. The whole growth outlook of DocuSign centers around the digitization and automation of the contract process. That is, the traditional contract process involves a ton of paper (which is bulky and sometimes costly) and requires that paper to be sent back and forth between various parties multiple times In other words, the traditional contractual process is antiquated, lengthy, and costly. DocuSign fixes all those problems by digitizing and automating the contract process. Among other things, it makes all the documents and the signing process digital, eliminating all the paper involved in those processes. DOCU also transforms the transit, record-keeping, and enforcement of contracts into digital processes. It basically makes the whole contractual process digital, causing it to become modern, fast, and affordable. For corporations, that\u2019s a good deal. That\u2019s why DocuSign has grown its enterprise and commercial customer base from 23,000 in 2015 to what will be north of 70,000 by the end of 2019. Still, at 70,000, DocuSign\u2019s customer base pales in comparison to the millions of businesses in the world, s\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": "-0.0114", "answer_numeric": -0.011424, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0114 (i.e., on a bad day with 5% probability, the loss exceeds 1.14%). CVaR(95%) = -0.0171.", "metadata": {"var": -0.011424, "cvar": -0.017139, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20161012_0922", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2016-10-12", "context_summary": "DBB: 60-day return history, mean=0.0001, std=0.0077.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=0.0001, std=0.0077, min=-0.0165, max=0.0204\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": "-0.0138", "answer_numeric": -0.013809, "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%) = -0.0150.", "metadata": {"var": -0.013809, "cvar": -0.015022, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181106_0924", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-11-06", "context_summary": "XRP-USD: 60-day return history, mean=0.0100, std=0.0727.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0100, std=0.0727, min=-0.1714, max=0.3257\nMarket regime: sideways\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": "-0.0615", "answer_numeric": -0.061463, "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%) = -0.1337.", "metadata": {"var": -0.061463, "cvar": -0.133678, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180330_0926", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2018-03-30", "context_summary": "IAU: 60-day return history, mean=0.0002, std=0.0072.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=0.0002, std=0.0072, min=-0.0139, max=0.0175\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": "-0.0125", "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%) = -0.0136.", "metadata": {"var": -0.012484, "cvar": -0.01365, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20160426_0929", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2016-04-26", "context_summary": "FXI: 60-day return history, mean=0.0019, std=0.0169.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0019, std=0.0169, min=-0.0259, max=0.0411\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-04-25] [\"3 Things Not To Like About Sony Apple (AAPL) camera components supplier Sony Corp. (6758.Japan/SNE) tumbled 6.3% today after the electronics maker said it would postpone its financial forecasts for the current fiscal year while assessing the damage from recent earthquakes that shut down its camera plants.Sony's stock faces 3 near-term headwinds, according to Citi Research's Kota Ezawa.READ MORE.\", \"Three Chip Stocks to be Wary of This Earnings Season Micron Technology has structural issues. Nvidia and Silicon Labs look overvalued on limited earnings upside.\", \"Don\\u2019t have Tidal? Beyonc\\u00e9\\u2019s \\u2018Lemonade\\u2019 coming to Apple\\u2019s iTunes Album headed for wide release after just 24 hours of exclusivity on Tidal Beyonc\\u00e9\\u2019s new album, \\u201cLemonade,\\u201d is expected to be released to the masses Sunday night, just 24 hours after its exclusive debut on the Tidal streaming service.\", \"\\u2018The efficient market is dead today just as sound banking died in 1999\\u2019 Critical intelligence before the U.S. market opens A mere 38% of money managers in Barron\\u2019s latest Big Money poll are bullish about the state of all things market. And this is a group, in general, that tends to put a smile on everything. At least for the clients they\\u2019re perpetually trying to woo.\", \"The market in a minute: Fed's tone, words will matter more than action While we agree that the Fed is unlikely to raise rates this go around, we believe that the risks are in what Chairwoman Yellen says, not what the committee does. So far, Dr. Yellen has been on the Dovish side, a trend that is sure to end at some point.\", \"Snapchat Must Be Reckoned With, Says SunTrust; Use Surpasses Twitter SunTrust Robinson Humphrey\\u2019s Robert Peck, who covers Facebook (FB), Twitter (TWTR) and other Internet stocks, today takes a deep dive into \\u201cThe Rise of Snapchat,\\u201d arguing of the privately held messaging service that \\\"digital media investors must pay attention to it for several reasons.\\\"Those reasons include the fact that it\\u2019s growing fast, it\\u2019s taking users away from other social media, and it\\u2019s also luring away advertisers and software talent.Digital media history is littered with companies that had early leads that eroded as new, innovative companies entered the industry (Friendster, MySpace, Yahoo, Alta Vista, etc). We are not proclaiming that Snapchat will unseat other digital media properties; however, it is paramount that digital media investors and the industry are mindful of Snapchat. This report is the first in a series of Snapchat reports that will aim to help investors understand Snapchat and its potential impact. It is important to understand that there is very limited publicly available information on Snapchat and we look forward to any feedback from the industry and investors, making the topic a living discussion.\", \"Goldman Ups Tesla Target, Potential For \\u2018Disruptive\\u2019 iPhone-Like Upside Goldman Sachs took a closer \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": "-0.0229", "answer_numeric": -0.02289, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0229 (i.e., on a bad day with 5% probability, the loss exceeds 2.29%). CVaR(95%) = -0.0248.", "metadata": {"var": -0.02289, "cvar": -0.024789, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20211027_0931", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2021-10-27", "context_summary": "BNB-USD: 60-day return history, mean=0.0004, std=0.0448.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0004, std=0.0448, min=-0.1581, max=0.1050\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-19] \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": "-0.0601", "answer_numeric": -0.060149, "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%) = -0.1154.", "metadata": {"var": -0.060149, "cvar": -0.115413, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20180517_0933", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2018-05-17", "context_summary": "XLB: 60-day return history, mean=-0.0001, std=0.0123.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0001, std=0.0123, min=-0.0303, max=0.0204\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-05-16] [\"Q1 13F Roundup: How Buffett, Einhorn, Ackman And Others Adjusted Their Portfolio\", \"Q1 13F Roundup: How Buffett, Einhorn, Ackman And Others Adjusted Their Portfolio\", \"25 Unstoppable Stocks to Buy No Matter What InvestorPlace - Stock Market News, Stock Advice & Trading Tips There is a lot of noise in the stock market. Every day, discrete events send stocks up and down. These discrete events can be company-specific, like earnings reports, murmurs about mergers and acquisitions, analyst upgrades and downgrades, or investor presentations. Those discrete events can also be macro-related, including economic data or geopolitical news. Nonetheless, every day, multiple events happen, causing the stock market volatility that we've been seeing from day to day. Day traders would be wise to continue paying attention to each and every crackle of noise in this market. Long-term investors, however, will find it in their best interest to ignore that noise. 30 Marijuana Stocks to Buy as the Future Turns Green With that in mind, here is a list of 25 stocks that should, regardless of near-term noise, head significantly higher over the next several years due to secular growth tailwinds. Unstoppable Stocks to Buy No Matter What: Apple Inc. (AAPL) Source: Yuanbin Du Via Flickr It is only fitting that this list starts with the biggest publicly traded company in the world, Apple Inc (NASDAQ: AAPL ). Apple got to this point ($930 billion market cap) by selling the world a ton of iPhones, iPads and Mac computers. But that business is drying up. Everyone who wants an iPhone, iPad or Mac already has one, so there aren't really any new buyers in the market. Instead, Apple just gets the upgrade buyers every year. Bears think this is a problem. But it's not. Apple is shifting from consumer technology company to software technology company. Through various software services like iCloud, Apple Music, Apple Pay and the App Store, Apple is starting to monetize its massive iOS ecosystem. These software revenues are higher margin than the hardware revenues, and they are also more predictable (most of the money comes from subscriptions), so Apple is actually turning into a company with higher margins and more predictable revenue streams. As this transformation plays out over the next several years, AAPL stock will head higher. The stock is pretty cheap on its face, trading at just 16-times forward earnings, and there is a bunch of cash on the balance sheet that will be weaponized over the next several years in the form of dividends, buybacks and acquisitions. Unstoppable Stocks to Buy No Matter What: Axon Enterprise Inc (AAXN) Source: Axon Although it is lesser known than Apple, Axon Enterprise Inc (NASDAQ: AAXN ) is undergoing a similar transition from largely a hardware company to a software and hardware company. Axon was formerly known as Taser International, and the business used to be selling tasers and other smart weapons to law enforcement agencies around the world. While se\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": "-0.0221", "answer_numeric": -0.022149, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0221 (i.e., on a bad day with 5% probability, the loss exceeds 2.21%). CVaR(95%) = -0.0275.", "metadata": {"var": -0.022149, "cvar": -0.02746, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180709_0935", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2018-07-09", "context_summary": "ETH-USD: 60-day return history, mean=-0.0061, std=0.0450.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0061, std=0.0450, min=-0.1190, max=0.0956\nMarket regime: sideways\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": "-0.0989", "answer_numeric": -0.098899, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0989 (i.e., on a bad day with 5% probability, the loss exceeds 9.89%). CVaR(95%) = -0.1116.", "metadata": {"var": -0.098899, "cvar": -0.111571, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181205_0937", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2018-12-05", "context_summary": "BIL: 60-day return history, mean=0.0001, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0001, std=0.0001, min=-0.0001, max=0.0003\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": "-0.0001", "answer_numeric": -0.000109, "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%) = -0.0001.", "metadata": {"var": -0.000109, "cvar": -0.000109, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210112_0940", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2021-01-12", "context_summary": "TIP: 60-day return history, mean=0.0002, std=0.0006.", "question": "Asset: TIP\nDaily returns (past 60 days): mean=0.0002, std=0.0006, min=-0.0013, max=0.0018\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": "-0.0008", "answer_numeric": -0.00077, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0008 (i.e., on a bad day with 5% probability, the loss exceeds 0.08%). CVaR(95%) = -0.0011.", "metadata": {"var": -0.00077, "cvar": -0.001063, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190705_0942", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLT"], "decision_date": "2019-07-05", "context_summary": "TLT: 60-day return history, mean=0.0016, std=0.0055.", "question": "Asset: TLT\nDaily returns (past 60 days): mean=0.0016, std=0.0055, min=-0.0114, max=0.0125\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for TLT. Express as a decimal (e.g., -0.02).", "answer": "-0.0072", "answer_numeric": -0.007238, "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%) = -0.0106.", "metadata": {"var": -0.007238, "cvar": -0.0106, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20150507_0944", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2015-05-07", "context_summary": "PALL: 60-day return history, mean=0.0007, std=0.0136.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=0.0007, std=0.0136, min=-0.0382, max=0.0290\nMarket regime: sideways\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": "-0.0217", "answer_numeric": -0.021682, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0217 (i.e., on a bad day with 5% probability, the loss exceeds 2.17%). CVaR(95%) = -0.0296.", "metadata": {"var": -0.021682, "cvar": -0.029604, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180214_0946", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2018-02-14", "context_summary": "VTI: 60-day return history, mean=0.0008, std=0.0088.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0008, std=0.0088, min=-0.0335, max=0.0162\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-02-13] [\"Google\\u2019s new AMP mobile story telling models Snapchat and Instagram Format doesn\\u2019t support advertising yet, which could slow its adoption among publishers Alphabet Inc.\\u2019s Google unveiled new technology that lets publishers create visual-oriented stories in a mobile-friendly format similar to the style popularized by Snapchat and Instagram.\", \"Apple services, watch businesses could be 'meaningful drivers' by 2020: analyst Instinet analyst Jeffrey Kvaal wrote Tuesday that he sees \\\"new drivers brewing\\\" for Apple Inc. , even as iPhone X demand seems to be falling short of the company's initial expectations. In a note to clients, Kvaal argued that the \\\"era of supercycle may be over,\\\" but he's optimistic about the potential for secondhand phone sales to continue growing the company's installed base. He noted that Apple's base did in fact grow during the latest quarter, which to him \\\"implies services - and perhaps the Watch - can emerge as meaningful drivers by ~2020.\\\" Kvaal believes that the services business could account for more than a third of the company's overall gross profit dollars by 2020. Still, he kept his neutral rating on the stock. Apple shares are down 0.2% in Tuesday morning trading and up 22% over the past 12 months. The Dow Jones Industrial Average has gained 20% in that time.\", \"Apple: Will Annual Meeting Bring Insight on Capital Plans? Apple's annual shareholder meeting takes place today at its Cupertino, California headquarters, with lots of unknowns about the company's exact plans for investment in the U.S. of hundreds of billions of dollars, and for its intentions for its capital returns programs. It's unlikely the company will shed any light, but that doesn't stop the Street from wondering about it.\", \"Don\\u2019t make big investing decisions until Feb. 14 No, it\\u2019s not due to Valentine\\u2019s Day; that\\u2019s when the all-important inflation report is released No, it\\u2019s not due to Valentine\\u2019s Day; that\\u2019s when the all-important inflation report is released. By Nigam Arora.\", \"Apple CEO: Special dividend for $285 billion in overseas cash unlikely Apple Inc. Chief Executive Tim Cook said Tuesday at the company's annual shareholder meeting that a special dividend is unlikely as Apple looks to spend $285 billion stashed overseas, according to a report. \\\"Special dividends, I'm not really a fan of,\\\" Cook said in response to a question, Reuters reported Tuesday. \\\"But in terms of annual increases in the dividend, it is something that this board and management are committed to doing.\\\" Apple stock is up less than 1% to $163.89 in afternoon trading. Cook said executives would update shareholders on the company's capital return program on its April earnings call. Apple stock has gained 23% in the past 12 months, as the S&P 500 index rose 14%. The Dow Jones Industrial Average , of which Apple is a component, has gained 21% in the past year.\", \"Will Apple\\u2019s New HomePod Soon Dominate Hi-fi Profi\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": "-0.0110", "answer_numeric": -0.011024, "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%) = -0.0295.", "metadata": {"var": -0.011024, "cvar": -0.029469, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20191028_0948", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2019-10-28", "context_summary": "VNQI: 60-day return history, mean=0.0010, std=0.0071.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=0.0010, std=0.0071, min=-0.0251, max=0.0199\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": "-0.0087", "answer_numeric": -0.00869, "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%) = -0.0171.", "metadata": {"var": -0.00869, "cvar": -0.017082, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20190204_0950", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2019-02-04", "context_summary": "SHV: 60-day return history, mean=0.0001, std=0.0001.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0001, std=0.0001, min=-0.0002, 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": "-0.0001", "answer_numeric": -9.1e-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%) = -0.0002.", "metadata": {"var": -9.1e-05, "cvar": -0.000151, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210416_0953", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2021-04-16", "context_summary": "BNO: 60-day return history, mean=0.0043, std=0.0229.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=0.0043, std=0.0229, min=-0.0619, max=0.0542\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": "-0.0354", "answer_numeric": -0.03539, "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%) = -0.0518.", "metadata": {"var": -0.03539, "cvar": -0.051802, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20191216_0955", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2019-12-16", "context_summary": "XLU: 60-day return history, mean=-0.0001, std=0.0063.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0001, std=0.0063, min=-0.0138, max=0.0147\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-13] [\"5 Stocks To Watch For December 13, 2019\", \"A Peek Into The Markets: US Stock Futures Climb Ahead Of Economic Reports\", \"20 Stocks Moving in Friday's Pre-Market Session\", \"Credit Suisse Reiterates Outperform on Adobe, Raises Price Target to $350\", \"Wells Fargo Reiterates Equal-Weight on Adobe, Raises Price Target to $315\", \"Barclays Maintains Overweight on Adobe, Raises Price Target to $350\", \"Adobe shares are trading higher after the company reported better-than-expected Q4 EPS and sales results.\", \"PiperJaffray Maintains Overweight on Adobe, Raises Price Target to $360\", \"Wedbush Maintains Neutral on Adobe, Raises Price Target to $315\", \"Stifel Maintains Buy on Adobe, Raises Price Target to $350\", \"10 Biggest Price Target Changes For Friday\", \"Adobe Did Good \\u2013 And Stock Is Headed To A Record High\", \"Nomura Maintains Buy on Adobe, Raises Price Target to $318\", \"Stifel Nicolaus Maintains Buy on Adobe, Raises Price Target to $350\", \"Canaccord Genuity Maintains Buy on Adobe, Raises Price Target to $350\", \"UPDATE: Credit Suisse Maintains Outperform On Adobe, Raises Target To $350 Notes 'While some may harp on the F1Q20 guide, we believe the outperformance in F4Q19 and reiteration of FY20 net new ARR likely signals upside to Digital Media'\", \"Mid-Morning Market Update: Markets Mixed; Adobe Earnings Beat Estimates\", \"Stocks That Hit 52-Week Highs On Friday\", \"UPDATE: Wells Fargo Maintains Outperform On Adobe, Raises Target To $315 As Firm Believes Believes The Stock's Current Valuation Reflects Co's 'successful transition to subscription and ability to increase its total addressable market'\", \"UPDATE: Nomura Maintains Buy On Adobe, Raises Target To $318 Notes 'After underwhelming bookings momentum around both Marketo (mid-market) and Analytics Cloud subscriptions in 3Q, things seem to have gained some positive traction in the quarter'\", \"36 Stocks Moving In Friday's Mid-Day Session\", \"Mid-Day Market Update: Crude Oil Rises Over 1%; Sarepta Therapeutics Shares Spike Higher\", \"The Street Reviews Adobe's 2019: 'Record Year'\", \"The Street Reviews Adobe's 2019: 'Record Year'\", \"Mid-Day Market Update: Crude Oil Rises Over 1%; Sarepta Therapeutics Shares Spike Higher\", \"36 Stocks Moving In Friday's Mid-Day Session\", \"UPDATE: Nomura Maintains Buy On Adobe, Raises Target To $318 Notes 'After underwhelming bookings momentum around both Marketo (mid-market) and Analytics Cloud subscriptions in 3Q, things seem to have gained some positive traction in the quarter'\", \"UPDATE: Wells Fargo Maintains Outperform On Adobe, Raises Target To $315 As Firm Believes Believes The Stock's Current Valuation Reflects Co's 'successful transition to subscription and ability to increase its total addressable market'\", \"Stocks That Hit 52-Week Highs On Friday\", \"Mid-Morning Market Update: Markets Mixed; Adobe Earnings Beat Estimates\", \"UPDATE: Credit Suisse Maintains Outperform On Adobe, Raises Target To $350 Notes 'While some may harp on the F1Q20 guide, we believe the outper\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": "-0.0129", "answer_numeric": -0.012903, "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%) = -0.0136.", "metadata": {"var": -0.012903, "cvar": -0.01361, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20210726_0957", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SLV"], "decision_date": "2021-07-26", "context_summary": "SLV: 60-day return history, mean=0.0000, std=0.0143.", "question": "Asset: SLV\nDaily returns (past 60 days): mean=0.0000, std=0.0143, min=-0.0452, max=0.0396\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SLV. Express as a decimal (e.g., -0.02).", "answer": "-0.0227", "answer_numeric": -0.022716, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0227 (i.e., on a bad day with 5% probability, the loss exceeds 2.27%). CVaR(95%) = -0.0322.", "metadata": {"var": -0.022716, "cvar": -0.032213, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220524_0959", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LQD"], "decision_date": "2022-05-24", "context_summary": "LQD: 60-day return history, mean=-0.0017, std=0.0073.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=-0.0017, std=0.0073, min=-0.0133, max=0.0111\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": "-0.0133", "answer_numeric": -0.013325, "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%) = -0.0133.", "metadata": {"var": -0.013325, "cvar": -0.013325, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180202_0961", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2018-02-02", "context_summary": "USMV: 60-day return history, mean=0.0010, std=0.0038.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0010, std=0.0038, min=-0.0076, max=0.0093\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-02-01] [\"Apple declines in late trading on iPhone supplier concerns Apple Inc. shares fell in late trading Wednesday after chip supplier Qualcomm Inc. reported that a large customer pared orders more than expected in the quarter. Qualcomm, which reported earnings Wednesday afternoon, supplies modems to Apple for its iPhones, and the information was believed to be a signal that Apple curtailed iPhone production earlier than expected. As Bloomberg News noted, another Apple component supplier, Broadcom Ltd. , made a similar disclosure in its own earnings report earlier Wednesday. Apple stock declined about 0.5% in after-hours action; the company is scheduled to reveal initial iPhone X sales in an earnings report Thursday afternoon.\", \"Asian markets mostly rise on brighter economic data Nikkei up 1.2% after 6 days of declines; stocks in China sink Some Asian stock markets rebounded after the broad pullback that started the week, but Chinese equities weakened again following another muted manufacturing reading, weighing on Hong Kong stocks.\", \"Qualcomm shores up licensing with expanded Samsung deal Charges related to licensing bit into Qualcomm profit The agreement with Samsung, which allows the two companies to share patents, doesn\\u2019t bear on the deals Qualcomm uses to license intellectual property for its smartphone chips, which are facing legal challenges by Apple and regulators.\", \"Apple earnings: Forget taxes and batteries, the $1,000 iPhone X remains the story Apple expected to post record sales for the holiday quarter, despite iPhone X shortages, thanks to high price tag Apple has generated attention for its comments on taxes and batteries, but investors will focus mostly on iPhone sales when the company reports earnings Feb. 1\", \"Qualcomm earnings show weak forecast amid massive fines, tax charge Tax law change, fines sock Qualcomm with $6 billion quarterly loss Qualcomm Inc. managed to beat expectations with its earnings Wednesday, but the chip maker\\u2019s outlook came up short and caused some concerns about Apple Inc.\\u2019s iPhone sales.\", \"The Amazon chart you may not want to see, but probably should Critical information for the U.S. trading day It\\u2019s a huge earnings day and investors will be scrambling to keep up. Our chart of the day offers food for thought for one of those big companies \\u2014 Amazon, while the chart of the day says don\\u2019t bail on stocks now.\", \"Facebook earnings send stock to record after massive ad price increase Average price for Facebook ads jumped 43% in fourth quarter Facebook Inc. shares reversed course to show gains in late trading Wednesday after the company reported double-digit advertising price growth amid massive changes to its core product.\", \"Apple Earnings: Hand-Wringing\\u2019s Silver Lining? Apple's quarterly report Thursday night finally brings the Street face to face with the numbers they've been obsessing about: How bad will the outlook be for the March quarter's iPhone units? There just has to\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": "-0.0056", "answer_numeric": -0.005648, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0056 (i.e., on a bad day with 5% probability, the loss exceeds 0.56%). CVaR(95%) = -0.0067.", "metadata": {"var": -0.005648, "cvar": -0.006747, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20170517_0963", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2017-05-17", "context_summary": "XLU: 60-day return history, mean=0.0008, std=0.0063.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0008, std=0.0063, min=-0.0145, max=0.0159\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-05-16] [\"Tech Today: Buffett Buys AAPL, Salesforce On Tap, AMD\\u2019s Prospects Warren Buffett bought more Apple stock, but others were loading up on Snapchat maker Snap, while analysts looked ahead to Advanced Micro Devices's annual meeting tomorrow, and earnings reports later this week from Salesforce.com and Applied Materials.\", \"Retail rundown: Three winners and six losers in the age of Amazon Some retailers are staying alive, while many face existential threats Some retailers are staying alive, while many face existential threats. By Jeff Reeves.\", \"Berkshire Hathaway confirms Warren Buffett\\u2019s Apple share purchase, IBM sale Berkshire more than doubled Apple holdings in first quarter to 129 million shares, worth $18.6 billion, as of March 31 Berkshire Hathaway Inc. sharply increased its holding of Apple Inc. and sold some of its stake in International Business Machines Corp. in the first quarter, according to a new securities filing.\", \"Apple stock price target raised to $180 from $165 at Canaccord Genuity\", \"Apple's stock price target gets a boost on increased iPhone sales estimates Apple Inc. stock price target was raised at Canaccord Genuity, citing increased estimates for iPhone sales. Analyst T. Michael Walkley lifted his target to $180, which is 16% above current levels, from $165. He increased his fiscal 2018 iPhone unit sales estimates to 248 million from 242 million. We anticipate a stronger upgrade cycle in C2018 with the 10-year anniversary iPhone 8, as our surveys indicate strong consumer interest in and anticipation for new iPhones anticipated to launch in September,\\\" Walkley wrote in a note to clients. Walkley's target is now tied for the third-highest price target among the 44 analysts surveyed by FactSet, behind Drexel Hamilton's $202 target and BTIG's $184 target, while Guggenheim Securities is also at $180, according to FactSet. Apple's stock slipped 0.1% in morning trade, but was just 0.4% below Friday's record close of $156.10. It has soared 34% year to date, while the Dow Jones Industrial Average has gained 6.3%.\", \"The \\u2018ridiculous\\u2019 reason tech stocks aren\\u2019t in a bubble Critical information for the U.S. trading day Technology stocks have been on a monster run, and not everyone is feeling OK about that. But here\\u2019s why investors, once again, have nothing to fear bubble-wise, says our call of the day..\", \"Fund managers say this is the \\u2018most crowded trade\\u2019 right now Technology stocks are looking awfully crowded, says the latest Bank of America Merrill Lynch fund-manager survey.\", \"Apple stock price target gets a big boost Canaccord\\u2019s Walkley becomes 29th analyst of the 44 surveyed by FactSet to lift Apple\\u2019s stock price target since May 2. Canaccord Genuity\\u2019s T. Michael Walkley joined the parade of analysts who have lifted Apple\\u2019s stock price target since May 2. Walkley\\u2019s new target is tied for third highest among 44 analysts surveyed by FactSet.\", \"Google Made E-mail Free;\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": "-0.0079", "answer_numeric": -0.007852, "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%) = -0.0115.", "metadata": {"var": -0.007852, "cvar": -0.011492, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20180706_0965", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2018-07-06", "context_summary": "XLRE: 60-day return history, mean=0.0014, std=0.0078.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0014, std=0.0078, min=-0.0226, max=0.0133\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-05] [\"PreMarket Prep Recap For July 5: Trading The Range In The S&P 500; Sean Udall Joins The Show\", \"PreMarket Prep Recap For July 5: Trading The Range In The S&P 500; Sean Udall Joins The Show\", \"Synopsys, Siemens Join Forces on EDA Interoperability Effort SynopsysSNPS is collaborating with Siemens PLM Software to jointly develop a wide range of electronic design automation (EDA) product interoperability projects. EDA is a category of tools used to analyze semiconductor devices. Many chip designers and manufacturers are opting for EDA, attracted by the reduced cost, errors and design time associated with its adoption. The increasing demand for EDA solutions are driven by growth in fast growing fields of cloud computing, Artificial Intelligence (AI), Internet of Things (IoT) and smart wearable devices. Collaboration to Boost Customer Base The synergistic collaboration between Synopsys and Siemens encompasses EDA domains from design to verification. The latest collaboration will help Synopsys address the needs of semiconductor and system-on-chip (SoC) manufacturing firms, which comprises the majority of its clientele. Moreover, the joint solution will enhance customers' digitization efforts. Further, the collaboration will ensure more effective EDA solutions for mutual customers. Notably, one major competitor of Synopsys was Mentor Graphics, which was recently acquired by Siemens. The companies have also settled all outstanding patent litigations Hence, we believe the collaboration with Siemens on EDA product interoperability solutions bodes well for Synopsys, as it will expand its penetration in the market. Synopsys, Inc. Revenue (TTM) Synopsys, Inc. Revenue (TTM) | Synopsys, Inc. Quote Extended Partner Base, New Solutions to Drive Growth We believe Synopsys will benefit from its expanding partner base. The company's extended relationships with the likes of AMD, Juniper, Realtek, Teradici, NetLogic Microsystems, Toshiba and Wolfson will continue to boost its top-line growth. Synopsys also collaborated with ARM Holdings plc which is expected to optimize the performance of its processors. The company is positive about its EDA design solutions which are helping in designing of new AI engines. The newly launched Fusion Technology has gained accolades from the Samsung, STMicroelectronics, Toshiba, and ANSYS. Further, strategic acquisitions have expanded the company's presence in the intensely competitive EDA market. Zacks Rank and Stocks to Consider Synopsys currently carries a Zacks Rank #3 (Hold). Some stocks worth considering in the broader Computer and Technology sector are Adobe ADBE , YY YY , and Verint VRNT . All three stocks sport a Zacks Rank #1 (Strong Buy). You can see the complete list of today's Zacks #1 Rank stocks here . Long-term earnings growth for Adobe, YY and Verint is projected to be 16.20%, 26.43% and 10%, respectively. Today's Stocks from Zacks' Hottest Strategies It's hard to believe, even for us at Zacks. But while the market gai\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": "-0.0120", "answer_numeric": -0.012037, "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%) = -0.0189.", "metadata": {"var": -0.012037, "cvar": -0.018859, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20221209_0967", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["CORN"], "decision_date": "2022-12-09", "context_summary": "CORN: 60-day return history, mean=-0.0006, std=0.0081.", "question": "Asset: CORN\nDaily returns (past 60 days): mean=-0.0006, std=0.0081, min=-0.0186, max=0.0192\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": "-0.0127", "answer_numeric": -0.01266, "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%) = -0.0154.", "metadata": {"var": -0.01266, "cvar": -0.01541, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210128_0969", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2021-01-28", "context_summary": "ICSH: 60-day return history, mean=-0.0000, std=0.0002.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=-0.0000, std=0.0002, min=-0.0004, 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": "-0.0004", "answer_numeric": -0.000396, "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%) = -0.0004.", "metadata": {"var": -0.000396, "cvar": -0.000396, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210813_0971", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2021-08-13", "context_summary": "IYR: 60-day return history, mean=0.0016, std=0.0081.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0016, std=0.0081, min=-0.0175, max=0.0225\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": "-0.0107", "answer_numeric": -0.010682, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0107 (i.e., on a bad day with 5% probability, the loss exceeds 1.07%). CVaR(95%) = -0.0159.", "metadata": {"var": -0.010682, "cvar": -0.015907, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20220715_0973", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2022-07-15", "context_summary": "XRP-USD: 60-day return history, mean=-0.0041, std=0.0391.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0041, std=0.0391, min=-0.1004, max=0.0955\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-14] \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": "-0.0601", "answer_numeric": -0.060113, "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%) = -0.0881.", "metadata": {"var": -0.060113, "cvar": -0.08812, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}}
{"id": "T2_all_20190524_0975", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2019-05-24", "context_summary": "BIL: 60-day return history, mean=0.0001, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0001, std=0.0001, min=-0.0001, max=0.0003\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": "-0.0001", "answer_numeric": -0.00011, "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%) = -0.0001.", "metadata": {"var": -0.00011, "cvar": -0.00011, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180702_0977", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2018-07-02", "context_summary": "REZ: 60-day return history, mean=0.0016, std=0.0085.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0016, std=0.0085, min=-0.0192, max=0.0256\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": "-0.0161", "answer_numeric": -0.016139, "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%) = -0.0177.", "metadata": {"var": -0.016139, "cvar": -0.017744, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20151013_0979", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2015-10-13", "context_summary": "QUAL: 60-day return history, mean=-0.0008, std=0.0126.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=-0.0008, std=0.0126, min=-0.0339, max=0.0266\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-10-12] Ameren Corp. (AEE) Raises Fourth Quarter Dividend by 3.7% Ameren CorporationAEE announced a 3.7% hike in its quarterly cash dividend, bringing the annualized payout to $1.70 per share, up from $1.64 paid earlier. The dividend increase will be effective from the fourth quarter of 2015. The raised dividend will amount to 42.5 cents per share from the prior payment of 41 cents. This amount will be paid on Dec 31, 2015, to shareholders of record as of Dec 9, 2015. With a market cap of $10.46 billion, this St. Louis-based company generates and distributes electricity and natural gas to residential, commercial, industrial and wholesale end markets in Missouri and Illinois. Utilities have been known to pay dividends consistently, thereby retaining the confidence of yield-hungry investors and proving the sector's defensive characteristics. Ameren is no exception to this trend. Ameren Corp. is also engaged in systematic investments in growth projects and infrastructure upgrade activities. In the first half of 2015, the company spent $556 million as capital expenditure, up 11% from the prior-year level. Ameren plans to complete several important projects in 2015, which include a new reactor vessel head at the Callaway Energy Center and an important substation in St. Louis. Under the Modernization Action Plan, the company intends to install around 140,000 electric and 73,000 gas meters at its service territory by 2015. Scheduled completion of these projects will enable the company to provide reliable services to its customers, besides meeting increasing demand. Ameren operates a rate-regulated business and has a stable earnings base serving 2.4 million electric customers and more than 900,000 natural gas customers in a 64,000-square-mile area. The company is expected to witness modest earnings growth at its core operations. Focus on its regulated utilities will help to meet the projected compound annualized earnings growth of 7-10% within a time span of 2013 to 2018. Zacks Rank AEE Corp. currently holds a Zacks Rank #2 (Buy). Other favorably placed stocks in the power sector are Brookfield Infrastructure Partners L.P. BIP , American Electric Power Co., Inc. AEP and Consolidated Edison, Inc. ED . While Brookfield sports a Zacks Rank #1 (Strong Buy), American Electric and Consolidated Edison carry a Zacks Rank #2 (Buy). 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 >> 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 AMEREN CORP (AEE): Free Stock Analysis Report AMER ELEC PWR (AEP): Free Stock Analysis Report BROOKFIELD INFR (BIP): Free Stock Analysis Report CONSOL EDISON (ED): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Research The views and opinions expressed herein are the views and opinions of the aut\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": "-0.0225", "answer_numeric": -0.022481, "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": -0.022481, "cvar": -0.031821, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20190717_0981", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2019-07-17", "context_summary": "VLUE: 60-day return history, mean=0.0001, std=0.0089.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0001, std=0.0089, min=-0.0282, max=0.0288\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-16] [\"Notable Tuesday Option Activity: UVE, AMD, WDC Among the underlying components of the Russell 3000 index, we saw noteworthy options trading volume today in Universal Insurance Holdings Inc (Symbol: UVE), where a total of 1,150 contracts have traded so far, representing approximately 115,000 underlying shares. That amounts to about 52.3% of UVE's average daily trading volume over the past month of 219,995 shares. Especially high volume was seen for the $25 strike call option expiring August 16, 2019, with 1,125 contracts trading so far today, representing approximately 112,500 underlying shares of UVE. Below is a chart showing UVE's trailing twelve month trading history, with the $25 strike highlighted in orange: Advanced Micro Devices Inc (Symbol: AMD) options are showing a volume of 294,746 contracts thus far today. That number of contracts represents approximately 29.5 million underlying shares, working out to a sizeable 50.7% of AMD's average daily trading volume over the past month, of 58.1 million shares. Particularly high volume was seen for the $35 strike call option expiring July 19, 2019, with 36,309 contracts trading so far today, representing approximately 3.6 million underlying shares of AMD. Below is a chart showing AMD's trailing twelve month trading history, with the $35 strike highlighted in orange: And Western Digital Corp (Symbol: WDC) options are showing a volume of 37,907 contracts thus far today. That number of contracts represents approximately 3.8 million underlying shares, working out to a sizeable 49.6% of WDC's average daily trading volume over the past month, of 7.6 million shares. Particularly high volume was seen for the $50 strike put option expiring July 19, 2019, with 4,169 contracts trading so far today, representing approximately 416,900 underlying shares of WDC. Below is a chart showing WDC's trailing twelve month trading history, with the $50 strike highlighted in orange: For the various different available expirations for UVE options, AMD options, or WDC options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"The AMD Stock Rally Has Gotten Way Too Advanced in Front of Earnings Shraes of Advanced Micro Devices (NASDAQ:) broke out to fresh multi-year highs yesterday. AMD stock finally closed above the $34 level after three previous failed tries. Momentum traders rejoiced, although shares did finish slightly off the highs of the day. Advanced Micro Devices has now added on over 30% since the lows near $26.50 in late May. All good things must come to an end, though. The red-hot rally in an overbought and overvalued AMD has come too far, too fast. Time to take some chips off the table. InvestorPlace contributor Jay Yao both the bullish and bearish case for AMD stock. He noted that AMD stock price was comparatively expensive, trading a\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": "-0.0137", "answer_numeric": -0.013701, "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%) = -0.0215.", "metadata": {"var": -0.013701, "cvar": -0.021548, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}}
{"id": "T2_all_20220912_0983", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2022-09-12", "context_summary": "EMB: 60-day return history, mean=0.0006, std=0.0092.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0006, std=0.0092, min=-0.0155, max=0.0165\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": "-0.0152", "answer_numeric": -0.015218, "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%) = -0.0155.", "metadata": {"var": -0.015218, "cvar": -0.015501, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20180913_0985", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2018-09-13", "context_summary": "HYG: 60-day return history, mean=0.0002, std=0.0014.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0002, std=0.0014, min=-0.0028, max=0.0038\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": "-0.0023", "answer_numeric": -0.002329, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0023 (i.e., on a bad day with 5% probability, the loss exceeds 0.23%). CVaR(95%) = -0.0025.", "metadata": {"var": -0.002329, "cvar": -0.002499, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20181010_0987", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2018-10-10", "context_summary": "SOYB: 60-day return history, mean=0.0011, std=0.0112.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=0.0011, std=0.0112, min=-0.0265, 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": "-0.0148", "answer_numeric": -0.014763, "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%) = -0.0213.", "metadata": {"var": -0.014763, "cvar": -0.021343, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20211012_0990", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["CORN"], "decision_date": "2021-10-12", "context_summary": "CORN: 60-day return history, mean=-0.0006, std=0.0117.", "question": "Asset: CORN\nDaily returns (past 60 days): mean=-0.0006, std=0.0117, min=-0.0268, max=0.0253\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": "-0.0178", "answer_numeric": -0.01784, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0178 (i.e., on a bad day with 5% probability, the loss exceeds 1.78%). CVaR(95%) = -0.0235.", "metadata": {"var": -0.01784, "cvar": -0.023499, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210118_0992", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2021-01-18", "context_summary": "XHB: 60-day return history, mean=0.0015, std=0.0153.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0015, std=0.0153, min=-0.0411, max=0.0350\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": "-0.0188", "answer_numeric": -0.018786, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0188 (i.e., on a bad day with 5% probability, the loss exceeds 1.88%). CVaR(95%) = -0.0310.", "metadata": {"var": -0.018786, "cvar": -0.03101, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20210223_0994", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2021-02-23", "context_summary": "MORT: 60-day return history, mean=0.0021, std=0.0142.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0021, std=0.0142, min=-0.0297, max=0.0315\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": "-0.0245", "answer_numeric": -0.024535, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0245 (i.e., on a bad day with 5% probability, the loss exceeds 2.45%). CVaR(95%) = -0.0293.", "metadata": {"var": -0.024535, "cvar": -0.029317, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20170203_0996", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2017-02-03", "context_summary": "IYR: 60-day return history, mean=0.0009, std=0.0093.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0009, std=0.0093, min=-0.0185, max=0.0195\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": "-0.0159", "answer_numeric": -0.015886, "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%) = -0.0184.", "metadata": {"var": -0.015886, "cvar": -0.018404, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T2_all_20201026_0999", "template": "T2", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-10-26", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0062, std=0.0490.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0062, std=0.0490, min=-0.1751, max=0.1042\nMarket regime: sideways\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": "-0.0894", "answer_numeric": -0.089439, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0894 (i.e., on a bad day with 5% probability, the loss exceeds 8.94%). CVaR(95%) = -0.1370.", "metadata": {"var": -0.089439, "cvar": -0.136987, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20171211_0000", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2017-12-11", "context_summary": "VCIT: 60-day history, VaR(99%)=-0.0034, max drawdown threshold=10%.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=0.0001, std=0.0015, worst_day=-0.0043\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 = 0.0034 (i.e., a 0.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0034 = 28.9860, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.00345, "expected_loss": 0.00345, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160523_0003", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2016-05-23", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0317, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0026, std=0.0142, worst_day=-0.0429\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-20] [\"Apple\\u2019s iPhone 7 Will Likely Have Dual Cameras: Who Will Benefit? Citi Research believes that all new 5.5\\\" Apple (AAPL) iPhone 7's coming this fall will be equipped with dual rear cameras. The street currently thinks the new 5.5\\\" iPhone will come with two models, one with dual cameras and one without.Dual-camera is a major spec upgrade this year. Huawei's new flagship P9 and LG Electronics' G5 both have this feature.So if Citi is correct, which Asian suppliers will be the biggest beneficiaries?READ MORE.\", \"LG Innotek: Sony Is Behind Apple\\u2019s iPhone7 Schedule, Nomura Raises To Buy LG Innotek(011070.Korea) is no longer a victim of AAPL (AAPL) weakness.Earlier today, I wrote that Citi Research now thinks all the new 5.5\\\" iPhones coming this fall will have dual cameras, contrary to street prediction that the new iPhone 7 will come in two models, one with dual camera and one without.Well, the street is moving over. Nomura Securities this morning also said \\\"the dual camera will be used in all new 5.5\\u201d iPhones.\\\"READ MORE.\", \"Google\\u2019s VR Push Boosts Applied Materials Higher computational needs for VR should continue to drive more powerful systems on chips.\", \"Here\\u2019s everything billionaires like Soros and Buffett don\\u2019t reveal in their 13F filings Data offers interesting peek, but take with grain of salt 13-F filings from hedge funds and other big investors can be entertaining and potentially profitable, but don\\u2019t take it too far.\", \"Google Daydream Will Introduce Virtual Reality To The Masses: Piper Piper Jaffray believes that virtual reality (VR) is the \\u201cstart of the next computing paradigm, and mixed reality (MR) will eventually replace the screen as we know it.\\u201dThus, analyst Gene Munster and his team have started a new monthly VR & MR Reality Check series, talking about developments in the space. Of course this week was dominated by news from Google parent Alphabet\\u2019s (GOOGL) I/O developer\\u2019s conference, where the firm didn\\u2019t show us a VR headset, but did say it was partnering with IMAX (IMAX) to make VR cameras.Read More \\u00bb\", \"Moody\\u2019s: Corporate Cash Holdings Continue to Grow With the ongoing slow growth economy and downturn in energy and segments of retail, you might think U.S. companies would have spent down some of the cash piles they accumulated in the long expansion.And some have. But a new report from Moody's Investors Service, which tallies the cash held by non-financial corporations in the U.S., found cash levels continued to grow in 2015. The total grew to $1.68 trillion by the end of last year -- up 1.8% from the end of 2014. Read More\\u00bb\", \"Tech Companies Have The Most Cash; Apple Still King: Moody\\u2019s Non-financial companies in the U.S. had a combined cash hoard of $1.68 trillion at the end of last year, a 1.8% year-over-year increase, according to a new report from Moody\\u2019s Investors Service\\u2014and tech led the way.U.S. companies had to have at least $6.\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 = 0.0317 (i.e., a 3.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0317 = 3.1577, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031669, "expected_loss": 0.031669, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180613_0006", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2018-06-13", "context_summary": "ITB: 60-day history, VaR(99%)=-0.0357, max drawdown threshold=10%.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=0.0005, std=0.0154, worst_day=-0.0379\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 = 0.0357 (i.e., a 3.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0357 = 2.7990, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035727, "expected_loss": 0.035727, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210326_0011", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2021-03-26", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0313, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0028, std=0.0157, worst_day=-0.0404\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 = 0.0313 (i.e., a 3.13% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0313 = 3.1986, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031264, "expected_loss": 0.031264, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210520_0014", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2021-05-20", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0233, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0011, std=0.0098, worst_day=-0.0247\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-05-19] [\"Analog Devices Guides Q3 In Line With Estimates, Declares Dividend - Quick Facts (RTTNews) - While reporting financial results for the second quarter on Wednesday, semiconductor company Analog Devices Inc. (ADI) provided earnings and revenue guidance for the third quarter, in line with analysts' expectations. For the third quarter, the company projects earnings in a range of $1.12 to $1.34 per share and adjusted earnings in a range of $1.50 to $1.72 per share on projected revenues between $1.63 billion and $1.77 billion. On average, analysts polled by Thomson Reuters expect the company to report earnings of $1.53 per share on revenues of $1.65 billion for the quarter. Analysts' estimates typically exclude special items. The company's Board of Directors also declared a quarterly cash dividend of $0.69 per outstanding share of common stock, payable on June 8, 2021 to all shareholders of record at the close of business on May 28, 2021. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Analog Devices shares rise after outlook, results beat expectations By Stephen Nellis May 19 (Reuters) - Shares of Analog Devices Inc ADI.O rose Wednesday after the chipmaker forecast third-quarter sales and profits above Wall Street expectations and as the company's chief executive said it had boosted spending on suppliers and its own factories to mitigate the effects of a chip shortage. ADI gave a fiscal third-quarter forecast with midpoints of $1.7 billion in sales and adjusted earnings of $1.61 per share, above estimates of $1.65 billion and $1.54 per share, according to IBES data from Refinitiv. Shares were up 3.8% at around 12:45 p.m. Eastern Time after the before-market-open results were released. For the fiscal second quarter, ADI reported sales of $1.66 billion and adjusted earnings of $1.54 per share versus analyst estimates of $1.61 billion and $1.45 per share, according to Refinitiv data. ADI makes some of its chips in its own factories and also sources some of them from outside factories. Chief Executive Officer Vincent Roche on Wednesday told Reuters the company has boosted capital expenditures with both to supply as many chips as possible and take advantage of growth opportunities. One emerging market for ADI is chips that manage the battery systems in electric vehicles. During the fiscal second quarter, the company signed Volvo as a customer for the chips, as well as what it described as a major European luxury automaker and two Asian brands. \\\"In the quarter that's just gone, we had an all-time record for shipments into the electric vehicle segment, particularly on the battery side,\\\" Roche said. \\\"We're represented in well over 50% of OEM battery systems.\\\" (Reporting by Stephen Nellis in San Francisco; Editing by David Gregorio) ((Stephen.Nellis@thomsonreuters.com; (415) 344-4934;)) The views and opinions expressed herein are the views and opinions of the author \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 = 0.0233 (i.e., a 2.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0233 = 4.2898, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023311, "expected_loss": 0.023311, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220127_0017", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2022-01-27", "context_summary": "UNG: 60-day history, VaR(99%)=-0.0858, max drawdown threshold=10%.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=-0.0039, std=0.0414, worst_day=-0.0858\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 = 0.0858 (i.e., a 8.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0858 = 1.1659, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.085769, "expected_loss": 0.085769, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210218_0020", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2021-02-18", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1459, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0298, std=0.0861, worst_day=-0.1736\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6852", "answer_numeric": 0.6852, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1459 (i.e., a 14.59% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1459 = 0.6852, capped at 1.0.\nMaximum position size = 0.6852 (68.5% of portfolio).", "metadata": {"var_99": -0.145936, "expected_loss": 0.145936, "max_drawdown_threshold": 0.1, "position_size": 0.6852, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200715_0023", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2020-07-15", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0339, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0006, std=0.0157, worst_day=-0.0339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-07-14] [\"S&P 500, Dow rise after mixed bank earnings; tech-heavy Nasdaq falls By Medha Singh and Devik Jain July 14 (Reuters) - The S&P 500 and Dow indexes edged higher in volatile trading on Tuesday as investors digested a mixed bag of quarterly earnings reports from U.S. lenders but technology stocks fell on worries over new business restrictions in California. JPMorgan Chase & Co JPM.N, the largest U.S. lender, was up 0.2% after it posted a smaller-than-expected 51% drop in second-quarter profit. Wells Fargo & Co WFC.N, however, fell 5.5% after booking a quarterly loss for the first time since the 2008 financial crisis. Citigroup Inc C.N was also down 2.5% as it reported a steep fall in quarterly profit. The S&P 500 banks index .SPXBK slumped 1.6% as the three banks set aside a combined $28 billion to cover potential losses on loans to borrowers hurt by the coronavirus pandemic. \\\"The choppiness is very natural as we've had our fair share of gains over the last two or three weeks now,\\\" said Luis Strohmeier, wealth advisor at Octavia in Los Angeles, California. \\\"There's a level of uncertainty due to California temporary shutting down indoors ... because we weren't prepared for a reversal in the opening.\\\" Wall Street has reclaimed most of its coronavirus-driven losses since March as a raft of monetary and fiscal stimulus and upbeat economic data raised hopes of a swift post-pandemic recovery. But a recent record surge in COVID-19 cases and new business restrictions, particularly in California, have sparked a selloff in tech stocks, with the Nasdaq pulling back about 6% from its intraday record high on Monday. Investors are bracing for what could be the sharpest drop in quarterly earnings for S&P 500 firms since the 2008 financial crisis, according to Refinitiv IBES data. At 12:55 p.m. ET, the Dow Jones Industrial Average .DJI was up 257.51 points, or 0.99%, at 26,343.31, the S&P 500 .SPX was up 7.03 points, or 0.22%, at 3,162.25. The Nasdaq Composite .IXIC was down 41.96 points, or 0.40%, at 10,348.88. Amazon.com Inc AMZN.O, Adobe Inc ADBE.O and Facebook Inc FB.O, all three of which hit record highs in intraday trading on Monday, were some of the biggest drags on the Nasdaq. Delta Air Lines Inc DAL.N fell 2.5% as it warned it will be more than two years before the industry sees a sustainable recovery from the \\\"staggering\\\" impact of the coronavirus pandemic, with demand largely tracking the curve of infections in different places. Moderna Inc MRNA.O rose 3.7% as it plans to start a late-stage clinical trial for its COVID-19 vaccine candidate on or around July 27. Advancing issues outnumbered decliners by a 1.41-to-1 ratio on the NYSE and for a 1.01-to-1 ratio on the Nasdaq. The S&P index recorded three new 52-week highs and no new low, while the Nasdaq recorded 23 new highs and 27 new lows. COVID-19's growing potential economic impacthttps://tmsnrt.rs/307zCt5 (Reporting by Medha Singh and Devik Jain in Bengaluru; Editing by Shounak Dasgupta and Ani\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 = 0.0339 (i.e., a 3.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0339 = 2.9516, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03388, "expected_loss": 0.03388, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200624_0025", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2020-06-24", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0021, std=0.0213, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-23] [\"9 Things Apple Announced at WWDC\\u2014and 5 Things It Didn\\u2019t iOS14, Car Play, and Apple Maps all got great upgrades, but what was missing from the lineup is just as interesting as what made the cut.\", \"Podcast: Apple Closes at Record High Amid Chip Announcement Blank-check companies are on pace to smash last year\\u2019s record for IPOs. Gold futures are the highest they have been since 2012. And Apple gets into the computer chip game.\", \"Apple stock price target raised to $380 from $350 at Deutsche Bank\", \"UBS boosts 12-month Apple price target to $400 from $325 per share\", \"Apple's stock rallies 1.6% premarket, after surging 2.6% on Monday to a record close\", \"The Dow Is Rising Because China Trade Deal Is \\u2018Fully Intact\\u2019 All three major U.S. stock indexes were solidly higher after a volatile evening. Apple gained on news that it will move away from Intel-designed processors and develop its own chips.\", \"Barron\\u2019s Daily: A Look at Today\\u2019s Primaries; U.S.-China Trade Deal Remains \\u2018Intact\\u2019 Trade deal with China still \\u201cintact,\\u201d May home sales took a dive, cases continue to surge in the U.S., and other news to start your day.\", \"Trump Suspends H-1B Visas. Tech Companies Aren\\u2019t Happy. On Monday, the president took another swipe at the tech giants by suspending the issuance of visas for foreign workers. Tech companies fired back.\", \"Apple stock price target raised to $400 from $325 at UBS\", \"Merck, Apple Inc. share gains contribute to Dow's nearly 150-point jump\", \"Dow's 225-point jump led by gains for shares of Apple Inc., Nike\", \"Charting a bullish summer start, Nasdaq takes flight to record territory Focus: Gold challenges seven-year highs, Biotech sector reaches record territory, Apple asserts bullish continuation pattern, GLD, XBI, AAPL, SPLK, HOLX Technically speaking, the U.S. benchmarks\\u2019 bigger-picture backdrop remains bullish, on balance, despite increasingly uneven market price action. On a headline basis, the Nasdaq Composite has taken flight \\u2014 reaching record highs, atop the 10,000 mark \\u2014 while the S&P 500 remains range-bound, digesting a sharp reversal from the June low.\", \"Crude Oil Is Trading Above a Key Level U.S. producers still have a long to go, however. Only Hess has gained since the last time oil traded above $40.\", \"Apple Stock Extends Rally as Analysts Gush Over Conference Speech The stock has now rallied about 60% from its March lows, a move that has lifted the company\\u2019s market valuation by close to $600 billion.\", \"Charting a bullish summer start, Nasdaq takes flight to record territory Focus: Gold challenges seven-year highs, Biotech sector reaches record territory, Apple asserts bullish continuation pattern, GLD, XBI, AAPL, SPLK, HOLX Technically speaking, the U.S. benchmarks\\u2019 bigger-picture backdrop remains bullish, on balance, despite increasingly uneven market price action, writes Michael Ashbaugh.\", \"Mercedes-Benz and Nvidia Sign a Deal to Make Car\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 = 0.0356 (i.e., a 3.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0356 = 2.8129, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035551, "expected_loss": 0.035551, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170817_0028", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2017-08-17", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0812, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0069, std=0.0455, worst_day=-0.1050\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0812 (i.e., a 8.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0812 = 1.2308, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.081249, "expected_loss": 0.081249, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200901_0031", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2020-09-01", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0299, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0025, std=0.0114, worst_day=-0.0388\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-08-31] [\"Apple's stock rallies as 4-for-1 split set to take effect Shares of Apple Inc. rallied 1.4% in premarket trading Monday, paring earlier gains, as the 4-for-1 stock split is set to become official after the opening bell. Given Friday's close was $499.23, the split-adjusted close is now $124.81. The stock would be adding roughly 11 points to the Dow Jones Industrial Average's price. The last after-hours trade at the pre-split-adjusted price was the equivalent of $501.90, representing a 0.5% gain, while the first premarket trade Monday at the split-adjusted price was $128.00, reflecting a gain of 2.6%. The Aug. 26 record close has been adjusted to $126.52, while the Aug. 24 all-time intraday high during regular-session hours has been adjusted to $128.79.\", \"Cruise operators took a deep bruising from COVID-19, but history says they will recover Cruise companies in the age of COVID-19: Industry with a history of disease outbreaks would appear to be doomed in a post-COVID world, but history says a loyal fan base has a short memory The cruise industry seemed doomed by the COVID-19 pandemic, given its history of onboard disease outbreaks. But it\\u2019s exactly that history that suggests this time won\\u2019t be different, and cruising will eventually flourish again.\", \"Five things you should know about Tesla ahead of its 5-for-1 stock split Tesla hopes to make ownership of its stock \\u2018more accessible\\u2019 Tesla Inc.shares will start trading Monday after a 5-for-1 stock split. Here are five things to know about the Silicon Valley electric-car maker.\", \"Three things you need to know about Apple\\u2019s stock split The fifth split in the company\\u2019s history led to changes for the Dow Jones Industrial Average that will also take place before trading begins Monday Apple Inc.\\u2019s stock price will appear quite a bit lower Monday morning, but investors shouldn\\u2019t fret.\", \"Barron\\u2019s Daily: Nestle Just Bought a Biotech Company. Here\\u2019s Why. Man dies after Portland protests turn violent, Dems clash with Trump administration over election security briefings, Apple and Tesla shares set for post-split trading, and other news to start your day.\", \"Tesla Stock, Apple Gain, and the Dow Is Rising U.S. stocks were poised to open higher, moving closer to completing their strongest August performances in decades.\", \"Apple stock's surges 2.1% as stock split takes effect\", \"Apple stock's first trade on Nasdaq at 9:30 a.m. ET after split adjustment was $127.62\", \"Apple\\u2019s Stock Split 4-for-1. Here\\u2019s What It Means for Investors. Morgan Stanley analyst Katy Huberty says Apple shares have historically outperformed the S&P 500 in the months both leading up to stock splits, and following them.\", \"Tesla Stock Split 5-for-1. What That Means for Investors. Shares of the electric-car company have gained 63% since the 5-for-1 split was announced on Aug. 11.\", \"Apple Split Its Stock. Analysts Stay Bullish and the Rally Continues. Investors take stock splits\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 = 0.0299 (i.e., a 2.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0299 = 3.3437, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029907, "expected_loss": 0.029907, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20171123_0034", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2017-11-23", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0103, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0005, std=0.0055, worst_day=-0.0108\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-11-22] [\"Apple Could Offer \\u2018iPhone 8s\\u2019 With Large, non-OLED Screen, Says Rosenblatt Apple may offer an \\\"iPhone 8s\\\" next year that ditches the AMOLED display but offers a larger screen in 2018, speculates analyst Jun Zhang with Rosenblatt Securities.\", \"\\u2018League of Legends\\u2019 owner Tencent is closing in on Amazon Tencent\\u2019s shares trade on the Pinks sheets, but the Hong Kong-based company is now more valuable than Facebook Pink sheets-listed Tencent Holding\\u2019s market value passed Facebook, and is now closing in on Amazon.\", \"Apple and big tech will drive total 2017 corporate cash stockpile up to $1.9 trillion Tech sector\\u2019s slice of all corporate cash approaches 50%, with its offshore stash only growing: Moody\\u2019s Led by Apple, technology companies continue to boast strong cash flow generation, leaving a select five firms atop a corporate cash heap that will only grow more this year, Moody\\u2019s Investors Service data out Monday showed.\", \"Apple has acquired augmented reality headset maker Vrvana: TechCrunch Apple Inc. has acquired Vrvana, maker of an augmented reality headset called Totem, for about $30 million, TechCrunch reported, citing two unnamed sources. The headset got strong reviews, but never shipped, the website reported. Apple declined to comment, but did not deny the story, said TechCrunch. Apple is reported to be preparing to ship an AR headset by 2020. Apple shares were slightly higher in premarket trade, and have gained 49% in 2017, while the Dow Jones Industrial Average has gained 19% and the S&P 500 has gained 16%.\", \"Samsung accidentally confirms its making a Galaxy X\\u2014and it\\u2019s not what you\\u2019d expect New device is Samsung\\u2019s first bendable smartphone The Galaxy X is Samsung\\u2019s first bendable smartphone, a device that\\u2019s so complicated it might see a limited launch before Samsung is able to manufacture it en-masse.\", \"These stocks are primed for their seasonal breakout \\u2014 and this time it\\u2019s a humdinger Critical information for the U.S. trading day Investors have gobbled up just about every corner of this market that has been performing well for them this year. Is there no hidden corner? Yes, says our call of the day, who is looking for small-caps to outperform in the next few months.\", \"Follow this pattern to make money outside FAANG stocks Wal-Mart, Intel, Cisco and Applied Materials can compete as investments with the likes of Facebook, Amazon and the other FAANG stocks Wal-Mart, Intel, Cisco and Applied Materials can compete as investments with the likes of Facebook, Amazon and the other FAANG stocks. By Nigam Arora.\", \"Forget AT&T. Time Warner Could Pair With Disney, CBS, Fox Even if the AT&T deal doesn't go through, it makes sense for Time Warner to partner up.\", \"Bring Out the Bulls: Stocks Gain More Tailwinds Hold the turkey: Thanksgiving is usually bullish. Stocks are up on earnings, tax hopes and seasonal cycles.\", \"Nvidia: VC Firm Loup Ventures Lauds Potentia\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 = 0.0103 (i.e., a 1.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0103 = 9.6652, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010346, "expected_loss": 0.010346, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180727_0037", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-07-27", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0985, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0043, std=0.0387, worst_day=-0.1086\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0985 (i.e., a 9.85% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0985 = 1.0156, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.09846, "expected_loss": 0.09846, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20191016_0042", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2019-10-16", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0248, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0009, std=0.0085, worst_day=-0.0251\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-10-15] 2 Cheap Dividend Stocks You Can Buy Right Now The technology sector has become a great place to look for dividend stocks, as the 3.2% average yield offered by companies in this sector is more than double the S&P 500's average dividend yield of 1.5%. What's more, dividend-paying technology companies offer investors the potential to benefit from fast-growing trends and the associated stock price upside. This is why we are going to take a closer look at Applied Materials (NASDAQ: AMAT) and Xilinx (NASDAQ: XLNX) -- two stocks that are sitting on notable opportunities and trade at very attractive valuations. Image Source: Getty Images Applied Materials could give its dividend a nice hike next year Applied Materials' 1.65% forward dividend yield might be lower than the technology sector's average, but there's a lot to like about the company. First, the stock has shot up over 50% so far in 2019 despite a muted financial performance lately, which shows its resilience and investors' faith in the company's long-term prospects. The rally doesn't seem to be misplaced as it is a solid bet on the rise of the semiconductor industry. It supplies chip fabrication equipment to semiconductor companies, so the demand for its products stands to rise in the future on the back of emerging technology trends -- 5G networks, the Internet of Things, artificial intelligence, and autonomous driving, among others -- that will create the need for more complex chips. The semiconductor industry is going through a lean patch right now, but the company sees a turnaround taking place next year. CEO Gary Dickerson pointed this out on the latest earnings conference call: \"Taking these factors into account, our view of overall wafer fab equipment spending for 2019 remains the same down mid-to-high teens on a percentage basis relative to last year. We see 2020 is a more positive set up for the industry in Applied with the start of a recovery and memory investment and sustained strength in foundry logic spending.\" The next reason to buy Applied Materials is valuation. Despite the rally, the stock continues to trade at an affordable valuation. Its trailing price-to-earnings (P/E) ratio of 15.7 is lower than the company's five-year average multiple of 18. So, now would be a good time to go long on the stock as a turnaround next year could encourage the company to give its dividend a nice bump. I'm saying that because Applied Materials had doubled its quarterly dividend payout in early 2018 thanks to a favorable financial performance and its tradition of returning around 90% of the free cash flow back to investors. It has stuck to that tradition despite a fall in its free cash flow over the past year, having returned $724 million to shareholders (share repurchases and dividend payments combined) in the fiscal third quarter when its free cash flow came in at $694 million. AMAT total dividends paid (quarterly) data by YCharts. Applied Materials' dividend payout was $196 million during the qu\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 = 0.0248 (i.e., a 2.48% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0248 = 4.0387, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02476, "expected_loss": 0.02476, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160802_0045", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2016-08-02", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0230, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0008, std=0.0080, worst_day=-0.0339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-08-01] [\"Tech Turbocharged By Earnings, Chart Breakouts Last week\\u2019s killer earnings from Facebook, Alphabet and Apple paced an already energized tech sector.\", \"The drive behind Uber and Didi\\u2019s odd billions Ride-hailing services battle for China with cash that isn\\u2019t coming from venture capital Two ride-hailing giants are bringing in billions of dollars from untraditional sources, and the goals seem clear.\", \"The complicated web of companies that will determine the future of cars Race with tech giants to autonomous services pushes partnerships between carmakers and ride-hailing startups Auto makers, ride-hailing companies and tech companies are all part of an intricate web of partnerships and investments working toward an autonomous future.\", \"Sony: Could Have 54% Upside; Four Reasons to Be Bullish Japanese electronics giant Sony (6758.JP) is making investors believe in the stock again. Shares are up 2.2% this morning following the company\\u2019s stunning June quarter earnings beat last Friday. The stock has rebounded 12% this year after having plummeted 35% in the second half ofSony unveiled a JPY56 billion operating profit for the June quarter, which is well above the JPY3 billion operating loss analysts were expecting. Revenues of JPY1.6 trillion were down 11% year-on-year although the fall narrows to 3% after adjusting for the stronger yen.READ MORE>>\", \"Didi Chuxing reaches deal to buy Uber\\u2019s China operations Uber, investors in UberChina unit will own 20% of Didi; Chinese ride-hailing company will invest $1 billion in Uber Global ride-hailing giant Uber Technologies Inc. has given up its costly battle for China\\u2019s riders, swapping its local operations there for a minority stake in the country\\u2019s homegrown champion, Didi Chuxing Technology Co.\", \"Earnings signal a bear market: \\u2018Sell the house, sell the car, sell the kids\\u2019 Critical intelligence before the U.S. market opens Investors are certainly looking for something to light a fire under this market, considering the S&P 500 over the past 11 days has been stuck in the narrowest range in 45 years.\", \"Worldwide tablet shipments plunge 12% in second quarter: IDC\", \"VirnetX's stock plunges 46% premarket after disappointing court ruling on Apple patent suits\", \"Apple grows share of total tablet market despite sales decline Worldwide shipments of tablets fell 12% in the second quarter, according to a new report from IDC. Roughly 65% of tablets shipped this past quarter were run on Alphabet Inc.'s Android operating system, followed by Apple Inc.'s ioS, which captured 26% of the market. Apple's shipments fell by 9% year-over-year, but the launch of a new iPad Pro earlier this year helped to increase average selling prices for iPads, lifting Apple's total share of the market from 25% last year. Samsung Electronics Co.'s share decreased to 15.6% from 18.2% a year ago, as its shipments plunged 25% during the quarter. Lenovo, Huawei and Amazon.com Inc. rounded out the top fi\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 = 0.0230 (i.e., a 2.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0230 = 4.3464, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023008, "expected_loss": 0.023008, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20171107_0047", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2017-11-07", "context_summary": "REZ: 60-day history, VaR(99%)=-0.0138, max drawdown threshold=10%.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0003, std=0.0060, worst_day=-0.0169\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 = 0.0138 (i.e., a 1.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0138 = 7.2646, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013765, "expected_loss": 0.013765, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20211130_0050", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2021-11-30", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0277, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0003, std=0.0110, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-11-29] [\"Is Autodesk Stock a Buy? Autodesk's (NASDAQ: ADSK) stock plunged 15% on Nov. 24 after the design software maker posted its third-quarter earnings report. Its revenue rose 18% year-over-year to $1.13 billion, which beat estimates by $10 million. Its adjusted earnings grew 28% to $1.33 per share, which also topped expectations by seven cents. Autodesk's headline numbers looked healthy, but its profit guidance for the fourth quarter slightly missed analysts' expectations. Did the market overreact and create an attractive buying opportunity? Image source: Getty Images. Its core businesses are still growing Autodesk organizes its software portfolio into four main segments: AEC (Architecture, Engineering, and Construction), AutoCAD and AutoCAD LT, MFG (Manufacturing), and M&E (Media and Entertainment). During the third quarter, it generated 45% of its revenue from the AEC segment, 28% from the AutoCAD segment, 20% from the MFG segment, and 6% from the M&E segment. All four segments have generated accelerating year-over-year growth over the past two quarters: REVENUE GROWTH (YOY) Q3 2021 Q4 2021 Q1 2022 Q2 2022 Q3 2022 AEC 17% 18% 16% 21% 22% AutoCAD 14% 11% 9% 12% 14% MFG 7% 17% 8% 12% 16% M&E 7% 14% 5% 10% 17% Total 13% 16% 12% 16% 18% Source: Autodesk. YOY = Year-over-year. Autodesk's businesses remained resilient throughout the pandemic because it had previously transformed its desktop software into cloud-based subscription services. That strategy, which closely mirrors Adobe's (NASDAQ: ADBE) transformation of its creative software into cloud-based services, locked in Autodesk's customers with sticky subscriptions. Just as Adobe's suite of creative software services are considered indispensable to many graphic designers and media professionals, Autodesk's software products are considered industry-standard tools for architects, engineers, designers, and other professionals. That \\\"best in breed\\\" reputation gives it a wide moat with plenty of pricing power. That pricing power and tighter cost controls boosted its adjusted operating margin year-over-year -- from 29% to 31% -- in the first nine months of fiscal 2022. It also expects to post an adjusted operating margin of approximately 31% for the full year, compared to 29% in fiscal 2021. Was Autodesk's guidance that bad? Autodesk expects that growth to continue. CFO Debbie Clifford said the market's \\\"demand was robust\\\" throughout the third quarter, and should \\\"remain so\\\" in the fourth quarter. However, the midpoints of Autodesk's revenue and earnings guidance for the fourth quarter slightly missed Wall Street's expectations, even though its full-year guidance still matched their estimates: METRIC (YOY) AUTODESK: ANALYSTS: Q4 2022 Revenue Growth 14%-15% 15% Q4 2022 Adjusted EPS Growth 19%-25% 25% FY 2022 Revenue Growth 15% 15% FY 2022 Adjusted EPS Growth 23%-24% 23% Source: Autodesk. Clifford attributed its slowdown in the fourth quarter to the \\\"supply chain disruption and resulting inflationar\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 = 0.0277 (i.e., a 2.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0277 = 3.6131, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027677, "expected_loss": 0.027677, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20221006_0053", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2022-10-06", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0305, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0003, std=0.0131, worst_day=-0.0309\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-05] [\"After Hours Most Active for Oct 5, 2022 : DKNG, BTRS, X, AAPL, TQQQ, FDX, QQQ, SHY, STOR, C, TMX, T The NASDAQ 100 After Hours Indicator is down -5.07 to 11,568.11. The total After hours volume is currently 56,919,551 shares traded. The following are the most active stocks for the after hours session: DraftKings Inc. (DKNG) is +0.02 at $16.72, with 4,538,767 shares traded. As reported by Zacks, the current mean recommendation for DKNG is in the \\\"buy range\\\". BTRS Holdings Inc. (BTRS) is unchanged at $9.30, with 3,054,891 shares traded. As reported in the last short interest update the days to cover for BTRS is 7.073858; this calculation is based on the average trading volume of the stock. United States Steel Corporation (X) is -0.04 at $20.15, with 2,353,442 shares traded. X's current last sale is 79.02% of the target price of $25.5. Apple Inc. (AAPL) is -0.03 at $146.37, with 1,812,454 shares traded. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". ProShares UltraPro QQQ (TQQQ) is -0.02 at $22.56, with 1,517,812 shares traded. This represents a 17.01% increase from its 52 Week Low. FedEx Corporation (FDX) is +0.01 at $156.88, with 1,504,179 shares traded. FDX's current last sale is 78.83% of the target price of $199. Invesco QQQ Trust, Series 1 (QQQ) is +0.09 at $282.07, with 1,464,731 shares traded. This represents a 5.6% increase from its 52 Week Low. iShares 1-3 Year Treasury Bond ETF (SHY) is +0.03 at $81.26, with 1,197,338 shares traded. This represents a .32% increase from its 52 Week Low. STORE Capital Corporation (STOR) is +0.05 at $31.48, with 1,160,148 shares traded. STOR's current last sale is 97.61% of the target price of $32.25. Citigroup Inc. (C) is unchanged at $43.84, with 1,073,662 shares traded. C's current last sale is 73.07% of the target price of $60. Terminix Global Holdings, Inc. (TMX) is -0.05 at $40.34, with 986,921 shares traded. TMX's current last sale is 91.68% of the target price of $44. AT&T Inc. (T) is +0.03 at $15.96, with 892,397 shares traded. T's current last sale is 71.73% of the target price of $22.25. 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 slides as Fed's hawkish talk snuffs two-day rally By Herbert Lash, Ankika Biswas and Bansari Mayur Kamdar Oct 5 (Reuters) - Wall Street stocks slid on Wednesday, ending the biggest two-day rally since 2020, after data showed U.S. labor demand remained strong and as Federal Reserve officials stuck to their hawkish message that interest rates will stay higher for longer. U.S. private employers stepped up hiring in September, the ADP National Employment report on Wednesday showed, suggesting rising rates and tighter financial conditions have yet to curb labor demand as the Fed battles high inflation. The Institute for Supply Management's services industry employment gauge shot up in another sign labor remains strong as t\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 = 0.0305 (i.e., a 3.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0305 = 3.2746, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030538, "expected_loss": 0.030538, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210503_0056", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2021-05-03", "context_summary": "MORT: 60-day history, VaR(99%)=-0.0305, max drawdown threshold=10%.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0026, std=0.0134, worst_day=-0.0363\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MORT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0305 (i.e., a 3.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0305 = 3.2783, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030504, "expected_loss": 0.030504, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20180129_0059", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2018-01-29", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0064, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0021, std=0.0053, worst_day=-0.0069\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-01-26] [\"Qualcomm Fined by EC, Signs MoU With 4 Handset Developers\", \"Semiconductors finish week strong on Intel earnings\", \"Semiconductors finish week strong on Intel earnings\", \"Qualcomm Fined by EC, Signs MoU With 4 Handset Developers\", \"Qualcomm Fined by EC, Signs MoU With 4 Handset Developers Qualcomm Inc.QCOM recently signed a memorandum of understanding with four leading Chinese handset developers, namely, Lenovo Mobile Communication Technology, Ltd., Guangdong OPPO Mobile Telecommunications Corp., Ltd., vivo Communication Technology Co., Ltd. and Xiaomi Communications Co., Ltd., for a multi-year sale of RF Front-End solutions. The value of the deal is more than $2 billion. Notably, China is the most important market for Qualcomm after the United States. However, the company also received a bad news. The EC (European Commission), the regulatory authority of the European Union, has slapped a fine of \\u20ac997 million (approximately $1.24 billion) on Qualcomm over anticompetitive practices related to mobile chipset sale. The EC claims that an iPhone/iPad modem exclusivity deal between Qualcomm and Apple Inc. AAPL , which lasted from 2011 to the end of 2016, amounted to anti-competitive behavior. Qualcomm abused its dominant market position for 4G LTE chipset and payed significantly to Apple to secure modem exclusivity. Another Major Recent Development Only a week ago, in a major relief to Qualcomm, the EC gave its nod to the company for the acquisition of NXP Semiconductors NV NXPI with some restrictive conditions. At the same time, South Korea's Fair Trade Commission also gave its nod for the deal. Notably, the deal has already been approved by the U.S. antitrust authorities. Only China is left to give its approval, which Qualcomm believes it will get very soon. The major positive of the contract is that it will enable Qualcomm to diversify its business model. The company is a leader in the mobile chipset market for smartphones and tablets. NXP, on the other hand, manufactures chips for next-generation automotive, industrial and Internet of Things (IoT) segments. Therefore, its acquisition of NXP will help Qualcomm to diversify into highly lucrative end markets such as auto, secured devices, connectivity and secure payments. These segments offer high-margin businesses with strong potential for future growth. The takeover will also push Qualcomm up the ranks to the second position after Intel Corp. INTC in terms of sales in the broader global semiconductor market. Moreover, the combined entity will emerge a formidable challenger to other large semiconductor firms like Broadcom Ltd. AVGO , Analog Devices Inc. ADI and ARM Holdings. Likely Effect on Broadcom's Hostile Bid On Nov 6, 2017, Broadcom submitted a bid to acquire Qualcomm for a consideration of $130 billion (including $25 billion in net debt). On Nov 13, Qualcomm's board of directors turned down the offer on grounds of inadequacy, as it is currently the largest mobile chipset maker globally.\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 = 0.0064 (i.e., a 0.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0064 = 15.6269, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.006399, "expected_loss": 0.006399, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181008_0062", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-10-08", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1380, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0085, std=0.0810, worst_day=-0.1449\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7249", "answer_numeric": 0.7249, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1380 (i.e., a 13.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1380 = 0.7249, capped at 1.0.\nMaximum position size = 0.7249 (72.5% of portfolio).", "metadata": {"var_99": -0.13795, "expected_loss": 0.13795, "max_drawdown_threshold": 0.1, "position_size": 0.7249, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20211029_0065", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2021-10-29", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.1320, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0015, std=0.0471, worst_day=-0.1581\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-27] \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": "0.7576", "answer_numeric": 0.7576, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1320 (i.e., a 13.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1320 = 0.7576, capped at 1.0.\nMaximum position size = 0.7576 (75.8% of portfolio).", "metadata": {"var_99": -0.132003, "expected_loss": 0.132003, "max_drawdown_threshold": 0.1, "position_size": 0.7576, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20211008_0068", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2021-10-08", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.1005, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0042, std=0.0385, worst_day=-0.1106\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9951", "answer_numeric": 0.9951, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1005 (i.e., a 10.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1005 = 0.9951, capped at 1.0.\nMaximum position size = 0.9951 (99.5% of portfolio).", "metadata": {"var_99": -0.10049, "expected_loss": 0.10049, "max_drawdown_threshold": 0.1, "position_size": 0.9951, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160804_0071", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2016-08-04", "context_summary": "BNDX: 60-day history, VaR(99%)=-0.0040, max drawdown threshold=10%.", "question": "Asset: BNDX\nDaily returns (past 60 days): mean=0.0004, std=0.0022, worst_day=-0.0041\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNDX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0040 (i.e., a 0.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0040 = 25.0127, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.003998, "expected_loss": 0.003998, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220915_0076", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2022-09-15", "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=0.0046, std=0.0598, worst_day=-0.1198\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-14] \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": "0.9160", "answer_numeric": 0.916, "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 = 0.9160, capped at 1.0.\nMaximum position size = 0.9160 (91.6% of portfolio).", "metadata": {"var_99": -0.109165, "expected_loss": 0.109165, "max_drawdown_threshold": 0.1, "position_size": 0.916, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20200106_0079", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2020-01-06", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0801, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0073, std=0.0271, worst_day=-0.1135\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0801 (i.e., a 8.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0801 = 1.2478, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080139, "expected_loss": 0.080139, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20161101_0082", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2016-11-01", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0290, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0002, std=0.0114, worst_day=-0.0341\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-10-31] [\"Music industry still plagued by pirated CDs Even in the digital era there are plenty of music fans who still buy old-fashioned compact discs for more than $10 a pop. But the money that shoppers have been spending on CDs lately hasn't necessarily been going to the artists and record labels who created the music.\", \"Apple hikes U.K. prices 20% \\u2014 blame Brexit Consumer confidence in the U.K. slides in October Apple becomes the latest corporate giant to raise prices in the U.K. to address the pound plunge and the moves are starting to squeeze British households.\", \"Apple\\u2019s underwhelming Mac event was lacking in innovation Opinion: Incremental improvements and annoying changes Apple Inc. hosted one of its most boring product launch events in recent years, one that is not likely to give investors confidence that innovation is alive and well at Apple\", \"Apple demolished by Microsoft at their respective PC events Microsoft hailed as the winner over Apple following back-to-back events Apple\\u2019s PC event was underwhelming compared with Microsoft\\u2019s, and many designers are for the first time turning to Windows over iOS.\", \"\\u2018Game changer\\u2019 could derail a traditionally great stretch for stocks Critical information ahead of the U.S. market\\u2019s open Thanks to the FBI\\u2019s fresh probe into Hillary\\u2019s emails, it looks like that volatility traders have been missing is back, and there\\u2019s nothing to suggest we won\\u2019t see more of the same as we careen toward Election Day\", \"Nomura Ups Qualcomm To Buy, Praises NXP Semi Deal Qualcomm (QCOM) is rising Monday, after Nomura analyst Romit Shah gave the NXP Semi (NXPI) deal his blessing and upgraded the stockShah raised his rating on the stock from Neutral to Buy and boosted his price target from $55 to $80, writing that NXP is a good business that will add \\u201ca ton\\u201d of scale for Qualcomm, expanding its total addressable market and creating new opportunities for its Snapdragon suite of chips.\", \"Four Key Takeaways From Apple\\u2019s 10K RBC Capital Markets\\u2019 Amit Daryanani reviewed Apple\\u2019s (AAPL) recently released 10K filing, and reiterated an Outperform rating and $125 price target on the stock Monday.He writes that there are a number of key findings from the stock, including the fact that initial fiscal 2017 capex spending is forecast up 26% year over year and total manufacturing and purchase commitments are up 3% year over year. The company has already spent some $133 billion of its $175 billion share repurchase authorization as well.\", \"Is buying a pair of Ivanka Trump shoes a political endorsement? A new survey found more than half of millennial women would still buy her shoes A new survey found more than half of millennial women would still buy shoes from the daughter of current Republican presidential candidate.\", \"Has Apple become a value play? In the wake of its earnings report, the stock may be flashing a buy signal.\", \"Could Apple Buy Time Warner? Would \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 = 0.0290 (i.e., a 2.90% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0290 = 3.4456, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029023, "expected_loss": 0.029023, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190619_0085", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-06-19", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0642, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0092, std=0.0378, worst_day=-0.0686\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0642 (i.e., a 6.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0642 = 1.5585, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064165, "expected_loss": 0.064165, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190729_0090", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2019-07-29", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0202, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0000, std=0.0079, worst_day=-0.0228\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-26] [\"SoftBank launches another tech megafund, backed by Apple, Microsoft Second Vision Fund, with about $108 billion secured, will invest in AI SoftBank Group Corp. said it would start a second technology megafund and has secured $108 billion in commitments from investors including Apple Inc., Japanese banks, Taiwanese investors and Kazakhstan\\u2019s sovereign-wealth fund.\", \"SoftBank Unveils Plans For $108 Billion Vision Fund 2 The Japanese holding company said investors in the new fund include Apple, Microsoft, Foxconn, and others.\", \"Asian markets pull back as Japan-South Korea trade tensions escalate Japan reportedly will diminish South Korea\\u2019s trade status Asian shares were lower Friday as investors continued to watch the brewing trade conflict between China and the U.S., and any signs of what\\u2019s in store from central banks.\", \"Tesla\\u2019s key executive departures, in one handy list News that Tesla\\u2019s Chief Technology Officer J.B. Straubel is stepping down from that role is just the latest move in a long list The departure of Tesla Inc.\\u2019s J.B. Straubel is a song Tesla has heard before \\u2014 numerous times.\", \"Even Intel doesn\\u2019t seem to know what\\u2019s going to happen with Intel Amid sale of modem-chip business to Apple and a forecast flip-flop, Intel seems to be unsure of path for it, or the chip industry, in second half In the semiconductor industry, \\u201cmixed signal\\u201d usually refers to chips that combine digital and analog circuitry. When referring to Intel Corp. right now, though, the standard definition of that phrase is more apt.\", \"Alphabet earnings show Google revenue growth rebounding, stock pops higher Profit and revenue beat expectations amid reported antitrust scrutiny Alphabet Inc. shares jumped 7% in after-hours trading Thursday after the online giant announced better-than-expected financial results.\", \"Facebook tops Amazon and Google in second-quarter lobbying spending Partisan split means \\u2018we see little room for any legislation to actually materialize in the near term,\\u2019 analysts say Facebook spent $4.1 million on lobbying Washington in the second quarter, topping the outlays by other so-called FAANG companies and keeping the tech giant on pace for another record year of spending to influence lawmakers and regulators.\", \"Google Needs to Buy Back Even More Stock Wall Street cheered the latest numbers, but Alphabet\\u2019s repurchase program barely exceed its stock-based compensation, which totaled $5.5 billion in the first half of 2019.\", \"Are you a \\u2018zombie eater\\u2019? It could be bad for your health Distracted diners who stare at screens tend to eat more calories and choose fattier foods Distracted diners who stare at screens tend to eat more calories and choose fattier foods.\", \"Intel\\u2019s earnings beat gets fairly cold reception from analysts Surprise rise in PC sales overshadowed by new chip rollout pace, AMD challenges Intel Corp. shares slip Friday following a big earnings beat\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 = 0.0202 (i.e., a 2.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0202 = 4.9469, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020215, "expected_loss": 0.020215, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160303_0093", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2016-03-03", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1798, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0007, std=0.0903, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-03-02] [\"Why Are Stocks Rising? Bond Market Has Answer Equities jumped 9% in two weeks, thanks to credit bounce. But debt can backfire, as energy sector shows.\", \"What to buy as the bulls get to partying again Critical information ahead of the U.S. market\\u2019s open The happy-clappy start to this month has left investors wondering if it\\u2019s actually OK to celebrate. If March is going to keep looking like a party for stock bulls, here\\u2019s how to join in.\", \"Apple Pay Most Requested By Merchants Adopting Mobile Wallets: Piper Jaffray Piper Jaffray\\u2019s Gene Munster has an update on Apple\\u2019s (AAPL) Apple Pay, writing that as merchants integrate mobile wallets, Apple Pay is the most requested.Munster surveyed more than 500 merchant processing channel partners, and found that 44% of their point of sale merchant customers are using or have requested information about mobile wallet solutions, and 67% of those wanted Apple Pay.That figure dwarfs the 18% that requested Android Pay/Google Wallet (GOOGL), 8% for PayPal (PYPL) and 7% for Samsung Pay.Read More \\u00bb\", \"Tech Today: Apple Pay Popularity, WhatsApp Ending BBRY Support, Zynga CEO Leaves Here are some things going on in your world of tech:Apple (AAPL) is lower, although Piper Jaffray writes that Apple Pay is the most requested mobile wallet from merchants.The FBI and Apple continue to testify before Congress in their battle over an encrypted iPhone used by a California shooter; the government agency admits it made a mistake early in the investigation. Microsoft (MSFT) spoke out again in support of Apple today.Read More \\u00bb\", \"Charting the U.S. markets\\u2019 March breakout Focus: The traditional sector leaders, XLF, QQQ, IYT, AAPL, ETN, KND, CMI The major U.S. benchmarks have broken out to start March, though with a move that gets low style marks. Nonetheless, each index has reached less-charted territory, placing distance atop its 50-day moving average.\", \"S&P Ups Technology Sector To Buy; Likes Apple, Google S&P Global Intelligence\\u2019s Scott Kessler and his team upgrade the tech sector from Marketweight to Overweight , writing that solid fundamentals, attractive valuations and strong balance sheets make tech names a buy.Kessler writes that while tech stocks have been punished of late, much of the selloff is an overreaction, as concerns about the global economy and technology growth are already more than reflected in stocks.S&P\\u2019s own data shows that S&P 500 IT Sector earnings rose 5% in 2015, even with the impact of a higher U.S. dollar to its large overseas business, and the highest net margins of any sector. Tech is projected to climb 2.8% this year, once again trumping the broader market. Yet its 2016 P/E is just 15.6 times, compared to 16.3 times for the S&P 500 as a whole.Read More \\u00bb\", \"Money managers selling off more popular stocks, creating new positions Apple only widely held stock seeing increased position Money managers are looking for a few new stock ideas as funds\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": "0.5562", "answer_numeric": 0.5562, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1798 (i.e., a 17.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1798 = 0.5562, capped at 1.0.\nMaximum position size = 0.5562 (55.6% of portfolio).", "metadata": {"var_99": -0.17978, "expected_loss": 0.17978, "max_drawdown_threshold": 0.1, "position_size": 0.5562, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180703_0104", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2018-07-03", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0129, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0009, std=0.0064, worst_day=-0.0141\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-02] [\"Why there may never be a Netflix of videogames Years into parallel efforts to deliver videogame streams from the cloud, latency \\u2014 and doubts \\u2014 persist Plenty of companies, from multibillion-dollar tech titans to startups, are trying to develop a streaming service for videogames that could do to consoles and individual videogame sales what Netflix did to DVDs and the cable bundle. But the issues that stand in the way could keep it from ever happening as imagined.\", \"Tech Today: Can Tesla Keep It Up? Dell Going Public, Facebook\\u2019s Instagram Numbers Tesla says it hit its goal of 5,000 Model 3s per week although some wonder if it's sustainable, Dell is going public again via a stock swap and CEO Michael Dell says the company will exploit a broad IT infrastructure spending trend, Lumentum is set to ride the expansion of \\\"augmented reality\\\" in Apple iPhones and other devices, and Facebook can see a big boost in revenue as its Instagram unit closes the pricing gap with other properties according to Ken Sena of Wells Fargo.\", \"Nasdaq supported by rebound in tech stocks; Apple up 0.8%\", \"NBA Veteran Jason Kidd Takes a Swing at Tech Investing Basketball legend Jason Kidd, like a growing number of other retired and current professional athletes, has invested in a tech startup. The appeal of making a bet on tech is proving to be irresistible. He cites the two-time defending NBA champion Golden State Warriors, whose players are dabbling in tech startups while lending star brand recognition to those companies.\", \"Taiwan Semi to Ride Wave of Custom AI Chips, Says Susquehanna Taiwan Semi has been the contract manufacturer to Apple and Qualcomm and Nvidia and others for a long time, but it has a new opportunity to make revenue off of the emerging industry of artificial intelligence chips, says Susquehanna's Mehdi Hosseini.\", \"U.S. stocks end higher as tech shares stage late-session rally U.S. stocks ended higher on Monday, reversing an early decline as a rebound in technology shares helped to offset ongoing uncertainty surrounding trade policy. The Dow Jones Industrial Average rose 0.1%. The S&P 500 ended 0.3% higher. The Nasdaq Composite Index gained 0.8%. Major indexes had opened lower in a broad decline, but equities improved throughout the session, and seven of the 11 primary S&P 500 sectors ended in positive territory. Leading the move higher was technology stocks, which rose 1% as the top-performing industry group of the day. Among the notable gainers, Apple Inc. added 1.1% while Microsoft Corp. was up 1.4%. Nvidia Corp. popped 2.3%.\", \"Tech sector contributed all of the stock market gains so far in 2018 Amazon.com accounted for more than a third of S&P 500 gains The equity markets\\u2019 story of 2018, much like last year, was and still is the one of FAANGs\\u2014high-flying large technology companies\", \"Why Apple stock is still a buy \\u2014 even at $200 a share Three key valuation measures prove the stock\\u2019s long-term value Three key v\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 = 0.0129 (i.e., a 1.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0129 = 7.7385, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012922, "expected_loss": 0.012922, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180607_0111", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2018-06-07", "context_summary": "TLH: 60-day history, VaR(99%)=-0.0065, max drawdown threshold=10%.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=0.0000, std=0.0040, worst_day=-0.0078\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 = 0.0065 (i.e., a 0.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0065 = 15.4273, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.006482, "expected_loss": 0.006482, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20171219_0114", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2017-12-19", "context_summary": "LINK-USD: 39-day history, VaR(99%)=-0.1712, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 39 days): mean=0.0168, std=0.0964, worst_day=-0.1767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5840", "answer_numeric": 0.584, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1712 (i.e., a 17.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1712 = 0.5840, capped at 1.0.\nMaximum position size = 0.5840 (58.4% of portfolio).", "metadata": {"var_99": -0.171239, "expected_loss": 0.171239, "max_drawdown_threshold": 0.1, "position_size": 0.584, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170414_0117", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2017-04-14", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0098, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0004, std=0.0045, worst_day=-0.0141\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-04-13] [\"CEO average pay climbed more than $1 million in 2016 Warren Buffett was the lowest-earning CEO on the list, though his company was the top in revenue The Equilar 100 annual survey found that 2016 was a good year for CEO pay, with average compensation of $16.6 million.\", \"BlackBerry will likely spend surprise $815 million arbitration award on acquisitions Analysts say the Canadian device maker will pocket the entire sum from a binding arbitration decision against Qualcomm Canadian mobile device maker will pocket the entire sum awarded in a dispute with Qualcomm and it will bolster its balance sheet, analysts agree.\", \"Apple loses top spot on Laptop Magazine\\u2019s best brands ranking for 2017 Lenovo takes top spot, followed by Asus, Dell and HP Apple drew only \\u2018modest\\u2019 reviews for its laptop lineup, because of its expensive products and lack of ports.\", \"Our Review of Apple's New Video Editor The \\\"Clips\\\" video-editing app has some of the magic you'd expect from Apple.\", \"PC companies must sell to businesses or die, but what about Apple? Opinion: First-quarter PC shipment reports warn that relying on consumers won\\u2019t work, except for one company Personal computer makers not involved in the corporate market are likely to face consolidation or some other form of death, as consumers are dramatically slowing their purchases of PCs.\", \"An Apple buyout of Disney is 'logical,' has 'greater than 0%' probability--RBC Capital\", \"Why Apple should buy Disney, says RBC It would be \\\"logical\\\" for Apple Inc. to buy Walt Disney Co. , as it would allow Apple to replicate its music-iTunes strategy in the content-media space, said analyst Amit Daryanani at RBC Capital. While the odds of deal are \\\"low,\\\" Daryanani said he sees a \\\"confluence of events that make an acquisition of [Disney] a 'greater than 0%' probability event.\\\" He suggested the odds could increase if Apple is able to access the more-than $200 billion in cash it has overseas through a repatriation tax holiday. Disney's market capitalization was about $178.7 billion, according to FactSet. Daryanani said a deal would accelerate Apple's push into services and content, with Apple instantly leapfrogging Netflix Inc. , Amazon.com Inc. and Alphabet Inc.'s YouTube in content. \\\"There are plenty of factors to consider, but such a deal would create a tech/media juggernaut like no other and instantly scale [Apple's] services, content and media portfolio, which would make the case for a higher valuation,\\\" Daryanani wrote in a note to clients. Apple's stock slipped 0.3% and Disney shares inched up 0.1% in premarket trade. Year to date, Apple's stock has soared 22%, Disney shares have climbed 8.5% and the Dow Jones Industrial Average has gained 4.7%.\", \"Apple: A $237B Bid for Disney Not a Bad Idea, Says RBC RBC Capital\\u2019s Amit Daryanani, who covers Apple (AAPL), today reflects on the chances the company might try to buyWalt Disney (DIS), arguing there is a better than 0% chance, because Appl\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 = 0.0098 (i.e., a 0.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0098 = 10.1968, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.009807, "expected_loss": 0.009807, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20191126_0122", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2019-11-26", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1226, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0078, std=0.0615, worst_day=-0.1261\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-25] [\"Noteworthy ETF Outflows: TQQQ, CMCSA, CSCO, ADBE Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel, one standout is the ProShares ProShares UltraPro QQQ (Symbol: TQQQ) where we have detected an approximate $92.8 million dollar outflow -- that's a 2.5% decrease week over week (from 49,850,000 to 48,600,000). Among the largest underlying components of TQQQ, in trading today Comcast Corp (Symbol: CMCSA) is off about 1.9%, Cisco Systems Inc (Symbol: CSCO) is up about 1%, and Adobe Inc (Symbol: ADBE) is higher by about 1.1%. For a complete list of holdings, visit the TQQQ Holdings page \\u00bb The chart below shows the one year price performance of TQQQ, versus its 200 day moving average: Looking at the chart above, TQQQ's low point in its 52 week range is $30.32 per share, with $76.47 as the 52 week high point \\u2014 that compares with a last trade of $76.36. 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 experienced notable outflows \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Why Adobe's Revenue Growth Rate Looks Poised To Increase In 2020 Adobe\\u00c2 (NASDAQ: ADBE)\\u00c2 makes money by selling software for creative content and marketing purposes with a focus on user experience. The company\\u00e2\\u0080\\u0099s products are offered as subscription-based service and through licenses.\\u00c2 Adobe competes with Apple, Autodesk, Avid, Corel, Microsoft, Affinity, Quark in its Digital Media offerings, and Google, IBM, Oracle, salesforce.com, SAP, SAS, Teradata, Shopify in its Digital Experience segment. Adobe\\u2019s strong results for the third quarter highlight the resilience of its revenue streams despite an uncertain macro-environment.\\u00c2 We highlight trends in Adobe\\u2019s Revenues over the years along with our forecast for 2019 and 2020 in an interactive dashboard. We believe that the company\\u2019s\\u00c2 2 core operating segments \\u2013 Digital Media as well as Digital Experience \\u2013 have significant growth prospects, which will help revenues\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": "0.8154", "answer_numeric": 0.8154, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1226 (i.e., a 12.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1226 = 0.8154, capped at 1.0.\nMaximum position size = 0.8154 (81.5% of portfolio).", "metadata": {"var_99": -0.122641, "expected_loss": 0.122641, "max_drawdown_threshold": 0.1, "position_size": 0.8154, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181121_0132", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2018-11-21", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0427, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=-0.0024, std=0.0165, worst_day=-0.0427\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-11-20] [\"Asian stocks drop as tech pullback, Nissan CEO\\u2019s arrest take toll Auto, electronics sectors weigh on Nikkei; tech stocks sink Hang Seng Asian stock markets fell Tuesday, following tech-led declines on Wall Street.\", \"Netflix\\u2019s \\u2018death cross\\u2019 is the third for FAANG stocks and Nasdaq Composite is next Amazon and Apple are the last FAANGs to not produce a \\u2018death cross\\u2019 while the Nasdaq Composite should produce one next week Netflix\\u2019s stock has fallen far enough and long enough to produce its first \\u201cdeath cross\\u201d pattern in nearly three years, becoming the third member of the FAANG technology darlings to suffer that bearish technical fate.\", \"Apple\\u2019s Tim Cook says tech regulation \\u2018inevitable\\u2019 because free market isn\\u2019t working In interview, CEO also says Silicon Valley has dropped the ball on gender diversity Regulation of tech companies is coming, Apple Inc. Chief Executive Tim Cook says, because the free market \\u201cis not working.\\u201d\", \"Apple's stock falls 2.1% premarket, on track to open in bear-market territory\", \"Apple's stock on track to open in bear-market territory, joining all other FAANG stocks Shares of Apple Inc. slumped 2.6% in premarket trade Tuesday, extending the previous session's losses to a 4 1/2-month low and to put them on track to open in bear-market territory. Many on Wall Street define a bear market as a decline of 20% or more from a bull-market high. On that basis, Apple's stock would be in a bear market with a close at or below $185.65, which is 20% below the Oct. 3 record close of $232.07. On Monday, the stock dipped below that threshold in intraday trade, but pared losses to close down 19.9% from its record close. Apple's stock hasn't been in a bear market since it came out of the last one on Aug. 15, 2016. Apple is the only FAANG stock that hasn't already entered a bear market. Shares of Facebook Inc. and Netflix Inc. have been in bear markets since July 30, Amazon.com Inc. has been in a bear market since Oct. 29 and Google parent Alphabet Inc. closed in a bear market on Monday. Meanwhile, the Nasdaq Composite closed Monday 13.3% below its Aug. 29 record close of 8,109.69 and the S&P 500 ended Monday 8.2% below its Sept. 20 record of 2,930.75.\", \"Apple target cut at Goldman amid concerns of 'deteriorating demand' Goldman Sachs analyst Rod Hall cut his price target on Apple Inc. shares to $182 from $209 late Monday amid the latest reports of iPhone production cuts coming from the Wall Street Journal. That report suggested \\\"deteriorating demand relative to what the company had initially expected\\\" for the new iPhones, according to Hall's take, and he sees \\\"additional twists\\\" to what was reported. \\\"In addition to weakness in demand for Apple's products in China and other emerging markets it also looks like the balance of price and features in the iPhone XR may not have been well-received by users outside of the U.S.,\\\" wrote Hall, who lowered his Apple \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 = 0.0427 (i.e., a 4.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0427 = 2.3410, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042717, "expected_loss": 0.042717, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201021_0135", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2020-10-21", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1411, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0018, std=0.0516, worst_day=-0.1683\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7086", "answer_numeric": 0.7086, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1411 (i.e., a 14.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1411 = 0.7086, capped at 1.0.\nMaximum position size = 0.7086 (70.9% of portfolio).", "metadata": {"var_99": -0.141124, "expected_loss": 0.141124, "max_drawdown_threshold": 0.1, "position_size": 0.7086, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200911_0138", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2020-09-11", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0383, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0020, std=0.0141, worst_day=-0.0383\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-10] [\"$718 mln options unwind signals more caution on tech stocks By April Joyner NEW YORK, Sept 10 (Reuters) - A large options player unwound bets on several technology-related companies on Thursday, offering another sign of the market's recently diminished appetite for shares in the sector. The unidentified investor took off around $718 million of notional value in bullish options spreads known as risk reversals in Facebook Inc FB.O, Netflix Inc NFLX.O and Adobe Inc ADBE.O, according to a Reuters analysis based on data from Susquehanna Financial Group. The investor partially closed a similar position in Saleforce.com Inc CRM.N on Tuesday. The trades were structured differently than positions widely attributed to SoftBank Group Corp 9984.T, whose big bets on equity derivatives tied to tech firms came to light last week. Thursday's unwinds were partial, and the positions still have a notional value of around $1.66 billion, the analysis showed. Still, investors following large institutional trades in tech-related names may view the moves as a bearish signal, said Christopher Murphy, co-head of derivatives strategy at Susquehanna Financial Group. \\\"Investors have been watching this big bullish flurry of trades that happened earlier in August, looking for signs of it beginning to be closed,\\\" he said. \\\"It could have a negative impact on sentiment.\\\" Robust options activity from institutions like SoftBank and hordes of retail investors is widely believed to have contributed to last month's big run-up in stocks, as well as a recent sell-off that the Nasdaq confirmed on Tuesday was a correction, commonly defined as a decline of 10% or more from an index's high. U.S. stocks closed lower after a choppy session on Thursday as heavyweight tech-related stocks resumed their decline following a sharp rebound the previous session. Overall, demand for protective put options has risen among tech-related names. But frothiness still remains in call options, which are used to position for upside in stocks, for certain companies such as Apple Inc AAPL.O and Tesla Inc TSLA.O, said Arnim Holzer, macro and correlation defense strategist at EAB Investment Group. Skew, a measure that gauges demand for puts in relation to calls, on Tesla options turned negative once again on Thursday, according to data from Trade Alert, reflecting surging demand for calls. \\\"There is a fair amount of call skew in some of those names,\\\" Holzer said. \\\"That gives us a sense that there can still be some downward pressure, relative to the S&P, in those very large-cap tech names.\\\" Most of the trades attributed to SoftBank, which are seen as bullish positions on tech-related names, remain in place. Some have been moved to higher strike prices in an apparent bet on a further rise in the underlying shares. SoftBank declined to comment. The trades attributed to SoftBank are call spreads - a combination of a put purchase and a put sale - several of which expire in November. By contrast, the bullish r\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 = 0.0383 (i.e., a 3.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0383 = 2.6134, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.038264, "expected_loss": 0.038264, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20211022_0141", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2021-10-22", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0190, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0006, std=0.0074, worst_day=-0.0212\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-21] [\"Customer engagement platform Batch raises $23 million after years of bootstrapping If you\\u2019ve been working in the French tech ecosystem, you may remember a startup called AppGratis. From the team that brought you AppGratis, Batch is a customer engagement platform that has been operating under the radar for many years. It\\u2019s a customer engagement platform that competes with Braze as well as big enterprise solutions from Salesforce, Adobe, Oracle, IBM and Microsoft.\", \"Apple will require unvaccinated employees to test for COVID-19 daily Apple will require all unvaccinated corporate employees to be tested for COVID-19 every time they have to work in the office.\", \"The Morning After: Will Facebook change its name? Today\\u2019s headlines: Some Windows 11 users can start testing Android apps, Netflix CEO says he 'screwed up' on Dave Chappelle as employees walk out, \\u2018Cyberpunk 2077' PS5 and Xbox Series X/S upgrades delayed until 2022.\", \"Apple will require unvaccinated employees to test for COVID-19 daily Apple has yet to issue a mandate similar to Google's that would require all employees to be vaccinated, but it's tightening its COVID-19 protocols nonetheless. According to Bloomberg, the tech giant will start requiring all unvaccinated corporate employees to be tested for COVID-19 every time they have to work in the office instead of working from home. Back in September, Bloomberg reported that Apple asked employees to share their vaccination status voluntarily.\", \"Apple's AirTags are 10 percent off at Woot today Apple's AirTags are down to $26 each when you buy them from Woot today only.\", \"Meet the 2021 Women in Technology Hall of Fame Inductees Female Executives and Leaders to be Honored for Their Impact and Achievements Featured Image for WITI - Women in Technology International Featured Image for WITI - Women in Technology International LOS ANGELES, Oct. 21, 2021 (GLOBE NEWSWIRE) -- Women in Technology International (WITI), the leading organization for the advancement and inclusion of women in business and technology, today announced its eight inductees into the 2021 Women in Technology Hall of Fame. The honorees will be inducted dur\", \"Product Marketing Alliance: From $0 to $1M+ ARR in 12 months: product marketing is the world's fastest-growing job role The role of product marketing is on the rise. It's no longer seen as a nice-to-have, it's a company commodity for forward-thinking, fast-growing, market-dominating organizations worldwide.\", \"Google lowers Play Store fees to 15% on subscription apps, as low as 10% for media apps Google is lowering commissions on all subscription-based businesses on the Google Play Store, the company announced today. Previously, the company had followed Apple's move by reducing commissions from 30% to 15% on the first $1 million of developer earnings. Instead of charging them 30% in the first year, which lowers to 15% in year two and beyond, Google says developers will only be charged 15% from day o\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 = 0.0190 (i.e., a 1.90% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0190 = 5.2642, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018996, "expected_loss": 0.018996, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201110_0146", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2020-11-10", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0551, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0007, std=0.0226, worst_day=-0.0592\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0551 (i.e., a 5.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0551 = 1.8150, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.055096, "expected_loss": 0.055096, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20201229_0149", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2020-12-29", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0848, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0116, std=0.0437, worst_day=-0.0909\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0848 (i.e., a 8.48% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0848 = 1.1792, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.084803, "expected_loss": 0.084803, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20201117_0153", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-11-17", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1145, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0021, std=0.0521, worst_day=-0.1372\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.8737", "answer_numeric": 0.8737, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1145 (i.e., a 11.45% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1145 = 0.8737, capped at 1.0.\nMaximum position size = 0.8737 (87.4% of portfolio).", "metadata": {"var_99": -0.114452, "expected_loss": 0.114452, "max_drawdown_threshold": 0.1, "position_size": 0.8737, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20150916_0156", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2015-09-16", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1825, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0032, std=0.1055, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-09-15] [\"Chip Stocks Up Despite Falling Semiconductor Billings\", \"Chip Stocks Up Despite Falling Semiconductor Billings\", \"Is Apple, Inc.'s \\\"3D Touch\\\" Supplier a Buy? As expected, the headline selling feature in Apple 's new iPhone 6s and 6s Plus models will be 3D Touch, the rebranded technology that integrates pressure sensitivity into the display to unlock a whole new slew of interface interactions. Seeing as how investing in Apple component suppliers is a popular investing trend these days, investors can't help wondering if Analog Devices is worth looking at, since the smaller analog-chip maker is reportedly the exclusive supplier of the microcontroller that drives the 3D Touch display. Is Analog Devices a buy? The Street has been busy tackling this very question. Last month before earnings, BlueFin Research Partners estimated that overall Force/3D Touch revenues could add up to an additional $500 million in fiscal 2016. The firm notes that Analog Devices has had some trouble finding customers willing to pay for its superior performance, but Apple fits the bill quite nicely. Seeing as how the iPhone 6s and 6s Plus production ramp likely started a few months ago, it was no surprise when Analog then reported record revenues of $863 million in its fiscal third quarter. It was also pretty obvious where the strength was coming from as well. Source: SEC filings. In no uncertain terms, the consumer segment stole the show. Naturally, Analog Devices has to speak vaguely when referring to Apple on the conference all, but it's pretty clear who it is. Here's CFO David Zinsner: Not only were the quarter's results better than expected, but Analog Devices also issued upbeat guidance. In the coming quarter, revenue is expected in the range of $880 million to $940 million, which utterly crushed the consensus forecast of $876 million. There's more where that came from Following the strong results, SunTrust Robinson Humphrey boosted its rating on Analog Devices to \\\"buy\\\" while increasing its price target from $68 to $71. The firm believes that Apple Force/3D Touch will proliferate throughout Apple's lineup in the coming quarters, and Analog Devices will be a key beneficiary as the incremental revenue adds up. This is an entirely reasonable conjecture, since Apple tends to introduce innovative new technologies in one major product before bringing it to the rest of the product portfolio. Usually, Apple does this with the iPhone first, but this time around it introduced Force Touch first in Apple Watch and the new MacBooks before the iPhone (Analog Devices supplies the chips in both of these devices). That being said, I fully expect the iPad to get 3D Touch next, although it'll take more time to implement the technology on such large displays. RBC Capital also rates Analog Devices \\\"outperform\\\" with a $70 price target. It seems that the Street is mostly bullish on Analog Devices as Apple ramps up Force/3D Touch. Even though Apple is contributing heavily to the near-te\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": "0.5480", "answer_numeric": 0.548, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1825 (i.e., a 18.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1825 = 0.5480, capped at 1.0.\nMaximum position size = 0.5480 (54.8% of portfolio).", "metadata": {"var_99": -0.182471, "expected_loss": 0.182471, "max_drawdown_threshold": 0.1, "position_size": 0.548, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190819_0164", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2019-08-19", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0188, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0007, std=0.0081, worst_day=-0.0220\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-08-16] [\"7 Stocks To Watch For August 16, 2019\", \"KeyBanc Maintains Overweight on Applied Materials, Lowers Price Target to $54\", \"A Peek Into The Markets: US Stock Futures Signal Higher Start On Wall Street\", \"26 Stocks Moving in Friday's Pre-Market Session\", \"Applied Materials shares are trading lower after the company reported Q3 earnings.\", \"Craig-Hallum Downgrades Applied Materials to Hold\", \"7 Technology Stocks Moving In Friday's Pre-Market Session\", \"Benzinga Pro's Top 10 Most-Searched Tickers For Morning of Friday., August 16, 2019\", \"Benzinga's Top Upgrades, Downgrades For August 16, 2019\", \"Morgan Stanley Maintains Equal-Weight on Applied Materials, Raises Price Target to $43\", \"Applied Materials Posts Solid Q3 Results, But Faces Near-Term Headwinds, KeyBanc Says\", \"A Look At Benzinga Pro's Most-Searched Tickers For August 16, 2019\", \"A Look At Benzinga Pro's Most-Searched Tickers For August 16, 2019\", \"Applied Materials Posts Solid Q3 Results, But Faces Near-Term Headwinds, KeyBanc Says\", \"Morgan Stanley Maintains Equal-Weight on Applied Materials, Raises Price Target to $43\", \"Benzinga's Top Upgrades, Downgrades For August 16, 2019\", \"Benzinga Pro's Top 10 Most-Searched Tickers For Morning of Friday., August 16, 2019\", \"7 Technology Stocks Moving In Friday's Pre-Market Session\", \"Craig-Hallum Downgrades Applied Materials to Hold\", \"Applied Materials shares are trading lower after the company reported Q3 earnings.\", \"26 Stocks Moving in Friday's Pre-Market Session\", \"A Peek Into The Markets: US Stock Futures Signal Higher Start On Wall Street\", \"KeyBanc Maintains Overweight on Applied Materials, Lowers Price Target to $54\", \"7 Stocks To Watch For August 16, 2019\", \"Technology Sector Update for 08/16/2019: CSCO,PHUN,NVDA,AMAT Top Tech Stocks MSFT +1.52% AAPL +2.23% IBM +1.22% CSCO +1.63% GOOG +0.98% Technology stocks held on to their prior gains this afternoon, with shares of tech stocks in the S&P 500 climbing nearly 1.8% while the Philadelphia Semiconductor Index was rising almost 2.9%. Among technology stocks moving on news: (+) Cisco Systems (CSCO) rose 1.6% on Friday after the networking equipment company disclosed plans to eliminate nearly 500 jobs at its facilities in San Jose and Milpitas, Calif. The company filed two WARN notices with the California Employment Development Department on July 30 stating it expects to cut 397 jobs at its corporate headquarters in San Jose and another 91 positions in Milpitas. In other sector news: (+) Phunware (PHUN) rose more than 7% on Friday, recouping a large slice of Thursday's 19% drop to a record low close of $1.13 a share after regulatory filings showed CEO and co-founder Alan Knitowski and chief technology officer and co-founder Luan Dang bought a combined 87,500 shares from the Curo Capital Appreciation Fund priced at $1.35 apiece. Thursday's steep drop followed the mobile applications company reporting an $0.08 per share Q2 net loss, reversing a $0.17 per share profit last year, while revenue \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 = 0.0188 (i.e., a 1.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0188 = 5.3284, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018768, "expected_loss": 0.018768, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220707_0169", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2022-07-07", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1923, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0086, std=0.0701, worst_day=-0.1989\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-06] \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": "0.5201", "answer_numeric": 0.5201, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1923 (i.e., a 19.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1923 = 0.5201, capped at 1.0.\nMaximum position size = 0.5201 (52.0% of portfolio).", "metadata": {"var_99": -0.192273, "expected_loss": 0.192273, "max_drawdown_threshold": 0.1, "position_size": 0.5201, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20180829_0172", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2018-08-29", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0176, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0002, std=0.0087, worst_day=-0.0185\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-08-28] [\"Here\\u2019s What Blockchain Technology Means for IBM Stock InvestorPlace - Stock Market News, Stock Advice & Trading Tips IBM (NYSE: IBM ) has been in a prolonged restructuring, and the results have been mixed at best. This is particularly aggravating since various other old-line tech giants like Microsoft (NASDAQ: MSFT ), Cisco (NASDAQ: CSCO ) and Adobe (NASDAQ: ADBE ), have staged strong turnarounds. But I think investors should not give up on IBM stock. The fact is that the company is making progress. More important, it has been investing heavily in next-generation technologies. Just look at the blockchain category. The roots of this technology go back to 2009, with the creation of the bitcoin cryptocurrency. The blockchain technology was the foundation of it, acting as a powerful ledger system. This meant that the transactions were stored in a decentralized database and only accessible by private key cryptography - making it highly secure. 21 Beverage Stocks to Buy for the Contrarian-Minded Since then, the interest in blockchain has certainly gotten more and more intense. But the applications are much wider than just cryptocurrency. Blockchain really represents a new way of storing any kind of critical information. And this is ideal for a company like IBM. In fact, the company has already made significant strides. IBM Stock and the Blockchain An example of this is TradeLens, which involves an alliance with Maersk, a major integrated container logistics company. The platform leverages blockchain technology to track transactions across the shipping supply chain. So far, there are 94 organizations in the program that account for 234 marine gateways worldwide. TradeLens provides transparency, which is often lacking in global trade. But there is also the use of sophisticated IoT (Internet-of-Things) sensor data to provide real-time access. To get a sense of the power of this platform, it has helped reduce the transit times of shipments of packing materials to the U.S. by as much as 40% . Keep in mind that global shipping represents about four trillion dollars in goods every year. But TradeLens is not the only initiative. For example, there is LedgerConnect , which helps financial institutions to create their own blockchain apps. Some of the partners include Barclays (NYSE: BCS ) and Citigroup (NYSE: C ). Some of the core functions of LedgerConnect include collateral management, sanctions screening and derivatives processing. Although, the technology should also help promote standards in the financial industry and also make it easier to develop new innovations. And as the system gets more traction, there is likely to be the benefit of network effects, which should lead to strong barriers to entry. The Bottom Line on IBM Stock When it comes to IBM stock, blockchain technology is still in the early stages, but it should have a pervasive impact in the coming years. What's more, IBM's efforts show that the company is focused on innovation and taking \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 = 0.0176 (i.e., a 1.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0176 = 5.6897, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017576, "expected_loss": 0.017576, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210914_0177", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-09-14", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1369, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0185, std=0.0647, worst_day=-0.1890\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7303", "answer_numeric": 0.7303, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1369 (i.e., a 13.69% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1369 = 0.7303, capped at 1.0.\nMaximum position size = 0.7303 (73.0% of portfolio).", "metadata": {"var_99": -0.136936, "expected_loss": 0.136936, "max_drawdown_threshold": 0.1, "position_size": 0.7303, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170615_0182", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2017-06-15", "context_summary": "BNDX: 60-day history, VaR(99%)=-0.0022, max drawdown threshold=10%.", "question": "Asset: BNDX\nDaily returns (past 60 days): mean=0.0003, std=0.0013, worst_day=-0.0024\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNDX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0022 (i.e., a 0.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0022 = 46.0446, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.002172, "expected_loss": 0.002172, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220110_0185", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2022-01-10", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0288, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0015, std=0.0154, worst_day=-0.0294\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-07] [\"Tuya Officially Announces Support for Matter Smart Home Standard Tuya Smart (NYSE: TUYA), a leading IoT development platform service provider, today officially affirmed its support for Matter, a commitment to ensure that Tuya's customers and business partners can seamlessly join in the new smart home connectivity standard and provide users with more convenient smart home experience.\", \"Startups at CES showed that age-tech can help everyone After all, the usefulness of things like mobility aids, health monitoring platforms and long-term financial planning aren\\u2019t limited to the elderly. It\\u2019s algorithms learns a person\\u2019s habits, and informs caregivers if there are any changes in behavior.\", \"Cannabis Megasite WayofLeaf.com Launches App That Monitors Health Effects of Different Marijuana Strains Cannabis and alternative health megasite WayofLeaf.com has announced the release of a new mobile app that monitors and tracks various health vital signs before and after the use of specific cannabis products. The goal of the app, according to its creators, is to help establish a reliable database that accurately outlines the health effects of various cannabis strains and products.\", \"Tinder's upcoming 'Swipe Party' feature lets friends help you choose dates Tinder is working on a new feature called Swipe Party that will let you invite friends online to help you vet dates.\", \"The weirdest stuff we saw at CES 2022: John Deere's self-driving tractor, robot masseuses Among the odder sights at this year's Consumer Electronics Show: an autonomous tractor from John Deere and robots that will give you a massage.\", \"Apple Fitness+ introduces new 'Collections' feature and 'Time to Run' series Apple Fitness+ is introducing a new \\\"Collections\\\" feature along with a new \\\"Time to Run\\\" series starting on January 10th. Apple says Collections will give users a suggested plan to help them make specific training choices. Apple's new \\\"Time to Run\\\" series is an extension of its \\\"Time to Walk\\\" feature that launched last year.\", \"Apple Fitness+ will add an audio-based running feature on January 10th A curated series of workouts and meditations called Collections debuts on the same day.\", \"The Mac Mini M1 is up to $150 off, plus the rest of the week's best tech deals This week's best tech deals include up to $150 off the Mac Mini M1 desktop, $60 off the iPad Air, and $40 off the Google Nest Hub smart display.\", \"Model Brooks Nader says someone used an AirTag to track her She claims she didn't get a notification about the device until she was walking home alone.\", \"Agency A+ plans to expand its operations to the United States Agency A+ celebrates 14 years in 2022 and plans to expand its activities to the United States. With a strong performance in integrated communication, the company is owned and managed by Tatiana Marzullo Varges and provides PR, Digital Marketing, Social Media and Corporate Communication services to several multinational and Brazilian compa\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 = 0.0288 (i.e., a 2.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0288 = 3.4677, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028838, "expected_loss": 0.028838, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220117_0188", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2022-01-17", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0355, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0009, std=0.0141, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-14] [\"3 Downtrodden Stocks to Sell Before It Gets Worse InvestorPlace - Stock Market News, Stock Advice & Trading Tips Downtrends are multiplying across the land, and bears\\u2019 ranks are swelling. Despite the fact that the Nasdaq Composite still sitting a stone\\u2019s throw from its peak, some 40% of the index has been cut in half. There\\u2019s trouble beneath the surface, making for narrowing leadership and, ultimately, more vulnerability. I scanned my watchlist of the downtrodden and discovered three ugly stocks to sell before they get worse. And you don\\u2019t need to perform any mental gymnastics to grasp why lower prices are in the offing. The stocks below are stuck in nasty downtrends. And that matters greatly because trend direction is the most important of all technical signals. It sits atop the hierarchy of charting, demanding deference from all who employ technical analysis. In short, you\\u2019re far better off betting with the trend than against it. 7 Undervalued Stocks to Buy Before Wall Street Catches On That said, here are three struggling stocks that are poised for lower prices. PayPal (NASDAQ:PYPL) Snapchat (NYSE:SNAP) Adobe (NASDAQ:ADBE) Let\\u2019s review each chart in greater detail and map out a smart options trade you can use to bank on further weakness. Downtrodden Stocks to Sell: PayPal (PYPL) Source: The thinkorswim\\u00ae platform from TD Ameritrade Distance from Peak: -43% PayPal could still fall a great distance despite getting cut nearly in half. Going into the 2020 pandemic, PYPL was sitting at $125, another $50 lower from here. Over the past six weeks, the daily downtrend has slowed and formed a sideways trading range. But instead of powering to the top side and building a compelling bullish breakout, it\\u2019s knocking heavily on the lower-end. The $177 support shelf has held long enough to where its failure would prove a significant breakdown. If previous support breaks are any indication, we could see a swift move down to $160 if sellers press their bets. Given the higher volatility of the stock, I suggest using a spread trade over buying puts outright. The Trade: Buy the Feb $175/$160 put vertical for $4.75. You\\u2019re risking $4.75 to make $10.25 if PYPL stock falls to $160 by expiration. Snap (SNAP) Source: The thinkorswim\\u00ae platform from TD Ameritrade Distance from Peak: -56% Snap\\u2019s unraveling following last quarter\\u2019s earnings report has been deathly. For a single announcement to cause the stock to drop over 50% within a single quarter is horrific and speaks to just how much the Street hated the numbers. Prices are now submerged deep beneath all major moving averages. Once again, it\\u2019s tempting to argue SNAP stock is down so much that it can\\u2019t go lower. But like PayPal, it was way, way lower before the pandemic. Shareholders are hoping the quarterly report on Feb. 3 saves them. For now, I think the downtrend continues. Prices are down big over the past three days, so if you want to wait for\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 = 0.0355 (i.e., a 3.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0355 = 2.8148, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035527, "expected_loss": 0.035527, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210316_0193", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2021-03-16", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0229, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0016, std=0.0110, worst_day=-0.0245\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-03-15] Cloud Computing's Trillion-Dollar Potential Cloud computing companies not only weathered the storm of the pandemic, they thrived. But even with those gains, the industry is still just scratching the surface of its potential. A new report from McKinsey Digital, which looks at cost-optimization and business use-cases, says there is $1 trillion in run-rate EBITDA up for grabs for Fortune 500 companies in 2030. And the companies that most aggressively pursue cloud opportunities could grab the lion\u2019s share of that value. The sector has seen its value soar in the past eight years. Since 2013, cloud companies on the Nasdaq index have seen their value increase 261%, according to the Bessemer Venture Partners Emerging Cloud Index, a stock index designed to track the performance of emerging public companies primarily involved in providing cloud software to their customers. Those companies currently have a market capitalization of $2 trillion. Cloud growth rates and access to capital are at all-time highs, says Bessemer, with an average growth of 80% YoY, among companies it follows. Over the past year, the top five public cloud companies \u2014 Paypal, Adobe, Salesforce, Shopify and Zoom \u2013 saw a 70% increase in their total market cap. Collectively, the five are already worth more than $1 trillion. And the bullishness on the future financial potential of cloud computing is widespread. IDC, last fall, estimated worldwide spending on cloud services, and opportunities around those services, would top $1 trillion by 2024. \"Cloud in all its permutations \u2013 hardware/software/services/as a service as well as public/private/hybrid/multi/edge \u2013 will play ever greater, and even dominant, roles across the IT industry for the foreseeable future,\" said Richard L. Villars, group vice president of worldwide research at IDC. \"By the end of 2021, based on lessons learned in the pandemic, most enterprises will put a mechanism in place to accelerate their shift to cloud-centric digital infrastructure and application services twice as fast as before the pandemic.\" Cloud technology, for many people, brings to mind things like smartphone or PC backup tools, online services or streaming media \u2013 the most frequently touted use-cases. But it has some much more direct real-world uses \u2013 perhaps most importantly, its recent contributions to COVID-19 vaccines. Moderna built its mRNA research platform on Amazon\u2019s cloud service to accelerate discovery and development \u2013 and when COVID hit, this helped the company deliver its first clinical batch of a vaccine candidate within 42 days of the sequencing of the virus. Scientists were able to integrate insights for a number of experiments, which were all running in parallel, to refine and streamline the production cycle. And the cloud is also playing a key role in the company\u2019s research into treatments for rare diseases and cancer. The company has over one dozen drug candidates in the pipeline, with seven going through trial studies. \u201cFor CEOs, cloud \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 = 0.0229 (i.e., a 2.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0229 = 4.3660, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022904, "expected_loss": 0.022904, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20191203_0196", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2019-12-03", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1172, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0001, std=0.0629, worst_day=-0.1202\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-02] [\"What\\u2019s worth streaming in December? \\u2018The Mandalorian,\\u2019 \\u2018Mrs. Maisel,\\u2019 \\u2018The Witcher\\u2019 and more With an avalanche of streaming options, here\\u2019s how to get your money\\u2019s worth without missing out on must-see shows Here\\u2019s a look at what\\u2019s coming to the various streaming services in December, and what\\u2019s really worth the monthly subscription fee.\", \"Apple stock price target raised to $296 from $290 at J.P. Morgan\", \"Apple target price gets a boost at JPM on optimism for four new iPhone models J.P. Morgan analyst Samik Chatterjee grew increasingly optimistic Monday about Apple Inc.'s iPhone volumes for 2020 and 2021, boosting his target price to $296 from $290. He expects Apple to launch four new iPhones in September 2020, all of which will support 5G capabilities but only two of which will have \\\"world-facing\\\" 3D sensing. He also thinks Apple will take a new approach to device launches the following year. \\\"Starting 2021, we expect Apple to smooth iPhone seasonality by shortening launch intervals and introducing two new iPhones in both 1H21 and 2H21,\\\" he wrote. Chatterjee has an overweight rating on Apple's stock, which is up 0.1% in premarket trading Monday. The shares have risen 69% so far this year, as the Dow Jones Industrial Average has climbed 20%.\", \"Apple Could Introduce More iPhones \\u2014 More Often \\u2014 Because It Has to Compete With Android J.P. Morgan analyst Samik Chatterjee says his discussions with Apple suppliers indicate the company is likely to unveil phones in both the spring and the fall in 2021.\", \"Apple will make some big changes with the next iPhone, JPMorgan says Analyst expects Apple to introduce four new iPhone models in fall 2020 before shifting to a staggered launch cadence in 2021 Apple Inc. could start making some notable changes to how it introduces new iPhones, and that has J.P. Morgan analyst Samik Chatterjee feeling increasingly upbeat about the company\\u2019s prospects.\", \"Democratic senators target Big Tech with privacy bill, but analyst say it\\u2019s unlikely to become law The measure \\u2018will likely throw yet another wrench in the yearlong effort to pass bipartisan data privacy legislation,\\u2019 analysts say Four Democratic senators have rolled out a bill that aims to provide better protections of personal data in Washington\\u2019s latest response to Facebook\\u2019s Cambridge Analytica scandal and other Silicon Valley foul-ups.\", \"Netflix Stock Is Down Because Streaming Competition Is Up Netflix stock is down because the streaming wars are heating up. KeyBanc analyst Andy Hargreaves sees things getting worse before they get better for the streaming giant.\", \"A Bounty of Dividends Exxon Mobil, AT&T, Apple, and Microsoft are among the companies that paid out the most in dividends in terms of total dollars paid. Their yield and growth rates, however, say different things.\", \"The Dow Lost 268 Points Because Manufacturing Data Blew a Hole in Cyber Monday\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": "0.8530", "answer_numeric": 0.853, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1172 (i.e., a 11.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1172 = 0.8530, capped at 1.0.\nMaximum position size = 0.8530 (85.3% of portfolio).", "metadata": {"var_99": -0.117235, "expected_loss": 0.117235, "max_drawdown_threshold": 0.1, "position_size": 0.853, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201006_0201", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2020-10-06", "context_summary": "DOT-USD: 46-day history, VaR(99%)=-0.1651, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 46 days): mean=0.0072, std=0.0872, worst_day=-0.1989\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6058", "answer_numeric": 0.6058, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1651 (i.e., a 16.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1651 = 0.6058, capped at 1.0.\nMaximum position size = 0.6058 (60.6% of portfolio).", "metadata": {"var_99": -0.165067, "expected_loss": 0.165067, "max_drawdown_threshold": 0.1, "position_size": 0.6058, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20191114_0204", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2019-11-14", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.0917, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0034, std=0.0489, worst_day=-0.0959\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0917 (i.e., a 9.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0917 = 1.0908, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.091675, "expected_loss": 0.091675, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160719_0209", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2016-07-19", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0341, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0010, std=0.0144, worst_day=-0.0438\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-07-18] [\"Corporate profits brace for fourth straight losing quarter Investors will look for signs that economy not in negative territory With more than 90 of the biggest U.S. companies reporting results this week, investors will get a clearer picture of what is expected to be the fourth straight quarter of declining profits for the group.\", \"Not Down Is the New Up in Chip Earnings Calendar Q2 and Q3 will both be mostly in line, despite Q3 estimates that already reflect above-seasonal growth.\", \"SoftBank to buy chip designer ARM in $32 billion deal Japan\\u2019s SoftBank bolsters its mobile internet effort Japan\\u2019s SoftBank Group has reached a deal to buy Apple supplier ARM Holdings in an all-cash deal valued at more than $32 billion, according to a person familiar with the situation\", \"SoftBank to buy ARM Holdings for more than $32B HONG KONG--U.K.-based chip designer ARM Holdings PLC confirmed Monday that it agreed to a buyout offer worth more than $32 billion from SoftBank Group Corp., marking a significant push for the Japanese telecommunications giant into the mobile internet.\", \"ARM: What you should know about the chip maker being purchased by SoftBank ARM is a British chip maker that has benefited from the rise of mobile ARM is a British chip maker that probably designed the chip in your smartphone.\", \"Canaccord Ups Intel Target Ahead of Q2 Earnings Intel (INTC) reports second-quarter earnings on Wednesday, and Canaccord thinks investors should be buying before the results.Analyst Matthew Ramsey and his team reiterated a Buy rating on the stock and upped their price target from $38 to $40. Ramsey admits that the report comes a mixed macro environment but is encouraged by better-than-feared second-quarter PC shipments. Other tailwinds will include the expiration of the downloadable Windows 10 upgrade program, and sales of a number of new products that should growth back toward the firm\\u2019s mid-tee target. With Intel\\u2019s first Apple (AAPL) iPhone modem sales, and significant cost cuts, he sees its mobile business losses coming down dramatically. Ramsey also likes the company\\u2019s yield and valuation, making it a \\u201ccompelling\\u201d core holding.\", \"European shares gain ground, but Turkish stocks fall after coup attempt Apple supplier ARM rises on buyout deal European stocks are higher Monday, led by a rally in shares of ARM Holdings, but Turkish shares are lower in the wake of a failed coup attempt.\", \"FTSE 100 climbs to 2016 high on ARM deal news Apple-supplier ARM shares surge by a record 41% after SoftBank buyout U.K. stocks are rising Monday, led by a spike in ARM shares after the chip designer agreed to be purchased for more than $32 billion.\", \"S&P 500, Dow close at all-time highs driven by tech, bank gains Nasdaq closes at new high for 2016 U.S. stocks trade within a narrow range Monday, finishing higher to give both the Dow Jones Industrial Average and the S&P 500 index fresh all-time closing highs and the Nasdaq Composite Inde\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 = 0.0341 (i.e., a 3.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0341 = 2.9345, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034078, "expected_loss": 0.034078, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170104_0212", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2017-01-04", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0233, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0006, std=0.0089, worst_day=-0.0254\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-03] [\"Seven highly valued tech startups that could IPO in 2017 Unicorns like Snap and Spotify are expected to reach Wall Street in 2017, but what about Uber, Lyft, Airbnb, Dropbox and Palantir? After a dismal year for IPOs, investors expects to see more billion dollar startups test the public market or at least make moves in that direction.\", \"Go after these long-term stock plays in 2017 \\u2014 don\\u2019t chase what already happened Critical information for the U.S. trading day The new year has kicked off with what looks like a bright start for stocks, but investors should check their desire to chase the market at the door. Our call of the day offers these ideas for investing in some themes that will deliver.\", \"Intel seeks German digital-map venture stake BERLIN-- Intel Corp. is positioning itself to join BMW AG, Daimler AG and Volkswagen AG's Audi unit in developing navigation technology for self-driving cars. The U.S. tech bellwether filed a request for regulatory approval in Germany to make a strategic acquisition of a minority stake in the digital-mapping service Here International B.V., the Berlin-based company that Germany's big-three car makers bought from Nokia in 2015 for about EUR2.5 billion ($2.6 billion).\", \"CES 2017: Can Virtual Reality Finally Go Mainstream? For VR, 2016 was supposed to be the year when everything came together. But VR headsets remain bulky, expensive, and nausea inducing. What to expect in 2017.\", \"Virtual Reality Fertile Ground for Loup Ventures Despite Failures Thus Far A couple weeks ago I spoke by phone with former analyst , who left the firm after many years being a star analyst on (AAPL) to become a venture capitalist, along with colleagues and .Their firm, , will invest in four areas, , , , and , which they sees as among the most promising tech trends of the next several years. They want to combin investment with dissemination of research notes like they have done as sell-side analysts.More info is available on their Web site.I was interested to talk with the trio because my own experience with virtual reality, related in this space, is that it's at best immature as a consumer product, and at worst, it just plain sucks.\", \"As India Investment Slumps, Will GDP Follow? Announcements about new investments in India declined in the quarter ending December 30, continuing a stubborn quarterly trend.Add demonetization to the mix, and one has to ask if expectations for India's economy are too elevated. Read More>>\", \"Intel buys 15% stake in German digital-map co. Intel Corp. is acquiring a 15% stake in Here International B.V. for an undisclosed sum, joining the digital mapmaker's core shareholders BMW AG, Daimler AG and Volkswagen AG's Audi unit in developing navigation technology for self-driving cars.\", \"Apple\\u2019s Key Risk: Nokia Litigation The beginning of the year will likely be quiet in terms of legal outcomes, but the second half could bring volatility.\", \"Meet the world\\u2019s friendliest home robot Kuri, 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 = 0.0233 (i.e., a 2.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0233 = 4.2874, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023324, "expected_loss": 0.023324, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20171215_0217", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2017-12-15", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0050, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0010, std=0.0034, worst_day=-0.0054\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-12-14] [\"Net neutrality repeal gets the internet all wrong, founders claim Signatories calling for FCC to wait on open-internet repeal included Vint Cerf and Tim Berners-Lee, considered founding figures behind the internet, and Apple\\u2019s Steve Wozniak.\", \"Criteo stock plunges on lowered outlook following Apple's iOS update Shares of ad-retargeting firm Criteo S.A. fell 12% in premarket trading Thursday after the company dramatically lowered its 2018 revenue forecast due to changes Apple Inc. made to its mobile operating system. Apple's new iOS 11.2 software \\\"disables the solution that some companies in the advertising ecosystem, including Criteo, currently use to reach Safari users,\\\" according to a release from Criteo. The company projects this change to reduce 2018 revenue by 22%, excluding traffic acquisition costs, if the firm can't effectively work within the new iOS landscape. Management had previously projected a 9% to 13% \\\"net negative impact.\\\" Criteo said that it had a new solution \\\"under development\\\" but also that \\\"its effectiveness cannot be assessed at this early stage.\\\" Criteo shares are down 23% this year, while Apple's stock is up 49%. The S&P 500 Index has gained 19%.\", \"Apple introduces Final Cut Pro update with support for 360-degree VR editing Shares of Apple Inc. are up 0.1% in premarket trading Thursday after the company announced an update for its Final Cut Pro X video-editing software. The new version supports \\\"360-degree VR video editing\\\" and high-dynamic range (HDR) video. It also has new advanced color grading tools. Apple announced earlier this week that its iMac Pro, which starts at $4,999 and is aimed at professional editors, would go on sale Thursday. Apple shares have gained 49% so far in 2017, compared with a 24% rise for the Dow Jones Industrial Average .\", \"Facebook\\u2019s Irish goodbye to overseas tax shelter stands out Alphabet, Twitter among companies that still have subsidiaries in Ireland for tax purposes Facebook Inc. said this week that it plans to book more of its revenue in the countries where it sells the ads that contribute, instead of funneling revenue through a subsidiary based in Ireland to avoid taxes.\", \"Disney & Fox: So the Rumors Were True\\u2026 Walt Disney is buying 21st Century Fox for $66.1 billion including debt. One team of analysts pans the deal.\", \"Silicon Slam Dunk? Golden State Warriors Bet on Tech Start-Ups Off the court, teammates Curry, Young, and others are becoming VCs.\", \"Clippy Is Not a Robot \\u2013 Yet Joining other tech giants, Microsoft turns to AI with enhancements to the Bing search engine.\", \"Square Stock Could Double The payments firm can grow big by going small. SMB Clients will drive gross payment volume 25%.\", \"Amazon again selling Apple TV and Google Chromecast Amazon.com Inc. said Thursday that it is again selling streaming devices made by Apple Inc. and Alphabet Inc. . Amazon stock is up nearly 1% to $1,173.68 in afternoon trading. Amazon ceased selling the devi\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 = 0.0050 (i.e., a 0.50% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0050 = 20.0467, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.004988, "expected_loss": 0.004988, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200819_0224", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2020-08-19", "context_summary": "SCHP: 60-day history, VaR(99%)=-0.0039, max drawdown threshold=10%.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0007, std=0.0021, worst_day=-0.0046\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 = 0.0039 (i.e., a 0.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0039 = 25.9272, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.003857, "expected_loss": 0.003857, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20211015_0227", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-10-15", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1567, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0004, std=0.0653, worst_day=-0.1762\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-12] \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": "0.6382", "answer_numeric": 0.6382, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1567 (i.e., a 15.67% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1567 = 0.6382, capped at 1.0.\nMaximum position size = 0.6382 (63.8% of portfolio).", "metadata": {"var_99": -0.156693, "expected_loss": 0.156693, "max_drawdown_threshold": 0.1, "position_size": 0.6382, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20211018_0230", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-10-18", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1779, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0122, std=0.0757, worst_day=-0.1890\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-15] \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": "0.5623", "answer_numeric": 0.5623, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1779 (i.e., a 17.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1779 = 0.5623, capped at 1.0.\nMaximum position size = 0.5623 (56.2% of portfolio).", "metadata": {"var_99": -0.177855, "expected_loss": 0.177855, "max_drawdown_threshold": 0.1, "position_size": 0.5623, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20160129_0233", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2016-01-29", "context_summary": "WEAT: 60-day history, VaR(99%)=-0.0265, max drawdown threshold=10%.", "question": "Asset: WEAT\nDaily returns (past 60 days): mean=-0.0013, std=0.0118, 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 WEAT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0265 (i.e., a 2.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0265 = 3.7795, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026459, "expected_loss": 0.026459, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190104_0238", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2019-01-04", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0033, std=0.0146, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-03] [\"Apple cuts holiday sales forecast on iPhone and China weakness, stock falls 8% CEO Tim Cook cites weaker-than-expected iPhone sales, China economy in reducing revenue forecast Apple Inc. lowered its holiday-quarter revenue forecast Wednesday afternoon, largely due to slowing iPhone sales and pressure in China.\", \"Asian markets mostly down as Apple\\u2019s warning weighs on tech stocks Apple suppliers hit hard after tech giant cuts sales forecast Asian markets were mostly lower Thursday after tumbling more than 1% on the first trading day of 2019.\", \"Apple's stock tumbles 8.9% premarket after revenue warning late Monday\", \"Apple's stock on track to open at lowest level since July 2017\", \"Apple stock price target cut to $200 from $275 at Wedbush\", \"Apple stock price target cut to $187 from $222 at Piper Jaffray\", \"Dow Set to Tumble as Apple Wrecks Any Chance for a Rally After battling back into positive territory on Wednesday, it would have been nice to see the market gain even more on Thursday. Apple\\u2019s drop virtually guarantees that won\\u2019t happen.\", \"Copper falls as data signals China slowdown LONDON--Copper prices were under pressure Thursday, after a surprise cut to Apple's sales forecast in China pointed to slowing growth in the country just a day after a measure of Chinese manufacturing activity fell into contraction territory.\", \"Apple stock price target cut to $228 from $266 at J.P. Morgan\", \"Apple's stock plunge cuts about 90 points off Dow's price The plunge in Apple Inc.'s stock in Thursday's premarket, following the technology giant's revenue warning, is the biggest reason for the selloff in Dow Jones Industrial Average futures , but it's not the only reason. Apple shares shed 8.5% ahead of the open, putting them on track to open at the lowest level seen during regular-session hours since July 2017. The price decline would shave about 91 points off the Dow's price , while Dow futures 332 dropped points. All 27 of the Dow components trading in the premarket are losing ground.\", \"Apple stock price target cut to $200 from $300 at Monness Crespi Hardt\", \"Apple average analyst stock price target drops to $198.18 from $215.91 on Monday--FactSet\", \"Lumentum's stock tumbles 7.3% premarket in wake of Apple's revenue warning\", \"Apple downgraded to hold from buy at Jefferies\", \"Apple stock price target cut to $160 from $225 at Jefferies\", \"Apple Supplier Stocks Saw Problems Coming Even if the Market Didn\\u2019t Shares in Apple suppliers have been taking it on the chin since reports surfaced that the tech giant was slashing orders for iPhone components.\", \"Apple's average stock price target slashed to 9-month low Apple Inc.'s revenue warning has prompted a host of Wall Street analysts to slash their stock price targets, bringing the average target down to the lowest level since April 2018. The smartphone maker's stock tumbled 8.2% in premarket trade, putting it on track to open at the lowest level seen during regular-session hours since Ju\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 = 0.0356 (i.e., a 3.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0356 = 2.8129, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035551, "expected_loss": 0.035551, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20221028_0242", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2022-10-28", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0427, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=-0.0025, std=0.0180, worst_day=-0.0427\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-27] [\"Apple (AAPL) Q4 2022 Earnings Call Transcript Image source: The Motley Fool. Apple (NASDAQ: AAPL) Q4 2022 Earnings Call Oct 27, 2022, 5:00 p.m. ET Contents: Prepared Remarks Questions and Answers Call Participants Prepared Remarks: Operator Good day, and welcome to the Apple Q4 fiscal year 2022earnings conference call For your information, today's call is being recorded. At this time, for opening remarks and introductions, I would like to turn the call over to Tejas Gala, director of investor relations and corporate finance. Please go ahead. Tejas Gala -- Director of Investor Relations and Corporate Finance Speaking first today is Apple's CEO, Tim Cook; and he'll be followed by CFO, Luca Maestri. After that, we'll open the call to questions from analysts. Before turning the call over to Tim, I would like to remind you that approximately once every six years, we add a week to the December quarter to realign our fiscal periods with the December calendar. So this December quarter will span 14 weeks rather than the usual 13 and will end on December 31. Please note that some of the information you'll hear during our discussion today will consist of forward-looking statements, including, without limitation, those regarding revenue, gross margin, operating expense, other income and expense, taxes, capital allocation, and future business outlook, including the potential impact of COVID-19 on the company's business and results of operations. These statements involve risks and uncertainties that may cause actual results or trends to differ materially from our forecast. For more information, please refer to the risk factors discussed in Apple's most recently filed annual report on Form 10-K and the Form 8-K filed with the SEC today, along with the associated press release. Apple assumes no obligation to update any forward-looking statements or information, which speak as of their respective dates. 10 stocks we like better than Apple When our award-winning 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 September 30, 2022 I'd now like to turn the call over to Tim for introductory remarks. Tim Cook -- Chief Executive Officer Thank you, Tejas. Good afternoon, everyone, and thank you for joining the call today. Over the past year, despite a range of challenges facing the world, our teams have come together in incredible ways to drive unparalleled innovation and deliver again and again for our customers.For the September quarter, we reported record revenue of $90.1 billion, which was better than we anticipated despite stronger-than-expected foreign currency headwinds. We set an all-time revenue record for Mac and S\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 = 0.0427 (i.e., a 4.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0427 = 2.3410, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042717, "expected_loss": 0.042717, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20191224_0247", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-12-24", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0928, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0057, std=0.0370, worst_day=-0.1137\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0928 (i.e., a 9.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0928 = 1.0776, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.092799, "expected_loss": 0.092799, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200729_0250", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2020-07-29", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0468, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0028, std=0.0251, worst_day=-0.0629\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0468 (i.e., a 4.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0468 = 2.1377, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.04678, "expected_loss": 0.04678, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210705_0253", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2021-07-05", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.1328, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0066, std=0.0536, worst_day=-0.1328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7528", "answer_numeric": 0.7528, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1328 (i.e., a 13.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1328 = 0.7528, capped at 1.0.\nMaximum position size = 0.7528 (75.3% of portfolio).", "metadata": {"var_99": -0.132837, "expected_loss": 0.132837, "max_drawdown_threshold": 0.1, "position_size": 0.7528, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20151008_0256", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2015-10-08", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0351, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0004, std=0.0136, worst_day=-0.0388\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-10-07] [\"Fast Money Picks For October 7\", \"Susquehanna Maintains Positive on Adobe Systems, Raises PT to $97.00\", \"Benzinga's Top #PreMarket Losers\", \"Adobe's Opportunity Is $48 Billion, But Expenditures Might Limit Investors\", \"Morning Market Losers\", \"Morning Market Losers\", \"Adobe's Opportunity Is $48 Billion, But Expenditures Might Limit Investors\", \"Benzinga's Top #PreMarket Losers\", \"Susquehanna Maintains Positive on Adobe Systems, Raises PT to $97.00\", \"Fast Money Picks For October 7\", \"Notable ETF Outflow Detected - QQQ, ADBE, BIDU, CTSH Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the PowerShares QQQ (Symbol: QQQ) where we have detected an approximate $199.4 million dollar outflow -- that's a 0.5% decrease week over week (from 361,550,000 to 359,650,000). Among the largest underlying components of QQQ, in trading today Adobe Systems, Inc. (Symbol: ADBE) is off about 5.7%, Baidu, Inc. (Symbol: BIDU) is down about 2.2%, and Cognizant Technology Solutions Corp. (Symbol: CTSH) is higher by about 1.4%. For a complete list of holdings, visit the QQQ Holdings page \\u00bb The chart below shows the one year price performance of QQQ, versus its 200 day moving average: Looking at the chart above, QQQ's low point in its 52 week range is $84.74 per share, with $114.39 as the 52 week high point - that compares with a last trade of $105.55. 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 experienced notable outflows \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Nasdaq 100 Movers: ADBE, WYNN In early trading on Wednesday, shares of Wynn Resorts ( WYNN ) topped the list of the day's best performing components of the Nasdaq 100 index, trading up 6.5%. Year to date, Wynn Resorts has lost about 51.4% of its value. And the worst performing Nasdaq 100 component thus far on the day is Adobe Systems ( ADBE ), trad\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 = 0.0351 (i.e., a 3.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0351 = 2.8476, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035117, "expected_loss": 0.035117, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20171201_0259", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2017-12-01", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0065, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0008, std=0.0039, worst_day=-0.0068\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-11-30] [\"High-flying tech stocks fall back toward earth, chip makers suffer worst day of year Tech stocks lead S&P 500 to a loss despite gains for nine of 11 sectors Tech stocks, admittedly the best performers of the year, took a big step back Wednesday to close sharply lower, led by a selloff of chip makers.\", \"Apple's stock gains as analyst sees 'super-long cycle' of iPhone X upgrades Apple Inc. shares rose 0.5% in premarket trading Thursday, after an analyst suggested that the latest iPhone technology will drive a multi-year wave of device upgrades. Piper Jaffray analyst Michael Olson wrote Thursday that Apple could come out with slightly enhanced version of the iPhone X next fall, including a larger-screen option, and cut the price of the original model that was released in early November. The combination of these factors could drive a \\\"super-long cycle\\\" of upgrades, beyond the single-year \\\"super-cycle\\\" investors were hoping for. \\\"We believe an elongated iPhone cycle in FY18, followed by a wider array of iPhone X 'offspring' in Fall 2018, along with growing awareness and interest in augmented reality (fueled by developers populating the App Store with new use cases and, longer-term, addition of rear facing 3D sensor), will all push out the need for Apple to answer the question of 'what's next?'\\\" Olson wrote. With overall global smartphone sales expanding slowly, Apple has been under some pressure to find new avenues for growth. Apple's stock is up 46% so far in 2017, compared with a 21% rise for the Dow Jones Industrial Average .\", \"Apple\\u2019s Delayed \\u2018Super-Long Cycle\\u2019 Will Be All the Better, Says Piper Apple's \\\"super cycle,\\\" the focus of investors for most of this year, hasn't quite lived up to the hype, thanks to delays in the iPhone X. But that's going to lead to a \\\"super-long cycle\\\" in subsequent years, according to Piper Jaffray's Michael Olson, who advises clients to stick with the stock as Apple's OLED-based iPhones lead to rising prices.\", \"Fitbit, Xiaomi knock Apple down to 3rd in wearables shipments Fitbit Inc. and China-based Xiaomi Inc. led the pack in terms of wearables shipments for the latest quarter, according to research firm IDC, knocking Apple Inc. down to third place from second. Both Fitbit and Xiaomi shipped 3.6 million devices in the quarter, IDC said, while overall shipments rose 7.3%, to 26.3 million units. Fitbit released its first full-fledged smartwatch, the Ionic, earlier this fall, and hopes the device will reinvigorate its fortunes as consumers gravitate away from simple fitness tracking bands. Fitbit's shares have lost two thirds of their value since the company's 2015 IPO, and its shipments for the third quarter declined 33% relative to a year earlier, according to IDC. The firm wrote that Apple's shipments of 2.7 million devices reflect the fact that the company launched its new cellular-enabled Apple Watch 3 late in the quarter. \\\"The introduction of a cellular-connected version should spur i\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 = 0.0065 (i.e., a 0.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0065 = 15.4266, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.006482, "expected_loss": 0.006482, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170406_0261", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2017-04-06", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0133, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0006, std=0.0071, worst_day=-0.0169\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-04-05] [\"ADP Posts Another Blowout Jobs Number to 263K Wednesday, April 5, 2017 For the second straight month, Automated Data Processing ADP private-sector jobs numbers blew the doors off expectations. A total of 263K new jobs were created for the month of March, a gain of 18,000 jobs from last month's (revised lower) ADP figure of 245K. And, for the second month in a row, Construction and Manufacturing jobs outperformed expectations, helping overall totals in the non-government labor market. The top industries in new job growth were Professional/Business Services (57K) and Leisure/Hospitality (55K), which is not surprising. But the 49K new jobs in Construction and the 30K in Manufacturing are far stronger than the historical average during this entire resurgence in U.S. jobs, which has been going on for the past 7-8 years. Confidence not only with the consumer (which we've seen in other recent econ data) but with the goods-producing sectors has led the way, at least partially due to expectations from the Trump administration's goals to bring back jobs in these categories. Small-sized companies (fewer than 50 employees) grew the most last month at 118K, Medium companies (50-499 employees) grew by 100K and Large firms added 45K jobs. Services still far outweighed Goods, 181K to 82K respectively, but to reiterate - goods-producing is much higher than it's been in the recent past, and for the second straight month. Projections for Friday's comprehensive non-farm payroll report from the Bureau of Labor Statistics (BLS) remain at 175K following today's ADP report, though last month we saw analysts ratchet up their estimates in the wake of the strong ADP numbers. Historically, ADP and BLS jobs figures do tend to align (considering they track differently; ADP does not include government jobs, for instance), but usually only after a month or two of revisions from initial figures. In any case, this has been one of the strongest three-month averages we have seen in a long time regarding jobs growth. This points to what several economists had predicted going back to last year, which is employment traction finally taking hold after a stubborn low-growth market in labor and elsewhere. Pre-markets jumped higher on the ADP data, though the 2-year and 10-year T-notes remain rangebound at this hour. Equities remain the place to be invested. Mark Vickery Senior Editor Questions or comments about this article and/or its author? Click here>> 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 SPDR-DJ IND AVG (DIA): ETF Research Reports NASDAQ-100 SHRS (QQQ): ETF Research Reports SPDR-SP 500 TR (SPY): ETF Research Reports Automatic Data Processing, Inc. (ADP): Free Stock Analysis Report To read this article on Zacks.com 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. The views \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 = 0.0133 (i.e., a 1.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0133 = 7.5411, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013261, "expected_loss": 0.013261, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190314_0268", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2019-03-14", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0264, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0002, std=0.0115, worst_day=-0.0294\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-03-13] [\"How your internet surfing could make you money in the coming blockchain revolution Decentralized internet will give people online privacy and data ownership A decentralized internet will give people online privacy and data ownership, writes Michael Edesess.\", \"Spotify shares aren't trading in the premarket\", \"Apple's stock adds 0.3% before the opening bell\", \"Spotify files antitrust complaint against Apple in European Union: reports\", \"Spotify files EU antitrust complaint over Apple\\u2019s App store Complaint alleges Apple abused its control over which apps appear in its App Store Music-streaming service Spotify Technology SA has filed an antitrust complaint in Europe against Apple Inc., a new salvo in the broader battle over how and whether to rein in alleged wrongdoing by tech giants.\", \"Spotify Is Hitting Apple With an Antitrust Complaint Over the \\u2018Unfair Advantage\\u2019 of the App Store Spotify CEO Daniel Elk said the App Store gives Apple\\u2019s own applications and services \\u201can unfair advantage at every turn.\\u201d\", \"Apple\\u2019s China Problems May Be Getting Even Worse Analysts expect Apple to report earnings of $2.38 per share on revenue of $57.54 billion, indicating declines of 13% and 5.9%, respectively, from the year-ago period.\", \"Charting a headline breakout attempt, S&P 500 challenges major resistance (2,817) Focus: Apple confirms its uptrend, Real estate sector tags 11-year highs, Utilities finally knife to record territory, AAPL, IYR, XLU, PANW, DDS, NRG U.S. stocks are firmly higher early Wednesday, rising amid distinctly bullish price action ahead of a key Brexit vote. Against this backdrop, the S&P 500 and Nasdaq Composite are challenging their five-month range top \\u2014 S&P 2,817 and Nasdaq 7,670 \\u2014 areas defining the immediate bull-bear tension. An eventual breakout opens the path to less-charted territory, and potentially material follow-through.\", \"Should stock-market investors watch out for a volatility pickup? \\u2018The cost of being wrong using options has seldom been lower,\\u2019 says BTIG\\u2019s Emanuel A 2019 stock-market rally comes alongside a fall in volatility. One analyst says investors can\\u2019t go wrong buying protection against a potential pickup.\", \"Podcast: Microsoft\\u2019s Surprising Comeback This week on The Readback, Alex Eule is joined by associate editor Jack Hough to talk about the surprising comeback of Microsoft.\", \"Apple, Amazon, Google, Facebook cast in Europe as harmful monopolies Spotify claims antitrust against Apple as U.K. report recommends new rules, oversight of big tech firms Facebook, Google, Amazon and Apple are once again being cast as monopolies that have become too powerful for society\\u2019s good, a recurring theme that\\u2019s increasing the pressure to rein them in.\", \"Apple Courts HBO and Showtime for Service to Challenge Netflix The company will host A-list celebrities and media executives on March 25 to outline how it will take on competitors like Amazon.com Inc\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 = 0.0264 (i.e., a 2.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0264 = 3.7926, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026367, "expected_loss": 0.026367, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220315_0271", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2022-03-15", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0206, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0000, std=0.0101, worst_day=-0.0256\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-03-14] [\"Foxconn closes Shenzhen factories after fresh COVID outbreak Foxconn and Unimicron have announced temporary shutdowns to deal with an outbreak in Shenzhen.\", \"Apple iPhone SE is a more than $20 billion opportunity: analyst Apple could have a financial winners on its hands with the cheaper iphone SE.\", \"The Morning After: Intel\\u2019s latest NUC mini-desktop is pretty powerful Today\\u2019s tech headlines: Apple stops selling LG's $1,299 UltraFine 5K Display, Samsung's next Galaxy phone event is on March 17th, Classic RPG Chrono Trigger just got an update for ultrawide PC screens.\", \"The new iPhone SE is a great iPhone at a reasonable price Apple launches its iPhone SE this Friday. After using the device, it's clear owners will get the essential iPhone experience for a better price.\", \"iPhone SE review (2022): A small throwback of a phone If you want a simple iPhone that runs like new, and don\\u2019t mind the dated design and single rear camera, the iPhone SE might fit the bill.\", \"The iPhone SE is the platonic ideal of a smartphone Since its re-launch in 2020, the entry model iPhone has transformed from a nod to relic-era sizing into a prime example of a \\u2018just what it needs to be and nothing more\\u2019 smartphone. The 2022 model runs on the A15 Bionic chip, which also powers its top of the line iPhone 13 Pro. This is not a parts bin iPhone from a core computing perspective.\", \"Apple's 16-inch MacBook Pro is $200 less than usual on Amazon Amazon knocks $200 off Apple's 16-inch MacBook Pro laptop, bringing it down to $2,299.\", \"How to clean your AirPods Here is everything you need to know about how to clean your AirPods, and any other true wireless earbuds you have.\", \"Apple's AirPods Max are back on sale for $449 Amazon knocks up to $100 off Apple's AirPods Max, bringing them down to $449.\", \"Ad Age Names TBWA Its 2022 Network of the Year TBWA\\\\Worldwide was today named 2022 Network of the Year by Ad Age, a global media brand that publishes news, analysis, and data on marketing and media.\", \"Apple releases iOS 15.4 with mask-friendly Face ID unlock Apple has begun rolling out iOS 15.4.\", \"macOS 12.3 arrives with Universal Control and spatial audio features Dozens more emoji, including a melting face and disco ball, are now available.\", \"Apple iOS 15.4 update: iPhone users can now unlock their phones with Face ID and masks Apple rolled out iOS 15.4 Monday for the iPhone which supports an updated Face ID feature that allows owners to unlock phones while wearing a mask.\", \"Apple's privacy chief regretted creating its infamous ad-tracking tool after developers started using it in ways the tech giant didn't intend, report says Erik Neuenschwander told colleagues he regretted building Apple's IDFA, which allows third parties to track user activity, per The Information.\", \"Europe Data Center Market Report 2022: Google, Facebook, Microsoft, Oracle, Amazon Web Services, and Apple are the Major Hyperscale Companies The \\\"Europe Data Center Market - In\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 = 0.0206 (i.e., a 2.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0206 = 4.8571, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020589, "expected_loss": 0.020589, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190117_0274", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-01-17", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1514, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0037, std=0.0686, worst_day=-0.1575\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6607", "answer_numeric": 0.6607, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1514 (i.e., a 15.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1514 = 0.6607, capped at 1.0.\nMaximum position size = 0.6607 (66.1% of portfolio).", "metadata": {"var_99": -0.151353, "expected_loss": 0.151353, "max_drawdown_threshold": 0.1, "position_size": 0.6607, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160505_0277", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2016-05-05", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0179, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0014, std=0.0110, worst_day=-0.0199\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-04] [\"Fitbit wins ruling in Jawbone patent dispute Patents invalidated, but trade-secret claims may continue A fight between two of the largest makers of fitness trackers just got smaller.\", \"Apple shares gain 0.7% to $95.85 to lead Dow gainers in early trade\", \"A.M. Funds Roundup: The ETF World\\u2019s Apple Conundrum\", \"Apple hires Google X\\u2019s co-founder for its health projects Apple hires Yoky Matsuoka, formally of Nest Labs and Quanttus Apple has hired Yoky Matsuoka, a Google X founder, who will report directly to COO Jeff Williams\", \"Fitbit Sold 21 Million Activity Trackers Last Year and No One Seems to Care; Plus, a Month with the Blaze Smartwatch\", \"European stocks end lower for 4th session in a row Eurozone PMI confirms flash reading European stock markets finished sharply lower on Wednesday, as investors assessed a mixed bag of corporate news, with shares in Dialog Semiconductor PLC and London Stock Exchange Group PLC dropping.\", \"Welcome to your Smart Future Investors need to open their minds to the possibilities of what future tech will bring, and along with it, great investment opportunities.\", \"Apple: Survey Says iPhone Demand to Recover, But Huawei, Oppo More \\u2018Aspirational,\\u2019 Says UBS UBS\\u2019s Steve Milunovich today offers up evidence from the firm\\u2019s \\u201cEvidence Lab\\u201d that there\\u2019s hope for a rise in Apple\\u2019s (AAPL) iPhone sales when it produces the next model of the device, presumably an \\u201ciPhone 7.\\\"Milunovich, who has a Buy rating on the shares, and a $120 price target, writes that his survey of 6,336 smartphone users in the U.S., U.K., Japan, Germany, and Mainland China, conducted online in March, found some improvement in sentiment for Apple\\u2019s wares.Milunovich\\u2019s report is actually contained in two notes.In the Apple-specific note, he writes of an improvement in the upgrade \\u201ccycle\\\" for the iPhone versus what many see as a lengthening of the time between when people buy a new iPhone, writing \\u201cin our fall survey we should have taken more seriously the two negatives: demand for the 6s was weaker than for the 6 and upgrade cycles slightly lengthened.\\\"The latest data \\\"finds a reversal,\\u201d he writes. \\\"interest in the iPhone 7 is better than for the 6s though not as strong as for the 6 and upgrade cycles appear shorter in the US and China though not in other countries.\\\"In the companion report on the survey itself, the intent of consumers has actually improved from that survey back in the fall, at least in the U.S. and China:\", \"Fitbit\\u2019s new products should propel the company through earnings Fitbit Blaze and Alta are big sellers Fitbit reports first-quarter earnings Wednesday, and analysts expect an easy beat.\", \"Apple CEO Cook: Bloomberg, Kass Explore the Credibility Gap (Update) A couple of individuals in the last 24 hours have offered some rebuttal to Apple (AAPL) CEO Tim Cook\\u2019s upbeat appearance Monday evening with Jim Cramer of CNBC on his \\u201cMad Money\\u201\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 = 0.0179 (i.e., a 1.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0179 = 5.5775, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017929, "expected_loss": 0.017929, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20221214_0284", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2022-12-14", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1492, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0488, worst_day=-0.1798\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-13] \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": "0.6701", "answer_numeric": 0.6701, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1492 (i.e., a 14.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1492 = 0.6701, capped at 1.0.\nMaximum position size = 0.6701 (67.0% of portfolio).", "metadata": {"var_99": -0.149238, "expected_loss": 0.149238, "max_drawdown_threshold": 0.1, "position_size": 0.6701, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20170824_0287", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2017-08-24", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0147, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0001, std=0.0057, worst_day=-0.0175\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-08-23] [\"Apple\\u2019s $1 billion TV move pits company against Spotify, not Netflix Apple\\u2019s investment in producing and acquiring TV content should help it achieve plan to double its services business by 2020 Apple\\u2019s $1 billion investment to buy and produce original TV programming pits the technology giant against Spotify, not Netflix Inc. and Amazon.com Inc., according to analysts at RBC Capital Markets \\u2014 at least for now.\", \"Koch Stock Buys: Cisco, BlackBerry, Qualcomm A unit of Koch Industries also bought Alphabet shares, and initiated large positions in Vistra Energy and BKLN.\", \"Income Reading List: How Investors View Venezuelan, European Debt; Companies Paying Big Dividends A few headlines that might interest income investors.\", \"A Tech Crash Isn\\u2019t Coming, But You Should Expect A Pullback There are a number of problems with comparing today to the dot com meltdown, but markets could still fall back a bit.\", \"Factors to Favor: What the Technicals Say Ned Davis Research Group says lower volatility and higher quality are factors exhibiting favorable technicals.\", \"Samsung Seeks to Redeem, Renew With \\u2018Note 8\\u2032 Ahead of Apple\\u2019s iPhone Event Samsung's set to unveil its \\\"Note 8,\\\" a replacement of the infamous Note 7 that got banned on airplanes last year for exploding batteries.\", \"Apple phone sales appear to be steady ahead of September launch Sales of Apple's iPhones appear to have been \\\"resilient\\\" and sell through share appears steady last month, even as many consumers seem to be waiting for the new iPhone release in September, Canaccord Genuity analysts said Wednesday. They estimate that Apple Inc. brought in 64% of industry profits in July, helped by carrier promotions, but down from 84% in its March quarter. Apple's sales took a hit from Samsung's launch of the Galaxy S8 phone and steady results from Chinese phone companies. However, they see Apple's new cycle of iPhones in September bringing Apple to 46.5 million iPhone units sold and leading Apple to increase its market share in calendar year 2018. In addition to strong sales of Apple's iPhone 8, they expect strong sales of 7S Plus models. They maintained a buy rating and $180 price target. Shares of Apple have gained 6.4% in the past month, while the S&P 500 has lost 1%.\", \"Why Amazon Should Sweat Google\\u2019s Wal-Mart Deal While Amazon is still well ahead of its rivals, Google is ramping up efforts to gain share in retail and voice-activated devices.\", \"Investors Favor Facebook, Amazon, Alphabet Recent feedback indicates that bullish viewers of Facebook expect over 35% year-over-year growth in ad revenue.\", \"Apple\\u2019s Share of Smartphone Profits Dives The new iPhones are likely to reverse the trend, however, one analyst predicts.\", \"Samsung Redemption: \\u2018Note 8\\u2032 Its Most Elegant Device Yet Samsung Electronics unveils \\\"Note 8,\\\" a sleeker version of the phablet computer, which last year was a black mark for the company when the Note 7 model had 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 = 0.0147 (i.e., a 1.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0147 = 6.8054, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014694, "expected_loss": 0.014694, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170301_0294", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2017-03-01", "context_summary": "HYG: 60-day history, VaR(99%)=-0.0050, max drawdown threshold=10%.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0007, std=0.0020, 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 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 = 0.0050 (i.e., a 0.50% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0050 = 20.1203, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.00497, "expected_loss": 0.00497, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200217_0297", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2020-02-17", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0180, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0024, std=0.0077, worst_day=-0.0209\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-02-14] [\"Applied Materials (AMAT): Strong Industry, Solid Earnings Estimate Revisions\", \"Tiger Management Buys Amazon.com Inc, NXP Semiconductors NV, CommScope Holding Co Inc, Sells ...\", \"Company News for Feb 14, 2020\", \"Top Research Reports for VMware, Applied Materials & Equinix\", \"Thames Capital Management Llc Buys Citigroup Inc, Applied Materials Inc, NVIDIA Corp, Sells ...\", \"Composite Rating For Applied Materials Jumps To 98\", \"Top Research Reports for VMware, Applied Materials & Equinix\", \"Thames Capital Management Llc Buys Citigroup Inc, Applied Materials Inc, NVIDIA Corp, Sells ...\", \"Composite Rating For Applied Materials Jumps To 98\", \"Company News for Feb 14, 2020\", \"Tiger Management Buys Amazon.com Inc, NXP Semiconductors NV, CommScope Holding Co Inc, Sells ...\", \"Applied Materials (AMAT): Strong Industry, Solid Earnings Estimate Revisions\", \"Ex-Dividend Reminder: Consolidated Edison, AFLAC and Applied Materials Looking at the universe of stocks we cover at Dividend Channel, on 2/18/20, Consolidated Edison Inc (Symbol: ED), AFLAC Inc (Symbol: AFL), and Applied Materials, Inc. (Symbol: AMAT) will all trade ex-dividend for their respective upcoming dividends. Consolidated Edison Inc will pay its quarterly dividend of $0.765 on 3/16/20, AFLAC Inc will pay its quarterly dividend of $0.28 on 3/2/20, and Applied Materials, Inc. will pay its quarterly dividend of $0.21 on 3/11/20. As a percentage of ED's recent stock price of $93.85, this dividend works out to approximately 0.82%, so look for shares of Consolidated Edison Inc to trade 0.82% lower \\u2014 all else being equal \\u2014 when ED shares open for trading on 2/18/20. Similarly, investors should look for AFL to open 0.53% lower in price and for AMAT to open 0.31% lower, all else being equal. Below are dividend history charts for ED, AFL, and AMAT, showing historical dividends prior to the most recent ones declared. Consolidated Edison Inc (Symbol: ED): AFLAC Inc (Symbol: AFL): Applied Materials, Inc. (Symbol: AMAT): In general, dividends are not always predictable, following the ups and downs of company profits over time. Therefore, a good first due diligence step in forming an expectation of annual yield going forward, is looking at the history above, for a sense of stability over time. This can help in judging whether the most recent dividends from these companies are likely to continue. If they do continue, the current estimated yields on annualized basis would be 3.26% for Consolidated Edison Inc, 2.13% for AFLAC Inc, and 1.25% for Applied Materials, Inc.. In Friday trading, Consolidated Edison Inc shares are currently up about 0.2%, AFLAC Inc shares are up about 0.1%, and Applied Materials, Inc. shares are up about 0.1% on the day. Click here to learn which 25 S.A.F.E. dividend stocks should be on your radar screen \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Top Research Reports for VMwa\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 = 0.0180 (i.e., a 1.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0180 = 5.5590, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017989, "expected_loss": 0.017989, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210512_0300", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2021-05-12", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0191, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0010, std=0.0097, worst_day=-0.0197\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-05-11] [\"2 Stocks to Invest in Virtual and Augmented Reality Augmented reality (AR) and virtual reality (VR) promise to change the world by enabling new types of immersive experiences. While still in the nascent stages today, both of these technologies could become as common as smartphones over the next decade. According to Boston Consulting Group, the AR/VR market will expand by 113% each year through 2024, reaching $297 billion. That incredible growth rate offers investors a potentially big opportunity. So how can they capitalize on it? The best strategy is to invest in companies that enable or benefit from these technologies, especially those that use AR or VR to differentiate their business. Specifically, investors should consider Adobe Systems (NASDAQ: ADBE) and Microsoft (NASDAQ: MSFT). Here's why. Image source: Getty Images Adobe Adobe has deep roots in creative content. For instance, it released the first version of its Photoshop software in 1990. And in the three decades since, the company has become a $230 billion software titan. Today, Adobe Creative Cloud offers a range of tools for artistic professionals: Photoshop for image editing, Illustrator for graphic design, Premiere Pro for film editing, and After Effects for motion graphics. Notably, all of these are considered industry standards, as are many other Adobe applications. In 2019, the company launched a new Creative Cloud product: Adobe Aero. This application makes it possible to blend the physical and digital worlds, allowing creators to build and share immersive AR experiences without a single program. Moreover, Aero supports integrations with other Adobe products. For example, creators can build 3D objects in Adobe Dimension, paint and texturize the objects with Adobe Substance, then upload the object into Adobe Aero. Alternatively, Adobe Medium allows creators to design 3D models in a VR environment, powered by Facebook's Oculus Rift headset. Adobe is also experimenting with other use cases for AR technology. For instance, Project Glasswing is a display prototype -- picture a clear pane of glass -- that combines tools like Photoshop and After Effects with the real world. For instance, the Glasswing display could be placed in front of an object, allowing the viewer to overlay digital Photoshop edits or After Effects graphics on the physical world. Here's the takeaway: Given Adobe's history of excellence in creative content, it seems likely that this company will play a significant role in the AR and VR industries. Microsoft Microsoft is one of the largest enterprises in the world. Its Office software suite has an incredible 90% market share, and its collaboration platform -- Microsoft Teams -- has seen significant adoption during the pandemic, reaching 145 million daily active users in the most recent quarter. Currently, Teams powers interaction through text, voice, and video, and it allows users to share and edit files in real time using apps like Word or PowerPoint. But the compan\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 = 0.0191 (i.e., a 1.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0191 = 5.2334, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019108, "expected_loss": 0.019108, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201013_0303", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-10-13", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1681, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0059, std=0.0746, worst_day=-0.1934\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5948", "answer_numeric": 0.5948, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1681 (i.e., a 16.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1681 = 0.5948, capped at 1.0.\nMaximum position size = 0.5948 (59.5% of portfolio).", "metadata": {"var_99": -0.168134, "expected_loss": 0.168134, "max_drawdown_threshold": 0.1, "position_size": 0.5948, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210309_0306", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2021-03-09", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1669, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0145, std=0.0800, worst_day=-0.1817\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5990", "answer_numeric": 0.599, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1669 (i.e., a 16.69% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1669 = 0.5990, capped at 1.0.\nMaximum position size = 0.5990 (59.9% of portfolio).", "metadata": {"var_99": -0.166943, "expected_loss": 0.166943, "max_drawdown_threshold": 0.1, "position_size": 0.599, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190211_0309", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2019-02-11", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0302, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0012, std=0.0132, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-08] [\"If you own Apple, Amazon, Facebook or AMD, look out below Those shares have been bid up by the average investor, but buying could slow or even reverse Those shares have been bid up by the average investor, but buying could slow or even reverse.\", \"Hasbro Falls, Trade Worries Worsen, and Dow Is in Line for Another Loss U.S. stock markets were poised to open lower for a third consecutive day.\", \"The stock market dip? Keep buying, says Bank of America Merrill Lynch Critical information for the U.S. trading day Stocks are on track to end the week on a sour note. If you\\u2019re a fan of the \\u2018buy-the-dip\\u2019 strategy, our call of the day from Bank of America Merrill Lynch, along with our chart of a stoic S&P says now is not the time to give up.\", \"Cody Willard: I\\u2019m most bullish on Apple, Alphabet and Verizon Also reviewed today: Amazon, Intel, Palo Alto Networks, Facebook and Nvidia Also reviewed today: Amazon, Intel, Palo Alto Networks, Facebook and Nvidia.\", \"Amazon Investors Are Worried About Bezos Blackmail Case Shares of the e-commerce giant are down nearly 3% on Friday, in the wake of CEO Jeff Bezos\\u2019 startling revelations.\", \"GoPro predicts profit, thanks to years of massive layoffs Company expects to flip to profit in 2019 despite single-digit revenue growth, after chopping expenses with layoffs in 2017 and 2018 GoPro Inc. executives have been sounding bullish in the last two months, and Wednesday\\u2019s fourth quarter conference call was no exception, with a forecast for profitability in 2019 for the action camera maker, but its results were helped by past cost cutting and company layoffs.\", \"3 Stocks Bucking the Earnings Slowdown Most companies these days seem to beat earnings estimates. This is a screen for stocks whose earnings estimates have been rising in the first quarter. Boeing and two more favorites.\", \"AT&T\\u2019s 5G Act Is Bad for Everyone Wireless phone service is full of confusing labels, but AT&T\\u2019s latest \\u201c5GE\\u201d is raising new ire from consumers and industry rivals.\", \"Apple Gives New Retail Head Stock Grants Worth About $8 Million The Cupertino, California-based technology giant gave O\\u2019Brien two sets of 23,922 restricted stock units -- one group that will vest across three years beginning Aug. 5, 2021, and the other based on the company\\u2019s performance that may vest on Oct. 1, 2021, according to a regulatory filing. Each set is\", \"Apple isn't too happy about apps that secretly record your phone's screen Following TechCrunch's report that certain iOS apps are using technology from a company called Glassbox to record everything a user does within the app, Apple has started telling app developers that they either need to disclose this to users or face getting banned from the App Store. \\\"Our App\", \"Dow Jones Rout: The Cat is in the Bag, the Bag is in Trump\\u2019s Hand Friday started off badly for the Dow Jones industrial average, with all major stock indexes trading markedly lower right out 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 = 0.0302 (i.e., a 3.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0302 = 3.3154, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030162, "expected_loss": 0.030162, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190201_0312", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2019-02-01", "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=0.0134, worst_day=-0.0263\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-31] [\"Apple may soup up cameras, boost AR capabilities in new iPhones: report With iPhone growth slowing, Apple Inc. hopes to reboot sales by significantly upgrading the smartphone's cameras and augmented-reality capabilities, Bloomberg News reported Wednesday. The 2019 phone could have three rear cameras, compared to the current two, and the 2020 model may have a rear 3D camera system, whereas the current version only has a front 3D camera, the report said. The new cameras for 2019 would also have a more powerful zoom, better resolution and a wider field of vision than the current iPhone's cameras. The 2020 version would reportedly include a laser-powered 3D camera that would improve depth perception to render more accurate augmented-reality overlays. Bloomberg reported Apple is in talks with Sony Corp. over sensors for the new 3D camera, and the 2020 phone could lead to a long-awaited AR headset. Bloomberg also said Apple is testing USB-C connectors with the 2019 iPhone, suggesting an eventual replacement to the Lightning port.\", \"Chip shortages cut into Microsoft's gains Microsoft Corp. said computer-chip shortages sliced expected sales of its Windows operating system in the last three months of 2018, and that the scarcity will likely continue to hurt sales in the months ahead.\", \"Qualcomm says disputes are weighing on revenue Qualcomm Inc. said revenue dropped 20% in its latest quarter and is likely to fall by a smaller amount in the current period, as disputes with customers including Apple Inc. continue to take a toll on the maker of communications chips.\", \"Will free Apple Music make us hate flying less? The wackiest new in-flight perks Airlines work to turn time wasted on flights into an opportunity Airlines work to turn time wasted on flights into an opportunity.\", \"Here are the biggest stock winners on the day the Fed went soft on interest rates A policy reversal by the central bank excites investors A policy reversal by the central bank excites investors.\", \"Amazon Earnings Will Highlight the Threat It Poses to Cloud and Ad Rivals Earnings figures, due out Thursday, will show how worried companies such as Netflix and Google should be as Amazon pushes into their turf.\", \"3 ETF Picks With Dividends You Can Trust These funds focus on Dividend Aristocrat indexes that feature long-term payout growth.\", \"Facebook faces more privacy questions, even as it announces record profit The social-media giant has admitted to monitoring the online activity of children The social-media giant has admitted to monitoring the online activity of children.\", \"The U.S. economy is fundamentally strong \\u2014 for now Job growth is great, the Fed is patient, and Trump may be ready to make a deal with China The fundamentals in the U.S. economy look strong, now that the shutdown has ended and the Fed has eased off, writes Tim Mullaney.\", \"Debt Could Hurt Netflix, GM, and CBS Stock, Bernstein Says Companies have become a lot less creditworthy over the past two decades, \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 = 4.2306, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023637, "expected_loss": 0.023637, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210907_0317", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2021-09-07", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0102, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0019, std=0.0064, worst_day=-0.0111\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-03] [\"Zip acquisition of Payflex means Africa is ripe for BNPL disruption Australian buy now, pay later (BNPL) company Zip this week acquired South Africa-based BNPL player Payflex for an undisclosed amount. It's a piece of news that once again highlights the hype around BNPL services and the quest for global dominance among the leading players. This year we have covered BNPL services from the likes of Afterpay, Klarna and Affirm.\", \"Apple faces probe from US labor board over complaints of hostile working conditions The US National Labor Relations Board is looking into cases filed against the tech giant by two of the main voices accusing the company of permitting a hostile work environment.\", \"Apple leads the way as smartwatches dominate the wearable band market The wearable market as a whole grew 5.6 percent last quarter, but that was largely due to sales of smartwatches at the expense of basic bands.\", \"The Apple Watch Series 6 falls back to $249 Amazon and Best Buy are giving you another chance to grab a 40mm Apple Watch Series 6 for its lowest price on the websites yet.\", \"The best Labor Day tech sales we could find The best Labor Day 2021 tech sales include $150 off Apple's MacBook Air M1, $60 off AirPods Pro and $20 off Google's Nest Audio smart speaker.\", \"Engadget Podcast: Satellite on iPhone, Windows 11, Neill Blomkamp on 'Demonic' This week, Devindra chats with Senior Editor Daniel Cooper about the iPhone potentially getting satellite phone connectivity, as well as the upcoming launch of Windows 11.\", \"Apple delays plans to roll out CSAM detection in iOS 15 Apple has delayed plans to roll out its child sexual abuse (CSAM) detection technology that it chaotically announced last month, citing feedback from customers and policy groups. The Electronic Frontier Foundation said this week it had amassed more than 25,000 signatures from consumers. On top of that, close to 100 policy and rights groups, including the American Civil Liberties Union, also called on Apple to abandon plans to roll out the technology.\", \"What to expect from the iPhone 13 Here's what to expect when Apple announces its next flagship phone: the iPhone 13.\", \"Apple is delaying its child safety features Privacy advocates criticized the CSAM detection tools, which were supposed to arrive alongside the iOS 15 update.\", \"Cristopher Rogel Blanquet Reveals the Painful Cost of Pesticide Use \\u201cSebasti\\u00e1n's father told me that when he was born, the doctors told him that his life expectancy would be a maximum of five years,\\u201d the photojournalist Cristopher Rogel Blanquet tells me. \\u201cThis year, he turns 19.\\u201d Blanquet met Sebasti\\u00e1n and his family while covering the human cost of agrochemical use in Villa Guerrero, Mexico, where 70% of the population works in the flower industry. Born with hydrocephalus, Sebasti\\u00e1n is one of several people in the community who will have to contend with health\", \"SIMBA Chain Raises $25 Million in Series A Funding South Bend, I\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 = 0.0102 (i.e., a 1.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0102 = 9.7575, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010249, "expected_loss": 0.010249, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180503_0322", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2018-05-03", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0001, std=0.0109, worst_day=-0.0309\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-05-02] [\"AMD the underdog bites back, as Intel and Qualcomm struggle in their own ways The chip companies\\u2019 quarterly reports show a divergent path: AMD is growing quickly, Intel is trying to kick-start innovation, and Qualcomm is bogged down in licensing deals The chip companies\\u2019 quarterly reports show a divergent path: AMD is growing quickly, Intel is trying to kick-start innovation, and Qualcomm is bogged down in licensing deals.\", \"Apple earnings were saved by the company\\u2019s new MVP Opinion: With iPhone unit sales struggling for growth, Apple now depends on all the money iPhone users are spending on apps Apple Inc.\\u2019s quarterly results were saved by stronger revenue of its software, services and its other products category, amid disappointing iPhone sales.\", \"Apple stock buybacks spiked to a new high as shares suffered a correction Apple spent more than $22 billion on repurchases before announcing $100 billion more is coming Apple Inc. bought back more shares in the most recent quarter than it ever has in a three-month period, as the stock was suffering a correction and executives were preparing to pump a record $100 billion more into repurchases.\", \"Apple's stock surge helps push Dow futures into positive territory Shares of Apple Inc. surged 4.4% in premarket trade Wednesday, to help push futures of the Dow Jones Industrial Average into positive territory, on the back of a better-than-expected earnings report. The price gain would add about 52 points to the Dow's price, and Dow futures are up 12 points. The price gain would also add about $38.0 billion to Apple's market capitalization; Apple was already the most valuable U.S. company with a market cap of $858.0 billion as of Tuesday's close, well above second-place Amazon.com Inc. at $767.8 billion. Apple's stock had slipped 0.1% year to date through Tuesday, while the Dow had lost 2.5%.\", \"Once-hated energy stocks are now too popular \\u2014 here\\u2019s when to plunge in Critical information for the U.S. trading day Apple\\u2019s quarterly report could help give the market a win today, though the Federal Reserve\\u2019s latest signals might end up spoiling the mood. Our call of the day says don\\u2019t go with energy stocks, if you\\u2019re looking to make buys.\", \"Apple stock price target raised to $208 from $200 at Canaccord Genuity\", \"Asian markets locked in narrow range, await upcoming economic data Singapore stocks gain, Nikkei down slightly Asia-Pacific stock moves were muted in early trading Wednesday, after most overseas benchmarks saw little change the previous day.\", \"Apple stock price target raised to $171 from $166 at BMO Capital\", \"Apple's stock adds about 40 points to Dow but broader market sees muted trade ahead of Fed U.S. stock-index benchmarks traded mostly flat Wednesday at at the open, as investors weighed a blowout quarter at Apple Inc. [a: AAPL] against worries about global trade and an expected policy statement from the Federal Reserve's rate-setting committee a\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 = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7271, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026831, "expected_loss": 0.026831, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220114_0325", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2022-01-14", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0789, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0051, std=0.0390, worst_day=-0.0847\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-13] \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 = 0.0789 (i.e., a 7.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0789 = 1.2675, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.078894, "expected_loss": 0.078894, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20200228_0328", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2020-02-28", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0240, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0004, std=0.0067, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-02-27] [\"Apple's stock drops 2.8% premarket, after rising 1.6% Wednesday to snap 4-day losing streak\", \"With Microsoft\\u2019s coronavirus warning, PC and hardware makers are probably next The refrain about a \\u2018better second half\\u2019 will probably start up again Now that Microsoft, the world\\u2019s most valuable tech giant, has warned investors that its PC business will not meet its recent guidance because of the impact of the coronavirus on the supply chain, the rest of the PC universe will likely follow suit.\", \"Tesla crash report may lack enforcement power, but implications are real, analysts say Lawsuits, temporary Autopilot halt some of the possibilities, Evercore says Tesla Autopilot is often misused, and recent report by a government agency on a fatal crash involving the feature may lack real enforcement power, but the implications for Tesla Inc. could be far reaching, analysts at Evercore ISI said in a note Wednesday.\", \"Why the Fed can\\u2019t defend the economy against the coronavirus outbreak Rate cuts are effective against weak demand \\u2014 not shocks to global supply When people can\\u2019t go to work, the goods and services they normally produce can\\u2019t be supplied to a global market. The Fed can\\u2019t do a lot about that.\", \"Dow Inc., Walt Disney share losses lead Dow's nearly 550-point fall\", \"There\\u2019s not a lot the Fed can do about a coronavirus recession Lowering interest rates here won\\u2019t get factories back to work in China Calls for the Federal Reserve to cut interest rates in response to the coronavirus epidemic are misplaced at best and more likely downright dangerous.\", \"Coronavirus Is Slamming Stocks. The Jury Is Still Out on M&A Activity. Coronavirus fears are clearly weighing on the broad market, but it is still too soon to tell whether the disease will affect mergers and acquisitions, bankers said.\", \"Dow's 720-point drop led by losses for Boeing, Apple Inc. stocks\", \"U.S. economy grew a mild 2.1% in 4th quarter, but coronavirus threatens to reduce GDP even further Business investment was already weak before viral outbreak The economy expanded at a 2.1% pace at the end of 2019, but the U.S. might struggle to achieve even that modest rate of growth in the months ahead if a new strain of coronavirus isn\\u2019t contained.\", \"Nokia Stock Gives Back Gains as Skepticism Over Deal Talk Grows Nokia shares spiked 6.1% yesterday after Bloomberg reported that Nokia could consider merging or joining with Ericsson. Analysts who follow the company find the deal implausible.\", \"Dow down 618 points on losses in shares of Apple Inc., Dow Inc.\", \"Dow Inc., Apple Inc. share losses contribute to Dow's 237-point fall\", \"Dow's 560-point fall led by losses in Dow Inc., Apple Inc. shares\", \"Here\\u2019s why you\\u2019ll never see a bad guy with an iPhone in the movies \\u2018Knives Out\\u2019 director Rian Johnson alleges Apple has strict product placement standards \\u2018Knives Out\\u2019 director Rian Johnson alleges Apple has strict pro\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 = 0.0240 (i.e., a 2.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0240 = 4.1637, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024017, "expected_loss": 0.024017, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20221010_0331", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2022-10-10", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0332, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0002, std=0.0154, worst_day=-0.0372\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-07] [\"US STOCKS-Wall Street slips as jobs growth boosts rate hike bets For a Reuters live blog on U.S., UK and European stock markets, click LIVE/ or type LIVE/ in a news window. U.S. adds more-than-expected jobs in September U.S. unemployment rate falls to 3.5% AMD leads chipmakers lower after revenue warning Technology leads sectoral declines on S&P 500 Indexes: Dow 1.63%, S&P 2.14%, Nasdaq 2.80% Updates prices at open, adds comments By Shreyashi Sanyal and Ankika Biswas Oct 7 (Reuters) - Wall Street slid on Friday as solid job growth and a drop in the unemployment rate last month gave more room for the Federal Reserve to stick to jumbo-sized interest rate hikes, while a revenue warning from Advanced Micro Devices hit chipmakers. The Labor Department's closely watched employment report showed nonfarm payrolls increased by 263,000 jobs last month after rising 315,000 in August. The report also showed the jobless rate fell to 3.5% in September, lower than expectations of 3.7%. Traders now see a 92% chance of 75 basis-point hike by the Fed, up from 83.4% before data. Aggressive rise in borrowing costs have stoked fears of slowing economic growth and a hit to corporate profits, but with the labor market remaining tight, the Fed was likely to continue with its monetary tightening plan. \\\"The markets are worried that the Fed is going to rely on information like this that's really a month old and they're going to overshoot and kill the economy,\\\" said Kim Forrest, chief investment officer at Bokeh Capital Partners. \\\"Investors don't have confidence in a soft landing because the Fed continues to have to ramp higher and higher to begin to slow the economy down.\\\" The Philadelphia Semiconductor SE index .SOX shed 4.2%, and was set for its biggest one-day percentage decline in nearly a month as a revenue warning from Advanced Micro Devices Inc AMD.O signaled the chip slump could be worse than expected. AMD fell 7.97% as its third-quarter revenue estimates were about a billion dollars less than previously forecast. Peers Qualcomm Inc QCOM.O, Intel Corp INTC.O, ON Semiconductors ON.O, Lam Research LRCX.O, and Nvidia Corp NVDA.O shed between 2.65% and 4.88%. \\\"People who had been hoping for some kind of turnaround in the chips are starting to give up that hope,\\\" said Robert Pavlik, senior portfolio manager at Dakota Wealth in Fairfield, Connecticut. The S&P 500 technology sector .SPLRCT index fell 3.1%, leading declines among the 11 major sector indexes. At 10:02 a.m. ET, the Dow Jones Industrial Average .DJI was down 488.84 points, or 1.63%, at 29,438.10, the S&P 500 .SPX was down 80.05 points, or 2.14%, at 3,664.47, and the Nasdaq Composite .IXIC was down 309.86 points, or 2.80%, at 10,763.45. All three main Wall Street indexes are still set to snap a three-week losing streak, heading for their biggest weekly gain in almost a month. With the benchmark 10-year Treasury yield US10YT=RR rising to 3.8875%, most rate-sensitive technology and growth stocks such as \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 = 0.0332 (i.e., a 3.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0332 = 3.0139, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033179, "expected_loss": 0.033179, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220418_0334", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2022-04-18", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0203, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0008, std=0.0109, worst_day=-0.0206\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-14] [\"Mercury Systems (MRCY) Clinches $14M SiP Assemblies Contract Mercury Systems MRCY has been awarded a $14-million contract by a leading defense prime contractor for providing system-in-package (SiP) assemblies for an airborne secure processing application. The order, received in the third quarter of fiscal 2022, is anticipated to be delivered over the next few quarters. The latest agreement showcases the credibility of Mercury's advanced SiP assemblies across the defense sector. The high-performance solution will enable new sensor processing applications for various defense platforms and programs. It reflects the company\\u2019s deep commitment toward transforming the U.S Department of Defense while ensuring commercial technology\\u2019s availability across the sector. Back-to-Back Deals Mercury has been steadily winning multiple development contracts from the federal government. Recently, it won a $6.9-million contract from a leading defense prime contractor for providing OpenVPX digital signal processing systems for a manned airborne radar application. In March, it secured a $165-million indefinite delivery/indefinite quantity contract from the United States Air Force to provide flight data recorders to support a secure mission data system of the air services' F-16 fleet. Mercury Systems Inc Price and Consensus Mercury Systems Inc price-consensus-chart | Mercury Systems Inc Quote Prior to that, in January, the company received a $17-million contract to provide crucial multi-channel radiofrequency microelectronics to the United States and its allies for the enhancement of missile capabilities. In August 2021, Mercury received a $17-million order from the U.S. Naval Air Warfare Center's Aircraft Division. In July, it teamed up with CoreAVI, winner of the Military and Aerospace Electronics 2017 Innovators Platinum Award, to provide its aerospace and defense customers CoreAVI's safety-certified graphics, video and GPU compute solutions. In June 2021, Mercury achieved a significant milestone with the delivery of more than 1,000 NanoSWITCH rugged network switches to Oshkosh Defense for its Joint Light Tactical Vehicle program. Mercury's total bookings at the fiscal second-quarter end were $236.9 million, reflecting a book-to-bill ratio of 1.08. The company ended the quarter with a backlog of $953.7 million, up $8.4 million from a year ago. From this backlog, products worth $572.4 million are expected to be shipped within the next 12 months. Modernization in radar, EW and C4I is rapid, thus providing the company with new opportunities in weapon systems, space, avionics processing, and mission computing, as well as embedded rugged services. Mercury's domain expertise in analog and digital integration has helped it build a solid business relationship with defense prime contractors. However, pandemic-induced modernization delays and changes in administration and customer execution issues are likely to continue impacting the company's organic revenue growt\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 = 0.0203 (i.e., a 2.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0203 = 4.9232, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020312, "expected_loss": 0.020312, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201005_0337", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2020-10-05", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1932, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0093, std=0.1022, worst_day=-0.2453\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5177", "answer_numeric": 0.5177, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1932 (i.e., a 19.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1932 = 0.5177, capped at 1.0.\nMaximum position size = 0.5177 (51.8% of portfolio).", "metadata": {"var_99": -0.193159, "expected_loss": 0.193159, "max_drawdown_threshold": 0.1, "position_size": 0.5177, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170103_0342", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2017-01-03", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0115, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0012, std=0.0073, worst_day=-0.0129\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-12-30] [\"Which Wall Street Firm Made The Best Stock Picks Of 2016?\", \"Which Wall Street Firm Made The Best Stock Picks Of 2016?\", \"7 Stocks Near 52 Week-High with More Room to Run The year 2016 will likely be remembered as one of the most eventful ones. An unexpected regime change, a long overdue interest rate hike and one of the fastest economic growth in recent times have surely made a mark. With President-elect Donald Trump taking office in 2017, the year is slated to be one wild roller coaster ride that can reward some and punish others. Meanwhile, the growing presence of high-valued stocks has made the market overvalued. In such a scenario, it may be na\\u00efve to invest in value stocks. Also, the prolonged slowdown in the global economy restricts the chances of further growth in the near term. At this point, it would be prudent to stack up on great momentum stocks. One such trend is spotting stocks that are at or above the 52-week high mark. The 52-week investment strategy is one of the relatively new entries in the investing rulebook. Borrowing from the basics of Momentum investing, this technique bets on the principle of buying high and selling higher. A wide group of investors today favor winning stocks with prospects of scaling higher. These investors have mastered the art of finding stocks that have strong upside potential and are still undervalued. Clubbing 52-week high stocks with the correct set of parameters is all you need to turn the tide in your favor. How Does it Work? Stocks near 52-week highs often instill the presumptive \\\"adjustment and anchoring bias\\\" in the minds of investors. This principle works on the belief that investors use the 52-week high price as a reference point and value stocks against this anchor. Many a times such stocks are prevented from scaling higher despite robust potential, due to the psychological bias of investors who fear that the stocks are overvalued and a price crash is impending. A few of the stocks remain undervalued due to prolonged under reaction on part of investors despite bullish growth drivers. Meanwhile, news pertaining to robust sales, surging profit levels, bullish earnings prospects and strategic acquisitions can drive the stock higher. However, when a string of positive developments start dominating the market, investors find their under-reaction unwarranted and the renewed interest might drive stocks beyond the 52-week high bar. Wall Street's fast paced trading makes it imperative for investors to step in before the market gets a whiff of it. Meanwhile, market gurus believe that the current price level rather than past changes in prices better reflect a stock's momentum. This implies that if a stock is trading close to its 52-week high range, chances are that it will perform better in the subsequent period. The Parameters to Rely on Our diligent screening technique has been deployed to find 52-week high stocks that hold tremendous potential compared to their respective industries. The add\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 = 0.0115 (i.e., a 1.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0115 = 8.6885, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011509, "expected_loss": 0.011509, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20151026_0344", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2015-10-26", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0039, std=0.0141, 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 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 = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7310, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026803, "expected_loss": 0.026803, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20221202_0347", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2022-12-02", "context_summary": "WEAT: 60-day history, VaR(99%)=-0.0379, max drawdown threshold=10%.", "question": "Asset: WEAT\nDaily returns (past 60 days): mean=-0.0014, std=0.0191, worst_day=-0.0405\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to WEAT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; 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 = 2.6397, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037883, "expected_loss": 0.037883, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20181212_0350", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2018-12-12", "context_summary": "DBB: 60-day history, VaR(99%)=-0.0202, max drawdown threshold=10%.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=0.0008, std=0.0107, 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 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 = 0.0202 (i.e., a 2.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0202 = 4.9532, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020189, "expected_loss": 0.020189, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20201203_0353", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2020-12-03", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1697, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0014, std=0.0743, worst_day=-0.1811\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5894", "answer_numeric": 0.5894, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1697 (i.e., a 16.97% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1697 = 0.5894, capped at 1.0.\nMaximum position size = 0.5894 (58.9% of portfolio).", "metadata": {"var_99": -0.169651, "expected_loss": 0.169651, "max_drawdown_threshold": 0.1, "position_size": 0.5894, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210420_0356", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2021-04-20", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1809, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0078, std=0.0828, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-04-19] [\"The Station: A chat with Scale AI's Alexandr Wang, the NYC scooter winners and TuSimple goes public The Station is a weekly newsletter dedicated to all things transportation. Sign up here \\u2014 just click The Station \\u2014 to receive it every weekend in your inbox. This is The Station, a weekly newsletter dedicated to all the ways people and packages move (today and in the future) from Point A to Point B.\", \"FleetPride Acquires Steubenville Truck Center, Continues Parts and Service Expansion FleetPride, Inc. announced today that it has acquired the assets of Steubenville Truck Center in Steubenville, Ohio. For nearly 70 years, Steubenville Truck Center has been providing outstanding truck parts and service to customers in eastern Ohio, northern West Virginia, and western Pennsylvania. The company has been in its current location since 1998 and is managed by Larry Remp.\", \"Verizon starts C-Band equipment deployment What you need to know: Basebands, radios and antennas from Ericsson and Samsung are currently being deployed in the Verizon network.The arrival of RAN equipment in combination with Verizon\\u2019s recent tower agreements will speed deployment of 5G Ultra Wideband on existing infrastructure using C-band spectrum.100 million customers will have access to the game-changing 5G Ultra Wideband service using C-band spectrum by the end of the first quarter in 2022 NEW YORK, April 19, 2021 (GLOBE NEWSWIRE) -- Verizon recently began installation of C-band equipment from Ericsson and Samsung Electronics Co., Ltd to speed deployment of its 5G Ultra Wideband and fixed wireless broadband service on its recently acquired C-band spectrum. Verizon secured an average of 161 MHz of C-band spectrum nationwide in the recent FCC auction, which will allow the company to offer expanded mobility and broadband services to millions more consumers and businesses. C-band spectrum provides a valuable middle ground between capacity and coverage for 5G networks, and will enable 5G Ultra Wideband speeds and coverage for both mobility, home broadband and business internet solutions. Deploying 5G Ultra Wideband on this spectrum requires new network equipment including basebands, radios and antennas to be placed on existing towers. Verizon tapped Ericsson and Samsung to supply the Radio Access Network (RAN) equipment for this massive deployment. Although the initial spectrum won\\u2019t be cleared until the end of this year, Verizon and its vendor partners have already begun the work to ensure the super-fast 5G Ultra Wideband service using C-band is deployed to 100 million customers by March 2022. \\u201cWe\\u2019re moving fast, with cooperation from our equipment partners, to have everything in place as soon as this C-band spectrum is cleared for use,\\u201d said Kyle Malady, Chief Technology Officer at Verizon. \\u201cThis is a massive undertaking designed to add this game-changing capability as quickly as possible to the network our customers already rely on for consiste\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": "0.5528", "answer_numeric": 0.5528, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1809 (i.e., a 18.09% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1809 = 0.5528, capped at 1.0.\nMaximum position size = 0.5528 (55.3% of portfolio).", "metadata": {"var_99": -0.180907, "expected_loss": 0.180907, "max_drawdown_threshold": 0.1, "position_size": 0.5528, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150409_0359", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2015-04-09", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0183, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0025, std=0.0084, worst_day=-0.0198\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-04-08] [\"Jabil a Buy Even if Business With Apple Ebbs Raymond James is upgrading the electronics supplier to Outperform with a price target of $27, about 16% above current levels.\", \"Apple cut to hold from buy at Societe Generale\", \"Apple's stock slips 0.3% in premarket trade after Societe Generale downgrade\", \"Apple's stock slips after Societe Generale downgrade NEW YORK (MarketWatch) -- Shares of Apple Inc. slipped 0.3% in premarket trade Wednesday, after Societe Generale downgraded the technology giant, citing concerns over smartphone selling prices and the negative effects of currency movements. Analyst Andy Perkins cut his rating to hold, after being at buy for the last 10 months, but kept his stock price target at $130, which is 3.2% above Tuesday's closing price or $126.01. He estimates that average selling prices of iPhones declined to $651 each during the March quarter from $687 in the December quarter, as the number of iPhone 6 and iPhone 6 Plus models declined as a percentage of total units sold. Perkins also said his breakdown of handset sales by country implies a 5% currency headwind given the U.S. dollar's strength during the quarter. Regarding the Apple Watch, Perkins expects sales to represent just 1.7% of total sales for fiscal 2015, compared with 63% for handsets, so he wrote in a note to clients that \\\"investors' focus should remain firmly on handsets, at least for now.\\\" The stock has run up 14% year to date, while the S&P 500 has gained 0.9%.\", \"Sideways market looks to Fed minutes, earnings kickoff for direction Critical intelligence before the U.S. market opens Earnings season gets under way this afternoon, and investors aren\\u2019t exactly buzzing over the prospects.\", \"Apple edges down 0.2% in wake of SocGen downgrade\", \"Apple hit by rare analyst downgrade Soc Gen analyst plays down importance of Apple Watch Apple\\u2019s stock was downgraded by an analyst at Soci\\u00e9t\\u00e9 G\\u00e9n\\u00e9rale, who cited concerns over future iPhone sales and played down the importance of the much-hyped Apple Watch, which goes on sale this month.\", \"Amazon hints at smart home future through Echo device Amazon informed Echo owners about some new services in an email Wednesday.\", \"Apple Watch Draws Raves for Sophistication, Functionality; Software Updates on The Way\", \"When it comes to stocks vs. cash, follow Buffett\\u2019s lead When volatility crops up in the market, many people decide to head for the exit, but if you were Warren Buffett, you\\u2019d be doing something else.\", \"U.S. stocks finish slightly higher after release of Fed minutes Stocks choppy as investors digest minutes against recent data U.S. stocks close slightly higher Wednesday in volatile trading following the release of Fed meeting minutes where several Federal Reserve officials had favored a June rate hike.\", \"Alcoa shares decline as revenue falls short of Street view Zynga shares drop on CEO departure Alcoa shares decline in the extended session Wednesday after the aluminum 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 = 0.0183 (i.e., a 1.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0183 = 5.4701, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018281, "expected_loss": 0.018281, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160308_0364", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2016-03-08", "context_summary": "SCHH: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%.", "question": "Asset: SCHH\nDaily returns (past 60 days): mean=0.0005, std=0.0129, worst_day=-0.0299\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 = 0.0289 (i.e., a 2.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0289 = 3.4627, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028879, "expected_loss": 0.028879, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20221124_0367", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2022-11-24", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0434, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0019, std=0.0243, worst_day=-0.0438\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-23] [\"Paramount (PARA) to Stream Top Gun: Maverick on Paramount+ Paramount Global PARA recently announced that it will be streaming Top Gun: Maverick on Paramount+ from Dec 22 in the United States, Canada, Australia, Germany, Switzerland, Austria, Italy, the U.K. and Latin America. In South Korea and France, it will be available from 2023. Top Gun: Maverick had a blockbuster performance across theatres as it remained in the top five on domestic box office charts for 14 of the 15 weeks since release in America. The film also set a holiday record with its $160.5 million debut and became Tom Cruise\\u2019s first movie to surpass $100 million in a single weekend, as well as his first to cross $1 billion in worldwide ticket sales. The movie gained traction and received huge support from fans on the big screen and the same is anticipated as it now heads towards its OTT launch. Paramount+ Aids Growth Paramount has been focused on setting a strong pipeline of movies and shows for its viewers on the streaming platform. The company recently unveiled its plans to celebrate the 50th anniversary of hip hop music and culture, for which Paramount+ will offer 50 of the most iconic episodes of MTV Entertainment\\u2019s original series Yo! MTV Raps for the first time since it premiered and episodes from the home-makeover series, Hip Hop My House. Paramount+ also announced the revival of the popular FBI drama, Criminal Minds. This is expected to fuel its fan base, which will pay even bigger returns after adding 4.6 million subscribers in the third quarter of 2022 and gaining 95% in revenues year over year. Paramount Global Price and Consensus Paramount Global price-consensus-chart | Paramount Global Quote Paramount also entered a new multi-year distribution agreement with Virgin Media, under which, Paramount+ will debut on Virgin TV in 2023 and Pluto TV will be more widely distributed on Virgin TV 360 and stream services. Besides expanding the content library, Paramount+ has also been expanding its footprints globally. It has plans to introduce Paramount+ in Germany, Austria and Switzerland and in France with Canal+ this year. What Lies Ahead for Paramount? Despite the wide expansion, Paramount faces certain headwinds. Advertisers continue to deal with macroeconomic challenges like inflation, higher interest rates and unfavourable forex with the U.S. dollar strengthening. This has led to cutbacks in their spending and has hindered the company\\u2019s top-line growth. Paramount is facing stiff competition from the likes of Disney DIS and Apple AAPL in the streaming market, which is currently dominated by Netflix NFLX. Netflix reported better-than-expected third-quarter 2022 subscriber numbers. It gained 2.41 million paid subscribers globally, higher than its estimate of gaining one million users. Disney lost 37.9% shares year to date. Disney+ added 12.1 million subscribers in fourth-quarter fiscal 2022. Both Netflix and Disney are set to launch their ad-tier subscriptions \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_20180320_0369", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2018-03-20", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1586, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0173, std=0.0775, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6304", "answer_numeric": 0.6304, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1586 (i.e., a 15.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1586 = 0.6304, capped at 1.0.\nMaximum position size = 0.6304 (63.0% of portfolio).", "metadata": {"var_99": -0.158636, "expected_loss": 0.158636, "max_drawdown_threshold": 0.1, "position_size": 0.6304, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20150707_0372", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2015-07-07", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0199, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0003, std=0.0078, worst_day=-0.0244\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-07-06] The Zacks Analyst Blog Highlights: Automatic Data Processing, Marriott Vacations Worldwide, Carnival and SkyWest - Press Releases For Immediate Release Chicago, IL - July 06, 2015 - 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 the Automatic Data Processing, Inc. ( ADP ), Marriott Vacations Worldwide Corp. ( VAC ), Carnival Corporation ( CCL ) and SkyWest Inc. ( SKYW ). Today, Zacks is promoting its ''Buy'' stock recommendations. Get #1Stock of the Day pick for free . Here are highlights from Thursday's Analyst Blog: 3 Travel Stocks for Summertime Fun Independence Day travel weekend is poised to be the busiest for holidaymakers since 2007. According to the American Automobile Association (AAA), around 41.9 million travelers are projected to travel 50 miles or more during the weekend. Cheaper gasoline prices, an upbeat labor market and a rise in consumer confidence are prompting more number of people to plan a holiday getaway this weekend. The Independence Day weekend is usually the busiest summer holiday travel period. Fourth of July Weekend Travel to Rise Independence Day Weekend travel is anticipated to increase 0.7% from 41.6 million people who traveled last year. Additionally, estimates for travelers during the Independence Day weekend is 13% higher compared to the forecasted Memorial Day weekend travelers. (Read: Memorial Day Weekend Travel to Hit 10-Yr High: 3 Choices ) Almost 85% or 35.5 million travelers are expected to drive, an increase of 0.7% over last year's Independence Day weekend. This would also be the highest since 2000. Travelers, in general, are already driving more. According to the Federal Highway Administration, travelers drove 987.8 billion miles for the first four months of 2015, topping 2007's record of 965.5 billion. Air travel is expected to account for 7.7% of all Independence Day holiday travel. About 3.21 million leisure travelers will take to the sky, which is 1.5% higher than year ago level. Additionally, a record number of travelers are expected to fly this summer season surpassing the pre-recession high in 2007, according to Airlines for America. (Read: Airlines Expect Busiest Summer Ever: 2 Stock Picks ) Meanwhile, travel by other modes of transport including cruises, trains and buses are expected to increase 0.5% to 3.2 million this Independence Day holiday. However, travelers will have to bear moderately higher lodging costs this Independence Day. According to AAA's Leisure Travel Index, average stay in a Three Diamond hotel will cost 9% higher this year at $195, while the cost of a Two Diamond hotel will be 6% higher this year at $145. Additionally, airfares for the top 40 domestic flights may also rise 6% to $227 this year. Nevertheless, cheap gasoline prices and rise in wages are expected to boost disposable income, w\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 = 0.0199 (i.e., a 1.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0199 = 5.0158, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019937, "expected_loss": 0.019937, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20221107_0375", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2022-11-07", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0588, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0017, std=0.0258, worst_day=-0.0927\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-06] \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 = 0.0588 (i.e., a 5.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0588 = 1.7018, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.058763, "expected_loss": 0.058763, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20221026_0378", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2022-10-26", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0325, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0024, std=0.0131, worst_day=-0.0341\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-25] [\"Why Is Everyone Talking About Apple? Apple's (NASDAQ: AAPL) stock has fallen about 10% since mid-September. The leading causes for the dip have been numerous reports that sales for its base-model iPhone 14 and 14 Plus have been underwhelming and an overall slowdown of consumer demand in the tech market. As the highest-valued company in the world, with a market cap of $2.37 trillion, Apple is one of the world's most scrutinized companies. The last two months have been no different as analysts pick apart the company's September iPhone launch and its 2022 iPad lineup unveiling in mid-October. Understanding the strategy behind Apple's recently announced products can be a great way to predict how far your investment will go. So, here's why Apple's new products have been making headlines. A confusing iPad launch On Oct. 18, Apple unveiled its 2022 iPad refresh by introducing a newly designed base iPad and upgraded iPad Pros. Time will tell how the new Apple tablets fare with consumers, but the media has been quick to criticize the devices. Bloomberg has called the new iPad lineup \\\"perplexing,\\\" while Techradar said its \\\"software and now hardware is a mess.\\\" The primary reason for the confusion lies in upgrades to the entry-level iPads, but not the Pro versions. The base iPads received a redesign with new colors, relocation of the front-facing camera to the landscape's edge, and a revamped Magic Keyboard accessory. Meanwhile, the 2022 iPad Pro models received the smallest update in their history. They were bumped up to the M2 chip, making them 15% faster than their predecessors, along with other minor performance upgrades. However, the higher-cost versions didn't receive the same optimal camera relocation or the redesigned Magic Keyboard. The Pro models didn't even receive the customary camera or display improvements that consumers have come to expect year to year. As a result, Apple has given consumers little reason to upgrade to the 2022 iPad Pro and created confusion by omitting features given to the base iPad. Moreover, despite the base iPad's more enticing improvements, it has not been left unscathed by criticism. The tablet has undergone a significant redesign, including its charging port going from lightning to the market-preferred USB-C. However, it is still only compatible with the 2015 Apple Pencil accessory that charges via lightning rather than the redesigned 2018 version that charges magnetically along the side of higher-tiered iPads. As a result, users need to use an adapter to charge their Apple Pencil with the new base iPad. iPhone 14 Plus is a bust In addition to a confusing iPad lineup, Apple has reportedly faced dismal demand for its iPhone 14 Plus, which hit stores on Oct. 7. The base-model iPhone was announced on Sept. 7, along with two new Pro models and a standard-sized base model. Apple had high hopes for the larger iPhone 14 as it signified a shakeup in the lineup. There hasn't been a Plus-sized base model since 2017's iPho\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 = 0.0325 (i.e., a 3.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0325 = 3.0808, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032459, "expected_loss": 0.032459, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220628_0383", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2022-06-28", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0335, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0025, std=0.0177, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-27] [\"CEOs will look past abortion bans, too Reuters Reuters NEW YORK (Reuters Breakingviews) - The demolition of the constitutionally protected right to an abortion in the United States is historic. But for companies doing business in America, the cost-benefit analysis it provokes will feel familiar. Corporate bosses will end up viewing America\\u2019s illiberal states the way they do any emerging market. Each state will be left to decide how and whether to regulate abortion after the Supreme Court on Friday decided that protections of \\u201clife, liberty, or property\\u201d don\\u2019t include ending a pregnancy as a right. At least eight states had already banned the procedure by Monday, and around half of the 50 are primed to outlaw it under statutes already in place. Removing access to abortion could increase maternal deaths https://read.dukeupress.edu/demography/article/58/6/2019/265968/The-Pregnancy-Related-Mortality-Impact-of-a-Total by over one-fifth, according to Duke University, and Black maternal deaths by one-third. Recognizing the anxiety, companies have moved to reassure their staff: Facebook owner Meta Platforms and Goldman Sachs are among those offering to fund travel costs for employees who need to go out of state for healthcare and reproductive services. But if the majority of Americans https://www.cbsnews.com/news/americans-react-to-roe-v-wade-overturn-opinion-poll-2022-06-26 who oppose the overturning of Roe vs. Wade hope their large, powerful employers will do more, they will be disappointed. Multinationals long ago made peace with setting up shop in locations where freedoms taken for granted in some countries are limited in the name of stability or ideology. Foreign direct investment into China surged by a third to $344 billion last year, according to Peterson Institute for International Economics. Net foreign investment in Saudi Arabia jumped more than threefold in 2021, according to state media. China and states like Texas are in that way somewhat similar. The Lone Star state offers low taxes, good universities, rich natural resources, and scale. Accepting bans on abortion is simply the cost of doing business for companies like Goldman Sachs and Apple. So is turning a blind eye to the governing Texas Republican Party\\u2019s recent declaration that \\u201chomosexuality\\u201d is \\u201can abnormal lifestyle choice https://texasgop.org/wp-content/uploads/2022/06/6-Permanent-Platform-Committee-FINAL-REPORT-6-16-2022.pdf,\\u201d an awkward reality for companies that trumpet their commitment to diversity. Emerging-market attitudes don\\u2019t always create economic success for nations \\u2013 or states. Mississippi, for example, has no Fortune 500 companies headquartered within its borders. It\\u2019s also the state with the least well-functioning healthcare system https://www.commonwealthfund.org/publications/scorecard/2022/jun/2022-scorecard-state-health-system-performance in the country, according to the Commonwealth Fund. Even then, the\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 = 0.0335 (i.e., a 3.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0335 = 2.9889, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033457, "expected_loss": 0.033457, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200904_0386", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2020-09-04", "context_summary": "BNO: 60-day history, VaR(99%)=-0.0373, max drawdown threshold=10%.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=0.0023, std=0.0157, worst_day=-0.0504\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 = 0.0373 (i.e., a 3.73% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0373 = 2.6815, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037293, "expected_loss": 0.037293, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210922_0391", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2021-09-22", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0350, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0024, std=0.0184, worst_day=-0.0360\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-09-21] [\"Over 2 Billion Devices Will be Shipped with a Dedicated Chipset for Ambient Sound or Natural Language Processing By 2026 Natural Language Processing (NLP) and ambient sound processing are traditionally considered exclusive cloud technologies and this has restricted their adoption in markets where security, privacy, and service continuity are critical elements for deployment. However, the advancements in deep learning compression technologies and edge Artificial Intelligence (AI) chipsets are now enabling these technologies to be integrated at the end-device level, which could mitigate security and privacy concerns\", \"PDMR Shareholding Notification of Transactions by Persons Discharging Managerial Responsibilities and Persons Closely Associated with them [This form is required for disclosure of transactions under Article 19 of Regulation (EU) No 596/2014 of the European Parliament and of the Council of 16 April 2014 on market abuse (Market Abuse Regulation)] 1Details of the person discharging managerial responsibilities/person closely associated a)NameAndrew Sheen 2Reason for the notification a)Position/statusPDMR / Managing D\", \"Apple adds new personalized recommendations in Podcasts' Listen Now page Apple has introduced new sharing and personalized recommendation features for Podcasts on iOS 15.\", \"Google\\u2019s updated iOS 15 apps support Focus Mode and iPad widgets One of those is Google, which detailed today the iOS 15-related enhancements you can expect from its apps. The biggest change involves how Gmail, Meet, Tasks, Maps, Home and many of Google's other applications will handle notifications. Should you have iOS 15\\u2019s new Focus Mode enabled, Google says prompts that don\\u2019t require your immediate attention will go to the Notifications Center where you can deal with them later.\", \"iPhone 13 and 13 mini review Should you get the iPhone 13 and 13 mini? Depends on how badly you want the new camera features and upgraded battery.\", \"Marvel shows are now available through Apple Podcast subscriptions Marvel and SiriusXM have opened a new Apple Podcasts channel, which includes a paid tier. The free Marvel channel includes Marvel's Wolverine: The Long Night and the sequel, Marvel's Wolverine: The Lost Trail. You'll be able to listen to Marvel/Method, in which Method Man interviews celebrities about Marvel, and This Week in Marvel, a weekly show about the latest news in the company's ecosystem.\", \"The iPhone 13 Pro goes to Disneyland This year\\u2019s iPhone review goes back to Disneyland for the first time in a couple of years for, uh, obvious reasons. One of the major reasons I keep bringing these iPhones back to Disneyland is that it\\u2019s pretty much the perfect place to test the improvements Apple claims it is making in an intense real-world setting. In my testing, most of Apple\\u2019s improvements actually had a visible impact on the quality of life of my trip, though in some cases not massive.\", \"Dynamic head tracking is now availabl\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 = 0.0350 (i.e., a 3.50% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0350 = 2.8547, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03503, "expected_loss": 0.03503, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201027_0394", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2020-10-27", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0314, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0012, std=0.0133, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-10-26] [\"Apple, Amazon, Boeing, Visa, Pfizer, and Other Stocks to Watch This Week Microsoft, Apple, Alphabet, Facebook, Amazon, AMD, Caterpillar, Comcast, GE, Ford, Pfixer, Visa, UPS, Exxon Mobil, Twitter, and more companies report third-quarter results.\", \"Apple earnings will be missing the usual star attraction The end of Apple Inc.'s fiscal year usually leads to a game of \\\"How is the new iPhone doing,\\\" but that gets a little harder in 2020.\", \"Ready for another Big Tech hearing/earnings doubleheader? Three months ago, Big Tech's biggest names traipsed into a Congressional hearing to be berated by politicians for their business dominance, then paraded in front of Wall Street a day later to be cheered for their financial dominance. Somebody must have enjoyed that, because it is about to happen all over again.\", \"Facebook earnings: Cleaning up content has been focus before elections As Facebook prepares to report its third-quarter results on Oct. 29, the company finds itself navigating the Beltway as much as Wall Street.\", \"Alphabet earnings: Antitrust charges cast long shadow over Google The historic lawsuit will be an underlying theme, both in the short- and long-term, when Google announces third-quarter results on Oct. 29 --- the same day as Facebook Inc., Amazon.com Inc., Apple Inc., and a raft of other tech companies.\", \"Big Tech Companies Report Third Quarter Earnings This Week The raft of earnings comes as large technology platform companies have come under increased scrutiny from regulators and politicians.\", \"Barron\\u2019s Daily: Dunkin\\u2019 Brands May Be Bought Out. Why Covid Has Boosted M&A. Europe tightens restrictions in desperate race against Covid second wave, Pence will continue campaign after aides\\u2019 positive Covid tests, Barrett set to be confirmed to Supreme Court, and other news to start your day.\", \"9 Promising Stocks From Emerging Markets Selection is key. But in overseas markets, there are a number of internet and health-care companies that are still in their growth trajectories, offering big opportunities.\", \"Dow Slumps as Election, Stimulus, Covid-19 and Earnings Worries Spike Earnings from SAP were added to an already combustible mix, helping to send the market sharply lower.\", \"All 30 Dow stocks are falling, led by American Express and Boeing Shares of all 30 components of they Dow Jones Industrial Average are falling in midday trading Monday, with 29 of them losing more than 1%, as the recent surge in new COVID-19 cases and the lack of progress on stimulus talks shook investor confidence. The Dow tumbled 682 points, or 2.4%, Among the Dow's biggest percentage losers, shares of American Express Co. shed 4.1%, Boeing Co. gave up 3.8% and Salesforce.com Inc. slid 3.5%. The biggest price decliners were shares of Saleforce, down $8.71, and UnitedHealth Group Inc. , down $8.15; combined, those stocks shaved about 111 points off the Dow's price. The Dow's best performer, and the lone stock that was down more than 1%, was Appl\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 = 0.0314 (i.e., a 3.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0314 = 3.1835, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031412, "expected_loss": 0.031412, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190926_0397", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-09-26", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0924, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0014, std=0.0310, worst_day=-0.1140\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0924 (i.e., a 9.24% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0924 = 1.0819, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.092432, "expected_loss": 0.092432, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20150602_0400", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["CPER"], "decision_date": "2015-06-02", "context_summary": "CPER: 60-day history, VaR(99%)=-0.0297, max drawdown threshold=10%.", "question": "Asset: CPER\nDaily returns (past 60 days): mean=-0.0000, std=0.0149, worst_day=-0.0313\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CPER, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0297 (i.e., a 2.97% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0297 = 3.3726, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029651, "expected_loss": 0.029651, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20171009_0403", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2017-10-09", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0104, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0004, std=0.0057, worst_day=-0.0108\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-10-06] [\"IYW, ADBE, CRM, CTSH: Large Outflows Detected at ETF Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the iShares U.S. Technology ETF (Symbol: IYW) where we have detected an approximate $98.7 million dollar outflow -- that's a 2.6% decrease week over week (from 24,600,000 to 23,950,000). Among the largest underlying components of IYW, in trading today Adobe Systems Inc (Symbol: ADBE) is up about 0.5%, Salesforce.com Inc (Symbol: CRM) is up about 0.7%, and Cognizant Technology Solutions Corp. (Symbol: CTSH) is higher by about 0.6%. For a complete list of holdings, visit the IYW Holdings page \\u00bb The chart below shows the one year price performance of IYW, versus its 200 day moving average: Looking at the chart above, IYW's low point in its 52 week range is $114.68 per share, with $151.91 as the 52 week high point - that compares with a last trade of $151.86. 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 experienced notable outflows \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"MKSI Instruments Looks Bullish on Robust Growth Drivers We issued an updated research report on premium scientific and technical instruments company, MKS Instruments, Inc.MKSI , on Oct 6. In the last month, shares of this Zacks Rank #2 (Buy) stock have yielded a return of 91.2%, outperforming 57.4% growth recorded by the industry . Notably, the attractiveness of this stock as a current investment choice is further accentuated by its favorable VGM Score B. Also, the stock's projected sales growth is 41.8% and earnings per share growth is 79.5% for 2017 compared to the respective tallies of 10.7% and 57.1% estimated for the industry. Moreover, the company's earnings are projected to be up 15.7% in the next three to five years. Why Should You Grab the Stock? MKS Instruments has a well-balanced technology portfolio and in\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 = 0.0104 (i.e., a 1.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0104 = 9.6220, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010393, "expected_loss": 0.010393, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220126_0408", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2022-01-26", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0403, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0022, std=0.0174, worst_day=-0.0411\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-25] [\"7 Best Technology Stocks to Buy After the Big Dip InvestorPlace - Stock Market News, Stock Advice & Trading Tips So far, 2022 is a huge bummer for technology stocks. But that won\\u2019t last forever. Technology stocks are taking an oversized beating to start the year. While the Dow Jones Industrial Average is down 7.5% year-to-date (YTD), the more tech-heavy Nasdaq composite is down 14.3% YTD. Exchange-traded funds like the Technology Select Sector SPDR Fund (NYSEARCA:XLK) are suffering, as well. The XLK is down more than 9% since Jan. 1. Tech stocks are the worst-performing sector in the S&P 500, according to the Wall Street Journal. Tech stocks in particular are being pressured as investors are turning instead to rising yields offered by government-backed bonds. Deutsche Bank analyst Jim Reid says so far, 2022 has been \\u201ca perfect negative storm for tech.\\u201d But here\\u2019s the thing about storms \\u2014 the clouds eventually part and the sun comes out again. And for technology stocks, that means a return to growth and profits. 7 Dividend Stocks to Profit off the Hot Real Estate Market When that happens, you\\u2019ll want to own these seven technology stocks: Microsoft (NASDAQ:MSFT) Nvidia (NASDAQ:NVDA) Visa (NYSE:V) Adobe (NASDAQ:ADBE) Broadcom (NASDAQ:AVGO) Salesforce (NYSE:CRM) PayPal (NASDAQ:PYPL) Best Technology Stocks to Buy: Microsoft (MSFT) MSFT) logo above the entrance.\\\" width=\\\"300\\\" height=\\\"169\\\"> Source: NYCStock / Shutterstock.com Microsoft was in the news lately with its announcement that it will buy video game publisher Activision Blizzard (NASDAQ:ATVI) for $68.7 billion. It would be the biggest tech deal ever. But that\\u2019s par for the course. Microsoft never does anything small. With its fingers in cloud, gaming and consumer businesses, MSFT has a market cap of $2.16 trillion these days. The stock rose more than 50% in 2021. Revenue jumped by 18% for the year, and earnings per share rose by 40%. But 2022 has been rough so far. MSFT stock is down 15.8% since Jan. 1 and Wall Street will eagerly be watching the company\\u2019s earnings report on Jan. 25. Analysts are calling for Microsoft to report revenues of $50.88 billion and earnings per share of $2.31. That would be a great way for Microsoft to start the year. The average price estimate for MSFT stock is $373.24, which represents a more than 25% upside from current levels. Nvidia (NVDA) Source: michelmond / Shutterstock.com Nvidia was another high-flyer in 2021 that has come down to earth. At one point last year, NVDA stock was up by more than 125% on a year-to-date basis. And even after it started falling in November, Nvidia still managed a 2021 gain of more than 70%. Over the last five years, Nvidia is up nearly 900%. You can\\u2019t ask for anything more from a stock. But 2022 has been a different story so far. Nvidia dropped 24% since the calendar turned in January. With a market cap of $555.86 billion, Nvidia is too much of a powerhouse and growth engine to falt\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 = 0.0403 (i.e., a 4.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0403 = 2.4800, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.040322, "expected_loss": 0.040322, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170207_0411", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2017-02-07", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0198, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0003, std=0.0093, worst_day=-0.0227\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-02-06] [\"Apple, Google among nearly 100 tech firms fighting Trump\\u2019s travel ban in court Companies claim president\\u2019s immigration order harms U.S. business, innovation and growth In a joint amicus brief filed in the Ninth U.S. Circuit Court of Appeals on Sunday, the firms challenge President Donald Trump\\u2019s executive order which temporarily restricts citizens of seven Muslim-majority countries from entering the U.S.\", \"Expect even more good news about Apple Analysts are likely to continue upping their estimates of Apple\\u2019s EPS Analysts are likely to continue upping their estimates of Apple\\u2019s per-share earnings.\", \"Trump rips polls as \\u2018fake news\\u2019 | Tech companies call travel ban unlawful Republicans\\u2019 Obamacare tax decision President Trump rips polls as \\u2018fake news\\u2019; tech companies call travel ban unlawful; Republicans\\u2019 Obamacare tax decision; and more.\", \"My dad talked me out of the decade\\u2019s best investment, but he wasn\\u2019t wrong Netflix is up about 3,400% over the past nine years, and I missed it The worst financial advice I ever got also happened to be correct.\", \"Apple Building \\u2018iPhone 8\\u2032 Earlier Than Normal, It Would Appear, Says BlueFin Boutique research firm BlueFin Research Partners\\u2019s John Donovan and Steve Mullane this morning write that they are seeing some indication Apple is ramping up production of its next iPhone, presumably an \\\"iPhone 8,\\u201d earlier than expected, thought it\\u2019s not clear if that means there will be any change in the release date of the device.\\\"Early indication AAPL trying to pull in next generation iPhone builds as much as possible,\\u201d write the authors.The most intriguing data points that we have uncovered suggests that AAPL is ramping the next generation iPhones earlier than historical norms, although we have no indication that there has been any change in release plans for the iPhone 8/X. Builds have been pulled in a few months while aggregate next generation forecasts have increased 10% from last month to 122M. Additionally, AAPL has adjusted iPhone 7, 7 Plus, and SE production downward in preparation for the next generation launch.Without citing specific sources, the authors say they\\u2019re seeing indications of the iPhone 8 in the supply chain plans for June, earlier than usual:\", \"Tech Today: High Bar for Nvidia, Good Times for Chips, Snap\\u2019s Youth Trap Here are some things going on today in your world of tech:Reflecting on the chip market, Wells Fargo\\u2019s David Wong writes this morning that an 18% jump in chip sales in December, reported by the Semiconductor Industry Association, reinforces his view \\u201cthe chip industry has entered the first stages of a recovery, which we expect to last through 2017.\\\"He raises his semi revenue growth projection to 11% to 17% for this year from an 8% to 14% level. Wong has Outperform ratings on AMD (AMD) and Micron Technology (MU), among others.On a similar note, B. Riley\\u2019s Craig Elli\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 = 0.0198 (i.e., a 1.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0198 = 5.0601, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019762, "expected_loss": 0.019762, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220721_0414", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2022-07-21", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0358, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=-0.0016, std=0.0175, worst_day=-0.0368\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-20] [\"US STOCKS-Nasdaq rises on positive earnings signals as inflation concerns loom By Echo Wang July 20 (Reuters) - The tech-heavy Nasdaq climbed over 1% on Wednesday as investors digest the latest earnings as positive signals of the economy, albeit rising concerns on inflation and a tightening Fed. The S&P 500 edged up 0.39% while the Dow Jones Industrial Average slipped 0.12%. Netflix Inc's NFLX.O shares jumped 6% after the company predicted it would return to customer growth during the third quarter, while posting a smaller-than-expected 1 million drop in subscribers in the second quarter. Other high-growth stocks extended gains following the forecast from the streaming service provider. Shares of Apple Inc AAPL.O, Amazon.com Inc AMZN.O, Microsoft Corp MSFT.O and Meta Platforms Inc META.O added between 1% and 3.6%. The S&P 500 technology sector index .SPLRCT rose 1.3%. \\u201cInflation remains a very strong consideration on investors\\u2019 minds\\u2026 what we are seeing today are some positive earnings announcements allowing investors to hang their hats on some positive news that should bode better for the remainder of Q3, and 2022,\\u201d said Greg Bassuk, chief executive at AXS Investments in Port Chester, New York. \\u201cFor Tesla, and Netflix and some of these bellwether companies \\u2026 investors are looking for messaging on the outlook that these companies have on the balance of 2022.\\u201d Electric vehicle maker Tesla Inc TSLA.O added 0.6% ahead of its earnings report after market close. Analysts expect aggregate year-on-year S&P 500 profit to grow 5.9% in this reporting season, down from the 6.8% estimate at the start of the quarter, according to Refinitiv data. Runaway inflation initially led markets to price in a full 100-basis-point hike in interest rates at the Fed's upcoming meeting next week, until some policymakers signaled a 75-basis-point increase. At 1:45 p.m. ET, the Dow Jones Industrial Average .DJI fell 37.45 points, or 0.12%, to 31,789.6, the S&P 500 .SPX gained 15.19 points, or 0.39%, to 3,951.88 and the Nasdaq Composite .IXIC added 145.44 points, or 1.24%, to 11,858.59. Trading remained volatile in thin volumes, with the CBOE Volatility index .VIX last down 24.05 points to its lowest in over a month. \\\"Low volumes accentuate market moves historically and even though we've wiped off $10 or $15 trillion from global equities this year, there's still a lot of excess liquidity. So low volume on excess liquidity can still accentuate moves,\\\" John Lynch, chief investment officer for Comerica Wealth Management, said. Health insurer Elevance Health Inc ELV.N plunged 9% as the largest S&P percentage loser, as the company\\u2019s medical costs failed to decrease in line with rival UnitedHealth Group Inc. Baker Hughes Co BKR.O tumbled 7.8% as the oilfield services provider reported a bigger second-quarter loss, while its adjusted profit also missed estimates. Advancing issues outnumbered declining ones on the NYSE by a 1.55-to-1 ratio; \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 = 0.0358 (i.e., a 3.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0358 = 2.7966, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035758, "expected_loss": 0.035758, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20221020_0417", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2022-10-20", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0006, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0001, std=0.0003, 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 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 = 0.0006 (i.e., a 0.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0006 = 166.9237, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000599, "expected_loss": 0.000599, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210810_0420", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2021-08-10", "context_summary": "UNG: 60-day history, VaR(99%)=-0.0384, max drawdown threshold=10%.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=0.0045, std=0.0188, worst_day=-0.0432\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 = 0.0384 (i.e., a 3.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0384 = 2.6027, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.038422, "expected_loss": 0.038422, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200612_0423", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2020-06-12", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0328, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0016, std=0.0187, worst_day=-0.0328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-11] [\"Can the all-new Cadillac CT5 take on its European competitors? Review: It\\u2019s meant to compete with European big boys like the BMW 3 Series and the Audi A4 The 2020 Cadillac CT5 review: The price is well below its in-segment competitors, but it doesn\\u2019t raise the bar.\", \"American muscle: We compare a Chevy Camaro to Dodge Challenger Take a look at the differences and similarities between the Challenger and the Camaro and see which one is right for you Dare to compare: The Challenger and Camaro are direct competitors in American muscle cars.\", \"Apple stock gets an upgrade at HSBC on services optimism Apple Inc. has a big opportunity to leverage its installed base of devices to drive services growth, HSBC analyst Nicolas Cote-Colisson wrote in a Wednesday note to clients. He upgraded Apple's stock to hold from sell in the report, writing that while he still has macroeconomic concerns about the company's overall business, there's also potential for the company to \\\"sustain innovation\\\" that could drive further momentum for its services segment, particularly around health care. \\\"The pandemic will, in our view, create more demand for health-related tools and Apple could play a large role in addressing that demand,\\\" Cote-Colisson wrote. Health represents \\\"the first or second largest sector in the economy\\\" depending on countries, he said, though Apple could face challenges getting regulatory clearance to collect health data. Cote-Colisson raised his price target on Apple to $295 from $225 in the report. Wells Fargo's Aaron Rakers took a more upbeat view, boosting his target to $385 from $315 in a Thursday note. \\\" Despite the strong [year-to-date] outperformance we have seen in shares of Apple...we continue to believe investors will view this as a favored high-quality large cap name given continued evidence of a post-COVID recovery in smartphone demand, coupled with an expectation of a positive 5G cycle materializing into late-2020/2021,\\\" Rakers wrote, even if that cycle is delayed by a month or two due to the pandemic. Apple shares are down 1.5% in premarket trading Thursday, though they've gained 12% over the past month as the Dow Jones Industrial Average has added 11%.\", \"Apple stock price target raised to $390 from $340 at BofA Securities\", \"As Apple Stock Hits Record Prices, Analysts See Higher Highs Ahead Three more Wall Street pundits turned incrementally more positive on the prospects for the company, which yesterday crossed the $1.5 trillion market capitalization level for the first time ever.\", \"Picking Winners and Losers as Video Streaming and Cord-Cutting Grow Consumers have finally hit a ceiling on how much money they\\u2019re willing to spend on video content\\u2014and the market is headed for a period of deep disruption that will only exaggerate recent trends in cord-cutting and subscription services.\", \"Apple to devote $100 Million to racial-justice initiative \\u2018Things must change\\u2019 Apple Chief Executive Tim Cook said\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 = 0.0328 (i.e., a 3.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0328 = 3.0503, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032784, "expected_loss": 0.032784, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200625_0430", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-06-25", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1267, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0082, std=0.0595, worst_day=-0.1465\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7892", "answer_numeric": 0.7892, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1267 (i.e., a 12.67% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1267 = 0.7892, capped at 1.0.\nMaximum position size = 0.7892 (78.9% of portfolio).", "metadata": {"var_99": -0.126708, "expected_loss": 0.126708, "max_drawdown_threshold": 0.1, "position_size": 0.7892, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20221116_0432", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2022-11-16", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1259, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0018, std=0.0397, worst_day=-0.1400\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-15] \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": "0.7942", "answer_numeric": 0.7942, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1259 (i.e., a 12.59% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1259 = 0.7942, capped at 1.0.\nMaximum position size = 0.7942 (79.4% of portfolio).", "metadata": {"var_99": -0.125919, "expected_loss": 0.125919, "max_drawdown_threshold": 0.1, "position_size": 0.7942, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20210217_0435", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2021-02-17", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1547, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0175, std=0.0800, worst_day=-0.1567\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6463", "answer_numeric": 0.6463, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1547 (i.e., a 15.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1547 = 0.6463, capped at 1.0.\nMaximum position size = 0.6463 (64.6% of portfolio).", "metadata": {"var_99": -0.154738, "expected_loss": 0.154738, "max_drawdown_threshold": 0.1, "position_size": 0.6463, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200128_0438", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2020-01-28", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0773, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0011, std=0.0344, worst_day=-0.1135\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0773 (i.e., a 7.73% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0773 = 1.2945, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.07725, "expected_loss": 0.07725, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220809_0441", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2022-08-09", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0388, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0025, std=0.0219, worst_day=-0.0388\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-08-08] [\"US STOCKS-Wall St set for higher open after selloff on jobs data By Bansari Mayur Kamdar and Aniruddha Ghosh Aug 8 (Reuters) - U.S. stock indexes were set to open higher on Monday after last week's blockbuster jobs data soothed some fears about an economic slowdown, but investors remained cautious as it also added to expectations of a hawkish Federal Reserve. The focus this week will be on consumer prices data on Wednesday. The S&P 500 has bounced back 13% from its mid-June lows, but investors fear that signs of persistent inflation this week could further bolster the Fed's case for aggressive monetary policy tightening. \\\"While it's clear the Fed needs to continue tightening policy, there are still about six weeks until the next meeting and we remind investors that economic data can change very quickly,\\\" said Robert Schein, chief investment officer, Blanke Schein Wealth Management. \\\"The CPI data will help to confirm if the Fed's tightening efforts have been successful in starting to tame inflation or if continued Fed tightening is needed.\\\" U.S. rate futures have priced in a 68.5% chance of a 75-basis-point hike at the Fed's September meeting, up from about 41% before payrolls data on Friday beat market expectations. IRPR Banks that tend to benefit from a higher interest rate environment extended their gains in trading before the bell. Megacap growth and technology stocks edged higher, with Tesla TSLA.O up 2.3%. The U.S. electric-car maker signed contracts worth about $5 billion to buy materials for their batteries from nickel processing companies in Indonesia, according to a CNBC report. Other high-growth stocks such as Apple Inc AAPL.O and Amazon.com Inc AMZN.O gained as U.S. Treasury yields pulled back from sharp highs in the previous session. The benchmark 10-year yield declined 1.6% in early trading. Meanwhile, the U.S. Senate on Sunday passed a sweeping $430 billion bill intended to fight climate change, lower drug prices and raise some corporate taxes. \\\"All in all, it's a net positive. Biotech and pharma should rebound after some uncertainty because it (the bill) is less onerous than initially anticipated as it relates to negotiating drug prices,\\\" said Thomas Hayes, managing member, Great Hill Capital LLC, New York. Hayes added that a lot of companies might accelerate their stock buybacks as they now have incentive to aggressively initiate buybacks before the 1% tax kicks in, helping the equity markets overall. Nvidia Corp NVDA.O fell 7% on saying it expects second-quarter revenue of about $6.70 billion, down 19% from the prior quarter, largely hurt by weakness in its gaming business. Signify Health Inc SGFY.N jumped 15.1% on a media report that CVS Health Corp CVS.N was looking to buy the health technology company. Global Blood Therapeutics climbed 4.6% on Pfizer's PFE.N $5.4 billion deal for the blood disorder drugmaker. At 08:50 a.m. ET, Dow e-minis 1YMcv1 were up 164 points, or 0.50%, S&P 500 e-minis EScv1 were up 25.75 points, \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 = 0.0388 (i.e., a 3.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0388 = 2.5763, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.038816, "expected_loss": 0.038816, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20151221_0444", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2015-12-21", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0168, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0006, std=0.0083, worst_day=-0.0203\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-12-18] Adobe (ADBE) Attains a New 52-Week High on Solid Earnings Shares of Adobe Systems Inc.ADBE attained a new 52-week high of $96.42 on Dec 17, eventually closing at $94.20. The company returned 26.5% in the past one year and approximately 29.6% year-to-date. Average volume of shares traded over the last three months was roughly 3,453K. What is Driving Adobe Systems? One of the largest software companies in the world, Adobe Systems' massive customer base provides it with a distinct competitive edge. We believe that the company is being driven by continuous innovation in the Creative Cloud and Marketing Cloud businesses. The price appreciation may be attributed to Adobe's strong fundamentals, solid adoption of creative cloud and better-than-expected fourth-quarter fiscal 2015 results reported on Dec 10. Since then, the stock has gained 5.9%. In the fourth quarter, Adobe reported earnings of 47 cents per share, surpassing the Zacks Consensus Estimate of 45 cents. The growth was backed by strong adoption of creative cloud that led to a record sequential Creative Cloud ARR (Annualized Recurring Revenue) growth and strong revenues in the Creative product family. Adobe's revenues jumped 9.4% sequentially and 23.2% year over year to $1.31 billion. Revenues were at the higher end of the guidance range and in line with our expectations. We believe that the company will continue to be driven by innovation in its Creative suite businesses. In addition, the consistent adoption of the Adobe marketing cloud could serve as a potential catalyst, going forward. We expect significant synergies over the long term from the integration of Fotolia. Moreover, the solid adoption of Document Cloud, a new subscription package that enables users to sign documents on the cloud, will boost revenues. Additionally, Adobe Systems delivered an average positive earnings surprise of nearly 6.39% over the trailing four quarters. The company's solid market position, compelling product lines (including CS cloud initiative and digital media products), strong revenue growth, continued innovation and strong long-term growth potential position it favorably. Adobe Systems currently has a Zacks Rank #3 (Hold). Stocks to Consider Some well-ranked stocks in the same space are Citrix Systems, Inc. CTXS , Datawatch Corporation DWCH and Fleetmatics Group PLC FLTX , all sporting a Zacks Rank #1 (Strong Buy). 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 >> 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 CITRIX SYS INC (CTXS): Free Stock Analysis Report ADOBE SYSTEMS (ADBE): Free Stock Analysis Report FLEETMATICS GRP (FLTX): Free Stock Analysis Report DATAWATCH CORP (DWCH): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Research The views and opin\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 = 0.0168 (i.e., a 1.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0168 = 5.9466, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016816, "expected_loss": 0.016816, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20191112_0449", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2019-11-12", "context_summary": "HYG: 60-day history, VaR(99%)=-0.0051, max drawdown threshold=10%.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0003, std=0.0022, worst_day=-0.0059\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 = 0.0051 (i.e., a 0.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0051 = 19.5016, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.005128, "expected_loss": 0.005128, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20191231_0453", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2019-12-31", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0123, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0022, std=0.0064, worst_day=-0.0151\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-30] Is North America Contribution To Amazon's Total Revenue 60%, 70%, Or 80%? Amazon\u2018s (NASDAQ:AMZN) North America business, consisting primarily of retail sales in the region, is expected to contribute $177.6 billion to Amazon\u2019s 2019 revenues, making up 61.2% of Amazon\u2019s $290.4 billion in expected revenues for 2019. The North America segment contribution is more than twice that from International business. Amazon is expected to add $154 billion in revenue between 2016 to 2019, out of which the North America segment is expected to provide $97 billion, that is 63% of the total expected increase. This North America revenue growth has been key to Amazon\u2019s 160% price appreciation since 2016, further helped by increasing margins. We discuss Amazon\u2019s valuation analysis in full, separately. Below we discuss Amazon\u2019s business model, followed by sections that review past performance and 2019 expectations for Amazon\u2019s revenue drivers and competitive comparisons of its Retail revenue with Walmart and Target. You can look at our interactive dashboard analysis ~ Amazon\u2019s Revenues: How Does Amazon Make Money? ~ for more details. Amazon Business Model: What does Amazon offer: Amazon.com, Inc. was incorporated in 1994 in the state of Washington. The company is one of the largest online retailers, and also dabbles in a broad range of businesses including its core e-commerce operations, cloud services, digital advertising, groceries, and prescription drugs. They also sell products such as the Alexa personal assistant and ecosystem, and also gives access to content through subscription on its Amazon Prime platform. Has 3 major Operating Segments: North America: The North America segment primarily consists of amounts earned from retail sales of consumer products (including from sellers) and subscriptions through North America-focused online and physical stores. This segment includes export sales from these online stores. International: The International segment primarily consists of amounts earned from retail sales of consumer products (including from sellers) and subscriptions through internationally-focused online stores. This segment includes export sales from these internationally-focused online stores (including export sales from these online stores to customers in the U.S., Mexico, and Canada), but excludes export sales from the North America-focused online stores. AWS: The AWS segment consists of amounts earned from global sales of computing, storage, database, and other service offerings for start-ups, enterprises, government agencies, and academic institutions. What Are The Alternatives? Major competitors are Walmart, eBay, Alibaba, Google, Facebook, and Apple. What Is The Basis of Competition? The principal competitive factors in the retail businesses include selection, price, and convenience, including fast and reliable fulfillment. Additional competitive factors for the seller and enterprise services include the quality, speed, and reliability of their servi\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 = 0.0123 (i.e., a 1.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0123 = 8.1560, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012261, "expected_loss": 0.012261, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190702_0456", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-07-02", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1059, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0112, std=0.0501, worst_day=-0.1262\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9447", "answer_numeric": 0.9447, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1059 (i.e., a 10.59% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1059 = 0.9447, capped at 1.0.\nMaximum position size = 0.9447 (94.5% of portfolio).", "metadata": {"var_99": -0.105854, "expected_loss": 0.105854, "max_drawdown_threshold": 0.1, "position_size": 0.9447, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200521_0459", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2020-05-21", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0309, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0006, std=0.0210, worst_day=-0.0309\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-05-20] [\"Earnings Scheduled For May 20, 2020\", \"Analog Devices Q2 Adj. EPS $1.080 Beats $1.040 Estimate, Sales $1.317B Miss $1.330B Estimate\", \"Recap: Analog Devices Q2 Earnings\", \"Analog Devices shares are trading higher after the company reported better-than-expected Q2 EPS results.\", \"Analog Devices shares are trading higher after the company reported better-than-expected Q2 EPS results.\", \"Recap: Analog Devices Q2 Earnings\", \"Analog Devices Q2 Adj. EPS $1.080 Beats $1.040 Estimate, Sales $1.317B Miss $1.330B Estimate\", \"Earnings Scheduled For May 20, 2020\", \"BUZZ-U.S. STOCKS ON THE MOVE-Atossa, Kornit Digital, Xcel Brands Eikon search string for individual stock moves: STXBZ The Day Ahead newsletter: http://tmsnrt.rs/2ggOmBi The Morning News Call newsletter: http://tmsnrt.rs/2fwPLTh Wall Street's main indexes surged and the Nasdaq hit a three-month high on Wednesday, as investors clung to hopes of a recovery from a coronavirus-fueled slump amid signs of more stimulus for ailing sectors..N At 11:00 ET, the Dow Jones Industrial Average .DJI was up 1.56% at 24,585.21. The S&P 500 .SPX was up 1.80% at 2,975.58 and the Nasdaq Composite .IXIC was up 1.93% at 9,362.654. The top three S&P 500 .PG.INX percentage gainers: ** TechnipFMC PLC , up 8.5% ** Analog Devices Inc , up 7.9% ** Zions Bancorporation NA , up 7.5% The top three S&P 500 .PL.INX percentage losers: ** L Brands Inc , down 5.2% ** Gap Inc , down 3.5% ** Royal Caribbean Cruises Ltd , down 3.2% The top three NYSE .PG.N percentage gainers: ** AeroCentury Corp , up 76.7% ** Cheetah Mobile Inc , up 33.3% ** Carriage Services Inc , up 22.5% The top three NYSE .PL.N percentage losers: ** Pyxus International Inc , down 18.5% ** Aurora Cannabis Inc , down 13.8% ** Direxion Daily Semiconductor Bear 3X Shares , down 10.9 % The top three Nasdaq .PG.O percentage gainers: ** Aurora Cannabis Inc , up 33.7% ** Altimmune Inc , up 31.4% ** Surface Oncology Inc , up 29.7% The top three Nasdaq .PL.O percentage losers: ** Luckin Coffe Inc , down 36.2% ** Cryoprt Inc Warrnats , down 17% ** Shiftpixy Inc , down 17.2% ** Enzo Biochem Inc ENZ.N: up 4.3% BUZZ-Rises on launch of COVID-19 antibody test ** ForeScout Technologies Inc FSCT.O: down 8.5% BUZZ-Slumps after legal action against Advent International ** Kornit Digital Ltd KRNT.O: up 27.7% BUZZ-Set for best day as brokerages lift PT on positive H2 outlook ** Cryoport Inc CYRX.O: down 14.5% BUZZ-Slides on planned $100 mln convertible debt offering ** Atossa Therapeutics Inc ATOS.O: up 33.7% BUZZ-Surges after drug blocks COVID-19 infection in in-vitro testing ** Arconic Corp ARNC.N: up 14.0% BUZZ-CS starts coverage with 'outperform' rating ** Walmart Inc WMT.N: up 0.5% BUZZ-Street View: Walmart a clear retail winner in most challenging of times ** Pyxus International Inc PYX.N: down 18.5% BUZZ-Plunges on report of co seeking financing for possible bankruptcy ** Lowe's Companies Inc LOW.N: up 0.6% BUZZ-Rises as first-quarter results beat ** Baxter International Inc BA\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 = 0.0309 (i.e., a 3.09% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0309 = 3.2314, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030947, "expected_loss": 0.030947, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160729_0461", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-07-29", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0282, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0015, std=0.0097, worst_day=-0.0399\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-07-28] [\"3M Stock Seen Edging Up to $186 Second-quarter margins expanded by about 50 basis points year-over-year, and should accelerate through the second half.\", \"An Aerospace Parts Maker That Can Fly 35% Higher Shares of airplane power systems supplier Astronics have lost altitude but could rise significantly.\", \"Cirrus Logic Surges 13%: Ride That iPhone Headset Plug! Shares of chip maker Cirrus Logic (CRUS), a prominent supplier to Apple (AAPL), are up $5.24, or 13%, at $47.01, after last night easily topping fiscal Q1 expectations and forecasting this quarter\\u2019s revenue well ahead of consensus as well.And, indeed, a big part of last night\\u2019s conference call with analysts was the company indirectly confirming a \\u201cdigital\\u201d jack for headsets for the next iPhone, presumably an \\\"iPhone 7,\\u201d which many think will appear in September. All that headphone capability now in a USB or \\u201clightning\\u201d port, believe analysts, translates directly into higher revenue for Cirrus for each phone sold.The company\\u2019s CEO, Jason Rhode, was asked by Needham & Co.\\u2019s Rajvindra Gill what he sees as the general increase in using \\u201cdigital,\\u201d or \\u201cUSB\\u201d ports for headphones. Said Rhode:Well, like I referred to earlier, we are excited to see there's already models on the market that have switched over to USBC completely, and either ship with -- either ship with or have available accessory USBC headsets or adapters, one or the other, or both. The interesting thing is that as the core chipsets stand today, that's quite a painful thing to do, just the way the USBC stack is handled and routing of audio and uses of voice interface is kind of clumsy in the handsets themselves. So, we see that getting sorted out over the next 6 to 12 months in a way that makes it significantly easier for handset manufacturers to go that route, and so we would anticipate that would gain a lot of momentum over that timeframe. And, like I say, I think we're extremely well-positioned to capitalize on that.\", \"MasterCard profit, revenue beat expectations MasterCard Inc. said profit and revenue grew in the second quarter as transactions increased at the credit card company. Results topped expectations, and shares climbed 1.8% premarket. Like fellow card company Visa Inc., MasterCard charges fees to financial institutions for transactions that travel over their networks.\", \"Smartphone market stagnant for second straight quarter The global smartphone market struggled to grow in the second quarter. Vendors shipped 343.3 million smartphones, a 0.3% increase from 342.4 million in the year-earlier period, according to IDC. That was the second straight quarter of stagnant volumes. Samsung Electronics maintained its lead in the market, nabbing a 22.4% global share, versus 21.3% last year. Apple Inc.'s share declined slightly, to 11.8% from 13.9%, while smaller Asian vendors such as Huawei, OPPO and Vivo continued to steal a larger part of the pie. Anthony Scarsel\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 = 0.0282 (i.e., a 2.82% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0282 = 3.5470, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028193, "expected_loss": 0.028193, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190111_0464", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2019-01-11", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0375, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0008, std=0.0136, worst_day=-0.0375\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-10] [\"Apple's stock slips 0.7% premarket, after rising 3.6% the past 2 sessions\", \"The stock market is too damaged for a sustained rally, strategist warns Morgan Stanley\\u2019s Wilson: Too much resistance in stock market for a \\u2018straight up\\u2019 recovery The stock market is in the midst of its longest winning streak in months but at least one Wall Street strategist is not convinced that investors are out of the woods yet.\", \"Q&A with Cody Willard: Apple, Disney, Adobe and small-cap stocks Stocks are vulnerable to another leg down Stocks are vulnerable to another leg down.\", \"Many retail investors panicked and sold during last month\\u2019s market meltdown (again) Yes, Main Street missed the latest rally, fund industry analyst says Yes, Main Street missed the latest rally, fund industry analyst says.\", \"Cisco Sees Its Chance as Internet Traffic Builds Cisco Systems used the Consumer Electronics Show as a place to tout its high-speed networks and security tools, products that will be more critical as the volume of data on the internet grows, and the flow speeds up.\", \"Elon Musk Goes to China at a Vital Time for Tesla and for the U.S. The backdrop of Musk\\u2019s visit was hard not to notice: The U.S. and China this week wrapped up the latest round of talks that investors hope will stabilize trade relations.\", \"The sharpest investors use this simple tool to pick stocks Valuing a public company like a private business gives a more realistic picture of its potential Valuing a public company like a private business gives a more realistic picture of its potential, writes Vitaliy Katsenelson.\", \"Roaring U.S. jobs market, waning inflation give Fed room to pause on interest rates Consumer price index likely softened again at end of 2018 A gargantuan surge in new jobs in December, a recent lull in inflation and a more cautious Federal Reserve have dispelled fears that the U.S. faces a looming recession.\", \"High-end cars and other luxury goods join Apple in feeling effect of China\\u2019s slowdown Jaguar Land Rover cites China demand as it cuts 4,500 jobs in the U.K. Automobile makers join luxury-goods companies in seeing demand dented as China\\u2019s economy slows and Chinese consumers\\u2019 mood takes a turn for the worse.\", \"Lenovo overtakes HP in PC sales as market contracts Overall worldwide PC sales declined for both the fourth quarter and year in 2018, while Lenovo Group Ltd. and Dell Technologies Inc.'s share of the market grew, according to research firm Gartner on Thursday. Global PC sales fell 4.3% to 68.6 million units in the fourth quarter, and 1.3% to 259.4 million in 2018, Gartner said. \\\"Just when demand in the PC market started seeing positive results, a shortage of CPUs (central processing units) created supply chain issues,\\\" said Mikako Kitagawa, senior principal analyst at Gartner, in a statement. \\\"After two quarters of growth in 2Q18 and 3Q18, PC shipments declined in the fourth quarter.\\\" Market share for Lenovo and Dell grew, however. \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 = 0.0375 (i.e., a 3.75% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0375 = 2.6646, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037529, "expected_loss": 0.037529, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210203_0467", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2021-02-03", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0284, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0019, std=0.0138, worst_day=-0.0411\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 = 0.0284 (i.e., a 2.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0284 = 3.5263, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028359, "expected_loss": 0.028359, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210614_0470", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2021-06-14", "context_summary": "EMB: 60-day history, VaR(99%)=-0.0069, max drawdown threshold=10%.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0009, std=0.0038, worst_day=-0.0091\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 = 0.0069 (i.e., a 0.69% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0069 = 14.4529, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.006919, "expected_loss": 0.006919, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210514_0473", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2021-05-14", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1510, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0062, std=0.0799, worst_day=-0.1550\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6623", "answer_numeric": 0.6623, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1510 (i.e., a 15.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1510 = 0.6623, capped at 1.0.\nMaximum position size = 0.6623 (66.2% of portfolio).", "metadata": {"var_99": -0.150986, "expected_loss": 0.150986, "max_drawdown_threshold": 0.1, "position_size": 0.6623, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210216_0476", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2021-02-16", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1547, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0179, std=0.0799, worst_day=-0.1567\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6463", "answer_numeric": 0.6463, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1547 (i.e., a 15.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1547 = 0.6463, capped at 1.0.\nMaximum position size = 0.6463 (64.6% of portfolio).", "metadata": {"var_99": -0.154738, "expected_loss": 0.154738, "max_drawdown_threshold": 0.1, "position_size": 0.6463, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20181123_0481", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2018-11-23", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1583, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0099, std=0.0438, worst_day=-0.1593\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6319", "answer_numeric": 0.6319, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1583 (i.e., a 15.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1583 = 0.6319, capped at 1.0.\nMaximum position size = 0.6319 (63.2% of portfolio).", "metadata": {"var_99": -0.158264, "expected_loss": 0.158264, "max_drawdown_threshold": 0.1, "position_size": 0.6319, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220425_0484", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2022-04-25", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0360, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0001, std=0.0204, worst_day=-0.0388\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-22] [\"Smart Speaker Market: 20.87% Y-O-Y Growth Rate in 2021 | By End-user (residential users and commercial users) and Geography | Global Forecast to 2025 The Smart Speaker Market value is set to grow by USD 20.72 billion, progressing at a CAGR of 25.98% from 2020 to 2025, as per the latest report by Technavio.\", \"AB Klaipedos nafta audited Annual information for the year 2021 AB Klaip\\u0117dos nafta, legal code 110648893, registered at Buri\\u0173 str. 19, Klaip\\u0117da (hereinafter \\u2013 the Company), Annual General Meeting of Shareholders held on 22 April 2022 in between the other questions approved the audited consolidated financial statements for the financial year ended 31 December 2021. The Group of AB Klaip\\u0117dos nafta (hereinafter \\u2013 the Group) revenue for the year 2021 comprises EUR 61.8 million, 22.8% less compared to the year 2020 (EUR 80.1 million). Company\\u2018s revenue comprises\", \"Engadget Podcast: We love the Playdate and BTS dance lessons on Apple Fitness+ This week's gadget news has been surprisingly pleasant, with the Playdate and a Pok\\u00e9mon-themed foldable phone making headlines.\", \"Amazon's Eero Pro mesh routers are up to 25 percent off Amazon is offering steep discounts for Eero Pro mesh routers, including WiFi 6 models.\", \"iRobot's Roomba 694 drops to $180, plus the rest of the week's best tech deals This week's best tech deals include the Roomba 694 for $180, Apple's latest AirPods for $150 and the 10.2-inch iPad for $309.\", \"Coinbase CEO says Apple's crypto rules highlight 'potential antitrust issues' Brian Armstrong, the chief executive of Coinbase, believes Apple's App Store rules have hampered the company's product roadmap, accusing the iPhone-maker of banning features from their app and generally not being friendly with the cryptocurrency industry. \\\"Apple so far has not really played nice with crypto, they've actually banned a bunch of features that we would like to have in the app, but they just won't allow it -- so there's potential antitrust issues there,\\\" Armstrong said. In the episode of Superteam Podcast, which aired this week, the co-founder of the publicly listed firm discussed Apple's influence and floated the idea that smartphones may soon need to build crypto-specific hardware features.\", \"Motorola\\u2019s endless rehashes will only make it less relevant Despite being having the third largest market share for smartphones in the US, Motorola's recent pattern of releasing too many low-quality handsets is becoming an issue.\", \"China Matters explores the promise of smart cities in Guiyang Why smart cities? From all perspectives, it ticks all the boxes: innovation, technology and new economy. On a day-to-day basis, it makes our urban environments more liveable, it saves energy, keeps traffic flowing and keeps us safe.\", \"'Borderlands 3' will finally add PlayStation cross-play support this spring 'Borderlands 3' is finally adding PlayStation cross-play years after Sony shot it down.\", \"Report reveals B\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 = 0.0360 (i.e., a 3.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0360 = 2.7802, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035969, "expected_loss": 0.035969, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180403_0491", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2018-04-03", "context_summary": "IGOV: 60-day history, VaR(99%)=-0.0084, max drawdown threshold=10%.", "question": "Asset: IGOV\nDaily returns (past 60 days): mean=0.0008, std=0.0041, worst_day=-0.0096\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 = 0.0084 (i.e., a 0.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0084 = 11.8837, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008415, "expected_loss": 0.008415, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200206_0496", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-02-06", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1741, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0728, worst_day=-0.2144\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5745", "answer_numeric": 0.5745, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1741 (i.e., a 17.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1741 = 0.5745, capped at 1.0.\nMaximum position size = 0.5745 (57.5% of portfolio).", "metadata": {"var_99": -0.174076, "expected_loss": 0.174076, "max_drawdown_threshold": 0.1, "position_size": 0.5745, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220810_0501", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2022-08-10", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.0969, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0063, std=0.0583, worst_day=-0.0986\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-08-09] [\"Down 47% in a Year, Time to Buy This Growth Stock? With a market cap of $8.3 billion, Cognex Corporation (NASDAQ: CGNX) is not a small-cap company. However, it's still a growth company trying to build out the adoption of technology with explosive growth potential. As the leader in machine vision, Cognex's strategic aim is to grow into a served market (estimated as being worth $4.2 billion in 2018) that management sees as growing at a 12% annual rate. The good news from 2022 is Cognex is achieving many of its strategic aims; the bad news is almost everything seems to be working against the company right now. Here's the lowdown. What a growth company needs If you are going to make up an informal list of objectives for a growth company, it will include the following: Win over some highly prominent and visible customers to demonstrate your technology's efficacy, expand revenue, win follow-up business, and sell to lower-tier players as they follow their industry leaders in adopting machine vision. Ensure you satisfy high-profile customers by investing in a high level of service. Continue establishing your technology in new growth markets. As alluded to earlier, Cognex is doing all three things. The company's three major machine vision markets are automotive, consumer electronics, and logistics/e-commerce. The biggest names in two of those three industries are Apple (named as a significant customer in a previous Cognex SEC filing) and Amazon.com (NASDAQ: AMZN). The latter was not named on Cognex's recentearnings call Still, Cognex's last 10-K filing referred to a large customer in the logistics industry that represented approximately 17% of their total revenue. When an analyst refers to \\\"the world's largest e-commerce customer,\\\" it's a reasonable bet that it's Amazon. One clear thing is that Cognex has won some very high-profile customers in the last five years, so you can tick off the first box on the checklist. Servicing customers and establishing new markets The other two boxes can be ticked off as well. Three sources indicate that Cognex is very careful in servicing its customers (an excellent quality in a growing company). First, back in 2014, when Cognex started working on Apple orders (its machine vision solutions help smartphone manufacturers fit screens), management significantly ramped its operating expenses to support the orders. Second, it was the same in 2021, with Cognex incurring an extra cost in providing a \\\"higher level of support on a large deployment by a customer in logistics.\\\" Third, back on the fourth-quarterearnings callin February, CEO Robert Willett disclosed Cognex had \\\"been prioritizing delivery during this time of global chip shortages that added incremental costs in 2021, due to the significant premiums we've paid to procure components through brokers, and for expedited freight.\\\" As for establishing new markets, the logistics market is a relatively new one for Cognex that's grown at a compound annual growth rate of \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 = 0.0969 (i.e., a 9.69% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0969 = 1.0319, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.096908, "expected_loss": 0.096908, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190521_0504", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2019-05-21", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0307, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0015, std=0.0127, worst_day=-0.0327\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-05-20] Credit Suisse Absolutely Is Right to Double Down on Pfizer Stock After upgrading Pfizer (NYSE:) to \u201cOutperform\u201d in January and raising its price target on Pfizer stock to $48 in May, one would think there\u2019s nothing else Credit Suisse could so to bolster its bullish case, but there is. Source: Following a meeting with the pharmaceutical giant\u2019s top brass just a few days ago, on Thursday, \u201ctop pick.\u201d It was apparently one heck of a meeting. The specifics prompting the accolade weren\u2019t made crystal clear, though Credit Suisse did note that the company\u2019s prospects for new products was compelling. Translation: Whatever stoked Credit Suisse\u2019s fires is likely to be in the company\u2019s late-stage pipeline, which is admittedly more exciting than it has been in a long while. A Brief Look at Pfizer It\u2019s not a story that needs a great deal of retelling. It was an unstoppable powerhouse when it had full patent protection of its erectile dysfunction drug Viagra and faced little competition. But, seeing the writing on the wall, the drugmaker allowed Teva Pharmaceutical Industries (NYSE:) to begin selling a generic version of the drug in 2017. In the meantime, consumer interest in ED drugs has broadly waned. Pfizer is about to lose ground with blockbuster neuropathic pain drug Lyrica too, which lost patent protection last year, threatening to once generic alternatives become available. It\u2019s the same story that plays out over and over within the pharmaceutical industry; these organizations must constantly replenish their portfolios with patent-protected drugs, or risk losing ground. It\u2019s something Pfizer hasn\u2019t done especially well in recent years. Although Pfizer stock has made reliable if choppy progress since turning around with all other stocks in 2009, revenue growth hasn\u2019t been overwhelming. The was not remarkable better than the $52.7 billion figure from a year earlier. \u201cPfizer has been working through a dark period with extensive patent expirations,\u201d said in late January. \u201cThat period is now nearing an end.\u201d Solid Pipeline What Pfizer told Credit Suisse at the meeting remains veiled, though when Divan upgraded Pfizer stock early this year he explicitly noted opportunities for several cancer and autoimmune disease drugs along with vaccinations. Two of the drugs Divan had in mind are (though they\u2019re actually different doses of the same molecule), which combats the buildup for amyloid in the heart. Alnylam Pharmaceuticals (NASDAQ:) and Ionis Pharmaceuticals (NASDAQ:) already make similar rival drugs, but their versions are considerably more expensive. Divan foresees peak sales of $2 billion for Vyndaqel, but is willing to entertain a number \u201csignificantly larger than that if Pfizer is able to commercialize it successfully.\u201d Pfizer has also partnered with Eli Lilly (NYSE:) on the development of a non-opioid arthritis treatment called tanezumab, another one of the 15 game-changing drugs Pfizer believes could be brought to the market within the next five years. So\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 = 0.0307 (i.e., a 3.07% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0307 = 3.2527, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030743, "expected_loss": 0.030743, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200311_0507", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2020-03-11", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0388, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0010, std=0.0148, worst_day=-0.0388\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-03-10] [\"123 Biggest Movers From Yesterday\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Morning Market Stats In 5 Minutes\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Morning Market Stats In 5 Minutes\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"123 Biggest Movers From Yesterday\", \"Peloton Shares Tick To Session Low As Hearing Report Apple Working On 'Guided Workout' Fitness App\", \"Morning Market Stats In 5 Minutes\", \"The Main Challenges Faced By The Upcoming EV Era\", \"Jedi Wars Between Amazon And Microsoft Are Still Very Much On\", \"Airlines Continue Suffering As Delta, American Announce Schedule Cuts, But Crude Bounces\", \"Shares of several technology companies are trading higher as markets look to rebound from Monday's selloff. The technology sector has been highly impacted by the coronavirus due to its China exposure and sensitivity to economic conditions.\", \"UBS Maintains Buy on Apple, Lowers Price Target to $335\", \"123 Biggest Movers From Yesterday\", \"Has the coronavirus selloff created a stock-buying opportunity, or is it too early? Here\\u2019s what analysts and strategists are advising Is it safe to go back into the water after stocks have been rocked by the COVID-19 outbreak?\", \"These 3 EVs are the lowest cost to own over 5 years The 5-Year Cost to Own equation includes insurance, fuel economy, interest rates, and depreciation\\u2014the Nissan Leaf comes out on top The Nissan Leaf takes home KBB\\u2019s Best EV 5-Year Cost to Own Award for the third year in a row.\", \"After markets plunge on fears of OPEC \\u2018price war\\u2019 and coronavirus \\u2014 5 questions to ask your financial adviser right now Advisers say this is a \\u2018great litmus test\\u2019 to evaluate your risk tolerance, but they say retail investors should proceed cautiously Advisers say this is a \\u2018great litmus test\\u2019 to evaluate your risk tolerance, but they say retail investors should proceed ca\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 = 0.0388 (i.e., a 3.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0388 = 2.5763, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.038816, "expected_loss": 0.038816, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190306_0510", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["CPER"], "decision_date": "2019-03-06", "context_summary": "CPER: 60-day history, VaR(99%)=-0.0245, max drawdown threshold=10%.", "question": "Asset: CPER\nDaily returns (past 60 days): mean=0.0014, std=0.0114, worst_day=-0.0292\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CPER, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0245 (i.e., a 2.45% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0245 = 4.0845, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024483, "expected_loss": 0.024483, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190225_0513", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2019-02-25", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0358, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0008, std=0.0161, worst_day=-0.0391\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-22] [\"Pinnacle West's (PNW) Q4 Earnings Beat Estimates, Up Y/Y Pinnacle West Capital CorporationPNW delivered adjusted earnings per share of 23 cents in the fourth quarter of 2018, beating the Zacks Consensus Estimate of 17 cents by 35.3%. In the year-ago quarter, the company had reported adjusted earnings of 19 cents. Impressive operational performance and favorable Arizona economy supported the quarterly numbers. In 2018, Pinnacle West Capital generated earnings of $4.54 per share, up from $4.35 in 2017. Total Revenues In the quarter under review, total revenues of $756.4 million fell 0.4% on a year-over-year basis. In 2018, the company delivered revenues of $3.69 billion, up from $3.57 billion in 2017. Pinnacle West Capital Corporation Price, Consensus and EPS Surprise Pinnacle West Capital Corporation Price, Consensus and EPS Surprise | Pinnacle West Capital Corporation Quote Operational Highlights In fourth-quarter 2018, total Operating Expenses were $689.5 million, up 2.3% from the year-ago quarter's tally. Operating income declined 21.8% year over year to $66.9 million. Interest expenses rose to $55.9 million from $50.6 million in the year-ago quarter. Courtesy of the improving Arizona economy, customer volumes improved 1.7% year over year in 2018, resulting in an increase of 16 cents in the company's earnings compared with 2017. Guidance Management projects 2019 EPS in the range of $4.75-$4.95, whose mid-point of $4.85 is higher than the current Zacks Consensus Estimate of $4.84. Zacks Rank Pinnacle West currently carries a Zacks Rank #2 (Buy). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here . Other Utility Releases NextEra Energy, Inc. NEE delivered fourth-quarter 2018 adjusted earnings of $1.49 per share, which lagged the Zacks Consensus Estimate of $1.51 by 1.3%. American Electric Power Co., Inc. AEP generated fourth-quarter 2018 operating EPS of 72 cents, in line with the Zacks Consensus Estimate. Xcel Energy Inc. XEL posted fourth-quarter 2018 operating earnings of 42 cents per share, in line with the Zacks Consensus Estimate. Wall Street's Next Amazon Zacks EVP Kevin Matras believes this familiar stock has only just begun its climb to become one of the greatest investments of all time. It's a once-in-a-generation opportunity to invest in pure genius. Click for details >> 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 NextEra Energy, Inc. (NEE): Free Stock Analysis Report Pinnacle West Capital Corporation (PNW): Free Stock Analysis Report American Electric Power Company, Inc. (AEP): Free Stock Analysis Report Xcel Energy Inc. (XEL): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Research The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein \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 = 0.0358 (i.e., a 3.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0358 = 2.7899, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035844, "expected_loss": 0.035844, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220706_0516", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2022-07-06", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0427, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=-0.0028, std=0.0232, worst_day=-0.0427\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-05] [\"EU lawmakers pass landmark tech rules, but enforcement a worry By Foo Yun Chee BRUSSELS, July 5 (Reuters) - EU lawmakers gave the thumbs up on Tuesday to landmark rules to rein in tech giants such as Alphabet GOOGL.O unit Google, Amazon AMZN.O, Apple AAPL.O, Facebook FB.O and Microsoft MSFT.O, but enforcement could be hampered by regulators' limited resources. In addition to the rules known as the Digital Markets Act (DMA), lawmakers also approved the Digital Services Act (DSA), which requires online platforms to do more to police the internet for illegal content. Companies face fines of up to 10% of annual global turnover for DMA violations and 6% for DSA breaches. Lawmakers and EU states had reached a political deal on both rule books earlier this year, leaving some details to be ironed out. The European Commission has set up a taskforce, with about 80 officials expected to join up, which critics say is inadequate. Last month it put out a 12 million euro ($12.3 million) tender for experts to help in investigations and compliance enforcement over a four-year period. EU industry chief Thierry Breton sought to address enforcement concerns, saying various teams would focus on different issues such as risk assessments, interoperability of messenger services and data access during implementation of the rules. Regulators will also set up a European Centre for Algorithmic Transparency to attract data science and algorithm scientists to help with enforcement. \\\"We have started to gear the internal organisation to this new role, including by shifting existing resources, and we also expect to ramp up recruitment next year and in 2024 to staff the dedicated DG CONNECT team with over 100 full time staff,\\\" Breton said in a blogpost. DEEP POCKETS Lawmaker Andreas Schwab, who steered the issue through the European Parliament, has called for a bigger taskforce to counter Big Tech's deep pockets and array of lawyers. European Consumer Organisation (BEUC) echoed the same worries. \\\"We raised the alarm last week with other civil society groups that if the Commission does not hire the experts it needs to monitor Big Tech's practices in the market, the legislation could be hamstrung by ineffective enforcement,\\\" BEUC Deputy Director General Ursula Pachl said in a statement. The DMA is set to force changes in companies' businesses, requiring them to make their messaging services interoperable and provide business users access to their data. Business users would be able to promote competing products and services on a platform and reach deals with customers off the platforms. Companies will not be allow to favour their own services over rivals' or prevent users from removing pre-installed software or apps, two rules that will hit Google and Apple hard. The DSA bans targeted advertising aimed at children or based on sensitive data such as religion, gender, race and political opinions. Dark patterns, which are tactics that mislead people into giving personal data to c\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 = 0.0427 (i.e., a 4.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0427 = 2.3410, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.042717, "expected_loss": 0.042717, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190207_0519", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2019-02-07", "context_summary": "SCHH: 60-day history, VaR(99%)=-0.0340, max drawdown threshold=10%.", "question": "Asset: SCHH\nDaily returns (past 60 days): mean=0.0010, std=0.0120, 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 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 = 0.0340 (i.e., a 3.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0340 = 2.9369, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034049, "expected_loss": 0.034049, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210824_0522", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-08-24", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1015, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0070, std=0.0651, worst_day=-0.1305\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9852", "answer_numeric": 0.9852, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1015 (i.e., a 10.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1015 = 0.9852, capped at 1.0.\nMaximum position size = 0.9852 (98.5% of portfolio).", "metadata": {"var_99": -0.101507, "expected_loss": 0.101507, "max_drawdown_threshold": 0.1, "position_size": 0.9852, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160510_0527", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2016-05-10", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0146, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0020, std=0.0090, worst_day=-0.0149\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-09] Drug Stocks Reporting on May 10: XON, ARIA, CPRX & More How is the Earnings Picture Evolving now that a large part of the first-quarter 2016 earnings season has come through with 87.2% (as of May 6) of the S&P 500 members having already reported results? This season is likely to finish as the fourth straight quarter of earnings declines for the S&P 500 index. Moreover, this trend of earnings declines is expected to continue into the second quarter as well. With several pharma and major biotech companies having released their earnings results, our Q1 scorecard shows that 92.5% of the Medical sector has reported results with a blended beat of 65.3% (the percentage of companies that have beaten both EPS as well as revenue estimates). Notably, the Medical sector is anticipated to be one of the seven sectors to record earnings growth in the first quarter of 2016, as per our Earnings Trends report. The earnings picture for both the pharma and the biotech sector looks pretty mixed with beats and misses. While in the biotech sector, Amgen Inc. AMGN topped first-quarter earnings and revenues and even raised the outlook for the year, another well-known biotech name Gilead lagged both earnings and revenue estimates even though it kept its outlook for the year intact. Among the other biotech stocks, Biogen, Celgene, Alexion and AbbVie managed to post mixed results, while some others came up with disappointing results and outlook for the year. Pharma giants like Johnson & Johnson JNJ , Pfizer and Bristol-Myers Squibb surpassed first-quarter earnings and revenue expectations and also raised the outlook for the year. Eli Lilly raised its outlook for the year despite an earnings miss while Glaxo expects core earnings growth of 10-12% at constant exchange rate in 2016. With several medium and small-sized drug companies still to report first-quarter 2016 results, let's see what awaits these drug stocks when they report their first-quarter results on May 10. What Awaits these Drug Stocks? Jazz Pharmaceuticals plcJAZZ , a biopharmaceutical company, has a portfolio of offerings targeting sleep and hematology/oncology disorders. Focus will be on the performance of marketed products including Xyrem, Defitelio and Erwinaze among others along with that of commercialization plans for Defitelio in the U.S., and the company's business development plans. Jazz's Earnings ESP of +6.11% and a Zacks Rank #3 (Hold) make us confident of an earnings beat this quarter (read more: Jazz Q1 Earnings: A Beat in the Cards for the Stock ). Palo Alto, CA-based Anacor Pharmaceuticals, Inc.ANAC is a biopharmaceutical company focused on the discovery, development and commercialization of small-molecule therapeutics derived from its boron chemistry platform. Anacor's track record so far has been mixed with the company missing estimates in two of the trailing four quarters with an average negative surprise of 16.68%. The company's Zacks Rank #4 (Sell) when combined with an ESP -32.35% makes a 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 = 0.0146 (i.e., a 1.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0146 = 6.8337, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014633, "expected_loss": 0.014633, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160517_0534", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2016-05-17", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0280, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0015, std=0.0136, worst_day=-0.0325\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-16] [\"Uber China Rival Didi Targets New York IPO In 2017\", \"With Buffett Betting Big, Is Apple\\u2019s Stock a Buy? With Warren Buffett\\u2019s Berkshire Hathaway buying $1 billion in stock, see what the charts recommend.\", \"Japanese firms expect more strong-yen headwinds TOKYO--Faced with a stronger yen, Japanese companies are reporting lower annual profits for the first time in four years, and projecting tepid earnings growth for the current year. The results for the financial year ended in March underscore how the record profits that many companies enjoyed in recent years depended on a weaker currency.\", \"Warren Buffett's Berkshire Hathaway took new 9.8 mln share stake in Apple in Q1\", \"Apple shares up 2.2% in premarket trade\", \"Apple's stock surges after Warren Buffett discloses new share stake Apple Inc.'s stock surged 2% in premarket trade Monday, after Warren Buffett's Berkshire Hathaway Inc. disclosed in a regulatory filing that it took a new 9.8 million share stake in the technology giant during the first quarter. That would represent about 0.2% of Apple's shares outstanding, according to FactSet data. Other moves Berkshire made include selling 99% of its stake in Procter & Gamble Co. to just 315,400 shares, trimming its stake in Wal-Mart Stores Inc. by 1.7% to 55.2 million shares. Berkshire also boosted its stake in Phillips 66 by 23% to 75.6 million shares, increased its stake in Liberty Media Corp. to 30 million shares, and slightly raised its stake in Deere & Co. and International Business Machines Corp. .\", \"Warren Buffett's Apple shares could be down $181 million since March Warren Buffett's investment vehicle Berkshire Hathaway Inc.'s new investment in Apple Inc. could be worth about $181.2 million less than it was 6 1/2 weeks ago, at the end of the first quarter. Berkshire's 13F filing showed that it owned a new 9,811,747 stake in Apple as of March 31, when the stock closed at $108.99, or 20% above Friday's closing price of $90.52. The filing did not disclose at what prices the shares were bought. The volume-weighted average price of Apple's stock during the quarter was $99.59. At that price, if its position in Apple was unchanged, Berkshire could have lost about $89 million on its Apple stake through Friday.\", \"A.M. Funds Roundup: How Are Your Mad Money Picks Doing?\", \"Warren Buffett\\u2019s Berkshire took new $1 billion Apple stake Legendary investor also sold entire AT&T position Warren Buffett\\u2019s Berkshire Hathaway took a new stake in Apple during the first quarter, valued at about $1 billion as of March 31.\", \"Apple Inc. jumps 1.4% to $91.67 in early trade after Berkshire Hathaway reveals stake\", \"Berkshire Bought Apple, Dumped AT&T in 1Q Berkshire Hathaway (BRK.B) disclosed a new, roughly $1.1 billion stake in Apple in documents filed Monday morning with securities regulators. The filings show that Berkshire added 9.8 million Apple shares that were valued at $1.069 billion as of the end of March, when Apple's stock traded at $\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 = 0.0280 (i.e., a 2.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0280 = 3.5730, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027987, "expected_loss": 0.027987, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190213_0536", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2019-02-13", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1007, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0440, worst_day=-0.1031\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9926", "answer_numeric": 0.9926, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1007 (i.e., a 10.07% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1007 = 0.9926, capped at 1.0.\nMaximum position size = 0.9926 (99.3% of portfolio).", "metadata": {"var_99": -0.100743, "expected_loss": 0.100743, "max_drawdown_threshold": 0.1, "position_size": 0.9926, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200724_0539", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2020-07-24", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0291, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0025, std=0.0130, worst_day=-0.0328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-07-23] [\"Elon Musk doesn\\u2019t want Tesla to be \\u2018super profitable\\u2019 as it soars toward a $300 billion valuation CEO says he wants to be \\u2018slightly profitable\\u2019 long-term while exaggerating timeline to full self-driving and counting on flagging solar business, but that doesn\\u2019t stop the stock Tesla Inc. Chief Executive Elon Musk, who heads a company with a valuation approaching $300 billion, doesn\\u2019t want his electric vehicle maker to be \\u201csuper profitable.\\u201d\", \"The Ariya is Nissan\\u2019s new electric crossover SUV, and it will have some semiautonomous tech If it comes on the market in a timely fashion, it can offer some competition for the Tesla Model Y With 300 miles of driving range, it offers some competition to the Tesla Model Y and Toyota RAV4 Prime.\", \"Tesla Stock\\u2019s Run-Up Isn\\u2019t Over Yet. How to Play It With Less Risk. To manage risk without ceding exposure to higher highs, investors can consider a \\u201cbull spread\\u201d that positions them for continued advances without meaningful exposure to weakness in the stock.\", \"This index ETF is beating the S&P 500 by excluding \\u2018losers\\u2019 Eliminating weak companies has led to outperformance for the GraniteShares XOUT U.S. Large Cap ETF Eliminating weak companies has led to outperformance for the GraniteShares XOUT U.S. Large Cap ETF.\", \"Apple joins tech rivals with pledge to be 100% carbon neutral by 2030 Apple says it has improved technology to pull rare earth magnets from old iPhones and is backing a first-ever carbon-free aluminum smelting process for MacBooks Apple Inc. on Tuesday joined the ambitious aim of rival tech giants, believing it can reduce and offset emissions along its entire supply chain and in the production of its iPhones and other devices, all in less than 10 years.\", \"The doctor behind a cognitive test Trump took says \\u2018it\\u2019s supposed to be easy\\u2019 The Montreal Cognitive Assessment, or MoCA, test discussed by President Trump and Chris Wallace is \\u2018not an IQ test,\\u2019 Dr. Ziad Nasreddine tells MarketWatch The Montreal Cognitive Assessment, or MoCA, test discussed by President Trump and Chris Wallace is \\u2018not an IQ test,\\u2019 Dr. Ziad Nasreddine tells MarketWatch\", \"Dow Inc., Travelers share losses lead Dow's nearly 150-point fall\", \"Hot Tech Stocks Show Signs of Cooling. Apple Could Be Next. With its stock up 33% year to date and sky-high Wall Street expectations for second quarter earnings, Apple could be the next disappointment.\", \"\\u2018We want a stable dollar,\\u2019 says U.S. Treasury Secretary Mnuchin: \\u2018It is the reserve currency of the world and we\\u2019re going to protect that\\u2019 Treasury Secretary Steven Mnuchin says that a stable U.S. dollar is the goal of the Trump administration, while, separately, noting that some froth was percolating in the stock market that has surged since its coronavirus lows in late March\", \"Dow's 75-point fall led by losses in shares of Dow Inc., Travelers\", \"Dow, Nasda\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 = 0.0291 (i.e., a 2.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0291 = 3.4354, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029109, "expected_loss": 0.029109, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220930_0542", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2022-09-30", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0959, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0025, std=0.0301, worst_day=-0.1006\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-29] \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 = 0.0959 (i.e., a 9.59% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0959 = 1.0423, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.095939, "expected_loss": 0.095939, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20221220_0545", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2022-12-20", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1859, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0023, std=0.0800, worst_day=-0.2144\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-19] \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": "0.5379", "answer_numeric": 0.5379, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1859 (i.e., a 18.59% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1859 = 0.5379, capped at 1.0.\nMaximum position size = 0.5379 (53.8% of portfolio).", "metadata": {"var_99": -0.185902, "expected_loss": 0.185902, "max_drawdown_threshold": 0.1, "position_size": 0.5379, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20160714_0550", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2016-07-14", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0278, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0009, std=0.0097, worst_day=-0.0336\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-07-13] [\"SAP-APWorks Team Up to Accelerate Industrial 3D Printing Taking another step in its 3D printing initiative, German software solutions corporation SAP SESAP inked a co-innovation agreement with APWorks, to accelerate the adoption and standardization of industrial 3D printing. This follows a promising collaboration with UPS in May, which aimed to establish a U.S. wide on-demand 3D printing network, by integrating SAP's extended supply chain solutions with UPS's additive industrial manufacturing and logistics network. SAP's deal with UPS aimed to provide access to on-demand manufacturing to companies, thus streamlining their supply chains, enhancing cost efficiency and reducing time-to-market. The APWorks Deal APWorks, a subsidiary of Airbus Defense and Space GmbH, and SAP intend to work toward facilitating the adoption and standardization of industrial 3D printing for the aerospace and defense industry. APWorks will leverage SAP's 3D printing services network to facilitate the development of a bionics network that will connect experts to end users. Using SAP's technology, APWorks will manufacture 3D printed components, enhance fuel efficiency and reduce CO2 emissions, along with managing spare part orders in real time. This will help it deliver qualified products on time for safety-critical applications in industries like aerospace and defense. In essence, SAP will be working with APWorks to manage orders better as they manufacture 3D printed components to deliver to industries where safety and quality is critical. Evolution of 3D Printing 3D printing has evolved past simple industrial prototyping and is fast racing toward manufacturing industries which use multiple materials like metals, plastics, and ceramics in 3D printing. This technology is on its way to revolutionize traditional manufacturing and redefine conventional notions of the industrial supply chain. It makes great sense for industries such as aerospace, where 3D printing will allow users to print the parts they need, thus ensuring the removal of several costs associated with traditional manufacturing. SAP's Initiatives SAP's collaborations corroborate the shift in manufacturing supply chain that 3D printing is enabling. In fact, SAP recently said that it intends to rationalize the supply chain in terms of collaborating and delivering certification cloud services for industrial 3D printing, using their own SAP HANA Cloud Platform. They also plan to create an on-demand 3D printing manufacturing network. This is in line with SAP's plans with APWorks, which will offer manufacturing and logistical cost savings while eliminating supply chain issues. SAP AG ADR Price SAP AG ADR Price | SAP AG ADR Quote However, SAP's prospects in the near term look gloomy as it contends with headwinds like stiff competition in the IT services industry, persistent weakness in multiple end-markets like Latin America and Brazil, and escalating research and development expenses. SAP currently has a Zacks Rank \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 = 0.0278 (i.e., a 2.78% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0278 = 3.5950, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027816, "expected_loss": 0.027816, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200914_0553", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2020-09-14", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1003, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0037, std=0.0644, worst_day=-0.1005\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-11] Ambarella Stock Could See Further Downside Ambarella Incorporated stock (NASDAQ: AMBA) is down 22% since the beginning of this year, but at the current price of $47 per share, we believe that Ambarella stock has a significant downside. Why is that? Our belief stems from the fact that Ambarella\u2019s stock has risen almost 35% from the low seen in early 2019. Our dashboard What Factors Drove 34% Change In Ambarella Inc. Stock Between 2018 And Now? provides the key numbers behind our thinking, and we explain more below. Ambarella is a semiconductor design company, manufacturing processors used across a variety of applications such as video compression, image processing, and computer vision. The stock rise over the past 2 years came despite a 22% drop in Ambarella\u2019s revenues, which combined with a roughly unchanged outstanding share count, led to a 22% fall in revenue per share (RPS) from 2018 to 2020. However, Ambarella\u2019s P/S ratio rose from about 3.9x at the end of 2018 to 8.7x at the end of 2019, but has dropped to 6.8x now. This fall came due to a drop in the company\u2019s profitability, with EPS falling from $0.57 in 2018 to -$1.35 in 2020, on the back of falling revenues and gross margins. Also, given the volatility of the current situation, there is further possible downside for Ambarella\u2019s multiple when compared to levels seen in the past years \u2013 P/S of 5.9x at the start of 2018, and 3.9x as recently as early 2019. So what\u2019s the likely trigger and timing to this downside? The global spread of coronavirus, and the resulting lockdowns and quarantine has led to a drop in demand for computing devices. Further, the rise in competitors in the video compression and computer vision markets has led to a drop in selling prices, weighing down company revenue. Ambarella\u2019s revenue for Q2 2021 came in at $50.1 million vs $56.4 million for the same period last year, and with expenses not dropping at the same rate, EPS came in at -$0.43 vs -$0.31. We expect this revenue drop to continue in the medium term. We believe Ambarella\u2019s Q3 results in December will confirm this and will also likely accompany a lower 2021 guidance. Regardless, if there isn\u2019t clear evidence of containment of the virus anytime soon, we believe the stock will see its P/S multiple decline from the current level of 6.8x to around 6x, which combined with a slight reduction in revenues and margins could result in the stock price shrinking to as low as $40. Want a more balanced portfolio instead? Here\u2019s a top quality portfolio to outperform the market, with over 100% return since 2016, versus 55% for the S&P 500. Comprised of companies with strong revenue growth, healthy profits, lots of cash, and low risk. It has outperformed the broader market year after year, consistently. See all Trefis Price Estimates and Download Trefis Data here What\u2019s behind Trefis? See How It\u2019s Powering New Collaboration and What-Ifs For CFOs and Finance Teams | Product, R&D, and Marketing Teams The views and opinions expre\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": "0.9966", "answer_numeric": 0.9966, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1003 (i.e., a 10.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1003 = 0.9966, capped at 1.0.\nMaximum position size = 0.9966 (99.7% of portfolio).", "metadata": {"var_99": -0.10034, "expected_loss": 0.10034, "max_drawdown_threshold": 0.1, "position_size": 0.9966, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200609_0556", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2020-06-09", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0035, std=0.0178, worst_day=-0.0289\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-08] [\"UBS Maintains Buy on Adobe, Raises Price Target to $450\", \"UBS Maintains Buy on Adobe, Raises Price Target to $450\", \"3 Top E-Commerce Stocks to Watch in June Many e-commerce businesses have seen tailwinds this year as conditions created by the novel coronavirus pandemic resulted in stores closing and spending migrating to digital channels. With many brick-and-mortar businesses beginning to reopen in conjunction with coronavirus restrictions being eased, June could provide valuable data about what the future of retail looks like. Investors interested in e-commerce stocks should keep an eye on Shopify (NYSE: SHOP), Baozun (NASDAQ: BZUN), and Adobe Systems (NASDAQ: ADBE) this month. Image source: Getty Images. 1. Shopify Shopify provides software that allows businesses to easily create and manage online-retail websites, and it's one of the e-commerce space's hottest stocks. Shares are crushing the market in 2020, climbing roughly 89.5% year to date after rallying 187% in 2019. SHOP data by YCharts. Shopify has posted torrid growth as it's brought more large companies on board its platform and become solidified as the category-leading e-commerce services provider for small-and-medium-size enterprises. The company saw heightened merchant-customer additions and shopper engagement as the novel coronavirus began disrupting brick-and-mortar retail operations in mid-March. Shopify stock hit a lifetime high in May, but shares have actually pulled back over the last couple of weeks despite the S&P 500 index climbing roughly 8% across the same stretch. The e-commerce company's valuation is currently down roughly 13% from the lifetime high it hit in May. With brick-and-mortar retail businesses beginning to reopen in the U.S. and other territories, Shopify's coronavirus-related momentum could be tested in June. Despite the potential for near-term volatility, the company's long-term growth outlook remains promising. E-commerce will only become more important for businesses, and pullback on the stock could present an entry point for long-term investors. 2. Baozun Baozun is sometimes referred to as \\\"the Shopify of China\\\" because it also provides website-creation tools and other e-commerce services. However, most of Baozun's customers are large companies, and its core business hinges on providing services for Western brands aiming to expand their presence in China's fast-growing e-commerce market. The stock is up roughly 4% year to date following Baozun's first-quarter earnings beat and encouraging Q2 guidance it published on June 2. Even with shares now in positive territory across 2020's trading, they're still down roughly 48% from their lifetime high two years ago due to slowing growth and tensions between the U.S. and China. Baozun is seeing business pick back up as the Chinese economy recovers from coronavirus-related conditions, but the country's increasingly fraught relationship with the U.S. could create obstacles to a sustained stock rebound. Phase on\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 = 0.0289 (i.e., a 2.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0289 = 3.4601, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028901, "expected_loss": 0.028901, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190920_0559", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-09-20", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0660, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0280, worst_day=-0.0775\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0660 (i.e., a 6.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0660 = 1.5144, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.066034, "expected_loss": 0.066034, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190902_0562", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2019-09-02", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0194, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0010, std=0.0085, worst_day=-0.0196\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-08-30] [\"Nvidia Stock Is a Long-Term Winner Predicting what technologies will be prevalent in ten years is difficult. Who\\u2019s to say whether the dominant smartphone will be Apple\\u2019s (NASDAQ:) iPhone or Alphabet\\u2019s (NASDAQ:, NASDAQ:GOOG) Pixel? But Nvidia (NASDAQ:), and Nvidia stock are easier to bet on because the company is powering the technological pillars of tomorrow. Source: Hairem / Shutterstock.com Many sectors, including agriculture, transportation, drones and cloud computing, are turning to artificial intelligence. Often referred to as A.I., this technology requires an insane amount of computing power. The company best suited to provide that computing power is Nvidia. As a result, NVDA and Nvidia stock are in prime position to be long-term winners. Earlier this year, I took a very . I suggest reading the column if you are curious about the company\\u2019s long-term outlook. I would not necessarily say that the company\\u2019s catalysts make NVDA stock a screaming buy, but they do make the shares worth considering for long-term investors. Valuing Nvidia Stock Nvidia stock was on an unsustainable flight path, rallying hundreds of percent in just a few years. In Oct. 2015, NVDA was changing hands in the $16 range. Now in the mid-$160s, NVDA is still up ten-fold from those levels. At its high near $300, NVDA stock had jumped almost 18 times from its late 2015 levels. Despite the pullback of Nvidia stock, Nvidia\\u2019s core business hasn\\u2019t been knocked off course. Previously, crypto miners were inflating demand for the company\\u2019s products, but that trend has since slowed greatly, hurting Nvidia\\u2019s results, Advanced Micro Devices (NASDAQ:) experienced a similar phenomenon, although that company has done a better job of sidestepping the pain. As it stands, AMD is forecast to have positive earnings and revenue growth this year and explosive growth next year. Unfortunately for Nvidia, it\\u2019s not in the same boat. Analysts, on average, expect its sales to slump 8% this year and predict that its earnings will tumble 18.8% in 2019. Investors are already aware that this is a down year for NVDA and that there\\u2019s not much to be done about it. But NVDA stock is treading higher in recent weeks, even as the trade war continues. The biggest risk facing Nvidia stock, in my view, is estimates for next year, Nvidia\\u2019s fiscal 2021. Analysts, on average, expect its top line to jump nearly 20% to $12.91 billion and predict that its earnings per share will surge about 31% to $7.08. Those figures would surpass Nvidia\\u2019s fiscal 2019 results and put it back on the path of growth. They would also makes its forward price-earnings ratio, which currently trading at 23.6, more reasonable. If the average estimates materialize, and the trailing 12 month P/E ratio of Nvidia stock stays around its current level of 38, its price would reach roughly $270. Trading NVDA Stock $270 does not seem like a great price for many investors, given that NVDA \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 = 0.0194 (i.e., a 1.94% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0194 = 5.1570, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019391, "expected_loss": 0.019391, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200828_0565", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2020-08-28", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0478, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0038, std=0.0228, worst_day=-0.0600\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0478 (i.e., a 4.78% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0478 = 2.0903, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.04784, "expected_loss": 0.04784, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210107_0570", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2021-01-07", "context_summary": "SCHP: 60-day history, VaR(99%)=-0.0034, max drawdown threshold=10%.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0002, std=0.0017, worst_day=-0.0041\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 = 0.0034 (i.e., a 0.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0034 = 29.3204, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.003411, "expected_loss": 0.003411, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160824_0573", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2016-08-24", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0256, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0009, std=0.0078, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-08-23] [\"Applied Materials' EPS Growing Faster Than Its Stock Price\", \"Applied Materials' EPS Growing Faster Than Its Stock Price\", \"Nasdaq 100 Movers: MYL, AMAT In early trading on Tuesday, shares of Applied Materials topped the list of the day's best performing components of the Nasdaq 100 index, trading up 2.0%. Year to date, Applied Materials registers a 59.2% gain. And the worst performing Nasdaq 100 component thus far on the day is Mylan, trading down 2.9%. Mylan is lower by about 14.0% looking at the year to date performance. Two other components making moves today are Incyte, trading down 0.6%, and Bed, Bath & Beyond, trading up 1.9% on the day. VIDEO: Nasdaq 100 Movers: MYL, AMAT The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"After Hours Most Active for Aug 23, 2016 : ESRX, AAPL, LMT, WIX, CSCO, MSFT, EMC, AMAT, WFT, PFE, BAC, C The NASDAQ 100 After Hours Indicator is down -1.39 to 4,817.09. The total After hours volume is currently 25,228,394 shares traded. The following are the most active stocks for the after hours session : Express Scripts Holding Company ( ESRX ) is unchanged at $77.15, with 2,576,986 shares traded. Over the last four weeks they have had 10 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2016. The consensus EPS forecast is $1.74. As reported in the last short interest update the days to cover for ESRX is 7.891486; this calculation is based on the average trading volume of the stock. Apple Inc. ( AAPL ) is -0.04 at $108.81, with 2,177,072 shares traded. Over the last four weeks they have had 8 up revisions for the earnings forecast, for the fiscal quarter ending Sep 2016. The consensus EPS forecast is $1.64. As reported by Zacks, the current mean recommendation for AAPL is in the \\\"buy range\\\". Lockheed Martin Corporation ( LMT ) is unchanged at $249.75, with 1,623,803 shares traded. LMT's current last sale is 96.06% of the target price of $260. Wix.com Ltd. ( WIX ) is -0.53 at $39.10, with 1,000,131 shares traded. Over the last four weeks they have had 3 up revisions for the earnings forecast, for the fiscal quarter ending Dec 2016. The consensus EPS forecast is $-0.15. , following a 52-week high recorded in today's regular session. Cisco Systems, Inc. ( CSCO ) is unchanged at $30.98, with 946,770 shares traded. As reported by Zacks, the current mean recommendation for CSCO is in the \\\"buy range\\\". Microsoft Corporation ( MSFT ) is +0.01 at $57.90, with 914,232 shares traded. As reported by Zacks, the current mean recommendation for MSFT is in the \\\"buy range\\\". EMC Corporation ( EMC ) is +0.05 at $28.68, with 818,256 shares traded. EMC's current last sale is 95.6% of the target price of $30. Applied Materials, Inc. ( AMAT ) is unchanged at $29.95, with 784,651 shares traded. O\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 = 0.0256 (i.e., a 2.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0256 = 3.9103, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025573, "expected_loss": 0.025573, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180109_0576", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2018-01-09", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0104, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0017, std=0.0059, worst_day=-0.0106\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-01-08] [\"Activist shareholders want Apple to help kids kick iPhone addictions Jana, teachers group push for better corporate responsibility The iPhone has made Apple Inc. and Wall Street hundreds of billions of dollars. Now some big shareholders are asking at what cost, in an unusual campaign to make the company more socially responsible.\", \"Consumer Tech To Hit Record $351 Billion In 2018: CES The semi-annual industry report, released shortly before the start of the Consumer Electronics Show (CES) here, includes for the first time a projection for consumer spending on music and video-streaming services, which it says will account for $19.5 billion.\", \"Whirlpool appliances to communicate with Apple Watch in early 2018 Whirlpool Corp. said Monday it will activate Apple Watch functionality for its home appliances in early 2018. Consumers will be able to remotely communicate with ovens, washers and dryers via Apple Inc.'s Apple Watch, with the roll out to more than 20 Whirlpool brand appliances. \\\"Bringing intuitive technology and functionality to the appliance category that helps take the friction out of household chores is chief among our goals as we innovate for the smart home,\\\" said Brett Dibkey, vice president of brand strategy. \\\"Our consumers are sophisticated and expect their appliances to work smarter, not harder.\\\" Separately, Whirlpool said it was collaborating with Honeywell International Inc. , to allow consumers to connect smart appliances from Whirlpool to Honeywell's thermostats. Whirlpool's stock was still inactive in premarket trade, while Apple shares eased 0.1%. Over the past three months, Whirlpool's stock has dropped 7.1%, Apple shares have climbed 12.7%, Honeywell shares have tacked on 8.3% and the Dow Jones Industrial Average has rallied 11.1%.\", \"U.S. consumer electronics sales expected to reach record $351B in 2018 with help from streaming services The U.S. consumer technology industry is expected to reach record sales of $351 billion in 2018, up 3.9% from 2017, according to the Consumer Technology Association. This year's sales got a boost from the addition of on-demand video services like Netflix Inc. , Hulu and Sling TV, and on-demand audio services like Spotify, Pandora and Apple Music . The CTA included these services for the first time in order \\\"to better capture the full expanse of the ever-evolving and expanding consumer technology market.\\\" Without these services, 2018 growth would only be 2.2%. Some of the technologies expected to drive sales this year are smart speakers, with sales expected to grow 60% this year, smart home items like smart locks and doorbells, expected to grow 41%, and virtual reality headsets and eyewear, expected to be up 25%. The top five \\\"mature\\\" technologies, including smartphones, laptops and TVs are expected to make up 51% of revenue for the year. The Consumer Electronics Show will be Jan. 9 through Jan. 12.\", \"6 ways to make smartphones more humane \\u2014 and less addictive 39% of millennia\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 = 0.0104 (i.e., a 1.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0104 = 9.6426, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010371, "expected_loss": 0.010371, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160121_0579", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2016-01-21", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0291, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=-0.0014, std=0.0123, worst_day=-0.0300\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-20] Commit To Buy American Electric Power Company At $45, Earn 5.7% Using Options Investors considering a purchase of American Electric Power Company, Inc. (Symbol: AEP) shares, but tentative about paying the going market price of $58.07/share, might benefit from considering selling puts among the alternative strategies at their disposal. One interesting put contract in particular, is the January 2018 put at the $45 strike, which has a bid at the time of this writing of $2.55. Collecting that bid as the premium represents a 5.7% return against the $45 commitment, or a 2.8% annualized rate of return (at Stock Options Channel we call this the YieldBoost ). Selling a put does not give an investor access to AEP's upside potential the way owning shares would, because the put seller only ends up owning shares in the scenario where the contract is exercised. And the person on the other side of the contract would only benefit from exercising at the $45 strike if doing so produced a better outcome than selling at the going market price. ( Do options carry counterparty risk? This and six other common options myths debunked ). So unless American Electric Power Company, Inc. sees its shares decline 23% and the contract is exercised (resulting in a cost basis of $42.45 per share before broker commissions, subtracting the $2.55 from $45), the only upside to the put seller is from collecting that premium for the 2.8% annualized rate of return. Below is a chart showing the trailing twelve month trading history for American Electric Power Company, Inc., and highlighting in green where the $45 strike is located relative to that history: The chart above, and the stock's historical volatility, can be a helpful guide in combination with fundamental analysis to judge whether selling the January 2018 put at the $45 strike for the 2.8% annualized rate of return represents good reward for the risks. We calculate the trailing twelve month volatility for American Electric Power Company, Inc. (considering the last 253 trading day closing values as well as today's price of $58.07) to be 20%. For other put options contract ideas at the various different available expirations, visit the AEP Stock Options page of StockOptionsChannel.com. In mid-afternoon trading on Wednesday, the put volume among S&P 500 components was 1.33M contracts, with call volume at 1.62M, for a put:call ratio of 0.82 so far for the day, which is unusually high compared to the long-term median put:call ratio of .65. In other words, there are lots more put buyers out there in options trading so far today than would normally be seen, as compared to call buyers. Find out which 15 call and put options traders are talking about today . Top YieldBoost Puts of the S&P 500 \u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect \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 = 0.0291 (i.e., a 2.91% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0291 = 3.4309, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029147, "expected_loss": 0.029147, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150217_0582", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2015-02-17", "context_summary": "XLK: 29-day history, VaR(99%)=-0.0254, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 29 days): mean=0.0011, std=0.0113, worst_day=-0.0293\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-02-13] [\"London wants a piece of New York\\u2019s startups U.K. led startup funding in Europe last month, raising $294 million The U.K. government launched a new initiative called HQUK this week to try and lure foreign businesses to the British isles.\", \"Goldman traded its reputation for quick profits It was once known as an investment bank but now it\\u2019s a hedge fund It was once known as an investment bank but now it\\u2019s a hedge fund, says David Weidner.\", \"Apple price target raised to $135 at BMO Capital Markets\", \"Apple price target raised to $150 at UBS\", \"Apple developing 'mega-ecosystem' as target raised to $150 NEW YORK (MarketWatch) - Apple Inc.'s price target was raised to $150 at UBS and to $135 at BMO Capital Markets on Friday, as analysts continue to grow more bullish on the iPhone maker's product line. On Thursday, Apple's stock closed at a record split-adjusted high of $126.46, valuing the company at more than $736 billion, the highest valuation of any U.S. company in history. UBS analyst Steven Milunovich, who rates Apple a buy, said Apple is creating a \\\"mega-ecosystem\\\" that is quickly turning the company into a platform, rather than just a device, company. \\\"Apple the platform company may take it to $1 trillion,\\\" he said. At $150, UBS is one of the most bullish brokerages on Apple's stock, behind just Cantor Fitzgerald, which has a $160 target on Apple. Meanwhile, BMO analyst Keith Bachman, who has an outperform rating on the stock, said he thinks Apple is adding \\\"far more users than are leaving the brand\\\" and that its fiscal 2015 iPhone unit forecast may be conservative. Shares of Apple edged 0.4% higher to $126.98 in premarket trade. To get to a $1 trillion market valuation, shares of Apple will have to reach $172.\", \"Apple\\u2019s expanding \\u2018Appleverse\\u2019 will lure you in Apple creating mega-ecosystem as target raised to $150 at UBS Apple wants iOS to permeate all aspects of consumers\\u2019 lives, more than it already does.\", \"Lovelorn single people should move to these cities Some singletons this Valentine\\u2019s Day may be looking for love in all the wrong places (or cities).\", \"Week in Review: Musk, Holocaust Chic and Homer go into \\u2018insane mode\\u2019 Marek Fuchs reviews the top events of the week, including news from Elon Musk, Holocaust Chic and Homer Simpson.\", \"American Express: After Costco, the Deluge\", \"10 biggest financial-market events this week Rising oil prices, energy stocks, Greece and Ukraine led the news Rising oil prices, energy stocks, Greece and Ukraine led the news.\", \"Groupon rallies as Zynga sinks; Tesla struggles Apple shrugs off analysts\\u2019 price target hikes Groupon, Zynga, Tesla, and Apple are among notable movers in Friday\\u2019s session.\", \"David Tepper's Appaloosa slashes equity holdings; closes Apple, Facebook positions NEW YORK (MarketWatch) -- David Tepper's hedge fund Appaloosa Management disclosed that the value of its equity holdings were reduced by 40% late last year, accor\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 = 0.0254 (i.e., a 2.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0254 = 3.9420, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025368, "expected_loss": 0.025368, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210729_0585", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2021-07-29", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0016, std=0.0102, worst_day=-0.0285\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-07-28] [\"LG will reportedly sell iPhones in its South Korean stores LG has confirmed that it will start selling iPhones and other Apple products in its South Korean stores next month,\", \"The Morning After: iPhone sales are up 50 percent year over year Today\\u2019s headlines: iPhone sales are up 50 percent year over year, Activision Blizzard employees plan walkout over harassment lawsuit response and Tesla pushes back Semi truck release to 2022.\", \"Stock futures mixed as investors digest tech earnings, await Fed Stock futures struggled for direction Wednesday morning, with investors digesting a slew of Big Tech earnings results and looking ahead to another set of reports. A monetary policy statement from the Federal Reserve is also slated for release.\", \"Nura finally goes fully wireless with the NuraTrue buds It\\u2019s also been a core part of Nura\\u2019s DNA since the beginning. Everything Nura does is built around its audio technology \\u2014 something that\\u2019s held true since before I had the opportunity to try the original Nuraphones as a prototype with a big, unsightly circuit board attached. Announced today, NuraTrue mark the company\\u2019s third entry into the headphone market, following the over-ear Nuraphones and the tethered Nuraloop.\", \"Google unveils its proposed 'safety section' for apps on Google Play In the wake of Apple's advances into consumer privacy with initiatives like App Tracking Transparency and App Store privacy labels, Google recently announced its own plans to introduce a new \\\"safety section\\\" on Google Play that offers more information about the data apps collect and share, and other security and privacy details. In May, Google explained the safety section would be designed to easily communicate to users how apps are handling their data so they could make informed choices. It said app developers would need to disclose to users whether their app uses security practices like data encryption, whether it follows Google Play's Families policy for apps aimed at kids, whether users have a choice in data sharing, whether the app's safety section had been verified by a third party, and if the app allowed users to request data deletion at the time of uninstalling, among other things.\", \"Spotify's podcast ad revenue jumps 627% in Q2 In the minutes before its quarterly earnings call this morning, Spotify played advertisements for its Originals & Exclusives, like the true crime show \\\"Deathbed Confessions,\\\" and the sex and relationships podcast \\\"Call Her Daddy,\\\" which Spotify recently acquired in a deal worth $60 million. Sure, it's kind of hilarious to hear a recording of host Alex Cooper's voice say, \\\"Hey, daddy gang!\\\" as investors log in to an 8 AM call, but the subtext rang clear: Spotify is serious about growing its podcast business. Given how many podcasting companies Spotify has acquired over the past few years, it would be concerning if there hadn't been significant growth in this realm.\", \"Shopify's Q2 results beat estimat\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 = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7337, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026783, "expected_loss": 0.026783, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20191011_0588", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-10-11", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1278, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0011, std=0.0381, worst_day=-0.1593\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7824", "answer_numeric": 0.7824, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1278 (i.e., a 12.78% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1278 = 0.7824, capped at 1.0.\nMaximum position size = 0.7824 (78.2% of portfolio).", "metadata": {"var_99": -0.127804, "expected_loss": 0.127804, "max_drawdown_threshold": 0.1, "position_size": 0.7824, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20191010_0591", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2019-10-10", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0349, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0008, std=0.0115, worst_day=-0.0399\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-10-09] [\"Monness Crespi Hardt becomes latest to slash its Netflix price target on competition concerns Monness Crespi Hardt became the latest house to slash its stock price target for Netflix Inc. on Wednesday, when it shaved $100 off its target to lower it to $340. Analyst Brian White reiterated his buy rating on the stock in a note to clients ahead of the streaming company's third-quarter earnings next week. \\\"In light of the weakening macro environment since Netflix last provided guidance, combined with more details last month from Apple around its planned launch of Apple TV+ and incremental data points around increasingly fierce competition for content, we are adjusting our estimates for Netflix accordingly and lowering our 12-month price target to $340 from $440,\\\" White wrote. Evercore analyst Vijay Jayant slashed his Netflix price target to $300 from $380 on Monday, also citing concerns about coming competition from providers including Disney . Netflix shares were up 0.4% premarket but have fallen 24% in the last 12 months, while the S&P 500 has gained 0.4%.\", \"Apple blasted by China\\u2019s state media for \\u2018unwise and reckless decision\\u2019 to allow apps that help Hong Kong protesters A separate newspaper identified the app as HKmap.live Apple accused of offering a mobile app that \\u201cclaims to provide transportation information for the convenience of the public,\\u201d but instead identifies police locations, the China paper says.\", \"China Trade Speed Bumps May Keep Haunting Investors U.S. stock futures are climbing on hopes that China may be ready to agree a partial trade deal, in a week that has whipsawed investors around over worries that talks between the two countries face big headwinds.\", \"Tech investors need to brace for this pivotal $160 billion \\u2018gut punch\\u2019 in December, says analyst Dan Ives Critical information for the U.S. trading day Our call of the day warns investors to mark their calendar for a \\u201cpivotal $160 billion\\u201d crucial moment ahead for the tech space.\", \"Apple Stock Is Beating the Market. Analyst Expects More Gains. Canaccord cited the success of the iPhone 11 and growth in the services business. The launch of Apple TV+ in November could give the stock an extra push.\", \"The Dow Is Up 146 Points Because Hopes Are Up for a China Trade Deal Stocks are holding onto gains approaching midday Wednesday. Investors are still hanging onto hope that there could be some progress on trade when the U.S. and China resume tariff talks tomorrow.\", \"Netflix Stock Could Take a Hit From Rising Content Costs, Analyst Says Rosenblatt Securities says Netflix stock is not attractive even after its big decline in recent months.\", \"Google is working on 5G version of smartphone: report Alphabet Inc.\\u2019s Google will probably join the 5G fray in 2020, leaving Apple Inc. as the last major vendor to announce its plans Alphabet Inc. is working on a 5G-version of its Pixel 4 smartphone, but don\\u2019t expect a sneak peek next we\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 = 0.0349 (i.e., a 3.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0349 = 2.8678, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03487, "expected_loss": 0.03487, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181016_0594", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2018-10-16", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0235, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0001, std=0.0058, worst_day=-0.0253\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-15] [\"GoPro to Sell Curated Video Clips to the Adobe Stock Marketplace\", \"Adobe Sees FY19 Total Adobe Sales Growth ~20% Year Over Year, Sees Digital Media Annualized Recurring Sales ~$1.4B Of Net New ARR\", \"Adobe Reaffirms Q4 Sales, EPS Guidance\", \"UPDATE: Adobe Reaffirms Q4 Guidance: Sales ~$2.42B vs $2.43B Estimate, Adj. EPS $1.87 vs $1.89 Est.\", \"Adobe To Host Call Mon., Oct. 15, 2018 At 5 p.m. EDT To Discuss Numerous Drivers For Growth Of Total Addressable Market To Expand From ~$83M In 2020 To ~$108M By 2021\", \"Adobe shares are up 5.8% after the company reaffirmed Q4 guidance; The company sees 20% year-over-year sales growth in FY19.\", \"5 Stocks Moving In Tuesday's After-Hours Session\", \"5 Stocks Moving In Tuesday's After-Hours Session\", \"Adobe shares are up 5.8% after the company reaffirmed Q4 guidance; The company sees 20% year-over-year sales growth in FY19.\", \"Adobe To Host Call Mon., Oct. 15, 2018 At 5 p.m. EDT To Discuss Numerous Drivers For Growth Of Total Addressable Market To Expand From ~$83M In 2020 To ~$108M By 2021\", \"UPDATE: Adobe Reaffirms Q4 Guidance: Sales ~$2.42B vs $2.43B Estimate, Adj. EPS $1.87 vs $1.89 Est.\", \"Adobe Sees FY19 Total Adobe Sales Growth ~20% Year Over Year, Sees Digital Media Annualized Recurring Sales ~$1.4B Of Net New ARR\", \"Adobe Reaffirms Q4 Sales, EPS Guidance\", \"GoPro to Sell Curated Video Clips to the Adobe Stock Marketplace\", \"Factors Setting the Tone for SAP SE (SAP) in Q3 Earnings SAP SESAP is scheduled to report third-quarter 2018 results on Oct 18. Notably, the company has a mixed record of earnings surprises in the trailing four quarters, with an average beat of 5.6%. The company reported second-quarter 2018 non-IFRS earnings of \\u20ac0.98 ($1.17) per share, up 4.3% on a year-over-year basis. However, the bottom line fell short of the Zacks Consensus Estimate of $1.18 per share. Total revenues, on non-IFRS basis, were \\u20ac6.01 billion ($7.15 billion), up 4% year over year (up 10% at constant currency), exceeding the Zacks Consensus Estimate of $7.11 billion. A flourishing cloud business and strong growth of support revenues aided top-line growth in the last reported quarter. What to Expect? The Zacks Consensus Estimate for third-quarter earnings is pegged at $1.26 per share, indicating an increase of 5.9% on a year-over-year basis. Revenues are estimated to be around $6.97 billion, indicating a rise of 6.1% from the year-ago quarter. Let's see how things are shaping up for this announcement. Factor Influencing Q3 Results SAP's Cloud and Software business have been consistent growth drivers for quite some time. In fact, Cloud and software business revenues came in at \\u20ac5.25 billion in the second quarter, up 4% year over year driven by Cloud subscriptions & support revenues of \\u20ac1.30 billion, which surged 40% from the year-ago quarter. Further, the company's human capital management (''HCM'') applications continue to boost the top line, including the likes of SuccessFactors and SAP Fieldgl\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 = 0.0235 (i.e., a 2.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0235 = 4.2496, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023532, "expected_loss": 0.023532, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220720_0599", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2022-07-20", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1355, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0721, worst_day=-0.1362\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-19] \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": "0.7382", "answer_numeric": 0.7382, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1355 (i.e., a 13.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1355 = 0.7382, capped at 1.0.\nMaximum position size = 0.7382 (73.8% of portfolio).", "metadata": {"var_99": -0.135473, "expected_loss": 0.135473, "max_drawdown_threshold": 0.1, "position_size": 0.7382, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20210728_0602", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2021-07-28", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1420, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0038, std=0.0582, worst_day=-0.1912\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7040", "answer_numeric": 0.704, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1420 (i.e., a 14.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1420 = 0.7040, capped at 1.0.\nMaximum position size = 0.7040 (70.4% of portfolio).", "metadata": {"var_99": -0.142049, "expected_loss": 0.142049, "max_drawdown_threshold": 0.1, "position_size": 0.704, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160623_0605", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2016-06-23", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0223, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0003, std=0.0103, worst_day=-0.0274\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-06-22] [\"Keep an Eye on These 10 Stocks for June 22, 2016\", \"A Peek Into The Markets: U.S. Stock Futures Edge Higher Ahead Of Yellen Speech\", \"JPMorgan Wanted More From Adobe\", \"12 Stocks Moving In Wednesday's Pre-Market Session\", \"Goldman Says Adobe Is Executing On Transition, But Asks What The Next Catalyst Could Be\", \"Citi Still Likes Adobe Shares Following Q2 Results\", \"The Market In 5 Minutes: Elon Musk's Trillion-Dollar Bet\", \"6 Largest Price Target Changes For Wednesday\", \"Slowing Digital Marketing Trend Could Weigh On Adobe Stock\", \"Canaccord Is Against The Majority On Adobe Systems: Reiterates Buy\", \"Adobe Might Not Have Done Enough This Quarter\", \"Adobe Had A 'Healthy' Q2 Beat\", \"Adobe's Slowing Digital Marketing Could Be An Overhang\", \"10 Biggest Mid-Day Losers For Wednesday\", \"RBC Reiterates Outperform On Adobe Shares\", \"Adobe Saw Continued Momentum In Its Creative Cloud, Says Deutsche Bank\", \"Adobe Saw Continued Momentum In Its Creative Cloud, Says Deutsche Bank\", \"RBC Reiterates Outperform On Adobe Shares\", \"10 Biggest Mid-Day Losers For Wednesday\", \"Adobe's Slowing Digital Marketing Could Be An Overhang\", \"Adobe Had A 'Healthy' Q2 Beat\", \"Adobe Might Not Have Done Enough This Quarter\", \"Canaccord Is Against The Majority On Adobe Systems: Reiterates Buy\", \"Slowing Digital Marketing Trend Could Weigh On Adobe Stock\", \"6 Largest Price Target Changes For Wednesday\", \"The Market In 5 Minutes: Elon Musk's Trillion-Dollar Bet\", \"Citi Still Likes Adobe Shares Following Q2 Results\", \"Goldman Says Adobe Is Executing On Transition, But Asks What The Next Catalyst Could Be\", \"12 Stocks Moving In Wednesday's Pre-Market Session\", \"JPMorgan Wanted More From Adobe\", \"A Peek Into The Markets: U.S. Stock Futures Edge Higher Ahead Of Yellen Speech\", \"Keep an Eye on These 10 Stocks for June 22, 2016\", \"Adobe (ADBE) Beats Earnings and Revenue Estimates in Q2 Adobe Systems Inc.ADBE reported second-quarter fiscal 2016 earnings of 55 cents per share, which beat the Zacks Consensus Estimate by a couple of cents. Adjusted earnings per share exclude one-time items but include stock-based compensation expense. Better-than-expected earnings were backed by a strong adoption of cloud that led to record Creative and Marketing Cloud revenues and better-than-expected Digital Media ARR (Annualized Recurring Revenue) growth. However, the share price fell more than 4% in after-hours trading session due to a weaker-than-expected fiscal third-quarter revenue guidance. ADOBE SYSTEMS Price, Consensus and EPS Surprise ADOBE SYSTEMS Price, Consensus and EPS Surprise | ADOBE SYSTEMS Quote Revenues Adobe's revenues of $1.40 billion increased 1.1% sequentially and 20.4% year over year. Reported revenues were on the higher end of management's guided range of $1.365-$1.415 billion and above the Zacks Consensus Estimate of $1.394 billion. Subscription comprised 57% of Adobe's total first-quarter revenues, up 40% from the year-ago period. Products declined 28.4% year over year and contri\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 = 0.0223 (i.e., a 2.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0223 = 4.4805, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022319, "expected_loss": 0.022319, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20171220_0608", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2017-12-20", "context_summary": "VCIT: 60-day history, VaR(99%)=-0.0039, max drawdown threshold=10%.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=0.0000, std=0.0016, worst_day=-0.0043\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 = 0.0039 (i.e., a 0.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0039 = 25.4155, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.003935, "expected_loss": 0.003935, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210929_0611", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2021-09-29", "context_summary": "MORT: 60-day history, VaR(99%)=-0.0263, max drawdown threshold=10%.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=-0.0002, std=0.0115, worst_day=-0.0327\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MORT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0263 (i.e., a 2.63% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0263 = 3.7999, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026317, "expected_loss": 0.026317, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200306_0616", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2020-03-06", "context_summary": "INDS: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%.", "question": "Asset: INDS\nDaily returns (past 60 days): mean=0.0001, std=0.0134, worst_day=-0.0391\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 = 0.0356 (i.e., a 3.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0356 = 2.8078, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035615, "expected_loss": 0.035615, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200409_0619", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2020-04-09", "context_summary": "BIL: 60-day history, VaR(99%)=-0.0003, max drawdown threshold=10%.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0000, std=0.0002, worst_day=-0.0003\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 = 0.0003 (i.e., a 0.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0003 = 305.5951, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000327, "expected_loss": 0.000327, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220921_0621", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2022-09-21", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0820, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0030, std=0.0345, worst_day=-0.0968\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-20] \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 = 0.0820 (i.e., a 8.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0820 = 1.2200, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.081967, "expected_loss": 0.081967, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20160920_0624", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2016-09-20", "context_summary": "USO: 60-day history, VaR(99%)=-0.0494, max drawdown threshold=10%.", "question": "Asset: USO\nDaily returns (past 60 days): mean=-0.0027, std=0.0243, worst_day=-0.0509\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USO, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0494 (i.e., a 4.94% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0494 = 2.0224, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.049447, "expected_loss": 0.049447, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190813_0627", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2019-08-13", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0219, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0007, std=0.0088, worst_day=-0.0312\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-08-12] [\"3 Great Stocks Beaten Down This Earnings Season This article was first published by MyWallSt. Find out more about MyWallSt's market-beating investing services now! If you follow Warren Buffett's long-term approach -- not owning a stock for 10 minutes if you wouldn't own it for 10 years -- then you should end up holding a stock for at least 40 quarterly earnings reports. Throughout the years, however, there are bound to be times when earnings fall below expectations or guidance is decreased. The best response to this is to ignore the urge to panic-sell and relax. Image source: Unsplash. Coming to the end of this earnings season, it can be a good opportunity to see if you still believe in a company, and if it still has the potential you saw when you first bought it. These three companies declined following their earnings reports, yet still have great promise. 1. Disney On Aug. 6, Walt Disney (NYSE: DIS) announced its third-quarter earnings. It reported earnings per share (EPS) of $1.35, under the expected value of $1.75. Disney blamed this underperformance on the disappointing results of Fox, increasing streaming investment costs, and weak theme park attendance. Following this announcement, shares dropped over 5%. Despite disappointing Wall Street, Disney still has significant potential. Disney's new streaming service, Disney+, launches on Nov. 12 and will prove to be a formidable competitor to Netflix (NASDAQ: NFLX). Not only will Disney+ offer exclusive Disney content, but the price of this service will be considerably cheaper, with Disney+ starting at $6.99 in comparison to $8.99 for Netflix. Furthermore, Disney announced that it will bundle Disney+, ESPN+, and Hulu for $12.99, expanding the target demographic of its subscription service. Over time, this platform will likely help the Fox acquisition become profitable. While park attendance may be down this quarter, revenue in this segment is up. Average spending at U.S. theme parks rose 10% thanks to an increase in food and merchandise spending, higher hotel occupancy, and a boost in ticket prices. Because of concerns about long wait times, Disney's new Star Wars theme park, Star Wars: Galaxy's Edge, saw a smaller crowd than anticipated, but Disney has introduced a new \\\"virtual queue\\\" system to provide a better experience for attendees. On Aug. 29, Disney is launching an Orlando-based Star Wars park, and with this new park opening in Disney's largest resort, there is no doubt that there will be a considerable revenue boost. An extensive range of intellectual properties has made Disney one of the most culturally significant companies that we see today. Long-term investors should not lose sleep over quarterly reports for this historic company. 2. Planet Fitness Planet Fitness (NYSE: PLNT), a gym franchise for novice and casual gym-goers, reported its Q2 earnings after the markets closed on Tuesday, Aug. 6. This report was overwhelmingly positive, with an EPS of $0.45, up from $0.31 last year a\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 = 0.0219 (i.e., a 2.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0219 = 4.5705, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021879, "expected_loss": 0.021879, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20191107_0632", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2019-11-07", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0276, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0007, std=0.0103, worst_day=-0.0322\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-06] [\"Robinhood glitch is letting users trade with unlimited amounts of borrowed cash Bug gives traders infinite leverage \\u2014 but it\\u2019s also a very bad idea to try A glitch in the stock-trading app Robinhood is allowing investors to trade with apparently unlimited amounts of borrowed money.\", \"Why Warren Buffett Should Buy Walgreens The Berkshire Hathaway CEO has been searching in vain for a large acquisition that could absorb a chunk of Berkshire\\u2019s growing cash balance. Walgreens Boots Alliance could be it.\", \"Roku remains a promising stock even after this year\\u2019s surge Roku is the most fairly valued pure play in the over-the-top space Roku is the most fairly valued pure play in the over-the-top space, writes Beth Kindig.\", \"Sonos could be the next hardware acquisition after Fitbit, says analyst D.A. Davidson analyst Tom Forte said Wednesday that Sonos Inc. looks well positioned to see its stock appreciate either due to improved investor perception or an acquisition, in the wake of Alphabet Inc.'s plans to purchase Fitbit Inc. \\\"On the bad block of hardware companies, we consider Sonos to be: 1) the best house on the block and 2) the one adjacent to the mansion on the neighboring block, Apple ,\\\" Forte wrote. He sees Sonos as similar to Apple due to his view that both companies make superior products with a focus on design and are able to charge more than competitors. \\\"We see Sonos as a natural acquisition target for Apple, given the similarities in: 1) product quality, 2) design acumen, and 3) premium brands,\\\" Forte wrote. \\\"Just as Fitbit fills a void for Google when it comes to healthcare-related data, acquiring Sonos could materially advance Apple's connected home efforts (an area we believe it needs improvement and where its own product, the HomePod, was a disappointment).\\\" Forte rates Sonos shares at buy with a $20 target price. The stock is up 37% so far this year as the S&P 500 has risen 23%, but it remains below its $15 initial-public-offering price from August 2018.\", \"Corporate tax avoidance demands a global solution The world should tax multinationals based on the destination of sales Multinational corporations have long avoided paying their full share of taxes, and time is running out to agree on a fair global solution.\", \"Apple Stock Is Up 65% This Year. More Gains Could Be Coming. The move has lifted the company\\u2019s market valuation by $450 billion, to $1.114 trillion. Bank of America Merrill Lynch says the move can continue.\", \"How the Saudi Aramco IPO Will Affect Other Oil Giants When the world\\u2019s largest oil producer goes public, it will surely mean a new dynamic for all the players in the oil industry.\", \"Apple expands privacy explanations on website, but actual policy remains unchanged The site updates are part of Apple\\u2019s push to distinguish itself from data-hungry rivals Google and Facebook The site updates are part of Apple\\u2019s push to distinguish itself from data-hungry rivals Google and Faceb\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 = 0.0276 (i.e., a 2.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0276 = 3.6198, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027626, "expected_loss": 0.027626, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170110_0635", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2017-01-10", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0179, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0002, std=0.0084, worst_day=-0.0219\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-01-09] [\"The Medicines Co LDL-Lowering Drug Positive in Phase II The Medicines CompanyMDCO announced positive top-line results from a Day 180 interim analysis of the ongoing ORION-1 phase II study on its pipeline candidate, Inclisiran (formerly PCSK9si), for the treatment of hypercholesterolemia. The Medicines Company is developing Inclisiran under a collaboration agreement with Alnylam Pharmaceuticals, Inc. ALNY , which was inked in early 2013. The Medicines Company is solely responsible for the development and commercialization of the candidate. The Medicines Company's three-month share price movement shows that the stock has outperformed the Zacks classified Medical - Biomedical and Genetics industry. Specifically, the company lost 1.7%, while the industry lost 3.7%. ORION-1 is a placebo-controlled, double-blinded, randomized, dose-finding phase II study. It compares and evaluates the effect of various doses of single or multiple subcutaneous injections of Inclisiran. The study was conducted in a total of 501 patients with atherosclerotic cardiovascular disease (ASCVD) or ASCVD-risk equivalents (hypercholesterolemia). Interim data demonstrated that Inclisiran led to a significant and durable reduction of LDL (low-density lipoprotein) cholesterol up to Day 210. Inclisiran was well tolerated throughout the study, with infrequent and mild or moderate injection site reactions. Data from the study will be presented at the annual meeting of the American College of Cardiology, scheduled to be held in Mar 2017. The company expects to move Inclisiran into phase III development (OROPN-4 study) after discussions with regulatory authorities. Meanwhile, the company announced the initiation of ORION-2 for evaluating the efficacy, safety and tolerability of Inclisiran in patients with homozygous familial hypercholesterolemia (HoFH). Moreover, the company commenced enrollment of ORION-1 patients in the phase II ORION-3 extension study, which will evaluate the efficacy, safety and tolerability of long-term dosing of Inclisiran. Note that, apart from Inclisiran, The Medicines Company has several interesting pipeline candidates targeting key focus areas. Three of these candidates - MDCO-216 (atherosclerotic plaque burden), ABP-700 (general anesthesia for surgical care) and Carbavance (treatment of hospitalized patients with serious gram-negative bacterial infections) - have blockbuster potential. The Medicines Company Price The Medicines Company Price | The Medicines Company Quote Zacks Rank & Other Key Picks The Medicines Company currently carries a Zacks Rank #2 (Buy). A couple of other favorably placed stocks in the health care sector include Orexigen Therapeutics, Inc. OREX and Arbutus Biopharma Corporation ABUS . Both the stocks sport a Zacks Rank #1 (Strong Buy). You can see the complete list of today's Zacks #1 Rank stocks here . Orexigen's loss estimates widened from $8.93 to $8.17 for 2016 and from $5.19 to $2.17 for 2017 over the last 60 days. The company pos\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 = 0.0179 (i.e., a 1.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0179 = 5.5981, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017863, "expected_loss": 0.017863, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150827_0638", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SLV"], "decision_date": "2015-08-27", "context_summary": "SLV: 60-day history, VaR(99%)=-0.0347, max drawdown threshold=10%.", "question": "Asset: SLV\nDaily returns (past 60 days): mean=-0.0025, std=0.0127, worst_day=-0.0374\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0347 (i.e., a 3.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0347 = 2.8818, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034701, "expected_loss": 0.034701, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20201111_0641", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2020-11-11", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0831, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0024, std=0.0442, worst_day=-0.1007\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0831 (i.e., a 8.31% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0831 = 1.2039, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.083062, "expected_loss": 0.083062, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210908_0644", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-09-08", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1295, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0068, std=0.0747, worst_day=-0.1762\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7719", "answer_numeric": 0.7719, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1295 (i.e., a 12.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1295 = 0.7719, capped at 1.0.\nMaximum position size = 0.7719 (77.2% of portfolio).", "metadata": {"var_99": -0.129543, "expected_loss": 0.129543, "max_drawdown_threshold": 0.1, "position_size": 0.7719, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220811_0647", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2022-08-11", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0411, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0021, std=0.0203, worst_day=-0.0411\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 = 0.0411 (i.e., a 4.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0411 = 2.4331, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.0411, "expected_loss": 0.0411, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190614_0650", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-06-14", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0642, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0080, std=0.0372, worst_day=-0.0686\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0642 (i.e., a 6.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0642 = 1.5585, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064165, "expected_loss": 0.064165, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160509_0653", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-05-09", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0158, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0015, std=0.0098, worst_day=-0.0166\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-06] FEYE Stock: FireEye Inc Tumbles, But It\u2019s Not Beat InvestorPlaceInvestorPlace - Stock Market News, Stock Advice & Trading Tips Heading into the first-quarter earnings report for FireEye Inc ( FEYE ), Wall Street analysts weren't short on worries \u2026 and it looks like that anxiety was warranted. Source: David via Flickr (Modified) FireEye is cratering this morning, off 14% after a pretty lousy report and a change in the C-suite. The biggest news of the day is that CEO David DeWalt is out - and stepping in will be company President Kevin Mandia, who founded Mandiant , which FireEye paid $1 billion to acquire back in 2014. Mandia will take the reins on June 15, and DeWalt will slip back to jsut being executive chairman. But the change in leadership isn't coming because all is hunky-dory. The financials from FireEye's Q1 report were far from encouraging. 7 Blue Chips That Are Getting Ugly in a Hurry An adjusted loss of 47 cents per share came in 3 cents ahead of expectations, and billings - a vital stat in the software space - came in at $186 million to easily best estimates for $176.2 million. But revenues were weak, at $168 million versus expectations of $171.7 million, and guidance didn't please anyone. FEYE expects Q2 sales to come in between $178 million to $185 million, with the entire range falling below analysts' estimate of $192.75 million. Those numbers also represent a deceleration in the growth path for FireEye. Yes, revenues were up 34% year-over-year \u2026 but that's far less than the 69% growth it saw in Q1 2015. Similarly, billings growth declined from 53% to 23%. A Bright Side to FEYE Stock? But that said, FEYE is a company in transition. It has been struggling to revamp its product line for the cloud, as well as to offer subscriptions to customers. And those are the right moves - they simply take time to pull off. Just ask Adobe Systems Incorporated ( ADBE ). Plus, FireEye is making some bold plays to make the transition successful, including acquiring firms such as iSight Partners and Invotas . What's more, Mandia may be the right person to lead the charge. I recently talked to Paul Kraus, founder and CEO of Eastwind Networks , who said: \"The board seems to believe he is a proven leader who can execute against FireEye's broader vision of monetizing its branded version of security-as-a service - FireEye-as-a-service or FaaS. \"Can Mandia propel FireEye to achieve its top-line revenue projections for FaaS? That will likely unfold over the coming quarters and remains to be seen. Cybersecurity is a hyper-crowded and rapidly evolving sector, and Mandia will have a clear charter to continue to focus on services, grab market share, and eventually turn a profit.\" Of course, that's an uphill climb, considering FireEye will be trying to grab that market share against companies like Palo Alto Networks Inc ( PANW ) and Cyberark Software Ltd ( CYBR ), as well as mega-tech firms like Cisco Systems, Inc. ( CSCO ) and International Business Machines Corp\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 = 0.0158 (i.e., a 1.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0158 = 6.3382, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015777, "expected_loss": 0.015777, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180131_0656", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2018-01-31", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.1754, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0282, std=0.1111, worst_day=-0.1754\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5701", "answer_numeric": 0.5701, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1754 (i.e., a 17.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1754 = 0.5701, capped at 1.0.\nMaximum position size = 0.5701 (57.0% of portfolio).", "metadata": {"var_99": -0.175402, "expected_loss": 0.175402, "max_drawdown_threshold": 0.1, "position_size": 0.5701, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20180130_0661", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2018-01-30", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0187, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0015, std=0.0072, worst_day=-0.0223\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-01-29] [\"Alibaba, Foxconn lead big investment in Chinese electric-car maker Tech companies branch out into burgeoning industry Chinese e-commerce giant Alibaba Group Holding Ltd. and Foxconn Technology Group have co-led a 2.2 billion yuan ($348 million) funding round into Chinese electric-vehicle manufacturer Xiaopeng Motors, marking Alibaba\\u2019s first big investment in a car maker\", \"Immersion enters settlement and license deal with Apple\", \"Immersion settles with Apple, reaches license agreements Immersion Corp. said Monday it has entered into settlement and license deals with Apple Inc. . Immersion, which develops touch feedback technology, had filed patent infringement lawsuits against Apple for technology used in iPhones and the trackpads used in MacBooks. Immersion said the terms of the agreements reached with Apple are confidential. The stock, which was still inactive in premarket trade, has tumbled 30% over the past 12 months, while the S&P 500 has gained 25%.\", \"Apple stock drops after report of iPhone X production cut Apple Inc. shares are down 0.5% in premarket trading Monday after a report in the Nikkei Asia Review said that the company planned to trim its iPhone X production target to 20 million for the March quarter, half of what it expected a few months ago. The Nikkei Asian Review attributes the production cut to lower-than-anticipated sales of the device. The phone's price tag of at least $999 could be a key reason for the demand issues, the publication said. Wall Street analysts have also been weighing in on the prospect of significantly weaker-than-expected iPhone X sales, with analysts at JP Morgan predicting last week that Apple would cut its build orders for the device by 50% in the March quarter, causing them to take a more cautious stance on a number of Apple suppliers. Apple shares are up 41% over the past 12 months, while the Dow Jones Industrial Average is up 30%.\", \"Robinhood\\u2019s crypto biz has drawn nearly 1 million in user interest: Watch out Coinbase! Coinbase is the No. 1\\u2013ranked U.S. crypto exchange platform over the past six months. Can Robinhood give it a run for its money in bitcoin, Ethereum trading? New-age brokerage platform Robinhood is jumping in on the cryptocurrency craze, declaring that it will allow trading in bitcoin and Ethereum\\u2019s currency starting in February, with more virtual currencies expected to be added soon.\", \"This \\u2018parabolic\\u2019 move for stocks has some investors nervous, but should it? Critical information for the U.S. trading day Is this bull market finally starting to feel a bit top-heavy? According to official MarketWatch records, this marks the 698th time that very question has been asked in this space since Trump took office.\", \"\\u2018Get Out\\u2019 is headed back to theaters after its 4 Oscar nominations \\u2018Get Out\\u2019 grossed $254.7 million at box offices worldwide on just a $4.5 million production budget It has been almost a year since \\u201cGet Out\\u201d opened i\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 = 0.0187 (i.e., a 1.87% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0187 = 5.3434, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018715, "expected_loss": 0.018715, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170224_0664", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2017-02-24", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0254, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0014, std=0.0090, worst_day=-0.0320\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-02-23] [\"Winners And Losers From Apple iPhone 8\\u2032s Super Cycle Not all components are created equal. As Apple (AAPL) starts to build iPhone 8, it will enhance certain features and ditch others.The biggest winners from iPhone 8 are the OLED suppliers; in this case, Samsung Electronics (SSNLF), and the biggest losers are the LCD suppliers, such as Sharp (6753.Japan) and Japan Display (6740.Japan). But Apple is also expected to ditch metal casing and go for glass casing, which is not good news for Catcher Technology (2474.Taiwan).\\\"Our research suggests that the key cost difference between i8 vs i7 are OLED panel, camera, wireless charging and speaker,\\\" according to Citi Research.READ MORE.\", \"Uber harassment scandal will hurt, but not in same way as #DeleteUber campaign Uber maintained lead on Lyft in daily downloads over holiday weekend, but employee recruitment will likely be affected Uber is facing another brand crisis, but experts say it\\u2019s unclear how much of an impact it will have on the ride-hailing service.\", \"Apple: We strongly believe that transgender students should be treated as equals\", \"Intel Could Shine in iPhone Next Year, Says Susquehanna Intel (INTC) could have a much stronger showing in Apple\\u2019s (AAPL) next iPhone, writes Susquehanna\\u2019s Christopher Rolland today, reiterating a \\u201cPositive\\u201d rating on the stock, and a $45 price target, thanks to new modem products that make it more competitive with wireless chip titan Qualcomm (QCOM).Citing the announcement this week by Intel, in advance of the Mobile World Congress show in Barcelona next week, of a new baseband modem, the \\u201cXMM 7560,\\u201d Rolland observes that Intel\\u2019s gains against Qualcomm in the iPhone 7 last year were despite the fact the existing part didn\\u2019t support the \\u201cCDMA\\u201d cellular technology, which this new one does.\\\"We believe CDMA support was a gating issue in winning the majority of iPhone 7 sockets as select global carriers require the standard (including Verizon and Sprint),\\u201d writes Rolland. \\\"Additionally, the inclusion of CDMA support may allow Intel to capture modem sockets at other OEMs in 2H17 and beyond.\\\"\", \"Garmin: All 12 Analysts, Still at a Hold, Doubt the Growth Outlook Shares of mobile and wearables pioneer Garmin (GRMN) are down $1.28, or 2.4%, at $52.87, giving up some gains after yesterday\\u2019s 7% jump following yesterday morning\\u2019s announcement of Q4 earnings that topped analysts expectations by a wide margin, and a forecast for this year\\u2019s revenue slightly higher than consensus.The quarter was marked by favorable sales trends for the company\\u2019s \\u201cFenix\\u201d activity tracker, and also a deal with BMW to supply infotainment parts for model year 2020 autos in China.Despite the beat, the skepticism is high from a number of analysts in the past 24 hours.\", \"Facebook is racking up the likes among the world\\u2019s biggest hedge funds Smart money loaded up on financials in the fourth quarte\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 = 0.0254 (i.e., a 2.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0254 = 3.9344, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025417, "expected_loss": 0.025417, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200806_0668", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2020-08-06", "context_summary": "MORT: 60-day history, VaR(99%)=-0.0446, max drawdown threshold=10%.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0030, std=0.0258, worst_day=-0.0446\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MORT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0446 (i.e., a 4.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0446 = 2.2411, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.044621, "expected_loss": 0.044621, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190924_0671", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-09-24", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0840, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0038, std=0.0407, worst_day=-0.0981\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0840 (i.e., a 8.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0840 = 1.1903, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.084014, "expected_loss": 0.084014, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190606_0674", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2019-06-06", "context_summary": "TLH: 60-day history, VaR(99%)=-0.0079, max drawdown threshold=10%.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=0.0009, std=0.0041, 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 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 = 0.0079 (i.e., a 0.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0079 = 12.6706, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.007892, "expected_loss": 0.007892, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20180119_0678", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2018-01-19", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0004, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0000, std=0.0002, worst_day=-0.0004\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 = 0.0004 (i.e., a 0.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0004 = 250.1990, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.0004, "expected_loss": 0.0004, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170308_0681", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2017-03-08", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0079, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0010, std=0.0041, worst_day=-0.0082\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-03-07] [\"LG Electronics Soars On Firm LCD Pricing, But Smartphone Business Drags LG Electronics (066570.Korea) soared 4.2% on Tuesday amid heavy buying after the latest LCD panel prices data alleviated market fears that the LCD panel cycle is peaking out soon.In the first week of March, LCD panel prices across different screen sizes stayed firm and the large-screen 65 inch TVs actually saw an increase in sales price.READ MORE.\", \"Go Long China, Short US: 5 Smart Stock Trades Concerns that U.S. stocks are overvalued may mean it\\u2019s time to buy their cheaper Chinese rivals.\", \"Most Investors Already Bullish On Apple\\u2019s iPhone 8: Any Upside Left? After meeting with over 150 investors globally, JP Morgan concluded that most investors are already on board with the Apple (AAPL) iPhone 8 super cycle trade.\\\"We agree that street expectations of ~100M units of new iPhone builds in 2H17 are now hard to exceed, but upside is likely to come from OLED iPhone mix and much higher ASPs. We have been advising investors to position into explicit OLED iPhone plays like Hon Hai, Samsung SDI or content gainers like WinSemi,LG Innotek and Lens Tech,\\\" reports JP Morgan.READ MORE.\", \"Which Tech Companies Will Win The Augmented Reality Race? Plenty of people have been wary of Snap Inc.'s (SNAP) worth as a social media company, but some may be buying the stock for its future as a camera company, and as a player in augmented reality (AR).Former Piper Jaffray analyst Gene Munster, who now works at AR and VR-focused venture capital firm writes that the question is broader than just Snap, however: With AR primed to come online in the next few years through existing operating systems, Munster has a new report out ranking how major tech players fare in the race to the new reality.\", \"House Republican Jason Chaffetz dangles Sophie\\u2019s choice: Your iPhone or your health? \\u2018Good morning to everyone except Jason Chaffetz\\u2019 Republicans unveiled new legislation this week to replace Obamacare and fix what President Trump describes as \\u201ca complete and total disaster.\\u201d Some sacrifices may be required, says Jason Chaffetz.\", \"Wall Street is at the very heart of American innovation: author Top politicians, says writer William D. Cohan, have bipolar relationships with Wall Street \\u2014 at best We need to understand Wall Street better, focusing not only on uncovering abuses but on the larger picture, placing even those probes into problem areas, which he said are often merited, into a broader context that includes Wall Street\\u2019s manifold services and innovations, argues William D. Cohan, author of \\u201cWhy Wall Street Matters.\\u201d\", \"Threat Of US Protectionism Not Fully Priced Into Tech Markets: Morgan Stanley Morgan Stanley\\u2019s Shawn Kim and team recently took a look at Asian technology companies, arguing that the risk of US protectionism isn\\u2019t fully priced into markets.They write that the tech sector is very exposed to the risk that policies will punis\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 = 0.0079 (i.e., a 0.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0079 = 12.7307, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.007855, "expected_loss": 0.007855, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210715_0684", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2021-07-15", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1761, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0045, std=0.0742, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5678", "answer_numeric": 0.5678, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1761 (i.e., a 17.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1761 = 0.5678, capped at 1.0.\nMaximum position size = 0.5678 (56.8% of portfolio).", "metadata": {"var_99": -0.17612, "expected_loss": 0.17612, "max_drawdown_threshold": 0.1, "position_size": 0.5678, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20181017_0687", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2018-10-17", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0260, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0001, std=0.0074, worst_day=-0.0324\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-16] [\"12 Stocks To Watch For October 16, 2018\", \"Barclays Maintains Overweight on Adobe, Raises Price Target to $304\", \"Adobe shares are trading higher after the company reaffirmed Q4 guidance and said it expects revenue to increase 20% in 2019.\", \"26 Stocks Moving In Tuesday's Pre-Market Session\", \"10 Biggest Price Target Changes For Tuesday\", \"40 Stocks Moving In Tuesday's Mid-Day Session\", \"40 Stocks Moving In Tuesday's Mid-Day Session\", \"10 Biggest Price Target Changes For Tuesday\", \"26 Stocks Moving In Tuesday's Pre-Market Session\", \"Adobe shares are trading higher after the company reaffirmed Q4 guidance and said it expects revenue to increase 20% in 2019.\", \"Barclays Maintains Overweight on Adobe, Raises Price Target to $304\", \"12 Stocks To Watch For October 16, 2018\", \"S&P 500 Movers: GWW, ADBE In early trading on Tuesday, shares of Adobe ( ADBE ) topped the list of the day's best performing components of the S&P 500 index, trading up 7.3%. Year to date, Adobe registers a 45.7% gain. And the worst performing S&P 500 component thus far on the day is W.W. Grainger ( GWW ), trading down 12.8%. W.W. Grainger is showing a gain of 17.3% looking at the year to date performance. Two other components making moves today are Blackrock ( BLK ), trading down 4.5%, and Progressive ( PGR ), trading up 5.0% on the day. VIDEO: S&P 500 Movers: GWW, ADBE The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Adobe Stock Is Floating in the Sunny Skies of the Cloud InvestorPlace - Stock Market News, Stock Advice & Trading Tips The chief benefits of open source go to the users. The cloud is a product of open source. I've been writing those two sentences, repeatedly, for over a decade now, and they're as true today as they ever were. Companies that fully embraced the economics of cloud have ridden it to glory. Few have done so as spectacularly as Adobe Systems (NASDAQ: ADBE ). By the standards of Silicon Valley it's old money, founded in 1982, its squat skyscraper a few blocks from the San Jose convention center. John Warnock and Charles Geschke founded Adobe around PC tools like PostScript and Photoshop. Shantanu Narayen re-invented the company by embracing the cloud and subscription as a service. Over the last five years the stock is up 342%, even with the recent tech wreck taking 13% out of the price. Clear Sailing Adobe said Oct. 15 it expects top-line growth of 20% next year, to $10.8 billion, well above previous analyst estimates , and the stock rose almost 6% in response . 10 Small-Caps With Straight-A Potential Both the recent fall and this rise are unsurprising. Even at its October 15 close of $238, Adobe was selling at an eye-popping 49 times earnings. The October 16 gains will send that even higher. But when you've got Amazon.Com (NASDAQ: AMZ\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 = 0.0260 (i.e., a 2.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0260 = 3.8481, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025987, "expected_loss": 0.025987, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181011_0690", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2018-10-11", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0546, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0202, worst_day=-0.0773\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0546 (i.e., a 5.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0546 = 1.8321, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.054581, "expected_loss": 0.054581, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220328_0693", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2022-03-28", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0242, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0012, std=0.0126, worst_day=-0.0309\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-03-25] [\"Europe says yes to messaging interoperability as it agrees major new regime for big tech Late Thursday the European Union secured agreement on the detail of a major competition reform that will see the most powerful, intermediating tech platforms subject to a set of up-front rules on how they can and cannot operate -- with the threat of fines of up to 10% of global annual turnover should they breach requirements (or even 20% for repeat violations). In three-way discussions between the European Council, parliament and Commission, which ran for around eight hours today, it was finally agreed that the Digital Markets Act (DMA) will apply to large companies providing \\\"core platform services\\\" -- such as social networks or search engines -- which have a market capitalisation of at least \\u20ac75 billion or an annual turnover of \\u20ac7.5 billion.\", \"European Union reaches provisional agreement on antitrust law targeting tech giants The European Union has reached an agreement to adopt the Digital Markets Act (DMA), a sweeping antitrust law meant to rein in Apple, Google, Meta and other tech giants.\", \"Europe agrees new law to curb Big Tech dominance Under the rules major firms like Apple and Google would have to open up their systems to rivals.\", \"Higher Education Market to grow by USD 45.11 billion | 37% growth to originate in North America | Technavio The global higher education market size is expected to increase by USD 45.11 billion between 2020 and 2025. The market observed a YOY growth of 13.40% in 2021 and the growth momentum is expected to accelerate at a CAGR of 13.84% during the forecast period. The report offers accurate predictions on the future market scenarios, YOY growth rates through 2025, and the trends and drivers impacting the growth of the market.\", \"Darktrace AI Stops Sophisticated Phishing Attacks at Brazilian Manufacturing Giant Darktrace, a global leader in cyber security AI, today announced that its AI-powered email security technology, Antigena Email, successfully stopped a series of phishing attacks targeting a global manufacturing organization in Brazil.\", \"Apple's 10.2-inch iPad with 256GB storage falls to a new Amazon low Apple's 2021 256GB 10.2-inch iPad is already a solid deal at $479, but you can now pick one up at an all-time low of $429.\", \"10 Things in Tech: iPhone subscriptions In today's edition: Tim Cook is expected to attend the Oscars, and Apple is considering creating a subscription service for iPhones.\", \"The Morning After: The inventor of the GIF has died Today\\u2019s tech headlines: Google says it thwarted North Korean cyberattacks in early 2022, Apple may be planning an iPhone hardware subscription service, Google seeks FDA approval for Fitbit's passive heart rate monitoring tech.\", \"US and EU aim to revive transatlantic data flows in new privacy deal President Biden said the preliminary agreement will 'enhance the Privacy Shield framework.'\", \"Engadget Podcast: Apple\\u2019s confounding Studio Display an\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 = 0.0242 (i.e., a 2.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0242 = 4.1286, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024221, "expected_loss": 0.024221, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160428_0698", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2016-04-28", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0293, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0015, std=0.0129, worst_day=-0.0310\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-04-27] [\"TSMC Will Meet Its Sales Target Despite Apple\\u2019s Fiscal Q2 Miss: Bernstein Bernstein Research cut its second-quarter revenue forecast for Apple's foundry provider Taiwan Semiconductor Manufacturing Corp., TSMC (2330.Taiwan/TSM) after Apple (AAPL) said it would cut $2 billion inventory. But TSMC will meet its 2016 revenue growth target of 5-10%, according to Bernstein.The last time Apple had a large cut in channel inventory was a year ago and it was only \\\"a bit less than $800 million\\\", said Apple. For details (a lot of it), check out my Barron's colleague Tiernan Ray's blog \\\"Apple Cutting $2B of Inventory Given Macro Environment\\\".READ MORE.\", \"Which Suppliers Are Most Vulnerable To Apple\\u2019s $2B Inventory Cut?\", \"What \\u2018margin of safety\\u2019 means for Netflix shares When managing your portfolio, you always have to consider the risk of owning an individual security, sometimes that\\u2019s not a big deal, but other times, you need to look at immediate risk and discuss whether or not it\\u2019s safe to continue to own those shares.\", \"Small-Cap Stocks Back? Charts Suggest They Are Right now, small- and medium-cap shares have stronger technicals than their large-cap cousins.\", \"The Case Against Apple Though Barron\\u2019s sees brighter days for the stock, Fortune thinks the news will get worse.\", \"Apple slumps 7% premarket after earnings miss\", \"Apple shares in Frankfurt trade drop 7.3%\", \"Apple stock price target cut to $153 from $172 at Piper Jaffray\", \"Apple's bullish thesis little changed despite disappointing Q2 results--Piper Jaffray\", \"Apple hints at big acquisition to cure growth ills Tim Cook says Apple willing to spend more than previous record To cure Apple\\u2019s growth problems, Chief Executive Tim Cook suggested Tuesday he may go shopping.\", \"Here are reasons to doubt the comeback by value stocks Not yet a \\u2018sustainable trend reversal\\u2019 Value stocks are leaving growth behind in what may be a long overdue turnaround. But one analyst has big doubts about whether the investing style will continue to prevail.\", \"Here\\u2019s what Apple\\u2019s horrible quarter means for the company in the long term \\u2018We look beyond the current cycle,\\u2019 Mizuho analysts say As Apple shares drop in premarket trading Wednesday after the iPhone maker\\u2019s disappointing earnings, analysts come to the company\\u2019s defense.\", \"Apple's stock tumble can be blamed for Dow futures' drop Apple Inc.'s stock tumbled 8.2% in premarket trade Wednesday, putting them on track to open at a two-month low, after the technology giant reported disappointing quarterly results. The stock's price decline of $8.60 would shave about 59 points off the Dow Jones Industrial Average , which is a price-weighted index. Dow futures were down 40 points ahead of the open.\", \"How Apple could wipe 60 points off the Dow Apple\\u2019s after-hours plunge would push the Dow about 60 points lower Apple Inc.\\u2019s disappointing corporate results late Tuesday may be a bad\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 = 0.0293 (i.e., a 2.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0293 = 3.4098, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029328, "expected_loss": 0.029328, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20211103_0702", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-11-03", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1779, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0096, std=0.0714, worst_day=-0.1890\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-11-02] \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": "0.5623", "answer_numeric": 0.5623, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1779 (i.e., a 17.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1779 = 0.5623, capped at 1.0.\nMaximum position size = 0.5623 (56.2% of portfolio).", "metadata": {"var_99": -0.177855, "expected_loss": 0.177855, "max_drawdown_threshold": 0.1, "position_size": 0.5623, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20210720_0704", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2021-07-20", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0137, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0006, std=0.0059, worst_day=-0.0166\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-07-19] This Segment of Tech Stocks Will Outpace the Rest Over the Next 4 Years Technology stocks have been the must-own sector for more than a couple of decades now. That's not apt to change in the foreseeable future either. If you think one technology stock is as good as another though, think again. They can be dramatically different when it comes to growth prospects, and enterprise software companies like Microsoft (NASDAQ: MSFT) and ServiceNow (NYSE: NOW) are poised to outgrow other tech names for the foreseeable future. That's the call from technology market research outfit Gartner (NYSE: IT) anyway, which recently posted its long-term IT spending outlook. The organization believes global tech spending will improve by 9% year over year in 2021, led by more than a 13% swell in software outlays. Unlike other technology arenas, however, enterprise software sales will remain abnormally brisk through 2025. Investors should make a point of holding exposure to this sliver of the tech sector during this time. Image source: Getty Images. Better than the rest All of the technology sector's key industries should benefit from IT spending growth this year, for the record, and this widespread progress is expected to persist through 2022. The rising tide isn't expected to lift all boats equally, however. The graphic below puts things in perspective. Services of all sorts will see steady growth through 2025, according to Gartner, and data center systems and device manufacturers are apt to fare even better. The standout area, however, is clearly enterprise software. Gartner estimates software spending will grow at a double-digit percentage pace every year through 2025. In fact, it will be the technology sector's only segment to achieve double-digit growth in any year except for this year's expected 13.9% growth in spending on devices, which is exaggerated this year due to last year's decline. Data source: Gartner Inc. Chart by author. And in case you're wondering, infrastructure software spending is projected to lead the way, albeit just barely. Spending on enterprise-level apps, or computer programs, should see almost as much growth, suggesting software spending plans are well balanced. Best of the best The stage may be set for growth, but which software stocks will make for the most productive picks? One of the most obvious beneficiaries of this projected growth is, of course, Microsoft. It's hardly a pure play, with offerings ranging from operating systems to video gaming to personal productivity to cloud computing. Its Intelligent Cloud division is now the company's single-biggest operating unit though, accounting for $15.1 billion of last quarter's revenue of $41.7 billion. Its cloud-management interface Azure saw a 46% year-over-year improvement in revenue, as enterprises embrace highly capable off-the-shelf solutions. Market researcher Canalys estimates Microsoft leveraged Azure to end Q1 with 19% of the world's cloud infrastructure spending market share, up \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 = 0.0137 (i.e., a 1.37% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0137 = 7.3201, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013661, "expected_loss": 0.013661, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190718_0705", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2019-07-18", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0152, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0010, std=0.0069, worst_day=-0.0165\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-17] [\"Netflix Reports Earnings Today. Here\\u2019s What to Expect. Management will likely face questions about competition from other media companies\\u2019 upcoming streaming services.\", \"Software Stocks Hit Record Valuations Just in Time for Earnings Season Software isn\\u2019t just \\u2018eating the world,\\u2019 but also huge swaths of investor portfolios.\", \"Amazon probed in Europe over third-party selling Amazon.com Inc. will face a formal European Union antitrust investigation into its dealings with third-party merchants, expanding a multipronged regulatory push that has ensnared other big Silicon Valley giants like Facebook Inc. and Alphabet Inc.\\u2019s Google.\", \"Walmart CEO McMillon says the retailer has been playing \\u2018catch up\\u2019 in e-commerce McMillon says customers want the convenience that Amazon and other e-commerce companies provide Walmart Chief Executive Doug McMillon discussed the retail giant\\u2019s digital progress and the competition, including Amazon.\", \"Amazon members bought more than 175 mln items during Prime Day event\", \"Amazon Prime Day was largest shopping event in co.'s history\", \"Amazon Prime Day top selling deals included Echo Dot, Fire TV Stock\", \"Amazon sees most-ever Prime member signups on July 15\", \"Amazon's stock edges up 0.1% in premarket trading\", \"Amazon Prime Day sales surpass Black Friday and Cyber Monday combined Amazon.com Inc. said Wednesday that this year's two-day Prime Day shopping event was the biggest shopping event in the company's history, surpassing Black Friday and Cyber Monday combined. More than 175 million items were purchased, with the event becoming the largest-ever for Amazon devices, including the Echo Dot and Fire TV Stick with Alexa Voice Remote. Prime members also bought 100,000 lunchboxes, 100,000 laptops, 350,000 luxury beauty products, and more than one million toys. Amazon says Prime members around the world saved more than $1 billion. Eighteen countries participated this year. And Amazon reports it signed up the most new Prime members ever on July 15 and nearly as many on July 16. Amazon stock has gained 33.6% in 2019 while the S&P 500 index is up nearly 20% for the period.\", \"Amazon Says Prime Day Was the Greatest Event in the History of Mankind The company uses a lot of superlatives without ever actually saying anything substantive about total sales for the event, or how they compared with previous Prime Days on a computational level.\", \"Microsoft earnings: Trillion-dollar valuation is banking on continuing cloud growth One analyst sees cloud accounting for 60% of Microsoft\\u2019s revenue in six years Growth of Microsoft Corp.\\u2019s cloud service Azure will be key in determining whether the software giant maintains its leading trillion-dollar market cap after its earnings report.\", \"China Is a Bigger Problem for the Global Economy Than You Think, Rupal Bhansali Says Rupal Bhansali, a Barron\\u2019s Roundtable panelist and the chief investment officer at Ariel Investments, says \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 = 0.0152 (i.e., a 1.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0152 = 6.5620, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015239, "expected_loss": 0.015239, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210701_0707", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2021-07-01", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0237, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0004, std=0.0104, worst_day=-0.0255\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-06-30] [\"Ably raises $70 million for its developer platform that enables realtime features Ably is a Pub/Sub messaging platform that companies can use to develop realtime features in their products. The company just raised a $70 million Series B funding round co-led by Insight Partners and Dawn Capital. A popular system that lets you create realtime features is called Pub/Sub, as in publish-subscribe.\", \"LG's 'QNED' Mini LED TVs are coming to the US in July LG's lineup of QNED 4K and 8K TVs unveiled late last year will arrive in the US in July, the company has announced.\", \"Amazon\\u2019s Halo app gets better with Movement Health update Amazon is rolling out its smartphone camera-driven service called Movement Health, which it announced earlier this month.\", \"Microsoft says a third of its government data requests have secrecy orders Microsoft's customer security chief says as many as one-third of all government demands that the company receives for customer data are issued with secrecy clauses that prevents it from disclosing the search to the subject of the warrant. The figure was disclosed in testimony by Microsoft's Tom Burt ahead of a House Judiciary Committee on Wednesday, as lawmakers weigh a legislative response to efforts by the Justice Department under the Trump administration to secretly obtain call and email records as part of an investigation into the leaks of classified information to reporters at The New York Times, The Washington Post, and CNN. Burt said that such secrecy orders \\\"have unfortunately become commonplace,\\\" and that Microsoft regularly receives \\\"boilerplate secrecy orders unsupported by any meaningful legal or factual analysis.\\\"\", \"Apple\\u2019s developer problems are much bigger than Epic and \\u2018Fortnite\\u2019 The Epic v. Apple trial exacerbated the company's developer relations problem, and it could still get worse.\", \"Facebook\\u2019s early antitrust win doesn't let it or Big Tech off the hook Facebook may have scored and early win in its antitrust battle with the FTC, but the war is far from over for the social networking giant, or the rest of Big Tech.\", \"The iOS 15, iPadOS 15 and watchOS 8 public betas are here The iOS 15 public beta is rolling out today. Here's how to get it.\", \"iOS 15 beta hands-on: A surprisingly complete preview iOS 15 features like SharePlay, Focus modes and Live Text are ready for testing.\", \"AT&T will soon enable RCS messaging for all Android phones Google Messages will be the default chat app for AT&T customers.\", \"watchOS 8 beta hands-on: Subtle but useful changes The watchOS 8 public beta might not be as big a change as iOS 15, but it still promises better integration with your iPhone, along with health and fitness updates.\", \"Lego should snap up this rapid-fire brick-finding iOS app Lego has worked extremely closely with Apple over the years, experimenting with unreleased iOS tech and demoing it onstage at launch events like WWDC; this has included some pretty heavy tinkering on the augmen\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 = 0.0237 (i.e., a 2.37% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0237 = 4.2109, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023748, "expected_loss": 0.023748, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190122_0709", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-01-22", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0961, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0435, worst_day=-0.1073\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0961 (i.e., a 9.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0961 = 1.0407, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.096089, "expected_loss": 0.096089, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210215_0711", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2021-02-15", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0016, std=0.0103, worst_day=-0.0313\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-02-12] [\"Which is better, the 2021 Toyota RAV4 or the 2021 Honda CR-V? The Toyota RAV4 and Honda CR-V are two popular, reliable, compact crossovers. Let's compare them side by side.\", \"Disney earnings: Surge by Disney+ to nearly 95 million subscriptions leads to surprise profit Walt Disney Co.'s streaming service, Disney+, proved again to be a big plus during a pandemic that has all but shuttered the Magic Kingdom's other businesses. And that has company shares up 3% in after-hours trading Thursday.\", \"Tesla is on this list of 20 S&P 500 companies that have produced the biggest sales increases along with pricing power The companies showed double-digit sales increases and expanded gross profit margins.\", \"Apple's stock falls 0.5% toward 4th straight decline\", \"My wild ride owning GameStop stock Why it's been easy to own a volatile stock and still keep my cool\", \"Antelope Enterprise Holdings Ltd. Announces Pricing Of Registered Direct Public Offering Antelope Enterprise Holdings Ltd. (f/k/a China Ceramics Co., Ltd.) (NASDAQ Capital Market: AEHL) (the \\\"Company\\\"), a leading Chinese manufacturer of ceramic tiles used for exterior siding and for interior flooring and design in residential and commercial buildings, today announced that it has entered into a definitive agreement with three institutional investors for a registered direct offering of securities with gross proceeds of approximately $2.1 million, before payment of commissions and expenses. The closing of the offering is expected to take place on or about February 17, 2021, subject to the satisfaction of customary closing conditions.\", \"Brookdale Launches \\\"Cheer a Hero\\\" Challenge to Cheer On Senior Living Workers Brookdale Senior Living is launching the \\\"Cheer a Hero\\\" letter challenge to support and encourage senior living associates throughout the United States. Brookdale, which has more than 720 communities across the country (as of December 21, 2020), is aiming to raise awareness and cheer for those individuals working in senior living/nursing home communities. You can \\\"Cheer a Hero\\\" in your hometown by posting to social media and using the hashtag \\\"#cheerahero,\\\" writing a letter or downloading this template to send a note to the staff of a senior living facility in your area or a Brookdale community near you.\", \"Garibaldi Intercepts Multiple Gold Bearing Veins & Silicified Units at Newly Discovered Casper Hydrothermal System Garibaldi Resources (TSXV: GGI) (the \\\"Company\\\" or \\\"Garibaldi\\\") is pleased to announce assay results from four shallow diamond drill holes totaling 639.5m, the first ever testing the new Casper Quartz Gold Vein System. The Casper discovery is located 12 km northwest of the Company's flagship E&L nickel-copper-cobalt massive sulphide project at Nickel Mountain, and 14 km west of Garibaldi's premier Eskay North gold prospect, bordering the historic Eskay Creek mine, now being redeveloped.\", \"Global Patient Monitoring Devices Market Report 2020-2027: Availability o\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 = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7360, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026767, "expected_loss": 0.026767, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180801_0713", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["TIP"], "decision_date": "2018-08-01", "context_summary": "TIP: 60-day history, VaR(99%)=-0.0015, max drawdown threshold=10%.", "question": "Asset: TIP\nDaily returns (past 60 days): mean=0.0001, std=0.0007, worst_day=-0.0016\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 = 0.0015 (i.e., a 0.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0015 = 66.9937, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.001493, "expected_loss": 0.001493, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20221021_0715", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2022-10-21", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0875, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0034, std=0.0305, worst_day=-0.0875\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-10-20] \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 = 0.0875 (i.e., a 8.75% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0875 = 1.1433, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.087465, "expected_loss": 0.087465, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20171115_0717", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2017-11-15", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0107, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0017, std=0.0051, worst_day=-0.0126\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-11-14] [\"Amazon selling its cloud-computing business in China Beijing Sinnet Technology says it\\u2019s buying unit for up to $300 million Amazon.com Inc.\\u2019s cloud-computing service is throwing in the towel in China.\", \"Developer gets death threats from fans annoyed with new Star Wars videogame EA\\u2019s response hailed as \\u2018the most downvoted comment of all time\\u2019 Electronic Arts has received plenty of backlash from gamers ahead of its release of Star Wars: Battlefront II, due out on Friday, and it\\u2019s response isn\\u2019t helping at all.\", \"The $1.5 trillion problem is making the U.S. stock market jittery Tax cuts could be a catalyst for stocks, but the final tally is unknown Tax cuts could be a catalyst for stocks, but the final tally is unknown, says Nigam Arora.\", \"The man who gave us the DVR says Roku is the future of TV CEO says Roku gives him the ability to do what he has always wanted: Build a new home for TV fans Anthony Wood has spent his career changing how we watch television, and says he has always had one goal: Offer a single destination for video. He believes that destination will be Roku, the company he developed at Netflix after learning lessons from his TV game-changer, the digital video recorder.\", \"Riding Amazon to New Heights How T. Rowe Price Media & Telecommunications is beating virtually all of its peers.\", \"Apple's stock in danger of 4th straight fall, but RBC sees multiple earnings 'tailwinds' A sharp increase in Apple Inc.'s off-balance-sheet manufacturing and purchase commitments to a record $37.6 billion in fiscal 2017, up 31% from a year ago, potentially indicate a strong ramp for iPhone X, according to RBC Capital analyst Amit Daryanani. After an analysis of Apple's audited annual report filed with the Securities and Exchange Commission, Daryanani said the 8% decline in warranty accruals was \\\"logical\\\" given the iPhone X delay; a slight decline in operating margins in the U.S. reflect carrier discounts on new phones; and the 31% rise in vendor non-trade receivables reflect component purchases by Apple for manufacturing licensee partners and overall inventory on Apple's balance sheet. Daryanani reiterated his outperform rating and $190 stock-price target, citing \\\"multiple tailwinds\\\" for EPS growth, including higher average selling prices for iPhone X, improved gross margins and potential tax reform. The stock slipped 0.8% in morning trade, which puts it on track for a fourth straight decline since it closed at a record $176.24 on Nov. 8. The stock has climbed 8.1% over the past three months, while the tech-heavy Nasdaq 100 has rallied 6.3% and the Dow Jones Industrial Average has gained 6.0%. (This updates a previous item that incorrectly reported a rise in \\\"nonreceivables\\\" rather than \\\"non-trade receivables.\\\")\", \"Apple\\u2019s iPhone X Production Problems Could Last Into \\u201918, Says Mizuho Apple is still struggling with \\\"yields\\\" of its 3-D sensing function in the iPhone X, claims Mizuho's Abhey Lam\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 = 0.0107 (i.e., a 1.07% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0107 = 9.3293, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010719, "expected_loss": 0.010719, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170901_0719", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2017-09-01", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0174, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0013, std=0.0076, worst_day=-0.0240\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-08-31] [\"3 Must Read Stories: Trump Blasts North Korea, Apple\\u2019s Market Cap Approaches $1 Trillion, Alibaba Pictures\", \"Toshiba continues chip-unit negotiations with three potential buyers Toshiba Corp. said late Wednesday that it is in ongoing negotiations with three potential buyers for its memory chip unit. In a statement, Toshiba said the suitors include a consortium led by Bain Capital and, reportedly, Apple Inc.; a consortium that includes Western Digital Corp. ; and a consortium that includes Hon Hai Precision Industry Co. , aka Foxconn. While Toshiba originally sought an Aug. 31 deadline to sell its chip unit, the company said negotiations have not yet reached a point where the board is ready to agree to a sale. Toshiba is seeking to sell its chip unit to raise capital, reportedly around $18 billion, following massive losses by its U.S. nuclear subsidiary, Westinghouse Electric Co., which filed for bankruptcy earlier this year.\", \"Apple\\u2019s new iPhone expected to lead to $180 billion in smartphone sales IDC predicts Android will continue to command majority of smartphone market, but Apple will take big money Though Apple Inc.\\u2019s iPhones may lag Android devices in terms of market share, Apple is expected to bring in $180 billion from its smartphones alone by 2021, according to a report from market intelligence firm IDC.\", \"Google-parent Alphabet may be key to this stock-market rally Critical information for the U.S. trading day September has been billed as a rough month for stocks, but the tech overlords may have something to say about that. A sparkle seems to be returning for that sector as a grind of a month comes to a close.\", \"Apple Should Throw in Some Freebies with That Pricey iPhone, Says Barclays Apple might want to think about bundling some freebies with its next iPhone, which is purported to cost, at the high end, $1,000 or more, says Barclays analyst Mark Moskowitz. He sees free stuff like an Apple Music subscription helping some consumers swallow a higher price and therefore potentially helping Apple boost iPhone revenue.\", \"Apple sends invite to expected iPhone event: reports\", \"Apple confirms expected iPhone event at 'Steve Jobs Theater' Apple Inc. invited media members Thursday to its new campus and theater named after co-founder Steve Jobs for a Sept. 12 event that is expected to include the introduction of a highly anticipated new iPhone, according to multiple media reports. \\\"Let's meet at our place,\\\" the invitation, shared on Twitter by multiple reporters, reads. \\\"Please join us for the first ever event at the new Steve Jobs Theater in Cupertino.\\\" The Steve Jobs Theater is part of Apple's new \\\"Spaceship\\\" campus that will be the new headquarters for the world's most valuable company. At the event, Apple is expected to introduce new iPhones on the tenth anniversary of the introduction of the original iconic Apple smartphone. Most anticipation focuses on a new, super-premium version of the phone that is expected to\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 = 0.0174 (i.e., a 1.74% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0174 = 5.7403, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017421, "expected_loss": 0.017421, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220623_0721", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2022-06-23", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0438, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0004, std=0.0246, worst_day=-0.0438\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-22] [\"Market Sell-Off: 1 Tech Stock to Buy Hand Over Fist Right Now Shares of contract electronics manufacturer Jabil (NYSE: JBL) were clobbered following the release of the company's fiscal 2022 third-quarter earnings report on May 16. The stock fell 10% in a single session as investors were spooked about the possibility of a slowdown in the demand for its offerings. Jabil reported healthy growth despite the supply chain issues plaguing the semiconductor industry. But management's comments on the latest earnings call regarding a potential weakness in demand due to economic slowdowns led investors to press the panic button. However, a closer look at Jabil's latest results and guidance indicates that investors may be overreacting. Jabil crushed expectations and raised its guidance once again Jabil delivered fiscal Q3 revenue of $8.3 billion, an increase of 15% over the prior-year period. Its adjusted earnings increased 32% year over year to $1.72 per share last quarter. Wall Street was looking for $1.62 per share in earnings on $8.22 billion in revenue from Jabil, but strong growth in the company's electronics manufacturing services (EMS) segment helped it crush expectations. Jabil's EMS business produced 54% of its top line and posted 23% year-over-year growth, driven by fast-growing end markets such as industrial and semiconductor capital equipment, 5G wireless, cloud computing, digital printing, and retail. The diversified manufacturing services (DMS) segment registered a 7% year-over-year increase in revenue despite headwinds in certain areas. Jabil pointed out that the automotive, mobility, and healthcare packaging markets witnessed healthy demand. More importantly, Jabil CFO Mike Dastoor said on the earnings call: \\\"Across the majority of our end markets, demand has been extremely resilient and continues to outstrip supply across our business, particularly in end markets that continue to benefit from strong secular tailwinds, markets such as electric vehicles, personalized medicine and healthcare, clean and smart energy infrastructure, 5G infrastructure, cloud, and semi-cap.\\\" Dastoor adds that these markets account for a large chunk of Jabil's portfolio, and \\\"sustained growth in these markets will continue, even if overall global economic growth slows from the solid levels over the last few years.\\\" Jabil management's confidence in healthy end-market demand reflects in the company's guidance, which was upgraded once again. The company now expects $32.8 billion in revenue this year along with adjusted earnings of $7.45 per share. For comparison, Jabil had guided for $6.35 per share in earnings on $31.5 billion in revenue at the beginning of the fiscal year. The improved guidance isn't surprising as Jabil headed into its quarterly report with multiple growth drivers, including the sunny prospects of its largest customer Apple (NASDAQ: AAPL). Jabil's current annual guidance points toward a 12% year-over-year increase in revenue, while fiscal 2022\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 = 0.0438 (i.e., a 4.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0438 = 2.2811, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.043839, "expected_loss": 0.043839, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200709_0723", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2020-07-09", "context_summary": "BIL: 60-day history, VaR(99%)=-0.0002, max drawdown threshold=10%.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=-0.0000, std=0.0001, 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 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 = 0.0002 (i.e., a 0.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0002 = 457.7642, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000218, "expected_loss": 0.000218, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190726_0725", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2019-07-26", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0214, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0005, std=0.0088, worst_day=-0.0302\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-25] [\"Asian markets little changed as investors await central bank decisions Stocks in Japan, Hong Kong rise slightly Asian markets were little changed in early trading Thursday, despite new record highs on Wall Street.\", \"Microsoft and 7 Other Tech Stocks That Yield Steady Payouts Technology stocks aren\\u2019t traditional dividend havens the way utilities, consumer staples, and other sectors have been. But that\\u2019s shifting as companies such as Microsoft, Apple, Cisco, and others operate mature businesses that throw off excess cash.\", \"Why App Stores Could Be an Early Target of Regulators Apple and Google take 30% on revenue generated from their app stores. That could be one area of interest as the Justice Department reviews online platforms.\", \"This GMO Strategist Is Bearish on U.S. Stocks but Positive on Modern Monetary Theory James Montier likes emerging markets, cites Monty Python, and is critical of Larry Summers\", \"Voice assistants gain new skills \\u2014 texting us, showing us graphics Multimodal responses to voice commands will make consumers more comfortable with artificial intelligence Multimodal responses to voice commands will make consumers more comfortable with artificial intelligence.\", \"U.S. government\\u2019s broadside against Big Tech could cause the stock rally to stumble Large technology companies have been the stock market leaders Large technology companies have been the stock market leaders.\", \"Big Tech could have avoided this antitrust mess with the stroke of a pen Humble advice to Alphabet, Amazon, Facebook and Apple: Get out your checkbooks Humble advice to Alphabet, Amazon, Facebook and Apple: Get out your checkbooks.\", \"Southwest takes drastic action to address 737 Max issues and stock is rewarded Earnings Watch: Alphabet and Amazon lurk on deck as antitrust interest heats up Air carriers have spent the past two weeks giving updates on the continued Boeing 737 Max groundings, and Southwest Airlines Co. just announced the most drastic plan so far.\", \"OK Google, tell us why your earnings growth is slowing down ... hello? Anyone there? Alphabet executives avoided discussing growth slowdown in last earnings report, and numbers don\\u2019t tell much of a story either As the parent company of Google nears its fiscal second quarter results on July 25, the chorus of disapproval over its evasive reporting policy has risen on Wall Street.\", \"A worrying theory after Equifax and Facebook settlements \\u2014 aggregated data is NOT enough to protect your privacy A new study says it\\u2019s possible to \\u2018reverse engineer\\u2019 anonymous data to identify individuals A new study says it\\u2019s possible to \\u2018reverse engineer\\u2019 anonymous data to identify individuals.\", \"Apple to acquire majority of Intel smartphone business for $1 billion\", \"Trump prods Republicans to back budget deal as he hails worker-pledge anniversary CEOs from Lockheed, Siemens join president at White House event President Donald Trump on Thursday urged House \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 = 0.0214 (i.e., a 2.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0214 = 4.6730, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021399, "expected_loss": 0.021399, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180316_0727", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2018-03-16", "context_summary": "BNDX: 60-day history, VaR(99%)=-0.0020, max drawdown threshold=10%.", "question": "Asset: BNDX\nDaily returns (past 60 days): mean=0.0001, std=0.0012, worst_day=-0.0022\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNDX, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0020 (i.e., a 0.20% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0020 = 50.1620, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.001994, "expected_loss": 0.001994, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190801_0729", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-08-01", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.1312, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0043, std=0.0526, worst_day=-0.1328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7621", "answer_numeric": 0.7621, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1312 (i.e., a 13.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1312 = 0.7621, capped at 1.0.\nMaximum position size = 0.7621 (76.2% of portfolio).", "metadata": {"var_99": -0.131222, "expected_loss": 0.131222, "max_drawdown_threshold": 0.1, "position_size": 0.7621, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160406_0731", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2016-04-06", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0157, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0013, std=0.0082, worst_day=-0.0159\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-04-05] [\"Apple is about to get a lot more of your money Average user predicted to top $100 on services like Apple Music by 2020, an 85% gain Apple\\u2019s customers will nearly double their spending on the company\\u2019s services offerings, such as Apple Pay and Apple Music, in the coming years, an analyst predicted Monday, meaning billions more in profit for the iPhone maker.\", \"The only three ETFs you need to own now These funds pursue outperformance without taking on too much risk These funds pursue outperformance without taking on too much risk, writes Jeff Reeves.\", \"Apple: Investors Unconcerned About Potentail EU Tax Bill, Says Piper\", \"Intel Production Improves in Late March, Says BlueFin; 30% iPhone Share on Track Boutique research house BlueFin Research Partners\\u2019s Steve Mullane writes today that Intel\\u2019s (INTC) production levels for its chips at the end of March began to pick up, indicating some improvement in the supply chain inventory clearing, despite still-weak personal computer shipments.Mullane, without citing sources, claims that Intel\\u2019s production in the last two weeks of March indicates a less-bad decline in production for Q1, and some momentum heading into Q2, the result of the global chip industry burning through inventory:In our Intel Update last month, we noted that the overall production levels at Intel were noticeably slowing down in February and dropping further through mid-March. These declines put the production level estimates on a pace of 5-6% sequential decrease for Q1, versus the flattish forecast to the materials suppliers at the outset of the quarter. The production declines were not totally surprising, given the lackluster PC shipments in January and February and the high inventory levels entering the quarter. Our latest estimates indicate that production levels bottomed in mid-March and have showed some modest improvement in the past few weeks. We estimate that Q1 production declined 4-5% sequentially, slightly better than the 5-6% decline projected in our prior update. The increased momentum at the end of March appears to be carrying over into Q2, as the material suppliers are forecasting a 5% sequential increase. Figure 1 depicts our production level estimates versus actual and forecasted INTC revenues. After two quarters of production declines, we are finally seeing a production increase for the June quarter which suggests that inventory are getting closer to target levels. While our latest reads on the PC Shipments (see our PC Market Update note yesterday) are projected to be up only slightly at 65M units in Q2, Skylake builds are expected to increase to 50% of the mix.\", \"Bull trend intact, U.S. benchmarks hesitate at major resistance Focus: Apple presses the 200-day average, AAPL, SIMO, MRK,FN, HIMX Technically speaking, each widely-tracked U.S. benchmark has reached its next major hurdle to start the second quarter. Against this backdrop, the selling pressure at resistance is worth tracking, though \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 = 0.0157 (i.e., a 1.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0157 = 6.3537, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015739, "expected_loss": 0.015739, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201211_0734", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2020-12-11", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1355, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0145, std=0.0760, worst_day=-0.1612\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7383", "answer_numeric": 0.7383, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1355 (i.e., a 13.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1355 = 0.7383, capped at 1.0.\nMaximum position size = 0.7383 (73.8% of portfolio).", "metadata": {"var_99": -0.135453, "expected_loss": 0.135453, "max_drawdown_threshold": 0.1, "position_size": 0.7383, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170403_0736", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2017-04-03", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0139, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0012, std=0.0082, worst_day=-0.0158\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 = 0.0139 (i.e., a 1.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0139 = 7.2070, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013875, "expected_loss": 0.013875, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160624_0738", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2016-06-24", "context_summary": "MORT: 60-day history, VaR(99%)=-0.0192, max drawdown threshold=10%.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0010, std=0.0077, worst_day=-0.0282\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MORT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; 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 = 5.1996, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019232, "expected_loss": 0.019232, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20191218_0740", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-12-18", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0816, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0053, std=0.0313, worst_day=-0.0824\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0816 (i.e., a 8.16% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0816 = 1.2257, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.081589, "expected_loss": 0.081589, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200224_0742", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2020-02-24", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0152, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0014, std=0.0067, worst_day=-0.0154\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-02-21] [\"Notable ETF Inflow Detected - MGK, ADBE, MCD, UNP Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel, one standout is the Vanguard Mega Cap Growth ETF (Symbol: MGK) where we have detected an approximate $193.1 million dollar inflow -- that's a 3.4% increase week over week in outstanding units (from 35,489,005 to 36,689,005). Among the largest underlying components of MGK, in trading today Adobe Inc (Symbol: ADBE) is down about 1.6%, McDonald's Corp (Symbol: MCD) is down about 0.1%, and Union Pacific Corp (Symbol: UNP) is lower by about 0.9%. For a complete list of holdings, visit the MGK Holdings page \\u00bb The chart below shows the one year price performance of MGK, versus its 200 day moving average: Looking at the chart above, MGK's low point in its 52 week range is $117.91 per share, with $162.49 as the 52 week high point \\u2014 that compares with a last trade of $159.12. 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 The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Salesforce vs. Adobe: Which Is a Better Digital Transformation Investment? Jim Cramer -- the energetic host of CNBC's Mad Money -- thinks that competition between salesforce.com (NYSE: CRM) and Adobe (NASDAQ: ADBE) could \\\"become one of the great rivalries in tech.\\\" Really? Customer relationship management software versus digital design and creativity software? The thing is, I agree. But I would suggest his timeline is off. It's already one of the great tech rivalries out there. Unbeknownst to the general public, digital transformation has been sweeping the globe and reshaping how organizations think about their operations and how to present themselves to customers. Salesforce and Adobe, while born of different disciplines, are some of the preeminent players in that digital transformation. Rather than choose one, though, I say own both. Image source: Getty Images. Data versus content creation First, though, it's worth acknowledging the two very different histori\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 = 0.0152 (i.e., a 1.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0152 = 6.5873, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015181, "expected_loss": 0.015181, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220607_0744", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2022-06-07", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0339, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=-0.0005, std=0.0146, 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 = 0.0339 (i.e., a 3.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0339 = 2.9528, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033866, "expected_loss": 0.033866, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20221122_0746", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2022-11-22", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0351, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0027, std=0.0169, worst_day=-0.0375\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-11-21] [\"Should Vanguard Mega Cap ETF (MGC) Be on Your Investing Radar? If you're interested in broad exposure to the Large Cap Blend segment of the US equity market, look no further than the Vanguard Mega Cap ETF (MGC), a passively managed exchange traded fund launched on 12/17/2007. The fund is sponsored by Vanguard. It has amassed assets over $3.62 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 Companies that find themselves in the large cap category typically have a market capitalization above $10 billion. Overall, they are usually a stable option, with less risk and more sure-fire cash flows 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 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 counterparts, other things remaining the same. Annual operating expenses for this ETF are 0.07%, making it one of the least expensive products in the space. It has a 12-month trailing dividend yield of 1.55%. 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. This ETF has heaviest allocation to the Information Technology sector--about 29.30% of the portfolio. Healthcare and Financials round out the top three. Looking at individual holdings, Apple Inc. (AAPL) accounts for about 8.48% of total assets, followed by Microsoft Corp. (MSFT) and Amazon.com Inc. (AMZN). The top 10 holdings account for about 33.08% of total assets under management. Performance and Risk MGC seeks to match the performance of the CRSP US Mega Cap Index before fees and expenses. The CRSP U.S. Mega Cap Index includes the largest U.S. companies, with a target of including the top 70% of investable market capitalization. The index includes securities traded on NYSE, NYSE Market, NASDAQ or ARCA. The ETF has lost about -17.90% so far this year and is down about -16.42% in the last one year (as of 11/21/2022). In the past 52-week period, it has traded between $124.31 and $169.35. The ETF has a beta of 1 and standard deviation of 25.25% for the trailing three-year period, making it a medium risk choice in the space. With about 239 holdings, it effectively diversifies company-specific risk. Alternatives Vanguard Mega Cap 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, MGC 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) and the SPDR\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 = 0.0351 (i.e., a 3.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0351 = 2.8513, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035072, "expected_loss": 0.035072, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200908_0749", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2020-09-08", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0011, std=0.0123, worst_day=-0.0315\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-09-04] [\"Asian markets slide, following Wall Street\\u2019s tumble Stocks fall in Tokyo, Hong Kong, Seoul Asian markets skidded Friday after Wall Street had its worst day since June, as investors\\u2019 exuberance faltered after a spate of record highs.\", \"Podcast: Nasdaq Composite Drops 5% Many of the pandemic\\u2019s hottest stocks saw steep declines on Thursday. The latest government jobs report looks worse than economists forecast. But spending on wireless spectrum licenses was up $4.5 billion last month.\", \"Coronavirus update: Global tally climbs above 26 million, U.S. above 6.1 million, amid concerns CDC will rush out a vaccine The global tally for confirmed cases of the coronavirus that causes COVID-19 climbed above 26 million on Thursday, while in the U.S. there were growing concerns that President Donald Trump\\u2019s administration will attempt to rush out a vaccine ahead of the November presidential election.\", \"Here are the biggest stock-market losers on Thursday as the tech sector tanks All S&P 500 sectors ended lower Thursday\\u2019s decline was broad, with all sectors of the S&P 500 ending lower.\", \"Just $5 and an iPhone can open the door to investing in the world\\u2019s rarest fine wines The pandemic has reinvigorated many people\\u2019s passion for hobbies and nostalgia, Rally\\u2019s co-founder says Rally\\u2019s wine offerings will have a combined value of $148,000 and include a \\u201905 Chateau Latour and 2016 Chateau Petrus\", \"Apple Stock Falls Again as the Nasdaq Keeps Dropping The Nasdaq\\u2019s loss in futures trading builds on Thursday\\u2019s sharp decline.\", \"Tech bloodbath aside, ride these two giants for the second half of the recovery, veteran analyst says Critical information for the U.S. trading day Never mind the carnage. One analyst says the second phase of the economic rebound, during the second half of this year and into 2021, will \\u201csupercharge\\u201d the fundamentals and growth trajectories of well positioned tech stocks\", \"Apple delays privacy policy change, much to the relief of Facebook, mobile ad sellers Digital advertising firms have dreaded the planned privacy changes that would require them to explain in their notifications why they are seeking tracking permissions Apple Inc. says it will delay until early next year changes to its privacy policy that Facebook Inc. and others claim will eviscerate advertising sales targeting users on iPhones and iPads.\", \"Apple Lost $180 Billion In Market Value Thursday. It\\u2019s the Biggest Loss For a Company Ever. Apple stock slid 8% on Thursday, a rotten day for technology shares. That translated to a loss of roughly $180 billion in the iPhone maker\\u2019s market capitalization.\", \"Salesforce.com Inc., Apple Inc. share losses lead Dow's 532-point fall\", \"Barron\\u2019s Daily: Tech Stocks Slide Again Trump takes aim at cities\\u2019 funding, \\u201cTenet\\u201d will be in many U.S. movie theaters this weekend, Fed\\u2019s Charles Evans says U.S. economy needs more support, and other ne\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 = 0.0289 (i.e., a 2.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0289 = 3.4649, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028861, "expected_loss": 0.028861, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180907_0751", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2018-09-07", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0319, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0022, std=0.0149, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-09-06] [\"7 Lucrative Biotech Stocks With Up to 300% Upside InvestorPlace - Stock Market News, Stock Advice & Trading Tips Forget market dynamics. These biotechs are playing to their own tune. According to the Street's top analysts this can be a very lucrative path. Biotech stocks can spike massively on positive news - be it key trial results or regulatory approvals. Of course, the opposite is also true and the biotech sector can crash just as quickly on unexpected disappointments. But the key point remains: Biotechs provide an outlet away from the rest of the market to potentially make serious money. That's especially welcome in the month of September - a notoriously tricky time for the markets. Indeed, September has been the worst performing month of the year for the Dow Jones Industrial Average and the S&P 500 since 1950. Your Chance to Cash In With Legal Sports Betting With that in mind, let's now turn to these seven strong buy biotechs now. I used TipRanks to ensure two crucial points: 1) big support from the Street, especially from top-performing analysts and 2) eye-watering upside potential ahead. Now let's see how these stocks tick these two boxes: Biotech Stocks to Buy: ObsEva (OBSV) ObsEva (NASDAQ: OBSV ) is developing best-in-class drug candidates to improve women's reproductive health. The lead is Linzagolix (OBE2109), a potentially best-in-class orally-dosed GnRH antagonist to treat symptoms of endometriosis (Ph2b) and uterine fibroids (Ph3). Top HC Wainwright analyst Ram Selvaraju ( Profile & Recommendations ) is very bullish on the stock's potential. He has just reiterated his \\\"buy\\\" rating with a $44 price target. From current levels that indicates massive upside potential of 237%! He notes that just-released data from AbbVie Inc (NYSE: ABBV ) reduces the risk for OBSV's Linzagolix. \\\"In our view, the long-term efficacy for elagolix should bode well for future development of linzagolix in uterine fibroids, since both drugs are GnRH receptor antagonists and have shown comparable potency in clinical studies.\\\" However, one of the key advantages for Linzagolix is the potential to be administered in certain patients without needing add-back therapy (ABT). This is the addition of a small amount of the hormones estrogen and/or progesterone to reduce undesirable effects of GnRH. Overall, six analysts have published back-to-back buy ratings on OBSV stock. This is with a $32 price target (147% upside potential). See what other Top Analysts are saying about OBSV . Biotech Stocks to Buy: Tocagen Inc (TOCA) This cutting-edge biotech stock is at the forefront of cancer therapy. Tocagen Inc (NASDAQ: TOCA ) is developing an RRV platform that can selectively deliver therapeutic genes into the DNA of cancer cells. Right now, all eyes are on Toca 511 and Toca FC. These drugs are in pivotal Phase 3 trials for recurrent high-grade gliomas (HGGs), with data due in 1H19. These are extremely difficult to treat cancers. \\\"Given the robustness of overall dataset\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 = 0.0319 (i.e., a 3.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0319 = 3.1344, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031904, "expected_loss": 0.031904, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20151005_0753", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2015-10-05", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0323, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0005, std=0.0116, worst_day=-0.0339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-10-02] [\"Micron Jumps On Q4 Beat But Is Down From Year Ago\", \"Analog Devices' Rating Upped by Citi; Target Price Reiterated\", \"Micron Jumps On Q4 Beat But Is Down From Year Ago\", \"Analog Devices' Rating Upped by Citi; Target Price Reiterated\", \"Analog Devices' Rating Upped by Citi; Target Price Reiterated Recently, Analog DevicesADI was upgraded to \\\"Buy\\\" from \\\"Neutral\\\" by Citi's analyst Christopher Danely. In addition, he reiterated the price target of $66.00. Danely remains optimistic about the company's solid business model, increasing margins and profits, high dividend yield and upside from the Apple Inc. AAPL design win. He believes that the touch technology used in Apple's devices will boost Analog Devices' earnings. According to him, this new design win could be accretive to revenues by 13% and add 36 cents to earnings in 2016. However, this design win could impact margins, thus lowering the company's overall margins to 33.2%. The analyst also believes that the Apple design win should expand Analog Devices' earnings growth at a compounded annual growth rate (CAGR) of 20%. Additionally, Danely expects the company's earnings to reach $4.50 per share in 2016, up 50% from the 2015 earnings estimate of $3.00. Moreover, the analyst remains encouraged by Analog Devices' dividend yield of 3%, which is 25% higher than the semiconductor group and 30% more than the S&P 500. Danely stated that though the demand from the company's industrial and automotive markets appears weak, Analog Devices' new products will continue to witness strong deployment in the communications market, further expanding its share in the sensor market. The analyst believes that the possibility that the company might supply Apple with components for next-generation iPhones and iPads will boost sales in the communications market. Analog Devices is a leading supplier of analog and digital signal processing (DSP) integrated circuits. Its large customer base provides a distinct competitive edge. We believe that the company's supremacy is driven by its innovative design technology and vast product portfolio. Currently, Analog Devices has a Zacks Rank #2 (Buy). A couple of well-ranked stocks in the same sector are Inphi Corporation IPHI and MaxLinear, Inc. MXL . While Inphi sports a Zacks Rank #1 (Strong Buy), MaxLinear has the same Zacks Rank as Analog Devices. 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 >> 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 ANALOG DEVICES (ADI): Free Stock Analysis Report INPHI CORP (IPHI): Free Stock Analysis Report MAXLINEAR INC-A (MXL): Free Stock Analysis Report To read this article on Zacks.com click here. Zacks Investment Research The views and opinions expressed herein are the views and opinions\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 = 0.0323 (i.e., a 3.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0323 = 3.0987, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032271, "expected_loss": 0.032271, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220902_0755", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2022-09-02", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0294, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=-0.0006, std=0.0137, 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 = 0.0294 (i.e., a 2.94% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0294 = 3.4018, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029396, "expected_loss": 0.029396, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190218_0757", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2019-02-18", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1287, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0059, std=0.0572, worst_day=-0.1471\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7770", "answer_numeric": 0.777, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1287 (i.e., a 12.87% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1287 = 0.7770, capped at 1.0.\nMaximum position size = 0.7770 (77.7% of portfolio).", "metadata": {"var_99": -0.128707, "expected_loss": 0.128707, "max_drawdown_threshold": 0.1, "position_size": 0.777, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200417_0759", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2020-04-17", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1446, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0028, std=0.0645, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6918", "answer_numeric": 0.6918, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1446 (i.e., a 14.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1446 = 0.6918, capped at 1.0.\nMaximum position size = 0.6918 (69.2% of portfolio).", "metadata": {"var_99": -0.144551, "expected_loss": 0.144551, "max_drawdown_threshold": 0.1, "position_size": 0.6918, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210817_0761", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2021-08-17", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0141, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0008, std=0.0056, worst_day=-0.0153\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-08-16] [\"C3 Global Services & IKG Global Consultants Form Strategic Partnership to Promote Healthcare Education and Exports The mission of the C3 Global Services and IKG Global Consultants strategic partnership is to develop an exchange that focuses on international businesses and academic institutions interested in creating new healthcare relationships in global markets.\", \"Metatron Acquires E-commerce Company and explores New Crypto Bot Fund DOVER, DE, Aug. 16, 2021 (GLOBE NEWSWIRE) -- Metatron (OTC Pink: MRNJ), a mobile and web technology pioneer having developed over 2,000 apps on iTunes and Google Play, is pleased to announce it has acquired a controlling interest in Mountain Green inc., an e-commerce company which generated over millions in sales over the last twelve months. Mountain Green has already added significantly to Metatron\\u2019s balance sheet since deal closing and brings to the table its thousands of customers and multipl\", \"Smartphone for Snapdragon Insiders review: Not for most people The Smartphone for Snapdragon Insiders boasts a 144Hz screen, comprehensive 5G support, fast charging and special audio enhancements.\", \"Verizon Authorized Retailer CellOnly Expands Southward, Acquires 14 Locations Across Texas and Oklahoma Communication Connection locations join CellOnly\\u2019s footprint of 56 wireless retail storesAMARILLO, Texas, Aug. 16, 2021 (GLOBE NEWSWIRE) -- Verizon Authorized Retailer CellOnly today announced the acquisition of 14 Communication Connection locations across Texas and Oklahoma, bringing the retailer\\u2019s total footprint to 56 stores across the Midwest and beyond. Communication Connection stores in Amarillo, Borger, Childress, Dumas, Haskell, Hereford, Hudson Oaks, Mineral Wells, Pampa, Perryton, Sham\", \"This Beautiful White Canon TLB Belongs in Your Hands Shooting Film Some cameras are just prettier than others. To that end, some lenses just make prettier images. For what they're worth, it's hard to beat Canon FD mount lenses. And luckily, this gorgeous Canon TLB can use them. How often have you seen them in white? It's rare--in fact, this one is most likely a one of a kind. But quite honestly, this Canon TLB checks all the marks of what we want in a camera. It's available through the Rare Camera Store right now. And trust me, you're going to be pleased.\", \"Brunswick CEO on the boom in boating Brunswick CEO David Foulkes discusses the company's strong second quarter, and electrification and autonomous tech the company is going to use in its power boats.\", \"The latest version of iCloud for Windows adds a full password manager With version 12.5 of iCloud for Windows, Apple is adding a password manager.\", \"Why We Think Fujifilm Doesn\\u2019t Have Animal Face Detection Yet Animal Face Detection has been a huge thing in the photo world. Everyone wants it. In the pandemic, we've taken to photographing as much wildlife and our furry friends as much as possible. But frustratingly, Fujifilm cameras don't have it. Yet a wh\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 = 0.0141 (i.e., a 1.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0141 = 7.0780, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014128, "expected_loss": 0.014128, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220701_0763", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2022-07-01", "context_summary": "DBC: 60-day history, VaR(99%)=-0.0293, max drawdown threshold=10%.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=0.0001, std=0.0146, worst_day=-0.0293\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 = 0.0293 (i.e., a 2.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0293 = 3.4171, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029265, "expected_loss": 0.029265, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210201_0766", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2021-02-01", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1934, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0156, std=0.0994, worst_day=-0.1969\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5171", "answer_numeric": 0.5171, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1934 (i.e., a 19.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1934 = 0.5171, capped at 1.0.\nMaximum position size = 0.5171 (51.7% of portfolio).", "metadata": {"var_99": -0.193385, "expected_loss": 0.193385, "max_drawdown_threshold": 0.1, "position_size": 0.5171, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220125_0768", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2022-01-25", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0219, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0008, std=0.0102, worst_day=-0.0219\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-24] [\"Buy Smart With Software Stocks on the Dip InvestorPlace - Stock Market News, Stock Advice & Trading Tips Technology stocks are getting crushed right now, and software stocks in particular are bearing the brunt of the selling. Year-to-date, the tech-heavy Nasdaq is off 12% \\u2014 marking its fourth worst start to a year ever. Worse yet, the Invesco Dynamic Software ETF (NYSEARCA:PSJ) is down nearly 18% in just three weeks. Source: Shutterstock Ouch! But as the old saying goes, it\\u2019s often best to be greedy when others are fearful. This time around, that saying is especially true because the stocks getting hit the hardest \\u2014 software stocks \\u2014 are the market\\u2019s best. Technology is taking over the world. You know that. I know that. We all know that. New tech products and services are redefining every aspect of our personal and professional lives. This trend won\\u2019t stop anytime soon. By 2030, the world will be run by tech. And these days, most of that tech is software \\u2014 not hardware. That\\u2019s because from a single piece of hardware, like a phone or computer, you can access an infinite number of software applications. Big picture: Software will inevitably run the world one day. That\\u2019s just a fact. And consequently, software stocks will be the market\\u2019s biggest winners. So\\u2026 when faced with a short-term pullback in a group of long-term winners \\u2014 like we\\u2019re seeing today in software stocks \\u2014 the best thing to do is buy the dip. But be careful \\u2014 because while some software stocks look like they\\u2019ve bottomed and are ready to rocket higher, the ones you\\u2019re probably thinking about buying have further yet to fall. Avoid Overvaluation The biggest software growth stocks in the market \\u2014 household companies making software that you and I use every day, with businesses growing at 10%-plus every year and gross margins above 60% \\u2014 are still overvalued. I\\u2019m talking Microsoft (NASDAQ:MSFT), Adobe (NASDAQ:ADBE), Intuit (NASDAQ:INTU), Autodesk (NASDAQ:ADSK), Fortinet (NASDAQ:FTNT), Illumina (NASDAQ:ILMN) and more. I\\u2019ve put together an index of the 10 most important software growth stocks in the market and tracked their price-to-sales multiples over the past five years. Before the pandemic \\u2014 before interest rates got cut to zero, before Treasury yields plunged and before enormous globs of fiscal stimulus hit the economy \\u2014 these stocks were trading around 10 to 12 times trailing sales. That should be considered a \\u201cnormal\\u201d valuation for high-margin software growth stocks. During the pandemic, though, those multiples ballooned to record highs. Now, even after the recent tech meltdown, the \\u201cBig Software 10\\u201d (as I like to call them) are still trading at 16 times trailing sales \\u2014 a huge premium to their valuations prior to the pandemic. Source: InvestorPlace In other words, those stocks still have a lot of room to fall if the Fed does hike interest rat\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 = 0.0219 (i.e., a 2.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0219 = 4.5664, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021899, "expected_loss": 0.021899, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201002_0770", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2020-10-02", "context_summary": "USO: 60-day history, VaR(99%)=-0.0478, max drawdown threshold=10%.", "question": "Asset: USO\nDaily returns (past 60 days): mean=-0.0013, std=0.0181, worst_day=-0.0617\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USO, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0478 (i.e., a 4.78% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0478 = 2.0919, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.047804, "expected_loss": 0.047804, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220412_0772", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2022-04-12", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1034, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0027, std=0.0464, worst_day=-0.1071\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-11] \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": "0.9671", "answer_numeric": 0.9671, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1034 (i.e., a 10.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1034 = 0.9671, capped at 1.0.\nMaximum position size = 0.9671 (96.7% of portfolio).", "metadata": {"var_99": -0.103401, "expected_loss": 0.103401, "max_drawdown_threshold": 0.1, "position_size": 0.9671, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20211101_0773", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2021-11-01", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1519, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0490, worst_day=-0.1902\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-10-29] \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": "0.6585", "answer_numeric": 0.6585, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1519 (i.e., a 15.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1519 = 0.6585, capped at 1.0.\nMaximum position size = 0.6585 (65.8% of portfolio).", "metadata": {"var_99": -0.151871, "expected_loss": 0.151871, "max_drawdown_threshold": 0.1, "position_size": 0.6585, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20190522_0775", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2019-05-22", "context_summary": "UNG: 60-day history, VaR(99%)=-0.0270, max drawdown threshold=10%.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=-0.0014, std=0.0124, worst_day=-0.0297\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 = 0.0270 (i.e., a 2.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0270 = 3.6997, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027029, "expected_loss": 0.027029, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220411_0777", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SLV"], "decision_date": "2022-04-11", "context_summary": "SLV: 60-day history, VaR(99%)=-0.0308, max drawdown threshold=10%.", "question": "Asset: SLV\nDaily returns (past 60 days): mean=0.0013, std=0.0148, worst_day=-0.0322\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0308 (i.e., a 3.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0308 = 3.2507, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030763, "expected_loss": 0.030763, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200916_0779", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2020-09-16", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.1428, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0091, std=0.0509, worst_day=-0.1649\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7001", "answer_numeric": 0.7001, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1428 (i.e., a 14.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1428 = 0.7001, capped at 1.0.\nMaximum position size = 0.7001 (70.0% of portfolio).", "metadata": {"var_99": -0.142836, "expected_loss": 0.142836, "max_drawdown_threshold": 0.1, "position_size": 0.7001, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220509_0781", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2022-05-09", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0698, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0031, std=0.0281, worst_day=-0.0787\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-05-08] \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 = 0.0698 (i.e., a 6.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0698 = 1.4327, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.069799, "expected_loss": 0.069799, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20171229_0785", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2017-12-29", "context_summary": "DBB: 60-day history, VaR(99%)=-0.0216, max drawdown threshold=10%.", "question": "Asset: DBB\nDaily returns (past 60 days): mean=0.0009, std=0.0087, worst_day=-0.0230\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 = 0.0216 (i.e., a 2.16% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0216 = 4.6319, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02159, "expected_loss": 0.02159, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20201113_0787", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2020-11-13", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0335, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0010, std=0.0130, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-11-12] [\"Better Buy: Slack vs. Adobe Slack (NYSE: WORK) and Adobe (NASDAQ: ADBE) are both forward-thinking companies that are changing how people work. Slack's enterprise communication platform reduced the need for clumsy email chains and time-consuming phone calls. It also recently expanded its platform with Slack Connect, which allows companies to communicate and collaborate securely with external partners. Adobe transformed its desktop software into cloud-based services that locked in customers with subscriptions and eliminated the need for local software installations and periodic upgrades. Adobe also expanded its cloud ecosystem with additional services for enterprise customers. Slack went public via a direct listing in June 2019. But after a few wild swings, its stock is still hovering near its initial reference price of $26. Meanwhile, Adobe's stock has surged nearly 60% just since Slack's public debut. Let's see why Adobe outperformed Slack, and if it will remain the faster-growing stock for the foreseeable future. Image source: Getty Images. Slack: A first mover with a shrinking moat Slack operates a \\\"freemium\\\" business model. Paying businesses gain unlimited messages and integrated tools, better security, more cloud storage, automation services for repetitive tasks, and other services. Slack was founded seven years ago, and it enjoys a first mover's advantage in its disruptive niche. However, Microsoft's (NASDAQ: MSFT) Teams, which was launched in 2017, copied many of Slack's features and was subsequently bundled into Office 365 subscriptions as a free service. In response, Slack filed an antitrust complaint against Microsoft in Europe earlier this year, alleging the tech giant was \\\"force installing\\\" a \\\"weak, copycat product\\\" onto \\\"millions\\\" of users. Slack continued to grow as Microsoft expanded Teams, but that competitive threat cast a long shadow over the underdog's future. Adobe: An evolving tech giant with an expanding ecosystem Adobe splits its business into two main divisions: the Digital Media unit, which provides its creativity and productivity software as cloud-based services; and the Digital Experience unit, which hosts its enterprise tools. The Digital Media unit's Creative Cloud hosts industry-standard software like Adobe Photoshop, Premiere Pro, Illustrator, After Effects, and Acrobat. Most of these software products dominate their respective markets. The Digital Experience unit, which hosts cloud-based advertising, analytics, advertising, and e-commerce tools, faces much tougher competition. salesforce.com (NYSE: CRM) competes against most of Adobe's enterprise-oriented services, while Shopify competes against Adobe's Magento e-commerce services. Which company is growing faster? Slack's revenue grew 57% year over year to $630 million in fiscal 2020, which ended on Jan. 30. Its GAAP net loss widened from $141 million to $571 million last year, but its non-GAAP net loss narrowed slightly from $116 million to $113 million. \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 = 0.0335 (i.e., a 3.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0335 = 2.9889, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033457, "expected_loss": 0.033457, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20171023_0789", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2017-10-23", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.1021, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0072, std=0.0449, worst_day=-0.1328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9798", "answer_numeric": 0.9798, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1021 (i.e., a 10.21% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1021 = 0.9798, capped at 1.0.\nMaximum position size = 0.9798 (98.0% of portfolio).", "metadata": {"var_99": -0.102066, "expected_loss": 0.102066, "max_drawdown_threshold": 0.1, "position_size": 0.9798, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20151113_0791", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2015-11-13", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0313, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0004, std=0.0131, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-11-12] How NVIDIA Corporation Gained 15% in October NVDA data by YCharts . What: Shares of NVIDIA gained 15% in October, according to data from S&P Capital IQ . The catalyst for this market-beating autumnal jaunt? Merger rumors in NVIDIA's neck of the semiconductor woods, even tough this particular chatter never involved NVIDIA itself. So what: On Oct. 14, the rumor mill echoed with reports that Analog Devices might merge with fellow mixed-signal processor maker Maxim Integrated Products . NVIDIA rose 4% that day and never looked back. Shareholders seem excited about the idea of sector giants on the prowl for a deal in the \"merger of equals\" category. Now what: Maxim and ADI never commented on those merger rumors, and the gossip has since moved on to pairing Maxim with even larger rival Texas Instruments . That development hasn't negated NVIDIA's potential-merger boost at all, especially since the graphics processor specialist followed up with a strong third-quarter report near the start of November. The chip market is awash in major mergers, and the time has never been more ripe for NVIDIA to define an exit strategy. In particular, I wouldn't be surprised to see Texas Instruments turning its sights away from Maxim due to broadly overlapping product portfolios, and take a closer look at NVIDIA. The overlaps would be far smaller here, making TI an instant contender in several parts of the mobile and automotive markets where NVIDIA has been eating TI's lunch in recent years. Mind you, it's all just rumors at this point. Maxim hasn't found a final buyer yet, and nobody has even hinted at talking to NVIDIA's board of directors. So NVIDIA's shareholders continue an inspiring ride that has seen share prices skyrocket 50% higher over the last six months. Maxim has only gained 24%, direct buyout rumors notwithstanding. Is NVIDIA going to Texas or Massachusetts in the near future, or perhaps nowhere at all? Grab a bag of popcorn and a comfy deck chair. We'll just have to wait and see. This iSecret stock could make this pop look tiny The world's biggest tech company forgot to show you something at its recent event, but a few Wall Street analysts and the Fool didn't miss a beat: There's a small company that's powering their brand-new gadgets and the coming revolution in technology. And we think its stock price has nearly unlimited room to run for early in-the-know investors! To be one of them, just click here . The article How NVIDIA Corporation Gained 15% in October originally appeared on Fool.com. Anders Bylund has no position in any stocks mentioned. The Motley Fool recommends Nvidia. Try any of our Foolish newsletter services free for 30 days .We Fools may not all hold the same opinions, but we all believe that considering a diverse range of insights makes us better investors. The Motley Fool has a disclosure policy . Copyright \u00a9 1995 - 2015 The Motley Fool, LLC. All rights reserved. The Motley Fool has a disclosure policy . The views and opinions expressed he\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 = 0.0313 (i.e., a 3.13% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0313 = 3.1955, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031294, "expected_loss": 0.031294, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170920_0793", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2017-09-20", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1635, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0014, std=0.0789, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-09-19] [\"18 Stocks to Capture the Next Tech Boom Janus Henderson Global Technology trounces its peers with big stocks like Alphabet and Facebook and dozens of much smaller ones.\", \"How Amazon\\u2019s stock could rise to $3,000 \\u2014 or fall to $400 Artificial intelligence will be a big catalyst, though the company\\u2019s fast growth will eventually come to an end Artificial intelligence will be a big catalyst, though the company\\u2019s fast growth will eventually come to an end, says Nigam Arora.\", \"Fitbit Ionic Review: A Smartwatch That\\u2019s Better at Fitness Than Time Fitbit\\u2019s new smartwatch excels on a run, but the interface holds the device back as an everyday watch option.\", \"Apple stock price target raised to $194 from $182 at Morgan Stanley\", \"Apple's price target raised at Morgan Stanley as higher ASPs should boost profits Shares of Apple Inc. inched up less than 0.1% in morning trade Tuesday, after Morgan Stanley raised its price target, citing an improved profit outlook on the back of that higher average selling prices (ASPs). Analyst Katy Huberty reiterated her overweight rating, but boosted her target to $194, which is more than 20% above current levels, from $182. Huberty said the key takeaway from Apple's product event last week is that ASPs were raised across the product line. She raised her fiscal 2018 earning-per-share estimate to $12.60 from $11.80--the FactSet consensus is $10.89--as high customer loyalty and a stronger U.S. dollar should keep higher prices from hurting demand. \\\"Apple is an aspirational brand offering high quality, innovative products at a premium price,\\\" Huberty wrote in a note to clients. \\\"As a result, the company escapes the typical trend of declining prices that drive demand for other devices.\\\" the stock has rallied 8.5% over the past three months, while the SPDR Technology Select Sector ETF has climbed 4.9% and the Dow has gained 3.8%.\", \"How your heart rate monitor could help criminals Researchers were able to intercept information from Fitbit devices Researchers were able to intercept information from Fitbit devices.\", \"Bitcoin needs to be worth $1,000,000 to be a legitimate currency A single bitcoin is equal to 100,000,000 Satoshi Think bitcoin has been in bubble territory? You ain\\u2019t seen nothing yet, as the cryptocurrency needs to surge about 300 times it value over the next several years to be considered a legitimate currency or risk retreating into obscurity and obsolescence, says one industry expert.\", \"Apple Benefits When It Raises Prices, Says Morgan Stanley Apple tends to do well when it raises prices, says Morgan Stanley's Katy Huberty, and she raised her price target on the company's stock to $194 to reflect several price increases coming out of last week's media event held by Apple, including not just on iPhone but also iPads and even the company's annual support contract.\", \"Tesla, Apple and Amazon: Alike in Spirit, Not Profits Another analyst has weighed in with a negative review of\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": "0.6118", "answer_numeric": 0.6118, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1635 (i.e., a 16.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1635 = 0.6118, capped at 1.0.\nMaximum position size = 0.6118 (61.2% of portfolio).", "metadata": {"var_99": -0.163455, "expected_loss": 0.163455, "max_drawdown_threshold": 0.1, "position_size": 0.6118, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200529_0795", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2020-05-29", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0438, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0005, std=0.0249, worst_day=-0.0438\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-05-28] [\"Tweedy Browne's \\u2014\\u2026\\u2014\\u2026 Annual Letter to Shareholders\", \"The Momentum Trade Driving Stocks Higher May Be About To Snap\", \"Kroger: Capital Preservation and More at a Good Price\", \"Tredje AP-fonden Buys Microsoft Corp, Amazon.com Inc, Apple Inc, Sells iShares U.S. ...\", \"Growth Stocks for 2020: Trading Tech Stocks + FANG Stocks\", \"Swiss National Bank Ready To Buy Much More Tech Stocks To Weaken The Franc\", \"Stocks Are Struggling To Post Gains On May 28 Ahead Of Initial Claims\", \"The Zacks Analyst Blog Highlights: Apple, Exxon Mobil, Cisco System and Chevron\", \"Tech Companies Aren't 'State Actors,' Judge Dismisses Conservative Bias Lawsuit Against Facebook, Twitter, Google, Apple\", \"Martin Scorsese's Next Movie Will Be Financed By Apple: Report\", \"Costco Earnings On Tap After Close As Investors Mull Strong Toll Brothers Results\", \"Trump's Executive Order To Expose Social Media To Lawsuits Over Content Policies\", \"Trump's Executive Order To Expose Social Media To Lawsuits Over Content Policies\", \"Costco Earnings On Tap After Close As Investors Mull Strong Toll Brothers Results\", \"Martin Scorsese's Next Movie Will Be Financed By Apple: Report\", \"Tech Companies Aren't 'State Actors,' Judge Dismisses Conservative Bias Lawsuit Against Facebook, Twitter, Google, Apple\", \"The Momentum Trade Driving Stocks Higher May Be About To Snap\", \"Tweedy Browne's \\u2014\\u2026\\u2014\\u2026 Annual Letter to Shareholders\", \"Kroger: Capital Preservation and More at a Good Price\", \"Tredje AP-fonden Buys Microsoft Corp, Amazon.com Inc, Apple Inc, Sells iShares U.S. ...\", \"The Zacks Analyst Blog Highlights: Apple, Exxon Mobil, Cisco System and Chevron\", \"Growth Stocks for 2020: Trading Tech Stocks + FANG Stocks\", \"Stocks Are Struggling To Post Gains On May 28 Ahead Of Initial Claims\", \"Swiss National Bank Ready To Buy Much More Tech Stocks To Weaken The Franc\", \"Trump's Executive Order To Expose Social Media To Lawsuits Over Content Policies\", \"Costco Earnings On Tap After Close As Investors Mull Strong Toll Brothers Results\", \"Martin Scorsese's Next Movie Will Be Financed By Apple: Report\", \"Tech Companies Aren't 'State Actors,' Judge Dismisses Conservative Bias Lawsuit Against Facebook, Twitter, Google, Apple\", \"The Momentum Trade Driving Stocks Higher May Be About To Snap\", \"Tweedy Browne's \\u2014\\u2026\\u2014\\u2026 Annual Letter to Shareholders\", \"Kroger: Capital Preservation and More at a Good Price\", \"Tredje AP-fonden Buys Microsoft Corp, Amazon.com Inc, Apple Inc, Sells iShares U.S. ...\", \"The Zacks Analyst Blog Highlights: Apple, Exxon Mobil, Cisco System and Chevron\", \"Growth Stocks for 2020: Trading Tech Stocks + FANG Stocks\", \"Stocks Are Struggling To Post Gains On May 28 Ahead Of Initial Claims\", \"Swiss National Bank Ready To Buy Much More Tech Stocks To Weaken The Franc\", \"Apple makes streaming deal for Martin Scorsese movie starring Leonardo DiCaprio \\u2018Killers of the Flower Moon\\u2019 to stream exclusively on Apple TV+ Apple Inc. has nabbed\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 = 0.0438 (i.e., a 4.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0438 = 2.2811, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.043839, "expected_loss": 0.043839, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200630_0797", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2020-06-30", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0371, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0035, std=0.0238, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-29] [\"Notable Monday Option Activity: NKE, AMD, HLT Among the underlying components of the S&P 500 index, we saw noteworthy options trading volume today in Nike (Symbol: NKE), where a total of 45,948 contracts have traded so far, representing approximately 4.6 million underlying shares. That amounts to about 55.9% of NKE's average daily trading volume over the past month of 8.2 million shares. Especially high volume was seen for the $92.50 strike put option expiring October 16, 2020, with 3,615 contracts trading so far today, representing approximately 361,500 underlying shares of NKE. Below is a chart showing NKE's trailing twelve month trading history, with the $92.50 strike highlighted in orange: Advanced Micro Devices Inc (Symbol: AMD) saw options trading volume of 251,471 contracts, representing approximately 25.1 million underlying shares or approximately 46.5% of AMD's average daily trading volume over the past month, of 54.1 million shares. Particularly high volume was seen for the $50 strike call option expiring July 02, 2020, with 15,378 contracts trading so far today, representing approximately 1.5 million underlying shares of AMD. Below is a chart showing AMD's trailing twelve month trading history, with the $50 strike highlighted in orange: And Hilton Worldwide Holdings Inc (Symbol: HLT) saw options trading volume of 18,555 contracts, representing approximately 1.9 million underlying shares or approximately 44.9% of HLT's average daily trading volume over the past month, of 4.1 million shares. Particularly high volume was seen for the $77.50 strike call option expiring July 17, 2020, with 5,811 contracts trading so far today, representing approximately 581,100 underlying shares of HLT. Below is a chart showing HLT's trailing twelve month trading history, with the $77.50 strike highlighted in orange: For the various different available expirations for NKE options, AMD options, or HLT options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"AMD\\u2019s New Mobile Ryzen CPUs Hit a Power Efficiency Milestone Back in 2014, AMD (NASDAQ: AMD) said the power efficiency of its mobile chips would improve 25-fold by 2020. It recently blew past that \\\"25x20\\\" goal with its \\\"Renoir\\\" Ryzen 4800H mobile chipsets, which boast a 31.7x increase in power efficiency over its \\\"Kaveri\\\" chipsets from 2014. AMD launched the Renoir chips earlier this year to succeed last year's \\\"Picasso\\\" chips. Renoir marks a big upgrade from Picasso, switching from Globalfoundries' 12nm process to TSMC's (NYSE: TSM) 7nm process and doubling its number of cores to eight. It's also integrated with a Vega GPU for high-end gaming. The upgrade not only boosted Renoir's power efficiency by 2.92x over Picasso, it also improved its clock-for-clock performance by 15%-20%. It also offers better graphics p\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 = 0.0371 (i.e., a 3.71% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0371 = 2.6978, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037067, "expected_loss": 0.037067, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190114_0799", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2019-01-14", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0353, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0014, std=0.0179, worst_day=-0.0383\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-01-11] [\"Friday's ETF with Unusual Volume: SIZE The iShares Edge MSCI USA Size Factor ETF is seeing unusually high volume in afternoon trading Friday, with over 314,000 shares traded versus three month average volume of about 32,000. Shares of SIZE were down about 0.2% on the day. Components of that ETF with the highest volume on Friday were General Electric, trading off about 0.1% with over 39.2 million shares changing hands so far this session, and Advanced Micro Devices, up about 0.5% on volume of over 37.5 million shares. General Motors is the component faring the best Friday, higher by about 8.3% on the day, while Vail Resorts is lagging other components of the iShares Edge MSCI USA Size Factor ETF, trading lower by about 13%. VIDEO: Friday's ETF with Unusual Volume: SIZE The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Noteworthy ETF Inflows: SOXX, NVDA, AMD, XLNX Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the iShares PHLX Semiconductor ETF (Symbol: SOXX) where we have detected an approximate $88.9 million dollar inflow -- that's a 8.2% increase week over week in outstanding units (from 6,700,000 to 7,250,000). Among the largest underlying components of SOXX, in trading today NVIDIA Corp (Symbol: NVDA) is off about 0.6%, Advanced Micro Devices Inc (Symbol: AMD) is off about 0.6%, and Xilinx, Inc. (Symbol: XLNX) is lower by about 0.3%. For a complete list of holdings, visit the SOXX Holdings page \\u00bb The chart below shows the one year price performance of SOXX, versus its 200 day moving average: Looking at the chart above, SOXX's low point in its 52 week range is $144.79 per share, with $198.84 as the 52 week high point - that compares with a last trade of $163.35. 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 The views and opinions expressed herein are the views and opi\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 = 0.0353 (i.e., a 3.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0353 = 2.8303, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035332, "expected_loss": 0.035332, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210104_0801", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-01-04", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1731, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0103, std=0.0653, worst_day=-0.1846\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5778", "answer_numeric": 0.5778, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1731 (i.e., a 17.31% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1731 = 0.5778, capped at 1.0.\nMaximum position size = 0.5778 (57.8% of portfolio).", "metadata": {"var_99": -0.173072, "expected_loss": 0.173072, "max_drawdown_threshold": 0.1, "position_size": 0.5778, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20160222_0803", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2016-02-22", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.1042, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0008, std=0.0338, worst_day=-0.1328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9601", "answer_numeric": 0.9601, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1042 (i.e., a 10.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1042 = 0.9601, capped at 1.0.\nMaximum position size = 0.9601 (96.0% of portfolio).", "metadata": {"var_99": -0.104158, "expected_loss": 0.104158, "max_drawdown_threshold": 0.1, "position_size": 0.9601, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200212_0806", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-02-12", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1243, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0080, std=0.0661, worst_day=-0.1452\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.8048", "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": -0.124256, "expected_loss": 0.124256, "max_drawdown_threshold": 0.1, "position_size": 0.8048, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200925_0809", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2020-09-25", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1527, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0577, worst_day=-0.1751\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6547", "answer_numeric": 0.6547, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1527 (i.e., a 15.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1527 = 0.6547, capped at 1.0.\nMaximum position size = 0.6547 (65.5% of portfolio).", "metadata": {"var_99": -0.152748, "expected_loss": 0.152748, "max_drawdown_threshold": 0.1, "position_size": 0.6547, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170724_0811", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2017-07-24", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0108, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0010, std=0.0052, worst_day=-0.0114\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-07-21] [\"XLU, EXC, PCG, AEP: Large Inflows Detected at ETF Looking today at week-over-week shares outstanding changes among the universe of ETFs covered at ETF Channel , one standout is the Utilities Select Sector SPDR Fund (Symbol: XLU) where we have detected an approximate $156.0 million dollar inflow -- that's a 2.1% increase week over week in outstanding units (from 139,774,160 to 142,724,160). Among the largest underlying components of XLU, in trading today Exelon Corp (Symbol: EXC) is down about 0.2%, PG&E Corp (Symbol: PCG) is up about 0.1%, and American Electric Power Company, Inc. (Symbol: AEP) is higher by about 0.3%. For a complete list of holdings, visit the XLU Holdings page \\u00bb The chart below shows the one year price performance of XLU, versus its 200 day moving average: Looking at the chart above, XLU's low point in its 52 week range is $45.33 per share, with $54.63 as the 52 week high point - that compares with a last trade of $52.93. 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 The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Friday Sector Leaders: Utilities, Consumer Products Looking at the sectors faring best as of midday Friday, shares of Utilities companies are outperforming other sectors, up 0.3%. Within that group, FirstEnergy Corp (Symbol: FE) and American Electric Power Company, Inc. (Symbol: AEP) are two large stocks leading the way, showing a gain of 1.4% and 1.1%, respectively. Among utilities ETFs , one ETF following the sector is the Utilities Select Sector SPDR ETF (Symbol: XLU), which is up 0.2% on the day, and up 10.82% year-to-date. FirstEnergy Corp, meanwhile, is up 4.55% year-to-date, and American Electric Power Company, Inc. is up 12.17% year-to-date. Combined, FE and AEP make up approximately 7.2% of the underlying holdings of XLU. The next best performing sector is the Consumer Products sector, higher by 0.1%. Among l\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 = 0.0108 (i.e., a 1.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0108 = 9.2264, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010838, "expected_loss": 0.010838, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201016_0813", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2020-10-16", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1411, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0030, std=0.0526, worst_day=-0.1683\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7086", "answer_numeric": 0.7086, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1411 (i.e., a 14.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1411 = 0.7086, capped at 1.0.\nMaximum position size = 0.7086 (70.9% of portfolio).", "metadata": {"var_99": -0.141124, "expected_loss": 0.141124, "max_drawdown_threshold": 0.1, "position_size": 0.7086, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170320_0815", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2017-03-20", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0079, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0013, std=0.0049, worst_day=-0.0086\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2017-03-17] [\"5 Stocks To Watch For March 17, 2017\", \"Wunderlich Upgrades Adobe Systems to Buy, Raises Price Target to $145.00\", \"A Peek Into The Markets: U.S. Stock Futures Edge Higher Ahead Of Consumer Sentiment Data\", \"Adobe's Premium Valuation Is Warranted; Wunderlich Upgrades To Buy\", \"20 Stocks Moving In Friday's Pre-Market Session\", \"The Market In 5 Minutes\", \"Benzinga's Top Upgrades, Downgrades For March 17, 2017\", \"This Is What Makes Adobe The Best Large-Cap Stock In Its Space\", \"Adobe Makes New All-Time High\", \"Success Stories With Facebook, T-Mobile And Others Keep Adobe Stock A Core Holding\", \"8 Biggest Price Target Changes For Friday\", \"15 Biggest Mid-Day Gainers For Friday\", \"Analyst: Good Q1 For Adobe, But Valuation Already Reflects Most Potential For Growth\", \"Analyst: Good Q1 For Adobe, But Valuation Already Reflects Most Potential For Growth\", \"15 Biggest Mid-Day Gainers For Friday\", \"8 Biggest Price Target Changes For Friday\", \"Success Stories With Facebook, T-Mobile And Others Keep Adobe Stock A Core Holding\", \"Adobe Makes New All-Time High\", \"This Is What Makes Adobe The Best Large-Cap Stock In Its Space\", \"Benzinga's Top Upgrades, Downgrades For March 17, 2017\", \"The Market In 5 Minutes\", \"20 Stocks Moving In Friday's Pre-Market Session\", \"Adobe's Premium Valuation Is Warranted; Wunderlich Upgrades To Buy\", \"A Peek Into The Markets: U.S. Stock Futures Edge Higher Ahead Of Consumer Sentiment Data\", \"Wunderlich Upgrades Adobe Systems to Buy, Raises Price Target to $145.00\", \"5 Stocks To Watch For March 17, 2017\", \"3 Big Stock Charts for Friday: Adobe Systems Incorporated (ADBE), Netflix, Inc. (NFLX) and International Business Machines Corp. (IBM) InvestorPlace - Stock Market News, Stock Advice & Trading Tips Earnings and upgrades are moving stocks in the technology sector today. Adobe Systems Incorporated (NASDAQ: ADBE ) announced better than expected earnings while Netflix, Inc. (NASDAQ: NFLX ) is seeing some cautious comments from the analyst community and International Business Machines Corp. (NYSE: IBM ) saw an upgrade to its price target from Morgan Stanley yesterday. All three of these stocks were already operating in strong bullish trends, but the recent price activity is signalling that the bulls are getting ready to engage these stocks again. Adobe Systems Incorporated (ADBE) Adobe announced earnings this morning, surprising the Street with better-than-expected results. ADBE shares are trading more than 5% higher after the news. Adobe shares have been trying to break into another volatility rally for the last week, but had failed to move above their top Bollinger Band. Today's news will change that as ADBE stock will open outside of the bands and likely see a further surge. 10 Monthly Dividend Stocks to Buy to Pay the Bills We saw a 9% reduction in the short interest on Adobe ahead of the earnings announcement, indicating that the short selling crowd has already started trying to get out of the way of ADBE shares breaking to new \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 = 0.0079 (i.e., a 0.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0079 = 12.5976, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.007938, "expected_loss": 0.007938, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200731_0818", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-07-31", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0996, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0108, std=0.0511, worst_day=-0.1016\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0996 (i.e., a 9.96% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0996 = 1.0039, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.099608, "expected_loss": 0.099608, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20200310_0820", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2020-03-10", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0253, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=-0.0010, std=0.0100, worst_day=-0.0253\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-03-09] [\"101 Stocks Moving In Monday's Mid-Day Session\", \"Investor Movement Index Summary: February 2020\", \"Crude Awakening: Energy Sector Takes A 20% Spill As Crude Price War Sends Oil To 4-Year Low\", \"Crude Awakening: Energy Sector Takes A 20% Spill As Crude Price War Sends Oil To 4-Year Low\", \"Investor Movement Index Summary: February 2020\", \"101 Stocks Moving In Monday's Mid-Day Session\", \"Crude Awakening: Energy Sector Takes A 20% Spill As Crude Price War Sends Oil To 4-Year Low\", \"Investor Movement Index Summary: February 2020\", \"101 Stocks Moving In Monday's Mid-Day Session\", \"Here\\u2019s what\\u2019s worth streaming in March 2020: \\u2018Ozark,\\u2019 \\u2018Making the Cut,\\u2019 \\u2018Little Fires Everywhere\\u2019 and more Netflix, Hulu, Amazon and Apple roll out the big names \\u2014 and big budgets \\u2014 with March releases While March doesn\\u2019t have a huge volume of new series and movies (Netflix excepted), it seems almost every streaming service has one or two or three high-quality, highly promising and star-studded new offerings\", \"Facebook, Apple and Twitter ask staff to work from home due to coronavirus \\u2014 now here\\u2019s the bad news for the rest of America New research by Deutsche Bank gives insights into the pressures felt by millions of Americans who don\\u2019t have the luxury to work remotely to prevent catching or spreading COVID-19 New research by Deutsche Bank gives insights into the pressures felt by millions of Americans who don\\u2019t have the luxury to work remotely to prevent catching or spreading COVID-19.\", \"Hollywood\\u2019s pandemic warning a decade ago could have been taken \\u2018much more seriously,\\u2019 pathologist says Tracey McNamara, professor of pathology at Western University of Health Sciences in California, served as a scientific adviser on the 2011 film \\u201cContagion,\\u201d and now she\\u2019s chiming in on the coronavirus.\", \"Apple iPhone Sales in China Collapsed Last Month. Why It Isn\\u2019t Time to Panic Yet. Demand for Apple iPhones in China fell sharply in February, new data shows, as economic activity the country ground to a near standstill in the face of the rapid spread of coronavirus.\", \"Apple supply challenges have the potential to impact 5G phone launch, analyst warns UBS analyst Timothy Arcuri cautioned in a Monday note to clients that sustained supply issues for Apple Inc. have the potential to thwart the company's expected launch of a 5G-enabled iPhone, although this is more of a worst-case scenario. \\\"Supply challenges have given way to broad global demand concerns; if the situation persists deep into the June [quarter], it is possible that Apple would have to delay the 5G iPhone launch this fall, though our base case remains that the launch is on-time and we maintain our C21 estimates unchanged and see long-term growth,\\\" he wrote. Arcuri also trimmed his March-quarter iPhone unit sales estimates to 40 million from 43 million following data from a Chinese government-affiliated research inst\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 = 0.0253 (i.e., a 2.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0253 = 3.9512, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025309, "expected_loss": 0.025309, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150416_0822", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2015-04-16", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0177, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0009, std=0.0091, worst_day=-0.0182\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-04-15] [\"3 Biotech Stocks Under $10 with Amazing Growth Prospects - Analyst Blog The biotech sector is witnessing changing dynamics with the focus shifting from large caps to smaller companies with high growth potential. Several big biotech players are being weighed down by pricing pressure and are feeling the threat of biosimilars. Pricing concerns in the biotech industry surfaced toward the end of last year after pharmacy benefit manager Express Scripts ESRX entered into an agreement with AbbVie Inc. ABBV adding the latter's lower priced Viekira Pak to its formulary, as an exclusive option for patients suffering from genotype 1 hepatitis C virus (HCV) infection. With this move, the leading pharmacy benefit manager removed Gilead Sciences Inc.'s GILD high-priced Sovaldi and Harvoni and Johnson & Johnson's JNJ HCV drug Olysio from its National Preferred Formulary. Since then, Gilead has entered into agreements with several pharmacy benefit managers and health care service companies. It even went on to state on its fourth quarterearnings callthat it is undertaking several pricing measures including an increase in discount, charge back and rebates. In the mean time, the first biosimilar has been approved in the U.S. Sandoz -- a Novartis company NVS -- gained approval for Zarxio, a biosimilar version of Amgen's AMGN blockbuster drug, Neupogen. Several other companies including Hospira HSP are looking to introduce biosimilars in the U.S. Earlier this year, Hospira announced that it has submitted a Biologics License Application looking to get Retacrit (a biosimilar to Epogen and Procrit) approved in the U.S. Hospira already markets several biosimilars in Europe including Retacrit and Nivestim (a biosimilar to Neupogen). Attracted by its lucrative biosimilars portfolio and pipeline, which is potentially worth multi-billion dollars, Pfizer PFE has entered into an agreement to acquire Hospira in a deal valued at approximately $17 billion. According to Pfizer, the worldwide biosimilars market is expected to be worth approximately $20 billion by 2020. Introduction of biosimilars is expected to directly affect the market for branded biotech drugs and eat into their share. In such a scenario, biotech companies with newer therapies or interesting pipeline candidates have been attracting a lot of attention. Big players are resorting to merger and acquisition (M&A) deals and licensing activity to bolster their beleaguered pipelines. Last month, AbbVie entered into an agreement to acquire Pharmacyclics PCYC in a deal valued at approximately $21 billion to gain partial rights to Imbruvica. Imbruvica is expected to generate U.S. net product revenues of approximately $1 billion in 2015. While the M&A frenzy shows no signs of slowing down, it is a great time to go beyond familiar names in the biotech sector and indulge in some cheap growth stocks. These pint-sized stocks are not only easy for the pockets but also ensure outsized returns in a trending market. How to Pick? P\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 = 0.0177 (i.e., a 1.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0177 = 5.6423, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017723, "expected_loss": 0.017723, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181210_0824", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2018-12-10", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0282, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0004, std=0.0119, worst_day=-0.0294\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-12-07] [\"What the Arrest of a Chinese Executive Means for the Stock Market A massive drop in the Dow Jones Industrial Average was spurred by the arrest of Huawei CFO Meng Wanzhou. And it was a confirmation that tensions between the U.S. and China are about more than trade.\", \"These 5 stocks are surprising winners amid the market\\u2019s wild swings Scana, Newell Brands, McCormick, Spirit Airlines, Dr. Reddy\\u2019s Impressive gains for investors so far this quarter.\", \"Morgan Stanley gets less bullish on Apple due to China demand woes Morgan Stanley analyst Katy Huberty cut her price target on Apple Inc. shares to $236 from $253 on Friday, citing weakness in the China market. She said that her supply-chain conversations in Asia suggest that the smartphone market is weakening in China. The country is \\\"following in the footsteps of the U.S. with replacement cycles lengthening after a structurally shorter cycle over the last decade,\\\" Huberty wrote. Rising average selling prices and overall better smartphone quality are leading people to keep their current devices for longer, according to Huberty. She also sees \\\"some risk of churn\\\" at the low end of Apple's customer base in China, given that some local manufacturers are offering phones with new features such as a triple camera. Huberty kept her overweight rating on the stock and said that wearables and services revenues could help the company amid a weak stretch for iPhones. Apple's shares are off 0.2% in Friday morning trading, and they're down 21% over the past three months. The Dow Jones Industrial Average has dropped 3.4% in that time.\", \"Apple\\u2019s iPhone Sales in China Will Slip, Says Morgan Stanley Analyst Katy Huberty cut her price target on Apple to $236 from $253 but reiterated an Outperform rating for the services business.\", \"All 30 Dow industrials stocks and the 20 Dow transport stocks are falling As the Dow Jones Industrial Average tumbles 659 points, or 2.6%, in afternoon trade, all 30 of its components are losing ground. Of the biggest decliners, shares of Microsoft Corp. dropped 4.4%, Caterpillar Inc. shed 4.3% and Intel Corp. declined 4.3%. The most active Dow stock was Apple Inc. , which shed 3.5% toward the lowest close since April 30. Elsewhere, the Dow Jones Transportation Average lost 4.2%, with all 20 components falling. Meanwhile, the defensive Dow Jones Utility Average rose 0.5%, with 14 of 15 components gaining ground.\", \"Online Holiday Sales Are Soaring Adobe Analytics expects a record $124.1 billion in domestic online holiday sales through Dec. 31, up 15% from $108.2 billion a year ago.\", \"Apple iPhones Won\\u2019t See Major Redesigns in 2019, Says Analyst The new iPhones in the second half of fiscal 2019 will likely have the same body size and displays as the current iPhone XR, XS, and XS Max models, according to Nomura\\u2019s Anne Lee.\", \"Older Consumers Are a Lucrative Market By 2030, seniors will be one billion strong globally and account for half of all consumer spending\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 = 0.0282 (i.e., a 2.82% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0282 = 3.5433, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028222, "expected_loss": 0.028222, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180918_0826", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2018-09-18", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0110, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0011, std=0.0049, worst_day=-0.0128\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-09-17] [\"New Apple Watch doesn\\u2019t have the feature most consumers want Price is the key factor for Apple smartwatch sales, analyst says, so most will buy older models instead of Apple Watch Series 4 \\u2018We continue to expect the lowest price option will account for the bulk of Watch volume on a global basis,\\u2019 says an analyst.\", \"Jeff Bezos\\u2019 fortune is growing even faster than he can give it away Bezos\\u2019 personal wealth has grown by about $4 billion this week The Amazon founder and CEO, the richest man in modern history, on Thursday stepped up his plans for major philanthropic giving by pledging $2 billion to set up the charitable \\u201cBezos Day One Fund.\\u201d\", \"Trade-war fears to loom large over stocks Bove: The Fed\\u2019s interest-rate hikes could trigger a recession The single biggest fear dogging the financial markets is not the possible unraveling of emerging markets or the U.S. midterm elections but the specter of a full blown trade war, according to some strategists.\", \"Apple's stock could be blamed for all of the Dow's decline Shares of Apple Inc. dropped 1.7% in morning trade Monday, enough to pace the Dow Jones Industrial Average's decliners and to pull the blue-chip barometer down into negative territory. Apple's price decline shaved about 26 points off the Dow's price, which was down 19 points. Instinet analyst Jeffrey Kvaal reiterated his neutral rating on the stock, saying his analysis of weekend orders for Apple's new iPhones suggests shipments are tracking in line with expectations. Apple's stock was still up 16.5% over the past three months while the Dow was up 4.1%.\", \"Tech stocks haven't had a losing month since March and that may change as Nasdaq suffers September slump The Nasdaq Composite Index slumped late-morning Monday, with the day's slide helping to push the technology-and-internet focused gauge to its first monthly loss since March, according to FactSet data. The Nasdaq in late-morning trade was down about 80 points, or 1%, at 7,931. Worries that the U.S. trade clash with China was on the verge of escalating this week has kept investors on edge, particularly in tech, because that sector could be harmed by another round of tech-focused tariffs, market participants said. The Trump administration is planning to unveil new import duties on $200 billion in Chinese goods. The Nasdaq was on pace to shed 2.1% in September, which would be the index's worst monthly and only decline since a 2.9% fall. Beyond tariffs, industry watchers also have feared that shares within the group have gotten rich. Meanwhile, the Dow Jones Industrial Average was experiencing a less-severe slide on Monday, down 0.1% at 26,132, while the S&P 500 index was down 0.3% at 2,895. Notably, shares of Apple Inc. and Amazon.com Inc. , two of the world's most highly valued companies, were trading sharply lower on Monday, weighing on the broader market. Technically, Amazon is classified as a consumer-discretionary company and not tech in major b\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 = 0.0110 (i.e., a 1.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0110 = 9.0855, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011007, "expected_loss": 0.011007, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20191127_0828", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2019-11-27", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0169, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0015, std=0.0065, worst_day=-0.0174\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-11-26] 5 Momentum Stocks to Buy on the Rebound In early September, we saw an unprecedented shift in the investment landscape from momentum stocks to value stocks. This came amid a recovery in economic fundamentals and a sharp rise in interest rates. By mid-September, the the iShares Momentum Factor ETF (BATS:) was down more than 1%, while the iShares Value Factor ETF (BATS:) was up more than 7%. This big divergence prompted me to write a piece on InvestorPlace outlining . The logic was simple. These sharp momentum-to-value shifts don\u2019t happen often. But, when they do, it\u2019s when the things are getting better. See late 2016. It is investors voting with their money that the coast is clear to buy stocks that require a good economy to head higher. As such, these shifts are normally temporary, and a harbinger of a broader market rally. When they end, both value and momentum stocks power higher alongside a rising economy. Thus, I reasoned that the September weakness in momentum stocks presented a solid buying opportunity into 2020, when all stocks would power higher supported by easing trade tensions, re-accelerated global capital investment and economic activity, revamped corporate profit growth, healthy labor markets and supportive central bank policy. Fast forward two months. Since then, both the Momentum Factor ETF and Value Factor ETF are up more than 3%, five of the seven momentum stocks I recommended are up more than 8%, and three of them are up more than 20%. I think this momentum stock rebound will continue. As such, let\u2019s take a deeper look at five of my favorite momentum stocks that have shown impressive strength since mid-September. Momentum Stocks to Buy on the Rebound: The Trade Desk (TTD) Source: Shutterstock % Gain Since Sept. 16: 20% At one point in time, programmatic advertising leader The Trade Desk (NASDAQ:) was one of the biggest losers in the mid-2019 momentum-to-value shift. Shares had shed almost a quarter of their value by mid-September. But, since then, shares have soared 20%. This big rebound in TTD stock will persist for a few reasons. First, the long-term fundamentals are favorable here. Programmatic advertising is \u201csmart\u201d advertising, which leverages algorithms, data and machine learning to transform ad transactions and ad spend allocations from a guess-and-check process, to an automated and optimized process. The whole ad industry is pivoting into programmatic advertising, yet only a small portion of global ad dollars are transacted programmatically today. The Trade Desk is at the center of this pivot. Thus, as more ad dollars flow into the programmatic channel over the next few years, TTD\u2019s revenues and profits will continue to roar higher. Second, the valuation remains reasonable. By my numbers, The Trade Desk will net $12 in earnings per share by fiscal 2025, behind 20%-plus annual revenue growth, steady profit margin expansion and 25%-plus profit growth. Based on an exit multiple of 35-times forward earnings (which is average\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 = 0.0169 (i.e., a 1.69% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0169 = 5.9219, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016886, "expected_loss": 0.016886, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210210_0830", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2021-02-10", "context_summary": "MATIC-USD: 60-day history, VaR(99%)=-0.1770, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0349, std=0.1149, worst_day=-0.1846\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.5650", "answer_numeric": 0.565, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1770 (i.e., a 17.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1770 = 0.5650, capped at 1.0.\nMaximum position size = 0.5650 (56.5% of portfolio).", "metadata": {"var_99": -0.176982, "expected_loss": 0.176982, "max_drawdown_threshold": 0.1, "position_size": 0.565, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20181115_0832", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2018-11-15", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0277, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0000, std=0.0102, worst_day=-0.0297\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-11-14] [\"Apple stock swings lower after Goldman cuts target, another supplier slashes guidance Shares fall to 3 1/2-month low after seesaw session, suffer fourth straight decline Apple shares swung back to losses after a downbeat report from Goldman Sachs and another revenue warning from a supplier of smartphone components fueled concerns over deteriorating iPhone demand.\", \"Apple downgraded to neutral from buy at Guggenheim\", \"Apple's stock falls after Guggenheim downgrades, cuts earnings outlook Shares of Apple Inc. fell 0.4% in premarket trade Wednesday, which puts them in danger of a fifth-straight decline, after the technology giant was downgraded by analyst Rob Cihra at Guggenheim Securities, who said rising average selling prices (ASPs) was \\\"no longer enough\\\" to offset declining iPhone units. Cihra cut his fiscal 2019 earnings estimate to $12.97 a share from $13.41--the FactSet consensus is $13.44--and his revenue estimate to $273 billion from $281 billion. \\\"Over the past 10 years, Apple's iPhone ASP has increased a dramatic +$220, or 40%, reflecting its growing value to both consumer and business markets, but nearly half of all that just came in [fiscal year 2018] alone, making a period of digestion now likely,\\\" Cihra wrote in a note to clients. Apple's stock has tumbled 8.4% over the past four sessions to close at a 3 1/2-month low amid growing concerns over slowing iPhone demand. It was still up 13.6% year to date, while the Dow Jones Industrial Average has gained 2.3%.\", \"Oil, Apple, and More to Think About as the Dow Presses On Global equity markets are still under pressure. Worry over demand for Apple iPhones and the price of oil are dragging on stocks.\", \"Apple's stock turns higher, rallies 0.8% in premarket trade\", \"Apple\\u2019s iPhone Revenue Is Poised to Fall Next Year, Analyst Says Demand for iPhones is likely to fall next year, and Apple\\u2019s revenue from its key product is poised to decline, according to Guggenheim Securities.\", \"Here\\u2019s how to easily reduce your investment risk just at the right time Mike Loewengart of E-Trade discusses equal-weighted and bond ETFs, and actively managed funds for diversification Mike Loewengart of E-Trade discusses equal-weighted and bond ETFs, and actively managed funds for diversification.\", \"The Dow Sinks Because There\\u2019s More to Worry About Than Oil and Apple The Dow Jones Industrial Average was lower Wednesday as investors balanced largely positive news on inflation against Chinese data and worries about Brexit.\", \"Apple's stock falls 2.1%, as market-cap drops below $900 bln\", \"Podcast: PowerPoint Fatigue This week on The Readback, Alex Eule speaks with Al Root about the possible connection between the lenght of a company\\u2019s earnings presentation and its stock.\", \"These two chart patterns tell the real story of the stock market Bullish and bearish patterns are of low quality Bullish and bearish patterns are of low quality.\", \"Dow's 205-point drop marks longest skid for blue ch\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 = 0.0277 (i.e., a 2.77% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0277 = 3.6072, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027722, "expected_loss": 0.027722, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20170718_0835", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2017-07-18", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.1026, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0032, std=0.0456, worst_day=-0.1050\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9749", "answer_numeric": 0.9749, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1026 (i.e., a 10.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1026 = 0.9749, capped at 1.0.\nMaximum position size = 0.9749 (97.5% of portfolio).", "metadata": {"var_99": -0.102579, "expected_loss": 0.102579, "max_drawdown_threshold": 0.1, "position_size": 0.9749, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190329_0837", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2019-03-29", "context_summary": "EMB: 60-day history, VaR(99%)=-0.0057, max drawdown threshold=10%.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0011, std=0.0034, worst_day=-0.0066\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 = 0.0057 (i.e., a 0.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0057 = 17.3919, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.00575, "expected_loss": 0.00575, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20161005_0839", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2016-10-05", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0316, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0006, std=0.0134, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-10-04] [\"Software-As-A-Service Competition Heats Up For Microsoft\", \"Software-As-A-Service Competition Heats Up For Microsoft\", \"Tech Stock Roundup: MSFT Deals, CRM Objections, TWTR Buy It was an eventful week for tech stocks in general and Microsoft MSFT in particular. The software giant entered into important alliances with Adobe ADBE , Workday WDAY , Dell, HP Enterprise HPE and got attacked by Salesforce CRM . Here's a quick look at the top stories: Microsoft Deal Week: Adobe, Workday, Renault Microsoft's alliances last week were notable. HP Enterprise and Dell, which officially joined Azure last week at its Ignite Conference in Atlanta, have everything to gain from the alliance. That's because Microsoft is the only one of the top cloud infrastructure providers that continues to bet on the hybrid cloud. Unlike Amazon AMZN and Alphabet's GOOGL Google, Microsoft expects companies to initially (and perhaps also later) use the public cloud for some operations while housing some sensitive operations on owned hardware. Therefore an alliance with Microsoft brings together the companies that can make this happen. Also at Ignite, the company announced a major collaboration with Adobe that will have the PDF software maker run its Adobe Marketing Cloud, Adobe Creative Cloud and Adobe Document Cloud on Azure. In return, Microsoft will make Adobe's marketing cloud the preferred marketing service for Dynamics 365, its own CRM solution. The combination of sales software from Microsoft and marketing software from Adobe will help users run Microsoft analytics on Adobe-stored data, thus putting up some solid competition for Salesforce's Sales Cloud and Marketing Cloud. What's more, the companies will cross-promote products. While Adobe will continue to work with Amazon's AWS for customers that want it, Adobe CEO Shantanu Narayen has said, \\\"We're going to be focusing our innovation and efforts on Azure.\\\" The company's alliance with Workday, intended to roll out this quarter, is intended to integrate Workdays' HR and finance software with Microsoft's Office 365 productivity solutions. The combined resources are expected to help customers \\\"simplify their business processes, enhance collaboration, and infuse more intelligence into their organizations,\\\" according to Microsoft CEO Nadella. There will also be employee-related analytics, such as how employee time is used. Renault and Nissan, that have gotten together to develop self driving car technology have now chosen Microsoft's Azure to provide advanced navigation, predictive maintenance and vehicle centric services, remote monitoring of car features, external mobile experiences and over-the-air updates. They also intend to collaborate on next-generation connected services for cars that will be powered by Azure services. SalesForce Opposes Microsoft-LinkedIn Deal After losing out in the bidding war to acquire LinkedIn, Salesforce is now trying to do what's second best. The main concern for the company is LinkedIn's d\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 = 0.0316 (i.e., a 3.16% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0316 = 3.1667, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031578, "expected_loss": 0.031578, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220729_0842", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2022-07-29", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0335, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0001, std=0.0171, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K MSFT 2022-07-28] msft-10k_20220630.htm false FY 0000789019 --06-30 P10Y http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member http://fasb.org/us-gaap/2022#AccountingStandardsUpdate201601Member 0000789019 2021-07-01 2022-06-30 0000789019 us-gaap:CommonStockMember 2021-07-01 2022-06-30 xbrli:shares 0000789019 2022-07-25 iso4217:USD 0000789019 2021-12-31 iso4217:USD xbrli:shares 0000789019 msft:NotesThreePointOneTwoFivePercentDueDecemberSixTwentyTwentyEightMember 2021-07-01 2022-06-30 0000789019 msft:NotesTwoPointSixTwoFivePercentDueMayTwoTwentyThirtyThreeMember 2021-07-01 2022-06-30 0000789019 us-gaap:ProductMember 2021-07-01 2022-06-30 0000789019 us-gaap:ProductMember 2020-07-01 2021-06-30 0000789019 us-gaap:ProductMember 2019-07-01 2020-06-30 0000789019 us-gaap:ServiceOtherMember 2021-07-01 2022-06-30 0000789019 us-gaap:ServiceOtherMember 2020-07-01 2021-06-30 0000789019 us-gaap:ServiceOtherMember 2019-07-01 2020-06-30 0000789019 2020-07-01 2021-06-30 0000789019 2019-07-01 2020-06-30 0000789019 2022-06-30 0000789019 2021-06-30 0000789019 2020-06-30 0000789019 2019-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2021-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2020-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2019-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2021-07-01 2022-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2020-07-01 2021-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2019-07-01 2020-06-30 0000789019 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2022-06-30 0000789019 us-gaap:RetainedEarningsMember 2021-06-30 0000789019 us-gaap:RetainedEarningsMember 2020-06-30 0000789019 us-gaap:RetainedEarningsMember 2019-06-30 0000789019 us-gaap:RetainedEarningsMember 2021-07-01 2022-06-30 0000789019 us-gaap:RetainedEarningsMember 2020-07-01 2021-06-30 0000789019 us-gaap:RetainedEarningsMember 2019-07-01 2020-06-30 0000789019 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2021-06-30 0000789019 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2020-06-30 0000789019 us-gaap:RetainedEarningsMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2019-06-30 0000789019 us-gaap:RetainedEarningsMember 2022-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-07-01 2022-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2020-07-01 2021-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2019-07-01 2020-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2021-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2020-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember srt:CumulativeEffectPeriodOfAdoptionAdjustmentMember 2019-06-30 0000789019 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-06-30 0000789019 us-gaap:DebtSecuritiesMember 2021-07-01 2022-06-30 0000789019 us-gaap:EquitySecuritiesMember 2021-07-01 2022-06-30 0000789019 us-gaap:CashFlowHedgingMember us-gaap:OtherComprehensiveIncomeMember 2021-07-01 2022-06-30 0000789019 msft:NuanceCommunicationsIncMember 2021-07-01 2022-06-30 0000789019 msft:ZeniMaxMediaIncMember 2021-07-01 2022-06-30 0000789019 msft:ServerEquipmentMember us-gaap:ServiceLifeMember 2021-07-01 2022-06-30 0000789019 msft:ServerEquipmentMember us-gaap:ServiceLifeMember us-gaap:SubsequentEventMember 2022-07-01 2022-07-01 0000789019 msft:NetworkEquipmentMember us-gaap:ServiceLifeMember 2021-07-01 2022-06-30 0000789019 msft:NetworkEquipmentMember us-gaap:ServiceLifeMember us-gaap:SubsequentEventMember 2022-07-01 2022-07-01 0000789019 us-gaap:AllowanceForCreditLossMember 2021-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2020-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2019-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2021-07-01 2022-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2020-07-01 2021-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2019-07-01 2020-06-30 0000789019 us-gaap:AllowanceForCreditLossMember 2022-06-30 0000789019 msft:AccountsReceivableNetMember us-gaap:AllowanceForCreditLossMember 2022-06-30 0000789019 msft:AccountsReceivableNetMember us-gaap:AllowanceForCreditLossMember 2021-06-30 0000789019 msft:AccountsReceivableNetMember us-gaap:AllowanceForCreditLossMember 2020-06-30 0000789019 us-gaap:OtherNoncurrentAssetsMember us-gaap:AllowanceForCreditLossMember 2022-06-30 0000789019 us-gaap:OtherNoncurrentAssetsMember us-gaap:AllowanceForCreditLossMember 2021-06-30 0000789019 us-gaap:OtherNoncurrentAssetsMember us-gaap:AllowanceForCreditLossMember 2020-06-30 0000789019 srt:MinimumMember us-gaap:SoftwareAndSoftwareDevelopmentCostsMember 2021-07-01 2022-06-30 0000789019 us-gaap:SoftwareAndSoftwareDevelopmentCostsMember srt:MaximumMember 2021-07-01 2022-06-30 0000789019 srt:MinimumMember us-gaap:ComputerEquipmentMember 2021-07-01 2022-06-30 0000789019 us-gaap:ComputerEquipmentMember srt:MaximumMember 2021-07-01 2022-06-30 0000789019 srt:MinimumMember us-gaap:BuildingAndBuildingImprovementsMember 2021-07-0 [...TRUNCATED...] 60; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; 104 &#160; Cover page formatted as Inline XBRL and contained in Exhibit 101 &#160; X &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; * Indicates a management contract or compensatory plan or arrangement. ** Furnished, not filed. &#160; &#160; 107 PART IV Item 16 &#160; &#160; ITEM&#160;16. FORM 10-K SUMMARY None. &#160; &#160; 108 &#160; &#160; SIGNATURES Pursuant to the requirements of Section&#160;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&#59; thereunto duly authorized, in the City of Redmond, State of Washington, on July 28, 2022. &#160; M ICROSOFT C ORPORATION &#160; /s/ A LICE L. J OLLA Alice L. Jolla Corporate&#160;Vice&#160;President and Chief Accounting Officer (Principal Accounting Officer) &#160; 109 &#160; &#160; 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 28, 2022. &#160; Signature &#160; Title &#160; &#160; &#160; /s/&#160;S ATYA N ADELLA&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Satya Nadella &#160; Chairman and Chief Executive Officer (Principal Executive Officer) &#160; &#160; /s/&#160;R EID H OFFMAN &#160; &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Reid Hoffman &#160; Director &#160; &#160; /s/&#160;H UGH F. J OHNSTON &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Hugh F. Johnston &#160; Director &#160; &#160; /s/&#160; T ERI L. L IST &#160; Teri L. List &#160; Director &#160; &#160; /s/&#160; S ANDRA E. P ETERSON &#160; Sandra E. Peterson &#160; Director &#160; &#160; &#160; /s/&#160;P ENNY S. P RITZKER &#160; Penny S. Pritzker &#160; Director &#160; &#160; /s/&#160;C ARLOS A. R ODRIGUEZ &#160; Director Carlos A. Rodriguez &#160; &#160; &#160; &#160; /s/&#160; C HARLES W. S CHARF&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Charles W. Scharf &#160; Director &#160; &#160; /s/&#160; J OHN W. S TANTON&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; John W. Stanton &#160; Director &#160; &#160; &#160; /s/&#160;J OHN W. T HOMPSON&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Lead Independent Director John W. Thompson &#160; &#160; &#160; &#160; /s/&#160;E MMA N. W ALMSLEY&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Emma N. Walmsley &#160; Director &#160; &#160; /s/&#160; P ADMASREE W ARRIOR &#160; Padmasree Warrior &#160; Director &#160; &#160; /s/&#160;A MY E. H OOD&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160; Amy E. Hood &#160; Executive Vice President and Chief Financial Officer (Principal Financial Officer) &#160; &#160; /s/&#160;A LICE L. J OLLA &#160; Alice L. Jolla &#160; Corporate&#160;Vice&#160;President and Chief Accounting Officer (Principal Accounting Officer) &#160; &#160; 110\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 = 0.0335 (i.e., a 3.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0335 = 2.9889, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033457, "expected_loss": 0.033457, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}}
{"id": "T3_all_20190715_0846", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2019-07-15", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0188, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0010, std=0.0080, worst_day=-0.0220\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-12] [\"Tlwm Buys Marathon Petroleum Corp, UnitedHealth Group Inc, HCP Inc, Sells Invesco S&P ...\", \"Will Hot Growth Stocks Break Out From These 5 Leading Industry Groups?\", \"Tigress Financial Analyst Ivan Feinseth Comments On Semiconductors Strength, Tell Benzinga 'Positive trends in US-China trade negotiations is lifting all the chip stocks.'\", \"UPDATE: Cassidy Also Tells Benzinga 'Japan / Korea trade issues may drive up the prices of memory devices following a year of memory prices in free fall. Prices for memory increased w/w for the first time in over a year.'\", \"Stifel Nicolaus Analyst Kevin Cassidy On Semiconductors Strength, Tells Benzinga 'The fed signaling lower interest rates and Trump loosening the ban on Huawei are both huge news for semiconductor companies.'\", \"Shares of several semiconductor companies are trading higher amid positive trends in US-China trade negotiations, Trump loosening the Huawei ban and the Fed signaling a rate cut. Japan/Korea trade tensions could also drive up memory prices.\", \"Shares of several semiconductor companies are trading higher amid positive trends in US-China trade negotiations, Trump loosening the Huawei ban and the Fed signaling a rate cut. Japan/Korea trade tensions could also drive up memory prices.\", \"UPDATE: Cassidy Also Tells Benzinga 'Japan / Korea trade issues may drive up the prices of memory devices following a year of memory prices in free fall. Prices for memory increased w/w for the first time in over a year.'\", \"Stifel Nicolaus Analyst Kevin Cassidy On Semiconductors Strength, Tells Benzinga 'The fed signaling lower interest rates and Trump loosening the ban on Huawei are both huge news for semiconductor companies.'\", \"Tigress Financial Analyst Ivan Feinseth Comments On Semiconductors Strength, Tell Benzinga 'Positive trends in US-China trade negotiations is lifting all the chip stocks.'\", \"Tlwm Buys Marathon Petroleum Corp, UnitedHealth Group Inc, HCP Inc, Sells Invesco S&P ...\", \"Will Hot Growth Stocks Break Out From These 5 Leading Industry Groups?\", \"Shares of several semiconductor companies are trading higher amid positive trends in US-China trade negotiations, Trump loosening the Huawei ban and the Fed signaling a rate cut. Japan/Korea trade tensions could also drive up memory prices.\", \"UPDATE: Cassidy Also Tells Benzinga 'Japan / Korea trade issues may drive up the prices of memory devices following a year of memory prices in free fall. Prices for memory increased w/w for the first time in over a year.'\", \"Stifel Nicolaus Analyst Kevin Cassidy On Semiconductors Strength, Tells Benzinga 'The fed signaling lower interest rates and Trump loosening the ban on Huawei are both huge news for semiconductor companies.'\", \"Tigress Financial Analyst Ivan Feinseth Comments On Semiconductors Strength, Tell Benzinga 'Positive trends in US-China trade negotiations is lifting all the chip stocks.'\", \"Tlwm Buys Marathon Petroleum Corp, UnitedHealth Group Inc, HCP Inc, Sells Invesco S&P ...\", \"Will H\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 = 0.0188 (i.e., a 1.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0188 = 5.3284, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018768, "expected_loss": 0.018768, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150610_0848", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2015-06-10", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0146, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0003, std=0.0070, worst_day=-0.0161\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-06-09] Amgen's Repatha Briefing Document Gives Mixed Review - Analyst Blog Amgen Inc. 's AMGN PCSK9 inhibitor, Repatha (evolocumab), is set to face the FDA's Endocrinologic and Metabolic Drugs Advisory Committee (EMDAC) on Jun 10, 2015. The FDA released briefing documents ahead of the advisory committee's meeting. Amgen is looking to get Repatha approved for the treatment of adult patients suffering from primary (non-familial) or heterozygous familial hypercholesterolemia and patients \u226512 years with homozygous familial hypercholesterolemia. In its briefing documents, the FDA noted that both dosing regimens (140 mg once every 2 weeks/Q2W and 420 mg once monthly) of Repatha resulted in a statistically significant reduction in LDL-C (\"bad\" cholesterol) of approximately 60% after 12 and 52 weeks of treatment. But concerns have been raised regarding the appropriate patient population likely to benefit from this drug given the lack of safety and efficacy data for the 420 mg Q2W dose since this dosing regimen could potentially be used in children aged 12 years or older. Moreover, the FDA recommended that, if approved, potential safety issues, including pancreatitis, serious renal disorders and a possible increased incidence of new onset diabetes in certain patients should be adequately addressed in the drug's labeling and appropriately monitored by health care providers. The regulatory agency also mentioned that these issues should be comprehensively assessed in ongoing studies. We note that last month, Repatha had gained a positive opinion from the European Medicines Agency's Committee for Medicinal Products for Human Use recommending its approval in the EU for cholesterol management. PCSK9 inhibitors work by inhibiting PCSK9, a protein that reduces the liver's ability to remove \"bad\" cholesterol from the blood. However, Amgen is not the only company working on bringing a PCSK9 inhibitor to market. We remind investors that Sanofi SNY and Regeneron REGN are also seeking EU and U.S. approval for their PCSK9 inhibitor Praluent. The FDA's EMDAC is scheduled to review the candidate today. We note that the FDA action date for Praluent is Jul 24, which is ahead of the FDA action date of Aug 27 for Repatha. Investor focus will remain on the outcome of the FDA advisory panel meetings. Amgen currently carries a Zacks Rank #2 (Buy). Gilead Sciences GILD is also a well-ranked stock in the health care sector sporting a Zacks Rank #1 (Strong Buy). 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 >> 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 REGENERON PHARM (REGN): Free Stock Analysis Report SANOFI-AVENTIS (SNY): Free Stock Analysis Report GILEAD SCIENCES (GILD): Free Stock Analysis Report AMGEN INC (AMGN): Free Stock Analysis Report To read this article on Zac\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 = 0.0146 (i.e., a 1.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0146 = 6.8358, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014629, "expected_loss": 0.014629, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220314_0849", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2022-03-14", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0206, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0003, std=0.0103, worst_day=-0.0256\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-03-11] [\"Notable Friday Option Activity: UNH, ADBE, MCD Looking at options trading activity among components of the S&P 500 index, there is noteworthy activity today in UnitedHealth Group Inc (Symbol: UNH), where a total volume of 15,484 contracts has been traded thus far today, a contract volume which is representative of approximately 1.5 million underlying shares (given that every 1 contract represents 100 underlying shares). That number works out to 48.7% of UNH's average daily trading volume over the past month, of 3.2 million shares. Especially high volume was seen for the $440 strike put option expiring April 14, 2022, with 1,640 contracts trading so far today, representing approximately 164,000 underlying shares of UNH. Below is a chart showing UNH's trailing twelve month trading history, with the $440 strike highlighted in orange: Adobe Inc (Symbol: ADBE) options are showing a volume of 17,235 contracts thus far today. That number of contracts represents approximately 1.7 million underlying shares, working out to a sizeable 45.3% of ADBE's average daily trading volume over the past month, of 3.8 million shares. Especially high volume was seen for the $460 strike call option expiring March 18, 2022, with 1,226 contracts trading so far today, representing approximately 122,600 underlying shares of ADBE. Below is a chart showing ADBE's trailing twelve month trading history, with the $460 strike highlighted in orange: And McDonald's Corp (Symbol: MCD) saw options trading volume of 18,089 contracts, representing approximately 1.8 million underlying shares or approximately 44.8% of MCD's average daily trading volume over the past month, of 4.0 million shares. Especially high volume was seen for the $225 strike put option expiring March 11, 2022, with 1,147 contracts trading so far today, representing approximately 114,700 underlying shares of MCD. Below is a chart showing MCD's trailing twelve month trading history, with the $225 strike highlighted in orange: For the various different available expirations for UNH options, ADBE options, or MCD options, visit StockOptionsChannel.com. Today's Most Active Call & Put Options of the S&P 500 \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"Implied PWB Analyst Target Price: $84 Looking at the underlying holdings of the ETFs in our coverage universe at ETF Channel, we have compared the trading price of each holding against the average analyst 12-month forward target price, and computed the weighted average implied analyst target price for the ETF itself. For the Invesco Dynamic Large Cap Growth ETF (Symbol: PWB), we found that the implied analyst target price for the ETF based upon its underlying holdings is $83.61 per unit. With PWB trading at a recent price near $67.17 per unit, that means that analysts see 24.47% upside for this ETF looking through to the average analyst targets of the underlying holdings. Three\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 = 0.0206 (i.e., a 2.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0206 = 4.8571, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020589, "expected_loss": 0.020589, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190704_0854", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2019-07-04", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0202, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0003, std=0.0078, worst_day=-0.0228\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-07-03] [\"Why Microsoft Stock Owners Shouldn\\u2019t Worry About Linux Normally, a competitor\\u2019s increased presence, especially in one\\u2019s own turf, represents serious trouble. And under this context, consumer technology giant Microsoft (NASDAQ:) should be worried. Recently, a developer for the open-source platform Linux accidentally revealed that Linux-based operating systems had greater presence in Microsoft\\u2019s Azure cloud network than Microsoft-based OS\\u2019. Does this signal a dumping opportunity for Microsoft stock? Source: Shutterstock At first glance, the suddenly of Linux may startle stakeholders of Microsoft stock. After all, Linux is a free and open-source collaboration, meaning that it\\u2019s impossible to profit from its mere existence. Of course, that philosophy runs counter to Microsoft\\u2019s legacy revenue channels, where it sold programs and updates to those programs. By all accounts, it was an extremely profitable venture. But this latest bit of Microsoft news demonstrates that we\\u2019re no longer in the 20th century. And despite the optics, the Linux development is a long-term positive for MSFT stock. How so? Because MSFT is, when it comes to software-related ventures, moving firmly toward the Software as a Solution (SaaS) model. Not only that, but the rise of Linux helps shift the narrative to the concept that Microsoft stock will now trade on the fundamentals of service offerings, not standalone products. For management, it doesn\\u2019t really matter that Linux is the go-to choice for Azure users. For one thing, there\\u2019s the fact that Azure is cheaper to run on Linux than on any other platform. Even Microsoft benefited from Linux\\u2019s streamlined and efficient architecture to power its Internet of Things (IoT) devices. In other words, MSFT stock wins as long as Microsoft is somehow involved in the process. Office 2019 Offers Insight Into \\u201cNew\\u201d MSFT Stock When Microsoft 2019 launched during last year\\u2019s fall season, it many observers. By that time, the tech firm had decisively entered the SaaS arena, and for good reasons. Namely, SaaS makes perfect sense for MSFT stock on multiple levels. First, subscription-based models utilize an ongoing contractual relationship. While the subscriber has to pay constantly, they also have access to the SaaS entity\\u2019s service umbrella. Thus, when the need for updates arise \\u2014 and that need perpetually exists \\u2014 the platform automatically refreshes with relevant features. Second, the subscription model can quickly convert prospective buyers due to their much cheaper initial cost outlay. Once subs are on board, companies have greater chances to convert them to higher-margin services. Such strategies have rejuvenated Microsoft stock in the past. They\\u2019ve also done wonders for Adobe (NASDAQ:). So when MSFT launched Office 2019, the computing public viewed it as one of the strangest pieces of Microsoft news. Unlike Office 365, Office 2019 was not an SaaS plat\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 = 0.0202 (i.e., a 2.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0202 = 4.9469, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020215, "expected_loss": 0.020215, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180627_0856", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2018-06-27", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1176, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0055, std=0.0483, worst_day=-0.1190\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.8501", "answer_numeric": 0.8501, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1176 (i.e., a 11.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1176 = 0.8501, capped at 1.0.\nMaximum position size = 0.8501 (85.0% of portfolio).", "metadata": {"var_99": -0.117632, "expected_loss": 0.117632, "max_drawdown_threshold": 0.1, "position_size": 0.8501, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20180629_0858", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2018-06-29", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0258, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0004, std=0.0102, worst_day=-0.0274\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-06-28] [\"These top-rated funds reveal some of the world\\u2019s hottest tech stocks All have beaten the S&P 500 tech sector for five years, and the holdings include less well-known companies such as Walsin Technology and Sino-American Silicon Products All have beaten the S&P 500 tech sector for five years, and the holdings include less well-known companies such as Walsin Technology and Sino-American Silicon Products.\", \"Ocasio-Cortez withholds support of Pelosi as House speaker | Trump to officiate at Foxconn groundbreaking McConnell vows vote on Supreme Court nominee before midterm elections Alexandria Ocasio-Cortez withholds support for Nancy Pelosi as House speaker; President Trump will officiate at a Foxconn facility groundbreaking on Thursday; and more.\", \"Here\\u2019s how much stock investors could lose in a \\u2018zero-sum\\u2019 trade war Critical information for the U.S. trading day The trade-war talk isn\\u2019t slowing down and our call of the day says global stocks could be set back years if this spat blows up.\", \"Cody Willard: I have more cash and hedges today than at any time in the past decade A trade war will knock the economy off-kilter A trade war will knock the economy off-kilter.\", \"DC Entertainment to launch digital subscription service in August DC Entertainment has begun accepting sign-ups for a beta version of its digital subscription service, dubbed DC Universe, the company announced Thursday. The beta version will launch in August, and a full launch will follow later in the fall. DC Entertainment is a subsidiary of Time Warner Inc., which was recently acquired by AT&T and renamed WarnerMedia. The subscription service will give fans access to new live-action and animated series, previously-released TV series and films and a curated, rotating selection of digital comic books, the company said. The platform will feature a social-media element where fans can connect with each other, earn rewards and participate in sweepstakes and contests. There will be shopping opportunities, as well. DC has not announced pricing yet, but is planning to launch DC Universe on iOS, Android, Roku, Apple TV, Amazon Fire TV, Android TV and the web, the company said. Shares of AT&T have fallen 18.3% so far this year, while the S&P 500 has gained 1.3%.\", \"Tech Today: Google vs Amazon, Buying Tesla, Lattice\\u2019s Turnaround Amazon's acquisition of pharmacy startup PillPack freaks out pharmacy stocks while its offer to help start small delivery businesses could be key to Whole Foods' expansion, Alphabet's Google needs to give away its home speaker to combat Amazon according to Morgan Stanley analyst Brian Nowak, now is the time to buy Tesla stock ahead of next week's Model 3 numbers according to Baird's Brian Kallo, T-Mobile's chances of getting Sprint are looking a little better to Wells Fargo's Jennifer Fritzsche, Lattice semiconductor may bounce back with new management and activist input thinks Dougherty's Charles Anderson, Square is no Amazon so says SunT\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 = 0.0258 (i.e., a 2.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0258 = 3.8799, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025774, "expected_loss": 0.025774, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160512_0860", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-05-12", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0158, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0010, std=0.0095, worst_day=-0.0166\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-05-11] [\"WhatsApp launches desktop version for Mac, Windows Popular mobile messaging app rivals Skype, Apple\\u2019s iMessage WhatsApp, the massively popular smartphone messaging app owned by Facebook Inc., is now available in a familiar place: your computer\\u2019s desktop.\", \"Justice Inquiry Reveals Wall Street\\u2019s Dirty Secret Firms profit by trading against individual investors, who they consider \\u201cdumb money.\\u201d\", \"Neither Trump nor Clinton can do much for the job market Technology and demographics are driving change, and the best that politicians can do is help retrain displaced workers Technology and demographics are driving change, and the best that politicians can do is help retrain displaced workers, says Howard Gold.\", \"Axel Springer looks to U.S. for digital growth BERLIN--German media giant Axel Springer SE says its U.S.-focused push into digital media is starting to pay off. One of Europe's biggest digital publishers, the old-line tabloid giant was once known for its Bild and Die Welt newspapers. It has worked for years to shed its reliance on print and boost online revenue.\", \"Apple: iPhone Upgrades Slowing, Stock is \\u2018Range Bound,\\u2019 Says UBS UBS\\u2019s Steve Milunovich today reiterates a Buy rating on Apple (AAPL) shares, while trimming his price target to $115 from $120, writing that he\\u2019s trimming his estimates for Apple\\u2019s iPhone sales and profit after accepting the device is going to see longer upgrade cycles for the foreseeable future.His verdict on the shares: \\u201cThe stock is likely range bound for now with low multiples acting as downside support and lack of demand catalysts an upper ceiling.\\\"The company will benefit from some increase in upgrade sales in 2017, but only to match what happened in 2015:We now expect iPhone unit growth of about 4% in F17 with upgrade growth offsetting a decline in new users. Strong sales in F15 stole from F16 but upgrades should hit in F17 or F18. Earnings only get back to the F15 level in our model, so new products may be required to excite investors beyond a trade. Apple has both annuity and hardware hits aspects, but we think the best way to understand the company is as a platform deserving of valuation b\", \"Apple suppliers in Taiwan struggling amid weaker iPhone demand Taiwan Semiconductor faces slowdown due to weak demand for premium phones like the iPhone: Nikkei Apple\\u2019s A10 chip supplier Taiwan Semiconductor Manufacturing Co. faces a slowdown in the second-half of the year\", \"Apple: \\u2018Value Trap\\u2019 as Margins Come Under Pressure, Says Former Berenberg Analyst Adnaan Ahmad, who used to be a stock analyst with Berenberg Bank covering Apple (AAPL), until last year, today issues a missive to \\u2014 well, I\\u2019m not sure if he has clients at this point, but to anyone out there, in which he continues to press the deeply negative view of Apple shares, for which he offers a Sell rating and an $80 price target.Although the stock below $100 \\u2014 it\\u2019s at $\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 = 0.0158 (i.e., a 1.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0158 = 6.3382, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015777, "expected_loss": 0.015777, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181015_0862", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2018-10-15", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0292, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0001, std=0.0090, worst_day=-0.0327\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-10-12] [\"Here\\u2019s a dividend-investment strategy designed to outperform in down markets The Reality Shares DIVCON Leaders Dividend ETF screens for quality, based on the likelihood of large-cap companies raising payouts to shareholders The Reality Shares DIVCON Leaders Dividend ETF screens for quality, based on the likelihood of large-cap companies raising payouts to shareholders.\", \"All 30 Dow stocks rally premarket, led by Microsoft The 257-point rally in Dow Jones Industrial Average futures is unanimous early Friday, as all 30 components are trading higher in the premarket. Among the biggest gainers, shares of Microsoft Corp. ran up 2.9%, Visa Inc. climbed 2.6% and Cisco Systems Inc. rose 2.5%. The most active stock was Apple Inc.'s , which gained 2.3%. The Dow's bounce follows a 1,378-point drubbing the past two sessions. Microsoft's stock had shed 5.7% the past two sessions, as part of a sharp pullback in technology stocks.\", \"JPMorgan Jumps, Netflix Flies as Dow Steps Away From the Abyss The Nasdaq was up 1.7% as stocks like Microsoft, Fitbit and others got upgraded.\", \"How one investor sidestepped this week\\u2019s stock-market decline Holding cash and hedges protects you from losing money Holding cash and hedges protects you from losing money.\", \"Cody Willard: I\\u2019m adding Snap to the portfolio The shares have been hit so hard, it\\u2019s time to bite The shares have been hit so hard, it\\u2019s time to bite.\", \"Charting a dead-cat bounce, S&P 500 retests 200-day average from underneath Focus: 10-year yield tags 200-month moving average, Gold and gold miners take flight, Apple weathers the October downdraft, General Electric\\u2019s backdrop strengthens? U.S. stocks are higher early Friday, rising from deeply oversold conditions amid the damaging October market downdraft.\", \"Flanked by musicians, Trump signs music copyright bill into law Joined by Kid Rock, original Beach Boys member Mike Love, and other stars, President Trump signed the Music Modernization Act on Thursday to close loopholes in existing copyright legislation.\", \"Netflix Earnings Are Coming. Here\\u2019s What Matters As positive as the outlook for streaming video is, with tech stocks under fire investors will still focus on Netflix\\u2019s quarterly subscriber growth\", \"Netflix and PayPal Execs Brace for Earnings After Market Tumble A more candid earnings season looms. First up: Netflix, PayPal, and Lam Research.\", \"Stocks rally to close higher but log worst week since March S&P 500 snaps 6-day losing streak U.S. stock market rallies on Friday, with equities rising broadly in a partial rebound from a multiday rout that slashed about 1,400 points from the Dow Jones Industrial Average and left the Nasdaq on the precipice of a correction.\", \"Tech Stocks Could Rebound Again but the Risks Are Growing Tech stocks are likely to rebound after their latest drubbing, but the selloff suggests that investors are paying more attention to the sector\\u2019s challenges.\", \"The Momentum Trade Is D\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 = 0.0292 (i.e., a 2.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0292 = 3.4238, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029207, "expected_loss": 0.029207, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150306_0866", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2015-03-06", "context_summary": "IGOV: 46-day history, VaR(99%)=-0.0134, max drawdown threshold=10%.", "question": "Asset: IGOV\nDaily returns (past 46 days): mean=-0.0010, std=0.0052, worst_day=-0.0136\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 = 7.4428, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013436, "expected_loss": 0.013436, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20201130_0869", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2020-11-30", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0217, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0017, std=0.0107, worst_day=-0.0254\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-11-27] [\"Coronavirus Stock Investing: 4 Industry Transformations That Are Just Getting Started The coronavirus pandemic has changed the world. But it has also accelerated certain technological trends that investors should be tapped into. From automation to genomics, these advancements are here to stay and there are many growth stocks that are just getting started. ProShares' Executive Director of Thematic Investing Scott Helfstein sat down with The Motley Fool to dive into some of the intriguing stocks in their new ETF: ProShares MSCI Transformational Changes ETF (NYSEMKT: ANEW). He shared plenty of tips that all kinds of investors can apply to their own portfolios. 10 stocks we like better than ProShares Trust-ProShares MSCI Transformational Changes ETF When investing geniuses David and Tom Gardner have 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.* David and Tom just revealed what they believe are the ten best stocks for investors to buy right now... and ProShares Trust-ProShares MSCI Transformational Changes ETF 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 November 20, 2020 Corinne Cardina: Hi, everybody. I am Corinne Cardina. I'm the Bureau Chief of Healthcare and Cannabis on fool.com. Before we get started, I'd like our viewers to know we're using a question and answer service called Slido. You can open that up in your browser. There's also an app. Our code is MFLive. You can submit questions, upvote other people's questions for the ones you want to see answered. I'm so excited to welcome Scott Helfstein, like I just said, Executive Director, Thematic Investing at ProShares. Hi, Scott, how are you? Scott Helfstein: Hey, Corinne. I'm well. How are you? Cardina: I'm good. Fools, for the next 30 minutes we are going to talk about ProShares' new ETF. It is called ANEW. I'm going to drop the ticker in the chat, and it tackles four transformational changes that are being accelerated by COVID-19. Scott, can you give us the highlights of what those four transformational changes are? Helfstein: Sure. It really has to do with how we've spent our time and our lives have changed over the months of the pandemic, and if we think about the hours of our day, if we're fortunate enough, we work, we try and to take care of ourselves. The way we consume has changed, the way we connect has changed. How many of us had FaceTime or Facebook (NASDAQ: FB) apps open at holiday tables at some point in the last nine months? So really, what we wanted to do was put together a set of companies that really spoke to how our lives have changed, but more importantly, how those changes were already in place and were accelerating. Really, there's four of them that we focused on. The first is the future of work. So we have, for example, things like video conference, but we're also focused on how the chan\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 = 0.0217 (i.e., a 2.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0217 = 4.6003, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021738, "expected_loss": 0.021738, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210924_0871", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2021-09-24", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1041, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0125, std=0.0616, worst_day=-0.1163\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.9604", "answer_numeric": 0.9604, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1041 (i.e., a 10.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1041 = 0.9604, capped at 1.0.\nMaximum position size = 0.9604 (96.0% of portfolio).", "metadata": {"var_99": -0.104127, "expected_loss": 0.104127, "max_drawdown_threshold": 0.1, "position_size": 0.9604, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190912_0875", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2019-09-12", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0312, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0004, std=0.0106, worst_day=-0.0341\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-09-11] [\"Asian markets gain ahead of ECB meeting Nikkei, Hang Seng edge up as stocks in mainland China dip Asian markets mostly gained in early trading Wednesday, ahead of expected further monetary easing by the European Central Bank.\", \"Welcome to Borrower\\u2019s Paradise. How Long Can It Last? Stocks have returned to within a percent or two of their record highs, while bond yields have fallen to near-record lows, making equities\\u2019 valuations more attractive while also helping to fund share buybacks.\", \"Podcast: Apple Goes Head-to-Head With Netflix 3 numbers to help you navigate the market\\u2014in just two minutes.\", \"It\\u2019s \\u2018Too Soon to Bail\\u2019 on Apple, Amazon, and Other Top Tech Stocks For investors interested in the big FAANG tech stocks, it\\u2019s late in the game\\u2014but not too late to benefit, an analyst says.\", \"Apple iPhone event reveals a dramatic change in strategy Apple is now competing on price, after years of focusing on high margins One of the most surprising elements of Apple Inc.\\u2019s September iPhone launch was its aggressive pricing on many products, especially its new streaming service.\", \"Apple drops price on new iPhone 11, undercuts Netflix and Disney on streaming At annual event, Apple unveils three new iPhones, prices for streaming services Apple Inc. tried to make cameras the focus of its iPhone launch event on Tuesday, but the company\\u2019s most striking announcements concerned the prices of its phones and streaming offerings.\", \"Apple's stock gains 0.4% premarket after rising 1.2% on Tuesday\", \"Shift into value stocks could fuel a solid rally, says J.P. Morgan Critical information for the U.S. trading day J.P. Morgan quant strategists Marko Kolanovic and Bram Kaplan say this switch to value stocks seen lately could be promising.\", \"Apple stock price target raised to $250 from $240 at BofA Merrill Lynch\", \"Dow's nearly 75-point jump highlighted by gains for Apple Inc., Walgreens Boots shares\", \"Apple on the verge of reaching $1 trillion in market cap for first time in 10 months Shares of Apple Inc. rallied 1.7% toward a 10-month high in morning trading Wednesday, after rising 1.2% the previous sessions on the back of the technology behemoth's iPhone launch event. With the stock's recent rally, Apple is on the verge of getting back to being a trillion dollar company, something it hasn't been since Nov. 1, 2018; Apple's market capitalization is currently $995.4 billion. The stock only needs to rise another 0.5% to close at or above $221.28 for Apple's market cap to top $1 trillion, based on the latest disclosed 4.52 billion shares outstanding as of July 19. Getting back to being a trillion-dollar company would complete a recovery from a market-cap low of about $672.5 billion on Jan. 3, when the stock closed at a 21-month low of $142.19. Since then, Apple's stock has run up 55%, while the Dow Jones Industrial Average has gained 19%. Apple's market cap is still behind first-place Microsoft Corp. at $1.04 trilli\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 = 0.0312 (i.e., a 3.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0312 = 3.2004, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031246, "expected_loss": 0.031246, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200203_0878", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2020-02-03", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0186, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=-0.0000, std=0.0060, worst_day=-0.0209\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-01-31] [\"Why it can pay to buy the stocks of companies you love to hate Start your search for diamonds in the rough by looking through the list of the most despised companies Start your search for diamonds in the rough by looking through the list of the most despised companies.\", \"Amazon\\u2019s record holiday sales send stock soaring toward $1 trillion valuation Amazon demolishes its own disappointing forecast and returns to earnings growth after previous quarter's decline Amazon.com Inc. defied its own disappointing forecast and returned to earnings growth in the holiday quarter with more than $3 billion in profit, sending shares soaring toward a $1 trillion valuation in the extended session Thursday.\", \"One Medical is going public: 5 things to know about the primary-care startup The pitch is convenience, as company looks to \\u2018delight\\u2019 working-age adults who get health insurance through their jobs and live in urban centers like New York City and San Francisco One Medical, a direct primary-care provider, has filed for its initial public offering, trading under the name 1Life Healthcare Inc.\", \"Amazon Soars to $1 Trillion Value After Earnings Crush Estimates Amazon reported fourth-quarter earnings $6.47 a share, versus analysts\\u2019 $4.03 estimate.\", \"McDonald\\u2019s is acting more like a FAANG, and investors should love it Here\\u2019s why the stock price should climb Here\\u2019s why the stock price should climb.\", \"Amazon's stock surges to set new all-time intraday high after blowout earnings Shares of Amazon.com Inc. rocketed to a new intraday record before paring some gains, but was still on track to leapfrog Google-parent Alphabet Inc. into third place as the largest U.S. company based on market capitalization after the e-commerce and cloud giant reported blowout fourth-quarter results. The was up as much as 9.9% to an intraday high of $2,055.72, above the previous intraday record of $2,050.50 on Sept. 4, 2018. The stock, now up 8.1%, is currently below the Sept. 4, 2018 record close of $2,039.51. The market cap is at $1.002 trillion, fractionally above Alphabet's, but still well below Microsoft Corp. at $1.306 trillion and Apple Inc. at $1.402 trillion.\", \"MedMen\\u2019s Colorful Pioneer of Cannabis, Adam Bierman, Resigns as CEO The chief executive\\u2019s lavish spending antagonized colleagues and torched bonfires of cash, dropping MedMen stock nearly 90% in the past year.\", \"Google-parent Alphabet's stock falls enough to knock market cap below the trillion-dollar mark Shares of Google-parent Alphabet Inc. dropped 1.4% in midday trading, putting the internet giant in danger of dropping out of the trillion-dollar club for the second time since it joined two weeks ago. Alphabet's market capitalization was now at $989.4 billion, which currently makes it the fourth-most valuable U.S. company. Amazon.com Inc. leapfrogged Alphabet to third place on Thursday, as the e-commerce and cloud giant's stock soared 8.9% to lift the market cap to $1.01 tri\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 = 0.0186 (i.e., a 1.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0186 = 5.3644, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018641, "expected_loss": 0.018641, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200601_0881", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2020-06-01", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0607, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0109, std=0.0436, worst_day=-0.0691\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0607 (i.e., a 6.07% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0607 = 1.6482, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060673, "expected_loss": 0.060673, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20151028_0883", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2015-10-28", "context_summary": "ITB: 60-day history, VaR(99%)=-0.0447, max drawdown threshold=10%.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=-0.0004, std=0.0171, 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 = 0.0447 (i.e., a 4.47% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0447 = 2.2356, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.04473, "expected_loss": 0.04473, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220531_0885", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2022-05-31", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0337, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0009, std=0.0153, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-05-27] [\"5 Growth Stocks For Your June 2022 Watchlist Are These The Best Growth Stocks To Buy Right Now? There\\u2019s no question that the stock market has taken quite a beating in recent months. And many of the top growth stocks are down along with it. Thus, some may find investing in these growth names less appealing compared to when the pandemic first started. Now, with the Fed taking a more aggressive stance on both interest rate hikes and tapering, it\\u2019s natural that investors are bearish on these stocks. But that doesn\\u2019t mean these are not great investments. Perhaps, what you need is a longer investment horizon. Investing in growth stocks involves having a long-term mindset. And adopting a long-term mindset will help you sift through the noise in the stock market and focus on the underlying business instead of the volatility of stock prices. With so much uncertainty continuing to loom over the stock market today, finding the best growth stocks to buy can be challenging. With the Nasdaq solidly in bear market territory and the S&P 500 dipping more than 15% from its record high, would now be a good time to put money into these stocks? If you believe so, here are five growth stocks to watch right now. Growth Stocks To Watch In June 2022 NVIDIA Corporation (NASDAQ: NVDA) Shopify Inc. (NYSE: SHOP) Sea Ltd. (NYSE: SE) Upstart Holdings Inc. (NASDAQ: UPST) Adobe Inc. (NASDAQ: ADBE) Nvidia When looking for top growth stocks to buy, graphics specialist Nvidia would often come to mind. The semiconductor giant reported better-than-expected figures earlier this week. From the latest quarterly report, revenue came in 46% higher at $8.29 billion. While the growth rate is lower than the previous quarter\\u2019s 53%, revenue still beat expectations of $8.1 billion. All in all, the company cites continuous strength in its gaming section. In detail, sales were driven by the GeForce RTX 30 Series, which remains the company\\u2019s best gaming product cycle in history. What\\u2019s more, reports said Cathie Wood purchased nearly 250,000 shares of NVDA stock across three ETFs, with the bulk of shares going towards her flagship fund. If anything, her latest investment in Nvidia may signal that this may be a good time to initiate a position for a long-term hold. Considering the upbeat quarter and Wood\\u2019s latest investment, would you be doing the same? [Read More] Best Stocks To Invest In Right Now? 5 Value Stocks To Watch This Week Shopify E-commerce innovator Shopify emerged as the pandemic darling, but its first-quarter report sent its shares falling. But before we give this stock a pass, let\\u2019s take a closer look at the most recent fiscal report. For the quarter, revenue came in 22% higher year-over-year to $1.2 billion. Additionally, its monthly recurring revenue also improved to $105.2 million, up 17% year-over-year. Admittedly, these figures may not be as exhilarating as those during the early stages of the pandemic. However, it does not change the fa\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 = 0.0337 (i.e., a 3.37% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0337 = 2.9659, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033716, "expected_loss": 0.033716, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200427_0889", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["CPER"], "decision_date": "2020-04-27", "context_summary": "CPER: 60-day history, VaR(99%)=-0.0392, max drawdown threshold=10%.", "question": "Asset: CPER\nDaily returns (past 60 days): mean=-0.0009, std=0.0165, worst_day=-0.0392\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CPER, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0392 (i.e., a 3.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0392 = 2.5519, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.039186, "expected_loss": 0.039186, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220215_0891", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2022-02-15", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1358, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0087, std=0.0523, worst_day=-0.1589\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-02-14] \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": "0.7363", "answer_numeric": 0.7363, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1358 (i.e., a 13.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1358 = 0.7363, capped at 1.0.\nMaximum position size = 0.7363 (73.6% of portfolio).", "metadata": {"var_99": -0.135818, "expected_loss": 0.135818, "max_drawdown_threshold": 0.1, "position_size": 0.7363, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20161228_0893", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2016-12-28", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0153, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0017, std=0.0097, worst_day=-0.0184\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-12-27] The Zacks Analyst Blog Highlights: IBM, BP, Disney, Adobe and Cisco For Immediate Release Chicago, IL - December 27, 2016 - 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 IBM (NYSE: IBM - Free Report ), BP (NYSE: BP - Free Report ), Disney (NYSE: DIS - Free Report ), Adobe (NASDAQ: ADBE - Free Report ) and Cisco (NASDAQ: CSCO - Free Report ). Today, Zacks is promoting its ''Buy'' stock recommendations. Get #1Stock of the Day pick for free. Here are highlights from Friday's Analyst Blog: Stock Research Reports for Tuesday: IBM, BP, DIS Today's Research Daily features new research reports on 16 major stocks, including IBM (NYSE: IBM - Free Report ), BP (NYSE: BP - Free Report ) and Disney (NYSE: DIS - Free Report ). IBM shares lagged the technology space and the S&P 500 index over the last few years as the company struggled to reposition its business to the evolving business landscape. But the stock turned around this year (up +21.4% in the year-to-date period vs. +9.3% for the Zacks Technology sector) on greater appreciation for the company's outlook. The Zacks analyst likes IBM's strategic growth initiatives, including its Big Data & business analytics, cloud computing, mobile and social business. The company is expected to report Q4 results on January 17th. (You can read the full research report on IBM here >>> ) The turnaround in oil prices this year has benefited all oil players, BP included. BP shares have gained in excess of +18% this year, modestly below the Zacks Oil Integrated industry's +19.1% gain. The Zacks analyst likes the company's major expense reductions over the last four quarters, which is expected to remain a focus in the coming quarters as well. BP is scheduled to report Q4 results on February 7th, with the oil giant expected to report $0.50 per share on $52.2 billion in revenues. While upstream volumes are expected to be modestly up from the Q3 level, the refining business could be under pressure. (You can read the full research report on BP here >>> ) Disney shares have struggled this year, weighed down by concerns about ESPN whose future growth has been clouded by the evolving media landscape as a result of 'cord cutting' and the steady migration of subscribers to online and digital platforms. However, management anticipates reporting modest earnings growth in fiscal 2017 and a \"more robust growth\" in fiscal 2018. The Zacks analyst likes Disney's movie business and the parks & resorts division. The company is expected to report Q4 results on February 14th. (You can read the full research report on Disney here >>> ) Other noteworthy reports we are featuring today include Adobe (NASDAQ: ADBE - Free Report ) and Cisco (NASDAQ: CSCO - Free Report ). You can check all of today's research reports here >>> Today's Long-Term Buys & Sells Today \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 = 0.0153 (i.e., a 1.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0153 = 6.5514, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015264, "expected_loss": 0.015264, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150814_0895", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2015-08-14", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0227, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0018, std=0.0094, worst_day=-0.0236\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-08-13] [\"Earnings Scheduled For August 13, 2015\", \"10 Stocks You Should Be Watching Today\", \"Option Alert: Applied Materials Sep $18 Call; 2000 Contracts @Ask @$0.32; Now $17.04\", \"Applied Materials Reports Q3 Adj. EPS $0.33, Inline, Sales $2.49B vs $2.54B Est.\", \"Applied Materials Expecting Q4 Adj. EPS $0.27-$0.31 vs $0.33 Est.\", \"UPDATE: Applied Materials Sees Q4 Sales Down 7% to Flat QoQ\", \"Nordstrom, El Pollo LoCo, King Digital Lead Thursday's After-Hours\", \"Applied Materials Posts In-Line Q3 Earnings, But Sales Miss Estimates\", \"Applied Materials Posts In-Line Q3 Earnings, But Sales Miss Estimates\", \"Nordstrom, El Pollo LoCo, King Digital Lead Thursday's After-Hours\", \"UPDATE: Applied Materials Sees Q4 Sales Down 7% to Flat QoQ\", \"Applied Materials Expecting Q4 Adj. EPS $0.27-$0.31 vs $0.33 Est.\", \"Applied Materials Reports Q3 Adj. EPS $0.33, Inline, Sales $2.49B vs $2.54B Est.\", \"Option Alert: Applied Materials Sep $18 Call; 2000 Contracts @Ask @$0.32; Now $17.04\", \"10 Stocks You Should Be Watching Today\", \"Earnings Scheduled For August 13, 2015\", \"Interesting AMAT Put And Call Options For October 2nd Investors in Applied Materials, Inc. (Symbol: AMAT) saw new options begin trading today, for the October 2nd expiration. At Stock Options Channel , our YieldBoost formula has looked up and down the AMAT options chain for the new October 2nd contracts and identified one put and one call contract of particular interest. The put contract at the $17.00 strike price has a current bid of 68 cents. If an investor was to sell-to-open that put contract, they are committing to purchase the stock at $17.00, but will also collect the premium, putting the cost basis of the shares at $16.32 (before broker commissions). To an investor already interested in purchasing shares of AMAT, that could represent an attractive alternative to paying $17.17/share today. Because the $17.00 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 55%. 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 4.00% return on the cash commitment, or 29.20% annualized - at Stock Options Channel we call this the YieldBoost . Below is a chart showing the trailing twelve month trading history for Applied Materials, Inc., and highlighting in green where the $17.00 strike is located relative to that history: Turning to the calls side of the option chain, the call contract at the $17.50 strike price has a current bid of 55 cents. If an investor was to purchase shares of AMAT stock at the current price level of $17.17/share, and\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 = 0.0227 (i.e., a 2.27% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0227 = 4.3991, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022732, "expected_loss": 0.022732, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200603_0897", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2020-06-03", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0399, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0017, std=0.0227, worst_day=-0.0399\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-02] [\"American Pie\", \"Tech Giants Dare Antitrust Deal Watchdogs\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Apple Cuts iPhone Prices in China To Push Sales As Country Reopens Economy\", \"Pepper Spray, Books On Racism, 'I Can't Breathe' Merchandise Are Top Sellers On Amazon As Protests Rage\", \"A Peek Into The Markets: US Stock Futures Up; Crude Oil Rises Over 2%\", \"Tesla CEO Musk Says Other Three Officers Should Be Charged In Floyd's Murder Case\", \"Hearing Susquehanna Check Suggests Total iPhone 12 Builds Tracking To 10M, Below Firm's Expectation Of 25M; Unconfirmed\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"'Apple is tracking iPhones stolen by looters' -Earlier NY Post Article\", \"'Apple is tracking iPhones stolen by looters' -Earlier NY Post Article\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Hearing Susquehanna Check Suggests Total iPhone 12 Builds Tracking To 10M, Below Firm's Expectation Of 25M; Unconfirmed\", \"Tesla CEO Musk Says Other Three Officers Should Be Charged In Floyd's Murder Case\", \"A Peek Into The Markets: US Stock Futures Up; Crude Oil Rises Over 2%\", \"Pepper Spray, Books On Racism, 'I Can't Breathe' Merchandise Are Top Sellers On Amazon As Protests Rage\", \"American Pie\", \"Tech Giants Dare Antitrust Deal Watchdogs\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"'Apple is tracking iPhones stolen by looters' -Earlier NY Post Article\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Hearing Susquehanna Check Suggests Total iPhone 12 Builds Tracking To 10M, Below Firm's Expectation Of 25M; Unconfirmed\", \"Tesla CEO Musk Says Other Three Officers Should Be Charged In Floyd's Murder Case\", \"A Peek Into The Markets: US Stock Futures Up; Crude Oil Rises Over 2%\", \"Pepper Spray, Books On Racism, 'I Can't Breathe' Merchandise Are Top Sellers On Amazon As Protests Rage\", \"American Pie\", \"Tech Giants Dare Antitrust Deal Watchdogs\", \"MoneyGram Shares Jump 50% As Western Union Reportedly Looks For Acquisition\", \"Here\\u2019s why the \\u2018unloved but welcome\\u2019 U.S. stock market rally from March lows won\\u2019t last, Goldman says Brief hopes that U.S.-China trade tensions may subside appear to have been dashed.\", \"Apple's stock slips 0.3% premarket, reversing earlier gains of as much as 0.7%\", \"How Apple Could Soar to a Valuation of $2 Trillion Apple is the world\\u2019s most highly valued company, with a market capitalization of $1.389 trillion. It is near the record closing level of $327.20 it hit in February, but Evercore ISI analyst Amit Daryanani thinks the stock can go higher.\", \"A semiconductor \\u2018cold war\\u2019 is heating up between the U.S. and China The world runs on semiconductors, most of which pass through Taiwan The world runs on semiconductors, most of which pass through Taiwan.\", \"Why Protests Rarely Rattle Markets The U.S. is experiencing painful civil\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 = 0.0399 (i.e., a 3.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0399 = 2.5054, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.039913, "expected_loss": 0.039913, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180807_0900", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2018-08-07", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0962, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0411, worst_day=-0.1114\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0962 (i.e., a 9.62% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0962 = 1.0397, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.096183, "expected_loss": 0.096183, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220606_0902", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2022-06-06", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1755, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0078, std=0.0682, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-06-05] \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": "0.5698", "answer_numeric": 0.5698, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1755 (i.e., a 17.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1755 = 0.5698, capped at 1.0.\nMaximum position size = 0.5698 (57.0% of portfolio).", "metadata": {"var_99": -0.1755, "expected_loss": 0.1755, "max_drawdown_threshold": 0.1, "position_size": 0.5698, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20191211_0904", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2019-12-11", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0209, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0012, std=0.0081, worst_day=-0.0213\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-12-10] Beware the Valuation Risks of Red-Hot DocuSign Stock E-signature pioneer DocuSign (NASDAQ:) delivered strong third-quarter earnings in early December. In response, DOCU stock rallied to all-time highs. Source: Sundry Photography / Shutterstock.com Everything in the report looked great. The company\u2019s customer growth was robust, as more and more businesses around the globe start to digitize and automate their contracts. The company\u2019s revenue growth was even more robust, as DocuSign\u2019s \u201cfoot in the door and grow\u201d model is working, and current customers are spending more on DocuSign\u2019s suite of Cloud Agreement products. Its gross margins held steady at an impressive 80%, while its strong revenue growth increased its profitability. As a result, its third-quarter profit was sizable, versus its tiny profit during the same period a year earlier. On top of all that, the company provided healthy Q4 guidance which indicated that all of these positive dynamics will persist into the end of the year. In other words, the 7% pop of DOCU stock after the Q3 results made sense, right? After all, its numbers were great, its growth outlook is healthy, and all signs point to \u201cGO\u201d\u2026 right? Wrong. While DocuSign is a great company and DOCU stock is a long-term winner, there is one big red flag now which warrants caution. That red flag is the valuation of DocuSign stock. I understand DOCU is a growth company that deserves a premium valuation. But, even aggressively assuming that the company will grow rapidly for the next decade, it\u2019s still tough to justify the current price of DOCU stock. As a result, I think DOCU stock is riddled with valuation risks. The stock may brush off those risks in the near-term, thanks to the momentum from its earnings. But, at some point, these risks will rear their ugly head. DocuSign Is a Great Company To be clear, I think DocuSign is a great company. The whole growth outlook of DocuSign centers around the digitization and automation of the contract process. That is, the traditional contract process involves a ton of paper (which is bulky and sometimes costly) and requires that paper to be sent back and forth between various parties multiple times In other words, the traditional contractual process is antiquated, lengthy, and costly. DocuSign fixes all those problems by digitizing and automating the contract process. Among other things, it makes all the documents and the signing process digital, eliminating all the paper involved in those processes. DOCU also transforms the transit, record-keeping, and enforcement of contracts into digital processes. It basically makes the whole contractual process digital, causing it to become modern, fast, and affordable. For corporations, that\u2019s a good deal. That\u2019s why DocuSign has grown its enterprise and commercial customer base from 23,000 in 2015 to what will be north of 70,000 by the end of 2019. Still, at 70,000, DocuSign\u2019s customer base pales in comparison to the millions of businesses in the world, s\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 = 0.0209 (i.e., a 2.09% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0209 = 4.7823, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02091, "expected_loss": 0.02091, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20161012_0906", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2016-10-12", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0016, std=0.0094, worst_day=-0.0375\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-10-11] [\"Why Samsung Could Hit Record Profit Even If It Terminates Galaxy Note 7 Samsung Electronics (005930.Korea/SSNLF) said on Monday that it would stop selling Galaxy Note 7 phones worldwide and advised consumers to \\\"power down and stop using the device\\\" as the company investigates its new flagship phone's production issues. Computer science experts now question if Galaxy Note 7's problem goes beyond faulty lithium-ion batteries.READ MORE.\", \"Don\\u2019t go into debt to pay for these 5 things Going into debt for material things isn\\u2019t going to change your life In some cases, borrowing money helps build wealth. Most people need a mortgage to buy a home, for instance, and student loans allow many people get an education that leads to a career.\", \"Apple's stock climbs 1.2% in premarket trade\", \"Apple's stock on track to open at highest level since Dec. 9, 2015\", \"Who can save Twitter? Only a Wall Street barbarian Critical information before the U.S. market\\u2019s open The rustle of crisp sell orders, the gabble of analysts defending their overly rosy calls \\u2014 it\\u2019s earnings season again, with Alcoa kicking it off. It\\u2019s also still peak season for guessing at what\\u2019s next for Twitter. Bankers should buy it, today\\u2019s call says.\", \"Apple's stock extends gain, rises 1.9% premarket as it heads for sixth-straight gain\", \"How to keep your smartphone from exploding Smartphone battery explosions are rare, but there are steps you can take to keep it from happening Jurica Dujmovi\\u0107 says smartphone battery explosions are rare, but there are steps you can take to keep it from happening.\", \"Apple Inc. shares jump 2.1% at $118.50 to lead Dow gainers as Samsung terminates Galaxy Note 7\", \"Apple Rising: Samsung \\u2018Note 7\\u2032 Collapse Means Another 8M iPhone 7 Sales, Says Drexel Samsung Electronics\\u2019s (005930KS) pain with its \\\"Note 7\\\" \\u2014 it first said it would stop making them, temporarily, and subsequently said it would permanently stop production of the device \\u2014 continues to be Apple\\u2019s (AAPL) gain, according to Drexel Hamilton\\u2019s Brian White.White, who has a Buy rating on Apple shares, and a $185 price target, thinks Apple could pick up 8 million more units of iPhone sales before this calendar year is out, thanks to the Note 7\\u2019s collapse:With original market expectations for approximately 10-14 million Galaxy Note 7 units in H2:2016 (availability began on August 19), we believe Apple has an opportunity to pick up at least 8 million incremental units in CY:16. Moreover, this fiasco could permanently damage the Samsung brand in the smartphone market, a big opportunity for Apple to gain market share.\", \"Twitter could sell for up to $15 billion, if there\\u2019s still a buyer Salesforce could still be a buyer, reports say Amid rumors that Twitter\\u2019s buyers may have backed out of the bidding process, an analyst from Monness, Crespi, Hardt is putting the lingering possibility of a sale at $11 billion to $15 b\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 = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7257, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02684, "expected_loss": 0.02684, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181106_0908", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2018-11-06", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0303, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0004, std=0.0098, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-11-05] [\"When the going gets tough, Apple hides its numbers Apple will stop reporting unit sales for its largest businesses as iPhone sales stall Apple Inc. dropped a bomb on Thursday, but it wasn\\u2019t the weak forecast for the holiday quarter: It was the fact that it will no longer disclose unit sales of its products for investors, as it has for more than a decade.\", \"Apple predicts record holiday sales, but that isn\\u2019t enough to save stock Apple falls in late trading despite earnings beat, thanks to forecast that appears cautious for several reasons Apple Inc. revealed a blockbuster September quarter Thursday and predicted record revenue for the holiday season. That wasn\\u2019t good enough for investors, though.\", \"Apple stock suffers worst day in more than four years after \\u2018Houdini-like move\\u2019 with earnings \\u2018The uncertainty that speculation breeds is rarely positive,\\u2019 BTIG writes of decision to eliminate unit-sales disclosures Apple shares dropped Friday, after the smartphone manufacturer beat expectations with its latest results but delivered a disappointing forecast and announced that it would no longer be providing unit-sales figures for the iPhone and other hardware products.\", \"Apple's stock falls 0.9% premarket, after tumbling 6.6% on Friday\", \"In sweeping interview, Elon Musk says Tesla will be cash-flow positive \\u2018all quarters going forward\\u2019 \\u2018Some people use their hair to express themselves; I use Twitter,\\u2019 Musk says Up until September, it was do or die for Silicon Valley car maker, Elon Musk says.\", \"Apple curbs plans for additional iPhone XR production lines: report Apple Inc. has told companies that assemble its smartphones to halt plans for new production lines that would add iPhone XR capacity, the Nikkei Asian Review reported Monday. The report, which cites multiple unnamed sources, said that Apple has given these instructions to Hon Hai Precision Industry Co. Ltd. , better known as Foxconn, and Pegatron. Apple increased orders for the iPhone 8 and iPhone 8 Plus, two cheaper devices that launched a year ago, according to sources. The report comes a few days after Apple delivered a disappointing December-quarter earnings outlook and disclosed that it would stop reporting unit-sales figures for its various product lines. The company didn't immediately respond to a MarketWatch request for comment. Apple shares are off 1.6% in premarket trading, and they're down 7.5% over the past month. The Dow Jones Industrial Average has slipped 4.5% in that time.\", \"Berkshire Hathaway Climbs, but Dow Slips Because Even Warren Buffett Can\\u2019t Lift the Market by Himself U.S. stocks weakened ahead of the open as jitters continue despite an earnings season that is turning out to be more or less as good as in the second quarter.\", \"Amazon discussions fuel speculation that northern Virginia is \\u2018HQ2\\u2019 front runner Sources say detailed talks have focused on Crystal City, Va. Sources tell the Washington Pos\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 = 0.0303 (i.e., a 3.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0303 = 3.2962, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030338, "expected_loss": 0.030338, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180330_0910", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2018-03-30", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1825, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0049, std=0.1053, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-03-29] [\"Can the stock market stand up to the tech wreck? Bull market loses its leader The key question for investors is whether a sharp selloff in tech shares puts the broader bull market in danger.\", \"How to know when to buy, sell or hold popular tech stocks today Amid increasing volatility, investors need to understand position size, time horizon and diversification Amid increasing volatility, investors need to understand position size, time horizon and diversification.\", \"Smart Home Devices: These Categories Are Growing the Fastest As new categories emerge, smart speakers are still expected to grow quickly.\", \"Spotify initiated at outperform by RBC ahead of trading debut RBC Capital Markets analyst Mark Mahaney initiated shares of Spotify Technology with an outperform rating and $220 price target, ahead of the stock's expected public debut in early April. Mahaney's target price represents \\\"70%+ upside vs. recent private transaction price of $127.50,\\\" he wrote. He likes the large total addressable market for music-streaming services and Spotify's leading position in the market. The Consumer Technology Association believes consumers will spend $6.6 billion on music streaming services in 2018. Spotify has nearly twice as many paid subscribers as Apple Inc.'s Apple Music does. \\\"Very high global aided brand awareness, relatively high customer satisfaction scores, and superior data-driven personalization all combine to help Spotify maintain its leadership position,\\\" Mahaney wrote. As for Spotify's financials, he believes gross margin can expand from 21% in 2017 to upwards of 30% by 2022. He also points to declining churn rates.\", \"Will a robot care for you in your old age? The great potential\\u2014and challenges\\u2014 of artificial intelligence for an aging population Realizing AI\\u2019s possibilities will require businesses to make it less expensive and for health care providers to embrace it.\", \"Nearly a billion smart home devices will ship in 2022, says IDC Market research firm IDC said Thursday that it expected shipments of smart home devices to grow at an 18.5% annual clip over the next five years, ultimately reaching 940 million devices shipped by 2022. Shipments of smart speakers will grow even faster over that period, IDC said, at a 32% annual rate. \\\"While it's still early days for the smart home market - and the wider consumer IoT ecosystem in general - we expect to see considerable growth over the next few years, especially as consumers become more aware of and increasingly interact with smart assistant platforms like Amazon's Alexa and [Alphabet Inc.'s ] Google Assistant,\\\" IDC senior research analyst Adam Wright said in a release. Amazon's Echo family of speakers is thought to be the market leader. Apple Inc. recently came out with its $349 HomePod speaker and will look to capture share of the market. Apple shares are up 18% over the past 12 months, while the Dow Jones Industrial Average has gained 17%.\", \"Apple\\u2019s Cook Has Pointed Ad\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": "0.5480", "answer_numeric": 0.548, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1825 (i.e., a 18.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1825 = 0.5480, capped at 1.0.\nMaximum position size = 0.5480 (54.8% of portfolio).", "metadata": {"var_99": -0.182471, "expected_loss": 0.182471, "max_drawdown_threshold": 0.1, "position_size": 0.548, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160426_0913", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2016-04-26", "context_summary": "JNK: 60-day history, VaR(99%)=-0.0102, max drawdown threshold=10%.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=0.0013, std=0.0061, worst_day=-0.0121\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 = 0.0102 (i.e., a 1.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0102 = 9.8033, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010201, "expected_loss": 0.010201, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20180517_0916", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2018-05-17", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0212, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0006, std=0.0094, 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 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 = 0.0212 (i.e., a 2.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0212 = 4.7159, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021205, "expected_loss": 0.021205, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20180709_0918", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2018-07-09", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0146, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=-0.0008, std=0.0054, worst_day=-0.0160\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-06] [\"Nasdaq 100 Movers: LRCX, BIIB In early trading on Friday, shares of Biogen ( BIIB ) topped the list of the day's best performing components of the Nasdaq 100 index, trading up 17.8%. Year to date, Biogen registers a 10.5% gain. And the worst performing Nasdaq 100 component thus far on the day is Lam Research ( LRCX ), trading down 1.2%. Lam Research is lower by about 7.8% looking at the year to date performance. Two other components making moves today are Applied Materials ( AMAT ), trading down 1.0%, and Check Point Software Technologies ( CHKP ), trading up 2.6% on the day. VIDEO: Nasdaq 100 Movers: LRCX, BIIB The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"After Hours Most Active for Jul 6, 2018 : QQQ, DPS, KKR, ATUS, NKE, WMB, ODP, CRM, FB, MDLZ, IEF, AMAT The NASDAQ 100 After Hours Indicator is up 1.83 to 7,209.16. The total After hours volume is currently 27,145,615 shares traded. The following are the most active stocks for the after hours session : Invesco QQQ Trust, Series 1 ( QQQ ) is -0.03 at $175.58, with 3,669,314 shares traded. This represents a 29.29% increase from its 52 Week Low. Dr Pepper Snapple Group, Inc ( DPS ) is unchanged at $122.92, with 2,809,452 shares traded. DPS's current last sale is 100.34% of the target price of $122.5. KKR & Co. Inc. ( KKR ) is unchanged at $27.04, with 1,033,438 shares traded. As reported by Zacks, the current mean recommendation for KKR is in the \\\"buy range\\\". Altice USA, Inc. ( ATUS ) is -0.0681 at $18.35, with 895,379 shares traded. As reported by Zacks, the current mean recommendation for ATUS is in the \\\"buy range\\\". Nike, Inc. ( NKE ) is unchanged at $76.48, with 874,325 shares traded. Over the last four weeks they have had 4 up revisions for the earnings forecast, for the fiscal quarter ending May 2019. The consensus EPS forecast is $0.79. NKE's current last sale is 98.05% of the target price of $78. Williams Companies, Inc. (The) ( WMB ) is unchanged at $27.58, with 848,571 shares traded. As reported by Zacks, the current mean recommendation for WMB is in the \\\"buy range\\\". Office Depot, Inc. ( ODP ) is unchanged at $2.70, with 810,779 shares traded. ODP's current last sale is 81.82% of the target price of $3.3. Salesforce.com Inc ( CRM ) is unchanged at $141.40, with 750,894 shares traded. As reported by Zacks, the current mean recommendation for CRM is in the \\\"buy range\\\". Facebook, Inc. ( FB ) is -0.11 at $203.12, with 739,123 shares traded. As reported by Zacks, the current mean recommendation for FB is in the \\\"buy range\\\". Mondelez International, Inc. ( MDLZ ) is unchanged at $42.35, with 620,964 shares traded. As reported by Zacks, the current mean recommendation for MDLZ is in the \\\"buy range\\\". iShares 7-10 Year Treasury Bond ETF ( IEF ) is unchanged at $10\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 = 0.0146 (i.e., a 1.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0146 = 6.8319, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014637, "expected_loss": 0.014637, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20181205_0920", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2018-12-05", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0336, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0015, std=0.0128, worst_day=-0.0336\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-12-04] [\"Another Apple Supplier Slashes Its Sales Guidance Cirrus Logic, a maker of audio chips, reduced its financial guidance for its third quarter after the close on Monday, citing \\u201crecent weaknesses in the smartphone market.\\u201d\", \"Apple's stock falls 1.9% in premarket trade, after rallying 3.5% on Monday\", \"Apple Drops, Aerospace Under Pressure as Stocks Falter After Trade-Related Surge The global equity rally was on hold Tuesday morning as global stock markets gave back some of their post-G-20 trade-related gains.\", \"Apple stock falls after HSBC downgrade Apple Inc. shares are down 2.1% in premarket trading Tuesday after HSBC analyst Erwan Rambourg downgraded the stock to hold from buy, writing that it was \\\"too late to sell, too early to buy\\\" Apple shares, which have fallen 19% over the past three months. \\\"Apple has to innovate to ensure that the installed hardware base doesn't shrink,\\\" wrote Rambourg, who suggested three \\\"complementary strategies\\\" for the company. One is \\\"horizontal diversification and geographic expansion,\\\" as services like Apple Pay are growing fast but could benefit from more reach, in Rambourg's view. Another approach would be adding new services and applications in areas such as augmented reality that would drive hardware improvement and excite current iPhone users. Rambourg's final strategy is \\\"pure innovation\\\" in new realms like autonomous driving, health, and augmented-reality glasses. He lowered his price target to $200 from $205, writing of an \\\"undemanding valuation\\\" but limited \\\"immediate catalysts.\\\" The shares are down 11% over the past month, while the Dow Jones Industrial Average has risen 2.2%.\", \"AutoZone Stock Gains, RH Soars and Three More Morning Movers Apple and Hartford Financial Services are also on the move.\", \"Apple will buy Tesla and other \\u2018outrageous predictions\\u2019 from Saxo Bank Critical information for the U.S. trading day Our call of the day says get ready for a corporate-credit nightmare in 2019, and tosses in some wild predictions.\", \"Cirrus Logic target cut at Susquehanna as analyst says negative revision was worse than expected Susquehanna analyst Christopher Rolland lowered his price target on shares of Cirrus Logic Inc. to $43 from $48 on Tuesday, after the Apple Inc. supplier delivered a negative pre-announcement the prior afternoon. Given that other suppliers have cut their outlooks in recent weeks and that Cirrus shares fell sharply when Lumentum Holdings Inc. delivered its warning in November, Rolland had assumed that most of the negative risk was priced into shares but called the new projections from Cirrus \\\"a bit worse than we had expected.\\\" He has a positive rating on the stock and hopes that management will \\\"revisit longer-term plans to ramp operating expenditures year over year.\\\" Oppenheimer's Rick Schafer also chimed in on the negative preannouncement. \\\"We continue to see disappointing iPhone units and a lack of incremental Cirrus content at Apple (82%\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 = 0.0336 (i.e., a 3.36% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0336 = 2.9791, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033567, "expected_loss": 0.033567, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160119_0922", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2016-01-19", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0264, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0021, std=0.0116, worst_day=-0.0264\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-15] [\"TSMC: Modesty Is Virtue, Bear Maybank Raises To Hold Analysts have been questioning Apple (AAPL) foundry Taiwan Semiconductor Manufacturing Corp.'s (2330.Taiwan/TSM) ambition lately, saying TSMC is unrealistic with its outlook.TSMC had a long-term goal of 10% annualized growth in revenue and profit. How can it be, when the overall smartphone growth is expected to dip to single-digit this year, they ask.After the market close on Thursday, TSMC reported fourth-quarter earnings per share of 2.81 new Taiwan dollars, above the consensus expectation of NT$2.65.But more importantly, TSMC guided its revenue growth outlook lower, expecting only 5-10% growth.READ MORE.\", \"Apple\\u2019s iPhone slowdown starting to take toll on suppliers Some Asian component makers warn of lower first-half revenues Companies that make parts for Apple Inc. are warning of lower first-half revenue this year, in a sign of slowing sales of the latest iPhones.\", \"Analog Devices Bruised by Apple The supplier is the latest hurt by lower iPhone demand. Consolation: more content in the new Apple Watch and iPhone 7.\", \"All Dow stocks trading premarket are down, led by Intel and Apple shares Bears are getting an early start Friday, as 26 of the 30 stocks in the Dow Jones Industrial Average are trading in the premarket, and they are all down. The biggest loser is Intel Corp.'s stock , which shed 5.9% after reporting disappointing fourth-quarter results late Thursday. The most active is Apple Inc.'s stock , which is down 2% on volume of about 105,000 shares. Among other more-active components, shares of Walt Disney Co. slid 2.7%, of Exxon Mobil Corp. fell 2.7%, of Microsoft Corp. dropped 2.3% and of General Electric Co. gave up 1.6%. Dow futures were last down around 268 points.\", \"This tech company hopes to help Hollywood through biometric analysis Lightwave measured 15 audience fight-or-flight responses in \\u2018The Revenant\\u2019 Biometric tech company Lightwave partnered with 20th Century Fox to track audiences response to \\u201cThe Revenant.\\u201d\", \"Analog Devices Slips Although Street Largely Yawns at the Apple Debacle Shares of chip maker Analog Devices (ADI) are down $1.03, or 2%, at $49.47, after the company yesterday afternoon cut its revenue outlook for its January-ending fiscal Q1, noting weakness in its \\u201cportable\\u201d products division, which most on the Street take as equating to the company\\u2019s sales to smartphones, and especially Apple's (AAPL) iPhone.Although there are price target and estimate cuts at all shops today, the sell side is largely yawning at this development.Although the impact from what appears to be some reduction in orders for parts from ADI by Apple is somewhat greater than many expected; and although the pain may last into next quarter as well, most seem to believe the problem is understood by investors and that it\\u2019s time to move on.The stock has gotten one upgrade today, that I can see, from Nomura\\u2019s Romit Shah, who raised his ratin\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 = 0.0264 (i.e., a 2.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0264 = 3.7915, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026375, "expected_loss": 0.026375, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210112_0924", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2021-01-12", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0360, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=0.0011, std=0.0154, worst_day=-0.0411\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 = 0.0360 (i.e., a 3.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0360 = 2.7791, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035982, "expected_loss": 0.035982, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190705_0926", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-07-05", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1425, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0260, std=0.0840, worst_day=-0.1553\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.7017", "answer_numeric": 0.7017, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1425 (i.e., a 14.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1425 = 0.7017, capped at 1.0.\nMaximum position size = 0.7017 (70.2% of portfolio).", "metadata": {"var_99": -0.142511, "expected_loss": 0.142511, "max_drawdown_threshold": 0.1, "position_size": 0.7017, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20150507_0928", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2015-05-07", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0196, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0011, std=0.0107, worst_day=-0.0225\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-05-06] [\"Itron (ITRI) Q1 Earnings Trail on Adverse Forex Impact - Analyst Blog\", \"Itron (ITRI) Q1 Earnings Trail on Adverse Forex Impact - Analyst Blog\", \"Itron (ITRI) Q1 Earnings Trail on Adverse Forex Impact - Analyst Blog Shares of Itron, Inc.ITRI lost around 1.2% and closed at $35.27, a day after the company reported disappointing first-quarter 2015 results on May 4. Adjusted earnings per share slumped 35.5% to 20 cents in the quarter from 31 cents in the prior-year quarter, mainly due to unfavorable impact of foreign currency exchange rates. Earnings also trailed the Zacks Consensus Estimate of 30 cents. Including one-time items, such as amortization, restructuring and acquisition-related expenses, the company reported earnings of 13 cents per share, contrary to a loss of 1 cent in the year-ago quarter. Itron Inc. - Earnings Surprise | FindTheCompany Operational Update Total revenue declined 5.6% to $448 million from $474.8 million in the year-ago quarter. Revenues, however, beat the Zacks Consensus Estimate of $429 million. Changes in foreign currency exchange rates unfavorably impacted revenues for the quarter. Excluding the impact of foreign currency, revenues increased 4% year over year. Improvement was driven by growth in the Electricity segment, which offset a decrease in the Gas segment. The Water segment was consistent with the prior-year period. Cost of goods sold went down to $310 million from $320 million in the prior-year quarter. Gross profit also decreased 10.6% year over year to $138 million. Gross margin decreased 170 basis points (bps) to 30.8%, primarily due to unfavorable product mix and increased warranty expense in the Gas and Water segments, partially offset by improved performance in Electricity. Adjusted operating expenses declined to $119.8 million from $131.9 million in the year-ago quarter. Adjusted operating profit decreased 21.7% year over year to $18 million. Including one-time items, Itron's operating income increased to $13.5 million in the quarter from $4.5 million in the year-ago quarter. Segment Performance Electricity Segment: Net sales at the Electricity Segment increased 7.6% year over year to $193.8 million. The segment reported adjusted operating income of $6 million unlike an operating loss of $15.9 million in the year-ago quarter. Gas Segment: The segment's sales went down 14.4% year over year to $125 million. Adjusted operating income for the quarter was $16 million, down 42.8% from $28 million in the year-ago quarter. Water Segment: The Water Segment reported sales of $129 million in the quarter, down 13% from $148.5 million in the prior-year quarter. Adjusted operating income for the quarter was $9.8 million, which plunged 58% from $23 million in the year-ago quarter. Financial Position Itron ended the quarter with cash and cash equivalents of $118 million versus $112.4 million as of 2014-end. The company reported cash used in operating activities of $3.9 million during first-quarter 2015 compared to cas\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 = 0.0196 (i.e., a 1.96% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0196 = 5.0937, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019632, "expected_loss": 0.019632, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180214_0930", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2018-02-14", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.2138, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0095, std=0.1154, worst_day=-0.2138\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.4677", "answer_numeric": 0.4677, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.2138 (i.e., a 21.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.2138 = 0.4677, capped at 1.0.\nMaximum position size = 0.4677 (46.8% of portfolio).", "metadata": {"var_99": -0.2138, "expected_loss": 0.2138, "max_drawdown_threshold": 0.1, "position_size": 0.4677, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20191028_0932", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-10-28", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0879, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0308, worst_day=-0.1140\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0879 (i.e., a 8.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0879 = 1.1379, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.087882, "expected_loss": 0.087882, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190204_0934", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2019-02-04", "context_summary": "SCHP: 60-day history, VaR(99%)=-0.0037, max drawdown threshold=10%.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0004, std=0.0023, worst_day=-0.0045\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 = 0.0037 (i.e., a 0.37% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0037 = 27.0427, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.003698, "expected_loss": 0.003698, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20170913_0936", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2017-09-13", "context_summary": "SHV: 60-day history, VaR(99%)=-0.0003, max drawdown threshold=10%.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0000, std=0.0002, worst_day=-0.0003\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 = 0.0003 (i.e., a 0.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0003 = 367.1313, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000272, "expected_loss": 0.000272, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210416_0938", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2021-04-16", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0749, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0050, std=0.0366, worst_day=-0.0993\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0749 (i.e., a 7.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0749 = 1.3354, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.074886, "expected_loss": 0.074886, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20191216_0940", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2019-12-16", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0581, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0022, std=0.0287, worst_day=-0.0698\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0581 (i.e., a 5.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0581 = 1.7224, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.058057, "expected_loss": 0.058057, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210726_0942", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2021-07-26", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1464, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0067, std=0.0659, worst_day=-0.1989\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6831", "answer_numeric": 0.6831, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1464 (i.e., a 14.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1464 = 0.6831, capped at 1.0.\nMaximum position size = 0.6831 (68.3% of portfolio).", "metadata": {"var_99": -0.146393, "expected_loss": 0.146393, "max_drawdown_threshold": 0.1, "position_size": 0.6831, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220524_0944", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2022-05-24", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1567, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0110, std=0.0480, worst_day=-0.1952\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-05-23] \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": "0.6383", "answer_numeric": 0.6383, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1567 (i.e., a 15.67% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1567 = 0.6383, capped at 1.0.\nMaximum position size = 0.6383 (63.8% of portfolio).", "metadata": {"var_99": -0.15666, "expected_loss": 0.15666, "max_drawdown_threshold": 0.1, "position_size": 0.6383, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20180202_0946", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2018-02-02", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1151, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0065, std=0.0614, worst_day=-0.1222\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-02-01] [\"Apple declines in late trading on iPhone supplier concerns Apple Inc. shares fell in late trading Wednesday after chip supplier Qualcomm Inc. reported that a large customer pared orders more than expected in the quarter. Qualcomm, which reported earnings Wednesday afternoon, supplies modems to Apple for its iPhones, and the information was believed to be a signal that Apple curtailed iPhone production earlier than expected. As Bloomberg News noted, another Apple component supplier, Broadcom Ltd. , made a similar disclosure in its own earnings report earlier Wednesday. Apple stock declined about 0.5% in after-hours action; the company is scheduled to reveal initial iPhone X sales in an earnings report Thursday afternoon.\", \"Asian markets mostly rise on brighter economic data Nikkei up 1.2% after 6 days of declines; stocks in China sink Some Asian stock markets rebounded after the broad pullback that started the week, but Chinese equities weakened again following another muted manufacturing reading, weighing on Hong Kong stocks.\", \"Qualcomm shores up licensing with expanded Samsung deal Charges related to licensing bit into Qualcomm profit The agreement with Samsung, which allows the two companies to share patents, doesn\\u2019t bear on the deals Qualcomm uses to license intellectual property for its smartphone chips, which are facing legal challenges by Apple and regulators.\", \"Apple earnings: Forget taxes and batteries, the $1,000 iPhone X remains the story Apple expected to post record sales for the holiday quarter, despite iPhone X shortages, thanks to high price tag Apple has generated attention for its comments on taxes and batteries, but investors will focus mostly on iPhone sales when the company reports earnings Feb. 1\", \"Qualcomm earnings show weak forecast amid massive fines, tax charge Tax law change, fines sock Qualcomm with $6 billion quarterly loss Qualcomm Inc. managed to beat expectations with its earnings Wednesday, but the chip maker\\u2019s outlook came up short and caused some concerns about Apple Inc.\\u2019s iPhone sales.\", \"The Amazon chart you may not want to see, but probably should Critical information for the U.S. trading day It\\u2019s a huge earnings day and investors will be scrambling to keep up. Our chart of the day offers food for thought for one of those big companies \\u2014 Amazon, while the chart of the day says don\\u2019t bail on stocks now.\", \"Facebook earnings send stock to record after massive ad price increase Average price for Facebook ads jumped 43% in fourth quarter Facebook Inc. shares reversed course to show gains in late trading Wednesday after the company reported double-digit advertising price growth amid massive changes to its core product.\", \"Apple Earnings: Hand-Wringing\\u2019s Silver Lining? Apple's quarterly report Thursday night finally brings the Street face to face with the numbers they've been obsessing about: How bad will the outlook be for the March quarter's iPhone units? There just has to\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": "0.8687", "answer_numeric": 0.8687, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1151 (i.e., a 11.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1151 = 0.8687, capped at 1.0.\nMaximum position size = 0.8687 (86.9% of portfolio).", "metadata": {"var_99": -0.115121, "expected_loss": 0.115121, "max_drawdown_threshold": 0.1, "position_size": 0.8687, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20180706_0949", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2018-07-06", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0130, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0001, std=0.0063, worst_day=-0.0143\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2018-07-05] [\"PreMarket Prep Recap For July 5: Trading The Range In The S&P 500; Sean Udall Joins The Show\", \"PreMarket Prep Recap For July 5: Trading The Range In The S&P 500; Sean Udall Joins The Show\", \"Synopsys, Siemens Join Forces on EDA Interoperability Effort SynopsysSNPS is collaborating with Siemens PLM Software to jointly develop a wide range of electronic design automation (EDA) product interoperability projects. EDA is a category of tools used to analyze semiconductor devices. Many chip designers and manufacturers are opting for EDA, attracted by the reduced cost, errors and design time associated with its adoption. The increasing demand for EDA solutions are driven by growth in fast growing fields of cloud computing, Artificial Intelligence (AI), Internet of Things (IoT) and smart wearable devices. Collaboration to Boost Customer Base The synergistic collaboration between Synopsys and Siemens encompasses EDA domains from design to verification. The latest collaboration will help Synopsys address the needs of semiconductor and system-on-chip (SoC) manufacturing firms, which comprises the majority of its clientele. Moreover, the joint solution will enhance customers' digitization efforts. Further, the collaboration will ensure more effective EDA solutions for mutual customers. Notably, one major competitor of Synopsys was Mentor Graphics, which was recently acquired by Siemens. The companies have also settled all outstanding patent litigations Hence, we believe the collaboration with Siemens on EDA product interoperability solutions bodes well for Synopsys, as it will expand its penetration in the market. Synopsys, Inc. Revenue (TTM) Synopsys, Inc. Revenue (TTM) | Synopsys, Inc. Quote Extended Partner Base, New Solutions to Drive Growth We believe Synopsys will benefit from its expanding partner base. The company's extended relationships with the likes of AMD, Juniper, Realtek, Teradici, NetLogic Microsystems, Toshiba and Wolfson will continue to boost its top-line growth. Synopsys also collaborated with ARM Holdings plc which is expected to optimize the performance of its processors. The company is positive about its EDA design solutions which are helping in designing of new AI engines. The newly launched Fusion Technology has gained accolades from the Samsung, STMicroelectronics, Toshiba, and ANSYS. Further, strategic acquisitions have expanded the company's presence in the intensely competitive EDA market. Zacks Rank and Stocks to Consider Synopsys currently carries a Zacks Rank #3 (Hold). Some stocks worth considering in the broader Computer and Technology sector are Adobe ADBE , YY YY , and Verint VRNT . All three stocks sport a Zacks Rank #1 (Strong Buy). You can see the complete list of today's Zacks #1 Rank stocks here . Long-term earnings growth for Adobe, YY and Verint is projected to be 16.20%, 26.43% and 10%, respectively. Today's Stocks from Zacks' Hottest Strategies It's hard to believe, even for us at Zacks. But while the market gai\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 = 0.0130 (i.e., a 1.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0130 = 7.7108, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012969, "expected_loss": 0.012969, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20221209_0951", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2022-12-09", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0211, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0004, std=0.0118, worst_day=-0.0222\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-12-08] [\"US STOCKS-S&P 500, Nasdaq snap losing streaks after jobless claims rise By David French Dec 8 (Reuters) - The S&P 500 .SPXended higher on Thursday, snapping a five-session losing streak, as investors interpreted data showing a rise in weekly jobless claims as a sign the pace of interest rate hikes could soon slow. Wall Street's main indexes had come under pressure in recent days, with the S&P 500 shedding 3.6% since the beginning of December on expectations of a longer rate-hike cycle and downbeat economic views from some top company executives. Such thinking had also weighed on the Nasdaq Composite .IXIC, which had posted four straight losing sessions prior to Thursday's advance on the tech-heavy index. Stocks rose as investors cheered data showing the number of Americans filing claims for jobless benefits increased moderately last week, while unemployment rolls hit a 10-month high toward the end of November. The report follows data last Friday that showed U.S. employers hired more workers than expected in November and increased wages, spurring fears that the Fed might stick to its aggressive stance to tame decades-high inflation. Markets have been swayed by data releases in recent days, with investors lacking certainty ahead of Federal Reserve guidance next week on interest rates. Such behavior means Friday's producer price index and the University of Michigan's consumer sentiment survey will likely dictate whether Wall Street can build on Thursday's rally. \\\"The market has to adjust to the fact that we're moving from a stimulus-based economy - both fiscal and monetary - into a fundamentals-based economy, and that's what we're grappling with right now,\\\" said Wiley Angell, chief market strategist at Ziegler Capital Management. The Dow Jones Industrial Average .DJI rose 183.56 points, or 0.55%, to close at 33,781.48; the S&P 500 .SPX gained 29.59 points, or 0.75%, to finish at 3,963.51; and the Nasdaq Composite .IXIC added 123.45 points, or 1.13%, at 11,082.00. Nine of the 11 major S&P 500 sectors rose, led by a 1.6% gain in technology stocks .SPLRCT. Most mega-cap technology and growth stocks gained. Apple Inc AAPL.O, Nvidia Corp NVDA.O and Amazon.com Inc AMZN.O rose between 1.2% and 6.5%. Microsoft Corp MSFT.O ended 1.2% higher, despite giving up some intraday gains after the Federal Trade Commission filed a complaint aimed at blocking the tech giant's $69 billion bid to buy Activision Blizzard Inc ATVI.O. The \\\"Call of Duty\\\" games maker closed 1.5% lower. The energy index .SPNY was an exception, slipping 0.5%, despite Exxon Mobil Corp XOM.N gaining 0.7% after announcing it would expand its $30-billion share repurchase program. The sector had been under pressure in recent sessions as commodity prices slipped: U.S. crude CLc1 is now hovering near its level at the start of 2022. Meanwhile, Moderna Inc MRNA.O advanced 3.2% after the U.S. Food and Drug Administration authorized COVID-19 shots from the vaccine maker that target both the original\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 = 0.0211 (i.e., a 2.11% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0211 = 4.7411, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021092, "expected_loss": 0.021092, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210128_0953", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2021-01-28", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1458, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0151, std=0.0592, worst_day=-0.1593\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6860", "answer_numeric": 0.686, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1458 (i.e., a 14.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1458 = 0.6860, capped at 1.0.\nMaximum position size = 0.6860 (68.6% of portfolio).", "metadata": {"var_99": -0.14577, "expected_loss": 0.14577, "max_drawdown_threshold": 0.1, "position_size": 0.686, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210813_0955", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2021-08-13", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1203, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0044, std=0.0494, worst_day=-0.1593\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.8313", "answer_numeric": 0.8313, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1203 (i.e., a 12.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1203 = 0.8313, capped at 1.0.\nMaximum position size = 0.8313 (83.1% of portfolio).", "metadata": {"var_99": -0.120299, "expected_loss": 0.120299, "max_drawdown_threshold": 0.1, "position_size": 0.8313, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220715_0957", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2022-07-15", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0328, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=-0.0021, std=0.0173, worst_day=-0.0328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-14] [\"5 Stocks to Outrun the Housing Market InvestorPlace - Stock Market News, Stock Advice & Trading Tips This article is excerpted from Tom Yeung\\u2019s Profit & Protection newsletter. To make sure you don\\u2019t miss any of Tom\\u2019s picks, subscribe to his mailing list here. CPI Hits 9.1%\\u2026 And Other Bad News On Tuesday, I wrote that exorbitant home prices are driving even relatively well-off professionals out of top markets. No matter how successful a doctor, lawyer or programmer you become, it\\u2019s hard to make $450,000 per year \\u2014 Fidelity Bank\\u2019s estimated buying price for the average apartment in New York\\u2019s Upper East Side. Right on cue, the Bureau of Labor Statistics (BLS) released even more bad news: Inflation hit 9.1% in the month of June. And as shocking as the figure might be, it actually understates the problem. According to data from Zillow, the average cost to rent has risen 14.7% in the past 12 months. But because only one-third of Americans rent (and making some adjustments for homeowners), the BLS only recorded a 5.6% increase in real estate spending among all Americans. But jumping into real estate today is also risky at best. Rising mortgage rates, slackening commodity prices and unaffordable prices point to prolonged stagnation in house values. Real estate prices cannot go to the moon unless wages do too. Instead, investors need to buy companies that benefit from real estate markets without the pricing risk. And today, we will cover five of these fast-growing tech firms that are upending the traditional real estate market. Source: Shutterstock / Unicode Vector 5 Stocks to Outrun the Housing Market Earlier this month, Zillow revealed housing prices have risen 19.4% over the past year. Many homeowners are nervously asking themselves how they\\u2019ll afford a new house if they ever need to move. Meanwhile, renters are in even worse shape. Wages have risen at just one-third the rate of rent increases. And Google\\u2019s 30 million results for the question \\u201chow much does a cardboard box cost to live in\\u201d yield very little helpful advice. At first glance, homebuilder stocks seem like a natural winner. As I mentioned on Tuesday, companies like America\\u2019s largest home builder D.H. Horton (DHI) are earning 4x their operating income compared to five years ago. If home prices are going up, shouldn\\u2019t homebuilder stocks too? But such conclusions fall into the trap of \\u201cfirst-level thinking,\\u201d a term coined by Oaktree Capital co-founder Howard Marks. First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in \\u201cThe outlook for the company is favorable, meaning the stock will go up.\\u201d Second-level thinking is deep, complex and convoluted. That\\u2019s because homebuilding is a low-margin business with virtually no barriers to entry. \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 = 0.0328 (i.e., a 3.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0328 = 3.0503, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032784, "expected_loss": 0.032784, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220912_0963", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2022-09-12", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0225, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0014, std=0.0101, worst_day=-0.0253\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-09] [\"ROKU Set to Launch The Rich Eisen Show on The Roku Channel Roku Inc. ROKU awaits the debut of The Rich Eisen Show hosted by Rich Eisen on the Roku Channel on Sep 12. This is a two-time Emmy-nominated talk show, which features a mix of sports, humor, and pop culture. Streamers can access the weekday live show through the FAST channel available on The Roku Channel and The Roku Channel\\u2019s Live TV Guide on Channel 210 from Monday-Friday, from 12:00-3:00 PM ET/9:00 AM-12:00 PM PT. The prior episodes of the show will be streamed when the broadcast is off air. The show, which previously attracted renowned personalities from sports and entertainment like Tom Brady, Shaquille O\\u2019Neal, Matt Damon and more, is now expected to attract users to The Roku Channel as it launches just a week into NFL. Roku, Inc. Price and Consensus Roku, Inc. price-consensus-chart | Roku, Inc. Quote The Roku Channel Expands Content Width The Roku Channel has been focused on expanding its library. It recently added 14 new linear channels, of which the local news channels seemed to gain the most traction. Roku expects all the newly launched channels that offer a wide range of genres like Westerns, Spanish-language entertainment and true crime to drive viewers\\u2019 interest and increase active accounts. The company boasts about maintaining its market leadership as it added 1.8 million incremental active accounts to reach 63.1 million in the second quarter of 2022. The continued momentum of Roku Originals complements the company\\u2019s market leadership. The second season of Chrissy\\u2019s Court was the highest-rated unscripted Roku Originals launch ever and delivered four times more unique views than the first season. The upcoming feature film WEIRD: The Al Yankovic Story, which is scheduled to be released on Nov 4, is anticipated to attract advertisers due to the new opportunities to engage with Roku Originals. Roku recently announced a new product called Shoppable Ads, which makes shopping on TV streaming hassle-free. Its partnership with Walmart, a leading retail giant to be their exclusive retailer shows growth prospects in this business unit. Considering these factors, the company estimates total net revenues to increase approximately 3% year over year to $700 million and total gross profits of roughly around $325 million. Roku Faces Uncertainty and Stiff Competition Despite investments toward expansion, COVID-19 and the Russia-Ukraine war have contributed to Roku facing a slowdown in TV advertising expenditure over the last two quarters. This apart, the company faces significant competitive pressure from Amazon\\u2019s AMZN Fire TV Stick, Alphabet Inc\\u2019s GOOGL Chromecast and Apple\\u2019s AAPL Apple TV. Roku\\u2019s shares have underperformed, having plunged 69.7% year to date compared to its peers \\u2014 Amazon, Google and Apple \\u2014 which have declined 22.2%, 24.4% and 13%, respectively. The Zacks Broadcast Radio and Television industry has seen a decline of 53\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 = 0.0225 (i.e., a 2.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0225 = 4.4536, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022453, "expected_loss": 0.022453, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20160114_0967", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2016-01-14", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0332, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0009, std=0.0124, worst_day=-0.0351\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2016-01-13] [\"CLSA Survey: China\\u2019s iPhone Demand Remains Firm Smartphone hardware stocks are sold off this year. Apple (AAPL) has fallen 5%, while Samsung Electronics (005930.Korea/SSNLF) has retreated 9.1% on concerns over a sharp smartphone growth slowdown.After conducting a consumer intent survey in December, Asia-based broker CLSA continues to feel bullish about Apple, but has cooled towards its competitors Huawei, Xiaomi and Samsung.READ MORE.\", \"Oversold Apple Stocks Apple's (AAPL) supply chain in Asia has sank with its patron this year. In Taiwan, casing supplier Catcher Technology (2474.Taiwan) lost a quarter of its market value in 7 trading days, while Apple's foundry Taiwan Semiconductor Manufacturing Corp., or TSMC (2330.Taiwan/TSM) retreated 7.6%.Some of the setback is media reports that Apple would cut its iPhone production by a third in the March quarter, but the weaker yuan, which has rattled stocks, commodities, and currencies worldwide, is also to blame.As yuan calms and dust settles, we may find some Apple suppliers oversold. \\\"On valuation, we find a few Apple names trading near book value, but still generating respectable free cash flow, ROE and dividend yields,\\\" noted HSBC's Steven Pelayo this morning.READ MORE.\", \"Qualcomm Teams with TDK in RF Assault on Skyworks, Qorvo Wireless chip giant Qualcomm (QCOM) early Wednesday morning announced it would team with Japan\\u2019s TDK (TTDKY) to produce more complete radio frequency chips, a move that could bring the company into closer competition with RF leaders Skyworks Solutions (SWKS) and Qorvo (QRVO).Qualcomm said it will form a joint venture with TDK, called RF360 Holdings, 51% owned by Qualcomm, to make what are known as \\u201cRF front-end modules,\\u201d combining parts from Qualcomm, such as power amplifiers,\\u201d with parts in which TDK specializes, such as radio-frequency filters.Qualcomm has long dominated the the baseband modem in smartphones such as Apple's (AAPL) iPhone and most other major devices. From the modem it has built a growing business supplying application processors, but also, increasingly, more of the radio-frequency chips that tune a phone to the particular electromagnetic frequency by which they must send and receive signals.TDK, founded in 1935, is best known for its magnetic recording media, especially the cassette tape. But it also has an extensive microelectronics business. That business includes parts of wireless equation that Qualcomm lacks, such as surface acoustic wave, or SAW, filters.Qualcomm has an option to buy out TDK\\u2019s share in the venture, after 30 months have passed from the closing of the deal. In a phone call I had with the company, Qualcomm\\u2019s chief financial officer, George Davis, said \\\"we would anticipate that being exercised\\u201d ultimately.\", \"Steer clear of Saudi Aramco\\u2019s initial public offering It would be world\\u2019s biggest listed company, but it\\u2019d come with lots of unknowns The initial public offering for Saudi \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 = 3.0156, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03316, "expected_loss": 0.03316, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20211012_0969", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2021-10-12", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1519, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0615, worst_day=-0.1902\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6585", "answer_numeric": 0.6585, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1519 (i.e., a 15.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1519 = 0.6585, capped at 1.0.\nMaximum position size = 0.6585 (65.8% of portfolio).", "metadata": {"var_99": -0.151871, "expected_loss": 0.151871, "max_drawdown_threshold": 0.1, "position_size": 0.6585, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20210118_0971", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2021-01-18", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0241, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0029, std=0.0141, worst_day=-0.0259\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2021-01-15] 3 Stocks That Need to Get Back on Track in 2021 Last year was a lucrative one for most investments, but some market favorites were sputtering near the 2020 finish line. These recent laggards need to get back on track, and we may as well go over the best chance for that to happen in 2021. Adobe Systems (NASDAQ: ADBE), Zoom Video Communications (NASDAQ: ZM), and Sirius XM Holdings (NASDAQ: SIRI) have a lot to prove after recently falling out of favor. Let's dive into what went wrong -- and what can go right in the year ahead. Image source: Getty Images. Adobe Adobe posted uninspiring financial results last month. Revenue for the quarter that ended in late November clocked in 14% higher. Top-line growth for the entire fiscal year came in at 15%. Growth in the low teens may not seem too shabby, but Adobe's revenue growth had topped 20% in each of the four previous fiscal years. Adobe should've been pandemic-proof. Digital publishing and its electronic signature business should've been booming during the shelter-in-place phase of the COVID-19 crisis. Adobe was a winner for the calendar year. The stock rose 52% in 2020. However, it gained just 2% in the final three months of the year when the general market was rallying. Adobe needs to get back on track, and thankfully it has the liquidity to make its own luck. Adobe spent $3 billion repurchasing 8 million shares in fiscal 2020, and its board just authorized another $15 billion of stock repurchases through the end of fiscal 2024 once the current plan is authorized. Adobe will have the flexibility to buy into any weakness at this point, and along the way it will improve its profitability on a per-share basis. Zoom You probably didn't expect to see Zoom on a list of laggards, but bear with me. There was a point in 2020 -- mid-October if you're calendar-checking -- when the next-gen videoconferencing platform was an eight-bagger. Here we are just three months later and the stock has fallen roughly 40% from its all-time highs. Like Adobe, Zoom is a tech stock that has faded while its peers are striking fresh highs. Investors began to bail on Zoom in November and December when a pair of viable vaccines emerged and were ultimately granted Emergency Use Authorization. The thinking here is that folks won't be on Zoom as much once the pandemic is over. Call me crazy, but I think there will be some form of virtual schooling in the future, and there's no way that families and corporations will stop meeting online every now and then for the sake of convenience and to save some money. Zoom is rocking. Revenue soared 367% in its most recent quarter. Returning customers are spending an average of at least 30% more than they were a year earlier, and that's been the case for 10 consecutive quarters. In short, the pandemic shaved a few years off of Zoom's growth trajectory, but it was and will continue to be a rock star in the next new normal. Sirius We finally get to a stock that retreated in 2020, and didn't just stum\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 = 0.0241 (i.e., a 2.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0241 = 4.1495, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024099, "expected_loss": 0.024099, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20210223_0973", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2021-02-23", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1608, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0103, std=0.0873, worst_day=-0.2138\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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": "0.6219", "answer_numeric": 0.6219, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1608 (i.e., a 16.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1608 = 0.6219, capped at 1.0.\nMaximum position size = 0.6219 (62.2% of portfolio).", "metadata": {"var_99": -0.160785, "expected_loss": 0.160785, "max_drawdown_threshold": 0.1, "position_size": 0.6219, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20190226_0976", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2019-02-26", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0358, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0005, std=0.0158, worst_day=-0.0391\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2019-02-25] [\"Apple's approach to video 'will likely remain uninspiring,' says KeyBanc KeyBanc Capital Markets analyst Andy Hargreaves isn't particularly upbeat about the streaming-video service that many expect Apple Inc. to unveil in the coming weeks. \\\"While this will likely usher in an era of Apple originals, the overall effort appears likely to be sub-scale, years behind key competitors, and lacking in meaningful differentiation,\\\" he wrote. \\\"We see little in the effort that appears likely to drive material profits or that could attract a significant number of incremental users to the Apple ecosystem.\\\" He said the company's efforts in video \\\"will likely remain uninspiring\\\" and doesn't see an easy way for Apple to catch up with rivals that are more experienced in the space. He rates the stock at sector weight. Apple shares are up 0.7% in premarket trading Monday, and they've gained 0.4% over the past three months. The Dow Jones Industrial Average has climbed 32% in that time.\", \"Apple card partnership with Goldman Sachs likely to be 'immaterial' to revenue: Bernstein Apple Inc. is reportedly planning to issue a co-branded Mastercard Inc. card with Goldman Sachs Group Inc. , according to the Wall Street Journal, an arrangement that seems to make strategic sense but likely won't help Apple's financials much, Bernstein analysts wrote Monday. \\\"The financial impact is likely immaterial to all three in our view,\\\" wrote the analysts, led by Harshita Rawat. \\\"For Apple, we believe it brings more ecosystem enhancing (vs. financial) benefits.\\\" The company likely doesn't bring in more than \\\"a few hundred million dollars\\\" in annual revenue from Apple Pay as is, Rawat said. Goldman, meanwhile, might not get credit from investors for this effort \\\"until they have a more coherent direct-to-consumer wealth management strategy,\\\" according to Rawat. She doubts whether there will be much uptake of this new card, which hasn't been officially confirmed or announced, given a highly competitive landscape for rewards credit cards. \\\"It is unclear that a value proposition centered on integration to the Apple eco-system is really enough to drive significant adoption,\\\" she wrote. Apple shares are up 0.7% in premarket trading Monday, and they've gained 0.4% over the past three months as the Dow Jones Industrial Average has climbed 7.2%.\", \"Dell returns to the earnings calendar as retailers\\u2019 holiday returns keep flowing Earnings Watch: Dell, HP and Best Buy provide a full look at electronics sales, software stocks\\u2019 gains could be tested Retail, software and personal-computer manufacturers will report earnings in the week ahead.\", \"Warren Buffett\\u2019s Berkshire Disappoints on Buybacks, Sees Stocks More Attractive Than Deals The investor\\u2019s closely read letter to shareholders has little to say about Kraft Heinz or the conglomerate\\u2019s intrinsic value.\", \"Buffett Likes JPMorgan, Blasts Bitcoin, and Isn\\u2019t Buying Apple Stock in JPMorgan Chase and other \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 = 0.0358 (i.e., a 3.58% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0358 = 2.7899, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035844, "expected_loss": 0.035844, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20201026_0978", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2020-10-26", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0325, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0016, std=0.0130, worst_day=-0.0357\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-10-23] What's The Downside For Texas Instruments Stock? Texas Instruments stock (NASDAQ: TXN) is up 64% since the beginning of this year, and at the current price of around $153 per share, we believe that TI stock has more than 15% potential downside. Why is that? Our belief stems from the fact that TI stock is still up over 70% from the low seen at the end of 2018, almost 2 years ago. Further, after posting weak Q2 2020 numbers, and with industrial demand still not up to pre-Covid levels, we believe Texas Instruments\u2019 stock could drift lower. Our dashboard What Factors Drove 70% Change In Texas Instruments Stock Between 2018 And Now? provides the key numbers behind our thinking, and we explain more below. TI stock\u2019s rise since late 2018 came despite a 9% drop in revenues, which further translated into a 10% drop in net income. which combined with a 4% drop in the outstanding share count, led to a 7% decrease in earnings per share (EPS). In addition, TI\u2019s P/E (price-to-earnings) ratio rose from 16x in 2018 to 24x in 2019, as the semiconductor supply glut cleared out and demand started rising again. The P/E multiple has since jumped to 29x so far this year. However, given TI\u2019s dismal Q2 \u201920 numbers and the fact that industrial demand is still not back to pre-Covid levels, there is possible downside risk for TI\u2019s multiple, especially when compared with previous years: P/E of 16x at the end of 2018 and 24x as recently as 2019. So what\u2019s the likely trigger and timing to this downside? The global spread of Coronavirus and the resulting lockdowns have hampered demand for TI\u2019s analog and embedded semiconductors across a variety of sectors, especially industrial and automotive. This is evident from TI\u2019s Q2 2020 earnings, where revenue came in at $3.24 billion, down from $3.67 billion for the same period in 2019. Also, as operating expenses didn\u2019t drop as much as revenue, operating margins came in lower at 37.9% from 41.1% for the same period last year. A tax benefit of $101 million vs a tax expense of $209 million last year, helped EPS rise to $1.50 vs $1.38 for the same period last year. However, given the slow demand revival we expect TI\u2019s revenue and operating margins to struggle in the near term. Regardless, if there isn\u2019t clear evidence of containment of the virus anytime soon, we believe the stock will see its P/E multiple decline from the current level of 29x to around 24x, which combined with a slight reduction in revenues and margins could result in the stock price shrinking to as low as $125, a downside of almost 20% from the current price of $153. What if you\u2019re looking for a more balanced portfolio instead? Here\u2019s a high quality portfolio to beat the market, with over 100% return since 2016, versus 55% for the S&P 500. Comprised of companies with strong revenue growth, healthy profits, lots of cash, and low risk, it has outperformed the broader market year after year, consistently. See all Trefis Price Estimates and Download Trefis Data here What\u2019s \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 = 0.0325 (i.e., a 3.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0325 = 3.0802, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032465, "expected_loss": 0.032465, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20200701_0980", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2020-07-01", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0341, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0031, std=0.0162, worst_day=-0.0341\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-06-30] [\"Dips in Advanced Micro Devices Stock Remain Buying Opportunities InvestorPlace - Stock Market News, Stock Advice & Trading Tips Advanced Micro Devices (NASDAQ:AMD) stock is trading well within the confines of its chart patterns this year. It is struggling a bit here, but that is its normal seasonal action. Source: Sundry Photography / Shutterstock.com I am a fan of buying dips in AMD stock, and therein lies today\\u2019s discussion. It is falling into a support zone that should hold if the stock markets in general don\\u2019t collapse. Technically from here into $45 there are buyers ready to pounce on it. The overnight positive reaction to Micron (NASDAQ:MU) earnings will also boost all chip stocks. There are still too many investors who do not believe in technical analysis, and they are committing a grave mistake. In this modern era of trading, machines do most of the trading and they do not do it based on opinion. The main drivers for their actions are math, ratios and patterns. Consequently investors \\u2014 especially those who actively trade without technical skills \\u2014 are putting themselves at a disadvantage. But we all do have tools to cover the basics, at least evening the game. AMD Stock Is a Buy-and-Hold Candidate Source: Charts by TradingView AMD stock has been a great long-term investment but also a fun stock to trade shorter-term. The two can go hand in hand, and investors don\\u2019t have to choose one or the other. 7 of the Newest Stocks That Made Good on Their IPOs Fundamentally it is not cheap, but that is not a deal-breaker. The sector is booming because the world is going digital. The global quarantine put the digital migration trend in high gear and the ramp is getting more exponential. There is a panic among people and businesses alike to get online. Fear is a great motivator. People are afraid to go out, and the only solutions that we have are digitally based. Advanced Micro Devices is one of the few companies that supply the brains to power the machines. They will have tremendous demand on there goods and services for years to come. And there\\u2019s plenty of room for it and all its competitors to thrive. Therefore dips in their stocks are opportunities to buy. Last week ended on a difficult note for AMD and Nvidia (NASDAQ:NVDA) and more pain on Monday morning but that could end today. Between these two I prefer AMD over Nvidia. I don\\u2019t like it when investors overpay for upside hopium. AMD Is Not Expensive, Contrary to Popular Belief The Nvidia stock price is 20 times its yearly sales, which is more than double what it is for AMD. Traditionally investors concentrate on the price-to-earnings to ascertain value, but doing so for AMD and Nvidia would be a mistake. They are growth stocks, and profitability is not the key metric to consider. Yes, AMD has a huge 121 tailing price-to-earnings ratio compared to Nvidia\\u2019s 71. But that doesn\\u2019t matter here, because what matters more is the top line and there NVDA has 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 = 0.0341 (i.e., a 3.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0341 = 2.9314, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.034114, "expected_loss": 0.034114, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20150907_0982", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2015-09-07", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=-0.0020, std=0.0122, worst_day=-0.0289\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2015-09-04] Dow 30 Stock Roundup: GE Announces Divestment of Fleet Businesses, Intel Unveils 6th Gen Intel Core chips The Dow endured a mixed week, suffering record losses before rebounding on the last two days. The blue-chip index declined on Monday after Federal Vice Chairman Stanley Fischer's comments on Saturday left possibilities of a September rate hike wide open. The Dow posted its third biggest drop of the year on Tuesday in terms of points, slumping 2.8% or 469.68 points. The blue-chip index gained 1.8% on Wednesday amid strong domestic data and rise in oil prices . The Dow gained on Thursday amid Mario Draghi's dovish comments, upbeat economic data and fluctuations in oil prices. The Dow has declined 1.6% during the first four trading days. LastWeek's Performance Last Friday, the Dow declined 0.1% amid another surge in oil prices and a Fed official's comment on the timing of a rate hike. Investors' move to eliminate their short trading positions and increase in tensions in Yemen helped oil prices move north for the second day on Friday. Saudi's ground offensive on Yemeni forces raised concerns about supply disruption, which eventually boosted oil prices. Dow components Exxon Mobil Corporation XOM and Chevron Corporation CVX advanced 0.3% and 3.6%, respectively. Meanwhile, investors remained focused on Federal Reserve Vice Chairman Stanley Fischer's comments on the timing of a rate hike. He indicated that the central bank may raise interest rates this year, but didn't mention any specific time. Investors' reaction to the less-than-expected rise in consumer spending remained mostly muted. Personal consumption expenditure increased 0.3% in July, less than the consensus estimate of a 0.4% increase. For the week, the Dow gained 1.1%. Additionally, the blue-chip index recorded its biggest intra-week reversal since the last week of Oct 1987. Upbeat GDP data, durable-goods report and rebound in oil prices helped benchmarks notch up gains for the week. Additionally, benchmarks staged a comeback on Wednesday after the New York Federal Reserve President William Dudley said that a September rate hike is \"less compelling\". Meanwhile, benchmarks had suffered a rout during the first two trading days of the week as investors were concerned about China's economic slowdown. The Dow declined to an 18-month closing low. Later, China's central bank decided to cut interest rates and reserve requirement ratio to shore up growth. The DowThisWeek The blue-chip index declined 0.7% on Monday after Federal Vice Chairman Stanley Fischer's comments on Saturday left possibilities of September rate hike wide open. Federal Vice Chairman Stanley Fischer said during the weekend that inflation in the U.S. is likely to rebound as pressure from dollar subsides. This in turn will allow the Fed to hike rates gradually. This follows Fischer's comments made last Friday, when he said that a September rate hike was \"pretty strong\" before China devalued its currency. Oil prices moved north on\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 = 0.0289 (i.e., a 2.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0289 = 3.4601, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028901, "expected_loss": 0.028901, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220203_0985", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2022-02-03", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0215, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0006, std=0.0096, worst_day=-0.0297\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-02-02] [\"Dick's Sporting Goods Inc. and Adobe Inc. highlighted as Zacks Bull and Bear of the Day For Immediate Release Chicago, IL \\u2013 February 2, 2022 \\u2013 Zacks Equity Research Shares Dick\\u2019s Sporting Goods Inc. DKS as the Bull of the Day, Adobe Inc. ADBE asthe Bear of the Day. In addition, Zacks Equity Research provides analysis on Ford F, O'Reilly Automotive ORLY and BorgWarner BWA. Here is a synopsis of all five stocks: Bull of the Day: Dick\\u2019s Sporting Goods Inc. is a popular, well-known retailer where customers can find a wide range of sporting goods products: athletic shoes; fitness apparel and accessories; and a broad selection of outdoor and athletic equipment for team sports, camping, fishing, tennis, golf, and water sports. Third Quarter Earnings Deliver the Goods Last November, Dick\\u2019s Sporting Goods reported impressive results for its fiscal third quarter. Net sales of $2.75 billion were a record, up 13.9% year-over-year and 40% compared to Q3 2019. Consolidated same store sales spiked 12.2% on top of a 23.2% increase in 2020, while e-commerce sales surged 97% compared to 2019. E-commerce now makes up 19% of total net sales. On a non-GAAP basis, DKS posted earnings of $3.19 per share, flying past estimates of $1.93 per share. Dick\\u2019s ended the quarter with $1.37 billion in cash and cash equivalents, and total inventory increased 7.3%. President & CEO Lauren Hobart said in the earnings release that consumer demand \\u201cremained strong,\\u201d and Dick\\u2019s \\u201cdifferentiated product assortment\\u201d helped drive momentum for sales and merchandise margins. Dick\\u2019s Sporting Goods also raised its adjusted EPS outlook, and now anticipates its bottom line to clock in between $14.60 and $14.80 per share DKS Offers Growth & Value Over the past one-year period, shares of Dick\\u2019s have climbed over 56% compared to the S&P 500\\u2019s gain of 17%. Estimates have been rising too, and DKS is a Zacks Rank #1 (Strong Buy) right now. For the current fiscal year, nine analysts have revised their bottom-line estimate upwards in the last 60 days, and the Zacks Consensus Estimate has moved up from $14.45 per share to $15.40 per share. Earnings are expected to see triple-digit growth for fiscal 2021, increasing more than 150%. Like fellow sports and outdoor recreational retailers, DKS saw a sales boom during the pandemic as people stuck at home looked to spend more time outside. The company benefited from social distancing as well, as outdoor activities allowed people to safely spend time with their loved ones. Q3 2021 marked the third consecutive \\u201cbeat-and-raise\\u201d quarter for Dick\\u2019s Sporting Goods. With this kind of growth, you\\u2019d expect to pay up, but DKS trades at only a 7.4X forward earnings multiple.Even more, Dick\\u2019s has a solid dividend that yields 1.6% on an annual basis. If you\\u2019re an investor searching for a retail stock to add to your portfolio, make sure to keep DKS on your shortlist. Bear of\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 = 0.0215 (i.e., a 2.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0215 = 4.6526, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021494, "expected_loss": 0.021494, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220426_0987", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2022-04-26", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0385, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0006, std=0.0201, worst_day=-0.0399\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-04-25] [\"Adobe Systems (ADBE) Outpaces Stock Market Gains: What You Should Know Adobe Systems (ADBE) closed at $413.95 in the latest trading session, marking a +1.29% move from the prior day. The stock outpaced the S&P 500's daily gain of 0.57%. Meanwhile, the Dow gained 0.7%, and the Nasdaq, a tech-heavy index, lost 0.1%. Prior to today's trading, shares of the software maker had lost 5.32% over the past month. This has was narrower than the Computer and Technology sector's loss of 11.12% and lagged the S&P 500's loss of 5.26% in that time. Adobe Systems will be looking to display strength as it nears its next earnings release. In that report, analysts expect Adobe Systems to post earnings of $3.30 per share. This would mark year-over-year growth of 8.91%. Our most recent consensus estimate is calling for quarterly revenue of $4.34 billion, up 13.12% from the year-ago period. For the full year, our Zacks Consensus Estimates are projecting earnings of $13.58 per share and revenue of $17.83 billion, which would represent changes of +8.81% and +12.93%, respectively, from the prior year. Investors might also notice recent changes to analyst estimates for Adobe Systems. These revisions help to show the ever-changing nature of near-term business trends. As a result, we can interpret positive estimate revisions as a good sign for the company's business outlook. Research indicates that these estimate revisions are directly correlated with near-term share price momentum. We developed the Zacks Rank to capitalize on this phenomenon. Our system takes these estimate changes into account and delivers a clear, actionable rating model. 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. Within the past 30 days, our consensus EPS projection has moved 0.01% higher. Adobe Systems is currently a Zacks Rank #3 (Hold). In terms of valuation, Adobe Systems is currently trading at a Forward P/E ratio of 30.09. Its industry sports an average Forward P/E of 28.39, so we one might conclude that Adobe Systems is trading at a premium comparatively. Meanwhile, ADBE's PEG ratio is currently 1.73. The PEG ratio is similar to the widely-used P/E ratio, but this metric also takes the company's expected earnings growth rate into account. The Computer - Software industry currently had an average PEG ratio of 2.37 as of yesterday's close. The Computer - Software industry is part of the Computer and Technology sector. This industry currently has a Zacks Industry Rank of 160, which puts it in the bottom 37% of all 250+ industries. The Zacks Industry Rank includes is listed in order 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. To follow ADBE in the coming trading sessions, b\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 = 0.0385 (i.e., a 3.85% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0385 = 2.5950, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.038536, "expected_loss": 0.038536, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220923_0989", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2022-09-23", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0279, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=-0.0007, std=0.0111, worst_day=-0.0325\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-09-22] [\"My 3 Favorite Stocks Right Now Investing more capital into your best ideas can lead to outsize rewards. The challenge, of course, is choosing the right stocks. To help you identify investments that are most worthy of your hard-earned money, I offer my three highest-conviction ideas right now. All are outstanding businesses that are well-positioned to generate handsome returns for their shareowners in the coming years. 1. The cloud data leader Snowflake (NYSE: SNOW) helps businesses make better use of their data at a time when harvesting valuable insights from the cloud is becoming more important every day. It's a massive market, one that could grow to a staggering $248 billion by 2026, according to the company's estimates. Snowflake is expanding at a blistering pace within this fast-growing market. Its revenue soared 83% year over year to $497 million in its fiscal 2023 second quarter, which ended on July 31. The company's new, consumption-based model is proving popular, as it allows businesses to pay only for the computing resources they use. By enabling its customers to better align their costs with their usage of data transfer, storage, and computing services, Snowflake is helping them save significant amounts of money. Companies, in turn, are flocking to Snowflake's cloud platform. It ended the second quarter with 6,808 customers, up 36% from the prior-year period. Snowflake also excels at deepening its relationships with its existing clients, as evidenced by its exceptional net revenue retention rate of 171%. Although Snowflake is not yet profitable (it generated an operating loss of $208 million in its most recent quarter), it did produce $54 million of free cash flow. Management also expects the company to reach impressive profitability by the end of the decade, with an adjusted operating margin of roughly 20%. With its data warehousing tools in high demand, investors can safely expect Snowflake's sales and cash flow production to grow even more impressive in the years ahead. Consider buying this cloud data leader's shares today so you, too, could cash in on its good growth prospects. 2. The e-commerce and cloud computing colossus Few businesses stand to benefit more from the global shift to the cloud than Amazon (NASDAQ: AMZN). Sure, Amazon is famous for its e-commerce platform. But the shining star these days is its Amazon Web Services (AWS), the leading provider of cloud infrastructure services. It's an incredibly valuable position to be in because an enormous amount of capital is expected to be invested in cloud computing services in the coming decade. AWS is already a $70 billion business. Yet only about 5% of worldwide information-technology spending is currently allocated toward cloud solutions, according to Amazon CEO Andy Jassy. Analysts expect this figure to march steadily higher, due to the security, cost, and scalability benefits that cloud computing provides compared to on-premise networks. Grand View Research, for one, proj\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 = 0.0279 (i.e., a 2.79% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0279 = 3.5860, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.027886, "expected_loss": 0.027886, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20220718_0991", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2022-07-18", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1355, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0037, std=0.0689, worst_day=-0.1362\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-07-17] \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": "0.7382", "answer_numeric": 0.7382, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1355 (i.e., a 13.55% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1355 = 0.7382, capped at 1.0.\nMaximum position size = 0.7382 (73.8% of portfolio).", "metadata": {"var_99": -0.135473, "expected_loss": 0.135473, "max_drawdown_threshold": 0.1, "position_size": 0.7382, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20200803_0993", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2020-08-03", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0375, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=0.0022, std=0.0167, worst_day=-0.0375\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-07-31] [\"Facebook Results Impress Despite Pandemic and Advertising Boycott The social media giant reported second-quarter sales of $18.7 billion and net income of $5.2 billion, easily beating Wall Street\\u2019s estimates.\", \"Asian markets fall after grim U.S. GDP data Stocks sink in Tokyo and Sydney, but rise slightly in Hong Kong and mainland China Asian shares tumbled Friday as reports showed layoffs of American workers are persisting at high levels after the U.S. economy contracted at a nearly 33% annual pace in the spring, the worst quarter on record.\", \"Apple stock price target raised to $475 from $450 at Wedbush\", \"Apple's stock soars 6.0% toward record high after Q3 results late Thursday\", \"Apple beats on earnings and announces stock split, sending shares toward record high Apple reports more than $11 billion in profit and nearly $60 billion in revenue, destroying expectations as stock heads for 4-to-1 split Apple Inc. brushed off the COVID-19 crisis to report record June-quarter results that came in ahead of expectations, and the company said in plans to split its stock in an attempt to make it \\u201cmore accessible to a broader base of investors.\\u201d\", \"Facebook shares rally as quarterly results easily top Street view Facebook reports EPS of $1.80 vs $1.39 Street estimate Facebook Inc. shares rally in the extended session Thursday after the social-media giant blows past Wall Street estimates for the second quarter and addresses how advertiser boycotts could potentially affect their business.\", \"Apple's stock soars after earnings, to add nearly 160 points to the Dow's price Shares of Apple Inc. shot up 6.1% toward a record high in premarket trading Friday, enough to pace the early gainers within the Dow Jones Industrial Average , in the wake of technology behemoth's blowout fiscal third-quarter results and announcement of a coming 4 for 1 stock split. The implied price gain, which should take the stock well above the $400 level for the first time after the open, would add about 159 points to the Dow's price, while Dow futures are up just 37 points, or 0.1%. The gain would also add about $100.3 billion to Apple market capitalization, to lift it to about $1.75 trillion, to further extend Apple's lead as the most valuable U.S. company.\", \"Apple stock price target raised to $440 from $400 at Deutsche Bank\", \"Apple stock price target raised to $470 from $370 at Monness Crespi Hardt\", \"Apple stock price target raised to $440 from $400 at Raymond James\", \"Barron\\u2019s Daily: Apple Stock Is Splitting Up. Here\\u2019s Why It Matters. Trump suggests postponing election, U.S. GDP contracts at fastest rate on record, no deal on federal unemployment benefits, and other news to start your day.\", \"Apple stock price target raised to $460 from $425 at J.P. Morgan\", \"The Nasdaq Gains as Apple Stock Soars. Chevron Drops. U.S. stocks appeared poised for a strong open after large tech companies dazzled Wall Street with their second-quarter results late Thursday.\",\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 = 0.0375 (i.e., a 3.75% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0375 = 2.6646, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037529, "expected_loss": 0.037529, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T3_all_20190404_0995", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2019-04-04", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0871, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0061, std=0.0445, worst_day=-0.1110\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\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 = 0.0871 (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": -0.087119, "expected_loss": 0.087119, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}}
{"id": "T3_all_20220106_0997", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2022-01-06", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1202, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0022, std=0.0573, worst_day=-0.1311\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2022-01-05] \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": "0.8316", "answer_numeric": 0.8316, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1202 (i.e., a 12.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1202 = 0.8316, capped at 1.0.\nMaximum position size = 0.8316 (83.2% of portfolio).", "metadata": {"var_99": -0.120248, "expected_loss": 0.120248, "max_drawdown_threshold": 0.1, "position_size": 0.8316, "has_text": true, "text_chars": 20}}
{"id": "T3_all_20200507_0999", "template": "T3", "complexity": 1, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2020-05-07", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0337, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0014, std=0.0254, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2020-05-06] [\"Wednesday Sector Laggards: Utilities, Financial In afternoon trading on Wednesday, Utilities stocks are the worst performing sector, showing a 2.3% loss. Within that group, NiSource Inc. (Symbol: NI) and American Electric Power Co Inc (Symbol: AEP) are two large stocks that are lagging, showing a loss of 5.6% and 4.1%, respectively. Among utilities ETFs, one ETF following the sector is the Utilities Select Sector SPDR ETF (Symbol: XLU), which is down 2.1% on the day, and down 13.25% year-to-date. NiSource Inc. , meanwhile, is down 15.32% year-to-date, and American Electric Power Co Inc, is down 14.73% year-to-date. Combined, NI and AEP make up approximately 6.3% of the underlying holdings of XLU. The next worst performing sector is the Financial sector, showing a 2.2% loss. Among large Financial stocks, Cincinnati Financial Corp. (Symbol: CINF) and Simon Property Group, Inc. (Symbol: SPG) are the most notable, showing a loss of 8.3% and 7.4%, respectively. One ETF closely tracking Financial stocks is the Financial Select Sector SPDR ETF (XLF), which is down 1.6% in midday trading, and down 29.83% on a year-to-date basis. Cincinnati Financial Corp., meanwhile, is down 48.00% year-to-date, and Simon Property Group, Inc., is down 60.95% year-to-date. CINF makes up approximately 0.4% of the underlying holdings of XLF. Comparing these stocks and ETFs on a trailing twelve month basis, below is a relative stock price performance chart, with each of the symbols shown in a different color as labeled in the legend at the bottom: Here's a snapshot of how the S&P 500 components within the various sectors are faring in afternoon trading on Wednesday. As you can see, one sector is up on the day, while seven sectors are down. SECTOR % CHANGE Technology & Communications +0.9% Healthcare 0.0% Services -0.2% Industrial -0.7% Consumer Products -0.9% Materials -1.6% Energy -1.8% Financial -2.2% Utilities -2.3% 25 Dividend Giants Widely Held By ETFs \\u00bb The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"American Electric Power Q1 20 Earnings Conference Call At 9:00 AM ET (RTTNews) - American Electric Power Co. Inc. (AEP) will host a conference call at 9:00 AM ET on May 6, 2020, to discuss Q1 20 earnings results. To access the live webcast, log on to http://www.aep.com/webcasts The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.\", \"American Electric Power Co Inc Q1 adjusted earnings Miss Estimates (RTTNews) - American Electric Power Co Inc (AEP) announced a profit for first quarter that declined from the same period last year. The company's earnings came in at $495.2 million, or $1.00 per share. This compares with $572.8 million, or $1.16 per share, in last year's first quarter. Excluding items, American Electric Power Co Inc reported adjusted earnings of $504.2 million or $1.02 per share for the p\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 = 0.0337 (i.e., a 3.37% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0337 = 2.9659, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033716, "expected_loss": 0.033716, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}}
{"id": "T4_all_20160523_0001", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BIL"], "decision_date": "2016-05-23", "context_summary": "IVV \u03c3=0.0071, BIL \u03c3=0.0002, \u03c1=0.088. Min-variance weights: IVV=0.000, BIL=1.000.", "question": "Assets: IVV, BIL\nIVV: annualized_mean_return=0.2016, daily_std=0.0071\nBIL: annualized_mean_return=0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0001\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_BIL) 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_BIL=X.XXXX", "answer": "w_IVV=0.0006, w_BIL=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 - 0.000000) / (0.000050 + 0.000000 - 0.000000)\n  Unconstrained: w_IVV=-0.0015\n  After long-only clamp: w_IVV=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"IVV": 0.0006, "BIL": 0.9994}, "sigma_1": 0.00706, "sigma_2": 0.00017, "covariance": 0.0, "correlation": 0.0877, "has_text": true, "text_chars": 3020, "mu_floor": 0.0001, "constraint_binding": false}}
{"id": "T4_all_20180613_0004", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "ICSH"], "decision_date": "2018-06-13", "context_summary": "XRP-USD \u03c3=0.0546, ICSH \u03c3=0.0003, \u03c1=0.230. Min-variance weights: XRP-USD=0.000, ICSH=1.000.", "question": "Assets: XRP-USD, ICSH\nXRP-USD: annualized_mean_return=-0.1512, daily_std=0.0546\nICSH: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): -0.0667\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 - 0.000003) / (0.002980 + 0.000000 - 0.000007)\n  Unconstrained: w_XRP-USD=-0.0011\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": 0.05459, "sigma_2": 0.000259, "covariance": 3e-06, "correlation": 0.2303, "has_text": false, "text_chars": 0, "mu_floor": -0.0667, "constraint_binding": false}}
{"id": "T4_all_20210326_0009", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "ICSH"], "decision_date": "2021-03-26", "context_summary": "SOL-USD \u03c3=0.0885, ICSH \u03c3=0.0002, \u03c1=0.269. Min-variance weights: SOL-USD=0.000, ICSH=1.000.", "question": "Assets: SOL-USD, ICSH\nSOL-USD: annualized_mean_return=6.3000, daily_std=0.0885\nICSH: annualized_mean_return=0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.0000\nMarket regime: sideways\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=0.0000, 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 - 0.000005) / (0.007838 + 0.000000 - 0.000010)\n  Unconstrained: w_SOL-USD=-0.0007\n  After long-only clamp: w_SOL-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"SOL-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.088531, "sigma_2": 0.000219, "covariance": 5e-06, "correlation": 0.2688, "has_text": false, "text_chars": 0, "mu_floor": -0.0, "constraint_binding": false}}
{"id": "T4_all_20210520_0012", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "INDS"], "decision_date": "2021-05-20", "context_summary": "EEM \u03c3=0.0131, INDS \u03c3=0.0101, \u03c1=0.391. Min-variance weights: EEM=0.299, INDS=0.701.", "question": "Assets: EEM, INDS\nEEM: annualized_mean_return=-0.2016, daily_std=0.0131\nINDS: annualized_mean_return=0.3528, daily_std=0.0101\nMinimum required portfolio return (annualized): 0.2527\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_INDS) 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_INDS=X.XXXX", "answer": "w_EEM=0.1806, w_INDS=0.8194", "answer_numeric": 0.1806, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000103 - 0.000052) / (0.000171 + 0.000103 - 0.000104)\n  Unconstrained: w_EEM=0.2994\n  After long-only clamp: w_EEM=0.2994, w_INDS=0.7006.", "metadata": {"weights": {"EEM": 0.1806, "INDS": 0.8194}, "sigma_1": 0.013087, "sigma_2": 0.010145, "covariance": 5.2e-05, "correlation": 0.391, "has_text": true, "text_chars": 3020, "mu_floor": 0.2527, "constraint_binding": true}}
{"id": "T4_all_20220127_0015", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "SGOV"], "decision_date": "2022-01-27", "context_summary": "BNB-USD \u03c3=0.0389, SGOV \u03c3=0.0001, \u03c1=0.060. Min-variance weights: BNB-USD=0.000, SGOV=1.000.", "question": "Assets: BNB-USD, SGOV\nBNB-USD: annualized_mean_return=-1.7640, daily_std=0.0389\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0752\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) / (0.001510 + 0.000000 - 0.000000)\n  Unconstrained: w_BNB-USD=-0.0001\n  After long-only clamp: w_BNB-USD=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"BNB-USD": 0.0, "SGOV": 1.0}, "sigma_1": 0.038861, "sigma_2": 5.9e-05, "covariance": 0.0, "correlation": 0.0601, "has_text": true, "text_chars": 20, "mu_floor": -0.0752, "constraint_binding": false}}
{"id": "T4_all_20210218_0018", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "DBA"], "decision_date": "2021-02-18", "context_summary": "IWM \u03c3=0.0121, DBA \u03c3=0.0063, \u03c1=0.023. Min-variance weights: IWM=0.208, DBA=0.792.", "question": "Assets: IWM, DBA\nIWM: annualized_mean_return=1.0080, daily_std=0.0121\nDBA: annualized_mean_return=0.3780, daily_std=0.0063\nMinimum required portfolio return (annualized): 0.7981\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=0.6668, w_DBA=0.3332", "answer_numeric": 0.6668, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000040 - 0.000002) / (0.000147 + 0.000040 - 0.000003)\n  Unconstrained: w_IWM=0.2083\n  After long-only clamp: w_IWM=0.2083, w_DBA=0.7917.", "metadata": {"weights": {"IWM": 0.6668, "DBA": 0.3332}, "sigma_1": 0.012106, "sigma_2": 0.006312, "covariance": 2e-06, "correlation": 0.0226, "has_text": true, "text_chars": 3020, "mu_floor": 0.7981, "constraint_binding": true}}
{"id": "T4_all_20200624_0023", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "IYR"], "decision_date": "2020-06-24", "context_summary": "XRP-USD \u03c3=0.0262, IYR \u03c3=0.0210, \u03c1=-0.103. Min-variance weights: XRP-USD=0.403, IYR=0.597.", "question": "Assets: XRP-USD, IYR\nXRP-USD: annualized_mean_return=-0.0252, daily_std=0.0262\nIYR: annualized_mean_return=0.3276, daily_std=0.0210\nMinimum required portfolio return (annualized): 0.0929\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=0.4029, w_IYR=0.5971", "answer_numeric": 0.4029, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000443 - -0.000057) / (0.000684 + 0.000443 - -0.000114)\n  Unconstrained: w_XRP-USD=0.4028\n  After long-only clamp: w_XRP-USD=0.4028, w_IYR=0.5972.", "metadata": {"weights": {"XRP-USD": 0.4029, "IYR": 0.5971}, "sigma_1": 0.026154, "sigma_2": 0.021047, "covariance": -5.7e-05, "correlation": -0.1034, "has_text": false, "text_chars": 0, "mu_floor": 0.0929, "constraint_binding": false}}
{"id": "T4_all_20200901_0028", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "REZ"], "decision_date": "2020-09-01", "context_summary": "XLV \u03c3=0.0094, REZ \u03c3=0.0164, \u03c1=0.504. Min-variance weights: XLV=0.946, REZ=0.054.", "question": "Assets: XLV, REZ\nXLV: annualized_mean_return=0.3276, daily_std=0.0094\nREZ: annualized_mean_return=-0.0504, daily_std=0.0164\nMinimum required portfolio return (annualized): 0.3210\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_REZ) 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_REZ=X.XXXX", "answer": "w_XLV=0.9825, w_REZ=0.0175", "answer_numeric": 0.9825, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000270 - 0.000078) / (0.000089 + 0.000270 - 0.000156)\n  Unconstrained: w_XLV=0.9464\n  After long-only clamp: w_XLV=0.9464, w_REZ=0.0536.", "metadata": {"weights": {"XLV": 0.9825, "REZ": 0.0175}, "sigma_1": 0.009423, "sigma_2": 0.016424, "covariance": 7.8e-05, "correlation": 0.5036, "has_text": true, "text_chars": 3020, "mu_floor": 0.321, "constraint_binding": true}}
{"id": "T4_all_20180727_0033", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "CORN"], "decision_date": "2018-07-27", "context_summary": "IWM \u03c3=0.0064, CORN \u03c3=0.0116, \u03c1=0.162. Min-variance weights: IWM=0.806, CORN=0.194.", "question": "Assets: IWM, CORN\nIWM: annualized_mean_return=0.3780, daily_std=0.0064\nCORN: annualized_mean_return=-0.3024, daily_std=0.0116\nMinimum required portfolio return (annualized): 0.1073\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=0.8057, w_CORN=0.1943", "answer_numeric": 0.8057, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000135 - 0.000012) / (0.000042 + 0.000135 - 0.000024)\n  Unconstrained: w_IWM=0.8062\n  After long-only clamp: w_IWM=0.8062, w_CORN=0.1938.", "metadata": {"weights": {"IWM": 0.8057, "CORN": 0.1943}, "sigma_1": 0.006448, "sigma_2": 0.011602, "covariance": 1.2e-05, "correlation": 0.1623, "has_text": true, "text_chars": 3020, "mu_floor": 0.1073, "constraint_binding": false}}
{"id": "T4_all_20160802_0040", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "SOYB"], "decision_date": "2016-08-02", "context_summary": "BTC-USD \u03c3=0.0381, SOYB \u03c3=0.0147, \u03c1=0.079. Min-variance weights: BTC-USD=0.109, SOYB=0.891.", "question": "Assets: BTC-USD, SOYB\nBTC-USD: annualized_mean_return=0.6804, daily_std=0.0381\nSOYB: annualized_mean_return=-0.0252, daily_std=0.0147\nMinimum required portfolio return (annualized): 0.3972\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_SOYB) 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_SOYB=X.XXXX", "answer": "w_BTC-USD=0.5986, w_SOYB=0.4014", "answer_numeric": 0.5986, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000216 - 0.000044) / (0.001451 + 0.000216 - 0.000088)\n  Unconstrained: w_BTC-USD=0.1087\n  After long-only clamp: w_BTC-USD=0.1087, w_SOYB=0.8913.", "metadata": {"weights": {"BTC-USD": 0.5986, "SOYB": 0.4014}, "sigma_1": 0.038093, "sigma_2": 0.014682, "covariance": 4.4e-05, "correlation": 0.0786, "has_text": false, "text_chars": 0, "mu_floor": 0.3972, "constraint_binding": true}}
{"id": "T4_all_20171107_0043", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "LQD"], "decision_date": "2017-11-07", "context_summary": "BTC-USD \u03c3=0.0450, LQD \u03c3=0.0022, \u03c1=0.032. Min-variance weights: BTC-USD=0.001, LQD=0.999.", "question": "Assets: BTC-USD, LQD\nBTC-USD: annualized_mean_return=2.0664, daily_std=0.0450\nLQD: annualized_mean_return=0.0504, daily_std=0.0022\nMinimum required portfolio return (annualized): 0.0511\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=0.0008, w_LQD=0.9992", "answer_numeric": 0.0008, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000005 - 0.000003) / (0.002026 + 0.000005 - 0.000006)\n  Unconstrained: w_BTC-USD=0.0008\n  After long-only clamp: w_BTC-USD=0.0008, w_LQD=0.9992.", "metadata": {"weights": {"BTC-USD": 0.0008, "LQD": 0.9992}, "sigma_1": 0.045014, "sigma_2": 0.002156, "covariance": 3e-06, "correlation": 0.0317, "has_text": false, "text_chars": 0, "mu_floor": 0.0511, "constraint_binding": false}}
{"id": "T4_all_20211130_0046", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ICSH"], "decision_date": "2021-11-30", "context_summary": "BNB-USD \u03c3=0.0397, ICSH \u03c3=0.0002, \u03c1=0.241. Min-variance weights: BNB-USD=0.000, ICSH=1.000.", "question": "Assets: BNB-USD, ICSH\nBNB-USD: annualized_mean_return=2.2176, daily_std=0.0397\nICSH: annualized_mean_return=-0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.8328\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=0.3755, w_ICSH=0.6245", "answer_numeric": 0.3755, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000002) / (0.001578 + 0.000000 - 0.000004)\n  Unconstrained: w_BNB-USD=-0.0012\n  After long-only clamp: w_BNB-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"BNB-USD": 0.3755, "ICSH": 0.6245}, "sigma_1": 0.039718, "sigma_2": 0.000194, "covariance": 2e-06, "correlation": 0.2409, "has_text": true, "text_chars": 20, "mu_floor": 0.8328, "constraint_binding": true}}
{"id": "T4_all_20221006_0049", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "USMV"], "decision_date": "2022-10-06", "context_summary": "DOT-USD \u03c3=0.0363, USMV \u03c3=0.0107, \u03c1=-0.103. Min-variance weights: DOT-USD=0.101, USMV=0.899.", "question": "Assets: DOT-USD, USMV\nDOT-USD: annualized_mean_return=-1.0080, daily_std=0.0363\nUSMV: annualized_mean_return=-0.0504, daily_std=0.0107\nMinimum required portfolio return (annualized): -0.5071\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_USMV) 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_USMV=X.XXXX", "answer": "w_DOT-USD=0.1014, w_USMV=0.8986", "answer_numeric": 0.1014, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000114 - -0.000040) / (0.001321 + 0.000114 - -0.000079)\n  Unconstrained: w_DOT-USD=0.1013\n  After long-only clamp: w_DOT-USD=0.1013, w_USMV=0.8987.", "metadata": {"weights": {"DOT-USD": 0.1014, "USMV": 0.8986}, "sigma_1": 0.036349, "sigma_2": 0.010659, "covariance": -4e-05, "correlation": -0.1026, "has_text": true, "text_chars": 20, "mu_floor": -0.5071, "constraint_binding": false}}
{"id": "T4_all_20210503_0052", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "GLD"], "decision_date": "2021-05-03", "context_summary": "MATIC-USD \u03c3=0.1198, GLD \u03c3=0.0086, \u03c1=-0.098. Min-variance weights: MATIC-USD=0.012, GLD=0.988.", "question": "Assets: MATIC-USD, GLD\nMATIC-USD: annualized_mean_return=6.6780, daily_std=0.1198\nGLD: annualized_mean_return=-0.1260, daily_std=0.0086\nMinimum required portfolio return (annualized): 4.8021\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=0.7243, w_GLD=0.2757", "answer_numeric": 0.7243, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000075 - -0.000101) / (0.014347 + 0.000075 - -0.000203)\n  Unconstrained: w_MATIC-USD=0.0120\n  After long-only clamp: w_MATIC-USD=0.0120, w_GLD=0.9880.", "metadata": {"weights": {"MATIC-USD": 0.7243, "GLD": 0.2757}, "sigma_1": 0.119781, "sigma_2": 0.008636, "covariance": -0.000101, "correlation": -0.0981, "has_text": false, "text_chars": 0, "mu_floor": 4.8021, "constraint_binding": true}}
{"id": "T4_all_20180129_0055", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "CORN"], "decision_date": "2018-01-29", "context_summary": "BNB-USD \u03c3=0.1088, CORN \u03c3=0.0055, \u03c1=-0.229. Min-variance weights: BNB-USD=0.014, CORN=0.986.", "question": "Assets: BNB-USD, CORN\nBNB-USD: annualized_mean_return=8.5932, daily_std=0.1088\nCORN: annualized_mean_return=-0.1008, daily_std=0.0055\nMinimum required portfolio return (annualized): -0.0306\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_CORN) 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_CORN=X.XXXX", "answer": "w_BNB-USD=0.0139, w_CORN=0.9861", "answer_numeric": 0.0139, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000030 - -0.000138) / (0.011839 + 0.000030 - -0.000275)\n  Unconstrained: w_BNB-USD=0.0138\n  After long-only clamp: w_BNB-USD=0.0138, w_CORN=0.9862.", "metadata": {"weights": {"BNB-USD": 0.0139, "CORN": 0.9861}, "sigma_1": 0.108808, "sigma_2": 0.005511, "covariance": -0.000138, "correlation": -0.2293, "has_text": false, "text_chars": 0, "mu_floor": -0.0306, "constraint_binding": false}}
{"id": "T4_all_20181008_0058", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "VCIT"], "decision_date": "2018-10-08", "context_summary": "EWJ \u03c3=0.0070, VCIT \u03c3=0.0016, \u03c1=0.104. Min-variance weights: EWJ=0.027, VCIT=0.973.", "question": "Assets: EWJ, VCIT\nEWJ: annualized_mean_return=0.1512, daily_std=0.0070\nVCIT: annualized_mean_return=-0.0252, daily_std=0.0016\nMinimum required portfolio return (annualized): 0.0473\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_EWJ=0.4110, w_VCIT=0.5890", "answer_numeric": 0.411, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000002 - 0.000001) / (0.000049 + 0.000002 - 0.000002)\n  Unconstrained: w_EWJ=0.0271\n  After long-only clamp: w_EWJ=0.0271, w_VCIT=0.9729.", "metadata": {"weights": {"EWJ": 0.411, "VCIT": 0.589}, "sigma_1": 0.006974, "sigma_2": 0.001571, "covariance": 1e-06, "correlation": 0.1044, "has_text": true, "text_chars": 3020, "mu_floor": 0.0473, "constraint_binding": true}}
{"id": "T4_all_20211029_0061", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD"], "decision_date": "2021-10-29", "context_summary": "QUAL \u03c3=0.0075, ETH-USD \u03c3=0.0480, \u03c1=0.096. Min-variance weights: QUAL=0.991, ETH-USD=0.009.", "question": "Assets: QUAL, ETH-USD\nQUAL: annualized_mean_return=0.1008, daily_std=0.0075\nETH-USD: annualized_mean_return=1.4868, daily_std=0.0480\nMinimum required portfolio return (annualized): 0.1063\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_ETH-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_ETH-USD=X.XXXX", "answer": "w_QUAL=0.9910, w_ETH-USD=0.0090", "answer_numeric": 0.991, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.002308 - 0.000035) / (0.000056 + 0.002308 - 0.000069)\n  Unconstrained: w_QUAL=0.9908\n  After long-only clamp: w_QUAL=0.9908, w_ETH-USD=0.0092.", "metadata": {"weights": {"QUAL": 0.991, "ETH-USD": 0.009}, "sigma_1": 0.007462, "sigma_2": 0.04804, "covariance": 3.5e-05, "correlation": 0.0964, "has_text": true, "text_chars": 3020, "mu_floor": 0.1063, "constraint_binding": false}}
{"id": "T4_all_20211008_0064", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "SGOV"], "decision_date": "2021-10-08", "context_summary": "ADA-USD \u03c3=0.0624, SGOV \u03c3=0.0001, \u03c1=0.120. Min-variance weights: ADA-USD=0.000, SGOV=1.000.", "question": "Assets: ADA-USD, SGOV\nADA-USD: annualized_mean_return=2.4444, daily_std=0.0624\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 1.4231\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_ADA-USD=0.5822, w_SGOV=0.4178", "answer_numeric": 0.5822, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000001) / (0.003900 + 0.000000 - 0.000001)\n  Unconstrained: w_ADA-USD=-0.0001\n  After long-only clamp: w_ADA-USD=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"ADA-USD": 0.5822, "SGOV": 0.4178}, "sigma_1": 0.062448, "sigma_2": 6.9e-05, "covariance": 1e-06, "correlation": 0.12, "has_text": false, "text_chars": 0, "mu_floor": 1.4231, "constraint_binding": true}}
{"id": "T4_all_20220915_0071", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ICSH"], "decision_date": "2022-09-15", "context_summary": "EWJ \u03c3=0.0112, ICSH \u03c3=0.0003, \u03c1=0.022. Min-variance weights: EWJ=0.000, ICSH=1.000.", "question": "Assets: EWJ, ICSH\nEWJ: annualized_mean_return=-0.0000, daily_std=0.0112\nICSH: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0208\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_ICSH) 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_ICSH=X.XXXX", "answer": "w_EWJ=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) / (0.000126 + 0.000000 - 0.000000)\n  Unconstrained: w_EWJ=0.0001\n  After long-only clamp: w_EWJ=0.0001, w_ICSH=0.9999.", "metadata": {"weights": {"EWJ": 0.0007, "ICSH": 0.9993}, "sigma_1": 0.011233, "sigma_2": 0.000303, "covariance": 0.0, "correlation": 0.0218, "has_text": true, "text_chars": 3020, "mu_floor": 0.0208, "constraint_binding": false}}
{"id": "T4_all_20200106_0074", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "ICSH"], "decision_date": "2020-01-06", "context_summary": "BTC-USD \u03c3=0.0255, ICSH \u03c3=0.0002, \u03c1=-0.046. Min-variance weights: BTC-USD=0.000, ICSH=1.000.", "question": "Assets: BTC-USD, ICSH\nBTC-USD: annualized_mean_return=-0.9072, daily_std=0.0255\nICSH: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0252\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_ICSH) 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_ICSH=X.XXXX", "answer": "w_BTC-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) / (0.000651 + 0.000000 - -0.000000)\n  Unconstrained: w_BTC-USD=0.0004\n  After long-only clamp: w_BTC-USD=0.0004, w_ICSH=0.9996.", "metadata": {"weights": {"BTC-USD": -0.0, "ICSH": 1.0}, "sigma_1": 0.02552, "sigma_2": 0.000207, "covariance": -0.0, "correlation": -0.0457, "has_text": false, "text_chars": 0, "mu_floor": 0.0252, "constraint_binding": true}}
{"id": "T4_all_20190619_0079", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ICSH"], "decision_date": "2019-06-19", "context_summary": "ACWI \u03c3=0.0072, ICSH \u03c3=0.0002, \u03c1=-0.012. Min-variance weights: ACWI=0.001, ICSH=0.999.", "question": "Assets: ACWI, ICSH\nACWI: annualized_mean_return=0.1512, daily_std=0.0072\nICSH: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0253\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=0.0009, 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 - -0.000000) / (0.000052 + 0.000000 - -0.000000)\n  Unconstrained: w_ACWI=0.0013\n  After long-only clamp: w_ACWI=0.0013, w_ICSH=0.9987.", "metadata": {"weights": {"ACWI": 0.0009, "ICSH": 0.9991}, "sigma_1": 0.007199, "sigma_2": 0.000217, "covariance": -0.0, "correlation": -0.0121, "has_text": true, "text_chars": 3020, "mu_floor": 0.0253, "constraint_binding": false}}
{"id": "T4_all_20210913_0089", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "PPLT"], "decision_date": "2021-09-13", "context_summary": "^VIX \u03c3=0.0779, PPLT \u03c3=0.0166, \u03c1=0.083. Min-variance weights: ^VIX=0.027, PPLT=0.973.", "question": "Assets: ^VIX, PPLT\n^VIX: annualized_mean_return=0.6048, daily_std=0.0779\nPPLT: annualized_mean_return=-0.3276, daily_std=0.0166\nMinimum required portfolio return (annualized): -0.3021\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_^VIX=0.0274, w_PPLT=0.9726", "answer_numeric": 0.0274, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000275 - 0.000107) / (0.006073 + 0.000275 - 0.000213)\n  Unconstrained: w_^VIX=0.0274\n  After long-only clamp: w_^VIX=0.0274, w_PPLT=0.9726.", "metadata": {"weights": {"^VIX": 0.0274, "PPLT": 0.9726}, "sigma_1": 0.077928, "sigma_2": 0.016578, "covariance": 0.000107, "correlation": 0.0826, "has_text": true, "text_chars": 3020, "mu_floor": -0.3021, "constraint_binding": false}}
{"id": "T4_all_20180406_0092", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "IAU"], "decision_date": "2018-04-06", "context_summary": "XLK \u03c3=0.0161, IAU \u03c3=0.0074, \u03c1=-0.004. Min-variance weights: XLK=0.175, IAU=0.825.", "question": "Assets: XLK, IAU\nXLK: annualized_mean_return=-0.0504, daily_std=0.0161\nIAU: annualized_mean_return=0.0756, daily_std=0.0074\nMinimum required portfolio return (annualized): 0.0698\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_IAU) 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_IAU=X.XXXX", "answer": "w_XLK=0.0460, w_IAU=0.9540", "answer_numeric": 0.046, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000055 - -0.000000) / (0.000259 + 0.000055 - -0.000001)\n  Unconstrained: w_XLK=0.1748\n  After long-only clamp: w_XLK=0.1748, w_IAU=0.8252.", "metadata": {"weights": {"XLK": 0.046, "IAU": 0.954}, "sigma_1": 0.016102, "sigma_2": 0.007385, "covariance": -0.0, "correlation": -0.004, "has_text": true, "text_chars": 3020, "mu_floor": 0.0698, "constraint_binding": true}}
{"id": "T4_all_20160111_0095", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "PDBC"], "decision_date": "2016-01-11", "context_summary": "IWM \u03c3=0.0120, PDBC \u03c3=0.0099, \u03c1=0.015. Min-variance weights: IWM=0.402, PDBC=0.598.", "question": "Assets: IWM, PDBC\nIWM: annualized_mean_return=-0.3780, daily_std=0.0120\nPDBC: annualized_mean_return=-0.7056, daily_std=0.0099\nMinimum required portfolio return (annualized): -0.6067\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_IWM=0.4016, w_PDBC=0.5984", "answer_numeric": 0.4016, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000097 - 0.000002) / (0.000144 + 0.000097 - 0.000003)\n  Unconstrained: w_IWM=0.4018\n  After long-only clamp: w_IWM=0.4018, w_PDBC=0.5982.", "metadata": {"weights": {"IWM": 0.4016, "PDBC": 0.5984}, "sigma_1": 0.011999, "sigma_2": 0.009863, "covariance": 2e-06, "correlation": 0.0146, "has_text": true, "text_chars": 3020, "mu_floor": -0.6067, "constraint_binding": false}}
{"id": "T4_all_20180703_0098", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LQD"], "decision_date": "2018-07-03", "context_summary": "MTUM \u03c3=0.0088, LQD \u03c3=0.0027, \u03c1=-0.054. Min-variance weights: MTUM=0.096, LQD=0.904.", "question": "Assets: MTUM, LQD\nMTUM: annualized_mean_return=0.3024, daily_std=0.0088\nLQD: annualized_mean_return=-0.0504, daily_std=0.0027\nMinimum required portfolio return (annualized): 0.0609\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_LQD) 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_LQD=X.XXXX", "answer": "w_MTUM=0.3155, w_LQD=0.6845", "answer_numeric": 0.3155, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000007 - -0.000001) / (0.000078 + 0.000007 - -0.000003)\n  Unconstrained: w_MTUM=0.0962\n  After long-only clamp: w_MTUM=0.0962, w_LQD=0.9038.", "metadata": {"weights": {"MTUM": 0.3155, "LQD": 0.6845}, "sigma_1": 0.00882, "sigma_2": 0.002673, "covariance": -1e-06, "correlation": -0.0536, "has_text": true, "text_chars": 3020, "mu_floor": 0.0609, "constraint_binding": true}}
{"id": "T4_all_20150714_0101", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "VCIT"], "decision_date": "2015-07-14", "context_summary": "BTC-USD \u03c3=0.0204, VCIT \u03c3=0.0035, \u03c1=0.000. Min-variance weights: BTC-USD=0.028, VCIT=0.972.", "question": "Assets: BTC-USD, VCIT\nBTC-USD: annualized_mean_return=0.9324, daily_std=0.0204\nVCIT: annualized_mean_return=-0.1260, daily_std=0.0035\nMinimum required portfolio return (annualized): -0.1052\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_BTC-USD=0.0283, w_VCIT=0.9717", "answer_numeric": 0.0283, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000012 - 0.000000) / (0.000417 + 0.000012 - 0.000000)\n  Unconstrained: w_BTC-USD=0.0283\n  After long-only clamp: w_BTC-USD=0.0283, w_VCIT=0.9717.", "metadata": {"weights": {"BTC-USD": 0.0283, "VCIT": 0.9717}, "sigma_1": 0.02041, "sigma_2": 0.003483, "covariance": 0.0, "correlation": 0.0001, "has_text": false, "text_chars": 0, "mu_floor": -0.1052, "constraint_binding": false}}
{"id": "T4_all_20180402_0104", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "HAUZ"], "decision_date": "2018-04-02", "context_summary": "XLU \u03c3=0.0102, HAUZ \u03c3=0.0096, \u03c1=0.109. Min-variance weights: XLU=0.466, HAUZ=0.534.", "question": "Assets: XLU, HAUZ\nXLU: annualized_mean_return=-0.1008, daily_std=0.0102\nHAUZ: annualized_mean_return=0.1260, daily_std=0.0096\nMinimum required portfolio return (annualized): 0.0438\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_XLU=0.3624, w_HAUZ=0.6376", "answer_numeric": 0.3624, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000093 - 0.000011) / (0.000105 + 0.000093 - 0.000022)\n  Unconstrained: w_XLU=0.4663\n  After long-only clamp: w_XLU=0.4663, w_HAUZ=0.5337.", "metadata": {"weights": {"XLU": 0.3624, "HAUZ": 0.6376}, "sigma_1": 0.010225, "sigma_2": 0.009628, "covariance": 1.1e-05, "correlation": 0.1094, "has_text": true, "text_chars": 3020, "mu_floor": 0.0438, "constraint_binding": true}}
{"id": "T4_all_20180607_0107", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ICSH"], "decision_date": "2018-06-07", "context_summary": "XLB \u03c3=0.0121, ICSH \u03c3=0.0003, \u03c1=-0.038. Min-variance weights: XLB=0.001, ICSH=0.999.", "question": "Assets: XLB, ICSH\nXLB: annualized_mean_return=0.0000, daily_std=0.0121\nICSH: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0164\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=0.0005, 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) / (0.000146 + 0.000000 - -0.000000)\n  Unconstrained: w_XLB=0.0014\n  After long-only clamp: w_XLB=0.0014, w_ICSH=0.9986.", "metadata": {"weights": {"XLB": 0.0005, "ICSH": 0.9995}, "sigma_1": 0.012086, "sigma_2": 0.000272, "covariance": -0.0, "correlation": -0.038, "has_text": true, "text_chars": 3020, "mu_floor": 0.0164, "constraint_binding": false}}
{"id": "T4_all_20171219_0108", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ICSH"], "decision_date": "2017-12-19", "context_summary": "XLI \u03c3=0.0058, ICSH \u03c3=0.0003, \u03c1=0.065. Min-variance weights: XLI=0.000, ICSH=1.000.", "question": "Assets: XLI, ICSH\nXLI: annualized_mean_return=0.2772, daily_std=0.0058\nICSH: annualized_mean_return=0.0000, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.1142\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=0.4120, w_ICSH=0.5880", "answer_numeric": 0.412, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000034 + 0.000000 - 0.000000)\n  Unconstrained: w_XLI=-0.0008\n  After long-only clamp: w_XLI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLI": 0.412, "ICSH": 0.588}, "sigma_1": 0.005815, "sigma_2": 0.000291, "covariance": 0.0, "correlation": 0.0653, "has_text": true, "text_chars": 3020, "mu_floor": 0.1142, "constraint_binding": true}}
{"id": "T4_all_20191126_0115", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LQD"], "decision_date": "2019-11-26", "context_summary": "XLF \u03c3=0.0083, LQD \u03c3=0.0038, \u03c1=-0.342. Min-variance weights: XLF=0.238, LQD=0.762.", "question": "Assets: XLF, LQD\nXLF: annualized_mean_return=0.5040, daily_std=0.0083\nLQD: annualized_mean_return=0.0000, daily_std=0.0038\nMinimum required portfolio return (annualized): 0.1196\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=0.2398, w_LQD=0.7602", "answer_numeric": 0.2398, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000014 - -0.000011) / (0.000069 + 0.000014 - -0.000021)\n  Unconstrained: w_XLF=0.2382\n  After long-only clamp: w_XLF=0.2382, w_LQD=0.7618.", "metadata": {"weights": {"XLF": 0.2398, "LQD": 0.7602}, "sigma_1": 0.008294, "sigma_2": 0.003764, "covariance": -1.1e-05, "correlation": -0.3423, "has_text": true, "text_chars": 3020, "mu_floor": 0.1196, "constraint_binding": false}}
{"id": "T4_all_20170317_0120", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "REZ"], "decision_date": "2017-03-17", "context_summary": "VEA \u03c3=0.0049, REZ \u03c3=0.0081, \u03c1=0.166. Min-variance weights: VEA=0.775, REZ=0.225.", "question": "Assets: VEA, REZ\nVEA: annualized_mean_return=0.3276, daily_std=0.0049\nREZ: annualized_mean_return=0.1512, daily_std=0.0081\nMinimum required portfolio return (annualized): 0.3082\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_REZ) 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_REZ=X.XXXX", "answer": "w_VEA=0.8900, w_REZ=0.1100", "answer_numeric": 0.89, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000066 - 0.000007) / (0.000024 + 0.000066 - 0.000013)\n  Unconstrained: w_VEA=0.7751\n  After long-only clamp: w_VEA=0.7751, w_REZ=0.2249.", "metadata": {"weights": {"VEA": 0.89, "REZ": 0.11}, "sigma_1": 0.004863, "sigma_2": 0.008093, "covariance": 7e-06, "correlation": 0.1661, "has_text": true, "text_chars": 3020, "mu_floor": 0.3082, "constraint_binding": true}}
{"id": "T4_all_20181121_0126", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "IGOV"], "decision_date": "2018-11-21", "context_summary": "XLI \u03c3=0.0114, IGOV \u03c3=0.0034, \u03c1=0.002. Min-variance weights: XLI=0.080, IGOV=0.920.", "question": "Assets: XLI, IGOV\nXLI: annualized_mean_return=-0.4536, daily_std=0.0114\nIGOV: annualized_mean_return=-0.1260, daily_std=0.0034\nMinimum required portfolio return (annualized): -0.1411\nMarket regime: sideways\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=0.0461, w_IGOV=0.9539", "answer_numeric": 0.0461, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000011 - 0.000000) / (0.000129 + 0.000011 - 0.000000)\n  Unconstrained: w_XLI=0.0802\n  After long-only clamp: w_XLI=0.0802, w_IGOV=0.9198.", "metadata": {"weights": {"XLI": 0.0461, "IGOV": 0.9539}, "sigma_1": 0.011372, "sigma_2": 0.003372, "covariance": 0.0, "correlation": 0.0025, "has_text": true, "text_chars": 3020, "mu_floor": -0.1411, "constraint_binding": true}}
{"id": "T4_all_20201021_0128", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DBA"], "decision_date": "2020-10-21", "context_summary": "XLB \u03c3=0.0134, DBA \u03c3=0.0072, \u03c1=0.169. Min-variance weights: XLB=0.176, DBA=0.824.", "question": "Assets: XLB, DBA\nXLB: annualized_mean_return=0.2268, daily_std=0.0134\nDBA: annualized_mean_return=0.3780, daily_std=0.0072\nMinimum required portfolio return (annualized): 0.3720\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=0.0397, w_DBA=0.9603", "answer_numeric": 0.0397, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000051 - 0.000016) / (0.000179 + 0.000051 - 0.000032)\n  Unconstrained: w_XLB=0.1765\n  After long-only clamp: w_XLB=0.1765, w_DBA=0.8235.", "metadata": {"weights": {"XLB": 0.0397, "DBA": 0.9603}, "sigma_1": 0.013396, "sigma_2": 0.007157, "covariance": 1.6e-05, "correlation": 0.1693, "has_text": true, "text_chars": 3020, "mu_floor": 0.372, "constraint_binding": true}}
{"id": "T4_all_20200911_0130", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "CORN"], "decision_date": "2020-09-11", "context_summary": "VLUE \u03c3=0.0122, CORN \u03c3=0.0124, \u03c1=-0.080. Min-variance weights: VLUE=0.507, CORN=0.493.", "question": "Assets: VLUE, CORN\nVLUE: annualized_mean_return=-0.0252, daily_std=0.0122\nCORN: annualized_mean_return=0.1512, daily_std=0.0124\nMinimum required portfolio return (annualized): 0.0949\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_CORN) 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_CORN=X.XXXX", "answer": "w_VLUE=0.3192, w_CORN=0.6808", "answer_numeric": 0.3192, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000154 - -0.000012) / (0.000149 + 0.000154 - -0.000024)\n  Unconstrained: w_VLUE=0.5073\n  After long-only clamp: w_VLUE=0.5073, w_CORN=0.4927.", "metadata": {"weights": {"VLUE": 0.3192, "CORN": 0.6808}, "sigma_1": 0.012196, "sigma_2": 0.01239, "covariance": -1.2e-05, "correlation": -0.08, "has_text": true, "text_chars": 3020, "mu_floor": 0.0949, "constraint_binding": true}}
{"id": "T4_all_20211022_0133", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "BIL"], "decision_date": "2021-10-22", "context_summary": "AVAX-USD \u03c3=0.0897, BIL \u03c3=0.0001, \u03c1=0.180. Min-variance weights: AVAX-USD=0.000, BIL=1.000.", "question": "Assets: AVAX-USD, BIL\nAVAX-USD: annualized_mean_return=2.4696, daily_std=0.0897\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0000\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=0.0000, 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 - 0.000002) / (0.008038 + 0.000000 - 0.000003)\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": 0.089653, "sigma_2": 0.0001, "covariance": 2e-06, "correlation": 0.1795, "has_text": true, "text_chars": 20, "mu_floor": -0.0, "constraint_binding": false}}
{"id": "T4_all_20180530_0136", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "HYG"], "decision_date": "2018-05-30", "context_summary": "VTI \u03c3=0.0098, HYG \u03c3=0.0024, \u03c1=-0.288. Min-variance weights: VTI=0.110, HYG=0.890.", "question": "Assets: VTI, HYG\nVTI: annualized_mean_return=0.0504, daily_std=0.0098\nHYG: annualized_mean_return=0.0000, daily_std=0.0024\nMinimum required portfolio return (annualized): 0.0318\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_HYG) 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_HYG=X.XXXX", "answer": "w_VTI=0.6310, w_HYG=0.3690", "answer_numeric": 0.631, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000006 - -0.000007) / (0.000097 + 0.000006 - -0.000014)\n  Unconstrained: w_VTI=0.1101\n  After long-only clamp: w_VTI=0.1101, w_HYG=0.8899.", "metadata": {"weights": {"VTI": 0.631, "HYG": 0.369}, "sigma_1": 0.009826, "sigma_2": 0.002433, "covariance": -7e-06, "correlation": -0.2876, "has_text": true, "text_chars": 3020, "mu_floor": 0.0318, "constraint_binding": true}}
{"id": "T4_all_20201110_0139", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "PALL"], "decision_date": "2020-11-10", "context_summary": "^VIX \u03c3=0.0679, PALL \u03c3=0.0181, \u03c1=-0.196. Min-variance weights: ^VIX=0.105, PALL=0.895.", "question": "Assets: ^VIX, PALL\n^VIX: annualized_mean_return=0.6552, daily_std=0.0679\nPALL: annualized_mean_return=0.5544, daily_std=0.0181\nMinimum required portfolio return (annualized): 0.5597\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_PALL) 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_PALL=X.XXXX", "answer": "w_^VIX=0.1052, w_PALL=0.8948", "answer_numeric": 0.1052, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000329 - -0.000241) / (0.004604 + 0.000329 - -0.000482)\n  Unconstrained: w_^VIX=0.1052\n  After long-only clamp: w_^VIX=0.1052, w_PALL=0.8948.", "metadata": {"weights": {"^VIX": 0.1052, "PALL": 0.8948}, "sigma_1": 0.067851, "sigma_2": 0.018129, "covariance": -0.000241, "correlation": -0.1961, "has_text": true, "text_chars": 3020, "mu_floor": 0.5597, "constraint_binding": false}}
{"id": "T4_all_20201229_0142", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "PALL"], "decision_date": "2020-12-29", "context_summary": "ADA-USD \u03c3=0.0624, PALL \u03c3=0.0197, \u03c1=0.012. Min-variance weights: ADA-USD=0.088, PALL=0.912.", "question": "Assets: ADA-USD, PALL\nADA-USD: annualized_mean_return=3.0744, daily_std=0.0624\nPALL: annualized_mean_return=-0.0252, daily_std=0.0197\nMinimum required portfolio return (annualized): 1.7917\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_PALL) 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_PALL=X.XXXX", "answer": "w_ADA-USD=0.5862, w_PALL=0.4138", "answer_numeric": 0.5862, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000390 - 0.000015) / (0.003890 + 0.000390 - 0.000029)\n  Unconstrained: w_ADA-USD=0.0882\n  After long-only clamp: w_ADA-USD=0.0882, w_PALL=0.9118.", "metadata": {"weights": {"ADA-USD": 0.5862, "PALL": 0.4138}, "sigma_1": 0.06237, "sigma_2": 0.019737, "covariance": 1.5e-05, "correlation": 0.0119, "has_text": false, "text_chars": 0, "mu_floor": 1.7917, "constraint_binding": true}}
{"id": "T4_all_20170324_0145", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNO"], "decision_date": "2017-03-24", "context_summary": "FXI \u03c3=0.0078, BNO \u03c3=0.0135, \u03c1=0.140. Min-variance weights: FXI=0.782, BNO=0.218.", "question": "Assets: FXI, BNO\nFXI: annualized_mean_return=0.6048, daily_std=0.0078\nBNO: annualized_mean_return=-0.5292, daily_std=0.0135\nMinimum required portfolio return (annualized): -0.1508\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_BNO) 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_BNO=X.XXXX", "answer": "w_FXI=0.7822, w_BNO=0.2178", "answer_numeric": 0.7822, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000181 - 0.000015) / (0.000061 + 0.000181 - 0.000030)\n  Unconstrained: w_FXI=0.7816\n  After long-only clamp: w_FXI=0.7816, w_BNO=0.2184.", "metadata": {"weights": {"FXI": 0.7822, "BNO": 0.2178}, "sigma_1": 0.007827, "sigma_2": 0.01346, "covariance": 1.5e-05, "correlation": 0.1402, "has_text": true, "text_chars": 3020, "mu_floor": -0.1508, "constraint_binding": false}}
{"id": "T4_all_20201117_0148", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "VNQI"], "decision_date": "2020-11-17", "context_summary": "ADA-USD \u03c3=0.0438, VNQI \u03c3=0.0110, \u03c1=0.128. Min-variance weights: ADA-USD=0.031, VNQI=0.969.", "question": "Assets: ADA-USD, VNQI\nADA-USD: annualized_mean_return=0.6552, daily_std=0.0438\nVNQI: annualized_mean_return=0.3276, daily_std=0.0110\nMinimum required portfolio return (annualized): 0.5826\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=0.7784, w_VNQI=0.2216", "answer_numeric": 0.7784, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000121 - 0.000062) / (0.001919 + 0.000121 - 0.000123)\n  Unconstrained: w_ADA-USD=0.0311\n  After long-only clamp: w_ADA-USD=0.0311, w_VNQI=0.9689.", "metadata": {"weights": {"ADA-USD": 0.7784, "VNQI": 0.2216}, "sigma_1": 0.043812, "sigma_2": 0.011012, "covariance": 6.2e-05, "correlation": 0.1276, "has_text": false, "text_chars": 0, "mu_floor": 0.5826, "constraint_binding": true}}
{"id": "T4_all_20190312_0153", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ICSH"], "decision_date": "2019-03-12", "context_summary": "XLB \u03c3=0.0122, ICSH \u03c3=0.0002, \u03c1=-0.034. Min-variance weights: XLB=0.001, ICSH=0.999.", "question": "Assets: XLB, ICSH\nXLB: annualized_mean_return=0.2520, daily_std=0.0122\nICSH: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0253\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=0.0004, w_ICSH=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) / (0.000150 + 0.000000 - -0.000000)\n  Unconstrained: w_XLB=0.0011\n  After long-only clamp: w_XLB=0.0011, w_ICSH=0.9989.", "metadata": {"weights": {"XLB": 0.0004, "ICSH": 0.9996}, "sigma_1": 0.012243, "sigma_2": 0.000244, "covariance": -0.0, "correlation": -0.0344, "has_text": true, "text_chars": 3020, "mu_floor": 0.0253, "constraint_binding": false}}
{"id": "T4_all_20160822_0158", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ICSH"], "decision_date": "2016-08-22", "context_summary": "XLU \u03c3=0.0080, ICSH \u03c3=0.0008, \u03c1=-0.005. Min-variance weights: XLU=0.011, ICSH=0.989.", "question": "Assets: XLU, ICSH\nXLU: annualized_mean_return=0.2016, daily_std=0.0080\nICSH: annualized_mean_return=0.0000, daily_std=0.0008\nMinimum required portfolio return (annualized): 0.1012\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=0.5020, w_ICSH=0.4980", "answer_numeric": 0.502, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000001 - -0.000000) / (0.000064 + 0.000001 - -0.000000)\n  Unconstrained: w_XLU=0.0108\n  After long-only clamp: w_XLU=0.0108, w_ICSH=0.9892.", "metadata": {"weights": {"XLU": 0.502, "ICSH": 0.498}, "sigma_1": 0.007996, "sigma_2": 0.000818, "covariance": -0.0, "correlation": -0.0048, "has_text": true, "text_chars": 3020, "mu_floor": 0.1012, "constraint_binding": true}}
{"id": "T4_all_20190819_0161", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "IEF"], "decision_date": "2019-08-19", "context_summary": "XLF \u03c3=0.0115, IEF \u03c3=0.0033, \u03c1=-0.443. Min-variance weights: XLF=0.159, IEF=0.841.", "question": "Assets: XLF, IEF\nXLF: annualized_mean_return=-0.0504, daily_std=0.0115\nIEF: annualized_mean_return=0.2772, daily_std=0.0033\nMinimum required portfolio return (annualized): 0.0873\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_IEF) 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_IEF=X.XXXX", "answer": "w_XLF=0.1585, w_IEF=0.8415", "answer_numeric": 0.1585, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000011 - -0.000017) / (0.000133 + 0.000011 - -0.000034)\n  Unconstrained: w_XLF=0.1586\n  After long-only clamp: w_XLF=0.1586, w_IEF=0.8414.", "metadata": {"weights": {"XLF": 0.1585, "IEF": 0.8415}, "sigma_1": 0.011515, "sigma_2": 0.003343, "covariance": -1.7e-05, "correlation": -0.4427, "has_text": true, "text_chars": 3020, "mu_floor": 0.0873, "constraint_binding": false}}
{"id": "T4_all_20181004_0164", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "WEAT"], "decision_date": "2018-10-04", "context_summary": "XLK \u03c3=0.0071, WEAT \u03c3=0.0165, \u03c1=-0.088. Min-variance weights: XLK=0.823, WEAT=0.177.", "question": "Assets: XLK, WEAT\nXLK: annualized_mean_return=0.2520, daily_std=0.0071\nWEAT: annualized_mean_return=0.3024, daily_std=0.0165\nMinimum required portfolio return (annualized): 0.2898\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_WEAT) 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_WEAT=X.XXXX", "answer": "w_XLK=0.2500, w_WEAT=0.7500", "answer_numeric": 0.25, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000273 - -0.000010) / (0.000051 + 0.000273 - -0.000021)\n  Unconstrained: w_XLK=0.8227\n  After long-only clamp: w_XLK=0.8227, w_WEAT=0.1773.", "metadata": {"weights": {"XLK": 0.25, "WEAT": 0.75}, "sigma_1": 0.007118, "sigma_2": 0.016513, "covariance": -1e-05, "correlation": -0.088, "has_text": true, "text_chars": 3020, "mu_floor": 0.2898, "constraint_binding": true}}
{"id": "T4_all_20220707_0167", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "HAUZ"], "decision_date": "2022-07-07", "context_summary": "ETH-USD \u03c3=0.0556, HAUZ \u03c3=0.0114, \u03c1=-0.142. Min-variance weights: ETH-USD=0.065, HAUZ=0.935.", "question": "Assets: ETH-USD, HAUZ\nETH-USD: annualized_mean_return=-2.8980, daily_std=0.0556\nHAUZ: annualized_mean_return=-0.7308, daily_std=0.0114\nMinimum required portfolio return (annualized): -1.5414\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_ETH-USD=0.0648, w_HAUZ=0.9352", "answer_numeric": 0.0648, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000131 - -0.000090) / (0.003091 + 0.000131 - -0.000180)\n  Unconstrained: w_ETH-USD=0.0649\n  After long-only clamp: w_ETH-USD=0.0649, w_HAUZ=0.9351.", "metadata": {"weights": {"ETH-USD": 0.0648, "HAUZ": 0.9352}, "sigma_1": 0.055593, "sigma_2": 0.011425, "covariance": -9e-05, "correlation": -0.1418, "has_text": true, "text_chars": 20, "mu_floor": -1.5414, "constraint_binding": false}}
{"id": "T4_all_20180829_0170", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "UNG"], "decision_date": "2018-08-29", "context_summary": "BTC-USD \u03c3=0.0308, UNG \u03c3=0.0110, \u03c1=-0.323. Min-variance weights: BTC-USD=0.179, UNG=0.821.", "question": "Assets: BTC-USD, UNG\nBTC-USD: annualized_mean_return=0.6804, daily_std=0.0308\nUNG: annualized_mean_return=-0.0000, daily_std=0.0110\nMinimum required portfolio return (annualized): 0.4331\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_UNG) 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_UNG=X.XXXX", "answer": "w_BTC-USD=0.6365, w_UNG=0.3635", "answer_numeric": 0.6365, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000121 - -0.000110) / (0.000947 + 0.000121 - -0.000219)\n  Unconstrained: w_BTC-USD=0.1792\n  After long-only clamp: w_BTC-USD=0.1792, w_UNG=0.8208.", "metadata": {"weights": {"BTC-USD": 0.6365, "UNG": 0.3635}, "sigma_1": 0.030777, "sigma_2": 0.01101, "covariance": -0.00011, "correlation": -0.3232, "has_text": false, "text_chars": 0, "mu_floor": 0.4331, "constraint_binding": true}}
{"id": "T4_all_20210914_0175", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SGOV"], "decision_date": "2021-09-14", "context_summary": "XLI \u03c3=0.0090, SGOV \u03c3=0.0001, \u03c1=0.218. Min-variance weights: XLI=0.000, SGOV=1.000.", "question": "Assets: XLI, SGOV\nXLI: annualized_mean_return=0.0756, daily_std=0.0090\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0000\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=0.0001, 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) / (0.000081 + 0.000000 - 0.000000)\n  Unconstrained: w_XLI=-0.0016\n  After long-only clamp: w_XLI=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"XLI": 0.0001, "SGOV": 0.9999}, "sigma_1": 0.009019, "sigma_2": 6.7e-05, "covariance": 0.0, "correlation": 0.2179, "has_text": true, "text_chars": 3020, "mu_floor": -0.0, "constraint_binding": false}}
{"id": "T4_all_20181126_0178", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "CORN"], "decision_date": "2018-11-26", "context_summary": "BNB-USD \u03c3=0.0405, CORN \u03c3=0.0092, \u03c1=0.021. Min-variance weights: BNB-USD=0.045, CORN=0.955.", "question": "Assets: BNB-USD, CORN\nBNB-USD: annualized_mean_return=-2.4192, daily_std=0.0405\nCORN: annualized_mean_return=0.0504, daily_std=0.0092\nMinimum required portfolio return (annualized): 0.0202\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_CORN) 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_CORN=X.XXXX", "answer": "w_BNB-USD=0.0122, w_CORN=0.9878", "answer_numeric": 0.0122, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000085 - 0.000008) / (0.001642 + 0.000085 - 0.000015)\n  Unconstrained: w_BNB-USD=0.0449\n  After long-only clamp: w_BNB-USD=0.0449, w_CORN=0.9551.", "metadata": {"weights": {"BNB-USD": 0.0122, "CORN": 0.9878}, "sigma_1": 0.040523, "sigma_2": 0.009192, "covariance": 8e-06, "correlation": 0.0206, "has_text": false, "text_chars": 0, "mu_floor": 0.0202, "constraint_binding": true}}
{"id": "T4_all_20170615_0181", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "IEF"], "decision_date": "2017-06-15", "context_summary": "IVV \u03c3=0.0045, IEF \u03c3=0.0026, \u03c1=-0.059. Min-variance weights: IVV=0.261, IEF=0.739.", "question": "Assets: IVV, IEF\nIVV: annualized_mean_return=0.1260, daily_std=0.0045\nIEF: annualized_mean_return=0.1260, daily_std=0.0026\nMinimum required portfolio return (annualized): 0.1260\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_IEF) 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_IEF=X.XXXX", "answer": "w_IVV=0.2659, w_IEF=0.7341", "answer_numeric": 0.2659, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000007 - -0.000001) / (0.000020 + 0.000007 - -0.000001)\n  Unconstrained: w_IVV=0.2607\n  After long-only clamp: w_IVV=0.2607, w_IEF=0.7393.", "metadata": {"weights": {"IVV": 0.2659, "IEF": 0.7341}, "sigma_1": 0.0045, "sigma_2": 0.002588, "covariance": -1e-06, "correlation": -0.0589, "has_text": true, "text_chars": 3020, "mu_floor": 0.126, "constraint_binding": false}}
{"id": "T4_all_20220110_0184", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SGOV"], "decision_date": "2022-01-10", "context_summary": "IWM \u03c3=0.0141, SGOV \u03c3=0.0001, \u03c1=-0.126. Min-variance weights: IWM=0.001, SGOV=1.000.", "question": "Assets: IWM, SGOV\nIWM: annualized_mean_return=-0.1008, daily_std=0.0141\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0308\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=0.0000, 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) / (0.000197 + 0.000000 - -0.000000)\n  Unconstrained: w_IWM=0.0005\n  After long-only clamp: w_IWM=0.0005, w_SGOV=0.9995.", "metadata": {"weights": {"IWM": 0.0, "SGOV": 1.0}, "sigma_1": 0.014052, "sigma_2": 5.8e-05, "covariance": -0.0, "correlation": -0.1259, "has_text": true, "text_chars": 3020, "mu_floor": -0.0308, "constraint_binding": false}}
{"id": "T4_all_20220117_0187", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SGOV"], "decision_date": "2022-01-17", "context_summary": "VTI \u03c3=0.0093, SGOV \u03c3=0.0001, \u03c1=-0.044. Min-variance weights: VTI=0.000, SGOV=1.000.", "question": "Assets: VTI, SGOV\nVTI: annualized_mean_return=0.0252, daily_std=0.0093\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0001\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=0.0000, 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) / (0.000087 + 0.000000 - -0.000000)\n  Unconstrained: w_VTI=0.0003\n  After long-only clamp: w_VTI=0.0003, w_SGOV=0.9997.", "metadata": {"weights": {"VTI": 0.0, "SGOV": 1.0}, "sigma_1": 0.009313, "sigma_2": 5.8e-05, "covariance": -0.0, "correlation": -0.0439, "has_text": true, "text_chars": 3020, "mu_floor": -0.0001, "constraint_binding": false}}
{"id": "T4_all_20210316_0192", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ICSH"], "decision_date": "2021-03-16", "context_summary": "XLB \u03c3=0.0121, ICSH \u03c3=0.0002, \u03c1=-0.060. Min-variance weights: XLB=0.001, ICSH=0.999.", "question": "Assets: XLB, ICSH\nXLB: annualized_mean_return=0.4032, daily_std=0.0121\nICSH: annualized_mean_return=0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.1301\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=0.3227, w_ICSH=0.6773", "answer_numeric": 0.3227, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - -0.000000) / (0.000147 + 0.000000 - -0.000000)\n  Unconstrained: w_XLB=0.0014\n  After long-only clamp: w_XLB=0.0014, w_ICSH=0.9986.", "metadata": {"weights": {"XLB": 0.3227, "ICSH": 0.6773}, "sigma_1": 0.012114, "sigma_2": 0.000219, "covariance": -0.0, "correlation": -0.0602, "has_text": true, "text_chars": 3020, "mu_floor": 0.1301, "constraint_binding": true}}
{"id": "T4_all_20191203_0195", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "IAU"], "decision_date": "2019-12-03", "context_summary": "BNB-USD \u03c3=0.0370, IAU \u03c3=0.0068, \u03c1=-0.204. Min-variance weights: BNB-USD=0.064, IAU=0.936.", "question": "Assets: BNB-USD, IAU\nBNB-USD: annualized_mean_return=0.0252, daily_std=0.0370\nIAU: annualized_mean_return=-0.0756, daily_std=0.0068\nMinimum required portfolio return (annualized): -0.0711\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_IAU) 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_IAU=X.XXXX", "answer": "w_BNB-USD=0.0641, w_IAU=0.9359", "answer_numeric": 0.0641, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000046 - -0.000051) / (0.001367 + 0.000046 - -0.000103)\n  Unconstrained: w_BNB-USD=0.0642\n  After long-only clamp: w_BNB-USD=0.0642, w_IAU=0.9358.", "metadata": {"weights": {"BNB-USD": 0.0641, "IAU": 0.9359}, "sigma_1": 0.03697, "sigma_2": 0.006785, "covariance": -5.1e-05, "correlation": -0.2044, "has_text": false, "text_chars": 0, "mu_floor": -0.0711, "constraint_binding": false}}
{"id": "T4_all_20201006_0199", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "BIL"], "decision_date": "2020-10-06", "context_summary": "LINK-USD \u03c3=0.0799, BIL \u03c3=0.0001, \u03c1=0.248. Min-variance weights: LINK-USD=0.000, BIL=1.000.", "question": "Assets: LINK-USD, BIL\nLINK-USD: annualized_mean_return=-0.4536, daily_std=0.0799\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.2282\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 - 0.000002) / (0.006382 + 0.000000 - 0.000004)\n  Unconstrained: w_LINK-USD=-0.0003\n  After long-only clamp: w_LINK-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.07989, "sigma_2": 0.000101, "covariance": 2e-06, "correlation": 0.2477, "has_text": false, "text_chars": 0, "mu_floor": -0.2282, "constraint_binding": false}}
{"id": "T4_all_20191114_0202", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "IAU"], "decision_date": "2019-11-14", "context_summary": "MATIC-USD \u03c3=0.0485, IAU \u03c3=0.0083, \u03c1=-0.193. Min-variance weights: MATIC-USD=0.057, IAU=0.943.", "question": "Assets: MATIC-USD, IAU\nMATIC-USD: annualized_mean_return=0.8568, daily_std=0.0485\nIAU: annualized_mean_return=-0.1260, daily_std=0.0083\nMinimum required portfolio return (annualized): 0.2400\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=0.3724, w_IAU=0.6276", "answer_numeric": 0.3724, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000068 - -0.000077) / (0.002348 + 0.000068 - -0.000155)\n  Unconstrained: w_MATIC-USD=0.0567\n  After long-only clamp: w_MATIC-USD=0.0567, w_IAU=0.9433.", "metadata": {"weights": {"MATIC-USD": 0.3724, "IAU": 0.6276}, "sigma_1": 0.048453, "sigma_2": 0.00827, "covariance": -7.7e-05, "correlation": -0.1934, "has_text": false, "text_chars": 0, "mu_floor": 0.24, "constraint_binding": true}}
{"id": "T4_all_20211018_0223", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SGOV"], "decision_date": "2021-10-18", "context_summary": "ETH-USD \u03c3=0.0461, SGOV \u03c3=0.0001, \u03c1=-0.124. Min-variance weights: ETH-USD=0.000, SGOV=1.000.", "question": "Assets: ETH-USD, SGOV\nETH-USD: annualized_mean_return=1.2852, daily_std=0.0461\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0001\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) / (0.002128 + 0.000000 - -0.000001)\n  Unconstrained: w_ETH-USD=0.0002\n  After long-only clamp: w_ETH-USD=0.0002, w_SGOV=0.9998.", "metadata": {"weights": {"ETH-USD": 0.0, "SGOV": 1.0}, "sigma_1": 0.046131, "sigma_2": 6.1e-05, "covariance": -0.0, "correlation": -0.1242, "has_text": true, "text_chars": 20, "mu_floor": -0.0001, "constraint_binding": false}}
{"id": "T4_all_20160129_0226", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ITB"], "decision_date": "2016-01-29", "context_summary": "XLI \u03c3=0.0105, ITB \u03c3=0.0160, \u03c1=0.871. Min-variance weights: XLI=1.000, ITB=0.000.", "question": "Assets: XLI, ITB\nXLI: annualized_mean_return=-0.4284, daily_std=0.0105\nITB: annualized_mean_return=-0.5544, daily_std=0.0160\nMinimum required portfolio return (annualized): -0.4891\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=1.0000, w_ITB=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000256 - 0.000146) / (0.000110 + 0.000256 - 0.000292)\n  Unconstrained: w_XLI=1.4906\n  After long-only clamp: w_XLI=1.0000, w_ITB=0.0000.", "metadata": {"weights": {"XLI": 1.0, "ITB": 0.0}, "sigma_1": 0.010487, "sigma_2": 0.015996, "covariance": 0.000146, "correlation": 0.871, "has_text": true, "text_chars": 3020, "mu_floor": -0.4891, "constraint_binding": false}}
{"id": "T4_all_20190104_0231", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ICSH"], "decision_date": "2019-01-04", "context_summary": "EFA \u03c3=0.0109, ICSH \u03c3=0.0003, \u03c1=-0.139. Min-variance weights: EFA=0.004, ICSH=0.996.", "question": "Assets: EFA, ICSH\nEFA: annualized_mean_return=-0.5040, daily_std=0.0109\nICSH: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0165\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_ICSH) 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_ICSH=X.XXXX", "answer": "w_EFA=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) / (0.000118 + 0.000000 - -0.000001)\n  Unconstrained: w_EFA=0.0045\n  After long-only clamp: w_EFA=0.0045, w_ICSH=0.9955.", "metadata": {"weights": {"EFA": 0.0007, "ICSH": 0.9993}, "sigma_1": 0.010881, "sigma_2": 0.000294, "covariance": -0.0, "correlation": -0.1392, "has_text": true, "text_chars": 3020, "mu_floor": 0.0165, "constraint_binding": false}}
{"id": "T4_all_20221028_0236", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "IYR"], "decision_date": "2022-10-28", "context_summary": "SOL-USD \u03c3=0.0365, IYR \u03c3=0.0155, \u03c1=0.030. Min-variance weights: SOL-USD=0.144, IYR=0.856.", "question": "Assets: SOL-USD, IYR\nSOL-USD: annualized_mean_return=0.2016, daily_std=0.0365\nIYR: annualized_mean_return=-0.7308, daily_std=0.0155\nMinimum required portfolio return (annualized): -0.2076\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_IYR) 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_IYR=X.XXXX", "answer": "w_SOL-USD=0.5611, w_IYR=0.4389", "answer_numeric": 0.5611, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000239 - 0.000017) / (0.001331 + 0.000239 - 0.000034)\n  Unconstrained: w_SOL-USD=0.1445\n  After long-only clamp: w_SOL-USD=0.1445, w_IYR=0.8555.", "metadata": {"weights": {"SOL-USD": 0.5611, "IYR": 0.4389}, "sigma_1": 0.036486, "sigma_2": 0.015462, "covariance": 1.7e-05, "correlation": 0.0304, "has_text": true, "text_chars": 20, "mu_floor": -0.2076, "constraint_binding": true}}
{"id": "T4_all_20170504_0239", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "DBB"], "decision_date": "2017-05-04", "context_summary": "VTI \u03c3=0.0046, DBB \u03c3=0.0117, \u03c1=0.081. Min-variance weights: VTI=0.891, DBB=0.109.", "question": "Assets: VTI, DBB\nVTI: annualized_mean_return=0.1764, daily_std=0.0046\nDBB: annualized_mean_return=-0.1764, daily_std=0.0117\nMinimum required portfolio return (annualized): 0.0079\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_DBB) 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_DBB=X.XXXX", "answer": "w_VTI=0.8888, w_DBB=0.1112", "answer_numeric": 0.8888, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000138 - 0.000004) / (0.000021 + 0.000138 - 0.000009)\n  Unconstrained: w_VTI=0.8906\n  After long-only clamp: w_VTI=0.8906, w_DBB=0.1094.", "metadata": {"weights": {"VTI": 0.8888, "DBB": 0.1112}, "sigma_1": 0.004551, "sigma_2": 0.011728, "covariance": 4e-06, "correlation": 0.0815, "has_text": true, "text_chars": 3020, "mu_floor": 0.0079, "constraint_binding": false}}
{"id": "T4_all_20191224_0242", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "REZ"], "decision_date": "2019-12-24", "context_summary": "MATIC-USD \u03c3=0.0944, REZ \u03c3=0.0081, \u03c1=0.096. Min-variance weights: MATIC-USD=0.000, REZ=1.000.", "question": "Assets: MATIC-USD, REZ\nMATIC-USD: annualized_mean_return=3.5280, daily_std=0.0944\nREZ: annualized_mean_return=-0.2520, daily_std=0.0081\nMinimum required portfolio return (annualized): 1.7015\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_REZ) 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_REZ=X.XXXX", "answer": "w_MATIC-USD=0.5168, w_REZ=0.4832", "answer_numeric": 0.5168, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000066 - 0.000074) / (0.008908 + 0.000066 - 0.000148)\n  Unconstrained: w_MATIC-USD=-0.0009\n  After long-only clamp: w_MATIC-USD=0.0000, w_REZ=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.5168, "REZ": 0.4832}, "sigma_1": 0.094384, "sigma_2": 0.008131, "covariance": 7.4e-05, "correlation": 0.0964, "has_text": false, "text_chars": 0, "mu_floor": 1.7015, "constraint_binding": true}}
{"id": "T4_all_20200729_0245", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "PALL"], "decision_date": "2020-07-29", "context_summary": "MATIC-USD \u03c3=0.0409, PALL \u03c3=0.0208, \u03c1=-0.180. Min-variance weights: MATIC-USD=0.243, PALL=0.757.", "question": "Assets: MATIC-USD, PALL\nMATIC-USD: annualized_mean_return=-0.7812, daily_std=0.0409\nPALL: annualized_mean_return=0.7560, daily_std=0.0208\nMinimum required portfolio return (annualized): 0.0562\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_PALL) 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_PALL=X.XXXX", "answer": "w_MATIC-USD=0.2426, w_PALL=0.7574", "answer_numeric": 0.2426, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000432 - -0.000153) / (0.001673 + 0.000432 - -0.000306)\n  Unconstrained: w_MATIC-USD=0.2426\n  After long-only clamp: w_MATIC-USD=0.2426, w_PALL=0.7574.", "metadata": {"weights": {"MATIC-USD": 0.2426, "PALL": 0.7574}, "sigma_1": 0.040897, "sigma_2": 0.020781, "covariance": -0.000153, "correlation": -0.1797, "has_text": false, "text_chars": 0, "mu_floor": 0.0562, "constraint_binding": false}}
{"id": "T4_all_20210705_0248", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "GLD"], "decision_date": "2021-07-05", "context_summary": "EWJ \u03c3=0.0092, GLD \u03c3=0.0078, \u03c1=0.268. Min-variance weights: EWJ=0.391, GLD=0.609.", "question": "Assets: EWJ, GLD\nEWJ: annualized_mean_return=-0.0252, daily_std=0.0092\nGLD: annualized_mean_return=0.1764, daily_std=0.0078\nMinimum required portfolio return (annualized): 0.1605\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_GLD) 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_GLD=X.XXXX", "answer": "w_EWJ=0.0789, w_GLD=0.9211", "answer_numeric": 0.0789, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000061 - 0.000019) / (0.000085 + 0.000061 - 0.000039)\n  Unconstrained: w_EWJ=0.3908\n  After long-only clamp: w_EWJ=0.3908, w_GLD=0.6092.", "metadata": {"weights": {"EWJ": 0.0789, "GLD": 0.9211}, "sigma_1": 0.009203, "sigma_2": 0.007826, "covariance": 1.9e-05, "correlation": 0.268, "has_text": true, "text_chars": 3020, "mu_floor": 0.1605, "constraint_binding": true}}
{"id": "T4_all_20151008_0251", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "PPLT"], "decision_date": "2015-10-08", "context_summary": "XLK \u03c3=0.0147, PPLT \u03c3=0.0133, \u03c1=0.416. Min-variance weights: XLK=0.414, PPLT=0.586.", "question": "Assets: XLK, PPLT\nXLK: annualized_mean_return=-0.1512, daily_std=0.0147\nPPLT: annualized_mean_return=-0.3276, daily_std=0.0133\nMinimum required portfolio return (annualized): -0.2769\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_XLK=0.4143, w_PPLT=0.5857", "answer_numeric": 0.4143, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000176 - 0.000081) / (0.000216 + 0.000176 - 0.000162)\n  Unconstrained: w_XLK=0.4143\n  After long-only clamp: w_XLK=0.4143, w_PPLT=0.5857.", "metadata": {"weights": {"XLK": 0.4143, "PPLT": 0.5857}, "sigma_1": 0.01468, "sigma_2": 0.013272, "covariance": 8.1e-05, "correlation": 0.4156, "has_text": true, "text_chars": 3020, "mu_floor": -0.2769, "constraint_binding": false}}
{"id": "T4_all_20171201_0254", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "VNQ"], "decision_date": "2017-12-01", "context_summary": "XLI \u03c3=0.0052, VNQ \u03c3=0.0051, \u03c1=0.083. Min-variance weights: XLI=0.488, VNQ=0.512.", "question": "Assets: XLI, VNQ\nXLI: annualized_mean_return=0.4032, daily_std=0.0052\nVNQ: annualized_mean_return=0.0504, daily_std=0.0051\nMinimum required portfolio return (annualized): 0.2951\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_VNQ) 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_VNQ=X.XXXX", "answer": "w_XLI=0.6936, w_VNQ=0.3064", "answer_numeric": 0.6936, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000026 - 0.000002) / (0.000027 + 0.000026 - 0.000004)\n  Unconstrained: w_XLI=0.4883\n  After long-only clamp: w_XLI=0.4883, w_VNQ=0.5117.", "metadata": {"weights": {"XLI": 0.6936, "VNQ": 0.3064}, "sigma_1": 0.005206, "sigma_2": 0.005095, "covariance": 2e-06, "correlation": 0.0829, "has_text": true, "text_chars": 3020, "mu_floor": 0.2951, "constraint_binding": true}}
{"id": "T4_all_20160108_0260", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "TLH"], "decision_date": "2016-01-08", "context_summary": "EWJ \u03c3=0.0100, TLH \u03c3=0.0041, \u03c1=-0.282. Min-variance weights: EWJ=0.205, TLH=0.795.", "question": "Assets: EWJ, TLH\nEWJ: annualized_mean_return=-0.1260, daily_std=0.0100\nTLH: annualized_mean_return=-0.0252, daily_std=0.0041\nMinimum required portfolio return (annualized): -0.0347\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_TLH) 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_TLH=X.XXXX", "answer": "w_EWJ=0.0942, w_TLH=0.9058", "answer_numeric": 0.0942, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000017 - -0.000012) / (0.000100 + 0.000017 - -0.000023)\n  Unconstrained: w_EWJ=0.2047\n  After long-only clamp: w_EWJ=0.2047, w_TLH=0.7953.", "metadata": {"weights": {"EWJ": 0.0942, "TLH": 0.9058}, "sigma_1": 0.010011, "sigma_2": 0.004137, "covariance": -1.2e-05, "correlation": -0.2822, "has_text": true, "text_chars": 3020, "mu_floor": -0.0347, "constraint_binding": true}}
{"id": "T4_all_20190314_0263", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "STIP"], "decision_date": "2019-03-14", "context_summary": "XLV \u03c3=0.0114, STIP \u03c3=0.0009, \u03c1=0.137. Min-variance weights: XLV=0.000, STIP=1.000.", "question": "Assets: XLV, STIP\nXLV: annualized_mean_return=-0.0504, daily_std=0.0114\nSTIP: annualized_mean_return=0.0756, daily_std=0.0009\nMinimum required portfolio return (annualized): 0.0741\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_STIP) 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_STIP=X.XXXX", "answer": "w_XLV=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  = (0.000001 - 0.000001) / (0.000130 + 0.000001 - 0.000003)\n  Unconstrained: w_XLV=-0.0047\n  After long-only clamp: w_XLV=0.0000, w_STIP=1.0000.", "metadata": {"weights": {"XLV": 0.0, "STIP": 1.0}, "sigma_1": 0.011392, "sigma_2": 0.000876, "covariance": 1e-06, "correlation": 0.1373, "has_text": true, "text_chars": 3020, "mu_floor": 0.0741, "constraint_binding": false}}
{"id": "T4_all_20160505_0269", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "IEF"], "decision_date": "2016-05-05", "context_summary": "XLK \u03c3=0.0089, IEF \u03c3=0.0034, \u03c1=-0.006. Min-variance weights: XLK=0.130, IEF=0.870.", "question": "Assets: XLK, IEF\nXLK: annualized_mean_return=0.3276, daily_std=0.0089\nIEF: annualized_mean_return=-0.0252, daily_std=0.0034\nMinimum required portfolio return (annualized): 0.0141\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_IEF) 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_IEF=X.XXXX", "answer": "w_XLK=0.1289, w_IEF=0.8711", "answer_numeric": 0.1289, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000012 - -0.000000) / (0.000079 + 0.000012 - -0.000000)\n  Unconstrained: w_XLK=0.1304\n  After long-only clamp: w_XLK=0.1304, w_IEF=0.8696.", "metadata": {"weights": {"XLK": 0.1289, "IEF": 0.8711}, "sigma_1": 0.008908, "sigma_2": 0.003426, "covariance": -0.0, "correlation": -0.0062, "has_text": true, "text_chars": 3020, "mu_floor": 0.0141, "constraint_binding": false}}
{"id": "T4_all_20221214_0276", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "HYG"], "decision_date": "2022-12-14", "context_summary": "DOT-USD \u03c3=0.0385, HYG \u03c3=0.0078, \u03c1=-0.226. Min-variance weights: DOT-USD=0.077, HYG=0.923.", "question": "Assets: DOT-USD, HYG\nDOT-USD: annualized_mean_return=-0.3780, daily_std=0.0385\nHYG: annualized_mean_return=0.1008, daily_std=0.0078\nMinimum required portfolio return (annualized): 0.0755\nMarket regime: sideways\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=0.0528, w_HYG=0.9472", "answer_numeric": 0.0528, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000061 - -0.000068) / (0.001479 + 0.000061 - -0.000135)\n  Unconstrained: w_DOT-USD=0.0766\n  After long-only clamp: w_DOT-USD=0.0766, w_HYG=0.9234.", "metadata": {"weights": {"DOT-USD": 0.0528, "HYG": 0.9472}, "sigma_1": 0.038458, "sigma_2": 0.007783, "covariance": -6.8e-05, "correlation": -0.2259, "has_text": true, "text_chars": 20, "mu_floor": 0.0755, "constraint_binding": true}}
{"id": "T4_all_20170824_0279", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "PPLT"], "decision_date": "2017-08-24", "context_summary": "QUAL \u03c3=0.0049, PPLT \u03c3=0.0088, \u03c1=-0.065. Min-variance weights: QUAL=0.747, PPLT=0.253.", "question": "Assets: QUAL, PPLT\nQUAL: annualized_mean_return=0.0252, daily_std=0.0049\nPPLT: annualized_mean_return=0.1512, daily_std=0.0088\nMinimum required portfolio return (annualized): 0.0569\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_QUAL=0.7464, w_PPLT=0.2536", "answer_numeric": 0.7464, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000077 - -0.000003) / (0.000024 + 0.000077 - -0.000006)\n  Unconstrained: w_QUAL=0.7474\n  After long-only clamp: w_QUAL=0.7474, w_PPLT=0.2526.", "metadata": {"weights": {"QUAL": 0.7464, "PPLT": 0.2536}, "sigma_1": 0.004903, "sigma_2": 0.008751, "covariance": -3e-06, "correlation": -0.0645, "has_text": true, "text_chars": 3020, "mu_floor": 0.0569, "constraint_binding": false}}
{"id": "T4_all_20200217_0288", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DBA"], "decision_date": "2020-02-17", "context_summary": "ACWI \u03c3=0.0062, DBA \u03c3=0.0062, \u03c1=0.097. Min-variance weights: ACWI=0.495, DBA=0.505.", "question": "Assets: ACWI, DBA\nACWI: annualized_mean_return=0.2520, daily_std=0.0062\nDBA: annualized_mean_return=0.0252, daily_std=0.0062\nMinimum required portfolio return (annualized): 0.1993\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_DBA) 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_DBA=X.XXXX", "answer": "w_ACWI=0.7676, w_DBA=0.2324", "answer_numeric": 0.7676, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000038 - 0.000004) / (0.000039 + 0.000038 - 0.000007)\n  Unconstrained: w_ACWI=0.4950\n  After long-only clamp: w_ACWI=0.4950, w_DBA=0.5050.", "metadata": {"weights": {"ACWI": 0.7676, "DBA": 0.2324}, "sigma_1": 0.006214, "sigma_2": 0.006159, "covariance": 4e-06, "correlation": 0.0966, "has_text": true, "text_chars": 3020, "mu_floor": 0.1993, "constraint_binding": true}}
{"id": "T4_all_20210512_0291", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "IEF"], "decision_date": "2021-05-12", "context_summary": "AVAX-USD \u03c3=0.0780, IEF \u03c3=0.0036, \u03c1=0.097. Min-variance weights: AVAX-USD=0.000, IEF=1.000.", "question": "Assets: AVAX-USD, IEF\nAVAX-USD: annualized_mean_return=1.8900, daily_std=0.0780\nIEF: annualized_mean_return=-0.0252, daily_std=0.0036\nMinimum required portfolio return (annualized): -0.0252\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_IEF) 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_IEF=X.XXXX", "answer": "w_AVAX-USD=0.0000, w_IEF=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 - 0.000027) / (0.006079 + 0.000013 - 0.000054)\n  Unconstrained: w_AVAX-USD=-0.0024\n  After long-only clamp: w_AVAX-USD=0.0000, w_IEF=1.0000.", "metadata": {"weights": {"AVAX-USD": 0.0, "IEF": 1.0}, "sigma_1": 0.077966, "sigma_2": 0.00355, "covariance": 2.7e-05, "correlation": 0.0969, "has_text": false, "text_chars": 0, "mu_floor": -0.0252, "constraint_binding": false}}
{"id": "T4_all_20201013_0294", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "PDBC"], "decision_date": "2020-10-13", "context_summary": "XLV \u03c3=0.0098, PDBC \u03c3=0.0102, \u03c1=0.497. Min-variance weights: XLV=0.541, PDBC=0.459.", "question": "Assets: XLV, PDBC\nXLV: annualized_mean_return=0.1512, daily_std=0.0098\nPDBC: annualized_mean_return=0.1008, daily_std=0.0102\nMinimum required portfolio return (annualized): 0.1429\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_XLV=0.8353, w_PDBC=0.1647", "answer_numeric": 0.8353, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000105 - 0.000050) / (0.000096 + 0.000105 - 0.000100)\n  Unconstrained: w_XLV=0.5410\n  After long-only clamp: w_XLV=0.5410, w_PDBC=0.4590.", "metadata": {"weights": {"XLV": 0.8353, "PDBC": 0.1647}, "sigma_1": 0.009811, "sigma_2": 0.010225, "covariance": 5e-05, "correlation": 0.4969, "has_text": true, "text_chars": 3020, "mu_floor": 0.1429, "constraint_binding": true}}
{"id": "T4_all_20210309_0297", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "IYR"], "decision_date": "2021-03-09", "context_summary": "ADA-USD \u03c3=0.0805, IYR \u03c3=0.0100, \u03c1=0.138. Min-variance weights: ADA-USD=0.000, IYR=1.000.", "question": "Assets: ADA-USD, IYR\nADA-USD: annualized_mean_return=6.0228, daily_std=0.0805\nIYR: annualized_mean_return=0.1260, daily_std=0.0100\nMinimum required portfolio return (annualized): 0.1260\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_IYR) 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_IYR=X.XXXX", "answer": "w_ADA-USD=0.0000, w_IYR=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000100 - 0.000111) / (0.006486 + 0.000100 - 0.000222)\n  Unconstrained: w_ADA-USD=-0.0017\n  After long-only clamp: w_ADA-USD=0.0000, w_IYR=1.0000.", "metadata": {"weights": {"ADA-USD": 0.0, "IYR": 1.0}, "sigma_1": 0.080538, "sigma_2": 0.010001, "covariance": 0.000111, "correlation": 0.1378, "has_text": false, "text_chars": 0, "mu_floor": 0.126, "constraint_binding": false}}
{"id": "T4_all_20190211_0300", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DBC"], "decision_date": "2019-02-11", "context_summary": "XLB \u03c3=0.0137, DBC \u03c3=0.0106, \u03c1=0.096. Min-variance weights: XLB=0.365, DBC=0.635.", "question": "Assets: XLB, DBC\nXLB: annualized_mean_return=-0.2268, daily_std=0.0137\nDBC: annualized_mean_return=-0.0252, daily_std=0.0106\nMinimum required portfolio return (annualized): -0.0612\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_DBC) 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_DBC=X.XXXX", "answer": "w_XLB=0.1786, w_DBC=0.8214", "answer_numeric": 0.1786, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000113 - 0.000014) / (0.000187 + 0.000113 - 0.000028)\n  Unconstrained: w_XLB=0.3646\n  After long-only clamp: w_XLB=0.3646, w_DBC=0.6354.", "metadata": {"weights": {"XLB": 0.1786, "DBC": 0.8214}, "sigma_1": 0.013672, "sigma_2": 0.010641, "covariance": 1.4e-05, "correlation": 0.0963, "has_text": true, "text_chars": 3020, "mu_floor": -0.0612, "constraint_binding": true}}
{"id": "T4_all_20190201_0303", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "HAUZ"], "decision_date": "2019-02-01", "context_summary": "MTUM \u03c3=0.0158, HAUZ \u03c3=0.0100, \u03c1=0.604. Min-variance weights: MTUM=0.028, HAUZ=0.973.", "question": "Assets: MTUM, HAUZ\nMTUM: annualized_mean_return=-0.2016, daily_std=0.0158\nHAUZ: annualized_mean_return=0.2268, daily_std=0.0100\nMinimum required portfolio return (annualized): 0.0747\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_MTUM=0.0275, w_HAUZ=0.9725", "answer_numeric": 0.0275, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000099 - 0.000095) / (0.000249 + 0.000099 - 0.000190)\n  Unconstrained: w_MTUM=0.0275\n  After long-only clamp: w_MTUM=0.0275, w_HAUZ=0.9725.", "metadata": {"weights": {"MTUM": 0.0275, "HAUZ": 0.9725}, "sigma_1": 0.015768, "sigma_2": 0.009967, "covariance": 9.5e-05, "correlation": 0.6044, "has_text": true, "text_chars": 3020, "mu_floor": 0.0747, "constraint_binding": false}}
{"id": "T4_all_20171019_0305", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LQD"], "decision_date": "2017-10-19", "context_summary": "XLU \u03c3=0.0057, LQD \u03c3=0.0022, \u03c1=-0.136. Min-variance weights: XLU=0.166, LQD=0.834.", "question": "Assets: XLU, LQD\nXLU: annualized_mean_return=0.1764, daily_std=0.0057\nLQD: annualized_mean_return=0.0252, daily_std=0.0022\nMinimum required portfolio return (annualized): 0.0474\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_LQD) 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_LQD=X.XXXX", "answer": "w_XLU=0.1705, w_LQD=0.8295", "answer_numeric": 0.1705, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000005 - -0.000002) / (0.000032 + 0.000005 - -0.000003)\n  Unconstrained: w_XLU=0.1659\n  After long-only clamp: w_XLU=0.1659, w_LQD=0.8341.", "metadata": {"weights": {"XLU": 0.1705, "LQD": 0.8295}, "sigma_1": 0.005662, "sigma_2": 0.002236, "covariance": -2e-06, "correlation": -0.1357, "has_text": true, "text_chars": 3020, "mu_floor": 0.0474, "constraint_binding": false}}
{"id": "T4_all_20210907_0308", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "TIP"], "decision_date": "2021-09-07", "context_summary": "XLF \u03c3=0.0120, TIP \u03c3=0.0012, \u03c1=0.017. Min-variance weights: XLF=0.009, TIP=0.991.", "question": "Assets: XLF, TIP\nXLF: annualized_mean_return=0.1008, daily_std=0.0120\nTIP: annualized_mean_return=0.0756, daily_std=0.0012\nMinimum required portfolio return (annualized): 0.0873\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_TIP) 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_TIP=X.XXXX", "answer": "w_XLF=0.4643, w_TIP=0.5357", "answer_numeric": 0.4643, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000002 - 0.000000) / (0.000144 + 0.000002 - 0.000000)\n  Unconstrained: w_XLF=0.0087\n  After long-only clamp: w_XLF=0.0087, w_TIP=0.9913.", "metadata": {"weights": {"XLF": 0.4643, "TIP": 0.5357}, "sigma_1": 0.01202, "sigma_2": 0.00123, "covariance": 0.0, "correlation": 0.0168, "has_text": true, "text_chars": 3020, "mu_floor": 0.0873, "constraint_binding": true}}
{"id": "T4_all_20180503_0313", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "TLT"], "decision_date": "2018-05-03", "context_summary": "MTUM \u03c3=0.0147, TLT \u03c3=0.0057, \u03c1=-0.017. Min-variance weights: MTUM=0.135, TLT=0.866.", "question": "Assets: MTUM, TLT\nMTUM: annualized_mean_return=0.1008, daily_std=0.0147\nTLT: annualized_mean_return=0.0504, daily_std=0.0057\nMinimum required portfolio return (annualized): 0.0562\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_TLT) 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_TLT=X.XXXX", "answer": "w_MTUM=0.1333, w_TLT=0.8667", "answer_numeric": 0.1333, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000032 - -0.000001) / (0.000215 + 0.000032 - -0.000003)\n  Unconstrained: w_MTUM=0.1345\n  After long-only clamp: w_MTUM=0.1345, w_TLT=0.8655.", "metadata": {"weights": {"MTUM": 0.1333, "TLT": 0.8667}, "sigma_1": 0.014654, "sigma_2": 0.005672, "covariance": -1e-06, "correlation": -0.0172, "has_text": true, "text_chars": 3020, "mu_floor": 0.0562, "constraint_binding": false}}
{"id": "T4_all_20220114_0316", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "PPLT"], "decision_date": "2022-01-14", "context_summary": "XLB \u03c3=0.0094, PPLT \u03c3=0.0162, \u03c1=0.271. Min-variance weights: XLB=0.822, PPLT=0.178.", "question": "Assets: XLB, PPLT\nXLB: annualized_mean_return=0.2520, daily_std=0.0094\nPPLT: annualized_mean_return=-0.3024, daily_std=0.0162\nMinimum required portfolio return (annualized): 0.2020\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_XLB=0.9098, w_PPLT=0.0902", "answer_numeric": 0.9098, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000262 - 0.000041) / (0.000089 + 0.000262 - 0.000083)\n  Unconstrained: w_XLB=0.8217\n  After long-only clamp: w_XLB=0.8217, w_PPLT=0.1783.", "metadata": {"weights": {"XLB": 0.9098, "PPLT": 0.0902}, "sigma_1": 0.009447, "sigma_2": 0.016178, "covariance": 4.1e-05, "correlation": 0.2712, "has_text": true, "text_chars": 3020, "mu_floor": 0.202, "constraint_binding": true}}
{"id": "T4_all_20221010_0321", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "BNO"], "decision_date": "2022-10-10", "context_summary": "ETH-USD \u03c3=0.0394, BNO \u03c3=0.0242, \u03c1=-0.172. Min-variance weights: ETH-USD=0.305, BNO=0.695.", "question": "Assets: ETH-USD, BNO\nETH-USD: annualized_mean_return=-1.2096, daily_std=0.0394\nBNO: annualized_mean_return=-0.0252, daily_std=0.0242\nMinimum required portfolio return (annualized): -0.5456\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_BNO) 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_BNO=X.XXXX", "answer": "w_ETH-USD=0.3046, w_BNO=0.6954", "answer_numeric": 0.3046, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000586 - -0.000164) / (0.001549 + 0.000586 - -0.000329)\n  Unconstrained: w_ETH-USD=0.3046\n  After long-only clamp: w_ETH-USD=0.3046, w_BNO=0.6954.", "metadata": {"weights": {"ETH-USD": 0.3046, "BNO": 0.6954}, "sigma_1": 0.039363, "sigma_2": 0.024215, "covariance": -0.000164, "correlation": -0.1725, "has_text": true, "text_chars": 20, "mu_floor": -0.5456, "constraint_binding": false}}
{"id": "T4_all_20220418_0324", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "SHV"], "decision_date": "2022-04-18", "context_summary": "BTC-USD \u03c3=0.0342, SHV \u03c3=0.0001, \u03c1=0.171. Min-variance weights: BTC-USD=0.000, SHV=1.000.", "question": "Assets: BTC-USD, SHV\nBTC-USD: annualized_mean_return=-0.3780, daily_std=0.0342\nSHV: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.1526\nMarket regime: sideways\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 - 0.000001) / (0.001170 + 0.000000 - 0.000002)\n  Unconstrained: w_BTC-USD=-0.0007\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": 0.034199, "sigma_2": 0.000146, "covariance": 1e-06, "correlation": 0.1705, "has_text": true, "text_chars": 20, "mu_floor": -0.1526, "constraint_binding": false}}
{"id": "T4_all_20201005_0327", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "TLT"], "decision_date": "2020-10-05", "context_summary": "BTC-USD \u03c3=0.0230, TLT \u03c3=0.0068, \u03c1=-0.060. Min-variance weights: BTC-USD=0.094, TLT=0.906.", "question": "Assets: BTC-USD, TLT\nBTC-USD: annualized_mean_return=-0.3276, daily_std=0.0230\nTLT: annualized_mean_return=-0.1512, daily_std=0.0068\nMinimum required portfolio return (annualized): -0.2297\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=0.0936, w_TLT=0.9064", "answer_numeric": 0.0936, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000046 - -0.000009) / (0.000528 + 0.000046 - -0.000019)\n  Unconstrained: w_BTC-USD=0.0941\n  After long-only clamp: w_BTC-USD=0.0941, w_TLT=0.9059.", "metadata": {"weights": {"BTC-USD": 0.0936, "TLT": 0.9064}, "sigma_1": 0.022972, "sigma_2": 0.006815, "covariance": -9e-06, "correlation": -0.0596, "has_text": false, "text_chars": 0, "mu_floor": -0.2297, "constraint_binding": false}}
{"id": "T4_all_20151026_0334", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "STIP"], "decision_date": "2015-10-26", "context_summary": "XLU \u03c3=0.0117, STIP \u03c3=0.0011, \u03c1=0.192. Min-variance weights: XLU=0.000, STIP=1.000.", "question": "Assets: XLU, STIP\nXLU: annualized_mean_return=0.1512, daily_std=0.0117\nSTIP: annualized_mean_return=-0.0252, daily_std=0.0011\nMinimum required portfolio return (annualized): 0.0774\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_STIP) 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_STIP=X.XXXX", "answer": "w_XLU=0.5816, w_STIP=0.4184", "answer_numeric": 0.5816, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000001 - 0.000003) / (0.000136 + 0.000001 - 0.000005)\n  Unconstrained: w_XLU=-0.0095\n  After long-only clamp: w_XLU=0.0000, w_STIP=1.0000.", "metadata": {"weights": {"XLU": 0.5816, "STIP": 0.4184}, "sigma_1": 0.011657, "sigma_2": 0.001147, "covariance": 3e-06, "correlation": 0.1919, "has_text": true, "text_chars": 3020, "mu_floor": 0.0774, "constraint_binding": true}}
{"id": "T4_all_20221202_0337", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BIL"], "decision_date": "2022-12-02", "context_summary": "XLY \u03c3=0.0188, BIL \u03c3=0.0002, \u03c1=0.051. Min-variance weights: XLY=0.000, BIL=1.000.", "question": "Assets: XLY, BIL\nXLY: annualized_mean_return=-0.5040, daily_std=0.0188\nBIL: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.0027\nMarket regime: sideways\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=0.0001, 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) / (0.000353 + 0.000000 - 0.000000)\n  Unconstrained: w_XLY=-0.0004\n  After long-only clamp: w_XLY=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLY": 0.0001, "BIL": 0.9999}, "sigma_1": 0.018781, "sigma_2": 0.000159, "covariance": 0.0, "correlation": 0.0509, "has_text": true, "text_chars": 3020, "mu_floor": -0.0027, "constraint_binding": false}}
{"id": "T4_all_20181212_0340", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "EMB"], "decision_date": "2018-12-12", "context_summary": "XLU \u03c3=0.0098, EMB \u03c3=0.0037, \u03c1=0.054. Min-variance weights: XLU=0.110, EMB=0.890.", "question": "Assets: XLU, EMB\nXLU: annualized_mean_return=0.2268, daily_std=0.0098\nEMB: annualized_mean_return=-0.0504, daily_std=0.0037\nMinimum required portfolio return (annualized): 0.1163\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_EMB) 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_EMB=X.XXXX", "answer": "w_XLU=0.6014, w_EMB=0.3986", "answer_numeric": 0.6014, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000013 - 0.000002) / (0.000096 + 0.000013 - 0.000004)\n  Unconstrained: w_XLU=0.1095\n  After long-only clamp: w_XLU=0.1095, w_EMB=0.8905.", "metadata": {"weights": {"XLU": 0.6014, "EMB": 0.3986}, "sigma_1": 0.009773, "sigma_2": 0.003668, "covariance": 2e-06, "correlation": 0.0541, "has_text": true, "text_chars": 3020, "mu_floor": 0.1163, "constraint_binding": true}}
{"id": "T4_all_20201203_0343", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "XHB"], "decision_date": "2020-12-03", "context_summary": "DOT-USD \u03c3=0.0462, XHB \u03c3=0.0162, \u03c1=-0.036. Min-variance weights: DOT-USD=0.118, XHB=0.882.", "question": "Assets: DOT-USD, XHB\nDOT-USD: annualized_mean_return=1.5120, daily_std=0.0462\nXHB: annualized_mean_return=0.4788, daily_std=0.0162\nMinimum required portfolio return (annualized): 0.5937\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=0.1181, w_XHB=0.8819", "answer_numeric": 0.1181, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000263 - -0.000027) / (0.002138 + 0.000263 - -0.000055)\n  Unconstrained: w_DOT-USD=0.1182\n  After long-only clamp: w_DOT-USD=0.1182, w_XHB=0.8818.", "metadata": {"weights": {"DOT-USD": 0.1181, "XHB": 0.8819}, "sigma_1": 0.046233, "sigma_2": 0.016215, "covariance": -2.7e-05, "correlation": -0.0364, "has_text": false, "text_chars": 0, "mu_floor": 0.5937, "constraint_binding": false}}
{"id": "T4_all_20210420_0346", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "EMB"], "decision_date": "2021-04-20", "context_summary": "BTC-USD \u03c3=0.0370, EMB \u03c3=0.0061, \u03c1=-0.049. Min-variance weights: BTC-USD=0.034, EMB=0.966.", "question": "Assets: BTC-USD, EMB\nBTC-USD: annualized_mean_return=0.4788, daily_std=0.0370\nEMB: annualized_mean_return=-0.0000, daily_std=0.0061\nMinimum required portfolio return (annualized): 0.1665\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_EMB) 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_EMB=X.XXXX", "answer": "w_BTC-USD=0.3477, w_EMB=0.6523", "answer_numeric": 0.3477, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000037 - -0.000011) / (0.001366 + 0.000037 - -0.000022)\n  Unconstrained: w_BTC-USD=0.0340\n  After long-only clamp: w_BTC-USD=0.0340, w_EMB=0.9660.", "metadata": {"weights": {"BTC-USD": 0.3477, "EMB": 0.6523}, "sigma_1": 0.036963, "sigma_2": 0.006117, "covariance": -1.1e-05, "correlation": -0.0492, "has_text": false, "text_chars": 0, "mu_floor": 0.1665, "constraint_binding": true}}
{"id": "T4_all_20210430_0351", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "BNDX"], "decision_date": "2021-04-30", "context_summary": "BNB-USD \u03c3=0.0709, BNDX \u03c3=0.0024, \u03c1=-0.076. Min-variance weights: BNB-USD=0.004, BNDX=0.996.", "question": "Assets: BNB-USD, BNDX\nBNB-USD: annualized_mean_return=5.0652, daily_std=0.0709\nBNDX: annualized_mean_return=-0.0504, daily_std=0.0024\nMinimum required portfolio return (annualized): -0.0407\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_BNDX) 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_BNDX=X.XXXX", "answer": "w_BNB-USD=0.0037, w_BNDX=0.9963", "answer_numeric": 0.0037, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000006 - -0.000013) / (0.005020 + 0.000006 - -0.000025)\n  Unconstrained: w_BNB-USD=0.0036\n  After long-only clamp: w_BNB-USD=0.0036, w_BNDX=0.9964.", "metadata": {"weights": {"BNB-USD": 0.0037, "BNDX": 0.9963}, "sigma_1": 0.070854, "sigma_2": 0.002362, "covariance": -1.3e-05, "correlation": -0.0757, "has_text": false, "text_chars": 0, "mu_floor": -0.0407, "constraint_binding": false}}
{"id": "T4_all_20160308_0354", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BIL"], "decision_date": "2016-03-08", "context_summary": "MTUM \u03c3=0.0129, BIL \u03c3=0.0002, \u03c1=0.097. Min-variance weights: MTUM=0.000, BIL=1.000.", "question": "Assets: MTUM, BIL\nMTUM: annualized_mean_return=-0.2268, daily_std=0.0129\nBIL: annualized_mean_return=-0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0000\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=-0.0000, 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) / (0.000167 + 0.000000 - 0.000000)\n  Unconstrained: w_MTUM=-0.0012\n  After long-only clamp: w_MTUM=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"MTUM": -0.0, "BIL": 1.0}, "sigma_1": 0.012941, "sigma_2": 0.000187, "covariance": 0.0, "correlation": 0.0972, "has_text": true, "text_chars": 3020, "mu_floor": 0.0, "constraint_binding": true}}
{"id": "T4_all_20221124_0357", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "SGOV"], "decision_date": "2022-11-24", "context_summary": "AVAX-USD \u03c3=0.0500, SGOV \u03c3=0.0001, \u03c1=-0.135. Min-variance weights: AVAX-USD=0.000, SGOV=1.000.", "question": "Assets: AVAX-USD, SGOV\nAVAX-USD: annualized_mean_return=-0.9324, daily_std=0.0500\nSGOV: annualized_mean_return=0.0252, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0513\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_AVAX-USD=0.0004, w_SGOV=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 - -0.000001) / (0.002502 + 0.000000 - -0.000002)\n  Unconstrained: w_AVAX-USD=0.0004\n  After long-only clamp: w_AVAX-USD=0.0004, w_SGOV=0.9996.", "metadata": {"weights": {"AVAX-USD": 0.0004, "SGOV": 0.9996}, "sigma_1": 0.050023, "sigma_2": 0.000134, "covariance": -1e-06, "correlation": -0.1354, "has_text": true, "text_chars": 20, "mu_floor": -0.0513, "constraint_binding": false}}
{"id": "T4_all_20150707_0362", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XHB"], "decision_date": "2015-07-07", "context_summary": "USMV \u03c3=0.0059, XHB \u03c3=0.0087, \u03c1=0.708. Min-variance weights: USMV=1.000, XHB=0.000.", "question": "Assets: USMV, XHB\nUSMV: annualized_mean_return=-0.0504, daily_std=0.0059\nXHB: annualized_mean_return=0.0252, daily_std=0.0087\nMinimum required portfolio return (annualized): -0.0103\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=0.4696, w_XHB=0.5304", "answer_numeric": 0.4696, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000076 - 0.000036) / (0.000035 + 0.000076 - 0.000073)\n  Unconstrained: w_USMV=1.0370\n  After long-only clamp: w_USMV=1.0000, w_XHB=0.0000.", "metadata": {"weights": {"USMV": 0.4696, "XHB": 0.5304}, "sigma_1": 0.005918, "sigma_2": 0.008693, "covariance": 3.6e-05, "correlation": 0.708, "has_text": true, "text_chars": 3020, "mu_floor": -0.0103, "constraint_binding": true}}
{"id": "T4_all_20221107_0365", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "EFA"], "decision_date": "2022-11-07", "context_summary": "BNB-USD \u03c3=0.0227, EFA \u03c3=0.0138, \u03c1=-0.008. Min-variance weights: BNB-USD=0.270, EFA=0.730.", "question": "Assets: BNB-USD, EFA\nBNB-USD: annualized_mean_return=0.8820, daily_std=0.0227\nEFA: annualized_mean_return=-0.4284, daily_std=0.0138\nMinimum required portfolio return (annualized): -0.2769\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_EFA) 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_EFA=X.XXXX", "answer": "w_BNB-USD=0.2699, w_EFA=0.7301", "answer_numeric": 0.2699, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000189 - -0.000002) / (0.000515 + 0.000189 - -0.000005)\n  Unconstrained: w_BNB-USD=0.2701\n  After long-only clamp: w_BNB-USD=0.2701, w_EFA=0.7299.", "metadata": {"weights": {"BNB-USD": 0.2699, "EFA": 0.7301}, "sigma_1": 0.022693, "sigma_2": 0.013751, "covariance": -2e-06, "correlation": -0.0077, "has_text": true, "text_chars": 20, "mu_floor": -0.2769, "constraint_binding": false}}
{"id": "T4_all_20221026_0368", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "BNO"], "decision_date": "2022-10-26", "context_summary": "XRP-USD \u03c3=0.0459, BNO \u03c3=0.0235, \u03c1=0.092. Min-variance weights: XRP-USD=0.183, BNO=0.817.", "question": "Assets: XRP-USD, BNO\nXRP-USD: annualized_mean_return=1.5624, daily_std=0.0459\nBNO: annualized_mean_return=-0.0504, daily_std=0.0235\nMinimum required portfolio return (annualized): 0.5305\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_BNO) 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_BNO=X.XXXX", "answer": "w_XRP-USD=0.3602, w_BNO=0.6398", "answer_numeric": 0.3602, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000550 - 0.000099) / (0.002107 + 0.000550 - 0.000198)\n  Unconstrained: w_XRP-USD=0.1835\n  After long-only clamp: w_XRP-USD=0.1835, w_BNO=0.8165.", "metadata": {"weights": {"XRP-USD": 0.3602, "BNO": 0.6398}, "sigma_1": 0.045897, "sigma_2": 0.023455, "covariance": 9.9e-05, "correlation": 0.092, "has_text": true, "text_chars": 20, "mu_floor": 0.5305, "constraint_binding": true}}
{"id": "T4_all_20220628_0373", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "SHV"], "decision_date": "2022-06-28", "context_summary": "BTC-USD \u03c3=0.0419, SHV \u03c3=0.0002, \u03c1=0.200. Min-variance weights: BTC-USD=0.000, SHV=1.000.", "question": "Assets: BTC-USD, SHV\nBTC-USD: annualized_mean_return=-2.3688, daily_std=0.0419\nSHV: annualized_mean_return=0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): -1.2999\nMarket regime: sideways\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 - 0.000001) / (0.001757 + 0.000000 - 0.000003)\n  Unconstrained: w_BTC-USD=-0.0008\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": 0.041919, "sigma_2": 0.000177, "covariance": 1e-06, "correlation": 0.2003, "has_text": true, "text_chars": 20, "mu_floor": -1.2999, "constraint_binding": false}}
{"id": "T4_all_20200904_0375", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "HYG"], "decision_date": "2020-09-04", "context_summary": "XLK \u03c3=0.0150, HYG \u03c3=0.0046, \u03c1=0.291. Min-variance weights: XLK=0.005, HYG=0.995.", "question": "Assets: XLK, HYG\nXLK: annualized_mean_return=0.7308, daily_std=0.0150\nHYG: annualized_mean_return=0.2520, daily_std=0.0046\nMinimum required portfolio return (annualized): 0.2535\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_HYG) 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_HYG=X.XXXX", "answer": "w_XLK=0.0046, w_HYG=0.9954", "answer_numeric": 0.0046, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000021 - 0.000020) / (0.000225 + 0.000021 - 0.000040)\n  Unconstrained: w_XLK=0.0047\n  After long-only clamp: w_XLK=0.0047, w_HYG=0.9953.", "metadata": {"weights": {"XLK": 0.0046, "HYG": 0.9954}, "sigma_1": 0.014994, "sigma_2": 0.004577, "covariance": 2e-05, "correlation": 0.291, "has_text": true, "text_chars": 3020, "mu_floor": 0.2535, "constraint_binding": false}}
{"id": "T4_all_20210922_0380", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SGOV"], "decision_date": "2021-09-22", "context_summary": "EEM \u03c3=0.0107, SGOV \u03c3=0.0001, \u03c1=0.091. Min-variance weights: EEM=0.000, SGOV=1.000.", "question": "Assets: EEM, SGOV\nEEM: annualized_mean_return=-0.4032, daily_std=0.0107\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0000\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=-0.0000, 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) / (0.000115 + 0.000000 - 0.000000)\n  Unconstrained: w_EEM=-0.0005\n  After long-only clamp: w_EEM=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"EEM": -0.0, "SGOV": 1.0}, "sigma_1": 0.010717, "sigma_2": 6.8e-05, "covariance": 0.0, "correlation": 0.0909, "has_text": true, "text_chars": 3020, "mu_floor": 0.0, "constraint_binding": true}}
{"id": "T4_all_20201027_0383", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "UNG"], "decision_date": "2020-10-27", "context_summary": "FXI \u03c3=0.0111, UNG \u03c3=0.0356, \u03c1=0.274. Min-variance weights: FXI=0.987, UNG=0.013.", "question": "Assets: FXI, UNG\nFXI: annualized_mean_return=0.3276, daily_std=0.0111\nUNG: annualized_mean_return=0.4788, daily_std=0.0356\nMinimum required portfolio return (annualized): 0.3288\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=0.9869, w_UNG=0.0131", "answer_numeric": 0.9869, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.001265 - 0.000108) / (0.000123 + 0.001265 - 0.000217)\n  Unconstrained: w_FXI=0.9871\n  After long-only clamp: w_FXI=0.9871, w_UNG=0.0129.", "metadata": {"weights": {"FXI": 0.9869, "UNG": 0.0131}, "sigma_1": 0.011109, "sigma_2": 0.035574, "covariance": 0.000108, "correlation": 0.2741, "has_text": true, "text_chars": 3020, "mu_floor": 0.3288, "constraint_binding": false}}
{"id": "T4_all_20171009_0390", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "VCIT"], "decision_date": "2017-10-09", "context_summary": "BTC-USD \u03c3=0.0450, VCIT \u03c3=0.0019, \u03c1=-0.170. Min-variance weights: BTC-USD=0.009, VCIT=0.991.", "question": "Assets: BTC-USD, VCIT\nBTC-USD: annualized_mean_return=1.6632, daily_std=0.0450\nVCIT: annualized_mean_return=0.0252, daily_std=0.0019\nMinimum required portfolio return (annualized): 1.0490\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_BTC-USD=0.6250, w_VCIT=0.3750", "answer_numeric": 0.625, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000004 - -0.000014) / (0.002026 + 0.000004 - -0.000029)\n  Unconstrained: w_BTC-USD=0.0087\n  After long-only clamp: w_BTC-USD=0.0087, w_VCIT=0.9913.", "metadata": {"weights": {"BTC-USD": 0.625, "VCIT": 0.375}, "sigma_1": 0.045016, "sigma_2": 0.001881, "covariance": -1.4e-05, "correlation": -0.1699, "has_text": false, "text_chars": 0, "mu_floor": 1.049, "constraint_binding": true}}
{"id": "T4_all_20171117_0393", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "XHB"], "decision_date": "2017-11-17", "context_summary": "XLE \u03c3=0.0065, XHB \u03c3=0.0068, \u03c1=0.021. Min-variance weights: XLE=0.523, XHB=0.477.", "question": "Assets: XLE, XHB\nXLE: annualized_mean_return=0.3528, daily_std=0.0065\nXHB: annualized_mean_return=0.4536, daily_std=0.0068\nMinimum required portfolio return (annualized): 0.3915\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_XHB) 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_XHB=X.XXXX", "answer": "w_XLE=0.5227, w_XHB=0.4773", "answer_numeric": 0.5227, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000047 - 0.000001) / (0.000043 + 0.000047 - 0.000002)\n  Unconstrained: w_XLE=0.5227\n  After long-only clamp: w_XLE=0.5227, w_XHB=0.4773.", "metadata": {"weights": {"XLE": 0.5227, "XHB": 0.4773}, "sigma_1": 0.006543, "sigma_2": 0.00684, "covariance": 1e-06, "correlation": 0.021, "has_text": true, "text_chars": 3020, "mu_floor": 0.3915, "constraint_binding": false}}
{"id": "T4_all_20220126_0396", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "TIP"], "decision_date": "2022-01-26", "context_summary": "USMV \u03c3=0.0072, TIP \u03c3=0.0015, \u03c1=0.222. Min-variance weights: USMV=0.000, TIP=1.000.", "question": "Assets: USMV, TIP\nUSMV: annualized_mean_return=-0.1512, daily_std=0.0072\nTIP: annualized_mean_return=0.0000, daily_std=0.0015\nMinimum required portfolio return (annualized): -0.0007\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_TIP) 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_TIP=X.XXXX", "answer": "w_USMV=0.0046, w_TIP=0.9954", "answer_numeric": 0.0046, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000002 - 0.000002) / (0.000051 + 0.000002 - 0.000005)\n  Unconstrained: w_USMV=-0.0021\n  After long-only clamp: w_USMV=0.0000, w_TIP=1.0000.", "metadata": {"weights": {"USMV": 0.0046, "TIP": 0.9954}, "sigma_1": 0.007169, "sigma_2": 0.001525, "covariance": 2e-06, "correlation": 0.2223, "has_text": true, "text_chars": 3020, "mu_floor": -0.0007, "constraint_binding": true}}
{"id": "T4_all_20220721_0400", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "USO"], "decision_date": "2022-07-21", "context_summary": "FXI \u03c3=0.0228, USO \u03c3=0.0266, \u03c1=0.173. Min-variance weights: FXI=0.592, USO=0.408.", "question": "Assets: FXI, USO\nFXI: annualized_mean_return=0.3780, daily_std=0.0228\nUSO: annualized_mean_return=-0.0000, daily_std=0.0266\nMinimum required portfolio return (annualized): 0.2888\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_USO) 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_USO=X.XXXX", "answer": "w_FXI=0.7640, w_USO=0.2360", "answer_numeric": 0.764, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000709 - 0.000105) / (0.000520 + 0.000709 - 0.000210)\n  Unconstrained: w_FXI=0.5923\n  After long-only clamp: w_FXI=0.5923, w_USO=0.4077.", "metadata": {"weights": {"FXI": 0.764, "USO": 0.236}, "sigma_1": 0.022812, "sigma_2": 0.026618, "covariance": 0.000105, "correlation": 0.1727, "has_text": true, "text_chars": 3020, "mu_floor": 0.2888, "constraint_binding": true}}
{"id": "T4_all_20221020_0403", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "DBC"], "decision_date": "2022-10-20", "context_summary": "ETH-USD \u03c3=0.0357, DBC \u03c3=0.0144, \u03c1=0.026. Min-variance weights: ETH-USD=0.133, DBC=0.867.", "question": "Assets: ETH-USD, DBC\nETH-USD: annualized_mean_return=-0.6804, daily_std=0.0357\nDBC: annualized_mean_return=-0.1764, daily_std=0.0144\nMinimum required portfolio return (annualized): -0.2629\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=0.1334, w_DBC=0.8666", "answer_numeric": 0.1334, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000207 - 0.000013) / (0.001274 + 0.000207 - 0.000027)\n  Unconstrained: w_ETH-USD=0.1333\n  After long-only clamp: w_ETH-USD=0.1333, w_DBC=0.8667.", "metadata": {"weights": {"ETH-USD": 0.1334, "DBC": 0.8666}, "sigma_1": 0.035696, "sigma_2": 0.014394, "covariance": 1.3e-05, "correlation": 0.026, "has_text": true, "text_chars": 20, "mu_floor": -0.2629, "constraint_binding": false}}
{"id": "T4_all_20210810_0406", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "VNQI"], "decision_date": "2021-08-10", "context_summary": "XLRE \u03c3=0.0077, VNQI \u03c3=0.0068, \u03c1=0.641. Min-variance weights: XLRE=0.332, VNQI=0.668.", "question": "Assets: XLRE, VNQI\nXLRE: annualized_mean_return=0.5040, daily_std=0.0077\nVNQI: annualized_mean_return=0.1512, daily_std=0.0068\nMinimum required portfolio return (annualized): 0.3672\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_VNQI) 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_VNQI=X.XXXX", "answer": "w_XLRE=0.6122, w_VNQI=0.3878", "answer_numeric": 0.6122, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000046 - 0.000034) / (0.000059 + 0.000046 - 0.000067)\n  Unconstrained: w_XLRE=0.3319\n  After long-only clamp: w_XLRE=0.3319, w_VNQI=0.6681.", "metadata": {"weights": {"XLRE": 0.6122, "VNQI": 0.3878}, "sigma_1": 0.007689, "sigma_2": 0.006799, "covariance": 3.4e-05, "correlation": 0.6411, "has_text": true, "text_chars": 3020, "mu_floor": 0.3672, "constraint_binding": true}}
{"id": "T4_all_20200612_0409", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "VNQI"], "decision_date": "2020-06-12", "context_summary": "QUAL \u03c3=0.0191, VNQI \u03c3=0.0168, \u03c1=0.780. Min-variance weights: QUAL=0.209, VNQI=0.791.", "question": "Assets: QUAL, VNQI\nQUAL: annualized_mean_return=0.3276, daily_std=0.0191\nVNQI: annualized_mean_return=0.4536, daily_std=0.0168\nMinimum required portfolio return (annualized): 0.3734\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_VNQI) 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_VNQI=X.XXXX", "answer": "w_QUAL=0.2109, w_VNQI=0.7891", "answer_numeric": 0.2109, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000281 - 0.000250) / (0.000367 + 0.000281 - 0.000501)\n  Unconstrained: w_QUAL=0.2092\n  After long-only clamp: w_QUAL=0.2092, w_VNQI=0.7908.", "metadata": {"weights": {"QUAL": 0.2109, "VNQI": 0.7891}, "sigma_1": 0.019147, "sigma_2": 0.016768, "covariance": 0.00025, "correlation": 0.7801, "has_text": true, "text_chars": 3020, "mu_floor": 0.3734, "constraint_binding": false}}
{"id": "T4_all_20190809_0413", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ICSH"], "decision_date": "2019-08-09", "context_summary": "QUAL \u03c3=0.0086, ICSH \u03c3=0.0003, \u03c1=-0.130. Min-variance weights: QUAL=0.005, ICSH=0.995.", "question": "Assets: QUAL, ICSH\nQUAL: annualized_mean_return=0.1764, daily_std=0.0086\nICSH: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0253\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=0.0011, w_ICSH=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) / (0.000075 + 0.000000 - -0.000001)\n  Unconstrained: w_QUAL=0.0053\n  After long-only clamp: w_QUAL=0.0053, w_ICSH=0.9947.", "metadata": {"weights": {"QUAL": 0.0011, "ICSH": 0.9989}, "sigma_1": 0.008634, "sigma_2": 0.000285, "covariance": -0.0, "correlation": -0.1304, "has_text": true, "text_chars": 3020, "mu_floor": 0.0253, "constraint_binding": false}}
{"id": "T4_all_20221116_0418", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "PPLT"], "decision_date": "2022-11-16", "context_summary": "MATIC-USD \u03c3=0.0777, PPLT \u03c3=0.0194, \u03c1=-0.118. Min-variance weights: MATIC-USD=0.082, PPLT=0.918.", "question": "Assets: MATIC-USD, PPLT\nMATIC-USD: annualized_mean_return=1.3860, daily_std=0.0777\nPPLT: annualized_mean_return=0.6048, daily_std=0.0194\nMinimum required portfolio return (annualized): 1.0770\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_MATIC-USD=0.6045, w_PPLT=0.3955", "answer_numeric": 0.6045, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000375 - -0.000177) / (0.006033 + 0.000375 - -0.000354)\n  Unconstrained: w_MATIC-USD=0.0816\n  After long-only clamp: w_MATIC-USD=0.0816, w_PPLT=0.9184.", "metadata": {"weights": {"MATIC-USD": 0.6045, "PPLT": 0.3955}, "sigma_1": 0.077674, "sigma_2": 0.019362, "covariance": -0.000177, "correlation": -0.1178, "has_text": true, "text_chars": 20, "mu_floor": 1.077, "constraint_binding": true}}
{"id": "T4_all_20210217_0421", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "XRP-USD"], "decision_date": "2021-02-17", "context_summary": "IWM \u03c3=0.0122, XRP-USD \u03c3=0.1000, \u03c1=-0.091. Min-variance weights: IWM=0.975, XRP-USD=0.025.", "question": "Assets: IWM, XRP-USD\nIWM: annualized_mean_return=0.9828, daily_std=0.0122\nXRP-USD: annualized_mean_return=1.5120, daily_std=0.1000\nMinimum required portfolio return (annualized): 0.9898\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_XRP-USD) 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_XRP-USD=X.XXXX", "answer": "w_IWM=0.9749, w_XRP-USD=0.0251", "answer_numeric": 0.9749, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.009993 - -0.000111) / (0.000150 + 0.009993 - -0.000222)\n  Unconstrained: w_IWM=0.9749\n  After long-only clamp: w_IWM=0.9749, w_XRP-USD=0.0251.", "metadata": {"weights": {"IWM": 0.9749, "XRP-USD": 0.0251}, "sigma_1": 0.012233, "sigma_2": 0.099967, "covariance": -0.000111, "correlation": -0.0906, "has_text": true, "text_chars": 3020, "mu_floor": 0.9898, "constraint_binding": false}}
{"id": "T4_all_20200128_0424", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "REZ"], "decision_date": "2020-01-28", "context_summary": "ACWI \u03c3=0.0051, REZ \u03c3=0.0088, \u03c1=-0.068. Min-variance weights: ACWI=0.737, REZ=0.263.", "question": "Assets: ACWI, REZ\nACWI: annualized_mean_return=0.2016, daily_std=0.0051\nREZ: annualized_mean_return=-0.0252, daily_std=0.0088\nMinimum required portfolio return (annualized): 0.1741\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_REZ) 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_REZ=X.XXXX", "answer": "w_ACWI=0.8787, w_REZ=0.1213", "answer_numeric": 0.8787, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000078 - -0.000003) / (0.000026 + 0.000078 - -0.000006)\n  Unconstrained: w_ACWI=0.7368\n  After long-only clamp: w_ACWI=0.7368, w_REZ=0.2632.", "metadata": {"weights": {"ACWI": 0.8787, "REZ": 0.1213}, "sigma_1": 0.00508, "sigma_2": 0.008814, "covariance": -3e-06, "correlation": -0.0676, "has_text": true, "text_chars": 3020, "mu_floor": 0.1741, "constraint_binding": true}}
{"id": "T4_all_20220809_0427", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "DBC"], "decision_date": "2022-08-09", "context_summary": "EEM \u03c3=0.0135, DBC \u03c3=0.0142, \u03c1=0.218. Min-variance weights: EEM=0.531, DBC=0.469.", "question": "Assets: EEM, DBC\nEEM: annualized_mean_return=0.1008, daily_std=0.0135\nDBC: annualized_mean_return=-0.3276, daily_std=0.0142\nMinimum required portfolio return (annualized): -0.2064\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_DBC) 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_DBC=X.XXXX", "answer": "w_EEM=0.5310, w_DBC=0.4690", "answer_numeric": 0.531, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000200 - 0.000042) / (0.000182 + 0.000200 - 0.000083)\n  Unconstrained: w_EEM=0.5309\n  After long-only clamp: w_EEM=0.5309, w_DBC=0.4691.", "metadata": {"weights": {"EEM": 0.531, "DBC": 0.469}, "sigma_1": 0.013486, "sigma_2": 0.014155, "covariance": 4.2e-05, "correlation": 0.2181, "has_text": true, "text_chars": 3020, "mu_floor": -0.2064, "constraint_binding": false}}
{"id": "T4_all_20151221_0430", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "EMB"], "decision_date": "2015-12-21", "context_summary": "XLY \u03c3=0.0110, EMB \u03c3=0.0040, \u03c1=0.269. Min-variance weights: XLY=0.037, EMB=0.963.", "question": "Assets: XLY, EMB\nXLY: annualized_mean_return=0.1512, daily_std=0.0110\nEMB: annualized_mean_return=0.0504, daily_std=0.0040\nMinimum required portfolio return (annualized): 0.0937\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_EMB) 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_EMB=X.XXXX", "answer": "w_XLY=0.4296, w_EMB=0.5704", "answer_numeric": 0.4296, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000016 - 0.000012) / (0.000121 + 0.000016 - 0.000024)\n  Unconstrained: w_XLY=0.0370\n  After long-only clamp: w_XLY=0.0370, w_EMB=0.9630.", "metadata": {"weights": {"XLY": 0.4296, "EMB": 0.5704}, "sigma_1": 0.011016, "sigma_2": 0.004012, "covariance": 1.2e-05, "correlation": 0.2691, "has_text": true, "text_chars": 3020, "mu_floor": 0.0937, "constraint_binding": true}}
{"id": "T4_all_20170120_0433", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "IYR"], "decision_date": "2017-01-20", "context_summary": "EWJ \u03c3=0.0071, IYR \u03c3=0.0101, \u03c1=0.291. Min-variance weights: EWJ=0.733, IYR=0.267.", "question": "Assets: EWJ, IYR\nEWJ: annualized_mean_return=0.0504, daily_std=0.0071\nIYR: annualized_mean_return=0.0252, daily_std=0.0101\nMinimum required portfolio return (annualized): 0.0361\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_IYR) 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_IYR=X.XXXX", "answer": "w_EWJ=0.7329, w_IYR=0.2671", "answer_numeric": 0.7329, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000102 - 0.000021) / (0.000051 + 0.000102 - 0.000042)\n  Unconstrained: w_EWJ=0.7326\n  After long-only clamp: w_EWJ=0.7326, w_IYR=0.2674.", "metadata": {"weights": {"EWJ": 0.7329, "IYR": 0.2671}, "sigma_1": 0.007112, "sigma_2": 0.010107, "covariance": 2.1e-05, "correlation": 0.2911, "has_text": true, "text_chars": 3020, "mu_floor": 0.0361, "constraint_binding": false}}
{"id": "T4_all_20191112_0436", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "ICSH"], "decision_date": "2019-11-12", "context_summary": "LINK-USD \u03c3=0.0424, ICSH \u03c3=0.0002, \u03c1=0.256. Min-variance weights: LINK-USD=0.000, ICSH=1.000.", "question": "Assets: LINK-USD, ICSH\nLINK-USD: annualized_mean_return=2.2428, daily_std=0.0424\nICSH: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 1.1222\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_ICSH) 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_ICSH=X.XXXX", "answer": "w_LINK-USD=0.4947, w_ICSH=0.5053", "answer_numeric": 0.4947, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000003) / (0.001797 + 0.000000 - 0.000005)\n  Unconstrained: w_LINK-USD=-0.0014\n  After long-only clamp: w_LINK-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"LINK-USD": 0.4947, "ICSH": 0.5053}, "sigma_1": 0.042394, "sigma_2": 0.00024, "covariance": 3e-06, "correlation": 0.2557, "has_text": false, "text_chars": 0, "mu_floor": 1.1222, "constraint_binding": true}}
{"id": "T4_all_20190702_0443", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD"], "decision_date": "2019-07-02", "context_summary": "EFA \u03c3=0.0071, LINK-USD \u03c3=0.0838, \u03c1=-0.087. Min-variance weights: EFA=0.986, LINK-USD=0.014.", "question": "Assets: EFA, LINK-USD\nEFA: annualized_mean_return=0.0756, daily_std=0.0071\nLINK-USD: annualized_mean_return=7.0812, daily_std=0.0838\nMinimum required portfolio return (annualized): 0.1392\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_LINK-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_LINK-USD=X.XXXX", "answer": "w_EFA=0.9857, w_LINK-USD=0.0143", "answer_numeric": 0.9857, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.007015 - -0.000052) / (0.000051 + 0.007015 - -0.000104)\n  Unconstrained: w_EFA=0.9857\n  After long-only clamp: w_EFA=0.9857, w_LINK-USD=0.0143.", "metadata": {"weights": {"EFA": 0.9857, "LINK-USD": 0.0143}, "sigma_1": 0.007126, "sigma_2": 0.083755, "covariance": -5.2e-05, "correlation": -0.087, "has_text": true, "text_chars": 3020, "mu_floor": 0.1392, "constraint_binding": false}}
{"id": "T4_all_20200521_0446", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "HAUZ"], "decision_date": "2020-05-21", "context_summary": "^VIX \u03c3=0.1079, HAUZ \u03c3=0.0198, \u03c1=-0.610. Min-variance weights: ^VIX=0.116, HAUZ=0.884.", "question": "Assets: ^VIX, HAUZ\n^VIX: annualized_mean_return=-0.9072, daily_std=0.1079\nHAUZ: annualized_mean_return=-0.2268, daily_std=0.0198\nMinimum required portfolio return (annualized): -0.2712\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_^VIX=0.0653, w_HAUZ=0.9347", "answer_numeric": 0.0653, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000391 - -0.001300) / (0.011638 + 0.000391 - -0.002601)\n  Unconstrained: w_^VIX=0.1156\n  After long-only clamp: w_^VIX=0.1156, w_HAUZ=0.8844.", "metadata": {"weights": {"^VIX": 0.0653, "HAUZ": 0.9347}, "sigma_1": 0.107879, "sigma_2": 0.019773, "covariance": -0.0013, "correlation": -0.6096, "has_text": true, "text_chars": 3020, "mu_floor": -0.2712, "constraint_binding": true}}
{"id": "T4_all_20190111_0451", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "DBB"], "decision_date": "2019-01-11", "context_summary": "VLUE \u03c3=0.0146, DBB \u03c3=0.0095, \u03c1=-0.011. Min-variance weights: VLUE=0.301, DBB=0.699.", "question": "Assets: VLUE, DBB\nVLUE: annualized_mean_return=-0.4284, daily_std=0.0146\nDBB: annualized_mean_return=-0.1260, daily_std=0.0095\nMinimum required portfolio return (annualized): -0.2747\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_DBB) 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_DBB=X.XXXX", "answer": "w_VLUE=0.3022, w_DBB=0.6978", "answer_numeric": 0.3022, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000091 - -0.000002) / (0.000212 + 0.000091 - -0.000003)\n  Unconstrained: w_VLUE=0.3015\n  After long-only clamp: w_VLUE=0.3015, w_DBB=0.6985.", "metadata": {"weights": {"VLUE": 0.3022, "DBB": 0.6978}, "sigma_1": 0.014567, "sigma_2": 0.009526, "covariance": -2e-06, "correlation": -0.0109, "has_text": true, "text_chars": 3020, "mu_floor": -0.2747, "constraint_binding": false}}
{"id": "T4_all_20210203_0454", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BIL"], "decision_date": "2021-02-03", "context_summary": "EFA \u03c3=0.0100, BIL \u03c3=0.0001, \u03c1=0.089. Min-variance weights: EFA=0.000, BIL=1.000.", "question": "Assets: EFA, BIL\nEFA: annualized_mean_return=0.6048, daily_std=0.0100\nBIL: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.1823\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=0.3014, w_BIL=0.6986", "answer_numeric": 0.3014, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000101 + 0.000000 - 0.000000)\n  Unconstrained: w_EFA=-0.0007\n  After long-only clamp: w_EFA=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"EFA": 0.3014, "BIL": 0.6986}, "sigma_1": 0.010026, "sigma_2": 8.4e-05, "covariance": 0.0, "correlation": 0.0894, "has_text": true, "text_chars": 3020, "mu_floor": 0.1823, "constraint_binding": true}}
{"id": "T4_all_20210614_0457", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "VCIT"], "decision_date": "2021-06-14", "context_summary": "DOT-USD \u03c3=0.0936, VCIT \u03c3=0.0021, \u03c1=0.032. Min-variance weights: DOT-USD=0.000, VCIT=1.000.", "question": "Assets: DOT-USD, VCIT\nDOT-USD: annualized_mean_return=-0.6300, daily_std=0.0936\nVCIT: annualized_mean_return=0.1512, daily_std=0.0021\nMinimum required portfolio return (annualized): -0.0062\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_DOT-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  = (0.000005 - 0.000007) / (0.008767 + 0.000005 - 0.000013)\n  Unconstrained: w_DOT-USD=-0.0002\n  After long-only clamp: w_DOT-USD=0.0000, w_VCIT=1.0000.", "metadata": {"weights": {"DOT-USD": 0.0, "VCIT": 1.0}, "sigma_1": 0.093631, "sigma_2": 0.002142, "covariance": 7e-06, "correlation": 0.0324, "has_text": false, "text_chars": 0, "mu_floor": -0.0062, "constraint_binding": false}}
{"id": "T4_all_20210514_0460", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ICSH"], "decision_date": "2021-05-14", "context_summary": "ACWI \u03c3=0.0091, ICSH \u03c3=0.0002, \u03c1=0.131. Min-variance weights: ACWI=0.000, ICSH=1.000.", "question": "Assets: ACWI, ICSH\nACWI: annualized_mean_return=0.0504, daily_std=0.0091\nICSH: annualized_mean_return=0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0381\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=0.7560, w_ICSH=0.2440", "answer_numeric": 0.756, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000084 + 0.000000 - 0.000000)\n  Unconstrained: w_ACWI=-0.0023\n  After long-only clamp: w_ACWI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"ACWI": 0.756, "ICSH": 0.244}, "sigma_1": 0.009149, "sigma_2": 0.000192, "covariance": 0.0, "correlation": 0.1315, "has_text": true, "text_chars": 3020, "mu_floor": 0.0381, "constraint_binding": true}}
{"id": "T4_all_20210216_0463", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "BIL"], "decision_date": "2021-02-16", "context_summary": "LINK-USD \u03c3=0.0793, BIL \u03c3=0.0001, \u03c1=0.084. Min-variance weights: LINK-USD=0.000, BIL=1.000.", "question": "Assets: LINK-USD, BIL\nLINK-USD: annualized_mean_return=4.5108, daily_std=0.0793\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0000\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 - 0.000001) / (0.006282 + 0.000000 - 0.000001)\n  Unconstrained: w_LINK-USD=-0.0001\n  After long-only clamp: w_LINK-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.07926, "sigma_2": 8e-05, "covariance": 1e-06, "correlation": 0.0843, "has_text": false, "text_chars": 0, "mu_floor": -0.0, "constraint_binding": false}}
{"id": "T4_all_20181123_0468", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "IAU"], "decision_date": "2018-11-23", "context_summary": "BTC-USD \u03c3=0.0273, IAU \u03c3=0.0056, \u03c1=0.041. Min-variance weights: BTC-USD=0.033, IAU=0.967.", "question": "Assets: BTC-USD, IAU\nBTC-USD: annualized_mean_return=-1.6884, daily_std=0.0273\nIAU: annualized_mean_return=0.1008, daily_std=0.0056\nMinimum required portfolio return (annualized): 0.0670\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_IAU) 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_IAU=X.XXXX", "answer": "w_BTC-USD=0.0189, w_IAU=0.9811", "answer_numeric": 0.0189, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000032 - 0.000006) / (0.000745 + 0.000032 - 0.000013)\n  Unconstrained: w_BTC-USD=0.0334\n  After long-only clamp: w_BTC-USD=0.0334, w_IAU=0.9666.", "metadata": {"weights": {"BTC-USD": 0.0189, "IAU": 0.9811}, "sigma_1": 0.027297, "sigma_2": 0.005644, "covariance": 6e-06, "correlation": 0.0409, "has_text": false, "text_chars": 0, "mu_floor": 0.067, "constraint_binding": true}}
{"id": "T4_all_20220425_0471", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BIL"], "decision_date": "2022-04-25", "context_summary": "IVV \u03c3=0.0139, BIL \u03c3=0.0001, \u03c1=0.172. Min-variance weights: IVV=0.000, BIL=1.000.", "question": "Assets: IVV, BIL\nIVV: annualized_mean_return=-0.0504, daily_std=0.0139\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0016\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_BIL) 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_BIL=X.XXXX", "answer": "w_IVV=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) / (0.000194 + 0.000000 - 0.000001)\n  Unconstrained: w_IVV=-0.0013\n  After long-only clamp: w_IVV=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"IVV": 0.0001, "BIL": 0.9999}, "sigma_1": 0.01393, "sigma_2": 0.000108, "covariance": 0.0, "correlation": 0.172, "has_text": true, "text_chars": 3020, "mu_floor": -0.0016, "constraint_binding": false}}
{"id": "T4_all_20160318_0474", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "REZ"], "decision_date": "2016-03-18", "context_summary": "IVV \u03c3=0.0119, REZ \u03c3=0.0133, \u03c1=0.720. Min-variance weights: IVV=0.700, REZ=0.300.", "question": "Assets: IVV, REZ\nIVV: annualized_mean_return=0.1008, daily_std=0.0119\nREZ: annualized_mean_return=0.3024, daily_std=0.0133\nMinimum required portfolio return (annualized): 0.2682\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_REZ) 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_REZ=X.XXXX", "answer": "w_IVV=0.1696, w_REZ=0.8304", "answer_numeric": 0.1696, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000178 - 0.000114) / (0.000142 + 0.000178 - 0.000229)\n  Unconstrained: w_IVV=0.6996\n  After long-only clamp: w_IVV=0.6996, w_REZ=0.3004.", "metadata": {"weights": {"IVV": 0.1696, "REZ": 0.8304}, "sigma_1": 0.011902, "sigma_2": 0.01334, "covariance": 0.000114, "correlation": 0.72, "has_text": true, "text_chars": 3020, "mu_floor": 0.2682, "constraint_binding": true}}
{"id": "T4_all_20160225_0477", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "EMB"], "decision_date": "2016-02-25", "context_summary": "XLF \u03c3=0.0154, EMB \u03c3=0.0043, \u03c1=0.157. Min-variance weights: XLF=0.035, EMB=0.965.", "question": "Assets: XLF, EMB\nXLF: annualized_mean_return=-0.6804, daily_std=0.0154\nEMB: annualized_mean_return=-0.0252, daily_std=0.0043\nMinimum required portfolio return (annualized): -0.1434\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_EMB) 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_EMB=X.XXXX", "answer": "w_XLF=0.0331, w_EMB=0.9669", "answer_numeric": 0.0331, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000019 - 0.000011) / (0.000238 + 0.000019 - 0.000021)\n  Unconstrained: w_XLF=0.0350\n  After long-only clamp: w_XLF=0.0350, w_EMB=0.9650.", "metadata": {"weights": {"XLF": 0.0331, "EMB": 0.9669}, "sigma_1": 0.015438, "sigma_2": 0.004333, "covariance": 1.1e-05, "correlation": 0.1573, "has_text": true, "text_chars": 3020, "mu_floor": -0.1434, "constraint_binding": false}}
{"id": "T4_all_20180403_0479", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "EMB"], "decision_date": "2018-04-03", "context_summary": "XRP-USD \u03c3=0.0675, EMB \u03c3=0.0037, \u03c1=-0.104. Min-variance weights: XRP-USD=0.008, EMB=0.992.", "question": "Assets: XRP-USD, EMB\nXRP-USD: annualized_mean_return=-2.1672, daily_std=0.0675\nEMB: annualized_mean_return=-0.0504, daily_std=0.0037\nMinimum required portfolio return (annualized): -0.3810\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_EMB) 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_EMB=X.XXXX", "answer": "w_XRP-USD=0.0085, w_EMB=0.9915", "answer_numeric": 0.0085, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000013 - -0.000026) / (0.004551 + 0.000013 - -0.000051)\n  Unconstrained: w_XRP-USD=0.0084\n  After long-only clamp: w_XRP-USD=0.0084, w_EMB=0.9916.", "metadata": {"weights": {"XRP-USD": 0.0085, "EMB": 0.9915}, "sigma_1": 0.067463, "sigma_2": 0.00365, "covariance": -2.6e-05, "correlation": -0.1038, "has_text": false, "text_chars": 0, "mu_floor": -0.381, "constraint_binding": false}}
{"id": "T4_all_20200206_0484", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "DBB"], "decision_date": "2020-02-06", "context_summary": "LINK-USD \u03c3=0.0412, DBB \u03c3=0.0082, \u03c1=0.026. Min-variance weights: LINK-USD=0.033, DBB=0.967.", "question": "Assets: LINK-USD, DBB\nLINK-USD: annualized_mean_return=1.5624, daily_std=0.0412\nDBB: annualized_mean_return=-0.2520, daily_std=0.0082\nMinimum required portfolio return (annualized): 0.7354\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=0.5442, w_DBB=0.4558", "answer_numeric": 0.5442, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000067 - 0.000009) / (0.001700 + 0.000067 - 0.000018)\n  Unconstrained: w_LINK-USD=0.0331\n  After long-only clamp: w_LINK-USD=0.0331, w_DBB=0.9669.", "metadata": {"weights": {"LINK-USD": 0.5442, "DBB": 0.4558}, "sigma_1": 0.041226, "sigma_2": 0.008169, "covariance": 9e-06, "correlation": 0.0261, "has_text": false, "text_chars": 0, "mu_floor": 0.7354, "constraint_binding": true}}
{"id": "T4_all_20151030_0487", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "REZ"], "decision_date": "2015-10-30", "context_summary": "QUAL \u03c3=0.0127, REZ \u03c3=0.0115, \u03c1=0.740. Min-variance weights: QUAL=0.317, REZ=0.683.", "question": "Assets: QUAL, REZ\nQUAL: annualized_mean_return=0.0000, daily_std=0.0127\nREZ: annualized_mean_return=0.2268, daily_std=0.0115\nMinimum required portfolio return (annualized): 0.0977\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=0.3157, w_REZ=0.6843", "answer_numeric": 0.3157, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000133 - 0.000109) / (0.000162 + 0.000133 - 0.000217)\n  Unconstrained: w_QUAL=0.3171\n  After long-only clamp: w_QUAL=0.3171, w_REZ=0.6829.", "metadata": {"weights": {"QUAL": 0.3157, "REZ": 0.6843}, "sigma_1": 0.01272, "sigma_2": 0.011548, "covariance": 0.000109, "correlation": 0.74, "has_text": true, "text_chars": 3020, "mu_floor": 0.0977, "constraint_binding": false}}
{"id": "T4_all_20220810_0490", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "PPLT"], "decision_date": "2022-08-10", "context_summary": "MATIC-USD \u03c3=0.0804, PPLT \u03c3=0.0170, \u03c1=0.255. Min-variance weights: MATIC-USD=0.000, PPLT=1.000.", "question": "Assets: MATIC-USD, PPLT\nMATIC-USD: annualized_mean_return=2.4696, daily_std=0.0804\nPPLT: annualized_mean_return=-0.1512, daily_std=0.0170\nMinimum required portfolio return (annualized): 0.8798\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_MATIC-USD=0.3934, w_PPLT=0.6066", "answer_numeric": 0.3934, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000289 - 0.000348) / (0.006459 + 0.000289 - 0.000696)\n  Unconstrained: w_MATIC-USD=-0.0097\n  After long-only clamp: w_MATIC-USD=0.0000, w_PPLT=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.3934, "PPLT": 0.6066}, "sigma_1": 0.080371, "sigma_2": 0.017005, "covariance": 0.000348, "correlation": 0.2547, "has_text": true, "text_chars": 20, "mu_floor": 0.8798, "constraint_binding": true}}
{"id": "T4_all_20200311_0495", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "ICSH"], "decision_date": "2020-03-11", "context_summary": "BTC-USD \u03c3=0.0277, ICSH \u03c3=0.0004, \u03c1=-0.077. Min-variance weights: BTC-USD=0.001, ICSH=0.999.", "question": "Assets: BTC-USD, ICSH\nBTC-USD: annualized_mean_return=-0.0252, daily_std=0.0277\nICSH: annualized_mean_return=0.0252, daily_std=0.0004\nMinimum required portfolio return (annualized): -0.0037\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_ICSH) 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_ICSH=X.XXXX", "answer": "w_BTC-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 - -0.000001) / (0.000770 + 0.000000 - -0.000002)\n  Unconstrained: w_BTC-USD=0.0011\n  After long-only clamp: w_BTC-USD=0.0011, w_ICSH=0.9989.", "metadata": {"weights": {"BTC-USD": 0.0015, "ICSH": 0.9985}, "sigma_1": 0.027749, "sigma_2": 0.000358, "covariance": -1e-06, "correlation": -0.0765, "has_text": false, "text_chars": 0, "mu_floor": -0.0037, "constraint_binding": false}}
{"id": "T4_all_20190306_0498", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "HAUZ"], "decision_date": "2019-03-06", "context_summary": "LINK-USD \u03c3=0.0626, HAUZ \u03c3=0.0087, \u03c1=-0.105. Min-variance weights: LINK-USD=0.032, HAUZ=0.968.", "question": "Assets: LINK-USD, HAUZ\nLINK-USD: annualized_mean_return=0.2016, daily_std=0.0626\nHAUZ: annualized_mean_return=0.2268, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.2265\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_LINK-USD=0.0119, w_HAUZ=0.9881", "answer_numeric": 0.0119, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000075 - -0.000057) / (0.003918 + 0.000075 - -0.000113)\n  Unconstrained: w_LINK-USD=0.0321\n  After long-only clamp: w_LINK-USD=0.0321, w_HAUZ=0.9679.", "metadata": {"weights": {"LINK-USD": 0.0119, "HAUZ": 0.9881}, "sigma_1": 0.062591, "sigma_2": 0.00867, "covariance": -5.7e-05, "correlation": -0.1046, "has_text": false, "text_chars": 0, "mu_floor": 0.2265, "constraint_binding": true}}
{"id": "T4_all_20190225_0501", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "BIL"], "decision_date": "2019-02-25", "context_summary": "LINK-USD \u03c3=0.0685, BIL \u03c3=0.0001, \u03c1=0.010. Min-variance weights: LINK-USD=0.000, BIL=1.000.", "question": "Assets: LINK-USD, BIL\nLINK-USD: annualized_mean_return=1.4868, daily_std=0.0685\nBIL: annualized_mean_return=0.0252, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0252\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) / (0.004688 + 0.000000 - 0.000000)\n  Unconstrained: w_LINK-USD=-0.0000\n  After long-only clamp: w_LINK-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.068471, "sigma_2": 0.000117, "covariance": 0.0, "correlation": 0.01, "has_text": false, "text_chars": 0, "mu_floor": 0.0252, "constraint_binding": false}}
{"id": "T4_all_20220706_0504", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SCHP"], "decision_date": "2022-07-06", "context_summary": "IWM \u03c3=0.0191, SCHP \u03c3=0.0054, \u03c1=-0.009. Min-variance weights: IWM=0.075, SCHP=0.924.", "question": "Assets: IWM, SCHP\nIWM: annualized_mean_return=-0.4788, daily_std=0.0191\nSCHP: annualized_mean_return=-0.1008, daily_std=0.0054\nMinimum required portfolio return (annualized): -0.1094\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_SCHP) 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_SCHP=X.XXXX", "answer": "w_IWM=0.0228, w_SCHP=0.9772", "answer_numeric": 0.0228, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000029 - -0.000001) / (0.000363 + 0.000029 - -0.000002)\n  Unconstrained: w_IWM=0.0755\n  After long-only clamp: w_IWM=0.0755, w_SCHP=0.9245.", "metadata": {"weights": {"IWM": 0.0228, "SCHP": 0.9772}, "sigma_1": 0.019057, "sigma_2": 0.005366, "covariance": -1e-06, "correlation": -0.0092, "has_text": true, "text_chars": 3020, "mu_floor": -0.1094, "constraint_binding": true}}
{"id": "T4_all_20190207_0506", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "PDBC"], "decision_date": "2019-02-07", "context_summary": "VLUE \u03c3=0.0130, PDBC \u03c3=0.0108, \u03c1=0.060. Min-variance weights: VLUE=0.400, PDBC=0.600.", "question": "Assets: VLUE, PDBC\nVLUE: annualized_mean_return=-0.2772, daily_std=0.0130\nPDBC: annualized_mean_return=0.0252, daily_std=0.0108\nMinimum required portfolio return (annualized): -0.0486\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_VLUE=0.2440, w_PDBC=0.7560", "answer_numeric": 0.244, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000116 - 0.000008) / (0.000170 + 0.000116 - 0.000017)\n  Unconstrained: w_VLUE=0.3996\n  After long-only clamp: w_VLUE=0.3996, w_PDBC=0.6004.", "metadata": {"weights": {"VLUE": 0.244, "PDBC": 0.756}, "sigma_1": 0.013046, "sigma_2": 0.010774, "covariance": 8e-06, "correlation": 0.06, "has_text": true, "text_chars": 3020, "mu_floor": -0.0486, "constraint_binding": true}}
{"id": "T4_all_20210824_0509", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BIL"], "decision_date": "2021-08-24", "context_summary": "XLK \u03c3=0.0075, BIL \u03c3=0.0001, \u03c1=-0.288. Min-variance weights: XLK=0.004, BIL=0.997.", "question": "Assets: XLK, BIL\nXLK: annualized_mean_return=0.5796, daily_std=0.0075\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0001\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=0.0001, 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) / (0.000057 + 0.000000 - -0.000000)\n  Unconstrained: w_XLK=0.0035\n  After long-only clamp: w_XLK=0.0035, w_BIL=0.9965.", "metadata": {"weights": {"XLK": 0.0001, "BIL": 0.9999}, "sigma_1": 0.007545, "sigma_2": 8.9e-05, "covariance": -0.0, "correlation": -0.2885, "has_text": true, "text_chars": 3020, "mu_floor": 0.0001, "constraint_binding": false}}
{"id": "T4_all_20201020_0515", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD"], "decision_date": "2020-10-20", "context_summary": "QQQ \u03c3=0.0161, ADA-USD \u03c3=0.0515, \u03c1=-0.058. Min-variance weights: QQQ=0.898, ADA-USD=0.102.", "question": "Assets: QQQ, ADA-USD\nQQQ: annualized_mean_return=0.5292, daily_std=0.0161\nADA-USD: annualized_mean_return=-0.5292, daily_std=0.0515\nMinimum required portfolio return (annualized): 0.3013\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_ADA-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_ADA-USD=X.XXXX", "answer": "w_QQQ=0.8976, w_ADA-USD=0.1024", "answer_numeric": 0.8976, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.002656 - -0.000048) / (0.000260 + 0.002656 - -0.000096)\n  Unconstrained: w_QQQ=0.8976\n  After long-only clamp: w_QQQ=0.8976, w_ADA-USD=0.1024.", "metadata": {"weights": {"QQQ": 0.8976, "ADA-USD": 0.1024}, "sigma_1": 0.016137, "sigma_2": 0.051534, "covariance": -4.8e-05, "correlation": -0.0577, "has_text": true, "text_chars": 3020, "mu_floor": 0.3013, "constraint_binding": false}}
{"id": "T4_all_20190213_0522", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SCHH"], "decision_date": "2019-02-13", "context_summary": "XLF \u03c3=0.0131, SCHH \u03c3=0.0120, \u03c1=0.421. Min-variance weights: XLF=0.425, SCHH=0.575.", "question": "Assets: XLF, SCHH\nXLF: annualized_mean_return=-0.0756, daily_std=0.0131\nSCHH: annualized_mean_return=0.2268, daily_std=0.0120\nMinimum required portfolio return (annualized): 0.1905\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_XLF=0.1200, w_SCHH=0.8800", "answer_numeric": 0.12, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000144 - 0.000066) / (0.000172 + 0.000144 - 0.000132)\n  Unconstrained: w_XLF=0.4248\n  After long-only clamp: w_XLF=0.4248, w_SCHH=0.5752.", "metadata": {"weights": {"XLF": 0.12, "SCHH": 0.88}, "sigma_1": 0.013099, "sigma_2": 0.012001, "covariance": 6.6e-05, "correlation": 0.4211, "has_text": true, "text_chars": 3020, "mu_floor": 0.1905, "constraint_binding": true}}
{"id": "T4_all_20220930_0527", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "LQD"], "decision_date": "2022-09-30", "context_summary": "ETH-USD \u03c3=0.0426, LQD \u03c3=0.0075, \u03c1=-0.356. Min-variance weights: ETH-USD=0.081, LQD=0.919.", "question": "Assets: ETH-USD, LQD\nETH-USD: annualized_mean_return=-0.7308, daily_std=0.0426\nLQD: annualized_mean_return=-0.2772, daily_std=0.0075\nMinimum required portfolio return (annualized): -0.5190\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=0.0810, w_LQD=0.9190", "answer_numeric": 0.081, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000056 - -0.000114) / (0.001816 + 0.000056 - -0.000227)\n  Unconstrained: w_ETH-USD=0.0808\n  After long-only clamp: w_ETH-USD=0.0808, w_LQD=0.9192.", "metadata": {"weights": {"ETH-USD": 0.081, "LQD": 0.919}, "sigma_1": 0.042612, "sigma_2": 0.007484, "covariance": -0.000114, "correlation": -0.3563, "has_text": true, "text_chars": 20, "mu_floor": -0.519, "constraint_binding": false}}
{"id": "T4_all_20221220_0530", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "VNQI"], "decision_date": "2022-12-20", "context_summary": "BTC-USD \u03c3=0.0314, VNQI \u03c3=0.0142, \u03c1=-0.232. Min-variance weights: BTC-USD=0.219, VNQI=0.781.", "question": "Assets: BTC-USD, VNQI\nBTC-USD: annualized_mean_return=-0.4284, daily_std=0.0314\nVNQI: annualized_mean_return=0.1008, daily_std=0.0142\nMinimum required portfolio return (annualized): 0.0151\nMarket regime: sideways\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=0.1619, w_VNQI=0.8381", "answer_numeric": 0.1619, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000202 - -0.000103) / (0.000988 + 0.000202 - -0.000207)\n  Unconstrained: w_BTC-USD=0.2186\n  After long-only clamp: w_BTC-USD=0.2186, w_VNQI=0.7814.", "metadata": {"weights": {"BTC-USD": 0.1619, "VNQI": 0.8381}, "sigma_1": 0.031439, "sigma_2": 0.01421, "covariance": -0.000103, "correlation": -0.2316, "has_text": true, "text_chars": 20, "mu_floor": 0.0151, "constraint_binding": true}}
{"id": "T4_all_20200914_0537", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SOYB"], "decision_date": "2020-09-14", "context_summary": "XLI \u03c3=0.0129, SOYB \u03c3=0.0079, \u03c1=0.141. Min-variance weights: XLI=0.239, SOYB=0.761.", "question": "Assets: XLI, SOYB\nXLI: annualized_mean_return=0.4284, daily_std=0.0129\nSOYB: annualized_mean_return=0.4536, daily_std=0.0079\nMinimum required portfolio return (annualized): 0.4453\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_SOYB) 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_SOYB=X.XXXX", "answer": "w_XLI=0.2405, w_SOYB=0.7595", "answer_numeric": 0.2405, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000063 - 0.000014) / (0.000167 + 0.000063 - 0.000029)\n  Unconstrained: w_XLI=0.2392\n  After long-only clamp: w_XLI=0.2392, w_SOYB=0.7608.", "metadata": {"weights": {"XLI": 0.2405, "SOYB": 0.7595}, "sigma_1": 0.012941, "sigma_2": 0.007911, "covariance": 1.4e-05, "correlation": 0.1414, "has_text": true, "text_chars": 3020, "mu_floor": 0.4453, "constraint_binding": false}}
{"id": "T4_all_20200609_0540", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "VCIT"], "decision_date": "2020-06-09", "context_summary": "XLU \u03c3=0.0223, VCIT \u03c3=0.0048, \u03c1=0.002. Min-variance weights: XLU=0.044, VCIT=0.956.", "question": "Assets: XLU, VCIT\nXLU: annualized_mean_return=0.0252, daily_std=0.0223\nVCIT: annualized_mean_return=0.2772, daily_std=0.0048\nMinimum required portfolio return (annualized): 0.2740\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_XLU=0.0127, w_VCIT=0.9873", "answer_numeric": 0.0127, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000023 - 0.000000) / (0.000499 + 0.000023 - 0.000000)\n  Unconstrained: w_XLU=0.0443\n  After long-only clamp: w_XLU=0.0443, w_VCIT=0.9557.", "metadata": {"weights": {"XLU": 0.0127, "VCIT": 0.9873}, "sigma_1": 0.022342, "sigma_2": 0.004833, "covariance": 0.0, "correlation": 0.002, "has_text": true, "text_chars": 3020, "mu_floor": 0.274, "constraint_binding": true}}
{"id": "T4_all_20190920_0543", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "CPER"], "decision_date": "2019-09-20", "context_summary": "BTC-USD \u03c3=0.0277, CPER \u03c3=0.0097, \u03c1=0.232. Min-variance weights: BTC-USD=0.042, CPER=0.958.", "question": "Assets: BTC-USD, CPER\nBTC-USD: annualized_mean_return=-0.0252, daily_std=0.0277\nCPER: annualized_mean_return=-0.1764, daily_std=0.0097\nMinimum required portfolio return (annualized): -0.1711\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=0.0426, w_CPER=0.9574", "answer_numeric": 0.0426, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000093 - 0.000062) / (0.000769 + 0.000093 - 0.000124)\n  Unconstrained: w_BTC-USD=0.0424\n  After long-only clamp: w_BTC-USD=0.0424, w_CPER=0.9576.", "metadata": {"weights": {"BTC-USD": 0.0426, "CPER": 0.9574}, "sigma_1": 0.027727, "sigma_2": 0.009668, "covariance": 6.2e-05, "correlation": 0.2321, "has_text": false, "text_chars": 0, "mu_floor": -0.1711, "constraint_binding": false}}
{"id": "T4_all_20190902_0546", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "EMB"], "decision_date": "2019-09-02", "context_summary": "BTC-USD \u03c3=0.0410, EMB \u03c3=0.0039, \u03c1=0.158. Min-variance weights: BTC-USD=0.000, EMB=1.000.", "question": "Assets: BTC-USD, EMB\nBTC-USD: annualized_mean_return=-0.6300, daily_std=0.0410\nEMB: annualized_mean_return=0.2016, daily_std=0.0039\nMinimum required portfolio return (annualized): 0.1946\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_EMB) 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_EMB=X.XXXX", "answer": "w_BTC-USD=0.0000, w_EMB=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000015 - 0.000025) / (0.001684 + 0.000015 - 0.000050)\n  Unconstrained: w_BTC-USD=-0.0061\n  After long-only clamp: w_BTC-USD=0.0000, w_EMB=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "EMB": 1.0}, "sigma_1": 0.04104, "sigma_2": 0.003867, "covariance": 2.5e-05, "correlation": 0.1578, "has_text": false, "text_chars": 0, "mu_floor": 0.1946, "constraint_binding": false}}
{"id": "T4_all_20160125_0551", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DBC"], "decision_date": "2016-01-25", "context_summary": "XLI \u03c3=0.0101, DBC \u03c3=0.0111, \u03c1=0.061. Min-variance weights: XLI=0.550, DBC=0.450.", "question": "Assets: XLI, DBC\nXLI: annualized_mean_return=-0.4536, daily_std=0.0101\nDBC: annualized_mean_return=-0.7812, daily_std=0.0111\nMinimum required portfolio return (annualized): -0.6153\nMarket regime: sideways\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=0.5497, w_DBC=0.4503", "answer_numeric": 0.5497, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000123 - 0.000007) / (0.000102 + 0.000123 - 0.000014)\n  Unconstrained: w_XLI=0.5496\n  After long-only clamp: w_XLI=0.5496, w_DBC=0.4504.", "metadata": {"weights": {"XLI": 0.5497, "DBC": 0.4503}, "sigma_1": 0.010082, "sigma_2": 0.011069, "covariance": 7e-06, "correlation": 0.0613, "has_text": true, "text_chars": 3020, "mu_floor": -0.6153, "constraint_binding": false}}
{"id": "T4_all_20210107_0554", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "JNK"], "decision_date": "2021-01-07", "context_summary": "^VIX \u03c3=0.0642, JNK \u03c3=0.0032, \u03c1=-0.377. Min-variance weights: ^VIX=0.021, JNK=0.979.", "question": "Assets: ^VIX, JNK\n^VIX: annualized_mean_return=0.0252, daily_std=0.0642\nJNK: annualized_mean_return=0.1764, daily_std=0.0032\nMinimum required portfolio return (annualized): 0.1753\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_JNK) 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_JNK=X.XXXX", "answer": "w_^VIX=0.0073, w_JNK=0.9927", "answer_numeric": 0.0073, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000010 - -0.000078) / (0.004125 + 0.000010 - -0.000157)\n  Unconstrained: w_^VIX=0.0207\n  After long-only clamp: w_^VIX=0.0207, w_JNK=0.9793.", "metadata": {"weights": {"^VIX": 0.0073, "JNK": 0.9927}, "sigma_1": 0.064226, "sigma_2": 0.003238, "covariance": -7.8e-05, "correlation": -0.3766, "has_text": true, "text_chars": 3020, "mu_floor": 0.1753, "constraint_binding": true}}
{"id": "T4_all_20180109_0559", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "TLT"], "decision_date": "2018-01-09", "context_summary": "VEA \u03c3=0.0041, TLT \u03c3=0.0061, \u03c1=-0.238. Min-variance weights: VEA=0.656, TLT=0.344.", "question": "Assets: VEA, TLT\nVEA: annualized_mean_return=0.2520, daily_std=0.0041\nTLT: annualized_mean_return=0.0504, daily_std=0.0061\nMinimum required portfolio return (annualized): 0.1481\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_TLT) 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_TLT=X.XXXX", "answer": "w_VEA=0.6561, w_TLT=0.3439", "answer_numeric": 0.6561, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000038 - -0.000006) / (0.000017 + 0.000038 - -0.000012)\n  Unconstrained: w_VEA=0.6561\n  After long-only clamp: w_VEA=0.6561, w_TLT=0.3439.", "metadata": {"weights": {"VEA": 0.6561, "TLT": 0.3439}, "sigma_1": 0.004103, "sigma_2": 0.006129, "covariance": -6e-06, "correlation": -0.2385, "has_text": true, "text_chars": 3020, "mu_floor": 0.1481, "constraint_binding": false}}
{"id": "T4_all_20191011_0568", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SCHP"], "decision_date": "2019-10-11", "context_summary": "EEM \u03c3=0.0102, SCHP \u03c3=0.0030, \u03c1=-0.053. Min-variance weights: EEM=0.092, SCHP=0.908.", "question": "Assets: EEM, SCHP\nEEM: annualized_mean_return=-0.1512, daily_std=0.0102\nSCHP: annualized_mean_return=0.0000, daily_std=0.0030\nMinimum required portfolio return (annualized): -0.0103\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_SCHP) 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_SCHP=X.XXXX", "answer": "w_EEM=0.0681, w_SCHP=0.9319", "answer_numeric": 0.0681, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000009 - -0.000002) / (0.000103 + 0.000009 - -0.000003)\n  Unconstrained: w_EEM=0.0922\n  After long-only clamp: w_EEM=0.0922, w_SCHP=0.9078.", "metadata": {"weights": {"EEM": 0.0681, "SCHP": 0.9319}, "sigma_1": 0.010157, "sigma_2": 0.003003, "covariance": -2e-06, "correlation": -0.0534, "has_text": true, "text_chars": 3020, "mu_floor": -0.0103, "constraint_binding": true}}
{"id": "T4_all_20191010_0571", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XHB"], "decision_date": "2019-10-10", "context_summary": "XLY \u03c3=0.0111, XHB \u03c3=0.0109, \u03c1=0.844. Min-variance weights: XLY=0.447, XHB=0.553.", "question": "Assets: XLY, XHB\nXLY: annualized_mean_return=-0.2016, daily_std=0.0111\nXHB: annualized_mean_return=0.0504, daily_std=0.0109\nMinimum required portfolio return (annualized): -0.0983\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=0.4463, w_XHB=0.5537", "answer_numeric": 0.4463, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000120 - 0.000103) / (0.000124 + 0.000120 - 0.000206)\n  Unconstrained: w_XLY=0.4467\n  After long-only clamp: w_XLY=0.4467, w_XHB=0.5533.", "metadata": {"weights": {"XLY": 0.4463, "XHB": 0.5537}, "sigma_1": 0.011133, "sigma_2": 0.010949, "covariance": 0.000103, "correlation": 0.8442, "has_text": true, "text_chars": 3020, "mu_floor": -0.0983, "constraint_binding": false}}
{"id": "T4_all_20220720_0578", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "QQQ"], "decision_date": "2022-07-20", "context_summary": "MATIC-USD \u03c3=0.0783, QQQ \u03c3=0.0225, \u03c1=-0.230. Min-variance weights: MATIC-USD=0.123, QQQ=0.877.", "question": "Assets: MATIC-USD, QQQ\nMATIC-USD: annualized_mean_return=2.3184, daily_std=0.0783\nQQQ: annualized_mean_return=-0.3276, daily_std=0.0225\nMinimum required portfolio return (annualized): 1.2625\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_QQQ) 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_QQQ=X.XXXX", "answer": "w_MATIC-USD=0.6009, w_QQQ=0.3991", "answer_numeric": 0.6009, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000508 - -0.000406) / (0.006131 + 0.000508 - -0.000812)\n  Unconstrained: w_MATIC-USD=0.1227\n  After long-only clamp: w_MATIC-USD=0.1227, w_QQQ=0.8773.", "metadata": {"weights": {"MATIC-USD": 0.6009, "QQQ": 0.3991}, "sigma_1": 0.078302, "sigma_2": 0.022548, "covariance": -0.000406, "correlation": -0.2301, "has_text": true, "text_chars": 20, "mu_floor": 1.2625, "constraint_binding": true}}
{"id": "T4_all_20210728_0581", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BIL"], "decision_date": "2021-07-28", "context_summary": "EWJ \u03c3=0.0097, BIL \u03c3=0.0001, \u03c1=-0.150. Min-variance weights: EWJ=0.001, BIL=0.999.", "question": "Assets: EWJ, BIL\nEWJ: annualized_mean_return=0.0252, daily_std=0.0097\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0000\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_BIL) 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_BIL=X.XXXX", "answer": "w_EWJ=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) / (0.000095 + 0.000000 - -0.000000)\n  Unconstrained: w_EWJ=0.0014\n  After long-only clamp: w_EWJ=0.0014, w_BIL=0.9986.", "metadata": {"weights": {"EWJ": 0.0001, "BIL": 0.9999}, "sigma_1": 0.009726, "sigma_2": 8.5e-05, "covariance": -0.0, "correlation": -0.1497, "has_text": true, "text_chars": 3020, "mu_floor": -0.0, "constraint_binding": false}}
{"id": "T4_all_20160623_0584", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "ITB"], "decision_date": "2016-06-23", "context_summary": "BTC-USD \u03c3=0.0354, ITB \u03c3=0.0108, \u03c1=0.101. Min-variance weights: BTC-USD=0.060, ITB=0.940.", "question": "Assets: BTC-USD, ITB\nBTC-USD: annualized_mean_return=1.3356, daily_std=0.0354\nITB: annualized_mean_return=0.0504, daily_std=0.0108\nMinimum required portfolio return (annualized): 0.5181\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=0.3639, w_ITB=0.6361", "answer_numeric": 0.3639, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000117 - 0.000039) / (0.001256 + 0.000117 - 0.000078)\n  Unconstrained: w_BTC-USD=0.0604\n  After long-only clamp: w_BTC-USD=0.0604, w_ITB=0.9396.", "metadata": {"weights": {"BTC-USD": 0.3639, "ITB": 0.6361}, "sigma_1": 0.035439, "sigma_2": 0.010825, "covariance": 3.9e-05, "correlation": 0.1014, "has_text": false, "text_chars": 0, "mu_floor": 0.5181, "constraint_binding": true}}
{"id": "T4_all_20210929_0588", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "ACWI"], "decision_date": "2021-09-29", "context_summary": "MATIC-USD \u03c3=0.0701, ACWI \u03c3=0.0069, \u03c1=-0.038. Min-variance weights: MATIC-USD=0.013, ACWI=0.987.", "question": "Assets: MATIC-USD, ACWI\nMATIC-USD: annualized_mean_return=0.5292, daily_std=0.0701\nACWI: annualized_mean_return=-0.0504, daily_std=0.0069\nMinimum required portfolio return (annualized): 0.2442\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_ACWI) 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_ACWI=X.XXXX", "answer": "w_MATIC-USD=0.5083, w_ACWI=0.4917", "answer_numeric": 0.5083, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000047 - -0.000018) / (0.004915 + 0.000047 - -0.000037)\n  Unconstrained: w_MATIC-USD=0.0131\n  After long-only clamp: w_MATIC-USD=0.0131, w_ACWI=0.9869.", "metadata": {"weights": {"MATIC-USD": 0.5083, "ACWI": 0.4917}, "sigma_1": 0.070109, "sigma_2": 0.006864, "covariance": -1.8e-05, "correlation": -0.038, "has_text": false, "text_chars": 0, "mu_floor": 0.2442, "constraint_binding": true}}
{"id": "T4_all_20220204_0591", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "AVAX-USD"], "decision_date": "2022-02-04", "context_summary": "XLK \u03c3=0.0160, AVAX-USD \u03c3=0.0634, \u03c1=-0.191. Min-variance weights: XLK=0.904, AVAX-USD=0.096.", "question": "Assets: XLK, AVAX-USD\nXLK: annualized_mean_return=-0.2520, daily_std=0.0160\nAVAX-USD: annualized_mean_return=-0.4536, daily_std=0.0634\nMinimum required portfolio return (annualized): -0.3368\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_AVAX-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_AVAX-USD=X.XXXX", "answer": "w_XLK=0.9040, w_AVAX-USD=0.0960", "answer_numeric": 0.904, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.004024 - -0.000193) / (0.000255 + 0.004024 - -0.000386)\n  Unconstrained: w_XLK=0.9040\n  After long-only clamp: w_XLK=0.9040, w_AVAX-USD=0.0960.", "metadata": {"weights": {"XLK": 0.904, "AVAX-USD": 0.096}, "sigma_1": 0.015957, "sigma_2": 0.063435, "covariance": -0.000193, "correlation": -0.1909, "has_text": true, "text_chars": 3020, "mu_floor": -0.3368, "constraint_binding": false}}
{"id": "T4_all_20200409_0596", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "MTUM"], "decision_date": "2020-04-09", "context_summary": "ADA-USD \u03c3=0.0648, MTUM \u03c3=0.0220, \u03c1=-0.043. Min-variance weights: ADA-USD=0.114, MTUM=0.886.", "question": "Assets: ADA-USD, MTUM\nADA-USD: annualized_mean_return=-0.2772, daily_std=0.0648\nMTUM: annualized_mean_return=-0.6552, daily_std=0.0220\nMinimum required portfolio return (annualized): -0.5204\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_MTUM) 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_MTUM=X.XXXX", "answer": "w_ADA-USD=0.3566, w_MTUM=0.6434", "answer_numeric": 0.3566, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000485 - -0.000062) / (0.004193 + 0.000485 - -0.000124)\n  Unconstrained: w_ADA-USD=0.1139\n  After long-only clamp: w_ADA-USD=0.1139, w_MTUM=0.8861.", "metadata": {"weights": {"ADA-USD": 0.3566, "MTUM": 0.6434}, "sigma_1": 0.064756, "sigma_2": 0.022027, "covariance": -6.2e-05, "correlation": -0.0434, "has_text": false, "text_chars": 0, "mu_floor": -0.5204, "constraint_binding": true}}
{"id": "T4_all_20220921_0599", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "HAUZ"], "decision_date": "2022-09-21", "context_summary": "XRP-USD \u03c3=0.0342, HAUZ \u03c3=0.0109, \u03c1=-0.077. Min-variance weights: XRP-USD=0.109, HAUZ=0.891.", "question": "Assets: XRP-USD, HAUZ\nXRP-USD: annualized_mean_return=0.7560, daily_std=0.0342\nHAUZ: annualized_mean_return=-0.2520, daily_std=0.0109\nMinimum required portfolio return (annualized): -0.2079\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_XRP-USD=0.1091, w_HAUZ=0.8909", "answer_numeric": 0.1091, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000118 - -0.000029) / (0.001171 + 0.000118 - -0.000057)\n  Unconstrained: w_XRP-USD=0.1089\n  After long-only clamp: w_XRP-USD=0.1089, w_HAUZ=0.8911.", "metadata": {"weights": {"XRP-USD": 0.1091, "HAUZ": 0.8909}, "sigma_1": 0.034217, "sigma_2": 0.010858, "covariance": -2.9e-05, "correlation": -0.077, "has_text": true, "text_chars": 20, "mu_floor": -0.2079, "constraint_binding": false}}
{"id": "T4_all_20160920_0602", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SCHH"], "decision_date": "2016-09-20", "context_summary": "QUAL \u03c3=0.0079, SCHH \u03c3=0.0094, \u03c1=0.639. Min-variance weights: QUAL=0.737, SCHH=0.263.", "question": "Assets: QUAL, SCHH\nQUAL: annualized_mean_return=0.0504, daily_std=0.0079\nSCHH: annualized_mean_return=0.0756, daily_std=0.0094\nMinimum required portfolio return (annualized): 0.0710\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=0.1825, w_SCHH=0.8175", "answer_numeric": 0.1825, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000089 - 0.000048) / (0.000062 + 0.000089 - 0.000095)\n  Unconstrained: w_QUAL=0.7371\n  After long-only clamp: w_QUAL=0.7371, w_SCHH=0.2629.", "metadata": {"weights": {"QUAL": 0.1825, "SCHH": 0.8175}, "sigma_1": 0.007897, "sigma_2": 0.009432, "covariance": 4.8e-05, "correlation": 0.6392, "has_text": true, "text_chars": 3020, "mu_floor": 0.071, "constraint_binding": true}}
{"id": "T4_all_20190813_0605", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ICSH"], "decision_date": "2019-08-13", "context_summary": "FXI \u03c3=0.0109, ICSH \u03c3=0.0003, \u03c1=-0.273. Min-variance weights: FXI=0.008, ICSH=0.992.", "question": "Assets: FXI, ICSH\nFXI: annualized_mean_return=-0.3276, daily_std=0.0109\nICSH: annualized_mean_return=0.0252, daily_std=0.0003\nMinimum required portfolio return (annualized): -0.1446\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=0.0088, w_ICSH=0.9912", "answer_numeric": 0.0088, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - -0.000001) / (0.000120 + 0.000000 - -0.000002)\n  Unconstrained: w_FXI=0.0076\n  After long-only clamp: w_FXI=0.0076, w_ICSH=0.9924.", "metadata": {"weights": {"FXI": 0.0088, "ICSH": 0.9912}, "sigma_1": 0.010947, "sigma_2": 0.00028, "covariance": -1e-06, "correlation": -0.2735, "has_text": true, "text_chars": 3020, "mu_floor": -0.1446, "constraint_binding": false}}
{"id": "T4_all_20170110_0612", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "TLH"], "decision_date": "2017-01-10", "context_summary": "MTUM \u03c3=0.0066, TLH \u03c3=0.0045, \u03c1=-0.332. Min-variance weights: MTUM=0.360, TLH=0.639.", "question": "Assets: MTUM, TLH\nMTUM: annualized_mean_return=0.0756, daily_std=0.0066\nTLH: annualized_mean_return=-0.1764, daily_std=0.0045\nMinimum required portfolio return (annualized): 0.0384\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_TLH) 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_TLH=X.XXXX", "answer": "w_MTUM=0.8524, w_TLH=0.1476", "answer_numeric": 0.8524, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000020 - -0.000010) / (0.000044 + 0.000020 - -0.000020)\n  Unconstrained: w_MTUM=0.3605\n  After long-only clamp: w_MTUM=0.3605, w_TLH=0.6395.", "metadata": {"weights": {"MTUM": 0.8524, "TLH": 0.1476}, "sigma_1": 0.006616, "sigma_2": 0.004511, "covariance": -1e-05, "correlation": -0.3318, "has_text": true, "text_chars": 3020, "mu_floor": 0.0384, "constraint_binding": true}}
{"id": "T4_all_20150827_0615", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "IGOV"], "decision_date": "2015-08-27", "context_summary": "XLK \u03c3=0.0124, IGOV \u03c3=0.0058, \u03c1=-0.431. Min-variance weights: XLK=0.259, IGOV=0.741.", "question": "Assets: XLK, IGOV\nXLK: annualized_mean_return=-0.4284, daily_std=0.0124\nIGOV: annualized_mean_return=0.0756, daily_std=0.0058\nMinimum required portfolio return (annualized): -0.1194\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_IGOV) 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_IGOV=X.XXXX", "answer": "w_XLK=0.2596, w_IGOV=0.7404", "answer_numeric": 0.2596, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000033 - -0.000031) / (0.000153 + 0.000033 - -0.000062)\n  Unconstrained: w_XLK=0.2591\n  After long-only clamp: w_XLK=0.2591, w_IGOV=0.7409.", "metadata": {"weights": {"XLK": 0.2596, "IGOV": 0.7404}, "sigma_1": 0.012353, "sigma_2": 0.005776, "covariance": -3.1e-05, "correlation": -0.4311, "has_text": true, "text_chars": 3020, "mu_floor": -0.1194, "constraint_binding": false}}
{"id": "T4_all_20201111_0618", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "FXI"], "decision_date": "2020-11-11", "context_summary": "BNB-USD \u03c3=0.0425, FXI \u03c3=0.0125, \u03c1=-0.017. Min-variance weights: BNB-USD=0.084, FXI=0.916.", "question": "Assets: BNB-USD, FXI\nBNB-USD: annualized_mean_return=0.6552, daily_std=0.0425\nFXI: annualized_mean_return=0.3024, daily_std=0.0125\nMinimum required portfolio return (annualized): 0.3974\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_FXI) 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_FXI=X.XXXX", "answer": "w_BNB-USD=0.2693, w_FXI=0.7307", "answer_numeric": 0.2693, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000157 - -0.000009) / (0.001802 + 0.000157 - -0.000018)\n  Unconstrained: w_BNB-USD=0.0841\n  After long-only clamp: w_BNB-USD=0.0841, w_FXI=0.9159.", "metadata": {"weights": {"BNB-USD": 0.2693, "FXI": 0.7307}, "sigma_1": 0.042454, "sigma_2": 0.012546, "covariance": -9e-06, "correlation": -0.0167, "has_text": false, "text_chars": 0, "mu_floor": 0.3974, "constraint_binding": true}}
{"id": "T4_all_20210908_0621", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "IEF"], "decision_date": "2021-09-08", "context_summary": "ETH-USD \u03c3=0.0437, IEF \u03c3=0.0031, \u03c1=0.339. Min-variance weights: ETH-USD=0.000, IEF=1.000.", "question": "Assets: ETH-USD, IEF\nETH-USD: annualized_mean_return=2.2176, daily_std=0.0437\nIEF: annualized_mean_return=0.1008, daily_std=0.0031\nMinimum required portfolio return (annualized): 0.1008\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=0.0000, w_IEF=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000009 - 0.000045) / (0.001906 + 0.000009 - 0.000091)\n  Unconstrained: w_ETH-USD=-0.0197\n  After long-only clamp: w_ETH-USD=0.0000, w_IEF=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "IEF": 1.0}, "sigma_1": 0.043663, "sigma_2": 0.003061, "covariance": 4.5e-05, "correlation": 0.3389, "has_text": false, "text_chars": 0, "mu_floor": 0.1008, "constraint_binding": false}}
{"id": "T4_all_20220811_0624", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "TLH"], "decision_date": "2022-08-11", "context_summary": "MATIC-USD \u03c3=0.0794, TLH \u03c3=0.0097, \u03c1=0.019. Min-variance weights: MATIC-USD=0.013, TLH=0.988.", "question": "Assets: MATIC-USD, TLH\nMATIC-USD: annualized_mean_return=3.0996, daily_std=0.0794\nTLH: annualized_mean_return=0.1008, daily_std=0.0097\nMinimum required portfolio return (annualized): 1.7382\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_TLH) 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_TLH=X.XXXX", "answer": "w_MATIC-USD=0.5460, w_TLH=0.4540", "answer_numeric": 0.546, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000095 - 0.000015) / (0.006301 + 0.000095 - 0.000030)\n  Unconstrained: w_MATIC-USD=0.0125\n  After long-only clamp: w_MATIC-USD=0.0125, w_TLH=0.9875.", "metadata": {"weights": {"MATIC-USD": 0.546, "TLH": 0.454}, "sigma_1": 0.07938, "sigma_2": 0.00974, "covariance": 1.5e-05, "correlation": 0.0195, "has_text": true, "text_chars": 20, "mu_floor": 1.7382, "constraint_binding": true}}
{"id": "T4_all_20190614_0627", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BIL"], "decision_date": "2019-06-14", "context_summary": "^VIX \u03c3=0.0806, BIL \u03c3=0.0001, \u03c1=0.206. Min-variance weights: ^VIX=0.000, BIL=1.000.", "question": "Assets: ^VIX, BIL\n^VIX: annualized_mean_return=0.6552, daily_std=0.0806\nBIL: annualized_mean_return=0.0252, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0252\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_BIL) 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_BIL=X.XXXX", "answer": "w_^VIX=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 - 0.000002) / (0.006504 + 0.000000 - 0.000004)\n  Unconstrained: w_^VIX=-0.0003\n  After long-only clamp: w_^VIX=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"^VIX": 0.0, "BIL": 1.0}, "sigma_1": 0.080645, "sigma_2": 0.000115, "covariance": 2e-06, "correlation": 0.2056, "has_text": true, "text_chars": 3020, "mu_floor": 0.0252, "constraint_binding": false}}
{"id": "T4_all_20160509_0630", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "PALL"], "decision_date": "2016-05-09", "context_summary": "MTUM \u03c3=0.0076, PALL \u03c3=0.0178, \u03c1=-0.102. Min-variance weights: MTUM=0.823, PALL=0.177.", "question": "Assets: MTUM, PALL\nMTUM: annualized_mean_return=0.4536, daily_std=0.0076\nPALL: annualized_mean_return=0.6804, daily_std=0.0178\nMinimum required portfolio return (annualized): 0.6305\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_PALL) 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_PALL=X.XXXX", "answer": "w_MTUM=0.2200, w_PALL=0.7800", "answer_numeric": 0.22, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000318 - -0.000014) / (0.000058 + 0.000318 - -0.000028)\n  Unconstrained: w_MTUM=0.8228\n  After long-only clamp: w_MTUM=0.8228, w_PALL=0.1772.", "metadata": {"weights": {"MTUM": 0.22, "PALL": 0.78}, "sigma_1": 0.007601, "sigma_2": 0.017846, "covariance": -1.4e-05, "correlation": -0.1016, "has_text": true, "text_chars": 3020, "mu_floor": 0.6305, "constraint_binding": true}}
{"id": "T4_all_20191017_0635", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "TIP"], "decision_date": "2019-10-17", "context_summary": "EEM \u03c3=0.0104, TIP \u03c3=0.0010, \u03c1=-0.019. Min-variance weights: EEM=0.011, TIP=0.989.", "question": "Assets: EEM, TIP\nEEM: annualized_mean_return=-0.0756, daily_std=0.0104\nTIP: annualized_mean_return=0.0000, daily_std=0.0010\nMinimum required portfolio return (annualized): -0.0283\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_TIP) 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_TIP=X.XXXX", "answer": "w_EEM=0.0096, w_TIP=0.9904", "answer_numeric": 0.0096, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000001 - -0.000000) / (0.000108 + 0.000001 - -0.000000)\n  Unconstrained: w_EEM=0.0114\n  After long-only clamp: w_EEM=0.0114, w_TIP=0.9886.", "metadata": {"weights": {"EEM": 0.0096, "TIP": 0.9904}, "sigma_1": 0.010412, "sigma_2": 0.001024, "covariance": -0.0, "correlation": -0.0189, "has_text": true, "text_chars": 3020, "mu_floor": -0.0283, "constraint_binding": false}}
{"id": "T4_all_20180130_0638", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "TLH"], "decision_date": "2018-01-30", "context_summary": "XLK \u03c3=0.0071, TLH \u03c3=0.0033, \u03c1=-0.281. Min-variance weights: XLK=0.232, TLH=0.768.", "question": "Assets: XLK, TLH\nXLK: annualized_mean_return=0.3780, daily_std=0.0071\nTLH: annualized_mean_return=-0.1008, daily_std=0.0033\nMinimum required portfolio return (annualized): 0.1045\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_TLH) 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_TLH=X.XXXX", "answer": "w_XLK=0.4288, w_TLH=0.5712", "answer_numeric": 0.4288, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000011 - -0.000007) / (0.000051 + 0.000011 - -0.000013)\n  Unconstrained: w_XLK=0.2318\n  After long-only clamp: w_XLK=0.2318, w_TLH=0.7682.", "metadata": {"weights": {"XLK": 0.4288, "TLH": 0.5712}, "sigma_1": 0.007132, "sigma_2": 0.00328, "covariance": -7e-06, "correlation": -0.281, "has_text": true, "text_chars": 3020, "mu_floor": 0.1045, "constraint_binding": true}}
{"id": "T4_all_20200520_0643", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "VNQI"], "decision_date": "2020-05-20", "context_summary": "BNB-USD \u03c3=0.0404, VNQI \u03c3=0.0170, \u03c1=-0.343. Min-variance weights: BNB-USD=0.220, VNQI=0.780.", "question": "Assets: BNB-USD, VNQI\nBNB-USD: annualized_mean_return=1.7640, daily_std=0.0404\nVNQI: annualized_mean_return=-0.3024, daily_std=0.0170\nMinimum required portfolio return (annualized): 0.1142\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=0.2198, w_VNQI=0.7802", "answer_numeric": 0.2198, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000291 - -0.000237) / (0.001635 + 0.000291 - -0.000473)\n  Unconstrained: w_BNB-USD=0.2198\n  After long-only clamp: w_BNB-USD=0.2198, w_VNQI=0.7802.", "metadata": {"weights": {"BNB-USD": 0.2198, "VNQI": 0.7802}, "sigma_1": 0.040439, "sigma_2": 0.017046, "covariance": -0.000237, "correlation": -0.3434, "has_text": false, "text_chars": 0, "mu_floor": 0.1142, "constraint_binding": false}}
{"id": "T4_all_20190924_0647", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "INDS"], "decision_date": "2019-09-24", "context_summary": "QQQ \u03c3=0.0116, INDS \u03c3=0.0089, \u03c1=0.699. Min-variance weights: QQQ=0.097, INDS=0.903.", "question": "Assets: QQQ, INDS\nQQQ: annualized_mean_return=0.1008, daily_std=0.0116\nINDS: annualized_mean_return=0.2268, daily_std=0.0089\nMinimum required portfolio return (annualized): 0.2024\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_INDS) 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_INDS=X.XXXX", "answer": "w_QQQ=0.0956, w_INDS=0.9044", "answer_numeric": 0.0956, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000079 - 0.000072) / (0.000134 + 0.000079 - 0.000144)\n  Unconstrained: w_QQQ=0.0966\n  After long-only clamp: w_QQQ=0.0966, w_INDS=0.9034.", "metadata": {"weights": {"QQQ": 0.0956, "INDS": 0.9044}, "sigma_1": 0.011597, "sigma_2": 0.008866, "covariance": 7.2e-05, "correlation": 0.6995, "has_text": true, "text_chars": 3020, "mu_floor": 0.2024, "constraint_binding": false}}
{"id": "T4_all_20170111_0652", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "DBC"], "decision_date": "2017-01-11", "context_summary": "QQQ \u03c3=0.0075, DBC \u03c3=0.0094, \u03c1=0.002. Min-variance weights: QQQ=0.610, DBC=0.390.", "question": "Assets: QQQ, DBC\nQQQ: annualized_mean_return=0.2016, daily_std=0.0075\nDBC: annualized_mean_return=0.0756, daily_std=0.0094\nMinimum required portfolio return (annualized): 0.1743\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_DBC) 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_DBC=X.XXXX", "answer": "w_QQQ=0.7833, w_DBC=0.2167", "answer_numeric": 0.7833, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000089 - 0.000000) / (0.000057 + 0.000089 - 0.000000)\n  Unconstrained: w_QQQ=0.6100\n  After long-only clamp: w_QQQ=0.6100, w_DBC=0.3900.", "metadata": {"weights": {"QQQ": 0.7833, "DBC": 0.2167}, "sigma_1": 0.007527, "sigma_2": 0.00941, "covariance": 0.0, "correlation": 0.0024, "has_text": true, "text_chars": 3020, "mu_floor": 0.1743, "constraint_binding": true}}
{"id": "T4_all_20180119_0655", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "IEF"], "decision_date": "2018-01-19", "context_summary": "BTC-USD \u03c3=0.0628, IEF \u03c3=0.0022, \u03c1=0.128. Min-variance weights: BTC-USD=0.000, IEF=1.000.", "question": "Assets: BTC-USD, IEF\nBTC-USD: annualized_mean_return=1.2600, daily_std=0.0628\nIEF: annualized_mean_return=-0.0252, daily_std=0.0022\nMinimum required portfolio return (annualized): -0.0252\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_IEF) 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_IEF=X.XXXX", "answer": "w_BTC-USD=0.0000, w_IEF=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 - 0.000017) / (0.003941 + 0.000005 - 0.000035)\n  Unconstrained: w_BTC-USD=-0.0032\n  After long-only clamp: w_BTC-USD=0.0000, w_IEF=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "IEF": 1.0}, "sigma_1": 0.062774, "sigma_2": 0.002159, "covariance": 1.7e-05, "correlation": 0.1281, "has_text": false, "text_chars": 0, "mu_floor": -0.0252, "constraint_binding": false}}
{"id": "T4_all_20210715_0660", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "BIL"], "decision_date": "2021-07-15", "context_summary": "DOT-USD \u03c3=0.0863, BIL \u03c3=0.0001, \u03c1=-0.174. Min-variance weights: DOT-USD=0.000, BIL=1.000.", "question": "Assets: DOT-USD, BIL\nDOT-USD: annualized_mean_return=-2.5956, daily_std=0.0863\nBIL: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0002\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_BIL) 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_BIL=X.XXXX", "answer": "w_DOT-USD=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 - -0.000001) / (0.007452 + 0.000000 - -0.000003)\n  Unconstrained: w_DOT-USD=0.0002\n  After long-only clamp: w_DOT-USD=0.0002, w_BIL=0.9998.", "metadata": {"weights": {"DOT-USD": 0.0001, "BIL": 0.9999}, "sigma_1": 0.086326, "sigma_2": 8.3e-05, "covariance": -1e-06, "correlation": -0.1741, "has_text": false, "text_chars": 0, "mu_floor": -0.0002, "constraint_binding": true}}
{"id": "T4_all_20181017_0663", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "WEAT"], "decision_date": "2018-10-17", "context_summary": "ETH-USD \u03c3=0.0522, WEAT \u03c3=0.0150, \u03c1=0.164. Min-variance weights: ETH-USD=0.036, WEAT=0.964.", "question": "Assets: ETH-USD, WEAT\nETH-USD: annualized_mean_return=-1.2096, daily_std=0.0522\nWEAT: annualized_mean_return=-0.0504, daily_std=0.0150\nMinimum required portfolio return (annualized): -0.3232\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=0.0360, w_WEAT=0.9640", "answer_numeric": 0.036, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000226 - 0.000129) / (0.002728 + 0.000226 - 0.000257)\n  Unconstrained: w_ETH-USD=0.0361\n  After long-only clamp: w_ETH-USD=0.0361, w_WEAT=0.9639.", "metadata": {"weights": {"ETH-USD": 0.036, "WEAT": 0.964}, "sigma_1": 0.052235, "sigma_2": 0.015037, "covariance": 0.000129, "correlation": 0.1639, "has_text": false, "text_chars": 0, "mu_floor": -0.3232, "constraint_binding": false}}
{"id": "T4_all_20220328_0668", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "TLT"], "decision_date": "2022-03-28", "context_summary": "USMV \u03c3=0.0098, TLT \u03c3=0.0114, \u03c1=-0.119. Min-variance weights: USMV=0.567, TLT=0.433.", "question": "Assets: USMV, TLT\nUSMV: annualized_mean_return=-0.2268, daily_std=0.0098\nTLT: annualized_mean_return=-0.5040, daily_std=0.0114\nMinimum required portfolio return (annualized): -0.2751\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_TLT) 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_TLT=X.XXXX", "answer": "w_USMV=0.8258, w_TLT=0.1742", "answer_numeric": 0.8258, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000130 - -0.000013) / (0.000097 + 0.000130 - -0.000027)\n  Unconstrained: w_USMV=0.5668\n  After long-only clamp: w_USMV=0.5668, w_TLT=0.4332.", "metadata": {"weights": {"USMV": 0.8258, "TLT": 0.1742}, "sigma_1": 0.009827, "sigma_2": 0.011423, "covariance": -1.3e-05, "correlation": -0.1192, "has_text": true, "text_chars": 3020, "mu_floor": -0.2751, "constraint_binding": true}}
{"id": "T4_all_20210603_0671", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "BNO"], "decision_date": "2021-06-03", "context_summary": "BNB-USD \u03c3=0.0856, BNO \u03c3=0.0214, \u03c1=-0.110. Min-variance weights: BNB-USD=0.080, BNO=0.920.", "question": "Assets: BNB-USD, BNO\nBNB-USD: annualized_mean_return=2.5704, daily_std=0.0856\nBNO: annualized_mean_return=0.2772, daily_std=0.0214\nMinimum required portfolio return (annualized): 0.4397\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_BNO) 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_BNO=X.XXXX", "answer": "w_BNB-USD=0.0803, w_BNO=0.9197", "answer_numeric": 0.0803, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000457 - -0.000201) / (0.007332 + 0.000457 - -0.000401)\n  Unconstrained: w_BNB-USD=0.0803\n  After long-only clamp: w_BNB-USD=0.0803, w_BNO=0.9197.", "metadata": {"weights": {"BNB-USD": 0.0803, "BNO": 0.9197}, "sigma_1": 0.085629, "sigma_2": 0.021375, "covariance": -0.000201, "correlation": -0.1095, "has_text": false, "text_chars": 0, "mu_floor": 0.4397, "constraint_binding": false}}
{"id": "T4_all_20211103_0677", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MORT"], "decision_date": "2021-11-03", "context_summary": "FXI \u03c3=0.0162, MORT \u03c3=0.0080, \u03c1=0.449. Min-variance weights: FXI=0.027, MORT=0.973.", "question": "Assets: FXI, MORT\nFXI: annualized_mean_return=-0.1260, daily_std=0.0162\nMORT: annualized_mean_return=0.2268, daily_std=0.0080\nMinimum required portfolio return (annualized): 0.0397\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=0.0289, w_MORT=0.9711", "answer_numeric": 0.0289, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000064 - 0.000058) / (0.000264 + 0.000064 - 0.000117)\n  Unconstrained: w_FXI=0.0270\n  After long-only clamp: w_FXI=0.0270, w_MORT=0.9730.", "metadata": {"weights": {"FXI": 0.0289, "MORT": 0.9711}, "sigma_1": 0.016236, "sigma_2": 0.008008, "covariance": 5.8e-05, "correlation": 0.4494, "has_text": true, "text_chars": 3020, "mu_floor": 0.0397, "constraint_binding": false}}
{"id": "T4_all_20210720_0679", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "DBC"], "decision_date": "2021-07-20", "context_summary": "XLK \u03c3=0.0102, DBC \u03c3=0.0109, \u03c1=0.136. Min-variance weights: XLK=0.541, DBC=0.459.", "question": "Assets: XLK, DBC\nXLK: annualized_mean_return=0.2268, daily_std=0.0102\nDBC: annualized_mean_return=0.1260, daily_std=0.0109\nMinimum required portfolio return (annualized): 0.1696\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_DBC) 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_DBC=X.XXXX", "answer": "w_XLK=0.5408, w_DBC=0.4592", "answer_numeric": 0.5408, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000119 - 0.000015) / (0.000103 + 0.000119 - 0.000030)\n  Unconstrained: w_XLK=0.5409\n  After long-only clamp: w_XLK=0.5409, w_DBC=0.4591.", "metadata": {"weights": {"XLK": 0.5408, "DBC": 0.4592}, "sigma_1": 0.010171, "sigma_2": 0.010917, "covariance": 1.5e-05, "correlation": 0.1362, "has_text": true, "text_chars": 3020, "mu_floor": 0.1696, "constraint_binding": false}}
{"id": "T4_all_20190718_0681", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "SCHP"], "decision_date": "2019-07-18", "context_summary": "BTC-USD \u03c3=0.0531, SCHP \u03c3=0.0024, \u03c1=0.095. Min-variance weights: BTC-USD=0.000, SCHP=1.000.", "question": "Assets: BTC-USD, SCHP\nBTC-USD: annualized_mean_return=1.5624, daily_std=0.0531\nSCHP: annualized_mean_return=0.1512, daily_std=0.0024\nMinimum required portfolio return (annualized): 0.1512\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_SCHP) 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_SCHP=X.XXXX", "answer": "w_BTC-USD=0.0000, w_SCHP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000006 - 0.000012) / (0.002818 + 0.000006 - 0.000024)\n  Unconstrained: w_BTC-USD=-0.0023\n  After long-only clamp: w_BTC-USD=0.0000, w_SCHP=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "SCHP": 1.0}, "sigma_1": 0.053088, "sigma_2": 0.002358, "covariance": 1.2e-05, "correlation": 0.0952, "has_text": false, "text_chars": 0, "mu_floor": 0.1512, "constraint_binding": false}}
{"id": "T4_all_20210701_0683", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "HAUZ"], "decision_date": "2021-07-01", "context_summary": "ADA-USD \u03c3=0.0864, HAUZ \u03c3=0.0074, \u03c1=0.250. Min-variance weights: ADA-USD=0.000, HAUZ=1.000.", "question": "Assets: ADA-USD, HAUZ\nADA-USD: annualized_mean_return=1.3860, daily_std=0.0864\nHAUZ: annualized_mean_return=0.2268, daily_std=0.0074\nMinimum required portfolio return (annualized): 0.2268\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_ADA-USD=0.0000, w_HAUZ=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000055 - 0.000160) / (0.007470 + 0.000055 - 0.000320)\n  Unconstrained: w_ADA-USD=-0.0146\n  After long-only clamp: w_ADA-USD=0.0000, w_HAUZ=1.0000.", "metadata": {"weights": {"ADA-USD": 0.0, "HAUZ": 1.0}, "sigma_1": 0.086428, "sigma_2": 0.007401, "covariance": 0.00016, "correlation": 0.2503, "has_text": false, "text_chars": 0, "mu_floor": 0.2268, "constraint_binding": false}}
{"id": "T4_all_20190122_0685", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "IYR"], "decision_date": "2019-01-22", "context_summary": "LINK-USD \u03c3=0.0818, IYR \u03c3=0.0122, \u03c1=-0.109. Min-variance weights: LINK-USD=0.036, IYR=0.964.", "question": "Assets: LINK-USD, IYR\nLINK-USD: annualized_mean_return=2.1420, daily_std=0.0818\nIYR: annualized_mean_return=0.2016, daily_std=0.0122\nMinimum required portfolio return (annualized): 0.2437\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_IYR) 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_IYR=X.XXXX", "answer": "w_LINK-USD=0.0364, w_IYR=0.9636", "answer_numeric": 0.0364, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000148 - -0.000108) / (0.006686 + 0.000148 - -0.000216)\n  Unconstrained: w_LINK-USD=0.0364\n  After long-only clamp: w_LINK-USD=0.0364, w_IYR=0.9636.", "metadata": {"weights": {"LINK-USD": 0.0364, "IYR": 0.9636}, "sigma_1": 0.081766, "sigma_2": 0.012185, "covariance": -0.000108, "correlation": -0.1086, "has_text": false, "text_chars": 0, "mu_floor": 0.2437, "constraint_binding": false}}
{"id": "T4_all_20210215_0687", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "SOYB"], "decision_date": "2021-02-15", "context_summary": "XRP-USD \u03c3=0.0991, SOYB \u03c3=0.0118, \u03c1=-0.044. Min-variance weights: XRP-USD=0.019, SOYB=0.981.", "question": "Assets: XRP-USD, SOYB\nXRP-USD: annualized_mean_return=2.1420, daily_std=0.0991\nSOYB: annualized_mean_return=0.6048, daily_std=0.0118\nMinimum required portfolio return (annualized): 0.6337\nMarket regime: sideways\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=0.0190, w_SOYB=0.9810", "answer_numeric": 0.019, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000139 - -0.000052) / (0.009822 + 0.000139 - -0.000104)\n  Unconstrained: w_XRP-USD=0.0189\n  After long-only clamp: w_XRP-USD=0.0189, w_SOYB=0.9811.", "metadata": {"weights": {"XRP-USD": 0.019, "SOYB": 0.981}, "sigma_1": 0.099106, "sigma_2": 0.011779, "covariance": -5.2e-05, "correlation": -0.0444, "has_text": false, "text_chars": 0, "mu_floor": 0.6337, "constraint_binding": false}}
{"id": "T4_all_20180801_0689", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "DBA"], "decision_date": "2018-08-01", "context_summary": "ADA-USD \u03c3=0.0519, DBA \u03c3=0.0084, \u03c1=-0.080. Min-variance weights: ADA-USD=0.037, DBA=0.963.", "question": "Assets: ADA-USD, DBA\nADA-USD: annualized_mean_return=-1.5120, daily_std=0.0519\nDBA: annualized_mean_return=-0.2268, daily_std=0.0084\nMinimum required portfolio return (annualized): -0.9776\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=0.0375, w_DBA=0.9625", "answer_numeric": 0.0375, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000071 - -0.000035) / (0.002690 + 0.000071 - -0.000070)\n  Unconstrained: w_ADA-USD=0.0375\n  After long-only clamp: w_ADA-USD=0.0375, w_DBA=0.9625.", "metadata": {"weights": {"ADA-USD": 0.0375, "DBA": 0.9625}, "sigma_1": 0.051869, "sigma_2": 0.008435, "covariance": -3.5e-05, "correlation": -0.0798, "has_text": false, "text_chars": 0, "mu_floor": -0.9776, "constraint_binding": false}}
{"id": "T4_all_20221021_0691", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "HAUZ"], "decision_date": "2022-10-21", "context_summary": "USMV \u03c3=0.0116, HAUZ \u03c3=0.0131, \u03c1=0.755. Min-variance weights: USMV=0.748, HAUZ=0.252.", "question": "Assets: USMV, HAUZ\nUSMV: annualized_mean_return=-0.2772, daily_std=0.0116\nHAUZ: annualized_mean_return=-0.7056, daily_std=0.0131\nMinimum required portfolio return (annualized): -0.4966\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=0.7461, w_HAUZ=0.2539", "answer_numeric": 0.7461, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000171 - 0.000114) / (0.000134 + 0.000171 - 0.000229)\n  Unconstrained: w_USMV=0.7480\n  After long-only clamp: w_USMV=0.7480, w_HAUZ=0.2520.", "metadata": {"weights": {"USMV": 0.7461, "HAUZ": 0.2539}, "sigma_1": 0.011556, "sigma_2": 0.013093, "covariance": 0.000114, "correlation": 0.7555, "has_text": true, "text_chars": 3020, "mu_floor": -0.4966, "constraint_binding": false}}
{"id": "T4_all_20170901_0694", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "XHB"], "decision_date": "2017-09-01", "context_summary": "VEA \u03c3=0.0051, XHB \u03c3=0.0076, \u03c1=0.591. Min-variance weights: VEA=0.925, XHB=0.075.", "question": "Assets: VEA, XHB\nVEA: annualized_mean_return=0.1008, daily_std=0.0051\nXHB: annualized_mean_return=0.0504, daily_std=0.0076\nMinimum required portfolio return (annualized): 0.0988\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_XHB) 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_XHB=X.XXXX", "answer": "w_VEA=0.9603, w_XHB=0.0397", "answer_numeric": 0.9603, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000058 - 0.000023) / (0.000026 + 0.000058 - 0.000046)\n  Unconstrained: w_VEA=0.9252\n  After long-only clamp: w_VEA=0.9252, w_XHB=0.0748.", "metadata": {"weights": {"VEA": 0.9603, "XHB": 0.0397}, "sigma_1": 0.005075, "sigma_2": 0.007634, "covariance": 2.3e-05, "correlation": 0.591, "has_text": true, "text_chars": 3020, "mu_floor": 0.0988, "constraint_binding": true}}
{"id": "T4_all_20220623_0696", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "BIL"], "decision_date": "2022-06-23", "context_summary": "XRP-USD \u03c3=0.0507, BIL \u03c3=0.0001, \u03c1=0.100. Min-variance weights: XRP-USD=0.000, BIL=1.000.", "question": "Assets: XRP-USD, BIL\nXRP-USD: annualized_mean_return=-2.9484, daily_std=0.0507\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.9996\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_BIL) 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_BIL=X.XXXX", "answer": "w_XRP-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) / (0.002575 + 0.000000 - 0.000001)\n  Unconstrained: w_XRP-USD=-0.0003\n  After long-only clamp: w_XRP-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XRP-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.050741, "sigma_2": 0.000144, "covariance": 1e-06, "correlation": 0.1005, "has_text": true, "text_chars": 20, "mu_floor": -0.9996, "constraint_binding": false}}
{"id": "T4_all_20200709_0698", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "BIL"], "decision_date": "2020-07-09", "context_summary": "BTC-USD \u03c3=0.0274, BIL \u03c3=0.0001, \u03c1=0.092. Min-variance weights: BTC-USD=0.000, BIL=1.000.", "question": "Assets: BTC-USD, BIL\nBTC-USD: annualized_mean_return=0.0252, daily_std=0.0274\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0079\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=0.3135, w_BIL=0.6865", "answer_numeric": 0.3135, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000751 + 0.000000 - 0.000001)\n  Unconstrained: w_BTC-USD=-0.0004\n  After long-only clamp: w_BTC-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"BTC-USD": 0.3135, "BIL": 0.6865}, "sigma_1": 0.027406, "sigma_2": 0.00011, "covariance": 0.0, "correlation": 0.092, "has_text": false, "text_chars": 0, "mu_floor": 0.0079, "constraint_binding": true}}
{"id": "T4_all_20190801_0702", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BIL"], "decision_date": "2019-08-01", "context_summary": "XLF \u03c3=0.0089, BIL \u03c3=0.0001, \u03c1=-0.225. Min-variance weights: XLF=0.003, BIL=0.997.", "question": "Assets: XLF, BIL\nXLF: annualized_mean_return=0.0756, daily_std=0.0089\nBIL: annualized_mean_return=0.0252, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0527\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=0.5456, w_BIL=0.4544", "answer_numeric": 0.5456, "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_XLF=0.0034\n  After long-only clamp: w_XLF=0.0034, w_BIL=0.9966.", "metadata": {"weights": {"XLF": 0.5456, "BIL": 0.4544}, "sigma_1": 0.008946, "sigma_2": 0.000129, "covariance": -0.0, "correlation": -0.2248, "has_text": true, "text_chars": 3020, "mu_floor": 0.0527, "constraint_binding": true}}
{"id": "T4_all_20201211_0706", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "ICSH"], "decision_date": "2020-12-11", "context_summary": "BTC-USD \u03c3=0.0309, ICSH \u03c3=0.0002, \u03c1=-0.040. Min-variance weights: BTC-USD=0.000, ICSH=1.000.", "question": "Assets: BTC-USD, ICSH\nBTC-USD: annualized_mean_return=2.1168, daily_std=0.0309\nICSH: annualized_mean_return=-0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.9743\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_ICSH) 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_ICSH=X.XXXX", "answer": "w_BTC-USD=0.4603, w_ICSH=0.5397", "answer_numeric": 0.4603, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - -0.000000) / (0.000952 + 0.000000 - -0.000000)\n  Unconstrained: w_BTC-USD=0.0003\n  After long-only clamp: w_BTC-USD=0.0003, w_ICSH=0.9997.", "metadata": {"weights": {"BTC-USD": 0.4603, "ICSH": 0.5397}, "sigma_1": 0.030862, "sigma_2": 0.0002, "covariance": -0.0, "correlation": -0.0402, "has_text": false, "text_chars": 0, "mu_floor": 0.9743, "constraint_binding": true}}
{"id": "T4_all_20170403_0708", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ICSH"], "decision_date": "2017-04-03", "context_summary": "VTI \u03c3=0.0044, ICSH \u03c3=0.0011, \u03c1=-0.032. Min-variance weights: VTI=0.062, ICSH=0.938.", "question": "Assets: VTI, ICSH\nVTI: annualized_mean_return=0.1764, daily_std=0.0044\nICSH: annualized_mean_return=0.0252, daily_std=0.0011\nMinimum required portfolio return (annualized): 0.1414\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=0.7685, w_ICSH=0.2315", "answer_numeric": 0.7685, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000001 - -0.000000) / (0.000019 + 0.000001 - -0.000000)\n  Unconstrained: w_VTI=0.0620\n  After long-only clamp: w_VTI=0.0620, w_ICSH=0.9380.", "metadata": {"weights": {"VTI": 0.7685, "ICSH": 0.2315}, "sigma_1": 0.004406, "sigma_2": 0.001069, "covariance": -0.0, "correlation": -0.0322, "has_text": true, "text_chars": 3020, "mu_floor": 0.1414, "constraint_binding": true}}
{"id": "T4_all_20160624_0710", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "MORT"], "decision_date": "2016-06-24", "context_summary": "BTC-USD \u03c3=0.0358, MORT \u03c3=0.0077, \u03c1=0.032. Min-variance weights: BTC-USD=0.038, MORT=0.962.", "question": "Assets: BTC-USD, MORT\nBTC-USD: annualized_mean_return=1.4364, daily_std=0.0358\nMORT: annualized_mean_return=0.2520, daily_std=0.0077\nMinimum required portfolio return (annualized): 1.0552\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_MORT) 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_MORT=X.XXXX", "answer": "w_BTC-USD=0.6781, w_MORT=0.3219", "answer_numeric": 0.6781, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000059 - 0.000009) / (0.001282 + 0.000059 - 0.000017)\n  Unconstrained: w_BTC-USD=0.0379\n  After long-only clamp: w_BTC-USD=0.0379, w_MORT=0.9621.", "metadata": {"weights": {"BTC-USD": 0.6781, "MORT": 0.3219}, "sigma_1": 0.035798, "sigma_2": 0.007664, "covariance": 9e-06, "correlation": 0.0315, "has_text": false, "text_chars": 0, "mu_floor": 1.0552, "constraint_binding": true}}
{"id": "T4_all_20191218_0712", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "BIL"], "decision_date": "2019-12-18", "context_summary": "XRP-USD \u03c3=0.0277, BIL \u03c3=0.0001, \u03c1=-0.002. Min-variance weights: XRP-USD=0.000, BIL=1.000.", "question": "Assets: XRP-USD, BIL\nXRP-USD: annualized_mean_return=-1.8900, daily_std=0.0277\nBIL: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0000\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_BIL) 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_BIL=X.XXXX", "answer": "w_XRP-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) / (0.000769 + 0.000000 - -0.000000)\n  Unconstrained: w_XRP-USD=0.0000\n  After long-only clamp: w_XRP-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XRP-USD": -0.0, "BIL": 1.0}, "sigma_1": 0.027729, "sigma_2": 0.000114, "covariance": -0.0, "correlation": -0.0015, "has_text": false, "text_chars": 0, "mu_floor": 0.0, "constraint_binding": true}}
{"id": "T4_all_20220607_0715", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "SCHP"], "decision_date": "2022-06-07", "context_summary": "MATIC-USD \u03c3=0.0626, SCHP \u03c3=0.0053, \u03c1=0.147. Min-variance weights: MATIC-USD=0.000, SCHP=1.000.", "question": "Assets: MATIC-USD, SCHP\nMATIC-USD: annualized_mean_return=-2.9232, daily_std=0.0626\nSCHP: annualized_mean_return=-0.2520, daily_std=0.0053\nMinimum required portfolio return (annualized): -1.2072\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_SCHP) 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_SCHP=X.XXXX", "answer": "w_MATIC-USD=0.0000, w_SCHP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000028 - 0.000049) / (0.003916 + 0.000028 - 0.000097)\n  Unconstrained: w_MATIC-USD=-0.0054\n  After long-only clamp: w_MATIC-USD=0.0000, w_SCHP=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0, "SCHP": 1.0}, "sigma_1": 0.062577, "sigma_2": 0.005269, "covariance": 4.9e-05, "correlation": 0.1473, "has_text": true, "text_chars": 20, "mu_floor": -1.2072, "constraint_binding": false}}
{"id": "T4_all_20221122_0717", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SHV"], "decision_date": "2022-11-22", "context_summary": "EFA \u03c3=0.0139, SHV \u03c3=0.0002, \u03c1=0.246. Min-variance weights: EFA=0.000, SHV=1.000.", "question": "Assets: EFA, SHV\nEFA: annualized_mean_return=-0.0504, daily_std=0.0139\nSHV: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0003\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=0.0000, 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 - 0.000001) / (0.000194 + 0.000000 - 0.000001)\n  Unconstrained: w_EFA=-0.0026\n  After long-only clamp: w_EFA=0.0000, w_SHV=1.0000.", "metadata": {"weights": {"EFA": 0.0, "SHV": 1.0}, "sigma_1": 0.013935, "sigma_2": 0.000153, "covariance": 1e-06, "correlation": 0.2457, "has_text": true, "text_chars": 3020, "mu_floor": 0.0003, "constraint_binding": false}}
{"id": "T4_all_20180907_0721", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD"], "decision_date": "2018-09-07", "context_summary": "VTI \u03c3=0.0050, BTC-USD \u03c3=0.0322, \u03c1=-0.031. Min-variance weights: VTI=0.972, BTC-USD=0.028.", "question": "Assets: VTI, BTC-USD\nVTI: annualized_mean_return=0.1512, daily_std=0.0050\nBTC-USD: annualized_mean_return=-0.0252, daily_std=0.0322\nMinimum required portfolio return (annualized): 0.1190\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_BTC-USD) 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_BTC-USD=X.XXXX", "answer": "w_VTI=0.9718, w_BTC-USD=0.0282", "answer_numeric": 0.9718, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.001039 - -0.000005) / (0.000025 + 0.001039 - -0.000010)\n  Unconstrained: w_VTI=0.9718\n  After long-only clamp: w_VTI=0.9718, w_BTC-USD=0.0282.", "metadata": {"weights": {"VTI": 0.9718, "BTC-USD": 0.0282}, "sigma_1": 0.005025, "sigma_2": 0.032235, "covariance": -5e-06, "correlation": -0.0312, "has_text": true, "text_chars": 3020, "mu_floor": 0.119, "constraint_binding": false}}
{"id": "T4_all_20151005_0723", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "VCIT"], "decision_date": "2015-10-05", "context_summary": "EFA \u03c3=0.0127, VCIT \u03c3=0.0028, \u03c1=-0.085. Min-variance weights: EFA=0.062, VCIT=0.938.", "question": "Assets: EFA, VCIT\nEFA: annualized_mean_return=-0.2520, daily_std=0.0127\nVCIT: annualized_mean_return=0.0756, daily_std=0.0028\nMinimum required portfolio return (annualized): -0.0101\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_EFA=0.0619, w_VCIT=0.9381", "answer_numeric": 0.0619, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000008 - -0.000003) / (0.000162 + 0.000008 - -0.000006)\n  Unconstrained: w_EFA=0.0621\n  After long-only clamp: w_EFA=0.0621, w_VCIT=0.9379.", "metadata": {"weights": {"EFA": 0.0619, "VCIT": 0.9381}, "sigma_1": 0.01273, "sigma_2": 0.002809, "covariance": -3e-06, "correlation": -0.085, "has_text": true, "text_chars": 3020, "mu_floor": -0.0101, "constraint_binding": false}}
{"id": "T4_all_20220902_0725", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "HYG"], "decision_date": "2022-09-02", "context_summary": "QQQ \u03c3=0.0184, HYG \u03c3=0.0076, \u03c1=0.297. Min-variance weights: QQQ=0.053, HYG=0.947.", "question": "Assets: QQQ, HYG\nQQQ: annualized_mean_return=-0.1260, daily_std=0.0184\nHYG: annualized_mean_return=0.1260, daily_std=0.0076\nMinimum required portfolio return (annualized): 0.0790\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_HYG) 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_HYG=X.XXXX", "answer": "w_QQQ=0.0539, w_HYG=0.9461", "answer_numeric": 0.0539, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000058 - 0.000041) / (0.000337 + 0.000058 - 0.000083)\n  Unconstrained: w_QQQ=0.0526\n  After long-only clamp: w_QQQ=0.0526, w_HYG=0.9474.", "metadata": {"weights": {"QQQ": 0.0539, "HYG": 0.9461}, "sigma_1": 0.018362, "sigma_2": 0.007607, "covariance": 4.1e-05, "correlation": 0.2967, "has_text": true, "text_chars": 3020, "mu_floor": 0.079, "constraint_binding": false}}
{"id": "T4_all_20190218_0727", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "MORT"], "decision_date": "2019-02-18", "context_summary": "EEM \u03c3=0.0123, MORT \u03c3=0.0103, \u03c1=0.325. Min-variance weights: EEM=0.372, MORT=0.628.", "question": "Assets: EEM, MORT\nEEM: annualized_mean_return=0.1764, daily_std=0.0123\nMORT: annualized_mean_return=0.1008, daily_std=0.0103\nMinimum required portfolio return (annualized): 0.1237\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_MORT) 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_MORT=X.XXXX", "answer": "w_EEM=0.3726, w_MORT=0.6274", "answer_numeric": 0.3726, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000107 - 0.000041) / (0.000151 + 0.000107 - 0.000083)\n  Unconstrained: w_EEM=0.3721\n  After long-only clamp: w_EEM=0.3721, w_MORT=0.6279.", "metadata": {"weights": {"EEM": 0.3726, "MORT": 0.6274}, "sigma_1": 0.012302, "sigma_2": 0.010321, "covariance": 4.1e-05, "correlation": 0.3253, "has_text": true, "text_chars": 3020, "mu_floor": 0.1237, "constraint_binding": false}}
{"id": "T4_all_20210817_0730", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ICSH"], "decision_date": "2021-08-17", "context_summary": "XLI \u03c3=0.0089, ICSH \u03c3=0.0001, \u03c1=0.289. Min-variance weights: XLI=0.000, ICSH=1.000.", "question": "Assets: XLI, ICSH\nXLI: annualized_mean_return=0.1260, daily_std=0.0089\nICSH: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0819\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=0.6500, w_ICSH=0.3500", "answer_numeric": 0.65, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000078 + 0.000000 - 0.000001)\n  Unconstrained: w_XLI=-0.0035\n  After long-only clamp: w_XLI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLI": 0.65, "ICSH": 0.35}, "sigma_1": 0.008856, "sigma_2": 0.00011, "covariance": 0.0, "correlation": 0.2892, "has_text": true, "text_chars": 3020, "mu_floor": 0.0819, "constraint_binding": true}}
{"id": "T4_all_20220701_0732", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "TLT"], "decision_date": "2022-07-01", "context_summary": "XLY \u03c3=0.0231, TLT \u03c3=0.0122, \u03c1=-0.117. Min-variance weights: XLY=0.243, TLT=0.757.", "question": "Assets: XLY, TLT\nXLY: annualized_mean_return=-1.0080, daily_std=0.0231\nTLT: annualized_mean_return=-0.3528, daily_std=0.0122\nMinimum required portfolio return (annualized): -0.4467\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=0.1433, w_TLT=0.8567", "answer_numeric": 0.1433, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000149 - -0.000033) / (0.000533 + 0.000149 - -0.000066)\n  Unconstrained: w_XLY=0.2428\n  After long-only clamp: w_XLY=0.2428, w_TLT=0.7572.", "metadata": {"weights": {"XLY": 0.1433, "TLT": 0.8567}, "sigma_1": 0.023079, "sigma_2": 0.012188, "covariance": -3.3e-05, "correlation": -0.1166, "has_text": true, "text_chars": 3020, "mu_floor": -0.4467, "constraint_binding": true}}
{"id": "T4_all_20180302_0734", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "JNK"], "decision_date": "2018-03-02", "context_summary": "VTI \u03c3=0.0096, JNK \u03c3=0.0030, \u03c1=0.303. Min-variance weights: VTI=0.005, JNK=0.995.", "question": "Assets: VTI, JNK\nVTI: annualized_mean_return=0.1008, daily_std=0.0096\nJNK: annualized_mean_return=-0.0252, daily_std=0.0030\nMinimum required portfolio return (annualized): 0.0093\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_JNK) 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_JNK=X.XXXX", "answer": "w_VTI=0.2738, w_JNK=0.7262", "answer_numeric": 0.2738, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000009 - 0.000009) / (0.000091 + 0.000009 - 0.000018)\n  Unconstrained: w_VTI=0.0052\n  After long-only clamp: w_VTI=0.0052, w_JNK=0.9948.", "metadata": {"weights": {"VTI": 0.2738, "JNK": 0.7262}, "sigma_1": 0.009564, "sigma_2": 0.003041, "covariance": 9e-06, "correlation": 0.3031, "has_text": true, "text_chars": 3020, "mu_floor": 0.0093, "constraint_binding": true}}
{"id": "T4_all_20210201_0736", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "SCHH"], "decision_date": "2021-02-01", "context_summary": "XRP-USD \u03c3=0.0969, SCHH \u03c3=0.0116, \u03c1=-0.048. Min-variance weights: XRP-USD=0.020, SCHH=0.980.", "question": "Assets: XRP-USD, SCHH\nXRP-USD: annualized_mean_return=0.6804, daily_std=0.0969\nSCHH: annualized_mean_return=0.4032, daily_std=0.0116\nMinimum required portfolio return (annualized): 0.5500\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_XRP-USD=0.5296, w_SCHH=0.4704", "answer_numeric": 0.5296, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000135 - -0.000055) / (0.009388 + 0.000135 - -0.000109)\n  Unconstrained: w_XRP-USD=0.0197\n  After long-only clamp: w_XRP-USD=0.0197, w_SCHH=0.9803.", "metadata": {"weights": {"XRP-USD": 0.5296, "SCHH": 0.4704}, "sigma_1": 0.096891, "sigma_2": 0.011629, "covariance": -5.5e-05, "correlation": -0.0484, "has_text": false, "text_chars": 0, "mu_floor": 0.55, "constraint_binding": true}}
{"id": "T4_all_20220125_0738", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SCHH"], "decision_date": "2022-01-25", "context_summary": "IVV \u03c3=0.0097, SCHH \u03c3=0.0106, \u03c1=0.752. Min-variance weights: IVV=0.677, SCHH=0.323.", "question": "Assets: IVV, SCHH\nIVV: annualized_mean_return=-0.1260, daily_std=0.0097\nSCHH: annualized_mean_return=-0.0252, daily_std=0.0106\nMinimum required portfolio return (annualized): -0.0764\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_IVV=0.5079, w_SCHH=0.4921", "answer_numeric": 0.5079, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000112 - 0.000077) / (0.000094 + 0.000112 - 0.000154)\n  Unconstrained: w_IVV=0.6771\n  After long-only clamp: w_IVV=0.6771, w_SCHH=0.3229.", "metadata": {"weights": {"IVV": 0.5079, "SCHH": 0.4921}, "sigma_1": 0.00967, "sigma_2": 0.010573, "covariance": 7.7e-05, "correlation": 0.7515, "has_text": true, "text_chars": 3020, "mu_floor": -0.0764, "constraint_binding": true}}
{"id": "T4_all_20201002_0740", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "XHB"], "decision_date": "2020-10-02", "context_summary": "ACWI \u03c3=0.0097, XHB \u03c3=0.0155, \u03c1=0.786. Min-variance weights: ACWI=1.000, XHB=0.000.", "question": "Assets: ACWI, XHB\nACWI: annualized_mean_return=0.2268, daily_std=0.0097\nXHB: annualized_mean_return=0.8568, daily_std=0.0155\nMinimum required portfolio return (annualized): 0.3532\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=0.7994, w_XHB=0.2006", "answer_numeric": 0.7994, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000239 - 0.000117) / (0.000093 + 0.000239 - 0.000235)\n  Unconstrained: w_ACWI=1.2472\n  After long-only clamp: w_ACWI=1.0000, w_XHB=0.0000.", "metadata": {"weights": {"ACWI": 0.7994, "XHB": 0.2006}, "sigma_1": 0.009664, "sigma_2": 0.015458, "covariance": 0.000117, "correlation": 0.7864, "has_text": true, "text_chars": 3020, "mu_floor": 0.3532, "constraint_binding": true}}
{"id": "T4_all_20220412_0742", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ITB"], "decision_date": "2022-04-12", "context_summary": "IVV \u03c3=0.0136, ITB \u03c3=0.0233, \u03c1=0.787. Min-variance weights: IVV=1.000, ITB=0.000.", "question": "Assets: IVV, ITB\nIVV: annualized_mean_return=-0.2268, daily_std=0.0136\nITB: annualized_mean_return=-1.1592, daily_std=0.0233\nMinimum required portfolio return (annualized): -0.2702\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=1.0000, w_ITB=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000541 - 0.000249) / (0.000185 + 0.000541 - 0.000498)\n  Unconstrained: w_IVV=1.2810\n  After long-only clamp: w_IVV=1.0000, w_ITB=0.0000.", "metadata": {"weights": {"IVV": 1.0, "ITB": 0.0}, "sigma_1": 0.013608, "sigma_2": 0.023265, "covariance": 0.000249, "correlation": 0.7873, "has_text": true, "text_chars": 3020, "mu_floor": -0.2702, "constraint_binding": false}}
{"id": "T4_all_20211101_0744", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "SCHH"], "decision_date": "2021-11-01", "context_summary": "SOL-USD \u03c3=0.0677, SCHH \u03c3=0.0084, \u03c1=-0.002. Min-variance weights: SOL-USD=0.015, SCHH=0.985.", "question": "Assets: SOL-USD, SCHH\nSOL-USD: annualized_mean_return=3.0996, daily_std=0.0677\nSCHH: annualized_mean_return=0.1008, daily_std=0.0084\nMinimum required portfolio return (annualized): 1.6529\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_SOL-USD=0.5176, w_SCHH=0.4824", "answer_numeric": 0.5176, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000070 - -0.000001) / (0.004583 + 0.000070 - -0.000003)\n  Unconstrained: w_SOL-USD=0.0154\n  After long-only clamp: w_SOL-USD=0.0154, w_SCHH=0.9846.", "metadata": {"weights": {"SOL-USD": 0.5176, "SCHH": 0.4824}, "sigma_1": 0.067698, "sigma_2": 0.008386, "covariance": -1e-06, "correlation": -0.0022, "has_text": true, "text_chars": 20, "mu_floor": 1.6529, "constraint_binding": true}}
{"id": "T4_all_20220411_0747", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "PPLT"], "decision_date": "2022-04-11", "context_summary": "DOT-USD \u03c3=0.0423, PPLT \u03c3=0.0174, \u03c1=-0.007. Min-variance weights: DOT-USD=0.146, PPLT=0.854.", "question": "Assets: DOT-USD, PPLT\nDOT-USD: annualized_mean_return=-0.3024, daily_std=0.0423\nPPLT: annualized_mean_return=0.0756, daily_std=0.0174\nMinimum required portfolio return (annualized): -0.0716\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=0.1463, w_PPLT=0.8537", "answer_numeric": 0.1463, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000303 - -0.000005) / (0.001793 + 0.000303 - -0.000011)\n  Unconstrained: w_DOT-USD=0.1465\n  After long-only clamp: w_DOT-USD=0.1465, w_PPLT=0.8535.", "metadata": {"weights": {"DOT-USD": 0.1463, "PPLT": 0.8537}, "sigma_1": 0.042348, "sigma_2": 0.017413, "covariance": -5e-06, "correlation": -0.0074, "has_text": true, "text_chars": 20, "mu_floor": -0.0716, "constraint_binding": false}}
{"id": "T4_all_20220509_0750", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "REZ"], "decision_date": "2022-05-09", "context_summary": "BNB-USD \u03c3=0.0278, REZ \u03c3=0.0135, \u03c1=-0.227. Min-variance weights: BNB-USD=0.237, REZ=0.763.", "question": "Assets: BNB-USD, REZ\nBNB-USD: annualized_mean_return=-0.3276, daily_std=0.0278\nREZ: annualized_mean_return=-0.2268, daily_std=0.0135\nMinimum required portfolio return (annualized): -0.2426\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_REZ) 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_REZ=X.XXXX", "answer": "w_BNB-USD=0.1567, w_REZ=0.8433", "answer_numeric": 0.1567, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000181 - -0.000085) / (0.000772 + 0.000181 - -0.000170)\n  Unconstrained: w_BNB-USD=0.2368\n  After long-only clamp: w_BNB-USD=0.2368, w_REZ=0.7632.", "metadata": {"weights": {"BNB-USD": 0.1567, "REZ": 0.8433}, "sigma_1": 0.027777, "sigma_2": 0.013453, "covariance": -8.5e-05, "correlation": -0.2269, "has_text": true, "text_chars": 20, "mu_floor": -0.2426, "constraint_binding": true}}
{"id": "T4_all_20190220_0752", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "DBC"], "decision_date": "2019-02-20", "context_summary": "ADA-USD \u03c3=0.0507, DBC \u03c3=0.0097, \u03c1=0.031. Min-variance weights: ADA-USD=0.030, DBC=0.970.", "question": "Assets: ADA-USD, DBC\nADA-USD: annualized_mean_return=0.8316, daily_std=0.0507\nDBC: annualized_mean_return=0.3528, daily_std=0.0097\nMinimum required portfolio return (annualized): 0.7028\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_DBC) 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_DBC=X.XXXX", "answer": "w_ADA-USD=0.7310, w_DBC=0.2690", "answer_numeric": 0.731, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000093 - 0.000015) / (0.002570 + 0.000093 - 0.000030)\n  Unconstrained: w_ADA-USD=0.0297\n  After long-only clamp: w_ADA-USD=0.0297, w_DBC=0.9703.", "metadata": {"weights": {"ADA-USD": 0.731, "DBC": 0.269}, "sigma_1": 0.050694, "sigma_2": 0.009658, "covariance": 1.5e-05, "correlation": 0.0308, "has_text": false, "text_chars": 0, "mu_floor": 0.7028, "constraint_binding": true}}
{"id": "T4_all_20180810_0754", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "INDS"], "decision_date": "2018-08-10", "context_summary": "IWM \u03c3=0.0069, INDS \u03c3=0.0079, \u03c1=0.336. Min-variance weights: IWM=0.608, INDS=0.392.", "question": "Assets: IWM, INDS\nIWM: annualized_mean_return=0.2520, daily_std=0.0069\nINDS: annualized_mean_return=0.1764, daily_std=0.0079\nMinimum required portfolio return (annualized): 0.2411\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_INDS) 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_INDS=X.XXXX", "answer": "w_IWM=0.8558, w_INDS=0.1442", "answer_numeric": 0.8558, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000063 - 0.000018) / (0.000047 + 0.000063 - 0.000037)\n  Unconstrained: w_IWM=0.6084\n  After long-only clamp: w_IWM=0.6084, w_INDS=0.3916.", "metadata": {"weights": {"IWM": 0.8558, "INDS": 0.1442}, "sigma_1": 0.006858, "sigma_2": 0.007934, "covariance": 1.8e-05, "correlation": 0.336, "has_text": true, "text_chars": 3020, "mu_floor": 0.2411, "constraint_binding": true}}
{"id": "T4_all_20201113_0757", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "TLH"], "decision_date": "2020-11-13", "context_summary": "VEA \u03c3=0.0112, TLH \u03c3=0.0062, \u03c1=0.033. Min-variance weights: VEA=0.226, TLH=0.774.", "question": "Assets: VEA, TLH\nVEA: annualized_mean_return=0.2268, daily_std=0.0112\nTLH: annualized_mean_return=-0.2520, daily_std=0.0062\nMinimum required portfolio return (annualized): -0.1667\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_TLH) 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_TLH=X.XXXX", "answer": "w_VEA=0.2272, w_TLH=0.7728", "answer_numeric": 0.2272, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000038 - 0.000002) / (0.000125 + 0.000038 - 0.000005)\n  Unconstrained: w_VEA=0.2261\n  After long-only clamp: w_VEA=0.2261, w_TLH=0.7739.", "metadata": {"weights": {"VEA": 0.2272, "TLH": 0.7728}, "sigma_1": 0.011202, "sigma_2": 0.006189, "covariance": 2e-06, "correlation": 0.0334, "has_text": true, "text_chars": 3020, "mu_floor": -0.1667, "constraint_binding": false}}
{"id": "T4_all_20171023_0759", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "IAU"], "decision_date": "2017-10-23", "context_summary": "XLP \u03c3=0.0046, IAU \u03c3=0.0066, \u03c1=0.012. Min-variance weights: XLP=0.671, IAU=0.329.", "question": "Assets: XLP, IAU\nXLP: annualized_mean_return=-0.1260, daily_std=0.0046\nIAU: annualized_mean_return=0.0252, daily_std=0.0066\nMinimum required portfolio return (annualized): -0.0808\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=0.6687, w_IAU=0.3313", "answer_numeric": 0.6687, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000043 - 0.000000) / (0.000021 + 0.000043 - 0.000001)\n  Unconstrained: w_XLP=0.6706\n  After long-only clamp: w_XLP=0.6706, w_IAU=0.3294.", "metadata": {"weights": {"XLP": 0.6687, "IAU": 0.3313}, "sigma_1": 0.004636, "sigma_2": 0.006587, "covariance": 0.0, "correlation": 0.0116, "has_text": true, "text_chars": 3020, "mu_floor": -0.0808, "constraint_binding": false}}
{"id": "T4_all_20170920_0762", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "WEAT"], "decision_date": "2017-09-20", "context_summary": "EFA \u03c3=0.0047, WEAT \u03c3=0.0186, \u03c1=-0.095. Min-variance weights: EFA=0.921, WEAT=0.079.", "question": "Assets: EFA, WEAT\nEFA: annualized_mean_return=0.2016, daily_std=0.0047\nWEAT: annualized_mean_return=0.0504, daily_std=0.0186\nMinimum required portfolio return (annualized): 0.1960\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_WEAT) 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_WEAT=X.XXXX", "answer": "w_EFA=0.9630, w_WEAT=0.0370", "answer_numeric": 0.963, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000345 - -0.000008) / (0.000022 + 0.000345 - -0.000017)\n  Unconstrained: w_EFA=0.9213\n  After long-only clamp: w_EFA=0.9213, w_WEAT=0.0787.", "metadata": {"weights": {"EFA": 0.963, "WEAT": 0.037}, "sigma_1": 0.004682, "sigma_2": 0.018579, "covariance": -8e-06, "correlation": -0.0954, "has_text": true, "text_chars": 3020, "mu_floor": 0.196, "constraint_binding": true}}
{"id": "T4_all_20200529_0764", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD"], "decision_date": "2020-05-29", "context_summary": "QQQ \u03c3=0.0233, ADA-USD \u03c3=0.0470, \u03c1=0.052. Min-variance weights: QQQ=0.815, ADA-USD=0.185.", "question": "Assets: QQQ, ADA-USD\nQQQ: annualized_mean_return=0.2772, daily_std=0.0233\nADA-USD: annualized_mean_return=3.7548, daily_std=0.0470\nMinimum required portfolio return (annualized): 2.4987\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_ADA-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_ADA-USD=X.XXXX", "answer": "w_QQQ=0.3612, w_ADA-USD=0.6388", "answer_numeric": 0.3612, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.002209 - 0.000057) / (0.000545 + 0.002209 - 0.000114)\n  Unconstrained: w_QQQ=0.8152\n  After long-only clamp: w_QQQ=0.8152, w_ADA-USD=0.1848.", "metadata": {"weights": {"QQQ": 0.3612, "ADA-USD": 0.6388}, "sigma_1": 0.023337, "sigma_2": 0.046998, "covariance": 5.7e-05, "correlation": 0.0519, "has_text": true, "text_chars": 3020, "mu_floor": 2.4987, "constraint_binding": true}}
{"id": "T4_all_20200630_0766", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ICSH"], "decision_date": "2020-06-30", "context_summary": "XLV \u03c3=0.0133, ICSH \u03c3=0.0002, \u03c1=0.219. Min-variance weights: XLV=0.000, ICSH=1.000.", "question": "Assets: XLV, ICSH\nXLV: annualized_mean_return=0.4284, daily_std=0.0133\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.2896\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=0.6328, w_ICSH=0.3672", "answer_numeric": 0.6328, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000001) / (0.000176 + 0.000000 - 0.000001)\n  Unconstrained: w_XLV=-0.0030\n  After long-only clamp: w_XLV=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLV": 0.6328, "ICSH": 0.3672}, "sigma_1": 0.013279, "sigma_2": 0.000194, "covariance": 1e-06, "correlation": 0.2194, "has_text": true, "text_chars": 3020, "mu_floor": 0.2896, "constraint_binding": true}}
{"id": "T4_all_20190114_0768", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ITB"], "decision_date": "2019-01-14", "context_summary": "BNB-USD \u03c3=0.0645, ITB \u03c3=0.0193, \u03c1=0.116. Min-variance weights: BNB-USD=0.054, ITB=0.946.", "question": "Assets: BNB-USD, ITB\nBNB-USD: annualized_mean_return=-1.1844, daily_std=0.0645\nITB: annualized_mean_return=0.2268, daily_std=0.0193\nMinimum required portfolio return (annualized): 0.2068\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=0.0142, w_ITB=0.9858", "answer_numeric": 0.0142, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000374 - 0.000145) / (0.004163 + 0.000374 - 0.000289)\n  Unconstrained: w_BNB-USD=0.0539\n  After long-only clamp: w_BNB-USD=0.0539, w_ITB=0.9461.", "metadata": {"weights": {"BNB-USD": 0.0142, "ITB": 0.9858}, "sigma_1": 0.064521, "sigma_2": 0.019332, "covariance": 0.000145, "correlation": 0.116, "has_text": false, "text_chars": 0, "mu_floor": 0.2068, "constraint_binding": true}}
{"id": "T4_all_20210104_0770", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "GLD"], "decision_date": "2021-01-04", "context_summary": "BTC-USD \u03c3=0.0361, GLD \u03c3=0.0088, \u03c1=0.345. Min-variance weights: BTC-USD=0.000, GLD=1.000.", "question": "Assets: BTC-USD, GLD\nBTC-USD: annualized_mean_return=3.7296, daily_std=0.0361\nGLD: annualized_mean_return=0.0756, daily_std=0.0088\nMinimum required portfolio return (annualized): 2.6039\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_GLD) 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_GLD=X.XXXX", "answer": "w_BTC-USD=0.6919, w_GLD=0.3081", "answer_numeric": 0.6919, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000078 - 0.000110) / (0.001301 + 0.000078 - 0.000220)\n  Unconstrained: w_BTC-USD=-0.0274\n  After long-only clamp: w_BTC-USD=0.0000, w_GLD=1.0000.", "metadata": {"weights": {"BTC-USD": 0.6919, "GLD": 0.3081}, "sigma_1": 0.036073, "sigma_2": 0.008836, "covariance": 0.00011, "correlation": 0.3446, "has_text": false, "text_chars": 0, "mu_floor": 2.6039, "constraint_binding": true}}
{"id": "T4_all_20200212_0774", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "MORT"], "decision_date": "2020-02-12", "context_summary": "ETH-USD \u03c3=0.0368, MORT \u03c3=0.0039, \u03c1=0.125. Min-variance weights: ETH-USD=0.000, MORT=1.000.", "question": "Assets: ETH-USD, MORT\nETH-USD: annualized_mean_return=2.2176, daily_std=0.0368\nMORT: annualized_mean_return=0.4032, daily_std=0.0039\nMinimum required portfolio return (annualized): 1.7609\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_MORT) 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_MORT=X.XXXX", "answer": "w_ETH-USD=0.7483, w_MORT=0.2517", "answer_numeric": 0.7483, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000015 - 0.000018) / (0.001356 + 0.000015 - 0.000036)\n  Unconstrained: w_ETH-USD=-0.0020\n  After long-only clamp: w_ETH-USD=0.0000, w_MORT=1.0000.", "metadata": {"weights": {"ETH-USD": 0.7483, "MORT": 0.2517}, "sigma_1": 0.036817, "sigma_2": 0.003902, "covariance": 1.8e-05, "correlation": 0.1247, "has_text": false, "text_chars": 0, "mu_floor": 1.7609, "constraint_binding": true}}
{"id": "T4_all_20151222_0776", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "GLD"], "decision_date": "2015-12-22", "context_summary": "XLP \u03c3=0.0092, GLD \u03c3=0.0092, \u03c1=0.230. Min-variance weights: XLP=0.500, GLD=0.500.", "question": "Assets: XLP, GLD\nXLP: annualized_mean_return=0.2268, daily_std=0.0092\nGLD: annualized_mean_return=-0.2268, daily_std=0.0092\nMinimum required portfolio return (annualized): 0.0498\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=0.6098, w_GLD=0.3902", "answer_numeric": 0.6098, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000085 - 0.000020) / (0.000085 + 0.000085 - 0.000039)\n  Unconstrained: w_XLP=0.5003\n  After long-only clamp: w_XLP=0.5003, w_GLD=0.4997.", "metadata": {"weights": {"XLP": 0.6098, "GLD": 0.3902}, "sigma_1": 0.009228, "sigma_2": 0.009233, "covariance": 2e-05, "correlation": 0.2299, "has_text": true, "text_chars": 3020, "mu_floor": 0.0498, "constraint_binding": true}}
{"id": "T4_all_20200925_0778", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "ICSH"], "decision_date": "2020-09-25", "context_summary": "ADA-USD \u03c3=0.0485, ICSH \u03c3=0.0002, \u03c1=0.040. Min-variance weights: ADA-USD=0.000, ICSH=1.000.", "question": "Assets: ADA-USD, ICSH\nADA-USD: annualized_mean_return=-2.1168, daily_std=0.0485\nICSH: annualized_mean_return=0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.0000\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 - 0.000000) / (0.002354 + 0.000000 - 0.000001)\n  Unconstrained: w_ADA-USD=-0.0002\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": 0.04852, "sigma_2": 0.000214, "covariance": 0.0, "correlation": 0.0398, "has_text": false, "text_chars": 0, "mu_floor": -0.0, "constraint_binding": true}}
{"id": "T4_all_20201016_0781", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "VNQI"], "decision_date": "2020-10-16", "context_summary": "VTI \u03c3=0.0111, VNQI \u03c3=0.0087, \u03c1=0.727. Min-variance weights: VTI=0.096, VNQI=0.904.", "question": "Assets: VTI, VNQI\nVTI: annualized_mean_return=0.3276, daily_std=0.0111\nVNQI: annualized_mean_return=0.1008, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.1208\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_VNQI) 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_VNQI=X.XXXX", "answer": "w_VTI=0.0918, w_VNQI=0.9082", "answer_numeric": 0.0918, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000075 - 0.000070) / (0.000122 + 0.000075 - 0.000139)\n  Unconstrained: w_VTI=0.0962\n  After long-only clamp: w_VTI=0.0962, w_VNQI=0.9038.", "metadata": {"weights": {"VTI": 0.0918, "VNQI": 0.9082}, "sigma_1": 0.011053, "sigma_2": 0.008676, "covariance": 7e-05, "correlation": 0.7267, "has_text": true, "text_chars": 3020, "mu_floor": 0.1208, "constraint_binding": false}}
{"id": "T4_all_20170320_0783", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "PDBC"], "decision_date": "2017-03-20", "context_summary": "XLK \u03c3=0.0043, PDBC \u03c3=0.0071, \u03c1=0.090. Min-variance weights: XLK=0.747, PDBC=0.253.", "question": "Assets: XLK, PDBC\nXLK: annualized_mean_return=0.3780, daily_std=0.0043\nPDBC: annualized_mean_return=-0.1512, daily_std=0.0071\nMinimum required portfolio return (annualized): 0.0520\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_XLK=0.7491, w_PDBC=0.2509", "answer_numeric": 0.7491, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000050 - 0.000003) / (0.000019 + 0.000050 - 0.000005)\n  Unconstrained: w_XLK=0.7471\n  After long-only clamp: w_XLK=0.7471, w_PDBC=0.2529.", "metadata": {"weights": {"XLK": 0.7491, "PDBC": 0.2509}, "sigma_1": 0.00432, "sigma_2": 0.007054, "covariance": 3e-06, "correlation": 0.09, "has_text": true, "text_chars": 3020, "mu_floor": 0.052, "constraint_binding": false}}
{"id": "T4_all_20200310_0787", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "REZ"], "decision_date": "2020-03-10", "context_summary": "ADA-USD \u03c3=0.0491, REZ \u03c3=0.0128, \u03c1=-0.022. Min-variance weights: ADA-USD=0.068, REZ=0.932.", "question": "Assets: ADA-USD, REZ\nADA-USD: annualized_mean_return=0.8568, daily_std=0.0491\nREZ: annualized_mean_return=-0.0504, daily_std=0.0128\nMinimum required portfolio return (annualized): -0.0198\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_REZ) 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_REZ=X.XXXX", "answer": "w_ADA-USD=0.0685, w_REZ=0.9315", "answer_numeric": 0.0685, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000164 - -0.000014) / (0.002411 + 0.000164 - -0.000028)\n  Unconstrained: w_ADA-USD=0.0684\n  After long-only clamp: w_ADA-USD=0.0684, w_REZ=0.9316.", "metadata": {"weights": {"ADA-USD": 0.0685, "REZ": 0.9315}, "sigma_1": 0.049107, "sigma_2": 0.012818, "covariance": -1.4e-05, "correlation": -0.022, "has_text": false, "text_chars": 0, "mu_floor": -0.0198, "constraint_binding": false}}
{"id": "T4_all_20150416_0789", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "PPLT"], "decision_date": "2015-04-16", "context_summary": "FXI \u03c3=0.0149, PPLT \u03c3=0.0117, \u03c1=-0.010. Min-variance weights: FXI=0.380, PPLT=0.620.", "question": "Assets: FXI, PPLT\nFXI: annualized_mean_return=0.7812, daily_std=0.0149\nPPLT: annualized_mean_return=-0.2520, daily_std=0.0117\nMinimum required portfolio return (annualized): -0.0139\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_FXI=0.3802, w_PPLT=0.6198", "answer_numeric": 0.3802, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000136 - -0.000002) / (0.000223 + 0.000136 - -0.000004)\n  Unconstrained: w_FXI=0.3801\n  After long-only clamp: w_FXI=0.3801, w_PPLT=0.6199.", "metadata": {"weights": {"FXI": 0.3802, "PPLT": 0.6198}, "sigma_1": 0.014928, "sigma_2": 0.011659, "covariance": -2e-06, "correlation": -0.0101, "has_text": true, "text_chars": 3020, "mu_floor": -0.0139, "constraint_binding": false}}
{"id": "T4_all_20181210_0791", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "SCHH"], "decision_date": "2018-12-10", "context_summary": "LINK-USD \u03c3=0.0723, SCHH \u03c3=0.0106, \u03c1=-0.091. Min-variance weights: LINK-USD=0.033, SCHH=0.967.", "question": "Assets: LINK-USD, SCHH\nLINK-USD: annualized_mean_return=-0.7560, daily_std=0.0723\nSCHH: annualized_mean_return=0.0252, daily_std=0.0106\nMinimum required portfolio return (annualized): -0.3150\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_LINK-USD=0.0334, w_SCHH=0.9666", "answer_numeric": 0.0334, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000113 - -0.000070) / (0.005228 + 0.000113 - -0.000140)\n  Unconstrained: w_LINK-USD=0.0334\n  After long-only clamp: w_LINK-USD=0.0334, w_SCHH=0.9666.", "metadata": {"weights": {"LINK-USD": 0.0334, "SCHH": 0.9666}, "sigma_1": 0.072306, "sigma_2": 0.010631, "covariance": -7e-05, "correlation": -0.0909, "has_text": false, "text_chars": 0, "mu_floor": -0.315, "constraint_binding": false}}
{"id": "T4_all_20180918_0793", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SOYB"], "decision_date": "2018-09-18", "context_summary": "FXI \u03c3=0.0147, SOYB \u03c3=0.0120, \u03c1=-0.031. Min-variance weights: FXI=0.405, SOYB=0.595.", "question": "Assets: FXI, SOYB\nFXI: annualized_mean_return=-0.2520, daily_std=0.0147\nSOYB: annualized_mean_return=-0.1008, daily_std=0.0120\nMinimum required portfolio return (annualized): -0.1994\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_SOYB) 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_SOYB=X.XXXX", "answer": "w_FXI=0.4048, w_SOYB=0.5952", "answer_numeric": 0.4048, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000145 - -0.000006) / (0.000216 + 0.000145 - -0.000011)\n  Unconstrained: w_FXI=0.4046\n  After long-only clamp: w_FXI=0.4046, w_SOYB=0.5954.", "metadata": {"weights": {"FXI": 0.4048, "SOYB": 0.5952}, "sigma_1": 0.014693, "sigma_2": 0.012037, "covariance": -6e-06, "correlation": -0.0314, "has_text": true, "text_chars": 3020, "mu_floor": -0.1994, "constraint_binding": false}}
{"id": "T4_all_20191127_0795", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "VEA"], "decision_date": "2019-11-27", "context_summary": "BTC-USD \u03c3=0.0283, VEA \u03c3=0.0058, \u03c1=0.342. Min-variance weights: BTC-USD=0.000, VEA=1.000.", "question": "Assets: BTC-USD, VEA\nBTC-USD: annualized_mean_return=-0.6048, daily_std=0.0283\nVEA: annualized_mean_return=0.3528, daily_std=0.0058\nMinimum required portfolio return (annualized): -0.1417\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_VEA) 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_VEA=X.XXXX", "answer": "w_BTC-USD=0.0000, w_VEA=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000034 - 0.000056) / (0.000800 + 0.000034 - 0.000112)\n  Unconstrained: w_BTC-USD=-0.0312\n  After long-only clamp: w_BTC-USD=0.0000, w_VEA=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "VEA": 1.0}, "sigma_1": 0.028292, "sigma_2": 0.005796, "covariance": 5.6e-05, "correlation": 0.3424, "has_text": false, "text_chars": 0, "mu_floor": -0.1417, "constraint_binding": false}}
{"id": "T4_all_20210210_0797", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "IWM"], "decision_date": "2021-02-10", "context_summary": "DOT-USD \u03c3=0.0998, IWM \u03c3=0.0127, \u03c1=0.215. Min-variance weights: DOT-USD=0.000, IWM=1.000.", "question": "Assets: DOT-USD, IWM\nDOT-USD: annualized_mean_return=7.3836, daily_std=0.0998\nIWM: annualized_mean_return=1.1592, daily_std=0.0127\nMinimum required portfolio return (annualized): 1.1592\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=0.0000, w_IWM=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000162 - 0.000273) / (0.009957 + 0.000162 - 0.000546)\n  Unconstrained: w_DOT-USD=-0.0115\n  After long-only clamp: w_DOT-USD=0.0000, w_IWM=1.0000.", "metadata": {"weights": {"DOT-USD": 0.0, "IWM": 1.0}, "sigma_1": 0.099782, "sigma_2": 0.012743, "covariance": 0.000273, "correlation": 0.2147, "has_text": false, "text_chars": 0, "mu_floor": 1.1592, "constraint_binding": false}}
{"id": "T4_all_20181115_0799", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "REZ"], "decision_date": "2018-11-15", "context_summary": "ETH-USD \u03c3=0.0405, REZ \u03c3=0.0108, \u03c1=-0.103. Min-variance weights: ETH-USD=0.088, REZ=0.912.", "question": "Assets: ETH-USD, REZ\nETH-USD: annualized_mean_return=-0.6552, daily_std=0.0405\nREZ: annualized_mean_return=0.0252, daily_std=0.0108\nMinimum required portfolio return (annualized): -0.3872\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_REZ) 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_REZ=X.XXXX", "answer": "w_ETH-USD=0.0876, w_REZ=0.9124", "answer_numeric": 0.0876, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000117 - -0.000045) / (0.001642 + 0.000117 - -0.000090)\n  Unconstrained: w_ETH-USD=0.0876\n  After long-only clamp: w_ETH-USD=0.0876, w_REZ=0.9124.", "metadata": {"weights": {"ETH-USD": 0.0876, "REZ": 0.9124}, "sigma_1": 0.04052, "sigma_2": 0.01081, "covariance": -4.5e-05, "correlation": -0.1032, "has_text": false, "text_chars": 0, "mu_floor": -0.3872, "constraint_binding": false}}
{"id": "T4_all_20170413_0801", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "MORT"], "decision_date": "2017-04-13", "context_summary": "XLP \u03c3=0.0039, MORT \u03c3=0.0056, \u03c1=0.321. Min-variance weights: XLP=0.751, MORT=0.249.", "question": "Assets: XLP, MORT\nXLP: annualized_mean_return=0.2520, daily_std=0.0039\nMORT: annualized_mean_return=0.3780, daily_std=0.0056\nMinimum required portfolio return (annualized): 0.2759\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_MORT) 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_MORT=X.XXXX", "answer": "w_XLP=0.7499, w_MORT=0.2501", "answer_numeric": 0.7499, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000032 - 0.000007) / (0.000015 + 0.000032 - 0.000014)\n  Unconstrained: w_XLP=0.7511\n  After long-only clamp: w_XLP=0.7511, w_MORT=0.2489.", "metadata": {"weights": {"XLP": 0.7499, "MORT": 0.2501}, "sigma_1": 0.003908, "sigma_2": 0.00564, "covariance": 7e-06, "correlation": 0.3212, "has_text": true, "text_chars": 3020, "mu_floor": 0.2759, "constraint_binding": false}}
{"id": "T4_all_20220729_0807", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "SGOV"], "decision_date": "2022-07-29", "context_summary": "XLE \u03c3=0.0248, SGOV \u03c3=0.0001, \u03c1=0.082. Min-variance weights: XLE=0.000, SGOV=1.000.", "question": "Assets: XLE, SGOV\nXLE: annualized_mean_return=0.2016, daily_std=0.0248\nSGOV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0000\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_XLE=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) / (0.000614 + 0.000000 - 0.000000)\n  Unconstrained: w_XLE=-0.0004\n  After long-only clamp: w_XLE=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"XLE": 0.0, "SGOV": 1.0}, "sigma_1": 0.024781, "sigma_2": 0.000115, "covariance": 0.0, "correlation": 0.0823, "has_text": true, "text_chars": 9046, "mu_floor": -0.0, "constraint_binding": false}}
{"id": "T4_all_20170124_0809", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "TIP"], "decision_date": "2017-01-24", "context_summary": "XLV \u03c3=0.0082, TIP \u03c3=0.0010, \u03c1=-0.239. Min-variance weights: XLV=0.042, TIP=0.958.", "question": "Assets: XLV, TIP\nXLV: annualized_mean_return=-0.0252, daily_std=0.0082\nTIP: annualized_mean_return=0.0000, daily_std=0.0010\nMinimum required portfolio return (annualized): -0.0064\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_TIP) 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_TIP=X.XXXX", "answer": "w_XLV=0.0417, w_TIP=0.9583", "answer_numeric": 0.0417, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000001 - -0.000002) / (0.000068 + 0.000001 - -0.000004)\n  Unconstrained: w_XLV=0.0416\n  After long-only clamp: w_XLV=0.0416, w_TIP=0.9584.", "metadata": {"weights": {"XLV": 0.0417, "TIP": 0.9583}, "sigma_1": 0.008225, "sigma_2": 0.001014, "covariance": -2e-06, "correlation": -0.2392, "has_text": true, "text_chars": 3020, "mu_floor": -0.0064, "constraint_binding": false}}
{"id": "T4_all_20150504_0812", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "BNO"], "decision_date": "2015-05-04", "context_summary": "BTC-USD \u03c3=0.0273, BNO \u03c3=0.0260, \u03c1=0.211. Min-variance weights: BTC-USD=0.470, BNO=0.530.", "question": "Assets: BTC-USD, BNO\nBTC-USD: annualized_mean_return=-0.4284, daily_std=0.0273\nBNO: annualized_mean_return=0.6552, daily_std=0.0260\nMinimum required portfolio return (annualized): 0.3004\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=0.3274, w_BNO=0.6726", "answer_numeric": 0.3274, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000678 - 0.000150) / (0.000745 + 0.000678 - 0.000300)\n  Unconstrained: w_BTC-USD=0.4704\n  After long-only clamp: w_BTC-USD=0.4704, w_BNO=0.5296.", "metadata": {"weights": {"BTC-USD": 0.3274, "BNO": 0.6726}, "sigma_1": 0.027289, "sigma_2": 0.026043, "covariance": 0.00015, "correlation": 0.2113, "has_text": false, "text_chars": 0, "mu_floor": 0.3004, "constraint_binding": true}}
{"id": "T4_all_20190715_0814", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "JNK"], "decision_date": "2019-07-15", "context_summary": "FXI \u03c3=0.0116, JNK \u03c3=0.0030, \u03c1=0.033. Min-variance weights: FXI=0.058, JNK=0.943.", "question": "Assets: FXI, JNK\nFXI: annualized_mean_return=-0.3024, daily_std=0.0116\nJNK: annualized_mean_return=0.0756, daily_std=0.0030\nMinimum required portfolio return (annualized): 0.0586\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_JNK) 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_JNK=X.XXXX", "answer": "w_FXI=0.0450, w_JNK=0.9550", "answer_numeric": 0.045, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000009 - 0.000001) / (0.000133 + 0.000009 - 0.000002)\n  Unconstrained: w_FXI=0.0575\n  After long-only clamp: w_FXI=0.0575, w_JNK=0.9425.", "metadata": {"weights": {"FXI": 0.045, "JNK": 0.955}, "sigma_1": 0.011551, "sigma_2": 0.003037, "covariance": 1e-06, "correlation": 0.0329, "has_text": true, "text_chars": 3020, "mu_floor": 0.0586, "constraint_binding": true}}
{"id": "T4_all_20220314_0817", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BNO"], "decision_date": "2022-03-14", "context_summary": "EFA \u03c3=0.0120, BNO \u03c3=0.0222, \u03c1=-0.367. Min-variance weights: EFA=0.710, BNO=0.290.", "question": "Assets: EFA, BNO\nEFA: annualized_mean_return=-0.5040, daily_std=0.0120\nBNO: annualized_mean_return=2.1924, daily_std=0.0222\nMinimum required portfolio return (annualized): 0.2624\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_BNO) 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_BNO=X.XXXX", "answer": "w_EFA=0.7098, w_BNO=0.2902", "answer_numeric": 0.7098, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000494 - -0.000098) / (0.000144 + 0.000494 - -0.000196)\n  Unconstrained: w_EFA=0.7099\n  After long-only clamp: w_EFA=0.7099, w_BNO=0.2901.", "metadata": {"weights": {"EFA": 0.7098, "BNO": 0.2902}, "sigma_1": 0.011993, "sigma_2": 0.022216, "covariance": -9.8e-05, "correlation": -0.3669, "has_text": true, "text_chars": 3020, "mu_floor": 0.2624, "constraint_binding": false}}
{"id": "T4_all_20180112_0819", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SHV"], "decision_date": "2018-01-12", "context_summary": "QUAL \u03c3=0.0033, SHV \u03c3=0.0001, \u03c1=-0.055. Min-variance weights: QUAL=0.003, SHV=0.998.", "question": "Assets: QUAL, SHV\nQUAL: annualized_mean_return=0.3528, daily_std=0.0033\nSHV: annualized_mean_return=0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0003\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_SHV) 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_SHV=X.XXXX", "answer": "w_QUAL=0.0009, w_SHV=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 - -0.000000) / (0.000011 + 0.000000 - -0.000000)\n  Unconstrained: w_QUAL=0.0025\n  After long-only clamp: w_QUAL=0.0025, w_SHV=0.9975.", "metadata": {"weights": {"QUAL": 0.0009, "SHV": 0.9991}, "sigma_1": 0.003317, "sigma_2": 0.0001, "covariance": -0.0, "correlation": -0.0546, "has_text": true, "text_chars": 3020, "mu_floor": 0.0003, "constraint_binding": false}}
{"id": "T4_all_20180627_0824", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "PDBC"], "decision_date": "2018-06-27", "context_summary": "XLY \u03c3=0.0082, PDBC \u03c3=0.0080, \u03c1=0.008. Min-variance weights: XLY=0.492, PDBC=0.508.", "question": "Assets: XLY, PDBC\nXLY: annualized_mean_return=0.4536, daily_std=0.0082\nPDBC: annualized_mean_return=0.0756, daily_std=0.0080\nMinimum required portfolio return (annualized): 0.3044\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_XLY=0.6053, w_PDBC=0.3947", "answer_numeric": 0.6053, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000065 - 0.000001) / (0.000067 + 0.000065 - 0.000001)\n  Unconstrained: w_XLY=0.4918\n  After long-only clamp: w_XLY=0.4918, w_PDBC=0.5082.", "metadata": {"weights": {"XLY": 0.6053, "PDBC": 0.3947}, "sigma_1": 0.008174, "sigma_2": 0.008041, "covariance": 1e-06, "correlation": 0.008, "has_text": true, "text_chars": 3020, "mu_floor": 0.3044, "constraint_binding": true}}
{"id": "T4_all_20180629_0826", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "JNK"], "decision_date": "2018-06-29", "context_summary": "XRP-USD \u03c3=0.0413, JNK \u03c3=0.0020, \u03c1=0.029. Min-variance weights: XRP-USD=0.001, JNK=0.999.", "question": "Assets: XRP-USD, JNK\nXRP-USD: annualized_mean_return=-2.5704, daily_std=0.0413\nJNK: annualized_mean_return=0.0000, daily_std=0.0020\nMinimum required portfolio return (annualized): -0.0015\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_JNK) 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_JNK=X.XXXX", "answer": "w_XRP-USD=0.0006, w_JNK=0.9994", "answer_numeric": 0.0006, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000004 - 0.000002) / (0.001704 + 0.000004 - 0.000005)\n  Unconstrained: w_XRP-USD=0.0009\n  After long-only clamp: w_XRP-USD=0.0009, w_JNK=0.9991.", "metadata": {"weights": {"XRP-USD": 0.0006, "JNK": 0.9994}, "sigma_1": 0.041283, "sigma_2": 0.001964, "covariance": 2e-06, "correlation": 0.0293, "has_text": false, "text_chars": 0, "mu_floor": -0.0015, "constraint_binding": true}}
{"id": "T4_all_20160512_0828", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BIL"], "decision_date": "2016-05-12", "context_summary": "XLK \u03c3=0.0087, BIL \u03c3=0.0002, \u03c1=0.061. Min-variance weights: XLK=0.000, BIL=1.000.", "question": "Assets: XLK, BIL\nXLK: annualized_mean_return=0.2772, daily_std=0.0087\nBIL: annualized_mean_return=0.0000, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.1771\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=0.6389, w_BIL=0.3611", "answer_numeric": 0.6389, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000076 + 0.000000 - 0.000000)\n  Unconstrained: w_XLK=-0.0008\n  After long-only clamp: w_XLK=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLK": 0.6389, "BIL": 0.3611}, "sigma_1": 0.008694, "sigma_2": 0.000173, "covariance": 0.0, "correlation": 0.0607, "has_text": true, "text_chars": 3020, "mu_floor": 0.1771, "constraint_binding": true}}
{"id": "T4_all_20181015_0830", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "PALL"], "decision_date": "2018-10-15", "context_summary": "BTC-USD \u03c3=0.0208, PALL \u03c3=0.0148, \u03c1=0.024. Min-variance weights: BTC-USD=0.333, PALL=0.667.", "question": "Assets: BTC-USD, PALL\nBTC-USD: annualized_mean_return=0.0504, daily_std=0.0208\nPALL: annualized_mean_return=0.8064, daily_std=0.0148\nMinimum required portfolio return (annualized): 0.7239\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_PALL) 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_PALL=X.XXXX", "answer": "w_BTC-USD=0.1091, w_PALL=0.8909", "answer_numeric": 0.1091, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000220 - 0.000007) / (0.000434 + 0.000220 - 0.000015)\n  Unconstrained: w_BTC-USD=0.3328\n  After long-only clamp: w_BTC-USD=0.3328, w_PALL=0.6672.", "metadata": {"weights": {"BTC-USD": 0.1091, "PALL": 0.8909}, "sigma_1": 0.020833, "sigma_2": 0.014839, "covariance": 7e-06, "correlation": 0.0241, "has_text": false, "text_chars": 0, "mu_floor": 0.7239, "constraint_binding": true}}
{"id": "T4_all_20150918_0835", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "EMB"], "decision_date": "2015-09-18", "context_summary": "BTC-USD \u03c3=0.0281, EMB \u03c3=0.0038, \u03c1=0.092. Min-variance weights: BTC-USD=0.006, EMB=0.994.", "question": "Assets: BTC-USD, EMB\nBTC-USD: annualized_mean_return=-0.3780, daily_std=0.0281\nEMB: annualized_mean_return=-0.0000, daily_std=0.0038\nMinimum required portfolio return (annualized): -0.0411\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_EMB) 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_EMB=X.XXXX", "answer": "w_BTC-USD=0.0055, w_EMB=0.9945", "answer_numeric": 0.0055, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000014 - 0.000010) / (0.000791 + 0.000014 - 0.000020)\n  Unconstrained: w_BTC-USD=0.0058\n  After long-only clamp: w_BTC-USD=0.0058, w_EMB=0.9942.", "metadata": {"weights": {"BTC-USD": 0.0055, "EMB": 0.9945}, "sigma_1": 0.028116, "sigma_2": 0.003788, "covariance": 1e-05, "correlation": 0.0917, "has_text": false, "text_chars": 0, "mu_floor": -0.0411, "constraint_binding": false}}
{"id": "T4_all_20201130_0837", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "CPER"], "decision_date": "2020-11-30", "context_summary": "XLK \u03c3=0.0181, CPER \u03c3=0.0138, \u03c1=0.277. Min-variance weights: XLK=0.320, CPER=0.680.", "question": "Assets: XLK, CPER\nXLK: annualized_mean_return=-0.0504, daily_std=0.0181\nCPER: annualized_mean_return=0.4536, daily_std=0.0138\nMinimum required portfolio return (annualized): 0.1481\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_CPER) 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_CPER=X.XXXX", "answer": "w_XLK=0.3205, w_CPER=0.6795", "answer_numeric": 0.3205, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000191 - 0.000069) / (0.000329 + 0.000191 - 0.000139)\n  Unconstrained: w_XLK=0.3201\n  After long-only clamp: w_XLK=0.3201, w_CPER=0.6799.", "metadata": {"weights": {"XLK": 0.3205, "CPER": 0.6795}, "sigma_1": 0.018126, "sigma_2": 0.013836, "covariance": 6.9e-05, "correlation": 0.2768, "has_text": true, "text_chars": 3020, "mu_floor": 0.1481, "constraint_binding": false}}
{"id": "T4_all_20210924_0839", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "TLT"], "decision_date": "2021-09-24", "context_summary": "XLY \u03c3=0.0086, TLT \u03c3=0.0085, \u03c1=-0.129. Min-variance weights: XLY=0.493, TLT=0.507.", "question": "Assets: XLY, TLT\nXLY: annualized_mean_return=0.1512, daily_std=0.0086\nTLT: annualized_mean_return=0.1260, daily_std=0.0085\nMinimum required portfolio return (annualized): 0.1350\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=0.4925, w_TLT=0.5075", "answer_numeric": 0.4925, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000071 - -0.000009) / (0.000074 + 0.000071 - -0.000019)\n  Unconstrained: w_XLY=0.4926\n  After long-only clamp: w_XLY=0.4926, w_TLT=0.5074.", "metadata": {"weights": {"XLY": 0.4925, "TLT": 0.5075}, "sigma_1": 0.008595, "sigma_2": 0.008452, "covariance": -9e-06, "correlation": -0.1288, "has_text": true, "text_chars": 3020, "mu_floor": 0.135, "constraint_binding": false}}
{"id": "T4_all_20170116_0842", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "REZ"], "decision_date": "2017-01-16", "context_summary": "QUAL \u03c3=0.0049, REZ \u03c3=0.0114, \u03c1=0.248. Min-variance weights: QUAL=0.918, REZ=0.082.", "question": "Assets: QUAL, REZ\nQUAL: annualized_mean_return=0.2268, daily_std=0.0049\nREZ: annualized_mean_return=-0.0000, daily_std=0.0114\nMinimum required portfolio return (annualized): 0.2229\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=0.9828, w_REZ=0.0172", "answer_numeric": 0.9828, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000131 - 0.000014) / (0.000024 + 0.000131 - 0.000028)\n  Unconstrained: w_QUAL=0.9177\n  After long-only clamp: w_QUAL=0.9177, w_REZ=0.0823.", "metadata": {"weights": {"QUAL": 0.9828, "REZ": 0.0172}, "sigma_1": 0.004948, "sigma_2": 0.011434, "covariance": 1.4e-05, "correlation": 0.2477, "has_text": true, "text_chars": 3020, "mu_floor": 0.2229, "constraint_binding": true}}
{"id": "T4_all_20190912_0844", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "TLH"], "decision_date": "2019-09-12", "context_summary": "MTUM \u03c3=0.0104, TLH \u03c3=0.0057, \u03c1=0.104. Min-variance weights: MTUM=0.207, TLH=0.793.", "question": "Assets: MTUM, TLH\nMTUM: annualized_mean_return=0.0756, daily_std=0.0104\nTLH: annualized_mean_return=0.2016, daily_std=0.0057\nMinimum required portfolio return (annualized): 0.1945\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_TLH) 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_TLH=X.XXXX", "answer": "w_MTUM=0.0563, w_TLH=0.9437", "answer_numeric": 0.0563, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000033 - 0.000006) / (0.000108 + 0.000033 - 0.000012)\n  Unconstrained: w_MTUM=0.2074\n  After long-only clamp: w_MTUM=0.2074, w_TLH=0.7926.", "metadata": {"weights": {"MTUM": 0.0563, "TLH": 0.9437}, "sigma_1": 0.010369, "sigma_2": 0.005718, "covariance": 6e-06, "correlation": 0.1043, "has_text": true, "text_chars": 3020, "mu_floor": 0.1945, "constraint_binding": true}}
{"id": "T4_all_20200203_0847", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "PALL"], "decision_date": "2020-02-03", "context_summary": "MATIC-USD \u03c3=0.0765, PALL \u03c3=0.0211, \u03c1=-0.208. Min-variance weights: MATIC-USD=0.112, PALL=0.888.", "question": "Assets: MATIC-USD, PALL\nMATIC-USD: annualized_mean_return=0.5544, daily_std=0.0765\nPALL: annualized_mean_return=1.6632, daily_std=0.0211\nMinimum required portfolio return (annualized): 1.4642\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_PALL) 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_PALL=X.XXXX", "answer": "w_MATIC-USD=0.1124, w_PALL=0.8876", "answer_numeric": 0.1124, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000447 - -0.000337) / (0.005855 + 0.000447 - -0.000674)\n  Unconstrained: w_MATIC-USD=0.1124\n  After long-only clamp: w_MATIC-USD=0.1124, w_PALL=0.8876.", "metadata": {"weights": {"MATIC-USD": 0.1124, "PALL": 0.8876}, "sigma_1": 0.076518, "sigma_2": 0.021146, "covariance": -0.000337, "correlation": -0.2082, "has_text": false, "text_chars": 0, "mu_floor": 1.4642, "constraint_binding": false}}
{"id": "T4_all_20180411_0849", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "XLP"], "decision_date": "2018-04-11", "context_summary": "BTC-USD \u03c3=0.0484, XLP \u03c3=0.0101, \u03c1=0.481. Min-variance weights: BTC-USD=0.000, XLP=1.000.", "question": "Assets: BTC-USD, XLP\nBTC-USD: annualized_mean_return=-0.7308, daily_std=0.0484\nXLP: annualized_mean_return=-0.2520, daily_std=0.0101\nMinimum required portfolio return (annualized): -0.2734\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_XLP) 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_XLP=X.XXXX", "answer": "w_BTC-USD=0.0000, w_XLP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000102 - 0.000235) / (0.002346 + 0.000102 - 0.000470)\n  Unconstrained: w_BTC-USD=-0.0673\n  After long-only clamp: w_BTC-USD=0.0000, w_XLP=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "XLP": 1.0}, "sigma_1": 0.048437, "sigma_2": 0.010101, "covariance": 0.000235, "correlation": 0.4805, "has_text": false, "text_chars": 0, "mu_floor": -0.2734, "constraint_binding": false}}
{"id": "T4_all_20200601_0851", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "STIP"], "decision_date": "2020-06-01", "context_summary": "MATIC-USD \u03c3=0.0640, STIP \u03c3=0.0024, \u03c1=-0.115. Min-variance weights: MATIC-USD=0.006, STIP=0.994.", "question": "Assets: MATIC-USD, STIP\nMATIC-USD: annualized_mean_return=3.0240, daily_std=0.0640\nSTIP: annualized_mean_return=0.0756, daily_std=0.0024\nMinimum required portfolio return (annualized): 0.0912\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=0.0057, w_STIP=0.9943", "answer_numeric": 0.0057, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000006 - -0.000018) / (0.004099 + 0.000006 - -0.000035)\n  Unconstrained: w_MATIC-USD=0.0056\n  After long-only clamp: w_MATIC-USD=0.0056, w_STIP=0.9944.", "metadata": {"weights": {"MATIC-USD": 0.0057, "STIP": 0.9943}, "sigma_1": 0.064026, "sigma_2": 0.002381, "covariance": -1.8e-05, "correlation": -0.115, "has_text": false, "text_chars": 0, "mu_floor": 0.0912, "constraint_binding": false}}
{"id": "T4_all_20151028_0853", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BIL"], "decision_date": "2015-10-28", "context_summary": "XLU \u03c3=0.0116, BIL \u03c3=0.0001, \u03c1=-0.255. Min-variance weights: XLU=0.003, BIL=0.997.", "question": "Assets: XLU, BIL\nXLU: annualized_mean_return=0.0504, daily_std=0.0116\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0000\nMarket regime: sideways\n\nCompute portfolio weights (w_XLU, w_BIL) 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_BIL=X.XXXX", "answer": "w_XLU=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) / (0.000135 + 0.000000 - -0.000001)\n  Unconstrained: w_XLU=0.0030\n  After long-only clamp: w_XLU=0.0030, w_BIL=0.9970.", "metadata": {"weights": {"XLU": 0.0001, "BIL": 0.9999}, "sigma_1": 0.011598, "sigma_2": 0.000132, "covariance": -0.0, "correlation": -0.2551, "has_text": true, "text_chars": 3020, "mu_floor": -0.0, "constraint_binding": false}}
{"id": "T4_all_20220531_0855", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "REZ"], "decision_date": "2022-05-31", "context_summary": "XLB \u03c3=0.0152, REZ \u03c3=0.0137, \u03c1=0.670. Min-variance weights: XLB=0.347, REZ=0.653.", "question": "Assets: XLB, REZ\nXLB: annualized_mean_return=0.2268, daily_std=0.0152\nREZ: annualized_mean_return=-0.1260, daily_std=0.0137\nMinimum required portfolio return (annualized): -0.0518\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=0.3479, w_REZ=0.6521", "answer_numeric": 0.3479, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000188 - 0.000139) / (0.000231 + 0.000188 - 0.000279)\n  Unconstrained: w_XLB=0.3469\n  After long-only clamp: w_XLB=0.3469, w_REZ=0.6531.", "metadata": {"weights": {"XLB": 0.3479, "REZ": 0.6521}, "sigma_1": 0.01519, "sigma_2": 0.013709, "covariance": 0.000139, "correlation": 0.6696, "has_text": true, "text_chars": 3020, "mu_floor": -0.0518, "constraint_binding": false}}
{"id": "T4_all_20150814_0862", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ICSH"], "decision_date": "2015-08-14", "context_summary": "VTI \u03c3=0.0068, ICSH \u03c3=0.0007, \u03c1=-0.139. Min-variance weights: VTI=0.024, ICSH=0.976.", "question": "Assets: VTI, ICSH\nVTI: annualized_mean_return=-0.0756, daily_std=0.0068\nICSH: annualized_mean_return=-0.0000, daily_std=0.0007\nMinimum required portfolio return (annualized): -0.0008\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=0.0106, w_ICSH=0.9894", "answer_numeric": 0.0106, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - -0.000001) / (0.000046 + 0.000000 - -0.000001)\n  Unconstrained: w_VTI=0.0237\n  After long-only clamp: w_VTI=0.0237, w_ICSH=0.9763.", "metadata": {"weights": {"VTI": 0.0106, "ICSH": 0.9894}, "sigma_1": 0.006763, "sigma_2": 0.00069, "covariance": -1e-06, "correlation": -0.1392, "has_text": true, "text_chars": 3020, "mu_floor": -0.0008, "constraint_binding": true}}
{"id": "T4_all_20200603_0864", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "HYG"], "decision_date": "2020-06-03", "context_summary": "QQQ \u03c3=0.0225, HYG \u03c3=0.0095, \u03c1=0.055. Min-variance weights: QQQ=0.138, HYG=0.862.", "question": "Assets: QQQ, HYG\nQQQ: annualized_mean_return=0.4284, daily_std=0.0225\nHYG: annualized_mean_return=0.1260, daily_std=0.0095\nMinimum required portfolio return (annualized): 0.2979\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_HYG) 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_HYG=X.XXXX", "answer": "w_QQQ=0.5685, w_HYG=0.4315", "answer_numeric": 0.5685, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000091 - 0.000012) / (0.000507 + 0.000091 - 0.000024)\n  Unconstrained: w_QQQ=0.1377\n  After long-only clamp: w_QQQ=0.1377, w_HYG=0.8623.", "metadata": {"weights": {"QQQ": 0.5685, "HYG": 0.4315}, "sigma_1": 0.022524, "sigma_2": 0.00954, "covariance": 1.2e-05, "correlation": 0.0553, "has_text": true, "text_chars": 3020, "mu_floor": 0.2979, "constraint_binding": true}}
{"id": "T4_all_20220606_0868", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD"], "decision_date": "2022-06-06", "context_summary": "MTUM \u03c3=0.0195, ADA-USD \u03c3=0.0677, \u03c1=0.357. Min-variance weights: MTUM=1.000, ADA-USD=0.000.", "question": "Assets: MTUM, ADA-USD\nMTUM: annualized_mean_return=-0.2016, daily_std=0.0195\nADA-USD: annualized_mean_return=-1.9656, daily_std=0.0677\nMinimum required portfolio return (annualized): -0.3726\nMarket regime: sideways\n\nCompute portfolio weights (w_MTUM, w_ADA-USD) 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_ADA-USD=X.XXXX", "answer": "w_MTUM=1.0000, w_ADA-USD=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.004577 - 0.000472) / (0.000382 + 0.004577 - 0.000944)\n  Unconstrained: w_MTUM=1.0224\n  After long-only clamp: w_MTUM=1.0000, w_ADA-USD=0.0000.", "metadata": {"weights": {"MTUM": 1.0, "ADA-USD": 0.0}, "sigma_1": 0.019536, "sigma_2": 0.067652, "covariance": 0.000472, "correlation": 0.357, "has_text": true, "text_chars": 3020, "mu_floor": -0.3726, "constraint_binding": false}}
{"id": "T4_all_20191211_0870", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ITB"], "decision_date": "2019-12-11", "context_summary": "BNB-USD \u03c3=0.0335, ITB \u03c3=0.0094, \u03c1=0.202. Min-variance weights: BNB-USD=0.022, ITB=0.978.", "question": "Assets: BNB-USD, ITB\nBNB-USD: annualized_mean_return=-0.3276, daily_std=0.0335\nITB: annualized_mean_return=0.3276, daily_std=0.0094\nMinimum required portfolio return (annualized): 0.3205\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=0.0108, w_ITB=0.9892", "answer_numeric": 0.0108, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000087 - 0.000063) / (0.001122 + 0.000087 - 0.000127)\n  Unconstrained: w_BNB-USD=0.0223\n  After long-only clamp: w_BNB-USD=0.0223, w_ITB=0.9777.", "metadata": {"weights": {"BNB-USD": 0.0108, "ITB": 0.9892}, "sigma_1": 0.033494, "sigma_2": 0.009353, "covariance": 6.3e-05, "correlation": 0.2022, "has_text": false, "text_chars": 0, "mu_floor": 0.3205, "constraint_binding": true}}
{"id": "T4_all_20181106_0873", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BIL"], "decision_date": "2018-11-06", "context_summary": "VTI \u03c3=0.0094, BIL \u03c3=0.0001, \u03c1=0.097. Min-variance weights: VTI=0.000, BIL=1.000.", "question": "Assets: VTI, BIL\nVTI: annualized_mean_return=-0.1512, daily_std=0.0094\nBIL: annualized_mean_return=0.0252, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0550\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_BIL) 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_BIL=X.XXXX", "answer": "w_VTI=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) / (0.000089 + 0.000000 - 0.000000)\n  Unconstrained: w_VTI=-0.0008\n  After long-only clamp: w_VTI=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"VTI": 0.0001, "BIL": 0.9999}, "sigma_1": 0.009423, "sigma_2": 8.3e-05, "covariance": 0.0, "correlation": 0.0971, "has_text": true, "text_chars": 3020, "mu_floor": -0.055, "constraint_binding": false}}
{"id": "T4_all_20180709_0880", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ICSH"], "decision_date": "2018-07-09", "context_summary": "XLI \u03c3=0.0086, ICSH \u03c3=0.0002, \u03c1=-0.100. Min-variance weights: XLI=0.004, ICSH=0.996.", "question": "Assets: XLI, ICSH\nXLI: annualized_mean_return=-0.0504, daily_std=0.0086\nICSH: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0252\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=-0.0000, 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) / (0.000074 + 0.000000 - -0.000000)\n  Unconstrained: w_XLI=0.0036\n  After long-only clamp: w_XLI=0.0036, w_ICSH=0.9964.", "metadata": {"weights": {"XLI": -0.0, "ICSH": 1.0}, "sigma_1": 0.008585, "sigma_2": 0.000245, "covariance": -0.0, "correlation": -0.1001, "has_text": true, "text_chars": 3020, "mu_floor": 0.0252, "constraint_binding": true}}
{"id": "T4_all_20181205_0882", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "CORN"], "decision_date": "2018-12-05", "context_summary": "ETH-USD \u03c3=0.0472, CORN \u03c3=0.0084, \u03c1=-0.038. Min-variance weights: ETH-USD=0.037, CORN=0.963.", "question": "Assets: ETH-USD, CORN\nETH-USD: annualized_mean_return=-2.7216, daily_std=0.0472\nCORN: annualized_mean_return=0.2268, daily_std=0.0084\nMinimum required portfolio return (annualized): 0.1492\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_CORN) 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_CORN=X.XXXX", "answer": "w_ETH-USD=0.0263, w_CORN=0.9737", "answer_numeric": 0.0263, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000071 - -0.000015) / (0.002225 + 0.000071 - -0.000030)\n  Unconstrained: w_ETH-USD=0.0369\n  After long-only clamp: w_ETH-USD=0.0369, w_CORN=0.9631.", "metadata": {"weights": {"ETH-USD": 0.0263, "CORN": 0.9737}, "sigma_1": 0.047167, "sigma_2": 0.008422, "covariance": -1.5e-05, "correlation": -0.0376, "has_text": false, "text_chars": 0, "mu_floor": 0.1492, "constraint_binding": true}}
{"id": "T4_all_20210112_0885", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "VNQ"], "decision_date": "2021-01-12", "context_summary": "VEA \u03c3=0.0104, VNQ \u03c3=0.0122, \u03c1=0.670. Min-variance weights: VEA=0.733, VNQ=0.267.", "question": "Assets: VEA, VNQ\nVEA: annualized_mean_return=0.6552, daily_std=0.0104\nVNQ: annualized_mean_return=0.1260, daily_std=0.0122\nMinimum required portfolio return (annualized): 0.4624\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_VNQ) 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_VNQ=X.XXXX", "answer": "w_VEA=0.7337, w_VNQ=0.2663", "answer_numeric": 0.7337, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000148 - 0.000085) / (0.000108 + 0.000148 - 0.000170)\n  Unconstrained: w_VEA=0.7328\n  After long-only clamp: w_VEA=0.7328, w_VNQ=0.2672.", "metadata": {"weights": {"VEA": 0.7337, "VNQ": 0.2663}, "sigma_1": 0.010394, "sigma_2": 0.012185, "covariance": 8.5e-05, "correlation": 0.6699, "has_text": true, "text_chars": 3020, "mu_floor": 0.4624, "constraint_binding": false}}
{"id": "T4_all_20190705_0887", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "VNQ"], "decision_date": "2019-07-05", "context_summary": "BTC-USD \u03c3=0.0507, VNQ \u03c3=0.0089, \u03c1=-0.076. Min-variance weights: BTC-USD=0.042, VNQ=0.958.", "question": "Assets: BTC-USD, VNQ\nBTC-USD: annualized_mean_return=3.0240, daily_std=0.0507\nVNQ: annualized_mean_return=0.1764, daily_std=0.0089\nMinimum required portfolio return (annualized): 0.2254\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_VNQ) 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_VNQ=X.XXXX", "answer": "w_BTC-USD=0.0418, w_VNQ=0.9582", "answer_numeric": 0.0418, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000080 - -0.000034) / (0.002573 + 0.000080 - -0.000068)\n  Unconstrained: w_BTC-USD=0.0419\n  After long-only clamp: w_BTC-USD=0.0419, w_VNQ=0.9581.", "metadata": {"weights": {"BTC-USD": 0.0418, "VNQ": 0.9582}, "sigma_1": 0.050722, "sigma_2": 0.008929, "covariance": -3.4e-05, "correlation": -0.0756, "has_text": false, "text_chars": 0, "mu_floor": 0.2254, "constraint_binding": false}}
{"id": "T4_all_20150507_0889", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ICSH"], "decision_date": "2015-05-07", "context_summary": "VTI \u03c3=0.0067, ICSH \u03c3=0.0006, \u03c1=0.107. Min-variance weights: VTI=0.000, ICSH=1.000.", "question": "Assets: VTI, ICSH\nVTI: annualized_mean_return=0.1008, daily_std=0.0067\nICSH: annualized_mean_return=-0.0252, daily_std=0.0006\nMinimum required portfolio return (annualized): -0.0245\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=0.0088, w_ICSH=0.9912", "answer_numeric": 0.0088, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000045 + 0.000000 - 0.000001)\n  Unconstrained: w_VTI=-0.0012\n  After long-only clamp: w_VTI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"VTI": 0.0088, "ICSH": 0.9912}, "sigma_1": 0.00669, "sigma_2": 0.000629, "covariance": 0.0, "correlation": 0.1067, "has_text": true, "text_chars": 3020, "mu_floor": -0.0245, "constraint_binding": false}}
{"id": "T4_all_20180214_0891", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "ICSH"], "decision_date": "2018-02-14", "context_summary": "ADA-USD \u03c3=0.1046, ICSH \u03c3=0.0004, \u03c1=-0.088. Min-variance weights: ADA-USD=0.000, ICSH=1.000.", "question": "Assets: ADA-USD, ICSH\nADA-USD: annualized_mean_return=0.8064, daily_std=0.1046\nICSH: annualized_mean_return=0.0000, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0003\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=0.0004, w_ICSH=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 - -0.000004) / (0.010942 + 0.000000 - -0.000008)\n  Unconstrained: w_ADA-USD=0.0004\n  After long-only clamp: w_ADA-USD=0.0004, w_ICSH=0.9996.", "metadata": {"weights": {"ADA-USD": 0.0004, "ICSH": 0.9996}, "sigma_1": 0.104605, "sigma_2": 0.000436, "covariance": -4e-06, "correlation": -0.088, "has_text": false, "text_chars": 0, "mu_floor": 0.0003, "constraint_binding": false}}
{"id": "T4_all_20191028_0893", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "DBB"], "decision_date": "2019-10-28", "context_summary": "^VIX \u03c3=0.0920, DBB \u03c3=0.0080, \u03c1=-0.275. Min-variance weights: ^VIX=0.030, DBB=0.970.", "question": "Assets: ^VIX, DBB\n^VIX: annualized_mean_return=-1.7136, daily_std=0.0920\nDBB: annualized_mean_return=0.1260, daily_std=0.0080\nMinimum required portfolio return (annualized): -0.9913\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_DBB) 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_DBB=X.XXXX", "answer": "w_^VIX=0.0296, w_DBB=0.9704", "answer_numeric": 0.0296, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000063 - -0.000201) / (0.008463 + 0.000063 - -0.000403)\n  Unconstrained: w_^VIX=0.0296\n  After long-only clamp: w_^VIX=0.0296, w_DBB=0.9704.", "metadata": {"weights": {"^VIX": 0.0296, "DBB": 0.9704}, "sigma_1": 0.091993, "sigma_2": 0.00795, "covariance": -0.000201, "correlation": -0.2753, "has_text": true, "text_chars": 3020, "mu_floor": -0.9913, "constraint_binding": false}}
{"id": "T4_all_20190204_0895", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "SLV"], "decision_date": "2019-02-04", "context_summary": "BNB-USD \u03c3=0.0555, SLV \u03c3=0.0086, \u03c1=0.117. Min-variance weights: BNB-USD=0.006, SLV=0.994.", "question": "Assets: BNB-USD, SLV\nBNB-USD: annualized_mean_return=0.9072, daily_std=0.0555\nSLV: annualized_mean_return=0.5040, daily_std=0.0086\nMinimum required portfolio return (annualized): 0.5063\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_SLV) 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_SLV=X.XXXX", "answer": "w_BNB-USD=0.0061, w_SLV=0.9939", "answer_numeric": 0.0061, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000075 - 0.000056) / (0.003080 + 0.000075 - 0.000112)\n  Unconstrained: w_BNB-USD=0.0061\n  After long-only clamp: w_BNB-USD=0.0061, w_SLV=0.9939.", "metadata": {"weights": {"BNB-USD": 0.0061, "SLV": 0.9939}, "sigma_1": 0.055502, "sigma_2": 0.008632, "covariance": 5.6e-05, "correlation": 0.1166, "has_text": false, "text_chars": 0, "mu_floor": 0.5063, "constraint_binding": false}}
{"id": "T4_all_20210416_0898", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "SCHH"], "decision_date": "2021-04-16", "context_summary": "XLRE \u03c3=0.0092, SCHH \u03c3=0.0092, \u03c1=0.985. Min-variance weights: XLRE=0.467, SCHH=0.533.", "question": "Assets: XLRE, SCHH\nXLRE: annualized_mean_return=0.6048, daily_std=0.0092\nSCHH: annualized_mean_return=0.5796, daily_std=0.0092\nMinimum required portfolio return (annualized): 0.5979\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_XLRE=0.7262, w_SCHH=0.2738", "answer_numeric": 0.7262, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000084 - 0.000083) / (0.000085 + 0.000084 - 0.000166)\n  Unconstrained: w_XLRE=0.4674\n  After long-only clamp: w_XLRE=0.4674, w_SCHH=0.5326.", "metadata": {"weights": {"XLRE": 0.7262, "SCHH": 0.2738}, "sigma_1": 0.009195, "sigma_2": 0.009186, "covariance": 8.3e-05, "correlation": 0.985, "has_text": true, "text_chars": 3020, "mu_floor": 0.5979, "constraint_binding": true}}
{"id": "T4_all_20191216_0900", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ICSH"], "decision_date": "2019-12-16", "context_summary": "IVV \u03c3=0.0061, ICSH \u03c3=0.0002, \u03c1=0.172. Min-variance weights: IVV=0.000, ICSH=1.000.", "question": "Assets: IVV, ICSH\nIVV: annualized_mean_return=0.2520, daily_std=0.0061\nICSH: annualized_mean_return=0.0252, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0944\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=0.3051, w_ICSH=0.6949", "answer_numeric": 0.3051, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.000038 + 0.000000 - 0.000000)\n  Unconstrained: w_IVV=-0.0047\n  After long-only clamp: w_IVV=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"IVV": 0.3051, "ICSH": 0.6949}, "sigma_1": 0.006148, "sigma_2": 0.000205, "covariance": 0.0, "correlation": 0.1723, "has_text": true, "text_chars": 3020, "mu_floor": 0.0944, "constraint_binding": true}}
{"id": "T4_all_20220524_0903", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "XHB"], "decision_date": "2022-05-24", "context_summary": "XLE \u03c3=0.0214, XHB \u03c3=0.0222, \u03c1=0.044. Min-variance weights: XLE=0.518, XHB=0.482.", "question": "Assets: XLE, XHB\nXLE: annualized_mean_return=1.0332, daily_std=0.0214\nXHB: annualized_mean_return=-0.4788, daily_std=0.0222\nMinimum required portfolio return (annualized): 0.1518\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_XHB) 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_XHB=X.XXXX", "answer": "w_XLE=0.5184, w_XHB=0.4816", "answer_numeric": 0.5184, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000491 - 0.000021) / (0.000458 + 0.000491 - 0.000042)\n  Unconstrained: w_XLE=0.5183\n  After long-only clamp: w_XLE=0.5183, w_XHB=0.4817.", "metadata": {"weights": {"XLE": 0.5184, "XHB": 0.4816}, "sigma_1": 0.021394, "sigma_2": 0.022159, "covariance": 2.1e-05, "correlation": 0.0442, "has_text": true, "text_chars": 3020, "mu_floor": 0.1518, "constraint_binding": false}}
{"id": "T4_all_20180202_0905", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "EMB"], "decision_date": "2018-02-02", "context_summary": "ETH-USD \u03c3=0.0711, EMB \u03c3=0.0019, \u03c1=0.183. Min-variance weights: ETH-USD=0.000, EMB=1.000.", "question": "Assets: ETH-USD, EMB\nETH-USD: annualized_mean_return=3.8304, daily_std=0.0711\nEMB: annualized_mean_return=0.0756, daily_std=0.0019\nMinimum required portfolio return (annualized): 0.0756\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_EMB) 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_EMB=X.XXXX", "answer": "w_ETH-USD=0.0000, w_EMB=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000004 - 0.000025) / (0.005051 + 0.000004 - 0.000051)\n  Unconstrained: w_ETH-USD=-0.0043\n  After long-only clamp: w_ETH-USD=0.0000, w_EMB=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "EMB": 1.0}, "sigma_1": 0.071071, "sigma_2": 0.001948, "covariance": 2.5e-05, "correlation": 0.1832, "has_text": false, "text_chars": 0, "mu_floor": 0.0756, "constraint_binding": false}}
{"id": "T4_all_20170517_0907", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "PDBC"], "decision_date": "2017-05-17", "context_summary": "EEM \u03c3=0.0081, PDBC \u03c3=0.0076, \u03c1=0.030. Min-variance weights: EEM=0.462, PDBC=0.538.", "question": "Assets: EEM, PDBC\nEEM: annualized_mean_return=0.3528, daily_std=0.0081\nPDBC: annualized_mean_return=-0.2520, daily_std=0.0076\nMinimum required portfolio return (annualized): -0.0325\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_EEM=0.4620, w_PDBC=0.5380", "answer_numeric": 0.462, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000057 - 0.000002) / (0.000066 + 0.000057 - 0.000004)\n  Unconstrained: w_EEM=0.4621\n  After long-only clamp: w_EEM=0.4621, w_PDBC=0.5379.", "metadata": {"weights": {"EEM": 0.462, "PDBC": 0.538}, "sigma_1": 0.008141, "sigma_2": 0.007563, "covariance": 2e-06, "correlation": 0.0305, "has_text": true, "text_chars": 3020, "mu_floor": -0.0325, "constraint_binding": false}}
{"id": "T4_all_20180706_0909", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SCHP"], "decision_date": "2018-07-06", "context_summary": "IVV \u03c3=0.0063, SCHP \u03c3=0.0018, \u03c1=-0.306. Min-variance weights: IVV=0.138, SCHP=0.862.", "question": "Assets: IVV, SCHP\nIVV: annualized_mean_return=0.1512, daily_std=0.0063\nSCHP: annualized_mean_return=0.0504, daily_std=0.0018\nMinimum required portfolio return (annualized): 0.0578\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_SCHP) 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_SCHP=X.XXXX", "answer": "w_IVV=0.1447, w_SCHP=0.8553", "answer_numeric": 0.1447, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000003 - -0.000004) / (0.000040 + 0.000003 - -0.000007)\n  Unconstrained: w_IVV=0.1380\n  After long-only clamp: w_IVV=0.1380, w_SCHP=0.8620.", "metadata": {"weights": {"IVV": 0.1447, "SCHP": 0.8553}, "sigma_1": 0.006288, "sigma_2": 0.001835, "covariance": -4e-06, "correlation": -0.3059, "has_text": true, "text_chars": 3020, "mu_floor": 0.0578, "constraint_binding": false}}
{"id": "T4_all_20221209_0911", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "IAU"], "decision_date": "2022-12-09", "context_summary": "XRP-USD \u03c3=0.0492, IAU \u03c3=0.0101, \u03c1=0.150. Min-variance weights: XRP-USD=0.012, IAU=0.988.", "question": "Assets: XRP-USD, IAU\nXRP-USD: annualized_mean_return=-0.9576, daily_std=0.0492\nIAU: annualized_mean_return=0.2772, daily_std=0.0101\nMinimum required portfolio return (annualized): -0.4204\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_IAU) 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_IAU=X.XXXX", "answer": "w_XRP-USD=0.0118, w_IAU=0.9882", "answer_numeric": 0.0118, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000103 - 0.000075) / (0.002419 + 0.000103 - 0.000150)\n  Unconstrained: w_XRP-USD=0.0118\n  After long-only clamp: w_XRP-USD=0.0118, w_IAU=0.9882.", "metadata": {"weights": {"XRP-USD": 0.0118, "IAU": 0.9882}, "sigma_1": 0.049184, "sigma_2": 0.010145, "covariance": 7.5e-05, "correlation": 0.1503, "has_text": true, "text_chars": 20, "mu_floor": -0.4204, "constraint_binding": false}}
{"id": "T4_all_20210128_0913", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "ITB"], "decision_date": "2021-01-28", "context_summary": "ADA-USD \u03c3=0.0766, ITB \u03c3=0.0194, \u03c1=0.176. Min-variance weights: ADA-USD=0.020, ITB=0.980.", "question": "Assets: ADA-USD, ITB\nADA-USD: annualized_mean_return=3.2256, daily_std=0.0766\nITB: annualized_mean_return=0.6552, daily_std=0.0194\nMinimum required portfolio return (annualized): 0.6952\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_ITB) 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_ITB=X.XXXX", "answer": "w_ADA-USD=0.0199, w_ITB=0.9801", "answer_numeric": 0.0199, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000375 - 0.000261) / (0.005862 + 0.000375 - 0.000522)\n  Unconstrained: w_ADA-USD=0.0199\n  After long-only clamp: w_ADA-USD=0.0199, w_ITB=0.9801.", "metadata": {"weights": {"ADA-USD": 0.0199, "ITB": 0.9801}, "sigma_1": 0.076566, "sigma_2": 0.019357, "covariance": 0.000261, "correlation": 0.1761, "has_text": false, "text_chars": 0, "mu_floor": 0.6952, "constraint_binding": false}}
{"id": "T4_all_20210813_0915", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LQD"], "decision_date": "2021-08-13", "context_summary": "FXI \u03c3=0.0156, LQD \u03c3=0.0032, \u03c1=-0.193. Min-variance weights: FXI=0.073, LQD=0.926.", "question": "Assets: FXI, LQD\nFXI: annualized_mean_return=-0.3528, daily_std=0.0156\nLQD: annualized_mean_return=0.1260, daily_std=0.0032\nMinimum required portfolio return (annualized): 0.0424\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_LQD) 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_LQD=X.XXXX", "answer": "w_FXI=0.0744, w_LQD=0.9256", "answer_numeric": 0.0744, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000010 - -0.000010) / (0.000244 + 0.000010 - -0.000019)\n  Unconstrained: w_FXI=0.0735\n  After long-only clamp: w_FXI=0.0735, w_LQD=0.9265.", "metadata": {"weights": {"FXI": 0.0744, "LQD": 0.9256}, "sigma_1": 0.015626, "sigma_2": 0.003228, "covariance": -1e-05, "correlation": -0.1927, "has_text": true, "text_chars": 3020, "mu_floor": 0.0424, "constraint_binding": false}}
{"id": "T4_all_20220715_0917", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "SCHP"], "decision_date": "2022-07-15", "context_summary": "MATIC-USD \u03c3=0.0738, SCHP \u03c3=0.0053, \u03c1=0.151. Min-variance weights: MATIC-USD=0.000, SCHP=1.000.", "question": "Assets: MATIC-USD, SCHP\nMATIC-USD: annualized_mean_return=0.5040, daily_std=0.0738\nSCHP: annualized_mean_return=-0.1260, daily_std=0.0053\nMinimum required portfolio return (annualized): -0.1260\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_SCHP) 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_SCHP=X.XXXX", "answer": "w_MATIC-USD=0.0000, w_SCHP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000029 - 0.000059) / (0.005442 + 0.000029 - 0.000119)\n  Unconstrained: w_MATIC-USD=-0.0058\n  After long-only clamp: w_MATIC-USD=0.0000, w_SCHP=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0, "SCHP": 1.0}, "sigma_1": 0.073769, "sigma_2": 0.005339, "covariance": 5.9e-05, "correlation": 0.1509, "has_text": true, "text_chars": 20, "mu_floor": -0.126, "constraint_binding": false}}
{"id": "T4_all_20190524_0919", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "LINK-USD"], "decision_date": "2019-05-24", "context_summary": "EEM \u03c3=0.0107, LINK-USD \u03c3=0.0560, \u03c1=0.050. Min-variance weights: EEM=0.974, LINK-USD=0.026.", "question": "Assets: EEM, LINK-USD\nEEM: annualized_mean_return=-0.3024, daily_std=0.0107\nLINK-USD: annualized_mean_return=4.6368, daily_std=0.0560\nMinimum required portfolio return (annualized): -0.2104\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=0.9735, w_LINK-USD=0.0265", "answer_numeric": 0.9735, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.003133 - 0.000030) / (0.000115 + 0.003133 - 0.000060)\n  Unconstrained: w_EEM=0.9735\n  After long-only clamp: w_EEM=0.9735, w_LINK-USD=0.0265.", "metadata": {"weights": {"EEM": 0.9735, "LINK-USD": 0.0265}, "sigma_1": 0.010703, "sigma_2": 0.055975, "covariance": 3e-05, "correlation": 0.0503, "has_text": true, "text_chars": 3020, "mu_floor": -0.2104, "constraint_binding": false}}
{"id": "T4_all_20180702_0921", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "STIP"], "decision_date": "2018-07-02", "context_summary": "EFA \u03c3=0.0063, STIP \u03c3=0.0007, \u03c1=0.062. Min-variance weights: EFA=0.005, STIP=0.995.", "question": "Assets: EFA, STIP\nEFA: annualized_mean_return=-0.1008, daily_std=0.0063\nSTIP: annualized_mean_return=0.0252, daily_std=0.0007\nMinimum required portfolio return (annualized): -0.0500\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_STIP) 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_STIP=X.XXXX", "answer": "w_EFA=0.0118, w_STIP=0.9882", "answer_numeric": 0.0118, "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_EFA=0.0051\n  After long-only clamp: w_EFA=0.0051, w_STIP=0.9949.", "metadata": {"weights": {"EFA": 0.0118, "STIP": 0.9882}, "sigma_1": 0.006321, "sigma_2": 0.00069, "covariance": 0.0, "correlation": 0.0622, "has_text": true, "text_chars": 3020, "mu_floor": -0.05, "constraint_binding": false}}
{"id": "T4_all_20180913_0926", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "EMB"], "decision_date": "2018-09-13", "context_summary": "QQQ \u03c3=0.0083, EMB \u03c3=0.0036, \u03c1=0.025. Min-variance weights: QQQ=0.156, EMB=0.844.", "question": "Assets: QQQ, EMB\nQQQ: annualized_mean_return=0.1512, daily_std=0.0083\nEMB: annualized_mean_return=0.0000, daily_std=0.0036\nMinimum required portfolio return (annualized): 0.0922\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=0.6098, w_EMB=0.3902", "answer_numeric": 0.6098, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000013 - 0.000001) / (0.000068 + 0.000013 - 0.000002)\n  Unconstrained: w_QQQ=0.1560\n  After long-only clamp: w_QQQ=0.1560, w_EMB=0.8440.", "metadata": {"weights": {"QQQ": 0.6098, "EMB": 0.3902}, "sigma_1": 0.008267, "sigma_2": 0.00364, "covariance": 1e-06, "correlation": 0.0252, "has_text": true, "text_chars": 3020, "mu_floor": 0.0922, "constraint_binding": true}}
{"id": "T4_all_20181010_0928", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "CPER"], "decision_date": "2018-10-10", "context_summary": "VEA \u03c3=0.0065, CPER \u03c3=0.0140, \u03c1=0.252. Min-variance weights: VEA=0.902, CPER=0.098.", "question": "Assets: VEA, CPER\nVEA: annualized_mean_return=-0.1260, daily_std=0.0065\nCPER: annualized_mean_return=-0.0252, daily_std=0.0140\nMinimum required portfolio return (annualized): -0.0672\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_CPER) 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_CPER=X.XXXX", "answer": "w_VEA=0.4167, w_CPER=0.5833", "answer_numeric": 0.4167, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000196 - 0.000023) / (0.000042 + 0.000196 - 0.000046)\n  Unconstrained: w_VEA=0.9016\n  After long-only clamp: w_VEA=0.9016, w_CPER=0.0984.", "metadata": {"weights": {"VEA": 0.4167, "CPER": 0.5833}, "sigma_1": 0.006461, "sigma_2": 0.014005, "covariance": 2.3e-05, "correlation": 0.2522, "has_text": true, "text_chars": 3020, "mu_floor": -0.0672, "constraint_binding": true}}
{"id": "T4_all_20160114_0930", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SOYB"], "decision_date": "2016-01-14", "context_summary": "VTI \u03c3=0.0102, SOYB \u03c3=0.0081, \u03c1=-0.043. Min-variance weights: VTI=0.392, SOYB=0.608.", "question": "Assets: VTI, SOYB\nVTI: annualized_mean_return=-0.3276, daily_std=0.0102\nSOYB: annualized_mean_return=-0.1260, daily_std=0.0081\nMinimum required portfolio return (annualized): -0.1524\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_SOYB) 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_SOYB=X.XXXX", "answer": "w_VTI=0.1310, w_SOYB=0.8690", "answer_numeric": 0.131, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000066 - -0.000004) / (0.000105 + 0.000066 - -0.000007)\n  Unconstrained: w_VTI=0.3919\n  After long-only clamp: w_VTI=0.3919, w_SOYB=0.6081.", "metadata": {"weights": {"VTI": 0.131, "SOYB": 0.869}, "sigma_1": 0.010231, "sigma_2": 0.008136, "covariance": -4e-06, "correlation": -0.043, "has_text": true, "text_chars": 3020, "mu_floor": -0.1524, "constraint_binding": true}}
{"id": "T4_all_20211012_0932", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "DBB"], "decision_date": "2021-10-12", "context_summary": "DOT-USD \u03c3=0.0724, DBB \u03c3=0.0104, \u03c1=-0.039. Min-variance weights: DOT-USD=0.026, DBB=0.974.", "question": "Assets: DOT-USD, DBB\nDOT-USD: annualized_mean_return=2.7720, daily_std=0.0724\nDBB: annualized_mean_return=0.4536, daily_std=0.0104\nMinimum required portfolio return (annualized): 1.4877\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=0.4460, w_DBB=0.5540", "answer_numeric": 0.446, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000109 - -0.000030) / (0.005246 + 0.000109 - -0.000060)\n  Unconstrained: w_DOT-USD=0.0256\n  After long-only clamp: w_DOT-USD=0.0256, w_DBB=0.9744.", "metadata": {"weights": {"DOT-USD": 0.446, "DBB": 0.554}, "sigma_1": 0.072428, "sigma_2": 0.010434, "covariance": -3e-05, "correlation": -0.0395, "has_text": false, "text_chars": 0, "mu_floor": 1.4877, "constraint_binding": true}}
{"id": "T4_all_20210118_0934", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "EMB"], "decision_date": "2021-01-18", "context_summary": "ETH-USD \u03c3=0.0529, EMB \u03c3=0.0039, \u03c1=0.057. Min-variance weights: ETH-USD=0.001, EMB=0.999.", "question": "Assets: ETH-USD, EMB\nETH-USD: annualized_mean_return=3.9816, daily_std=0.0529\nEMB: annualized_mean_return=0.1260, daily_std=0.0039\nMinimum required portfolio return (annualized): 2.0957\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_EMB) 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_EMB=X.XXXX", "answer": "w_ETH-USD=0.5109, w_EMB=0.4891", "answer_numeric": 0.5109, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000015 - 0.000012) / (0.002802 + 0.000015 - 0.000024)\n  Unconstrained: w_ETH-USD=0.0012\n  After long-only clamp: w_ETH-USD=0.0012, w_EMB=0.9988.", "metadata": {"weights": {"ETH-USD": 0.5109, "EMB": 0.4891}, "sigma_1": 0.052935, "sigma_2": 0.003901, "covariance": 1.2e-05, "correlation": 0.0571, "has_text": false, "text_chars": 0, "mu_floor": 2.0957, "constraint_binding": true}}
{"id": "T4_all_20210223_0936", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "IYR"], "decision_date": "2021-02-23", "context_summary": "ADA-USD \u03c3=0.0846, IYR \u03c3=0.0096, \u03c1=-0.168. Min-variance weights: ADA-USD=0.030, IYR=0.970.", "question": "Assets: ADA-USD, IYR\nADA-USD: annualized_mean_return=8.7192, daily_std=0.0846\nIYR: annualized_mean_return=0.2520, daily_std=0.0096\nMinimum required portfolio return (annualized): 4.8296\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_IYR) 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_IYR=X.XXXX", "answer": "w_ADA-USD=0.5406, w_IYR=0.4594", "answer_numeric": 0.5406, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000093 - -0.000137) / (0.007166 + 0.000093 - -0.000274)\n  Unconstrained: w_ADA-USD=0.0305\n  After long-only clamp: w_ADA-USD=0.0305, w_IYR=0.9695.", "metadata": {"weights": {"ADA-USD": 0.5406, "IYR": 0.4594}, "sigma_1": 0.084649, "sigma_2": 0.009633, "covariance": -0.000137, "correlation": -0.1681, "has_text": false, "text_chars": 0, "mu_floor": 4.8296, "constraint_binding": true}}
{"id": "T4_all_20170203_0938", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "TLH"], "decision_date": "2017-02-03", "context_summary": "VTI \u03c3=0.0053, TLH \u03c3=0.0042, \u03c1=-0.202. Min-variance weights: VTI=0.409, TLH=0.591.", "question": "Assets: VTI, TLH\nVTI: annualized_mean_return=0.4284, daily_std=0.0053\nTLH: annualized_mean_return=-0.1260, daily_std=0.0042\nMinimum required portfolio return (annualized): 0.3604\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_TLH) 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_TLH=X.XXXX", "answer": "w_VTI=0.8773, w_TLH=0.1227", "answer_numeric": 0.8773, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000018 - -0.000005) / (0.000028 + 0.000018 - -0.000009)\n  Unconstrained: w_VTI=0.4093\n  After long-only clamp: w_VTI=0.4093, w_TLH=0.5907.", "metadata": {"weights": {"VTI": 0.8773, "TLH": 0.1227}, "sigma_1": 0.005292, "sigma_2": 0.004244, "covariance": -5e-06, "correlation": -0.2023, "has_text": true, "text_chars": 3020, "mu_floor": 0.3604, "constraint_binding": true}}
{"id": "T4_all_20190226_0940", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "IVV"], "decision_date": "2019-02-26", "context_summary": "XRP-USD \u03c3=0.0369, IVV \u03c3=0.0120, \u03c1=0.100. Min-variance weights: XRP-USD=0.070, IVV=0.929.", "question": "Assets: XRP-USD, IVV\nXRP-USD: annualized_mean_return=0.0000, daily_std=0.0369\nIVV: annualized_mean_return=0.0756, daily_std=0.0120\nMinimum required portfolio return (annualized): 0.0725\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=0.0410, w_IVV=0.9590", "answer_numeric": 0.041, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000144 - 0.000044) / (0.001363 + 0.000144 - 0.000088)\n  Unconstrained: w_XRP-USD=0.0705\n  After long-only clamp: w_XRP-USD=0.0705, w_IVV=0.9295.", "metadata": {"weights": {"XRP-USD": 0.041, "IVV": 0.959}, "sigma_1": 0.036913, "sigma_2": 0.012004, "covariance": 4.4e-05, "correlation": 0.0995, "has_text": false, "text_chars": 0, "mu_floor": 0.0725, "constraint_binding": true}}
{"id": "T4_all_20201026_0942", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD"], "decision_date": "2020-10-26", "context_summary": "ACWI \u03c3=0.0097, DOT-USD \u03c3=0.0581, \u03c1=-0.112. Min-variance weights: ACWI=0.956, DOT-USD=0.044.", "question": "Assets: ACWI, DOT-USD\nACWI: annualized_mean_return=0.2268, daily_std=0.0097\nDOT-USD: annualized_mean_return=-0.9828, daily_std=0.0581\nMinimum required portfolio return (annualized): 0.2077\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_DOT-USD) 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_DOT-USD=X.XXXX", "answer": "w_ACWI=0.9842, w_DOT-USD=0.0158", "answer_numeric": 0.9842, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.003371 - -0.000063) / (0.000095 + 0.003371 - -0.000127)\n  Unconstrained: w_ACWI=0.9560\n  After long-only clamp: w_ACWI=0.9560, w_DOT-USD=0.0440.", "metadata": {"weights": {"ACWI": 0.9842, "DOT-USD": 0.0158}, "sigma_1": 0.009729, "sigma_2": 0.058059, "covariance": -6.3e-05, "correlation": -0.1121, "has_text": true, "text_chars": 3020, "mu_floor": 0.2077, "constraint_binding": true}}
{"id": "T4_all_20200701_0944", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SOL-USD"], "decision_date": "2020-07-01", "context_summary": "FXI \u03c3=0.0164, SOL-USD \u03c3=0.0531, \u03c1=0.077. Min-variance weights: FXI=0.932, SOL-USD=0.068.", "question": "Assets: FXI, SOL-USD\nFXI: annualized_mean_return=0.3528, daily_std=0.0164\nSOL-USD: annualized_mean_return=1.0584, daily_std=0.0531\nMinimum required portfolio return (annualized): 0.6542\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_SOL-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_SOL-USD=X.XXXX", "answer": "w_FXI=0.5728, w_SOL-USD=0.4272", "answer_numeric": 0.5728, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.002823 - 0.000067) / (0.000267 + 0.002823 - 0.000134)\n  Unconstrained: w_FXI=0.9322\n  After long-only clamp: w_FXI=0.9322, w_SOL-USD=0.0678.", "metadata": {"weights": {"FXI": 0.5728, "SOL-USD": 0.4272}, "sigma_1": 0.016355, "sigma_2": 0.053135, "covariance": 6.7e-05, "correlation": 0.077, "has_text": true, "text_chars": 3020, "mu_floor": 0.6542, "constraint_binding": true}}
{"id": "T4_all_20220203_0948", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SCHP"], "decision_date": "2022-02-03", "context_summary": "EEM \u03c3=0.0110, SCHP \u03c3=0.0034, \u03c1=0.140. Min-variance weights: EEM=0.053, SCHP=0.947.", "question": "Assets: EEM, SCHP\nEEM: annualized_mean_return=-0.1008, daily_std=0.0110\nSCHP: annualized_mean_return=-0.1260, daily_std=0.0034\nMinimum required portfolio return (annualized): -0.1106\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_SCHP) 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_SCHP=X.XXXX", "answer": "w_EEM=0.6111, w_SCHP=0.3889", "answer_numeric": 0.6111, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000012 - 0.000005) / (0.000120 + 0.000012 - 0.000011)\n  Unconstrained: w_EEM=0.0532\n  After long-only clamp: w_EEM=0.0532, w_SCHP=0.9468.", "metadata": {"weights": {"EEM": 0.6111, "SCHP": 0.3889}, "sigma_1": 0.010959, "sigma_2": 0.003425, "covariance": 5e-06, "correlation": 0.1404, "has_text": true, "text_chars": 3020, "mu_floor": -0.1106, "constraint_binding": true}}
{"id": "T4_all_20220426_0950", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "BIL"], "decision_date": "2022-04-26", "context_summary": "ETH-USD \u03c3=0.0345, BIL \u03c3=0.0001, \u03c1=0.030. Min-variance weights: ETH-USD=0.000, BIL=1.000.", "question": "Assets: ETH-USD, BIL\nETH-USD: annualized_mean_return=0.7560, daily_std=0.0345\nBIL: annualized_mean_return=-0.0000, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.5273\nMarket regime: sideways\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=0.6975, w_BIL=0.3025", "answer_numeric": 0.6975, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000000 - 0.000000) / (0.001193 + 0.000000 - 0.000000)\n  Unconstrained: w_ETH-USD=-0.0001\n  After long-only clamp: w_ETH-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"ETH-USD": 0.6975, "BIL": 0.3025}, "sigma_1": 0.034543, "sigma_2": 0.000109, "covariance": 0.0, "correlation": 0.03, "has_text": true, "text_chars": 20, "mu_floor": 0.5273, "constraint_binding": true}}
{"id": "T4_all_20220923_0952", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "VNQI"], "decision_date": "2022-09-23", "context_summary": "ADA-USD \u03c3=0.0384, VNQI \u03c3=0.0106, \u03c1=0.105. Min-variance weights: ADA-USD=0.047, VNQI=0.953.", "question": "Assets: ADA-USD, VNQI\nADA-USD: annualized_mean_return=-0.2772, daily_std=0.0384\nVNQI: annualized_mean_return=-0.4536, daily_std=0.0106\nMinimum required portfolio return (annualized): -0.3202\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=0.7562, w_VNQI=0.2438", "answer_numeric": 0.7562, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000113 - 0.000043) / (0.001478 + 0.000113 - 0.000086)\n  Unconstrained: w_ADA-USD=0.0466\n  After long-only clamp: w_ADA-USD=0.0466, w_VNQI=0.9534.", "metadata": {"weights": {"ADA-USD": 0.7562, "VNQI": 0.2438}, "sigma_1": 0.038439, "sigma_2": 0.010635, "covariance": 4.3e-05, "correlation": 0.105, "has_text": true, "text_chars": 20, "mu_floor": -0.3202, "constraint_binding": true}}
{"id": "T4_all_20220718_0954", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "TLH"], "decision_date": "2022-07-18", "context_summary": "BTC-USD \u03c3=0.0377, TLH \u03c3=0.0097, \u03c1=0.219. Min-variance weights: BTC-USD=0.010, TLH=0.990.", "question": "Assets: BTC-USD, TLH\nBTC-USD: annualized_mean_return=-1.0332, daily_std=0.0377\nTLH: annualized_mean_return=-0.0504, daily_std=0.0097\nMinimum required portfolio return (annualized): -0.0539\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_TLH) 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_TLH=X.XXXX", "answer": "w_BTC-USD=0.0036, w_TLH=0.9964", "answer_numeric": 0.0036, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000093 - 0.000080) / (0.001424 + 0.000093 - 0.000159)\n  Unconstrained: w_BTC-USD=0.0099\n  After long-only clamp: w_BTC-USD=0.0099, w_TLH=0.9901.", "metadata": {"weights": {"BTC-USD": 0.0036, "TLH": 0.9964}, "sigma_1": 0.037741, "sigma_2": 0.00965, "covariance": 8e-05, "correlation": 0.2186, "has_text": true, "text_chars": 20, "mu_floor": -0.0539, "constraint_binding": true}}
{"id": "T4_all_20200803_0956", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "VCIT"], "decision_date": "2020-08-03", "context_summary": "EWJ \u03c3=0.0122, VCIT \u03c3=0.0027, \u03c1=0.104. Min-variance weights: EWJ=0.026, VCIT=0.974.", "question": "Assets: EWJ, VCIT\nEWJ: annualized_mean_return=0.3276, daily_std=0.0122\nVCIT: annualized_mean_return=0.3276, daily_std=0.0027\nMinimum required portfolio return (annualized): 0.3276\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_EWJ=0.0281, w_VCIT=0.9719", "answer_numeric": 0.0281, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000007 - 0.000003) / (0.000148 + 0.000007 - 0.000007)\n  Unconstrained: w_EWJ=0.0257\n  After long-only clamp: w_EWJ=0.0257, w_VCIT=0.9743.", "metadata": {"weights": {"EWJ": 0.0281, "VCIT": 0.9719}, "sigma_1": 0.012173, "sigma_2": 0.002684, "covariance": 3e-06, "correlation": 0.1035, "has_text": true, "text_chars": 3020, "mu_floor": 0.3276, "constraint_binding": false}}
{"id": "T4_all_20190404_0958", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "GLD"], "decision_date": "2019-04-04", "context_summary": "FXI \u03c3=0.0113, GLD \u03c3=0.0062, \u03c1=-0.071. Min-variance weights: FXI=0.247, GLD=0.753.", "question": "Assets: FXI, GLD\nFXI: annualized_mean_return=0.5544, daily_std=0.0113\nGLD: annualized_mean_return=-0.0252, daily_std=0.0062\nMinimum required portfolio return (annualized): 0.4376\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_GLD) 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_GLD=X.XXXX", "answer": "w_FXI=0.7985, w_GLD=0.2015", "answer_numeric": 0.7985, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000039 - -0.000005) / (0.000129 + 0.000039 - -0.000010)\n  Unconstrained: w_FXI=0.2466\n  After long-only clamp: w_FXI=0.2466, w_GLD=0.7534.", "metadata": {"weights": {"FXI": 0.7985, "GLD": 0.2015}, "sigma_1": 0.011346, "sigma_2": 0.006226, "covariance": -5e-06, "correlation": -0.071, "has_text": true, "text_chars": 3020, "mu_floor": 0.4376, "constraint_binding": true}}
{"id": "T4_all_20220106_0960", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "SLV"], "decision_date": "2022-01-06", "context_summary": "MATIC-USD \u03c3=0.0658, SLV \u03c3=0.0122, \u03c1=0.138. Min-variance weights: MATIC-USD=0.009, SLV=0.991.", "question": "Assets: MATIC-USD, SLV\nMATIC-USD: annualized_mean_return=1.1844, daily_std=0.0658\nSLV: annualized_mean_return=-0.0504, daily_std=0.0122\nMinimum required portfolio return (annualized): 0.4368\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_SLV) 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_SLV=X.XXXX", "answer": "w_MATIC-USD=0.3946, w_SLV=0.6054", "answer_numeric": 0.3946, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000148 - 0.000111) / (0.004331 + 0.000148 - 0.000221)\n  Unconstrained: w_MATIC-USD=0.0088\n  After long-only clamp: w_MATIC-USD=0.0088, w_SLV=0.9912.", "metadata": {"weights": {"MATIC-USD": 0.3946, "SLV": 0.6054}, "sigma_1": 0.06581, "sigma_2": 0.012168, "covariance": 0.000111, "correlation": 0.1383, "has_text": true, "text_chars": 20, "mu_floor": 0.4368, "constraint_binding": true}}
{"id": "T4_all_20200507_0962", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ICSH"], "decision_date": "2020-05-07", "context_summary": "XLB \u03c3=0.0252, ICSH \u03c3=0.0033, \u03c1=-0.054. Min-variance weights: XLB=0.024, ICSH=0.976.", "question": "Assets: XLB, ICSH\nXLB: annualized_mean_return=-0.3528, daily_std=0.0252\nICSH: annualized_mean_return=0.0756, daily_std=0.0033\nMinimum required portfolio return (annualized): 0.0682\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=0.0173, w_ICSH=0.9827", "answer_numeric": 0.0173, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000011 - -0.000005) / (0.000633 + 0.000011 - -0.000009)\n  Unconstrained: w_XLB=0.0240\n  After long-only clamp: w_XLB=0.0240, w_ICSH=0.9760.", "metadata": {"weights": {"XLB": 0.0173, "ICSH": 0.9827}, "sigma_1": 0.025155, "sigma_2": 0.003341, "covariance": -5e-06, "correlation": -0.0539, "has_text": true, "text_chars": 3020, "mu_floor": 0.0682, "constraint_binding": true}}
{"id": "T4_all_20220712_0964", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "TIP"], "decision_date": "2022-07-12", "context_summary": "BTC-USD \u03c3=0.0385, TIP \u03c3=0.0024, \u03c1=0.164. Min-variance weights: BTC-USD=0.000, TIP=1.000.", "question": "Assets: BTC-USD, TIP\nBTC-USD: annualized_mean_return=-1.2348, daily_std=0.0385\nTIP: annualized_mean_return=-0.0000, daily_std=0.0024\nMinimum required portfolio return (annualized): -0.4263\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_TIP) 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_TIP=X.XXXX", "answer": "w_BTC-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  = (0.000006 - 0.000015) / (0.001480 + 0.000006 - 0.000030)\n  Unconstrained: w_BTC-USD=-0.0064\n  After long-only clamp: w_BTC-USD=0.0000, w_TIP=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "TIP": 1.0}, "sigma_1": 0.038465, "sigma_2": 0.002376, "covariance": 1.5e-05, "correlation": 0.1643, "has_text": true, "text_chars": 20, "mu_floor": -0.4263, "constraint_binding": false}}
{"id": "T4_all_20171128_0967", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "PPLT"], "decision_date": "2017-11-28", "context_summary": "VTI \u03c3=0.0033, PPLT \u03c3=0.0093, \u03c1=0.049. Min-variance weights: VTI=0.898, PPLT=0.102.", "question": "Assets: VTI, PPLT\nVTI: annualized_mean_return=0.2520, daily_std=0.0033\nPPLT: annualized_mean_return=-0.2772, daily_std=0.0093\nMinimum required portfolio return (annualized): 0.1160\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_VTI=0.9022, w_PPLT=0.0978", "answer_numeric": 0.9022, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000086 - 0.000002) / (0.000011 + 0.000086 - 0.000003)\n  Unconstrained: w_VTI=0.8981\n  After long-only clamp: w_VTI=0.8981, w_PPLT=0.1019.", "metadata": {"weights": {"VTI": 0.9022, "PPLT": 0.0978}, "sigma_1": 0.003337, "sigma_2": 0.00929, "covariance": 2e-06, "correlation": 0.0488, "has_text": true, "text_chars": 3020, "mu_floor": 0.116, "constraint_binding": false}}
{"id": "T4_all_20191128_0970", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "XHB"], "decision_date": "2019-11-28", "context_summary": "^VIX \u03c3=0.0590, XHB \u03c3=0.0074, \u03c1=-0.631. Min-variance weights: ^VIX=0.081, XHB=0.919.", "question": "Assets: ^VIX, XHB\n^VIX: annualized_mean_return=-1.6380, daily_std=0.0590\nXHB: annualized_mean_return=0.4536, daily_std=0.0074\nMinimum required portfolio return (annualized): 0.3622\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_XHB) 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_XHB=X.XXXX", "answer": "w_^VIX=0.0437, w_XHB=0.9563", "answer_numeric": 0.0437, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000054 - -0.000274) / (0.003476 + 0.000054 - -0.000548)\n  Unconstrained: w_^VIX=0.0805\n  After long-only clamp: w_^VIX=0.0805, w_XHB=0.9195.", "metadata": {"weights": {"^VIX": 0.0437, "XHB": 0.9563}, "sigma_1": 0.058962, "sigma_2": 0.007365, "covariance": -0.000274, "correlation": -0.6314, "has_text": true, "text_chars": 3020, "mu_floor": 0.3622, "constraint_binding": true}}
{"id": "T4_all_20190318_0972", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "EMB"], "decision_date": "2019-03-18", "context_summary": "IVV \u03c3=0.0099, EMB \u03c3=0.0031, \u03c1=0.046. Min-variance weights: IVV=0.078, EMB=0.922.", "question": "Assets: IVV, EMB\nIVV: annualized_mean_return=0.3276, daily_std=0.0099\nEMB: annualized_mean_return=0.2772, daily_std=0.0031\nMinimum required portfolio return (annualized): 0.2920\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_EMB) 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_EMB=X.XXXX", "answer": "w_IVV=0.2937, w_EMB=0.7063", "answer_numeric": 0.2937, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000010 - 0.000001) / (0.000099 + 0.000010 - 0.000003)\n  Unconstrained: w_IVV=0.0777\n  After long-only clamp: w_IVV=0.0777, w_EMB=0.9223.", "metadata": {"weights": {"IVV": 0.2937, "EMB": 0.7063}, "sigma_1": 0.009946, "sigma_2": 0.003103, "covariance": 1e-06, "correlation": 0.0456, "has_text": true, "text_chars": 3020, "mu_floor": 0.292, "constraint_binding": true}}
{"id": "T4_all_20180116_0974", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "EMB"], "decision_date": "2018-01-16", "context_summary": "IWM \u03c3=0.0065, EMB \u03c3=0.0022, \u03c1=-0.070. Min-variance weights: IWM=0.120, EMB=0.880.", "question": "Assets: IWM, EMB\nIWM: annualized_mean_return=0.2772, daily_std=0.0065\nEMB: annualized_mean_return=0.0756, daily_std=0.0022\nMinimum required portfolio return (annualized): 0.2254\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_EMB) 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_EMB=X.XXXX", "answer": "w_IWM=0.7431, w_EMB=0.2569", "answer_numeric": 0.7431, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000005 - -0.000001) / (0.000042 + 0.000005 - -0.000002)\n  Unconstrained: w_IWM=0.1204\n  After long-only clamp: w_IWM=0.1204, w_EMB=0.8796.", "metadata": {"weights": {"IWM": 0.7431, "EMB": 0.2569}, "sigma_1": 0.006477, "sigma_2": 0.002208, "covariance": -1e-06, "correlation": -0.0701, "has_text": true, "text_chars": 3020, "mu_floor": 0.2254, "constraint_binding": true}}
{"id": "T4_all_20190507_0976", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "CORN"], "decision_date": "2019-05-07", "context_summary": "BTC-USD \u03c3=0.0218, CORN \u03c3=0.0083, \u03c1=0.298. Min-variance weights: BTC-USD=0.036, CORN=0.964.", "question": "Assets: BTC-USD, CORN\nBTC-USD: annualized_mean_return=1.4616, daily_std=0.0218\nCORN: annualized_mean_return=-0.2268, daily_std=0.0083\nMinimum required portfolio return (annualized): 1.1353\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_CORN) 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_CORN=X.XXXX", "answer": "w_BTC-USD=0.8067, w_CORN=0.1933", "answer_numeric": 0.8067, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000070 - 0.000054) / (0.000473 + 0.000070 - 0.000108)\n  Unconstrained: w_BTC-USD=0.0360\n  After long-only clamp: w_BTC-USD=0.0360, w_CORN=0.9640.", "metadata": {"weights": {"BTC-USD": 0.8067, "CORN": 0.1933}, "sigma_1": 0.021755, "sigma_2": 0.008349, "covariance": 5.4e-05, "correlation": 0.2976, "has_text": false, "text_chars": 0, "mu_floor": 1.1353, "constraint_binding": true}}
{"id": "T4_all_20180628_0978", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "HAUZ"], "decision_date": "2018-06-28", "context_summary": "XLK \u03c3=0.0097, HAUZ \u03c3=0.0119, \u03c1=0.287. Min-variance weights: XLK=0.642, HAUZ=0.358.", "question": "Assets: XLK, HAUZ\nXLK: annualized_mean_return=0.2772, daily_std=0.0097\nHAUZ: annualized_mean_return=0.1008, daily_std=0.0119\nMinimum required portfolio return (annualized): 0.2321\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_XLK=0.7443, w_HAUZ=0.2557", "answer_numeric": 0.7443, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000141 - 0.000033) / (0.000093 + 0.000141 - 0.000066)\n  Unconstrained: w_XLK=0.6419\n  After long-only clamp: w_XLK=0.6419, w_HAUZ=0.3581.", "metadata": {"weights": {"XLK": 0.7443, "HAUZ": 0.2557}, "sigma_1": 0.009663, "sigma_2": 0.011883, "covariance": 3.3e-05, "correlation": 0.2875, "has_text": true, "text_chars": 3020, "mu_floor": 0.2321, "constraint_binding": true}}
{"id": "T4_all_20210802_0980", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "LINK-USD"], "decision_date": "2021-08-02", "context_summary": "QQQ \u03c3=0.0090, LINK-USD \u03c3=0.0647, \u03c1=0.365. Min-variance weights: QQQ=1.000, LINK-USD=0.000.", "question": "Assets: QQQ, LINK-USD\nQQQ: annualized_mean_return=0.4284, daily_std=0.0090\nLINK-USD: annualized_mean_return=-0.8064, daily_std=0.0647\nMinimum required portfolio return (annualized): -0.0060\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_LINK-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_LINK-USD=X.XXXX", "answer": "w_QQQ=1.0000, w_LINK-USD=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.004182 - 0.000211) / (0.000080 + 0.004182 - 0.000423)\n  Unconstrained: w_QQQ=1.0341\n  After long-only clamp: w_QQQ=1.0000, w_LINK-USD=0.0000.", "metadata": {"weights": {"QQQ": 1.0, "LINK-USD": 0.0}, "sigma_1": 0.008959, "sigma_2": 0.064667, "covariance": 0.000211, "correlation": 0.3647, "has_text": true, "text_chars": 3020, "mu_floor": -0.006, "constraint_binding": false}}
{"id": "T4_all_20201127_0982", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "EMB"], "decision_date": "2020-11-27", "context_summary": "BTC-USD \u03c3=0.0272, EMB \u03c3=0.0047, \u03c1=0.112. Min-variance weights: BTC-USD=0.010, EMB=0.990.", "question": "Assets: BTC-USD, EMB\nBTC-USD: annualized_mean_return=2.0412, daily_std=0.0272\nEMB: annualized_mean_return=0.0252, daily_std=0.0047\nMinimum required portfolio return (annualized): 1.3134\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_EMB) 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_EMB=X.XXXX", "answer": "w_BTC-USD=0.6390, w_EMB=0.3610", "answer_numeric": 0.639, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000022 - 0.000014) / (0.000739 + 0.000022 - 0.000028)\n  Unconstrained: w_BTC-USD=0.0103\n  After long-only clamp: w_BTC-USD=0.0103, w_EMB=0.9897.", "metadata": {"weights": {"BTC-USD": 0.639, "EMB": 0.361}, "sigma_1": 0.027187, "sigma_2": 0.004666, "covariance": 1.4e-05, "correlation": 0.1122, "has_text": false, "text_chars": 0, "mu_floor": 1.3134, "constraint_binding": true}}
{"id": "T4_all_20200324_0984", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "IAU"], "decision_date": "2020-03-24", "context_summary": "VTI \u03c3=0.0170, IAU \u03c3=0.0114, \u03c1=0.051. Min-variance weights: VTI=0.301, IAU=0.699.", "question": "Assets: VTI, IAU\nVTI: annualized_mean_return=-1.0080, daily_std=0.0170\nIAU: annualized_mean_return=0.1008, daily_std=0.0114\nMinimum required portfolio return (annualized): -0.1611\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=0.2362, w_IAU=0.7638", "answer_numeric": 0.2362, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000131 - 0.000010) / (0.000290 + 0.000131 - 0.000020)\n  Unconstrained: w_VTI=0.3011\n  After long-only clamp: w_VTI=0.3011, w_IAU=0.6989.", "metadata": {"weights": {"VTI": 0.2362, "IAU": 0.7638}, "sigma_1": 0.017034, "sigma_2": 0.01143, "covariance": 1e-05, "correlation": 0.0507, "has_text": true, "text_chars": 3020, "mu_floor": -0.1611, "constraint_binding": true}}
{"id": "T4_all_20211223_0986", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "INDS"], "decision_date": "2021-12-23", "context_summary": "IVV \u03c3=0.0090, INDS \u03c3=0.0092, \u03c1=0.619. Min-variance weights: IVV=0.535, INDS=0.465.", "question": "Assets: IVV, INDS\nIVV: annualized_mean_return=0.3276, daily_std=0.0089\nINDS: annualized_mean_return=0.8820, daily_std=0.0092\nMinimum required portfolio return (annualized): 0.7210\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=0.2904, w_INDS=0.7096", "answer_numeric": 0.2904, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000084 - 0.000051) / (0.000080 + 0.000084 - 0.000102)\n  Unconstrained: w_IVV=0.5350\n  After long-only clamp: w_IVV=0.5350, w_INDS=0.4650.", "metadata": {"weights": {"IVV": 0.2904, "INDS": 0.7096}, "sigma_1": 0.00895, "sigma_2": 0.009192, "covariance": 5.1e-05, "correlation": 0.6186, "has_text": true, "text_chars": 3020, "mu_floor": 0.721, "constraint_binding": true}}
{"id": "T4_all_20180720_0988", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "SHV"], "decision_date": "2018-07-20", "context_summary": "XRP-USD \u03c3=0.0397, SHV \u03c3=0.0001, \u03c1=-0.072. Min-variance weights: XRP-USD=0.000, SHV=1.000.", "question": "Assets: XRP-USD, SHV\nXRP-USD: annualized_mean_return=-1.4112, daily_std=0.0397\nSHV: annualized_mean_return=0.0252, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0252\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_SHV) 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_SHV=X.XXXX", "answer": "w_XRP-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) / (0.001575 + 0.000000 - -0.000001)\n  Unconstrained: w_XRP-USD=0.0002\n  After long-only clamp: w_XRP-USD=0.0002, w_SHV=0.9998.", "metadata": {"weights": {"XRP-USD": -0.0, "SHV": 1.0}, "sigma_1": 0.03968, "sigma_2": 0.000117, "covariance": -0.0, "correlation": -0.0724, "has_text": false, "text_chars": 0, "mu_floor": 0.0252, "constraint_binding": true}}
{"id": "T4_all_20210209_0992", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "INDS"], "decision_date": "2021-02-09", "context_summary": "VTI \u03c3=0.0084, INDS \u03c3=0.0117, \u03c1=0.624. Min-variance weights: VTI=0.887, INDS=0.113.", "question": "Assets: VTI, INDS\nVTI: annualized_mean_return=0.5544, daily_std=0.0084\nINDS: annualized_mean_return=0.4032, daily_std=0.0117\nMinimum required portfolio return (annualized): 0.5478\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_INDS) 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_INDS=X.XXXX", "answer": "w_VTI=0.9563, w_INDS=0.0437", "answer_numeric": 0.9563, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000137 - 0.000062) / (0.000071 + 0.000137 - 0.000123)\n  Unconstrained: w_VTI=0.8873\n  After long-only clamp: w_VTI=0.8873, w_INDS=0.1127.", "metadata": {"weights": {"VTI": 0.9563, "INDS": 0.0437}, "sigma_1": 0.00843, "sigma_2": 0.011693, "covariance": 6.2e-05, "correlation": 0.6241, "has_text": true, "text_chars": 3020, "mu_floor": 0.5478, "constraint_binding": true}}
{"id": "T4_all_20160602_0994", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "MORT"], "decision_date": "2016-06-02", "context_summary": "XLI \u03c3=0.0075, MORT \u03c3=0.0090, \u03c1=0.410. Min-variance weights: XLI=0.654, MORT=0.346.", "question": "Assets: XLI, MORT\nXLI: annualized_mean_return=0.1764, daily_std=0.0075\nMORT: annualized_mean_return=0.3528, daily_std=0.0090\nMinimum required portfolio return (annualized): 0.3217\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_MORT) 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_MORT=X.XXXX", "answer": "w_XLI=0.1763, w_MORT=0.8237", "answer_numeric": 0.1763, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000081 - 0.000028) / (0.000056 + 0.000081 - 0.000055)\n  Unconstrained: w_XLI=0.6536\n  After long-only clamp: w_XLI=0.6536, w_MORT=0.3464.", "metadata": {"weights": {"XLI": 0.1763, "MORT": 0.8237}, "sigma_1": 0.007483, "sigma_2": 0.009009, "covariance": 2.8e-05, "correlation": 0.4099, "has_text": true, "text_chars": 3020, "mu_floor": 0.3217, "constraint_binding": true}}
{"id": "T4_all_20221207_0997", "template": "T4", "complexity": 2, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "BNDX"], "decision_date": "2022-12-07", "context_summary": "XRP-USD \u03c3=0.0492, BNDX \u03c3=0.0042, \u03c1=-0.031. Min-variance weights: XRP-USD=0.010, BNDX=0.990.", "question": "Assets: XRP-USD, BNDX\nXRP-USD: annualized_mean_return=-0.8568, daily_std=0.0492\nBNDX: annualized_mean_return=0.0504, daily_std=0.0042\nMinimum required portfolio return (annualized): -0.2586\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_BNDX) 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_BNDX=X.XXXX", "answer": "w_XRP-USD=0.0097, w_BNDX=0.9903", "answer_numeric": 0.0097, "explanation": "Analytic min-variance formula:\n  w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n  = (0.000018 - -0.000006) / (0.002419 + 0.000018 - -0.000013)\n  Unconstrained: w_XRP-USD=0.0099\n  After long-only clamp: w_XRP-USD=0.0099, w_BNDX=0.9901.", "metadata": {"weights": {"XRP-USD": 0.0097, "BNDX": 0.9903}, "sigma_1": 0.049184, "sigma_2": 0.00421, "covariance": -6e-06, "correlation": -0.0312, "has_text": true, "text_chars": 20, "mu_floor": -0.2586, "constraint_binding": false}}
{"id": "T5_all_20180613_0004", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "IEF", "BNO"], "decision_date": "2018-06-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.505. Portfolio: return=36.02%, vol=21.28%. Weights: w_VEA=0.0000, w_BTC-USD=0.0000, w_IEF=0.0000, w_BNO=1.0000.", "question": "Assets: VEA, BTC-USD, IEF, BNO\nAnnualized mean returns: VEA:-0.0014, BTC-USD:-1.0527, IEF:-0.0372, BNO:0.3602\nCovariance matrix (annualized):\n[[0.009376, -0.00356, -0.002425, 0.008461], [-0.00356, 0.3135, 0.002931, 0.009335], [-0.002425, 0.002931, 0.002383, -0.002674], [0.008461, 0.009335, -0.002674, 0.045267]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_IEF=0.0000, w_BNO=1.0000", "answer_numeric": 1.5050402339154978, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_BTC-USD=0.0000, w_IEF=0.0000, w_BNO=1.0000\nPortfolio annualized return: 36.02%, volatility: 21.28%\nSharpe ratio: (0.3602 - 0.0400) / 0.2128 = 1.5050", "metadata": {"weights": {"VEA": 0.0, "BTC-USD": 0.0, "IEF": 0.0, "BNO": 1.0}, "sharpe_ratio": 1.505, "portfolio_return": 0.360212, "portfolio_vol": 0.212759, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210326_0009", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "MATIC-USD", "SGOV", "REZ"], "decision_date": "2021-03-26", "context_summary": "4-asset optimization. Max-Sharpe: 7.423. Portfolio: return=244.96%, vol=32.46%. Weights: w_XLP=0.4134, w_MATIC-USD=0.1479, w_SGOV=0.0000, w_REZ=0.4387.", "question": "Assets: XLP, MATIC-USD, SGOV, REZ\nAnnualized mean returns: XLP:0.2324, MATIC-USD:14.4524, SGOV:0.0006, REZ:0.4938\nCovariance matrix (annualized):\n[[0.016857, -0.026248, 2.2e-05, 0.012143], [-0.026248, 4.311629, -0.000158, 0.008437], [2.2e-05, -0.000158, 1e-06, 7e-06], [0.012143, 0.008437, 7e-06, 0.030951]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4134, w_MATIC-USD=0.1479, w_SGOV=0.0000, w_REZ=0.4387", "answer_numeric": 7.422500818676502, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.4134, w_MATIC-USD=0.1479, w_SGOV=0.0000, w_REZ=0.4387\nPortfolio annualized return: 244.96%, volatility: 32.46%\nSharpe ratio: (2.4496 - 0.0400) / 0.3246 = 7.4225", "metadata": {"weights": {"XLP": 0.4134, "MATIC-USD": 0.1479, "SGOV": 0.0, "REZ": 0.4387}, "sharpe_ratio": 7.4225, "portfolio_return": 2.449576, "portfolio_vol": 0.324631, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210520_0012", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "LINK-USD", "HYG", "ICSH"], "decision_date": "2021-05-20", "context_summary": "4-asset optimization. Max-Sharpe: 2.297. Portfolio: return=66.69%, vol=27.30%. Weights: w_VTI=0.8210, w_LINK-USD=0.1790, w_HYG=0.0000, w_ICSH=0.0000.", "question": "Assets: VTI, LINK-USD, HYG, ICSH\nAnnualized mean returns: VTI:0.2358, LINK-USD:2.6440, HYG:0.0793, ICSH:0.0070\nCovariance matrix (annualized):\n[[0.018316, 0.046048, 0.003358, -1.8e-05], [0.046048, 1.517899, 0.01302, -0.001029], [0.003358, 0.01302, 0.001171, -0.0], [-1.8e-05, -0.001029, -0.0, 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_VTI=0.8210, w_LINK-USD=0.1790, w_HYG=0.0000, w_ICSH=0.0000", "answer_numeric": 2.296558114790538, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.8210, w_LINK-USD=0.1790, w_HYG=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 66.69%, volatility: 27.30%\nSharpe ratio: (0.6669 - 0.0400) / 0.2730 = 2.2966", "metadata": {"weights": {"VTI": 0.821, "LINK-USD": 0.179, "HYG": 0.0, "ICSH": 0.0}, "sharpe_ratio": 2.2966, "portfolio_return": 0.666942, "portfolio_vol": 0.272992, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220127_0015", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "VNQI", "DBA"], "decision_date": "2022-01-27", "context_summary": "4-asset optimization. Max-Sharpe: 0.230. Portfolio: return=6.90%, vol=12.65%. Weights: w_XLU=0.0000, w_AVAX-USD=0.0000, w_VNQI=0.0000, w_DBA=1.0000.", "question": "Assets: XLU, AVAX-USD, VNQI, DBA\nAnnualized mean returns: XLU:0.0297, AVAX-USD:-1.2064, VNQI:-0.1177, DBA:0.0690\nCovariance matrix (annualized):\n[[0.022825, -0.013025, 0.005839, 0.004927], [-0.013025, 1.234613, 0.016189, -0.015051], [0.005839, 0.016189, 0.012878, 0.006782], [0.004927, -0.015051, 0.006782, 0.015991]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_VNQI=0.0000, w_DBA=1.0000", "answer_numeric": 0.22969870275500817, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_AVAX-USD=0.0000, w_VNQI=0.0000, w_DBA=1.0000\nPortfolio annualized return: 6.90%, volatility: 12.65%\nSharpe ratio: (0.0690 - 0.0400) / 0.1265 = 0.2297", "metadata": {"weights": {"XLU": 0.0, "AVAX-USD": 0.0, "VNQI": 0.0, "DBA": 1.0}, "sharpe_ratio": 0.2297, "portfolio_return": 0.069047, "portfolio_vol": 0.126457, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210218_0018", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "DOT-USD", "SCHP", "VNQ"], "decision_date": "2021-02-18", "context_summary": "4-asset optimization. Max-Sharpe: 6.687. Portfolio: return=296.77%, vol=43.78%. Weights: w_VTI=0.7715, w_DOT-USD=0.2285, w_SCHP=0.0000, w_VNQ=0.0000.", "question": "Assets: VTI, DOT-USD, SCHP, VNQ\nAnnualized mean returns: VTI:0.4533, DOT-USD:11.4564, SCHP:0.0024, VNQ:0.4027\nCovariance matrix (annualized):\n[[0.018286, 0.056683, 0.000105, 0.013759], [0.056683, 3.079737, 0.006521, 0.093904], [0.000105, 0.006521, 0.000718, 0.000487], [0.013759, 0.093904, 0.000487, 0.024722]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7715, w_DOT-USD=0.2285, w_SCHP=0.0000, w_VNQ=0.0000", "answer_numeric": 6.686817765404276, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.7715, w_DOT-USD=0.2285, w_SCHP=0.0000, w_VNQ=0.0000\nPortfolio annualized return: 296.77%, volatility: 43.78%\nSharpe ratio: (2.9677 - 0.0400) / 0.4378 = 6.6868", "metadata": {"weights": {"VTI": 0.7715, "DOT-USD": 0.2285, "SCHP": 0.0, "VNQ": 0.0}, "sharpe_ratio": 6.6868, "portfolio_return": 2.967735, "portfolio_vol": 0.437837, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200715_0021", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ETH-USD", "HYG", "HAUZ"], "decision_date": "2020-07-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.810. Portfolio: return=47.68%, vol=11.46%. Weights: w_VLUE=0.0000, w_ETH-USD=0.0311, w_HYG=0.8685, w_HAUZ=0.1004.", "question": "Assets: VLUE, ETH-USD, HYG, HAUZ\nAnnualized mean returns: VLUE:0.6998, ETH-USD:0.8817, HYG:0.4261, HAUZ:0.7897\nCovariance matrix (annualized):\n[[0.08543, 0.03735, 0.022056, 0.049244], [0.03735, 0.216043, 0.016098, 0.04614], [0.022056, 0.016098, 0.010667, 0.018454], [0.049244, 0.04614, 0.018454, 0.050735]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0311, w_HYG=0.8685, w_HAUZ=0.1004", "answer_numeric": 3.810060041899085, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_ETH-USD=0.0311, w_HYG=0.8685, w_HAUZ=0.1004\nPortfolio annualized return: 47.68%, volatility: 11.46%\nSharpe ratio: (0.4768 - 0.0400) / 0.1146 = 3.8101", "metadata": {"weights": {"VLUE": 0.0, "ETH-USD": 0.0311, "HYG": 0.8685, "HAUZ": 0.1004}, "sharpe_ratio": 3.8101, "portfolio_return": 0.476766, "portfolio_vol": 0.114635, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200901_0028", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "SCHH", "TLT"], "decision_date": "2020-09-01", "context_summary": "4-asset optimization. Max-Sharpe: 4.251. Portfolio: return=48.48%, vol=10.46%. Weights: w_XLF=0.4204, w_BTC-USD=0.2127, w_SCHH=0.0000, w_TLT=0.3669.", "question": "Assets: XLF, BTC-USD, SCHH, TLT\nAnnualized mean returns: XLF:0.5352, BTC-USD:1.2898, SCHH:0.1420, TLT:-0.0396\nCovariance matrix (annualized):\n[[0.039832, 0.001276, 0.009854, -0.013157], [0.001276, 0.152404, 0.015511, -0.005974], [0.009854, 0.015511, 0.030546, -0.001848], [-0.013157, -0.005974, -0.001848, 0.013203]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4204, w_BTC-USD=0.2127, w_SCHH=0.0000, w_TLT=0.3669", "answer_numeric": 4.251399711178159, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.4204, w_BTC-USD=0.2127, w_SCHH=0.0000, w_TLT=0.3669\nPortfolio annualized return: 48.48%, volatility: 10.46%\nSharpe ratio: (0.4848 - 0.0400) / 0.1046 = 4.2514", "metadata": {"weights": {"XLF": 0.4204, "BTC-USD": 0.2127, "SCHH": 0.0, "TLT": 0.3669}, "sharpe_ratio": 4.2514, "portfolio_return": 0.48485, "portfolio_vol": 0.104636, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191016_0035", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "DBA", "VNQI"], "decision_date": "2019-10-16", "context_summary": "4-asset optimization. Max-Sharpe: 4.391. Portfolio: return=35.84%, vol=7.25%. Weights: w_XLE=0.0000, w_ADA-USD=0.0000, w_DBA=0.3858, w_VNQI=0.6142.", "question": "Assets: XLE, ADA-USD, DBA, VNQI\nAnnualized mean returns: XLE:0.1713, ADA-USD:-0.9763, DBA:0.3663, VNQI:0.3535\nCovariance matrix (annualized):\n[[0.045265, -0.014303, 0.005621, 0.007446], [-0.014303, 0.474104, -0.010122, -0.007149], [0.005621, -0.010122, 0.012046, 0.001205], [0.007446, -0.007149, 0.001205, 0.007673]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3858, w_VNQI=0.6142", "answer_numeric": 4.3912832773721115, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_ADA-USD=0.0000, w_DBA=0.3858, w_VNQI=0.6142\nPortfolio annualized return: 35.84%, volatility: 7.25%\nSharpe ratio: (0.3584 - 0.0400) / 0.0725 = 4.3913", "metadata": {"weights": {"XLE": 0.0, "ADA-USD": 0.0, "DBA": 0.3858, "VNQI": 0.6142}, "sharpe_ratio": 4.3913, "portfolio_return": 0.358438, "portfolio_vol": 0.072516, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221006_0044", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "LINK-USD", "ICSH", "HAUZ"], "decision_date": "2022-10-06", "context_summary": "4-asset optimization. Max-Sharpe: -0.165. Portfolio: return=-7.61%, vol=70.52%. Weights: w_IWM=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_HAUZ=0.0000.", "question": "Assets: IWM, LINK-USD, ICSH, HAUZ\nAnnualized mean returns: IWM:-0.5046, LINK-USD:-0.0761, ICSH:0.0132, HAUZ:-0.8199\nCovariance matrix (annualized):\n[[0.077654, 0.078477, 0.000492, 0.049474], [0.078477, 0.4973, 4.7e-05, 0.042115], [0.000492, 4.7e-05, 2.5e-05, 0.000497], [0.049474, 0.042115, 0.000497, 0.047258]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=1.0000, w_ICSH=0.0000, w_HAUZ=0.0000", "answer_numeric": -0.16461712068911358, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: -7.61%, volatility: 70.52%\nSharpe ratio: (-0.0761 - 0.0400) / 0.7052 = -0.1646", "metadata": {"weights": {"IWM": 0.0, "LINK-USD": 1.0, "ICSH": 0.0, "HAUZ": 0.0}, "sharpe_ratio": -0.1646, "portfolio_return": -0.076087, "portfolio_vol": 0.705195, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210503_0047", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "PPLT", "SHY"], "decision_date": "2021-05-03", "context_summary": "4-asset optimization. Max-Sharpe: 0.478. Portfolio: return=18.47%, vol=30.27%. Weights: w_XLE=0.0000, w_DOT-USD=0.2002, w_PPLT=0.7998, w_SHY=0.0000.", "question": "Assets: XLE, DOT-USD, PPLT, SHY\nAnnualized mean returns: XLE:0.0079, DOT-USD:0.3250, PPLT:0.1496, SHY:0.0028\nCovariance matrix (annualized):\n[[0.084514, -0.035639, 0.012192, 0.000183], [-0.035639, 0.717478, 0.04604, -0.000371], [0.012192, 0.04604, 0.075271, 2.6e-05], [0.000183, -0.000371, 2.6e-05, 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=0.0000, w_DOT-USD=0.2002, w_PPLT=0.7998, w_SHY=0.0000", "answer_numeric": 0.47806399001954974, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_DOT-USD=0.2002, w_PPLT=0.7998, w_SHY=0.0000\nPortfolio annualized return: 18.47%, volatility: 30.27%\nSharpe ratio: (0.1847 - 0.0400) / 0.3027 = 0.4781", "metadata": {"weights": {"XLE": 0.0, "DOT-USD": 0.2002, "PPLT": 0.7998, "SHY": 0.0}, "sharpe_ratio": 0.4781, "portfolio_return": 0.184725, "portfolio_vol": 0.302731, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211008_0056", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "STIP", "CORN"], "decision_date": "2021-10-08", "context_summary": "4-asset optimization. Max-Sharpe: 2.700. Portfolio: return=300.14%, vol=109.69%. Weights: w_QUAL=0.0000, w_ADA-USD=1.0000, w_STIP=0.0000, w_CORN=0.0000.", "question": "Assets: QUAL, ADA-USD, STIP, CORN\nAnnualized mean returns: QUAL:-0.1861, ADA-USD:3.0014, STIP:0.0398, CORN:-0.1212\nCovariance matrix (annualized):\n[[0.015097, 0.064691, 0.000634, 0.00295], [0.064691, 1.203256, 0.003895, 0.031849], [0.000634, 0.003895, 0.00026, 0.000873], [0.00295, 0.031849, 0.000873, 0.033027]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_STIP=0.0000, w_CORN=0.0000", "answer_numeric": 2.69975486906289, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_ADA-USD=1.0000, w_STIP=0.0000, w_CORN=0.0000\nPortfolio annualized return: 300.14%, volatility: 109.69%\nSharpe ratio: (3.0014 - 0.0400) / 1.0969 = 2.6998", "metadata": {"weights": {"QUAL": 0.0, "ADA-USD": 1.0, "STIP": 0.0, "CORN": 0.0}, "sharpe_ratio": 2.6998, "portfolio_return": 3.001443, "portfolio_vol": 1.09693, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210913_0077", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "INDS", "EMB"], "decision_date": "2021-09-13", "context_summary": "4-asset optimization. Max-Sharpe: 8.592. Portfolio: return=600.60%, vol=69.44%. Weights: w_IVV=0.0000, w_SOL-USD=0.6187, w_INDS=0.0000, w_EMB=0.3813.", "question": "Assets: IVV, SOL-USD, INDS, EMB\nAnnualized mean returns: IVV:0.1315, SOL-USD:9.6629, INDS:0.1557, EMB:0.0715\nCovariance matrix (annualized):\n[[0.009031, 0.03496, 0.006933, 0.000955], [0.03496, 1.25506, 0.036422, 0.003164], [0.006933, 0.036422, 0.020221, 0.001828], [0.000955, 0.003164, 0.001828, 0.001548]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6187, w_INDS=0.0000, w_EMB=0.3813", "answer_numeric": 8.59164310390397, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_SOL-USD=0.6187, w_INDS=0.0000, w_EMB=0.3813\nPortfolio annualized return: 600.60%, volatility: 69.44%\nSharpe ratio: (6.0060 - 0.0400) / 0.6944 = 8.5916", "metadata": {"weights": {"IVV": 0.0, "SOL-USD": 0.6187, "INDS": 0.0, "EMB": 0.3813}, "sharpe_ratio": 8.5916, "portfolio_return": 6.005954, "portfolio_vol": 0.69439, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180703_0083", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "STIP", "DBB"], "decision_date": "2018-07-03", "context_summary": "4-asset optimization. Max-Sharpe: 0.978. Portfolio: return=17.93%, vol=14.25%. Weights: w_XLU=1.0000, w_LINK-USD=0.0000, w_STIP=0.0000, w_DBB=0.0000.", "question": "Assets: XLU, LINK-USD, STIP, DBB\nAnnualized mean returns: XLU:0.1793, LINK-USD:-3.9351, STIP:0.0318, DBB:-0.3827\nCovariance matrix (annualized):\n[[0.020295, -0.001297, 0.000699, -0.007988], [-0.001297, 1.071198, 0.001468, -0.024727], [0.000699, 0.001468, 0.000128, -0.000406], [-0.007988, -0.024727, -0.000406, 0.019452]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=0.0000, w_STIP=0.0000, w_DBB=0.0000", "answer_numeric": 0.9779212379229583, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=1.0000, w_LINK-USD=0.0000, w_STIP=0.0000, w_DBB=0.0000\nPortfolio annualized return: 17.93%, volatility: 14.25%\nSharpe ratio: (0.1793 - 0.0400) / 0.1425 = 0.9779", "metadata": {"weights": {"XLU": 1.0, "LINK-USD": 0.0, "STIP": 0.0, "DBB": 0.0}, "sharpe_ratio": 0.9779, "portfolio_return": 0.179315, "portfolio_vol": 0.14246, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20160107_0099", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "ITB", "SHY"], "decision_date": "2016-01-07", "context_summary": "4-asset optimization. Max-Sharpe: 2.112. Portfolio: return=120.73%, vol=55.27%. Weights: w_VEA=0.0000, w_BTC-USD=1.0000, w_ITB=0.0000, w_SHY=0.0000.", "question": "Assets: VEA, BTC-USD, ITB, SHY\nAnnualized mean returns: VEA:-0.3840, BTC-USD:1.2073, ITB:-0.3076, SHY:-0.0004\nCovariance matrix (annualized):\n[[0.022082, -0.024986, 0.02937, -0.000547], [-0.024986, 0.305493, -0.056026, 0.000548], [0.02937, -0.056026, 0.058347, -0.00063], [-0.000547, 0.000548, -0.00063, 7.7e-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_VEA=0.0000, w_BTC-USD=1.0000, w_ITB=0.0000, w_SHY=0.0000", "answer_numeric": 2.1120204770250792, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_BTC-USD=1.0000, w_ITB=0.0000, w_SHY=0.0000\nPortfolio annualized return: 120.73%, volatility: 55.27%\nSharpe ratio: (1.2073 - 0.0400) / 0.5527 = 2.1120", "metadata": {"weights": {"VEA": 0.0, "BTC-USD": 1.0, "ITB": 0.0, "SHY": 0.0}, "sharpe_ratio": 2.112, "portfolio_return": 1.207343, "portfolio_vol": 0.552714, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181121_0106", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "WEAT", "TIP"], "decision_date": "2018-11-21", "context_summary": "4-asset optimization. Max-Sharpe: -1.876. Portfolio: return=-165.69%, vol=90.43%. Weights: w_USMV=0.0000, w_XRP-USD=1.0000, w_WEAT=0.0000, w_TIP=0.0000.", "question": "Assets: USMV, XRP-USD, WEAT, TIP\nAnnualized mean returns: USMV:-0.2603, XRP-USD:-1.6569, WEAT:-0.3513, TIP:-0.0130\nCovariance matrix (annualized):\n[[0.019777, 0.063604, -0.001565, -0.000205], [0.063604, 0.817817, 0.014455, 0.000774], [-0.001565, 0.014455, 0.032313, 0.000708], [-0.000205, 0.000774, 0.000708, 0.000169]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_WEAT=0.0000, w_TIP=0.0000", "answer_numeric": -1.8763703878938998, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_XRP-USD=1.0000, w_WEAT=0.0000, w_TIP=0.0000\nPortfolio annualized return: -165.69%, volatility: 90.43%\nSharpe ratio: (-1.6569 - 0.0400) / 0.9043 = -1.8764", "metadata": {"weights": {"USMV": 0.0, "XRP-USD": 1.0, "WEAT": 0.0, "TIP": 0.0}, "sharpe_ratio": -1.8764, "portfolio_return": -1.656862, "portfolio_vol": 0.904332, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201021_0109", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "LINK-USD", "PALL", "SGOV"], "decision_date": "2020-10-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.373. Portfolio: return=68.32%, vol=27.11%. Weights: w_VEA=0.0000, w_LINK-USD=0.0000, w_PALL=1.0000, w_SGOV=0.0000.", "question": "Assets: VEA, LINK-USD, PALL, SGOV\nAnnualized mean returns: VEA:0.0635, LINK-USD:-3.1381, PALL:0.6832, SGOV:0.0004\nCovariance matrix (annualized):\n[[0.023793, 0.081252, 0.017159, -2e-06], [0.081252, 1.147903, 0.029542, -0.000217], [0.017159, 0.029542, 0.073488, -2.1e-05], [-2e-06, -0.000217, -2.1e-05, 1e-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_LINK-USD=0.0000, w_PALL=1.0000, w_SGOV=0.0000", "answer_numeric": 2.372858501761656, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_LINK-USD=0.0000, w_PALL=1.0000, w_SGOV=0.0000\nPortfolio annualized return: 68.32%, volatility: 27.11%\nSharpe ratio: (0.6832 - 0.0400) / 0.2711 = 2.3729", "metadata": {"weights": {"VEA": 0.0, "LINK-USD": 0.0, "PALL": 1.0, "SGOV": 0.0}, "sharpe_ratio": 2.3729, "portfolio_return": 0.683248, "portfolio_vol": 0.271086, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200911_0112", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "DBA", "ICSH"], "decision_date": "2020-09-11", "context_summary": "4-asset optimization. Max-Sharpe: 3.989. Portfolio: return=45.22%, vol=10.33%. Weights: w_XLF=0.1602, w_BTC-USD=0.0000, w_DBA=0.8398, w_ICSH=0.0000.", "question": "Assets: XLF, BTC-USD, DBA, ICSH\nAnnualized mean returns: XLF:0.2638, BTC-USD:0.5175, DBA:0.4882, ICSH:0.0114\nCovariance matrix (annualized):\n[[0.032685, 0.00501, 0.000667, -8.5e-05], [0.00501, 0.227481, 0.017958, -0.000167], [0.000667, 0.017958, 0.013698, 2.1e-05], [-8.5e-05, -0.000167, 2.1e-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_XLF=0.1602, w_BTC-USD=0.0000, w_DBA=0.8398, w_ICSH=0.0000", "answer_numeric": 3.9889979872576684, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.1602, w_BTC-USD=0.0000, w_DBA=0.8398, w_ICSH=0.0000\nPortfolio annualized return: 45.22%, volatility: 10.33%\nSharpe ratio: (0.4522 - 0.0400) / 0.1033 = 3.9890", "metadata": {"weights": {"XLF": 0.1602, "BTC-USD": 0.0, "DBA": 0.8398, "ICSH": 0.0}, "sharpe_ratio": 3.989, "portfolio_return": 0.452212, "portfolio_vol": 0.103337, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211022_0115", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "LQD", "ICSH"], "decision_date": "2021-10-22", "context_summary": "4-asset optimization. Max-Sharpe: -1.001. Portfolio: return=-124.41%, vol=128.34%. Weights: w_^VIX=1.0000, w_ADA-USD=0.0000, w_LQD=0.0000, w_ICSH=0.0000.", "question": "Assets: ^VIX, ADA-USD, LQD, ICSH\nAnnualized mean returns: ^VIX:-1.2441, ADA-USD:-0.4425, LQD:-0.1282, ICSH:0.0002\nCovariance matrix (annualized):\n[[1.647103, -0.732629, -0.022018, 0.000355], [-0.732629, 0.708946, 0.014684, 0.000302], [-0.022018, 0.014684, 0.003698, 2.3e-05], [0.000355, 0.000302, 2.3e-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_^VIX=1.0000, w_ADA-USD=0.0000, w_LQD=0.0000, w_ICSH=0.0000", "answer_numeric": -1.0005725865065125, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=1.0000, w_ADA-USD=0.0000, w_LQD=0.0000, w_ICSH=0.0000\nPortfolio annualized return: -124.41%, volatility: 128.34%\nSharpe ratio: (-1.2441 - 0.0400) / 1.2834 = -1.0006", "metadata": {"weights": {"^VIX": 1.0, "ADA-USD": 0.0, "LQD": 0.0, "ICSH": 0.0}, "sharpe_ratio": -1.0006, "portfolio_return": -1.24413, "portfolio_vol": 1.283395, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201110_0120", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "SLV", "SGOV"], "decision_date": "2020-11-10", "context_summary": "4-asset optimization. Max-Sharpe: 1.635. Portfolio: return=63.45%, vol=36.36%. Weights: w_XLRE=0.4264, w_ETH-USD=0.5736, w_SLV=0.0000, w_SGOV=0.0000.", "question": "Assets: XLRE, ETH-USD, SLV, SGOV\nAnnualized mean returns: XLRE:0.1855, ETH-USD:0.9684, SLV:-0.2174, SGOV:0.0009\nCovariance matrix (annualized):\n[[0.052188, 0.017623, 0.030693, 1.8e-05], [0.017623, 0.346901, 0.102881, -7e-06], [0.030693, 0.102881, 0.138783, 1e-05], [1.8e-05, -7e-06, 1e-05, 0.0]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4264, w_ETH-USD=0.5736, w_SLV=0.0000, w_SGOV=0.0000", "answer_numeric": 1.635014221517429, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.4264, w_ETH-USD=0.5736, w_SLV=0.0000, w_SGOV=0.0000\nPortfolio annualized return: 63.45%, volatility: 36.36%\nSharpe ratio: (0.6345 - 0.0400) / 0.3636 = 1.6350", "metadata": {"weights": {"XLRE": 0.4264, "ETH-USD": 0.5736, "SLV": 0.0, "SGOV": 0.0}, "sharpe_ratio": 1.635, "portfolio_return": 0.634544, "portfolio_vol": 0.363632, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201229_0123", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "CORN", "TLH"], "decision_date": "2020-12-29", "context_summary": "4-asset optimization. Max-Sharpe: 7.086. Portfolio: return=79.30%, vol=10.63%. Weights: w_IVV=0.5653, w_MATIC-USD=0.0172, w_CORN=0.4175, w_TLH=0.0000.", "question": "Assets: IVV, MATIC-USD, CORN, TLH\nAnnualized mean returns: IVV:0.7863, MATIC-USD:2.1194, CORN:0.7474, TLH:-0.0571\nCovariance matrix (annualized):\n[[0.018426, -0.004166, 0.002031, -0.001801], [-0.004166, 1.047259, 0.037185, -0.003401], [0.002031, 0.037185, 0.02113, -0.000148], [-0.001801, -0.003401, -0.000148, 0.010382]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5653, w_MATIC-USD=0.0172, w_CORN=0.4175, w_TLH=0.0000", "answer_numeric": 7.086133570536074, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.5653, w_MATIC-USD=0.0172, w_CORN=0.4175, w_TLH=0.0000\nPortfolio annualized return: 79.30%, volatility: 10.63%\nSharpe ratio: (0.7930 - 0.0400) / 0.1063 = 7.0861", "metadata": {"weights": {"IVV": 0.5653, "MATIC-USD": 0.0172, "CORN": 0.4175, "TLH": 0.0}, "sharpe_ratio": 7.0861, "portfolio_return": 0.793032, "portfolio_vol": 0.106268, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201117_0128", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "XRP-USD", "GLD", "VCIT"], "decision_date": "2020-11-17", "context_summary": "4-asset optimization. Max-Sharpe: 1.117. Portfolio: return=49.59%, vol=40.82%. Weights: w_^VIX=0.0000, w_XRP-USD=1.0000, w_GLD=0.0000, w_VCIT=0.0000.", "question": "Assets: ^VIX, XRP-USD, GLD, VCIT\nAnnualized mean returns: ^VIX:-0.9758, XRP-USD:0.4959, GLD:-0.0560, VCIT:0.0212\nCovariance matrix (annualized):\n[[1.096188, -0.221055, -0.064038, -0.015321], [-0.221055, 0.166609, 0.02823, 0.001308], [-0.064038, 0.02823, 0.023525, 0.002329], [-0.015321, 0.001308, 0.002329, 0.001426]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=1.0000, w_GLD=0.0000, w_VCIT=0.0000", "answer_numeric": 1.116801467634919, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_XRP-USD=1.0000, w_GLD=0.0000, w_VCIT=0.0000\nPortfolio annualized return: 49.59%, volatility: 40.82%\nSharpe ratio: (0.4959 - 0.0400) / 0.4082 = 1.1168", "metadata": {"weights": {"^VIX": 0.0, "XRP-USD": 1.0, "GLD": 0.0, "VCIT": 0.0}, "sharpe_ratio": 1.1168, "portfolio_return": 0.495853, "portfolio_vol": 0.408178, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190819_0138", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "HAUZ", "STIP"], "decision_date": "2019-08-19", "context_summary": "4-asset optimization. Max-Sharpe: 2.940. Portfolio: return=80.14%, vol=25.90%. Weights: w_XLF=0.0000, w_BTC-USD=0.2884, w_HAUZ=0.0000, w_STIP=0.7116.", "question": "Assets: XLF, BTC-USD, HAUZ, STIP\nAnnualized mean returns: XLF:-0.1319, BTC-USD:2.6640, HAUZ:-0.1183, STIP:0.0464\nCovariance matrix (annualized):\n[[0.038037, -0.009351, 0.016851, 1.1e-05], [-0.009351, 0.797586, 0.009495, 0.001473], [0.016851, 0.009495, 0.013023, 0.000382], [1.1e-05, 0.001473, 0.000382, 0.000198]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2884, w_HAUZ=0.0000, w_STIP=0.7116", "answer_numeric": 2.9402817373144896, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BTC-USD=0.2884, w_HAUZ=0.0000, w_STIP=0.7116\nPortfolio annualized return: 80.14%, volatility: 25.90%\nSharpe ratio: (0.8014 - 0.0400) / 0.2590 = 2.9403", "metadata": {"weights": {"XLF": 0.0, "BTC-USD": 0.2884, "HAUZ": 0.0, "STIP": 0.7116}, "sharpe_ratio": 2.9403, "portfolio_return": 0.801402, "portfolio_vol": 0.258955, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181004_0141", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ETH-USD", "ICSH", "HAUZ"], "decision_date": "2018-10-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.135. Portfolio: return=17.41%, vol=6.28%. Weights: w_VTI=1.0000, w_ETH-USD=0.0000, w_ICSH=0.0000, w_HAUZ=0.0000.", "question": "Assets: VTI, ETH-USD, ICSH, HAUZ\nAnnualized mean returns: VTI:0.1741, ETH-USD:-2.3599, ICSH:0.0257, HAUZ:-0.2345\nCovariance matrix (annualized):\n[[0.003942, 0.028043, -1.1e-05, 0.005075], [0.028043, 0.889348, -0.000781, 0.054392], [-1.1e-05, -0.000781, 1.6e-05, -9e-05], [0.005075, 0.054392, -9e-05, 0.015667]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_ETH-USD=0.0000, w_ICSH=0.0000, w_HAUZ=0.0000", "answer_numeric": 2.1350176089535386, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=1.0000, w_ETH-USD=0.0000, w_ICSH=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: 17.41%, volatility: 6.28%\nSharpe ratio: (0.1741 - 0.0400) / 0.0628 = 2.1350", "metadata": {"weights": {"VTI": 1.0, "ETH-USD": 0.0, "ICSH": 0.0, "HAUZ": 0.0}, "sharpe_ratio": 2.135, "portfolio_return": 0.174056, "portfolio_vol": 0.062789, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220707_0144", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "SOL-USD", "BNDX", "SGOV"], "decision_date": "2022-07-07", "context_summary": "4-asset optimization. Max-Sharpe: -0.427. Portfolio: return=-4.10%, vol=18.95%. Weights: w_XLP=1.0000, w_SOL-USD=0.0000, w_BNDX=0.0000, w_SGOV=0.0000.", "question": "Assets: XLP, SOL-USD, BNDX, SGOV\nAnnualized mean returns: XLP:-0.0410, SOL-USD:-5.9637, BNDX:-0.0341, SGOV:0.0076\nCovariance matrix (annualized):\n[[0.035921, 0.069582, 0.003164, 1.5e-05], [0.069582, 1.773357, 0.005436, -0.000147], [0.003164, 0.005436, 0.004855, -2.2e-05], [1.5e-05, -0.000147, -2.2e-05, 2e-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=1.0000, w_SOL-USD=0.0000, w_BNDX=0.0000, w_SGOV=0.0000", "answer_numeric": -0.42746748480117597, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=1.0000, w_SOL-USD=0.0000, w_BNDX=0.0000, w_SGOV=0.0000\nPortfolio annualized return: -4.10%, volatility: 18.95%\nSharpe ratio: (-0.0410 - 0.0400) / 0.1895 = -0.4275", "metadata": {"weights": {"XLP": 1.0, "SOL-USD": 0.0, "BNDX": 0.0, "SGOV": 0.0}, "sharpe_ratio": -0.4275, "portfolio_return": -0.041017, "portfolio_vol": 0.189528, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210914_0151", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "SOL-USD", "VNQI", "ICSH"], "decision_date": "2021-09-14", "context_summary": "4-asset optimization. Max-Sharpe: 9.201. Portfolio: return=1003.33%, vol=108.61%. Weights: w_QQQ=0.0000, w_SOL-USD=1.0000, w_VNQI=0.0000, w_ICSH=0.0000.", "question": "Assets: QQQ, SOL-USD, VNQI, ICSH\nAnnualized mean returns: QQQ:0.2638, SOL-USD:10.0333, VNQI:0.0286, ICSH:0.0040\nCovariance matrix (annualized):\n[[0.010538, 0.030073, 0.00505, -7e-06], [0.030073, 1.179606, 0.032149, 0.000462], [0.00505, 0.032149, 0.011865, 7.7e-05], [-7e-06, 0.000462, 7.7e-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_QQQ=0.0000, w_SOL-USD=1.0000, w_VNQI=0.0000, w_ICSH=0.0000", "answer_numeric": 9.20108114531169, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_SOL-USD=1.0000, w_VNQI=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 1003.33%, volatility: 108.61%\nSharpe ratio: (10.0333 - 0.0400) / 1.0861 = 9.2011", "metadata": {"weights": {"QQQ": 0.0, "SOL-USD": 1.0, "VNQI": 0.0, "ICSH": 0.0}, "sharpe_ratio": 9.2011, "portfolio_return": 10.033266, "portfolio_vol": 1.086097, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181126_0154", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNB-USD", "SCHP", "BIL"], "decision_date": "2018-11-26", "context_summary": "4-asset optimization. Max-Sharpe: -1.521. Portfolio: return=-40.13%, vol=29.01%. Weights: w_FXI=1.0000, w_BNB-USD=0.0000, w_SCHP=0.0000, w_BIL=0.0000.", "question": "Assets: FXI, BNB-USD, SCHP, BIL\nAnnualized mean returns: FXI:-0.4013, BNB-USD:-2.6669, SCHP:-0.0853, BIL:0.0206\nCovariance matrix (annualized):\n[[0.084147, 0.041958, -0.001769, 8.2e-05], [0.041958, 0.535317, 6.8e-05, 0.000308], [-0.001769, 6.8e-05, 0.001061, 4e-06], [8.2e-05, 0.000308, 4e-06, 3e-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_FXI=1.0000, w_BNB-USD=0.0000, w_SCHP=0.0000, w_BIL=0.0000", "answer_numeric": -1.5214486324590153, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=1.0000, w_BNB-USD=0.0000, w_SCHP=0.0000, w_BIL=0.0000\nPortfolio annualized return: -40.13%, volatility: 29.01%\nSharpe ratio: (-0.4013 - 0.0400) / 0.2901 = -1.5214", "metadata": {"weights": {"FXI": 1.0, "BNB-USD": 0.0, "SCHP": 0.0, "BIL": 0.0}, "sharpe_ratio": -1.5214, "portfolio_return": -0.401344, "portfolio_vol": 0.290081, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220110_0159", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "SGOV", "VNQI"], "decision_date": "2022-01-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.814. Portfolio: return=19.86%, vol=19.47%. Weights: w_XLRE=1.0000, w_ETH-USD=0.0000, w_SGOV=0.0000, w_VNQI=0.0000.", "question": "Assets: XLRE, ETH-USD, SGOV, VNQI\nAnnualized mean returns: XLRE:0.1986, ETH-USD:-3.0351, SGOV:0.0002, VNQI:-0.0979\nCovariance matrix (annualized):\n[[0.037914, 0.0341, 3.1e-05, 0.01627], [0.0341, 0.44736, 2.5e-05, 0.021089], [3.1e-05, 2.5e-05, 1e-06, 2e-06], [0.01627, 0.021089, 2e-06, 0.014179]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_ETH-USD=0.0000, w_SGOV=0.0000, w_VNQI=0.0000", "answer_numeric": 0.8144677140831786, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=1.0000, w_ETH-USD=0.0000, w_SGOV=0.0000, w_VNQI=0.0000\nPortfolio annualized return: 19.86%, volatility: 19.47%\nSharpe ratio: (0.1986 - 0.0400) / 0.1947 = 0.8145", "metadata": {"weights": {"XLRE": 1.0, "ETH-USD": 0.0, "SGOV": 0.0, "VNQI": 0.0}, "sharpe_ratio": 0.8145, "portfolio_return": 0.198589, "portfolio_vol": 0.194715, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220117_0162", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "ITB", "SGOV"], "decision_date": "2022-01-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.900. Portfolio: return=42.48%, vol=13.27%. Weights: w_XLP=1.0000, w_XRP-USD=0.0000, w_ITB=0.0000, w_SGOV=0.0000.", "question": "Assets: XLP, XRP-USD, ITB, SGOV\nAnnualized mean returns: XLP:0.4248, XRP-USD:-1.3459, ITB:-0.0793, SGOV:0.0008\nCovariance matrix (annualized):\n[[0.017606, -0.008812, 0.015771, 3.5e-05], [-0.008812, 0.413359, 0.052772, 5.3e-05], [0.015771, 0.052772, 0.078416, -9e-06], [3.5e-05, 5.3e-05, -9e-06, 1e-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=1.0000, w_XRP-USD=0.0000, w_ITB=0.0000, w_SGOV=0.0000", "answer_numeric": 2.9000782620633054, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=1.0000, w_XRP-USD=0.0000, w_ITB=0.0000, w_SGOV=0.0000\nPortfolio annualized return: 42.48%, volatility: 13.27%\nSharpe ratio: (0.4248 - 0.0400) / 0.1327 = 2.9001", "metadata": {"weights": {"XLP": 1.0, "XRP-USD": 0.0, "ITB": 0.0, "SGOV": 0.0}, "sharpe_ratio": 2.9001, "portfolio_return": 0.424801, "portfolio_vol": 0.132686, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20160816_0165", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "VCIT", "MORT"], "decision_date": "2016-08-16", "context_summary": "4-asset optimization. Max-Sharpe: 3.782. Portfolio: return=22.64%, vol=4.93%. Weights: w_VTI=0.1354, w_BTC-USD=0.0000, w_VCIT=0.6383, w_MORT=0.2263.", "question": "Assets: VTI, BTC-USD, VCIT, MORT\nAnnualized mean returns: VTI:0.3766, BTC-USD:-1.3108, VCIT:0.1095, MORT:0.4665\nCovariance matrix (annualized):\n[[0.020476, -0.001071, -0.001539, 0.011479], [-0.001071, 0.322931, 0.006148, 0.019675], [-0.001539, 0.006148, 0.001796, -0.000142], [0.011479, 0.019675, -0.000142, 0.018099]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1354, w_BTC-USD=0.0000, w_VCIT=0.6383, w_MORT=0.2263", "answer_numeric": 3.7818449858505074, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.1354, w_BTC-USD=0.0000, w_VCIT=0.6383, w_MORT=0.2263\nPortfolio annualized return: 22.64%, volatility: 4.93%\nSharpe ratio: (0.2264 - 0.0400) / 0.0493 = 3.7818", "metadata": {"weights": {"VTI": 0.1354, "BTC-USD": 0.0, "VCIT": 0.6383, "MORT": 0.2263}, "sharpe_ratio": 3.7818, "portfolio_return": 0.22644, "portfolio_vol": 0.049299, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210316_0168", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "SCHP", "IYR"], "decision_date": "2021-03-16", "context_summary": "4-asset optimization. Max-Sharpe: 6.636. Portfolio: return=192.61%, vol=28.42%. Weights: w_EEM=0.0000, w_BNB-USD=0.1285, w_SCHP=0.0000, w_IYR=0.8715.", "question": "Assets: EEM, BNB-USD, SCHP, IYR\nAnnualized mean returns: EEM:-0.1165, BNB-USD:10.7850, SCHP:-0.0668, IYR:0.6201\nCovariance matrix (annualized):\n[[0.061752, 0.178666, 0.003778, 0.017029], [0.178666, 3.302973, -0.006573, 0.04108], [0.003778, -0.006573, 0.003, 0.000743], [0.017029, 0.04108, 0.000743, 0.022448]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1285, w_SCHP=0.0000, w_IYR=0.8715", "answer_numeric": 6.6361928694851535, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_BNB-USD=0.1285, w_SCHP=0.0000, w_IYR=0.8715\nPortfolio annualized return: 192.61%, volatility: 28.42%\nSharpe ratio: (1.9261 - 0.0400) / 0.2842 = 6.6362", "metadata": {"weights": {"EEM": 0.0, "BNB-USD": 0.1285, "SCHP": 0.0, "IYR": 0.8715}, "sharpe_ratio": 6.6362, "portfolio_return": 1.926068, "portfolio_vol": 0.284209, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191203_0171", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "XRP-USD", "ITB", "GLD"], "decision_date": "2019-12-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.293. Portfolio: return=38.33%, vol=8.00%. Weights: w_ACWI=0.8741, w_XRP-USD=0.0000, w_ITB=0.1259, w_GLD=0.0000.", "question": "Assets: ACWI, XRP-USD, ITB, GLD\nAnnualized mean returns: ACWI:0.3920, XRP-USD:-0.5872, ITB:0.3227, GLD:-0.1762\nCovariance matrix (annualized):\n[[0.007199, -0.0065, 0.0021, -0.003107], [-0.0065, 0.270746, 0.003255, 0.012262], [0.0021, 0.003255, 0.027248, 0.006348], [-0.003107, 0.012262, 0.006348, 0.008957]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8741, w_XRP-USD=0.0000, w_ITB=0.1259, w_GLD=0.0000", "answer_numeric": 4.292752993763024, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.8741, w_XRP-USD=0.0000, w_ITB=0.1259, w_GLD=0.0000\nPortfolio annualized return: 38.33%, volatility: 8.00%\nSharpe ratio: (0.3833 - 0.0400) / 0.0800 = 4.2928", "metadata": {"weights": {"ACWI": 0.8741, "XRP-USD": 0.0, "ITB": 0.1259, "GLD": 0.0}, "sharpe_ratio": 4.2928, "portfolio_return": 0.383274, "portfolio_vol": 0.079966, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201006_0176", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "DOT-USD", "HYG", "DBC"], "decision_date": "2020-10-06", "context_summary": "4-asset optimization. Max-Sharpe: 1.950. Portfolio: return=120.93%, vol=59.97%. Weights: w_XLY=0.5321, w_DOT-USD=0.4679, w_HYG=0.0000, w_DBC=0.0000.", "question": "Assets: XLY, DOT-USD, HYG, DBC\nAnnualized mean returns: XLY:0.2813, DOT-USD:2.2645, HYG:0.0417, DBC:-0.2044\nCovariance matrix (annualized):\n[[0.043845, 0.108758, 0.011582, 0.015295], [0.108758, 1.338676, 0.035891, 0.107712], [0.011582, 0.035891, 0.004618, 0.007825], [0.015295, 0.107712, 0.007825, 0.033749]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5321, w_DOT-USD=0.4679, w_HYG=0.0000, w_DBC=0.0000", "answer_numeric": 1.949645452100955, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.5321, w_DOT-USD=0.4679, w_HYG=0.0000, w_DBC=0.0000\nPortfolio annualized return: 120.93%, volatility: 59.97%\nSharpe ratio: (1.2093 - 0.0400) / 0.5997 = 1.9496", "metadata": {"weights": {"XLY": 0.5321, "DOT-USD": 0.4679, "HYG": 0.0, "DBC": 0.0}, "sharpe_ratio": 1.9496, "portfolio_return": 1.209295, "portfolio_vol": 0.599748, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191114_0179", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ETH-USD", "INDS", "WEAT"], "decision_date": "2019-11-14", "context_summary": "4-asset optimization. Max-Sharpe: 3.367. Portfolio: return=31.69%, vol=8.23%. Weights: w_MTUM=0.0000, w_ETH-USD=0.0183, w_INDS=0.7228, w_WEAT=0.2589.", "question": "Assets: MTUM, ETH-USD, INDS, WEAT\nAnnualized mean returns: MTUM:0.1045, ETH-USD:0.4406, INDS:0.3271, WEAT:0.2800\nCovariance matrix (annualized):\n[[0.014518, 0.006422, 0.005397, -7.1e-05], [0.006422, 0.461239, 0.001995, -0.000413], [0.005397, 0.001995, 0.010539, -0.00248], [-7.1e-05, -0.000413, -0.00248, 0.029598]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.0183, w_INDS=0.7228, w_WEAT=0.2589", "answer_numeric": 3.366981559655665, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_ETH-USD=0.0183, w_INDS=0.7228, w_WEAT=0.2589\nPortfolio annualized return: 31.69%, volatility: 8.23%\nSharpe ratio: (0.3169 - 0.0400) / 0.0823 = 3.3670", "metadata": {"weights": {"MTUM": 0.0, "ETH-USD": 0.0183, "INDS": 0.7228, "WEAT": 0.2589}, "sharpe_ratio": 3.367, "portfolio_return": 0.316944, "portfolio_vol": 0.082253, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190826_0182", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XRP-USD", "ITB", "SLV"], "decision_date": "2019-08-26", "context_summary": "4-asset optimization. Max-Sharpe: 4.911. Portfolio: return=70.11%, vol=13.46%. Weights: w_MTUM=0.0000, w_XRP-USD=0.0000, w_ITB=0.3609, w_SLV=0.6391.", "question": "Assets: MTUM, XRP-USD, ITB, SLV\nAnnualized mean returns: MTUM:-0.0031, XRP-USD:-2.5047, ITB:0.4662, SLV:0.8338\nCovariance matrix (annualized):\n[[0.0311, 0.007374, 0.023471, -0.006395], [0.007374, 0.400285, -0.000189, 0.017816], [0.023471, -0.000189, 0.040051, -0.004333], [-0.006395, 0.017816, -0.004333, 0.0365]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=0.0000, w_ITB=0.3609, w_SLV=0.6391", "answer_numeric": 4.910620695677931, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_XRP-USD=0.0000, w_ITB=0.3609, w_SLV=0.6391\nPortfolio annualized return: 70.11%, volatility: 13.46%\nSharpe ratio: (0.7011 - 0.0400) / 0.1346 = 4.9106", "metadata": {"weights": {"MTUM": 0.0, "XRP-USD": 0.0, "ITB": 0.3609, "SLV": 0.6391}, "sharpe_ratio": 4.9106, "portfolio_return": 0.701139, "portfolio_vol": 0.134635, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200819_0196", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "SHV", "REZ"], "decision_date": "2020-08-19", "context_summary": "4-asset optimization. Max-Sharpe: 3.988. Portfolio: return=87.74%, vol=21.00%. Weights: w_XLV=0.5640, w_BTC-USD=0.4360, w_SHV=0.0000, w_REZ=0.0000.", "question": "Assets: XLV, BTC-USD, SHV, REZ\nAnnualized mean returns: XLV:0.4188, BTC-USD:1.4707, SHV:0.0009, REZ:0.1730\nCovariance matrix (annualized):\n[[0.021358, 0.018123, 3e-06, 0.01587], [0.018123, 0.14934, 3.7e-05, 0.012616], [3e-06, 3.7e-05, 1e-06, -7e-05], [0.01587, 0.012616, -7e-05, 0.052195]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5640, w_BTC-USD=0.4360, w_SHV=0.0000, w_REZ=0.0000", "answer_numeric": 3.9880725606228586, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.5640, w_BTC-USD=0.4360, w_SHV=0.0000, w_REZ=0.0000\nPortfolio annualized return: 87.74%, volatility: 21.00%\nSharpe ratio: (0.8774 - 0.0400) / 0.2100 = 3.9881", "metadata": {"weights": {"XLV": 0.564, "BTC-USD": 0.436, "SHV": 0.0, "REZ": 0.0}, "sharpe_ratio": 3.9881, "portfolio_return": 0.877444, "portfolio_vol": 0.209987, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211015_0199", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "UNG", "REZ"], "decision_date": "2021-10-15", "context_summary": "4-asset optimization. Max-Sharpe: 4.285. Portfolio: return=85.72%, vol=19.07%. Weights: w_^VIX=0.0745, w_BTC-USD=0.1151, w_UNG=0.2884, w_REZ=0.5220.", "question": "Assets: ^VIX, BTC-USD, UNG, REZ\nAnnualized mean returns: ^VIX:0.5118, BTC-USD:0.8213, UNG:2.2373, REZ:0.1518\nCovariance matrix (annualized):\n[[2.058649, -0.501819, -0.124885, -0.073818], [-0.501819, 0.466993, 0.010601, 0.029366], [-0.124885, 0.010601, 0.390067, -0.01275], [-0.073818, 0.029366, -0.01275, 0.020631]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0745, w_BTC-USD=0.1151, w_UNG=0.2884, w_REZ=0.5220", "answer_numeric": 4.285460048204892, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0745, w_BTC-USD=0.1151, w_UNG=0.2884, w_REZ=0.5220\nPortfolio annualized return: 85.72%, volatility: 19.07%\nSharpe ratio: (0.8572 - 0.0400) / 0.1907 = 4.2855", "metadata": {"weights": {"^VIX": 0.0745, "BTC-USD": 0.1151, "UNG": 0.2884, "REZ": 0.522}, "sharpe_ratio": 4.2855, "portfolio_return": 0.857174, "portfolio_vol": 0.190685, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211018_0202", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "SCHH", "SGOV"], "decision_date": "2021-10-18", "context_summary": "4-asset optimization. Max-Sharpe: 0.648. Portfolio: return=21.21%, vol=26.55%. Weights: w_QQQ=0.8059, w_ADA-USD=0.1941, w_SCHH=0.0000, w_SGOV=0.0000.", "question": "Assets: QQQ, ADA-USD, SCHH, SGOV\nAnnualized mean returns: QQQ:0.1200, ADA-USD:0.5948, SCHH:0.0755, SGOV:0.0001\nCovariance matrix (annualized):\n[[0.023633, 0.070548, 0.008032, 1e-06], [0.070548, 0.877273, 0.045323, -0.000181], [0.008032, 0.045323, 0.020327, -1.1e-05], [1e-06, -0.000181, -1.1e-05, 1e-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=0.8059, w_ADA-USD=0.1941, w_SCHH=0.0000, w_SGOV=0.0000", "answer_numeric": 0.6483749594385522, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.8059, w_ADA-USD=0.1941, w_SCHH=0.0000, w_SGOV=0.0000\nPortfolio annualized return: 21.21%, volatility: 26.55%\nSharpe ratio: (0.2121 - 0.0400) / 0.2655 = 0.6484", "metadata": {"weights": {"QQQ": 0.8059, "ADA-USD": 0.1941, "SCHH": 0.0, "SGOV": 0.0}, "sharpe_ratio": 0.6484, "portfolio_return": 0.212115, "portfolio_vol": 0.265456, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190104_0208", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "LINK-USD", "SHV", "USO"], "decision_date": "2019-01-04", "context_summary": "4-asset optimization. Max-Sharpe: 0.038. Portfolio: return=9.33%, vol=141.18%. Weights: w_XLK=0.0000, w_LINK-USD=1.0000, w_SHV=0.0000, w_USO=0.0000.", "question": "Assets: XLK, LINK-USD, SHV, USO\nAnnualized mean returns: XLK:-1.0247, LINK-USD:0.0933, SHV:0.0269, USO:-1.7530\nCovariance matrix (annualized):\n[[0.109727, 0.01649, -0.000166, 0.028635], [0.01649, 1.993219, -8e-05, -0.039361], [-0.000166, -8e-05, 4e-06, -0.000162], [0.028635, -0.039361, -0.000162, 0.215059]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=1.0000, w_SHV=0.0000, w_USO=0.0000", "answer_numeric": 0.03773983815917779, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_LINK-USD=1.0000, w_SHV=0.0000, w_USO=0.0000\nPortfolio annualized return: 9.33%, volatility: 141.18%\nSharpe ratio: (0.0933 - 0.0400) / 1.4118 = 0.0377", "metadata": {"weights": {"XLK": 0.0, "LINK-USD": 1.0, "SHV": 0.0, "USO": 0.0}, "sharpe_ratio": 0.0377, "portfolio_return": 0.093282, "portfolio_vol": 1.411814, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221028_0213", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BNB-USD", "TLH", "MORT"], "decision_date": "2022-10-28", "context_summary": "4-asset optimization. Max-Sharpe: 0.992. Portfolio: return=41.08%, vol=37.36%. Weights: w_QUAL=0.0000, w_BNB-USD=1.0000, w_TLH=0.0000, w_MORT=0.0000.", "question": "Assets: QUAL, BNB-USD, TLH, MORT\nAnnualized mean returns: QUAL:-0.3246, BNB-USD:0.4108, TLH:-0.7154, MORT:-1.3075\nCovariance matrix (annualized):\n[[0.062147, 0.047989, 0.011288, 0.063421], [0.047989, 0.139599, 0.020552, 0.058476], [0.011288, 0.020552, 0.022805, 0.028955], [0.063421, 0.058476, 0.028955, 0.129888]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNB-USD=1.0000, w_TLH=0.0000, w_MORT=0.0000", "answer_numeric": 0.9924076982298338, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_BNB-USD=1.0000, w_TLH=0.0000, w_MORT=0.0000\nPortfolio annualized return: 41.08%, volatility: 37.36%\nSharpe ratio: (0.4108 - 0.0400) / 0.3736 = 0.9924", "metadata": {"weights": {"QUAL": 0.0, "BNB-USD": 1.0, "TLH": 0.0, "MORT": 0.0}, "sharpe_ratio": 0.9924, "portfolio_return": 0.410793, "portfolio_vol": 0.37363, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191224_0217", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "MATIC-USD", "HYG", "ICSH"], "decision_date": "2019-12-24", "context_summary": "4-asset optimization. Max-Sharpe: 4.172. Portfolio: return=35.13%, vol=7.46%. Weights: w_VEA=0.7766, w_MATIC-USD=0.0231, w_HYG=0.2003, w_ICSH=0.0000.", "question": "Assets: VEA, MATIC-USD, HYG, ICSH\nAnnualized mean returns: VEA:0.3044, MATIC-USD:4.0737, HYG:0.1030, ICSH:0.0237\nCovariance matrix (annualized):\n[[0.005015, 0.02513, 0.001267, -7.9e-05], [0.02513, 2.289632, -0.001797, -0.001493], [0.001267, -0.001797, 0.000925, 3e-06], [-7.9e-05, -0.001493, 3e-06, 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_VEA=0.7766, w_MATIC-USD=0.0231, w_HYG=0.2003, w_ICSH=0.0000", "answer_numeric": 4.171868189115604, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.7766, w_MATIC-USD=0.0231, w_HYG=0.2003, w_ICSH=0.0000\nPortfolio annualized return: 35.13%, volatility: 7.46%\nSharpe ratio: (0.3513 - 0.0400) / 0.0746 = 4.1719", "metadata": {"weights": {"VEA": 0.7766, "MATIC-USD": 0.0231, "HYG": 0.2003, "ICSH": 0.0}, "sharpe_ratio": 4.1719, "portfolio_return": 0.351331, "portfolio_vol": 0.074626, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210705_0222", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "SHV", "ICSH"], "decision_date": "2021-07-05", "context_summary": "4-asset optimization. Max-Sharpe: 1.341. Portfolio: return=26.22%, vol=16.57%. Weights: w_MTUM=1.0000, w_LINK-USD=0.0000, w_SHV=0.0000, w_ICSH=0.0000.", "question": "Assets: MTUM, LINK-USD, SHV, ICSH\nAnnualized mean returns: MTUM:0.2622, LINK-USD:-3.9325, SHV:-0.0017, ICSH:0.0017\nCovariance matrix (annualized):\n[[0.027464, 0.093408, 4e-05, 5e-06], [0.093408, 2.449492, 0.000178, 0.000604], [4e-05, 0.000178, 2e-06, -1e-06], [5e-06, 0.000604, -1e-06, 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_MTUM=1.0000, w_LINK-USD=0.0000, w_SHV=0.0000, w_ICSH=0.0000", "answer_numeric": 1.3408389398009266, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=1.0000, w_LINK-USD=0.0000, w_SHV=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 26.22%, volatility: 16.57%\nSharpe ratio: (0.2622 - 0.0400) / 0.1657 = 1.3408", "metadata": {"weights": {"MTUM": 1.0, "LINK-USD": 0.0, "SHV": 0.0, "ICSH": 0.0}, "sharpe_ratio": 1.3408, "portfolio_return": 0.262206, "portfolio_vol": 0.165721, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190314_0235", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "TLT", "DBB"], "decision_date": "2019-03-14", "context_summary": "4-asset optimization. Max-Sharpe: 4.134. Portfolio: return=42.96%, vol=9.42%. Weights: w_FXI=0.1480, w_BTC-USD=0.1241, w_TLT=0.2159, w_DBB=0.5120.", "question": "Assets: FXI, BTC-USD, TLT, DBB\nAnnualized mean returns: FXI:0.5248, BTC-USD:0.5589, TLT:0.0757, DBB:0.5200\nCovariance matrix (annualized):\n[[0.035999, 0.002643, -0.001126, 0.011015], [0.002643, 0.082657, 0.001592, 0.001637], [-0.001126, 0.001592, 0.00671, -0.0013], [0.011015, 0.001637, -0.0013, 0.01834]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1480, w_BTC-USD=0.1241, w_TLT=0.2159, w_DBB=0.5120", "answer_numeric": 4.134114333487734, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.1480, w_BTC-USD=0.1241, w_TLT=0.2159, w_DBB=0.5120\nPortfolio annualized return: 42.96%, volatility: 9.42%\nSharpe ratio: (0.4296 - 0.0400) / 0.0942 = 4.1341", "metadata": {"weights": {"FXI": 0.148, "BTC-USD": 0.1241, "TLT": 0.2159, "DBB": 0.512}, "sharpe_ratio": 4.1341, "portfolio_return": 0.42963, "portfolio_vol": 0.094248, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220315_0238", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "BNDX", "SGOV"], "decision_date": "2022-03-15", "context_summary": "4-asset optimization. Max-Sharpe: -0.013. Portfolio: return=2.92%, vol=80.86%. Weights: w_XLU=0.0000, w_ETH-USD=1.0000, w_BNDX=0.0000, w_SGOV=0.0000.", "question": "Assets: XLU, ETH-USD, BNDX, SGOV\nAnnualized mean returns: XLU:0.0206, ETH-USD:0.0292, BNDX:-0.2433, SGOV:0.0016\nCovariance matrix (annualized):\n[[0.032957, -0.007469, 0.002855, -9e-06], [-0.007469, 0.6538, -0.007998, 8.8e-05], [0.002855, -0.007998, 0.003643, 2e-06], [-9e-06, 8.8e-05, 2e-06, 1e-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_ETH-USD=1.0000, w_BNDX=0.0000, w_SGOV=0.0000", "answer_numeric": -0.013310187648275636, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_ETH-USD=1.0000, w_BNDX=0.0000, w_SGOV=0.0000\nPortfolio annualized return: 2.92%, volatility: 80.86%\nSharpe ratio: (0.0292 - 0.0400) / 0.8086 = -0.0133", "metadata": {"weights": {"XLU": 0.0, "ETH-USD": 1.0, "BNDX": 0.0, "SGOV": 0.0}, "sharpe_ratio": -0.0133, "portfolio_return": 0.029238, "portfolio_vol": 0.808579, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221214_0249", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "SGOV", "STIP"], "decision_date": "2022-12-14", "context_summary": "4-asset optimization. Max-Sharpe: 0.518. Portfolio: return=5.83%, vol=3.53%. Weights: w_XLY=0.0000, w_ADA-USD=0.0000, w_SGOV=0.0000, w_STIP=1.0000.", "question": "Assets: XLY, ADA-USD, SGOV, STIP\nAnnualized mean returns: XLY:-0.0620, ADA-USD:0.0770, SGOV:0.0352, STIP:0.0583\nCovariance matrix (annualized):\n[[0.073365, 0.12199, -0.000135, 0.005417], [0.12199, 0.573205, -0.00049, 0.008578], [-0.000135, -0.00049, 7e-06, -0.0], [0.005417, 0.008578, -0.0, 0.001243]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=0.0000, w_SGOV=0.0000, w_STIP=1.0000", "answer_numeric": 0.5177729456306926, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_ADA-USD=0.0000, w_SGOV=0.0000, w_STIP=1.0000\nPortfolio annualized return: 5.83%, volatility: 3.53%\nSharpe ratio: (0.0583 - 0.0400) / 0.0353 = 0.5178", "metadata": {"weights": {"XLY": 0.0, "ADA-USD": 0.0, "SGOV": 0.0, "STIP": 1.0}, "sharpe_ratio": 0.5178, "portfolio_return": 0.058258, "portfolio_vol": 0.035263, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210512_0261", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "SGOV", "DBA"], "decision_date": "2021-05-12", "context_summary": "4-asset optimization. Max-Sharpe: 6.460. Portfolio: return=82.66%, vol=12.18%. Weights: w_XLRE=0.5854, w_ADA-USD=0.0612, w_SGOV=0.0000, w_DBA=0.3534.", "question": "Assets: XLRE, ADA-USD, SGOV, DBA\nAnnualized mean returns: XLRE:0.5206, ADA-USD:4.7526, SGOV:0.0006, DBA:0.6538\nCovariance matrix (annualized):\n[[0.017135, -0.007768, 1.2e-05, -0.001405], [-0.007768, 1.109188, 0.000147, 0.072228], [1.2e-05, 0.000147, 1e-06, -3.4e-05], [-0.001405, 0.072228, -3.4e-05, 0.022563]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5854, w_ADA-USD=0.0612, w_SGOV=0.0000, w_DBA=0.3534", "answer_numeric": 6.459654391887447, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.5854, w_ADA-USD=0.0612, w_SGOV=0.0000, w_DBA=0.3534\nPortfolio annualized return: 82.66%, volatility: 12.18%\nSharpe ratio: (0.8266 - 0.0400) / 0.1218 = 6.4597", "metadata": {"weights": {"XLRE": 0.5854, "ADA-USD": 0.0612, "SGOV": 0.0, "DBA": 0.3534}, "sharpe_ratio": 6.4597, "portfolio_return": 0.826568, "portfolio_vol": 0.121766, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210309_0266", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "SHY", "CPER"], "decision_date": "2021-03-09", "context_summary": "4-asset optimization. Max-Sharpe: 4.191. Portfolio: return=246.03%, vol=57.76%. Weights: w_XLY=0.0000, w_ADA-USD=0.3946, w_SHY=0.0000, w_CPER=0.6054.", "question": "Assets: XLY, ADA-USD, SHY, CPER\nAnnualized mean returns: XLY:-0.3272, ADA-USD:5.2630, SHY:-0.0057, CPER:0.6335\nCovariance matrix (annualized):\n[[0.054284, 0.100204, 0.000394, 0.023465], [0.100204, 1.719047, 0.00102, 0.068562], [0.000394, 0.00102, 3.5e-05, 4.6e-05], [0.023465, 0.068562, 4.6e-05, 0.090414]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=0.3946, w_SHY=0.0000, w_CPER=0.6054", "answer_numeric": 4.190591219924234, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_ADA-USD=0.3946, w_SHY=0.0000, w_CPER=0.6054\nPortfolio annualized return: 246.03%, volatility: 57.76%\nSharpe ratio: (2.4603 - 0.0400) / 0.5776 = 4.1906", "metadata": {"weights": {"XLY": 0.0, "ADA-USD": 0.3946, "SHY": 0.0, "CPER": 0.6054}, "sharpe_ratio": 4.1906, "portfolio_return": 2.460312, "portfolio_vol": 0.577559, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210907_0275", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "DOT-USD", "BIL", "IEF"], "decision_date": "2021-09-07", "context_summary": "4-asset optimization. Max-Sharpe: 4.334. Portfolio: return=377.96%, vol=86.28%. Weights: w_^VIX=0.1249, w_DOT-USD=0.8751, w_BIL=0.0000, w_IEF=0.0000.", "question": "Assets: ^VIX, DOT-USD, BIL, IEF\nAnnualized mean returns: ^VIX:-0.9007, DOT-USD:4.4474, BIL:-0.0013, IEF:0.0094\nCovariance matrix (annualized):\n[[1.596619, -0.441831, -7.1e-05, 0.024598], [-0.441831, 1.065647, -5.1e-05, -0.008039], [-7.1e-05, -5.1e-05, 3e-06, -4e-06], [0.024598, -0.008039, -4e-06, 0.00248]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1249, w_DOT-USD=0.8751, w_BIL=0.0000, w_IEF=0.0000", "answer_numeric": 4.334179606090085, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.1249, w_DOT-USD=0.8751, w_BIL=0.0000, w_IEF=0.0000\nPortfolio annualized return: 377.96%, volatility: 86.28%\nSharpe ratio: (3.7796 - 0.0400) / 0.8628 = 4.3342", "metadata": {"weights": {"^VIX": 0.1249, "DOT-USD": 0.8751, "BIL": 0.0, "IEF": 0.0}, "sharpe_ratio": 4.3342, "portfolio_return": 3.779593, "portfolio_vol": 0.862814, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190130_0278", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "LINK-USD", "SCHP", "BIL"], "decision_date": "2019-01-30", "context_summary": "4-asset optimization. Max-Sharpe: 2.334. Portfolio: return=278.56%, vol=117.63%. Weights: w_QQQ=0.0000, w_LINK-USD=0.8094, w_SCHP=0.1906, w_BIL=0.0000.", "question": "Assets: QQQ, LINK-USD, SCHP, BIL\nAnnualized mean returns: QQQ:-0.5221, LINK-USD:3.4274, SCHP:0.0594, BIL:0.0223\nCovariance matrix (annualized):\n[[0.081335, -0.044146, -0.004335, -0.000124], [-0.044146, 2.106301, 0.011833, -0.00016], [-0.004335, 0.011833, 0.001015, 1.3e-05], [-0.000124, -0.00016, 1.3e-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_QQQ=0.0000, w_LINK-USD=0.8094, w_SCHP=0.1906, w_BIL=0.0000", "answer_numeric": 2.334044209315536, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_LINK-USD=0.8094, w_SCHP=0.1906, w_BIL=0.0000\nPortfolio annualized return: 278.56%, volatility: 117.63%\nSharpe ratio: (2.7856 - 0.0400) / 1.1763 = 2.3340", "metadata": {"weights": {"QQQ": 0.0, "LINK-USD": 0.8094, "SCHP": 0.1906, "BIL": 0.0}, "sharpe_ratio": 2.334, "portfolio_return": 2.785558, "portfolio_vol": 1.176309, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180503_0281", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD", "BIL", "IYR"], "decision_date": "2018-05-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.846. Portfolio: return=40.21%, vol=12.72%. Weights: w_QQQ=0.0000, w_BNB-USD=0.0782, w_BIL=0.0000, w_IYR=0.9218.", "question": "Assets: QQQ, BNB-USD, BIL, IYR\nAnnualized mean returns: QQQ:-0.1578, BNB-USD:1.6678, BIL:0.0139, IYR:0.2947\nCovariance matrix (annualized):\n[[0.060791, -0.112897, -4.9e-05, 0.017212], [-0.112897, 1.496469, -0.000237, -0.047987], [-4.9e-05, -0.000237, 3e-06, 1.3e-05], [0.017212, -0.047987, 1.3e-05, 0.016417]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNB-USD=0.0782, w_BIL=0.0000, w_IYR=0.9218", "answer_numeric": 2.8464424256900926, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_BNB-USD=0.0782, w_BIL=0.0000, w_IYR=0.9218\nPortfolio annualized return: 40.21%, volatility: 12.72%\nSharpe ratio: (0.4021 - 0.0400) / 0.1272 = 2.8464", "metadata": {"weights": {"QQQ": 0.0, "BNB-USD": 0.0782, "BIL": 0.0, "IYR": 0.9218}, "sharpe_ratio": 2.8464, "portfolio_return": 0.40206, "portfolio_vol": 0.127198, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220114_0284", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "XHB", "ICSH"], "decision_date": "2022-01-14", "context_summary": "4-asset optimization. Max-Sharpe: -0.584. Portfolio: return=-10.09%, vol=24.14%. Weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_XHB=1.0000, w_ICSH=0.0000.", "question": "Assets: VEA, ADA-USD, XHB, ICSH\nAnnualized mean returns: VEA:-0.0623, ADA-USD:-2.7654, XHB:-0.1009, ICSH:-0.0034\nCovariance matrix (annualized):\n[[0.019954, 0.06629, 0.021509, -5.2e-05], [0.06629, 0.702358, 0.096919, -0.000151], [0.021509, 0.096919, 0.058293, -0.000258], [-5.2e-05, -0.000151, -0.000258, 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_ADA-USD=0.0000, w_XHB=1.0000, w_ICSH=0.0000", "answer_numeric": -0.5837906527650382, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_XHB=1.0000, w_ICSH=0.0000\nPortfolio annualized return: -10.09%, volatility: 24.14%\nSharpe ratio: (-0.1009 - 0.0400) / 0.2414 = -0.5838", "metadata": {"weights": {"VEA": 0.0, "ADA-USD": 0.0, "XHB": 1.0, "ICSH": 0.0}, "sharpe_ratio": -0.5838, "portfolio_return": -0.10095, "portfolio_vol": 0.241439, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220418_0291", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "IYR", "SOYB"], "decision_date": "2022-04-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.010. Portfolio: return=45.93%, vol=10.46%. Weights: w_IVV=0.0000, w_SOL-USD=0.0146, w_IYR=0.5016, w_SOYB=0.4838.", "question": "Assets: IVV, SOL-USD, IYR, SOYB\nAnnualized mean returns: IVV:-0.1068, SOL-USD:1.1080, IYR:0.3587, SOYB:0.5441\nCovariance matrix (annualized):\n[[0.048038, 0.094715, 0.031163, -0.014043], [0.094715, 0.85444, 0.025429, 0.005422], [0.031163, 0.025429, 0.034499, -0.019363], [-0.014043, 0.005422, -0.019363, 0.047083]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0146, w_IYR=0.5016, w_SOYB=0.4838", "answer_numeric": 4.010237838153351, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_SOL-USD=0.0146, w_IYR=0.5016, w_SOYB=0.4838\nPortfolio annualized return: 45.93%, volatility: 10.46%\nSharpe ratio: (0.4593 - 0.0400) / 0.1046 = 4.0102", "metadata": {"weights": {"IVV": 0.0, "SOL-USD": 0.0146, "IYR": 0.5016, "SOYB": 0.4838}, "sharpe_ratio": 4.0102, "portfolio_return": 0.459319, "portfolio_vol": 0.104562, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201005_0294", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SOL-USD", "WEAT", "HYG"], "decision_date": "2020-10-05", "context_summary": "4-asset optimization. Max-Sharpe: 2.493. Portfolio: return=68.28%, vol=25.78%. Weights: w_VTI=0.0000, w_SOL-USD=0.0808, w_WEAT=0.9192, w_HYG=0.0000.", "question": "Assets: VTI, SOL-USD, WEAT, HYG\nAnnualized mean returns: VTI:0.0931, SOL-USD:2.2239, WEAT:0.5472, HYG:-0.0460\nCovariance matrix (annualized):\n[[0.035013, 0.120367, 0.007882, 0.009015], [0.120367, 2.77279, 0.001855, 0.026887], [0.007882, 0.001855, 0.056904, 0.00502], [0.009015, 0.026887, 0.00502, 0.004114]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0808, w_WEAT=0.9192, w_HYG=0.0000", "answer_numeric": 2.4930801846761184, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_SOL-USD=0.0808, w_WEAT=0.9192, w_HYG=0.0000\nPortfolio annualized return: 68.28%, volatility: 25.78%\nSharpe ratio: (0.6828 - 0.0400) / 0.2578 = 2.4931", "metadata": {"weights": {"VTI": 0.0, "SOL-USD": 0.0808, "WEAT": 0.9192, "HYG": 0.0}, "sharpe_ratio": 2.4931, "portfolio_return": 0.682761, "portfolio_vol": 0.257818, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221202_0302", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BNB-USD", "INDS", "CSHI"], "decision_date": "2022-12-02", "context_summary": "4-asset optimization. Max-Sharpe: 3.987. Portfolio: return=27.17%, vol=5.81%. Weights: w_XLE=0.1692, w_BNB-USD=0.0000, w_INDS=0.0000, w_CSHI=0.8308.", "question": "Assets: XLE, BNB-USD, INDS, CSHI\nAnnualized mean returns: XLE:1.3090, BNB-USD:0.6612, INDS:0.2706, CSHI:0.0605\nCovariance matrix (annualized):\n[[0.102708, 0.098383, 0.029584, 0.001348], [0.098383, 0.539629, 0.07588, 0.000308], [0.029584, 0.07588, 0.078089, 0.001013], [0.001348, 0.000308, 0.001013, 8.4e-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_XLE=0.1692, w_BNB-USD=0.0000, w_INDS=0.0000, w_CSHI=0.8308", "answer_numeric": 3.9870218046401176, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.1692, w_BNB-USD=0.0000, w_INDS=0.0000, w_CSHI=0.8308\nPortfolio annualized return: 27.17%, volatility: 5.81%\nSharpe ratio: (0.2717 - 0.0400) / 0.0581 = 3.9870", "metadata": {"weights": {"XLE": 0.1692, "BNB-USD": 0.0, "INDS": 0.0, "CSHI": 0.8308}, "sharpe_ratio": 3.987, "portfolio_return": 0.271747, "portfolio_vol": 0.058125, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201203_0307", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ETH-USD", "INDS", "BIL"], "decision_date": "2020-12-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.373. Portfolio: return=227.20%, vol=51.04%. Weights: w_MTUM=0.1440, w_ETH-USD=0.8560, w_INDS=0.0000, w_BIL=0.0000.", "question": "Assets: MTUM, ETH-USD, INDS, BIL\nAnnualized mean returns: MTUM:0.3140, ETH-USD:2.6014, INDS:-0.0086, BIL:0.0002\nCovariance matrix (annualized):\n[[0.043526, 0.030039, 0.027545, -3.3e-05], [0.030039, 0.344187, 0.013338, -3e-05], [0.027545, 0.013338, 0.049622, -2.1e-05], [-3.3e-05, -3e-05, -2.1e-05, 1e-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=0.1440, w_ETH-USD=0.8560, w_INDS=0.0000, w_BIL=0.0000", "answer_numeric": 4.373021370742847, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.1440, w_ETH-USD=0.8560, w_INDS=0.0000, w_BIL=0.0000\nPortfolio annualized return: 227.20%, volatility: 51.04%\nSharpe ratio: (2.2720 - 0.0400) / 0.5104 = 4.3730", "metadata": {"weights": {"MTUM": 0.144, "ETH-USD": 0.856, "INDS": 0.0, "BIL": 0.0}, "sharpe_ratio": 4.373, "portfolio_return": 2.271951, "portfolio_vol": 0.510391, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210420_0310", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "UNG", "BIL"], "decision_date": "2021-04-20", "context_summary": "4-asset optimization. Max-Sharpe: 1.238. Portfolio: return=145.83%, vol=114.60%. Weights: w_EWJ=0.0000, w_LINK-USD=1.0000, w_UNG=0.0000, w_BIL=0.0000.", "question": "Assets: EWJ, LINK-USD, UNG, BIL\nAnnualized mean returns: EWJ:-0.1412, LINK-USD:1.4583, UNG:-0.4844, BIL:-0.0013\nCovariance matrix (annualized):\n[[0.02119, 0.030807, 0.004802, -6e-06], [0.030807, 1.313355, 0.032919, 6.1e-05], [0.004802, 0.032919, 0.081859, 7.7e-05], [-6e-06, 6.1e-05, 7.7e-05, 2e-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_LINK-USD=1.0000, w_UNG=0.0000, w_BIL=0.0000", "answer_numeric": 1.2375737790175747, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_LINK-USD=1.0000, w_UNG=0.0000, w_BIL=0.0000\nPortfolio annualized return: 145.83%, volatility: 114.60%\nSharpe ratio: (1.4583 - 0.0400) / 1.1460 = 1.2376", "metadata": {"weights": {"EWJ": 0.0, "LINK-USD": 1.0, "UNG": 0.0, "BIL": 0.0}, "sharpe_ratio": 1.2376, "portfolio_return": 1.458281, "portfolio_vol": 1.146017, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221124_0319", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "BIL", "DBA"], "decision_date": "2022-11-24", "context_summary": "4-asset optimization. Max-Sharpe: 2.324. Portfolio: return=56.63%, vol=22.65%. Weights: w_VEA=1.0000, w_ETH-USD=0.0000, w_BIL=0.0000, w_DBA=0.0000.", "question": "Assets: VEA, ETH-USD, BIL, DBA\nAnnualized mean returns: VEA:0.5663, ETH-USD:0.5142, BIL:0.0277, DBA:-0.1067\nCovariance matrix (annualized):\n[[0.051288, 0.080315, -3.7e-05, 0.007601], [0.080315, 0.626151, -0.000547, 0.011627], [-3.7e-05, -0.000547, 8e-06, 3e-06], [0.007601, 0.011627, 3e-06, 0.008767]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.0000, w_BIL=0.0000, w_DBA=0.0000", "answer_numeric": 2.3238578827313265, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=1.0000, w_ETH-USD=0.0000, w_BIL=0.0000, w_DBA=0.0000\nPortfolio annualized return: 56.63%, volatility: 22.65%\nSharpe ratio: (0.5663 - 0.0400) / 0.2265 = 2.3239", "metadata": {"weights": {"VEA": 1.0, "ETH-USD": 0.0, "BIL": 0.0, "DBA": 0.0}, "sharpe_ratio": 2.3239, "portfolio_return": 0.566283, "portfolio_vol": 0.22647, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180320_0322", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "ICSH", "IEF"], "decision_date": "2018-03-20", "context_summary": "4-asset optimization. Max-Sharpe: -2.088. Portfolio: return=-308.78%, vol=149.81%. Weights: w_FXI=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_IEF=0.0000.", "question": "Assets: FXI, LINK-USD, ICSH, IEF\nAnnualized mean returns: FXI:-0.2408, LINK-USD:-3.0878, ICSH:0.0101, IEF:-0.0861\nCovariance matrix (annualized):\n[[0.087382, 0.109566, 0.000127, -0.001031], [0.109566, 2.244393, 0.000557, -0.000713], [0.000127, 0.000557, 6.2e-05, -1.7e-05], [-0.001031, -0.000713, -1.7e-05, 0.002046]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ICSH=0.0000, w_IEF=0.0000", "answer_numeric": -2.087804982660621, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_IEF=0.0000\nPortfolio annualized return: -308.78%, volatility: 149.81%\nSharpe ratio: (-3.0878 - 0.0400) / 1.4981 = -2.0878", "metadata": {"weights": {"FXI": 0.0, "LINK-USD": 1.0, "ICSH": 0.0, "IEF": 0.0}, "sharpe_ratio": -2.0878, "portfolio_return": -3.087803, "portfolio_vol": 1.49813, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221107_0327", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "LINK-USD", "SLV", "ITB"], "decision_date": "2022-11-07", "context_summary": "4-asset optimization. Max-Sharpe: 1.283. Portfolio: return=34.44%, vol=23.73%. Weights: w_^VIX=0.1791, w_LINK-USD=0.1281, w_SLV=0.6928, w_ITB=0.0000.", "question": "Assets: ^VIX, LINK-USD, SLV, ITB\nAnnualized mean returns: ^VIX:-0.0220, LINK-USD:0.3802, SLV:0.4324, ITB:-0.0100\nCovariance matrix (annualized):\n[[0.476624, -0.182299, -0.106038, -0.149443], [-0.182299, 0.39401, 0.0651, 0.087292], [-0.106038, 0.0651, 0.120163, 0.076757], [-0.149443, 0.087292, 0.076757, 0.150172]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1791, w_LINK-USD=0.1281, w_SLV=0.6928, w_ITB=0.0000", "answer_numeric": 1.2826701324466303, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.1791, w_LINK-USD=0.1281, w_SLV=0.6928, w_ITB=0.0000\nPortfolio annualized return: 34.44%, volatility: 23.73%\nSharpe ratio: (0.3444 - 0.0400) / 0.2373 = 1.2827", "metadata": {"weights": {"^VIX": 0.1791, "LINK-USD": 0.1281, "SLV": 0.6928, "ITB": 0.0}, "sharpe_ratio": 1.2827, "portfolio_return": 0.344362, "portfolio_vol": 0.237288, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221026_0330", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "CSHI", "SCHP"], "decision_date": "2022-10-26", "context_summary": "4-asset optimization. Max-Sharpe: 0.618. Portfolio: return=27.16%, vol=37.47%. Weights: w_XLB=0.0000, w_BNB-USD=1.0000, w_CSHI=0.0000, w_SCHP=0.0000.", "question": "Assets: XLB, BNB-USD, CSHI, SCHP\nAnnualized mean returns: XLB:-0.2035, BNB-USD:0.2716, CSHI:0.0407, SCHP:-0.4024\nCovariance matrix (annualized):\n[[0.092573, 0.061324, 0.002489, 0.01157], [0.061324, 0.140373, 0.001357, 0.010055], [0.002489, 0.001357, 0.000126, 0.000276], [0.01157, 0.010055, 0.000276, 0.006409]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_CSHI=0.0000, w_SCHP=0.0000", "answer_numeric": 0.6180453298470482, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_BNB-USD=1.0000, w_CSHI=0.0000, w_SCHP=0.0000\nPortfolio annualized return: 27.16%, volatility: 37.47%\nSharpe ratio: (0.2716 - 0.0400) / 0.3747 = 0.6180", "metadata": {"weights": {"XLB": 0.0, "BNB-USD": 1.0, "CSHI": 0.0, "SCHP": 0.0}, "sharpe_ratio": 0.618, "portfolio_return": 0.271559, "portfolio_vol": 0.374663, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220628_0335", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "INDS", "SLV"], "decision_date": "2022-06-28", "context_summary": "4-asset optimization. Max-Sharpe: -3.068. Portfolio: return=-372.95%, vol=122.88%. Weights: w_XLP=0.0000, w_ADA-USD=1.0000, w_INDS=0.0000, w_SLV=0.0000.", "question": "Assets: XLP, ADA-USD, INDS, SLV\nAnnualized mean returns: XLP:-0.3079, ADA-USD:-3.7295, INDS:-1.0291, SLV:-0.5565\nCovariance matrix (annualized):\n[[0.042954, 0.086514, 0.048306, 0.021093], [0.086514, 1.510047, 0.198738, 0.092805], [0.048306, 0.198738, 0.103739, 0.041608], [0.021093, 0.092805, 0.041608, 0.077128]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=1.0000, w_INDS=0.0000, w_SLV=0.0000", "answer_numeric": -3.067511541888582, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_ADA-USD=1.0000, w_INDS=0.0000, w_SLV=0.0000\nPortfolio annualized return: -372.95%, volatility: 122.88%\nSharpe ratio: (-3.7295 - 0.0400) / 1.2288 = -3.0675", "metadata": {"weights": {"XLP": 0.0, "ADA-USD": 1.0, "INDS": 0.0, "SLV": 0.0}, "sharpe_ratio": -3.0675, "portfolio_return": -3.72948, "portfolio_vol": 1.22884, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200904_0338", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "BIL", "TLT"], "decision_date": "2020-09-04", "context_summary": "4-asset optimization. Max-Sharpe: 4.208. Portfolio: return=44.64%, vol=9.66%. Weights: w_IVV=0.7028, w_BNB-USD=0.0000, w_BIL=0.0000, w_TLT=0.2972.", "question": "Assets: IVV, BNB-USD, BIL, TLT\nAnnualized mean returns: IVV:0.5932, BNB-USD:0.8557, BIL:-0.0006, TLT:0.0994\nCovariance matrix (annualized):\n[[0.019677, 0.044485, 2.1e-05, -0.003806], [0.044485, 0.395771, 9.9e-05, -0.002333], [2.1e-05, 9.9e-05, 1e-06, 2.2e-05], [-0.003806, -0.002333, 2.2e-05, 0.013593]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7028, w_BNB-USD=0.0000, w_BIL=0.0000, w_TLT=0.2972", "answer_numeric": 4.207686936031347, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.7028, w_BNB-USD=0.0000, w_BIL=0.0000, w_TLT=0.2972\nPortfolio annualized return: 44.64%, volatility: 9.66%\nSharpe ratio: (0.4464 - 0.0400) / 0.0966 = 4.2077", "metadata": {"weights": {"IVV": 0.7028, "BNB-USD": 0.0, "BIL": 0.0, "TLT": 0.2972}, "sharpe_ratio": 4.2077, "portfolio_return": 0.446437, "portfolio_vol": 0.096594, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180227_0341", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "VNQ", "TIP"], "decision_date": "2018-02-27", "context_summary": "4-asset optimization. Max-Sharpe: -0.099. Portfolio: return=-14.78%, vol=190.35%. Weights: w_XLRE=0.0000, w_XRP-USD=1.0000, w_VNQ=0.0000, w_TIP=0.0000.", "question": "Assets: XLRE, XRP-USD, VNQ, TIP\nAnnualized mean returns: XLRE:-0.4261, XRP-USD:-0.1478, VNQ:-0.6190, TIP:0.0007\nCovariance matrix (annualized):\n[[0.037949, 0.058347, 0.03705, 9.2e-05], [0.058347, 3.623302, 0.070722, 0.002215], [0.03705, 0.070722, 0.037372, 6.7e-05], [9.2e-05, 0.002215, 6.7e-05, 0.000104]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=1.0000, w_VNQ=0.0000, w_TIP=0.0000", "answer_numeric": -0.0986761404085964, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_XRP-USD=1.0000, w_VNQ=0.0000, w_TIP=0.0000\nPortfolio annualized return: -14.78%, volatility: 190.35%\nSharpe ratio: (-0.1478 - 0.0400) / 1.9035 = -0.0987", "metadata": {"weights": {"XLRE": 0.0, "XRP-USD": 1.0, "VNQ": 0.0, "TIP": 0.0}, "sharpe_ratio": -0.0987, "portfolio_return": -0.14783, "portfolio_vol": 1.903497, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210922_0344", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "XRP-USD", "ITB", "PDBC"], "decision_date": "2021-09-22", "context_summary": "4-asset optimization. Max-Sharpe: 1.339. Portfolio: return=152.89%, vol=111.20%. Weights: w_EFA=0.0000, w_XRP-USD=1.0000, w_ITB=0.0000, w_PDBC=0.0000.", "question": "Assets: EFA, XRP-USD, ITB, PDBC\nAnnualized mean returns: EFA:0.0441, XRP-USD:1.5289, ITB:-0.1241, PDBC:0.0311\nCovariance matrix (annualized):\n[[0.010494, 0.041678, 0.012217, 0.008561], [0.041678, 1.236633, 0.090212, 0.026286], [0.012217, 0.090212, 0.045108, 0.013603], [0.008561, 0.026286, 0.013603, 0.034813]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ITB=0.0000, w_PDBC=0.0000", "answer_numeric": 1.3388725557734928, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_XRP-USD=1.0000, w_ITB=0.0000, w_PDBC=0.0000\nPortfolio annualized return: 152.89%, volatility: 111.20%\nSharpe ratio: (1.5289 - 0.0400) / 1.1120 = 1.3389", "metadata": {"weights": {"EFA": 0.0, "XRP-USD": 1.0, "ITB": 0.0, "PDBC": 0.0}, "sharpe_ratio": 1.3389, "portfolio_return": 1.52888, "portfolio_vol": 1.11204, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201027_0347", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "BIL", "SCHP"], "decision_date": "2020-10-27", "context_summary": "4-asset optimization. Max-Sharpe: 0.414. Portfolio: return=14.10%, vol=24.38%. Weights: w_XLB=1.0000, w_ADA-USD=0.0000, w_BIL=0.0000, w_SCHP=0.0000.", "question": "Assets: XLB, ADA-USD, BIL, SCHP\nAnnualized mean returns: XLB:0.1410, ADA-USD:-0.3266, BIL:0.0000, SCHP:0.0236\nCovariance matrix (annualized):\n[[0.059418, 0.089565, 2.8e-05, 0.000522], [0.089565, 0.742697, 0.000228, 0.007792], [2.8e-05, 0.000228, 2e-06, 6e-06], [0.000522, 0.007792, 6e-06, 0.000696]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_ADA-USD=0.0000, w_BIL=0.0000, w_SCHP=0.0000", "answer_numeric": 0.4143503810076163, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=1.0000, w_ADA-USD=0.0000, w_BIL=0.0000, w_SCHP=0.0000\nPortfolio annualized return: 14.10%, volatility: 24.38%\nSharpe ratio: (0.1410 - 0.0400) / 0.2438 = 0.4144", "metadata": {"weights": {"XLB": 1.0, "ADA-USD": 0.0, "BIL": 0.0, "SCHP": 0.0}, "sharpe_ratio": 0.4144, "portfolio_return": 0.141001, "portfolio_vol": 0.243757, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190926_0350", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BNB-USD", "ICSH", "UNG"], "decision_date": "2019-09-26", "context_summary": "4-asset optimization. Max-Sharpe: 2.688. Portfolio: return=87.34%, vol=31.00%. Weights: w_EFA=0.0000, w_BNB-USD=0.0000, w_ICSH=0.0000, w_UNG=1.0000.", "question": "Assets: EFA, BNB-USD, ICSH, UNG\nAnnualized mean returns: EFA:-0.0506, BNB-USD:-2.6433, ICSH:0.0279, UNG:0.8734\nCovariance matrix (annualized):\n[[0.019017, 0.011096, -7.9e-05, 0.010466], [0.011096, 0.466423, 0.000569, 0.003044], [-7.9e-05, 0.000569, 1.2e-05, -0.000297], [0.010466, 0.003044, -0.000297, 0.096117]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ICSH=0.0000, w_UNG=1.0000", "answer_numeric": 2.6880777353129517, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_BNB-USD=0.0000, w_ICSH=0.0000, w_UNG=1.0000\nPortfolio annualized return: 87.34%, volatility: 31.00%\nSharpe ratio: (0.8734 - 0.0400) / 0.3100 = 2.6881", "metadata": {"weights": {"EFA": 0.0, "BNB-USD": 0.0, "ICSH": 0.0, "UNG": 1.0}, "sharpe_ratio": 2.6881, "portfolio_return": 0.873377, "portfolio_vol": 0.310027, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20170207_0361", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "VCIT", "IYR"], "decision_date": "2017-02-07", "context_summary": "4-asset optimization. Max-Sharpe: 3.000. Portfolio: return=36.28%, vol=10.76%. Weights: w_EFA=0.8891, w_BTC-USD=0.1109, w_VCIT=0.0000, w_IYR=0.0000.", "question": "Assets: EFA, BTC-USD, VCIT, IYR\nAnnualized mean returns: EFA:0.2021, BTC-USD:1.6513, VCIT:0.0657, IYR:0.0858\nCovariance matrix (annualized):\n[[0.006938, -0.003189, 0.00088, 0.004196], [-0.003189, 0.546695, 0.006753, 0.014617], [0.00088, 0.006753, 0.001804, 0.002475], [0.004196, 0.014617, 0.002475, 0.015416]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8891, w_BTC-USD=0.1109, w_VCIT=0.0000, w_IYR=0.0000", "answer_numeric": 2.9996971476347833, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.8891, w_BTC-USD=0.1109, w_VCIT=0.0000, w_IYR=0.0000\nPortfolio annualized return: 36.28%, volatility: 10.76%\nSharpe ratio: (0.3628 - 0.0400) / 0.1076 = 2.9997", "metadata": {"weights": {"EFA": 0.8891, "BTC-USD": 0.1109, "VCIT": 0.0, "IYR": 0.0}, "sharpe_ratio": 2.9997, "portfolio_return": 0.362842, "portfolio_vol": 0.107625, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220721_0364", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "HAUZ", "BIL"], "decision_date": "2022-07-21", "context_summary": "4-asset optimization. Max-Sharpe: -2.055. Portfolio: return=-235.49%, vol=116.55%. Weights: w_EFA=0.0000, w_AVAX-USD=1.0000, w_HAUZ=0.0000, w_BIL=0.0000.", "question": "Assets: EFA, AVAX-USD, HAUZ, BIL\nAnnualized mean returns: EFA:-0.3300, AVAX-USD:-2.3549, HAUZ:-0.4682, BIL:0.0030\nCovariance matrix (annualized):\n[[0.048519, 0.097978, 0.038784, -3.3e-05], [0.097978, 1.358385, 0.079594, -0.000279], [0.038784, 0.079594, 0.035593, -2.9e-05], [-3.3e-05, -0.000279, -2.9e-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_EFA=0.0000, w_AVAX-USD=1.0000, w_HAUZ=0.0000, w_BIL=0.0000", "answer_numeric": -2.0548534729405055, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_AVAX-USD=1.0000, w_HAUZ=0.0000, w_BIL=0.0000\nPortfolio annualized return: -235.49%, volatility: 116.55%\nSharpe ratio: (-2.3549 - 0.0400) / 1.1655 = -2.0549", "metadata": {"weights": {"EFA": 0.0, "AVAX-USD": 1.0, "HAUZ": 0.0, "BIL": 0.0}, "sharpe_ratio": -2.0549, "portfolio_return": -2.354927, "portfolio_vol": 1.165498, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221020_0367", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SOL-USD", "WEAT", "MORT"], "decision_date": "2022-10-20", "context_summary": "4-asset optimization. Max-Sharpe: 1.147. Portfolio: return=47.74%, vol=38.12%. Weights: w_XLI=0.0000, w_SOL-USD=0.0000, w_WEAT=1.0000, w_MORT=0.0000.", "question": "Assets: XLI, SOL-USD, WEAT, MORT\nAnnualized mean returns: XLI:-0.6491, SOL-USD:-0.5111, WEAT:0.4774, MORT:-1.7510\nCovariance matrix (annualized):\n[[0.065526, 0.076528, -0.003201, 0.065039], [0.076528, 0.404213, -0.032721, 0.044265], [-0.003201, -0.032721, 0.145328, 0.01046], [0.065039, 0.044265, 0.01046, 0.122629]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_WEAT=1.0000, w_MORT=0.0000", "answer_numeric": 1.1473602067322437, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_SOL-USD=0.0000, w_WEAT=1.0000, w_MORT=0.0000\nPortfolio annualized return: 47.74%, volatility: 38.12%\nSharpe ratio: (0.4774 - 0.0400) / 0.3812 = 1.1474", "metadata": {"weights": {"XLI": 0.0, "SOL-USD": 0.0, "WEAT": 1.0, "MORT": 0.0}, "sharpe_ratio": 1.1474, "portfolio_return": 0.477395, "portfolio_vol": 0.381219, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210810_0370", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "DOT-USD", "SGOV", "ITB"], "decision_date": "2021-08-10", "context_summary": "4-asset optimization. Max-Sharpe: 3.412. Portfolio: return=38.68%, vol=10.16%. Weights: w_QUAL=1.0000, w_DOT-USD=0.0000, w_SGOV=0.0000, w_ITB=0.0000.", "question": "Assets: QUAL, DOT-USD, SGOV, ITB\nAnnualized mean returns: QUAL:0.3868, DOT-USD:-1.0678, SGOV:-0.0001, ITB:0.3473\nCovariance matrix (annualized):\n[[0.010327, -0.002573, 1.8e-05, 0.013158], [-0.002573, 1.164386, -0.00015, 0.005791], [1.8e-05, -0.00015, 1e-06, 3e-06], [0.013158, 0.005791, 3e-06, 0.045957]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_DOT-USD=0.0000, w_SGOV=0.0000, w_ITB=0.0000", "answer_numeric": 3.4122182453707564, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=1.0000, w_DOT-USD=0.0000, w_SGOV=0.0000, w_ITB=0.0000\nPortfolio annualized return: 38.68%, volatility: 10.16%\nSharpe ratio: (0.3868 - 0.0400) / 0.1016 = 3.4122", "metadata": {"weights": {"QUAL": 1.0, "DOT-USD": 0.0, "SGOV": 0.0, "ITB": 0.0}, "sharpe_ratio": 3.4122, "portfolio_return": 0.386759, "portfolio_vol": 0.101623, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190809_0377", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ADA-USD", "BIL", "HAUZ"], "decision_date": "2019-08-09", "context_summary": "4-asset optimization. Max-Sharpe: -1.159. Portfolio: return=-87.15%, vol=78.68%. Weights: w_EEM=0.0000, w_ADA-USD=1.0000, w_BIL=0.0000, w_HAUZ=0.0000.", "question": "Assets: EEM, ADA-USD, BIL, HAUZ\nAnnualized mean returns: EEM:-0.0640, ADA-USD:-0.8715, BIL:0.0224, HAUZ:-0.0381\nCovariance matrix (annualized):\n[[0.026028, -0.012452, 2.4e-05, 0.011684], [-0.012452, 0.619, 1.6e-05, -0.008779], [2.4e-05, 1.6e-05, 4e-06, 4.5e-05], [0.011684, -0.008779, 4.5e-05, 0.009573]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_BIL=0.0000, w_HAUZ=0.0000", "answer_numeric": -1.1585024520742924, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_ADA-USD=1.0000, w_BIL=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: -87.15%, volatility: 78.68%\nSharpe ratio: (-0.8715 - 0.0400) / 0.7868 = -1.1585", "metadata": {"weights": {"EEM": 0.0, "ADA-USD": 1.0, "BIL": 0.0, "HAUZ": 0.0}, "sharpe_ratio": -1.1585, "portfolio_return": -0.87147, "portfolio_vol": 0.786765, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221116_0382", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "SHY", "DBA"], "decision_date": "2022-11-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.561. Portfolio: return=285.66%, vol=109.99%. Weights: w_XLRE=0.0000, w_XRP-USD=1.0000, w_SHY=0.0000, w_DBA=0.0000.", "question": "Assets: XLRE, XRP-USD, SHY, DBA\nAnnualized mean returns: XLRE:-0.6083, XRP-USD:2.8566, SHY:-0.0326, DBA:-0.1093\nCovariance matrix (annualized):\n[[0.082781, 0.028856, 0.00337, 0.005461], [0.028856, 1.209814, -0.000796, 0.029056], [0.00337, -0.000796, 0.000509, 0.000441], [0.005461, 0.029056, 0.000441, 0.011919]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=1.0000, w_SHY=0.0000, w_DBA=0.0000", "answer_numeric": 2.5607247730309792, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_XRP-USD=1.0000, w_SHY=0.0000, w_DBA=0.0000\nPortfolio annualized return: 285.66%, volatility: 109.99%\nSharpe ratio: (2.8566 - 0.0400) / 1.0999 = 2.5607", "metadata": {"weights": {"XLRE": 0.0, "XRP-USD": 1.0, "SHY": 0.0, "DBA": 0.0}, "sharpe_ratio": 2.5607, "portfolio_return": 2.856581, "portfolio_vol": 1.099916, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210217_0385", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "SGOV", "SHV"], "decision_date": "2021-02-17", "context_summary": "4-asset optimization. Max-Sharpe: 5.714. Portfolio: return=185.50%, vol=31.77%. Weights: w_QUAL=0.8553, w_MATIC-USD=0.1447, w_SGOV=0.0000, w_SHV=0.0000.", "question": "Assets: QUAL, MATIC-USD, SGOV, SHV\nAnnualized mean returns: QUAL:0.2667, MATIC-USD:11.2446, SGOV:0.0003, SHV:0.0000\nCovariance matrix (annualized):\n[[0.018117, -0.01998, 0.0, -4.5e-05], [-0.01998, 4.423669, -0.000127, 0.000354], [0.0, -0.000127, 0.0, -0.0], [-4.5e-05, 0.000354, -0.0, 1e-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=0.8553, w_MATIC-USD=0.1447, w_SGOV=0.0000, w_SHV=0.0000", "answer_numeric": 5.713725811816572, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.8553, w_MATIC-USD=0.1447, w_SGOV=0.0000, w_SHV=0.0000\nPortfolio annualized return: 185.50%, volatility: 31.77%\nSharpe ratio: (1.8550 - 0.0400) / 0.3177 = 5.7137", "metadata": {"weights": {"QUAL": 0.8553, "MATIC-USD": 0.1447, "SGOV": 0.0, "SHV": 0.0}, "sharpe_ratio": 5.7137, "portfolio_return": 1.855014, "portfolio_vol": 0.317659, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220809_0390", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "MATIC-USD", "DBB", "IYR"], "decision_date": "2022-08-09", "context_summary": "4-asset optimization. Max-Sharpe: 3.195. Portfolio: return=200.57%, vol=61.52%. Weights: w_EEM=0.0000, w_MATIC-USD=0.3885, w_DBB=0.0000, w_IYR=0.6115.", "question": "Assets: EEM, MATIC-USD, DBB, IYR\nAnnualized mean returns: EEM:-0.2187, MATIC-USD:4.5061, DBB:-0.7275, IYR:0.4171\nCovariance matrix (annualized):\n[[0.041611, 0.127691, 0.021212, 0.026874], [0.127691, 2.035679, 0.071249, 0.112727], [0.021212, 0.071249, 0.065493, 0.017366], [0.026874, 0.112727, 0.017366, 0.047093]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3885, w_DBB=0.0000, w_IYR=0.6115", "answer_numeric": 3.1953617722172662, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_MATIC-USD=0.3885, w_DBB=0.0000, w_IYR=0.6115\nPortfolio annualized return: 200.57%, volatility: 61.52%\nSharpe ratio: (2.0057 - 0.0400) / 0.6152 = 3.1954", "metadata": {"weights": {"EEM": 0.0, "MATIC-USD": 0.3885, "DBB": 0.0, "IYR": 0.6115}, "sharpe_ratio": 3.1954, "portfolio_return": 2.005673, "portfolio_vol": 0.615165, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191112_0397", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "JNK", "INDS"], "decision_date": "2019-11-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.569. Portfolio: return=30.00%, vol=10.12%. Weights: w_IWM=0.0000, w_BTC-USD=0.0000, w_JNK=0.0000, w_INDS=1.0000.", "question": "Assets: IWM, BTC-USD, JNK, INDS\nAnnualized mean returns: IWM:0.0872, BTC-USD:-1.6849, JNK:0.0083, INDS:0.3000\nCovariance matrix (annualized):\n[[0.016527, 0.011237, 0.002883, 0.003622], [0.011237, 0.279983, 0.000736, -0.005333], [0.002883, 0.000736, 0.001019, 0.000339], [0.003622, -0.005333, 0.000339, 0.010246]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_JNK=0.0000, w_INDS=1.0000", "answer_numeric": 2.5687185450337693, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_BTC-USD=0.0000, w_JNK=0.0000, w_INDS=1.0000\nPortfolio annualized return: 30.00%, volatility: 10.12%\nSharpe ratio: (0.3000 - 0.0400) / 0.1012 = 2.5687", "metadata": {"weights": {"IWM": 0.0, "BTC-USD": 0.0, "JNK": 0.0, "INDS": 1.0}, "sharpe_ratio": 2.5687, "portfolio_return": 0.300015, "portfolio_vol": 0.101223, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191231_0402", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "IYR", "SHY"], "decision_date": "2019-12-31", "context_summary": "4-asset optimization. Max-Sharpe: 0.970. Portfolio: return=11.43%, vol=7.66%. Weights: w_EWJ=1.0000, w_BNB-USD=0.0000, w_IYR=0.0000, w_SHY=0.0000.", "question": "Assets: EWJ, BNB-USD, IYR, SHY\nAnnualized mean returns: EWJ:0.1143, BNB-USD:-1.9780, IYR:-0.0475, SHY:0.0076\nCovariance matrix (annualized):\n[[0.005875, -0.003872, -0.000864, -0.000262], [-0.003872, 0.303748, 0.020189, 0.000589], [-0.000864, 0.020189, 0.013527, 0.000477], [-0.000262, 0.000589, 0.000477, 8.4e-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_EWJ=1.0000, w_BNB-USD=0.0000, w_IYR=0.0000, w_SHY=0.0000", "answer_numeric": 0.9695874436905183, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=1.0000, w_BNB-USD=0.0000, w_IYR=0.0000, w_SHY=0.0000\nPortfolio annualized return: 11.43%, volatility: 7.66%\nSharpe ratio: (0.1143 - 0.0400) / 0.0766 = 0.9696", "metadata": {"weights": {"EWJ": 1.0, "BNB-USD": 0.0, "IYR": 0.0, "SHY": 0.0}, "sharpe_ratio": 0.9696, "portfolio_return": 0.114317, "portfolio_vol": 0.076648, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200521_0406", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "XHB", "TLH"], "decision_date": "2020-05-21", "context_summary": "4-asset optimization. Max-Sharpe: 6.423. Portfolio: return=166.13%, vol=25.24%. Weights: w_XLU=0.0000, w_LINK-USD=0.2958, w_XHB=0.1501, w_TLH=0.5541.", "question": "Assets: XLU, LINK-USD, XHB, TLH\nAnnualized mean returns: XLU:-0.1149, LINK-USD:4.7483, XHB:1.3571, TLH:0.0956\nCovariance matrix (annualized):\n[[0.130153, 0.0622, 0.136561, -0.01848], [0.0622, 0.581636, 0.110507, -0.006467], [0.136561, 0.110507, 0.246588, -0.032377], [-0.01848, -0.006467, -0.032377, 0.016171]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2958, w_XHB=0.1501, w_TLH=0.5541", "answer_numeric": 6.422643497624467, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_LINK-USD=0.2958, w_XHB=0.1501, w_TLH=0.5541\nPortfolio annualized return: 166.13%, volatility: 25.24%\nSharpe ratio: (1.6613 - 0.0400) / 0.2524 = 6.4226", "metadata": {"weights": {"XLU": 0.0, "LINK-USD": 0.2958, "XHB": 0.1501, "TLH": 0.5541}, "sharpe_ratio": 6.4226, "portfolio_return": 1.66129, "portfolio_vol": 0.252433, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210203_0413", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "MATIC-USD", "MORT", "BNO"], "decision_date": "2021-02-03", "context_summary": "4-asset optimization. Max-Sharpe: 5.192. Portfolio: return=139.71%, vol=26.14%. Weights: w_XLB=0.0000, w_MATIC-USD=0.0907, w_MORT=0.0000, w_BNO=0.9093.", "question": "Assets: XLB, MATIC-USD, MORT, BNO\nAnnualized mean returns: XLB:0.0408, MATIC-USD:4.8189, MORT:0.2597, BNO:1.0557\nCovariance matrix (annualized):\n[[0.03779, 0.045085, 0.026445, 0.022675], [0.045085, 3.353876, 0.001519, -0.070096], [0.026445, 0.001519, 0.044705, 0.017596], [0.022675, -0.070096, 0.017596, 0.06323]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0907, w_MORT=0.0000, w_BNO=0.9093", "answer_numeric": 5.192075226694015, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_MATIC-USD=0.0907, w_MORT=0.0000, w_BNO=0.9093\nPortfolio annualized return: 139.71%, volatility: 26.14%\nSharpe ratio: (1.3971 - 0.0400) / 0.2614 = 5.1921", "metadata": {"weights": {"XLB": 0.0, "MATIC-USD": 0.0907, "MORT": 0.0, "BNO": 0.9093}, "sharpe_ratio": 5.1921, "portfolio_return": 1.397138, "portfolio_vol": 0.261386, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210614_0416", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "AVAX-USD", "BIL", "UNG"], "decision_date": "2021-06-14", "context_summary": "4-asset optimization. Max-Sharpe: 5.731. Portfolio: return=61.72%, vol=10.07%. Weights: w_XLV=0.6251, w_AVAX-USD=0.0024, w_BIL=0.0000, w_UNG=0.3725.", "question": "Assets: XLV, AVAX-USD, BIL, UNG\nAnnualized mean returns: XLV:0.3035, AVAX-USD:0.0870, BIL:-0.0007, UNG:1.1470\nCovariance matrix (annualized):\n[[0.012635, 0.004819, 1.2e-05, -0.008804], [0.004819, 2.735375, 0.000112, -0.023291], [1.2e-05, 0.000112, 2e-06, 3.7e-05], [-0.008804, -0.023291, 3.7e-05, 0.067139]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6251, w_AVAX-USD=0.0024, w_BIL=0.0000, w_UNG=0.3725", "answer_numeric": 5.730972730105289, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.6251, w_AVAX-USD=0.0024, w_BIL=0.0000, w_UNG=0.3725\nPortfolio annualized return: 61.72%, volatility: 10.07%\nSharpe ratio: (0.6172 - 0.0400) / 0.1007 = 5.7310", "metadata": {"weights": {"XLV": 0.6251, "AVAX-USD": 0.0024, "BIL": 0.0, "UNG": 0.3725}, "sharpe_ratio": 5.731, "portfolio_return": 0.617183, "portfolio_vol": 0.100713, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210514_0419", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "SOL-USD", "TLH", "BIL"], "decision_date": "2021-05-14", "context_summary": "4-asset optimization. Max-Sharpe: 0.867. Portfolio: return=15.08%, vol=12.78%. Weights: w_ACWI=0.9597, w_SOL-USD=0.0403, w_TLH=0.0000, w_BIL=0.0000.", "question": "Assets: ACWI, SOL-USD, TLH, BIL\nAnnualized mean returns: ACWI:0.1442, SOL-USD:0.3092, TLH:0.0371, BIL:-0.0013\nCovariance matrix (annualized):\n[[0.015608, 0.009451, 0.002412, 2.3e-05], [0.009451, 0.759903, 0.005981, 0.000293], [0.002412, 0.005981, 0.00687, 3.2e-05], [2.3e-05, 0.000293, 3.2e-05, 2e-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=0.9597, w_SOL-USD=0.0403, w_TLH=0.0000, w_BIL=0.0000", "answer_numeric": 0.8668100473975431, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.9597, w_SOL-USD=0.0403, w_TLH=0.0000, w_BIL=0.0000\nPortfolio annualized return: 15.08%, volatility: 12.78%\nSharpe ratio: (0.1508 - 0.0400) / 0.1278 = 0.8668", "metadata": {"weights": {"ACWI": 0.9597, "SOL-USD": 0.0403, "TLH": 0.0, "BIL": 0.0}, "sharpe_ratio": 0.8668, "portfolio_return": 0.150805, "portfolio_vol": 0.127831, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220425_0427", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "SOL-USD", "TLT", "VNQI"], "decision_date": "2022-04-25", "context_summary": "4-asset optimization. Max-Sharpe: 2.031. Portfolio: return=78.86%, vol=36.86%. Weights: w_XLB=0.6746, w_SOL-USD=0.3254, w_TLT=0.0000, w_VNQI=0.0000.", "question": "Assets: XLB, SOL-USD, TLT, VNQI\nAnnualized mean returns: XLB:0.3438, SOL-USD:1.7107, TLT:-0.6834, VNQI:-0.2800\nCovariance matrix (annualized):\n[[0.051587, 0.06251, -0.004946, 0.02932], [0.06251, 0.802252, 0.055228, 0.050316], [-0.004946, 0.055228, 0.038965, -0.002511], [0.02932, 0.050316, -0.002511, 0.030215]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6746, w_SOL-USD=0.3254, w_TLT=0.0000, w_VNQI=0.0000", "answer_numeric": 2.0308909062362055, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.6746, w_SOL-USD=0.3254, w_TLT=0.0000, w_VNQI=0.0000\nPortfolio annualized return: 78.86%, volatility: 36.86%\nSharpe ratio: (0.7886 - 0.0400) / 0.3686 = 2.0309", "metadata": {"weights": {"XLB": 0.6746, "SOL-USD": 0.3254, "TLT": 0.0, "VNQI": 0.0}, "sharpe_ratio": 2.0309, "portfolio_return": 0.788645, "portfolio_vol": 0.368629, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200206_0438", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "DBC", "XHB"], "decision_date": "2020-02-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.375. Portfolio: return=36.70%, vol=13.77%. Weights: w_XLF=0.0000, w_XRP-USD=0.0485, w_DBC=0.0000, w_XHB=0.9515.", "question": "Assets: XLF, XRP-USD, DBC, XHB\nAnnualized mean returns: XLF:0.1776, XRP-USD:0.7274, DBC:-0.3592, XHB:0.3486\nCovariance matrix (annualized):\n[[0.018162, 0.002507, 0.005378, 0.010616], [0.002507, 0.438831, 0.012829, 0.019528], [0.005378, 0.012829, 0.01548, 0.002173], [0.010616, 0.019528, 0.002173, 0.017814]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0485, w_DBC=0.0000, w_XHB=0.9515", "answer_numeric": 2.3746404922991142, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_XRP-USD=0.0485, w_DBC=0.0000, w_XHB=0.9515\nPortfolio annualized return: 36.70%, volatility: 13.77%\nSharpe ratio: (0.3670 - 0.0400) / 0.1377 = 2.3746", "metadata": {"weights": {"XLF": 0.0, "XRP-USD": 0.0485, "DBC": 0.0, "XHB": 0.9515}, "sharpe_ratio": 2.3746, "portfolio_return": 0.366994, "portfolio_vol": 0.137703, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220810_0443", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ADA-USD", "TLH", "SGOV"], "decision_date": "2022-08-10", "context_summary": "4-asset optimization. Max-Sharpe: 2.531. Portfolio: return=39.95%, vol=14.21%. Weights: w_IWM=0.4597, w_ADA-USD=0.0000, w_TLH=0.5403, w_SGOV=0.0000.", "question": "Assets: IWM, ADA-USD, TLH, SGOV\nAnnualized mean returns: IWM:0.5313, ADA-USD:-0.1963, TLH:0.2874, SGOV:0.0135\nCovariance matrix (annualized):\n[[0.06259, 0.104799, -0.002204, -8.2e-05], [0.104799, 0.536535, -0.007335, -7.6e-05], [-0.002204, -0.007335, 0.027575, 3.9e-05], [-8.2e-05, -7.6e-05, 3.9e-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_IWM=0.4597, w_ADA-USD=0.0000, w_TLH=0.5403, w_SGOV=0.0000", "answer_numeric": 2.530707645178771, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.4597, w_ADA-USD=0.0000, w_TLH=0.5403, w_SGOV=0.0000\nPortfolio annualized return: 39.95%, volatility: 14.21%\nSharpe ratio: (0.3995 - 0.0400) / 0.1421 = 2.5307", "metadata": {"weights": {"IWM": 0.4597, "ADA-USD": 0.0, "TLH": 0.5403, "SGOV": 0.0}, "sharpe_ratio": 2.5307, "portfolio_return": 0.399517, "portfolio_vol": 0.142062, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200311_0448", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "MATIC-USD", "XHB", "HYG"], "decision_date": "2020-03-11", "context_summary": "4-asset optimization. Max-Sharpe: 4.602. Portfolio: return=454.95%, vol=97.98%. Weights: w_XLP=0.0000, w_MATIC-USD=1.0000, w_XHB=0.0000, w_HYG=0.0000.", "question": "Assets: XLP, MATIC-USD, XHB, HYG\nAnnualized mean returns: XLP:-0.3984, MATIC-USD:4.5495, XHB:-0.4376, HYG:-0.1821\nCovariance matrix (annualized):\n[[0.032755, 0.043926, 0.04999, 0.014588], [0.043926, 0.960019, 0.087176, 0.019061], [0.04999, 0.087176, 0.094586, 0.025407], [0.014588, 0.019061, 0.025407, 0.009851]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_XHB=0.0000, w_HYG=0.0000", "answer_numeric": 4.602484718611735, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_MATIC-USD=1.0000, w_XHB=0.0000, w_HYG=0.0000\nPortfolio annualized return: 454.95%, volatility: 97.98%\nSharpe ratio: (4.5495 - 0.0400) / 0.9798 = 4.6025", "metadata": {"weights": {"XLP": 0.0, "MATIC-USD": 1.0, "XHB": 0.0, "HYG": 0.0}, "sharpe_ratio": 4.6025, "portfolio_return": 4.54954, "portfolio_vol": 0.979806, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190225_0452", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ETH-USD", "UNG", "IYR"], "decision_date": "2019-02-25", "context_summary": "4-asset optimization. Max-Sharpe: 8.386. Portfolio: return=81.48%, vol=9.24%. Weights: w_MTUM=0.1771, w_ETH-USD=0.0408, w_UNG=0.0000, w_IYR=0.7821.", "question": "Assets: MTUM, ETH-USD, UNG, IYR\nAnnualized mean returns: MTUM:0.7663, ETH-USD:-0.0536, UNG:-1.1399, IYR:0.8710\nCovariance matrix (annualized):\n[[0.024049, -0.007795, 0.008548, 0.005191], [-0.007795, 0.791109, 0.066059, -0.040799], [0.008548, 0.066059, 0.255287, -0.002017], [0.005191, -0.040799, -0.002017, 0.012657]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1771, w_ETH-USD=0.0408, w_UNG=0.0000, w_IYR=0.7821", "answer_numeric": 8.386285940001212, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.1771, w_ETH-USD=0.0408, w_UNG=0.0000, w_IYR=0.7821\nPortfolio annualized return: 81.48%, volatility: 9.24%\nSharpe ratio: (0.8148 - 0.0400) / 0.0924 = 8.3863", "metadata": {"weights": {"MTUM": 0.1771, "ETH-USD": 0.0408, "UNG": 0.0, "IYR": 0.7821}, "sharpe_ratio": 8.3863, "portfolio_return": 0.814768, "portfolio_vol": 0.092385, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190207_0457", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "STIP", "BIL"], "decision_date": "2019-02-07", "context_summary": "4-asset optimization. Max-Sharpe: 0.043. Portfolio: return=6.51%, vol=57.98%. Weights: w_XLV=0.0000, w_BTC-USD=1.0000, w_STIP=0.0000, w_BIL=0.0000.", "question": "Assets: XLV, BTC-USD, STIP, BIL\nAnnualized mean returns: XLV:-0.0729, BTC-USD:0.0651, STIP:0.0397, BIL:0.0227\nCovariance matrix (annualized):\n[[0.0398, -0.027619, 0.000201, -1.6e-05], [-0.027619, 0.336167, -0.00111, -0.000177], [0.000201, -0.00111, 0.00027, 1e-05], [-1.6e-05, -0.000177, 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_XLV=0.0000, w_BTC-USD=1.0000, w_STIP=0.0000, w_BIL=0.0000", "answer_numeric": 0.043279028686635974, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_BTC-USD=1.0000, w_STIP=0.0000, w_BIL=0.0000\nPortfolio annualized return: 6.51%, volatility: 57.98%\nSharpe ratio: (0.0651 - 0.0400) / 0.5798 = 0.0433", "metadata": {"weights": {"XLV": 0.0, "BTC-USD": 1.0, "STIP": 0.0, "BIL": 0.0}, "sharpe_ratio": 0.0433, "portfolio_return": 0.065093, "portfolio_vol": 0.579799, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210824_0460", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "XHB", "BIL"], "decision_date": "2021-08-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.914. Portfolio: return=63.73%, vol=15.26%. Weights: w_IVV=0.8428, w_BNB-USD=0.1572, w_XHB=0.0000, w_BIL=0.0000.", "question": "Assets: IVV, BNB-USD, XHB, BIL\nAnnualized mean returns: IVV:0.3133, BNB-USD:2.3749, XHB:0.3950, BIL:-0.0020\nCovariance matrix (annualized):\n[[0.009306, 0.017881, 0.01448, -2e-06], [0.017881, 0.483332, 0.028238, -9e-05], [0.01448, 0.028238, 0.047675, -2.2e-05], [-2e-06, -9e-05, -2.2e-05, 2e-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=0.8428, w_BNB-USD=0.1572, w_XHB=0.0000, w_BIL=0.0000", "answer_numeric": 3.9139765031550153, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.8428, w_BNB-USD=0.1572, w_XHB=0.0000, w_BIL=0.0000\nPortfolio annualized return: 63.73%, volatility: 15.26%\nSharpe ratio: (0.6373 - 0.0400) / 0.1526 = 3.9140", "metadata": {"weights": {"IVV": 0.8428, "BNB-USD": 0.1572, "XHB": 0.0, "BIL": 0.0}, "sharpe_ratio": 3.914, "portfolio_return": 0.637251, "portfolio_vol": 0.152594, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201020_0467", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "STIP", "CORN"], "decision_date": "2020-10-20", "context_summary": "4-asset optimization. Max-Sharpe: 4.651. Portfolio: return=70.19%, vol=14.23%. Weights: w_XLB=0.0777, w_ADA-USD=0.0000, w_STIP=0.0000, w_CORN=0.9223.", "question": "Assets: XLB, ADA-USD, STIP, CORN\nAnnualized mean returns: XLB:0.3449, ADA-USD:-1.3298, STIP:0.0317, CORN:0.7320\nCovariance matrix (annualized):\n[[0.057546, 0.097111, 0.001215, 0.005268], [0.097111, 0.812388, 0.004277, 0.007587], [0.001215, 0.004277, 0.000151, 0.000355], [0.005268, 0.007587, 0.000355, 0.022512]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0777, w_ADA-USD=0.0000, w_STIP=0.0000, w_CORN=0.9223", "answer_numeric": 4.6510422722202795, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0777, w_ADA-USD=0.0000, w_STIP=0.0000, w_CORN=0.9223\nPortfolio annualized return: 70.19%, volatility: 14.23%\nSharpe ratio: (0.7019 - 0.0400) / 0.1423 = 4.6510", "metadata": {"weights": {"XLB": 0.0777, "ADA-USD": 0.0, "STIP": 0.0, "CORN": 0.9223}, "sharpe_ratio": 4.651, "portfolio_return": 0.70189, "portfolio_vol": 0.14231, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200724_0476", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "BNO", "SHY"], "decision_date": "2020-07-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.421. Portfolio: return=117.97%, vol=33.32%. Weights: w_XLRE=0.1985, w_XRP-USD=0.0000, w_BNO=0.8015, w_SHY=0.0000.", "question": "Assets: XLRE, XRP-USD, BNO, SHY\nAnnualized mean returns: XLRE:0.5735, XRP-USD:0.3507, BNO:1.3298, SHY:0.0042\nCovariance matrix (annualized):\n[[0.070366, 0.031833, 0.047398, -0.000348], [0.031833, 0.178387, 0.031221, 3.5e-05], [0.047398, 0.031221, 0.144981, 5.3e-05], [-0.000348, 3.5e-05, 5.3e-05, 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_XLRE=0.1985, w_XRP-USD=0.0000, w_BNO=0.8015, w_SHY=0.0000", "answer_numeric": 3.4209268632887, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.1985, w_XRP-USD=0.0000, w_BNO=0.8015, w_SHY=0.0000\nPortfolio annualized return: 117.97%, volatility: 33.32%\nSharpe ratio: (1.1797 - 0.0400) / 0.3332 = 3.4209", "metadata": {"weights": {"XLRE": 0.1985, "XRP-USD": 0.0, "BNO": 0.8015, "SHY": 0.0}, "sharpe_ratio": 3.4209, "portfolio_return": 1.179723, "portfolio_vol": 0.333162, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220930_0479", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BTC-USD", "CORN", "INDS"], "decision_date": "2022-09-30", "context_summary": "4-asset optimization. Max-Sharpe: 1.711. Portfolio: return=39.68%, vol=20.86%. Weights: w_EWJ=0.0000, w_BTC-USD=0.0000, w_CORN=1.0000, w_INDS=0.0000.", "question": "Assets: EWJ, BTC-USD, CORN, INDS\nAnnualized mean returns: EWJ:-0.7728, BTC-USD:-0.6268, CORN:0.3968, INDS:-1.3083\nCovariance matrix (annualized):\n[[0.037885, 0.068032, 0.002789, 0.028338], [0.068032, 0.298551, 0.004222, 0.052892], [0.002789, 0.004222, 0.043497, 0.003832], [0.028338, 0.052892, 0.003832, 0.054414]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.0000, w_CORN=1.0000, w_INDS=0.0000", "answer_numeric": 1.710638314206923, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BTC-USD=0.0000, w_CORN=1.0000, w_INDS=0.0000\nPortfolio annualized return: 39.68%, volatility: 20.86%\nSharpe ratio: (0.3968 - 0.0400) / 0.2086 = 1.7106", "metadata": {"weights": {"EWJ": 0.0, "BTC-USD": 0.0, "CORN": 1.0, "INDS": 0.0}, "sharpe_ratio": 1.7106, "portfolio_return": 0.396769, "portfolio_vol": 0.208559, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221220_0482", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BNB-USD", "BIL", "REZ"], "decision_date": "2022-12-20", "context_summary": "4-asset optimization. Max-Sharpe: 0.636. Portfolio: return=18.51%, vol=22.80%. Weights: w_QUAL=1.0000, w_BNB-USD=0.0000, w_BIL=0.0000, w_REZ=0.0000.", "question": "Assets: QUAL, BNB-USD, BIL, REZ\nAnnualized mean returns: QUAL:0.1851, BNB-USD:-0.6001, BIL:0.0349, REZ:-0.1625\nCovariance matrix (annualized):\n[[0.051994, 0.093514, -0.000207, 0.041601], [0.093514, 0.654099, -0.000215, 0.097088], [-0.000207, -0.000215, 8e-06, -7e-05], [0.041601, 0.097088, -7e-05, 0.059504]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNB-USD=0.0000, w_BIL=0.0000, w_REZ=0.0000", "answer_numeric": 0.6363178063489681, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=1.0000, w_BNB-USD=0.0000, w_BIL=0.0000, w_REZ=0.0000\nPortfolio annualized return: 18.51%, volatility: 22.80%\nSharpe ratio: (0.1851 - 0.0400) / 0.2280 = 0.6363", "metadata": {"weights": {"QUAL": 1.0, "BNB-USD": 0.0, "BIL": 0.0, "REZ": 0.0}, "sharpe_ratio": 0.6363, "portfolio_return": 0.185094, "portfolio_vol": 0.228021, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200914_0489", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ADA-USD", "VNQ", "TIP"], "decision_date": "2020-09-14", "context_summary": "4-asset optimization. Max-Sharpe: 2.896. Portfolio: return=7.87%, vol=1.34%. Weights: w_XLV=0.0000, w_ADA-USD=0.0000, w_VNQ=0.0102, w_TIP=0.9898.", "question": "Assets: XLV, ADA-USD, VNQ, TIP\nAnnualized mean returns: XLV:-0.0023, ADA-USD:-2.5478, VNQ:0.1421, TIP:0.0780\nCovariance matrix (annualized):\n[[0.022051, 0.004165, 0.014349, 0.000752], [0.004165, 0.578859, 0.007012, 0.004307], [0.014349, 0.007012, 0.029507, 0.00017], [0.000752, 0.004307, 0.00017, 0.000176]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_VNQ=0.0102, w_TIP=0.9898", "answer_numeric": 2.89620292761786, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_ADA-USD=0.0000, w_VNQ=0.0102, w_TIP=0.9898\nPortfolio annualized return: 7.87%, volatility: 1.34%\nSharpe ratio: (0.0787 - 0.0400) / 0.0134 = 2.8962", "metadata": {"weights": {"XLV": 0.0, "ADA-USD": 0.0, "VNQ": 0.0102, "TIP": 0.9898}, "sharpe_ratio": 2.8962, "portfolio_return": 0.078705, "portfolio_vol": 0.013364, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20160824_0503", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "XHB", "BNO"], "decision_date": "2016-08-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.901. Portfolio: return=65.35%, vol=15.73%. Weights: w_VLUE=0.2872, w_BTC-USD=0.0000, w_XHB=0.7128, w_BNO=0.0000.", "question": "Assets: VLUE, BTC-USD, XHB, BNO\nAnnualized mean returns: VLUE:0.5247, BTC-USD:-0.2991, XHB:0.7054, BNO:0.1035\nCovariance matrix (annualized):\n[[0.018947, 0.011985, 0.019784, 0.025707], [0.011985, 0.152226, 0.006782, 0.039714], [0.019784, 0.006782, 0.029666, 0.017843], [0.025707, 0.039714, 0.017843, 0.143406]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2872, w_BTC-USD=0.0000, w_XHB=0.7128, w_BNO=0.0000", "answer_numeric": 3.9006930292288526, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.2872, w_BTC-USD=0.0000, w_XHB=0.7128, w_BNO=0.0000\nPortfolio annualized return: 65.35%, volatility: 15.73%\nSharpe ratio: (0.6535 - 0.0400) / 0.1573 = 3.9007", "metadata": {"weights": {"VLUE": 0.2872, "BTC-USD": 0.0, "XHB": 0.7128, "BNO": 0.0}, "sharpe_ratio": 3.9007, "portfolio_return": 0.653484, "portfolio_vol": 0.157276, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180109_0506", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "TLH", "HAUZ"], "decision_date": "2018-01-09", "context_summary": "4-asset optimization. Max-Sharpe: 6.380. Portfolio: return=357.47%, vol=55.41%. Weights: w_XLRE=0.0000, w_XRP-USD=0.2581, w_TLH=0.0000, w_HAUZ=0.7419.", "question": "Assets: XLRE, XRP-USD, TLH, HAUZ\nAnnualized mean returns: XLRE:-0.1864, XRP-USD:13.2014, TLH:-0.0422, HAUZ:0.2262\nCovariance matrix (annualized):\n[[0.009494, 0.006866, 0.000922, 0.000801], [0.006866, 4.404893, 0.032226, 0.00842], [0.000922, 0.032226, 0.003022, -0.002712], [0.000801, 0.00842, -0.002712, 0.018869]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=0.2581, w_TLH=0.0000, w_HAUZ=0.7419", "answer_numeric": 6.37971012348724, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_XRP-USD=0.2581, w_TLH=0.0000, w_HAUZ=0.7419\nPortfolio annualized return: 357.47%, volatility: 55.41%\nSharpe ratio: (3.5747 - 0.0400) / 0.5541 = 6.3797", "metadata": {"weights": {"XLRE": 0.0, "XRP-USD": 0.2581, "TLH": 0.0, "HAUZ": 0.7419}, "sharpe_ratio": 6.3797, "portfolio_return": 3.574721, "portfolio_vol": 0.554057, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210729_0512", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BNB-USD", "IAU", "VNQ"], "decision_date": "2021-07-29", "context_summary": "4-asset optimization. Max-Sharpe: 3.774. Portfolio: return=41.83%, vol=10.02%. Weights: w_XLV=0.7067, w_BNB-USD=0.0000, w_IAU=0.0000, w_VNQ=0.2933.", "question": "Assets: XLV, BNB-USD, IAU, VNQ\nAnnualized mean returns: XLV:0.4146, BNB-USD:-1.2228, IAU:-0.2653, VNQ:0.4274\nCovariance matrix (annualized):\n[[0.011729, -0.015577, 0.002319, 0.005657], [-0.015577, 0.874152, -0.025795, -0.011115], [0.002319, -0.025795, 0.014326, 0.005824], [0.005657, -0.011115, 0.005824, 0.02145]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7067, w_BNB-USD=0.0000, w_IAU=0.0000, w_VNQ=0.2933", "answer_numeric": 3.7741529313418414, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.7067, w_BNB-USD=0.0000, w_IAU=0.0000, w_VNQ=0.2933\nPortfolio annualized return: 41.83%, volatility: 10.02%\nSharpe ratio: (0.4183 - 0.0400) / 0.1002 = 3.7742", "metadata": {"weights": {"XLV": 0.7067, "BNB-USD": 0.0, "IAU": 0.0, "VNQ": 0.2933}, "sharpe_ratio": 3.7742, "portfolio_return": 0.418326, "portfolio_vol": 0.100241, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181016_0518", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "XRP-USD", "VNQI", "DBB"], "decision_date": "2018-10-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.728. Portfolio: return=199.01%, vol=71.49%. Weights: w_XLV=0.0000, w_XRP-USD=0.4254, w_VNQI=0.0000, w_DBB=0.5746.", "question": "Assets: XLV, XRP-USD, VNQI, DBB\nAnnualized mean returns: XLV:-0.0012, XRP-USD:4.2566, VNQI:-0.3826, DBB:0.3119\nCovariance matrix (annualized):\n[[0.014539, 0.071824, 0.009558, 0.010384], [0.071824, 2.439892, 0.080343, 0.116748], [0.009558, 0.080343, 0.015891, 0.013103], [0.010384, 0.116748, 0.013103, 0.037576]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=0.4254, w_VNQI=0.0000, w_DBB=0.5746", "answer_numeric": 2.7277992744287345, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_XRP-USD=0.4254, w_VNQI=0.0000, w_DBB=0.5746\nPortfolio annualized return: 199.01%, volatility: 71.49%\nSharpe ratio: (1.9901 - 0.0400) / 0.7149 = 2.7278", "metadata": {"weights": {"XLV": 0.0, "XRP-USD": 0.4254, "VNQI": 0.0, "DBB": 0.5746}, "sharpe_ratio": 2.7278, "portfolio_return": 1.990128, "portfolio_vol": 0.714909, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220720_0523", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "SCHP", "HAUZ"], "decision_date": "2022-07-20", "context_summary": "4-asset optimization. Max-Sharpe: -0.966. Portfolio: return=-80.65%, vol=87.59%. Weights: w_XLI=0.0000, w_ADA-USD=1.0000, w_SCHP=0.0000, w_HAUZ=0.0000.", "question": "Assets: XLI, ADA-USD, SCHP, HAUZ\nAnnualized mean returns: XLI:-0.0506, ADA-USD:-0.8065, SCHP:-0.1065, HAUZ:-0.4370\nCovariance matrix (annualized):\n[[0.059629, 0.0651, 0.005909, 0.039923], [0.0651, 0.767273, 0.004939, 0.05987], [0.005909, 0.004939, 0.006082, 0.003893], [0.039923, 0.05987, 0.003893, 0.036371]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_SCHP=0.0000, w_HAUZ=0.0000", "answer_numeric": -0.9664288017188607, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_ADA-USD=1.0000, w_SCHP=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: -80.65%, volatility: 87.59%\nSharpe ratio: (-0.8065 - 0.0400) / 0.8759 = -0.9664", "metadata": {"weights": {"XLI": 0.0, "ADA-USD": 1.0, "SCHP": 0.0, "HAUZ": 0.0}, "sharpe_ratio": -0.9664, "portfolio_return": -0.806535, "portfolio_vol": 0.875941, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210728_0526", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNB-USD", "SOYB", "TLH"], "decision_date": "2021-07-28", "context_summary": "4-asset optimization. Max-Sharpe: 3.407. Portfolio: return=40.44%, vol=10.70%. Weights: w_FXI=0.0000, w_BNB-USD=0.0000, w_SOYB=0.0370, w_TLH=0.9630.", "question": "Assets: FXI, BNB-USD, SOYB, TLH\nAnnualized mean returns: FXI:-0.9559, BNB-USD:-1.2499, SOYB:0.1898, TLH:0.4126\nCovariance matrix (annualized):\n[[0.060448, 0.001847, 0.006105, -0.004229], [0.001847, 0.896444, -0.024247, 0.003463], [0.006105, -0.024247, 0.056695, 0.002708], [-0.004229, 0.003463, 0.002708, 0.012045]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNB-USD=0.0000, w_SOYB=0.0370, w_TLH=0.9630", "answer_numeric": 3.406525613448367, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_BNB-USD=0.0000, w_SOYB=0.0370, w_TLH=0.9630\nPortfolio annualized return: 40.44%, volatility: 10.70%\nSharpe ratio: (0.4044 - 0.0400) / 0.1070 = 3.4065", "metadata": {"weights": {"FXI": 0.0, "BNB-USD": 0.0, "SOYB": 0.037, "TLH": 0.963}, "sharpe_ratio": 3.4065, "portfolio_return": 0.404385, "portfolio_vol": 0.106967, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210929_0533", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "AVAX-USD", "BNO", "ICSH"], "decision_date": "2021-09-29", "context_summary": "4-asset optimization. Max-Sharpe: 5.272. Portfolio: return=546.06%, vol=102.82%. Weights: w_VLUE=0.0000, w_AVAX-USD=0.5210, w_BNO=0.4790, w_ICSH=0.0000.", "question": "Assets: VLUE, AVAX-USD, BNO, ICSH\nAnnualized mean returns: VLUE:-0.0795, AVAX-USD:10.1597, BNO:0.3491, ICSH:0.0028\nCovariance matrix (annualized):\n[[0.017919, 0.052018, 0.022755, 2e-06], [0.052018, 3.754839, 0.036544, 0.000228], [0.022755, 0.036544, 0.086128, 1.5e-05], [2e-06, 0.000228, 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_VLUE=0.0000, w_AVAX-USD=0.5210, w_BNO=0.4790, w_ICSH=0.0000", "answer_numeric": 5.271728209319177, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_AVAX-USD=0.5210, w_BNO=0.4790, w_ICSH=0.0000\nPortfolio annualized return: 546.06%, volatility: 102.82%\nSharpe ratio: (5.4606 - 0.0400) / 1.0282 = 5.2717", "metadata": {"weights": {"VLUE": 0.0, "AVAX-USD": 0.521, "BNO": 0.479, "ICSH": 0.0}, "sharpe_ratio": 5.2717, "portfolio_return": 5.460633, "portfolio_vol": 1.028246, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200306_0537", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "BTC-USD", "IAU", "INDS"], "decision_date": "2020-03-06", "context_summary": "4-asset optimization. Max-Sharpe: 4.119. Portfolio: return=72.00%, vol=16.51%. Weights: w_XLRE=0.0000, w_BTC-USD=0.2200, w_IAU=0.7800, w_INDS=0.0000.", "question": "Assets: XLRE, BTC-USD, IAU, INDS\nAnnualized mean returns: XLRE:0.0839, BTC-USD:1.5039, IAU:0.4989, INDS:0.1181\nCovariance matrix (annualized):\n[[0.046259, 0.014502, 0.002225, 0.050777], [0.014502, 0.223831, 0.012105, 0.016519], [0.002225, 0.012105, 0.020169, 0.002934], [0.050777, 0.016519, 0.002934, 0.059305]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.2200, w_IAU=0.7800, w_INDS=0.0000", "answer_numeric": 4.11867924848034, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_BTC-USD=0.2200, w_IAU=0.7800, w_INDS=0.0000\nPortfolio annualized return: 72.00%, volatility: 16.51%\nSharpe ratio: (0.7200 - 0.0400) / 0.1651 = 4.1187", "metadata": {"weights": {"XLRE": 0.0, "BTC-USD": 0.22, "IAU": 0.78, "INDS": 0.0}, "sharpe_ratio": 4.1187, "portfolio_return": 0.719964, "portfolio_vol": 0.165093, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220921_0542", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "DOT-USD", "BNO", "XHB"], "decision_date": "2022-09-21", "context_summary": "4-asset optimization. Max-Sharpe: -0.297. Portfolio: return=-19.27%, vol=78.38%. Weights: w_QUAL=0.0000, w_DOT-USD=1.0000, w_BNO=0.0000, w_XHB=0.0000.", "question": "Assets: QUAL, DOT-USD, BNO, XHB\nAnnualized mean returns: QUAL:-0.2155, DOT-USD:-0.1927, BNO:-0.3513, XHB:-0.3002\nCovariance matrix (annualized):\n[[0.046546, 0.105096, 0.006668, 0.056599], [0.105096, 0.614322, 0.075989, 0.150025], [0.006668, 0.075989, 0.149097, 7.7e-05], [0.056599, 0.150025, 7.7e-05, 0.086897]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_DOT-USD=1.0000, w_BNO=0.0000, w_XHB=0.0000", "answer_numeric": -0.29688732674690776, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_DOT-USD=1.0000, w_BNO=0.0000, w_XHB=0.0000\nPortfolio annualized return: -19.27%, volatility: 78.38%\nSharpe ratio: (-0.1927 - 0.0400) / 0.7838 = -0.2969", "metadata": {"weights": {"QUAL": 0.0, "DOT-USD": 1.0, "BNO": 0.0, "XHB": 0.0}, "sharpe_ratio": -0.2969, "portfolio_return": -0.192696, "portfolio_vol": 0.783787, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191107_0551", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "MATIC-USD", "MORT", "ICSH"], "decision_date": "2019-11-07", "context_summary": "4-asset optimization. Max-Sharpe: 5.276. Portfolio: return=47.59%, vol=8.26%. Weights: w_XLRE=0.0000, w_MATIC-USD=0.0387, w_MORT=0.9613, w_ICSH=0.0000.", "question": "Assets: XLRE, MATIC-USD, MORT, ICSH\nAnnualized mean returns: XLRE:-0.1922, MATIC-USD:1.6358, MORT:0.4292, ICSH:0.0247\nCovariance matrix (annualized):\n[[0.013557, -0.011018, 0.002705, 4.3e-05], [-0.011018, 0.702993, -0.00234, 6.6e-05], [0.002705, -0.00234, 0.006434, -1.9e-05], [4.3e-05, 6.6e-05, -1.9e-05, 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_XLRE=0.0000, w_MATIC-USD=0.0387, w_MORT=0.9613, w_ICSH=0.0000", "answer_numeric": 5.276322081187995, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_MATIC-USD=0.0387, w_MORT=0.9613, w_ICSH=0.0000\nPortfolio annualized return: 47.59%, volatility: 8.26%\nSharpe ratio: (0.4759 - 0.0400) / 0.0826 = 5.2763", "metadata": {"weights": {"XLRE": 0.0, "MATIC-USD": 0.0387, "MORT": 0.9613, "ICSH": 0.0}, "sharpe_ratio": 5.2763, "portfolio_return": 0.475924, "portfolio_vol": 0.082619, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201111_0558", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNB-USD", "BIL", "STIP"], "decision_date": "2020-11-11", "context_summary": "4-asset optimization. Max-Sharpe: 2.816. Portfolio: return=61.21%, vol=20.32%. Weights: w_FXI=1.0000, w_BNB-USD=0.0000, w_BIL=0.0000, w_STIP=0.0000.", "question": "Assets: FXI, BNB-USD, BIL, STIP\nAnnualized mean returns: FXI:0.6121, BNB-USD:-0.7284, BIL:0.0000, STIP:0.0075\nCovariance matrix (annualized):\n[[0.041289, 0.009694, 2.8e-05, 9.1e-05], [0.009694, 0.466563, 0.000251, 0.001748], [2.8e-05, 0.000251, 2e-06, 2e-06], [9.1e-05, 0.001748, 2e-06, 0.000122]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNB-USD=0.0000, w_BIL=0.0000, w_STIP=0.0000", "answer_numeric": 2.8155237961964827, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=1.0000, w_BNB-USD=0.0000, w_BIL=0.0000, w_STIP=0.0000\nPortfolio annualized return: 61.21%, volatility: 20.32%\nSharpe ratio: (0.6121 - 0.0400) / 0.2032 = 2.8155", "metadata": {"weights": {"FXI": 1.0, "BNB-USD": 0.0, "BIL": 0.0, "STIP": 0.0}, "sharpe_ratio": 2.8155, "portfolio_return": 0.612105, "portfolio_vol": 0.203197, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220811_0563", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "TLT", "PPLT"], "decision_date": "2022-08-11", "context_summary": "4-asset optimization. Max-Sharpe: 2.578. Portfolio: return=39.57%, vol=13.80%. Weights: w_USMV=0.7592, w_BTC-USD=0.0000, w_TLT=0.2408, w_PPLT=0.0000.", "question": "Assets: USMV, BTC-USD, TLT, PPLT\nAnnualized mean returns: USMV:0.4390, BTC-USD:-0.1119, TLT:0.2593, PPLT:-0.1904\nCovariance matrix (annualized):\n[[0.02754, 0.058913, 0.001861, 0.012725], [0.058913, 0.413985, -0.005317, 0.07911], [0.001861, -0.005317, 0.042855, 0.004037], [0.012725, 0.07911, 0.004037, 0.072547]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7592, w_BTC-USD=0.0000, w_TLT=0.2408, w_PPLT=0.0000", "answer_numeric": 2.5782920140130976, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.7592, w_BTC-USD=0.0000, w_TLT=0.2408, w_PPLT=0.0000\nPortfolio annualized return: 39.57%, volatility: 13.80%\nSharpe ratio: (0.3957 - 0.0400) / 0.1380 = 2.5783", "metadata": {"weights": {"USMV": 0.7592, "BTC-USD": 0.0, "TLT": 0.2408, "PPLT": 0.0}, "sharpe_ratio": 2.5783, "portfolio_return": 0.395746, "portfolio_vol": 0.137977, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190614_0566", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "SCHH", "ICSH"], "decision_date": "2019-06-14", "context_summary": "4-asset optimization. Max-Sharpe: 0.289. Portfolio: return=8.18%, vol=14.49%. Weights: w_XLK=0.0000, w_ADA-USD=0.0035, w_SCHH=0.9965, w_ICSH=0.0000.", "question": "Assets: XLK, ADA-USD, SCHH, ICSH\nAnnualized mean returns: XLK:-0.0031, ADA-USD:0.0651, SCHH:0.0819, ICSH:0.0372\nCovariance matrix (annualized):\n[[0.038422, 0.011605, 0.00757, -0.000122], [0.011605, 0.74862, 0.010022, -0.000634], [0.00757, 0.010022, 0.021062, -6.3e-05], [-0.000122, -0.000634, -6.3e-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_XLK=0.0000, w_ADA-USD=0.0035, w_SCHH=0.9965, w_ICSH=0.0000", "answer_numeric": 0.28860061141143556, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_ADA-USD=0.0035, w_SCHH=0.9965, w_ICSH=0.0000\nPortfolio annualized return: 8.18%, volatility: 14.49%\nSharpe ratio: (0.0818 - 0.0400) / 0.1449 = 0.2886", "metadata": {"weights": {"XLK": 0.0, "ADA-USD": 0.0035, "SCHH": 0.9965, "ICSH": 0.0}, "sharpe_ratio": 0.2886, "portfolio_return": 0.081817, "portfolio_vol": 0.144895, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191017_0573", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "BNO", "BIL"], "decision_date": "2019-10-17", "context_summary": "4-asset optimization. Max-Sharpe: 0.486. Portfolio: return=11.85%, vol=16.14%. Weights: w_XLB=1.0000, w_LINK-USD=0.0000, w_BNO=0.0000, w_BIL=0.0000.", "question": "Assets: XLB, LINK-USD, BNO, BIL\nAnnualized mean returns: XLB:0.1185, LINK-USD:-0.1930, BNO:-0.1014, BIL:0.0187\nCovariance matrix (annualized):\n[[0.026064, -0.032653, 0.007988, 5.4e-05], [-0.032653, 0.602569, -0.071004, 3.6e-05], [0.007988, -0.071004, 0.108047, -9.2e-05], [5.4e-05, 3.6e-05, -9.2e-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_XLB=1.0000, w_LINK-USD=0.0000, w_BNO=0.0000, w_BIL=0.0000", "answer_numeric": 0.48593226436915693, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=1.0000, w_LINK-USD=0.0000, w_BNO=0.0000, w_BIL=0.0000\nPortfolio annualized return: 11.85%, volatility: 16.14%\nSharpe ratio: (0.1185 - 0.0400) / 0.1614 = 0.4859", "metadata": {"weights": {"XLB": 1.0, "LINK-USD": 0.0, "BNO": 0.0, "BIL": 0.0}, "sharpe_ratio": 0.4859, "portfolio_return": 0.11845, "portfolio_vol": 0.161443, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200806_0580", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "MORT", "SLV"], "decision_date": "2020-08-06", "context_summary": "4-asset optimization. Max-Sharpe: 6.496. Portfolio: return=210.57%, vol=31.80%. Weights: w_FXI=0.0000, w_ETH-USD=0.2981, w_MORT=0.0000, w_SLV=0.7019.", "question": "Assets: FXI, ETH-USD, MORT, SLV\nAnnualized mean returns: FXI:-0.0184, ETH-USD:2.0441, MORT:-0.0518, SLV:2.1318\nCovariance matrix (annualized):\n[[0.065454, 0.048781, 0.02268, 0.02747], [0.048781, 0.19627, 0.058497, 0.056405], [0.02268, 0.058497, 0.14168, 0.044457], [0.02747, 0.056405, 0.044457, 0.12193]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2981, w_MORT=0.0000, w_SLV=0.7019", "answer_numeric": 6.4961480025004885, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_ETH-USD=0.2981, w_MORT=0.0000, w_SLV=0.7019\nPortfolio annualized return: 210.57%, volatility: 31.80%\nSharpe ratio: (2.1057 - 0.0400) / 0.3180 = 6.4961", "metadata": {"weights": {"FXI": 0.0, "ETH-USD": 0.2981, "MORT": 0.0, "SLV": 0.7019}, "sharpe_ratio": 6.4961, "portfolio_return": 2.10569, "portfolio_vol": 0.317987, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190606_0585", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "INDS", "CPER"], "decision_date": "2019-06-06", "context_summary": "4-asset optimization. Max-Sharpe: 1.272. Portfolio: return=27.29%, vol=18.31%. Weights: w_XLE=0.0000, w_BTC-USD=0.2199, w_INDS=0.7801, w_CPER=0.0000.", "question": "Assets: XLE, BTC-USD, INDS, CPER\nAnnualized mean returns: XLE:-0.7462, BTC-USD:0.5444, INDS:0.1964, CPER:-0.5867\nCovariance matrix (annualized):\n[[0.032369, -0.012024, 0.002013, 0.012016], [-0.012024, 0.309634, 0.005759, -0.002928], [0.002013, 0.005759, 0.027224, 0.001236], [0.012016, -0.002928, 0.001236, 0.030518]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.2199, w_INDS=0.7801, w_CPER=0.0000", "answer_numeric": 1.272236961401638, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_BTC-USD=0.2199, w_INDS=0.7801, w_CPER=0.0000\nPortfolio annualized return: 27.29%, volatility: 18.31%\nSharpe ratio: (0.2729 - 0.0400) / 0.1831 = 1.2722", "metadata": {"weights": {"XLE": 0.0, "BTC-USD": 0.2199, "INDS": 0.7801, "CPER": 0.0}, "sharpe_ratio": 1.2722, "portfolio_return": 0.272927, "portfolio_vol": 0.183085, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210715_0594", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "SGOV", "XHB"], "decision_date": "2021-07-15", "context_summary": "4-asset optimization. Max-Sharpe: 2.201. Portfolio: return=22.43%, vol=8.37%. Weights: w_USMV=1.0000, w_ADA-USD=0.0000, w_SGOV=0.0000, w_XHB=0.0000.", "question": "Assets: USMV, ADA-USD, SGOV, XHB\nAnnualized mean returns: USMV:0.2243, ADA-USD:-2.9859, SGOV:-0.0001, XHB:-0.3418\nCovariance matrix (annualized):\n[[0.007012, 0.017281, 1.4e-05, 0.007221], [0.017281, 1.637473, -8e-06, 0.028598], [1.4e-05, -8e-06, 1e-06, 4e-06], [0.007221, 0.028598, 4e-06, 0.033262]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=0.0000, w_SGOV=0.0000, w_XHB=0.0000", "answer_numeric": 2.2010871360873496, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=1.0000, w_ADA-USD=0.0000, w_SGOV=0.0000, w_XHB=0.0000\nPortfolio annualized return: 22.43%, volatility: 8.37%\nSharpe ratio: (0.2243 - 0.0400) / 0.0837 = 2.2011", "metadata": {"weights": {"USMV": 1.0, "ADA-USD": 0.0, "SGOV": 0.0, "XHB": 0.0}, "sharpe_ratio": 2.2011, "portfolio_return": 0.224319, "portfolio_vol": 0.08374, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181011_0599", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "SLV", "VNQI"], "decision_date": "2018-10-11", "context_summary": "4-asset optimization. Max-Sharpe: 3.362. Portfolio: return=292.76%, vol=85.88%. Weights: w_XLE=0.0000, w_LINK-USD=1.0000, w_SLV=0.0000, w_VNQI=0.0000.", "question": "Assets: XLE, LINK-USD, SLV, VNQI\nAnnualized mean returns: XLE:0.0459, LINK-USD:2.9276, SLV:-0.3958, VNQI:-0.4173\nCovariance matrix (annualized):\n[[0.026262, 0.009059, 0.015833, 0.010774], [0.009059, 0.737619, 0.038093, 0.038926], [0.015833, 0.038093, 0.035561, 0.010266], [0.010774, 0.038926, 0.010266, 0.016321]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_SLV=0.0000, w_VNQI=0.0000", "answer_numeric": 3.3622289802635565, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_LINK-USD=1.0000, w_SLV=0.0000, w_VNQI=0.0000\nPortfolio annualized return: 292.76%, volatility: 85.88%\nSharpe ratio: (2.9276 - 0.0400) / 0.8588 = 3.3622", "metadata": {"weights": {"XLE": 0.0, "LINK-USD": 1.0, "SLV": 0.0, "VNQI": 0.0}, "sharpe_ratio": 3.3622, "portfolio_return": 2.927642, "portfolio_vol": 0.858848, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220328_0602", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SOL-USD", "ICSH", "INDS"], "decision_date": "2022-03-28", "context_summary": "4-asset optimization. Max-Sharpe: 2.383. Portfolio: return=153.42%, vol=62.72%. Weights: w_^VIX=0.0000, w_SOL-USD=0.6851, w_ICSH=0.0000, w_INDS=0.3149.", "question": "Assets: ^VIX, SOL-USD, ICSH, INDS\nAnnualized mean returns: ^VIX:-2.6371, SOL-USD:2.1811, ICSH:-0.0218, INDS:0.1270\nCovariance matrix (annualized):\n[[1.569319, -0.490206, -0.001418, -0.160048], [-0.490206, 0.816531, 0.000859, 0.013323], [-0.001418, 0.000859, 3.8e-05, 0.000356], [-0.160048, 0.013323, 0.000356, 0.043778]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6851, w_ICSH=0.0000, w_INDS=0.3149", "answer_numeric": 2.382562537526706, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_SOL-USD=0.6851, w_ICSH=0.0000, w_INDS=0.3149\nPortfolio annualized return: 153.42%, volatility: 62.72%\nSharpe ratio: (1.5342 - 0.0400) / 0.6272 = 2.3826", "metadata": {"weights": {"^VIX": 0.0, "SOL-USD": 0.6851, "ICSH": 0.0, "INDS": 0.3149}, "sharpe_ratio": 2.3826, "portfolio_return": 1.534249, "portfolio_vol": 0.62716, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210603_0604", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "MATIC-USD", "PPLT", "SHV"], "decision_date": "2021-06-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.966. Portfolio: return=261.75%, vol=51.90%. Weights: w_VLUE=0.8097, w_MATIC-USD=0.1903, w_PPLT=0.0000, w_SHV=0.0000.", "question": "Assets: VLUE, MATIC-USD, PPLT, SHV\nAnnualized mean returns: VLUE:0.2564, MATIC-USD:12.6613, PPLT:-0.0843, SHV:0.0000\nCovariance matrix (annualized):\n[[0.020143, 0.033146, 0.014383, 1.1e-05], [0.033146, 6.788353, 0.067552, -0.000355], [0.014383, 0.067552, 0.057897, -2e-06], [1.1e-05, -0.000355, -2e-06, 1e-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=0.8097, w_MATIC-USD=0.1903, w_PPLT=0.0000, w_SHV=0.0000", "answer_numeric": 4.966452725751697, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.8097, w_MATIC-USD=0.1903, w_PPLT=0.0000, w_SHV=0.0000\nPortfolio annualized return: 261.75%, volatility: 51.90%\nSharpe ratio: (2.6175 - 0.0400) / 0.5190 = 4.9665", "metadata": {"weights": {"VLUE": 0.8097, "MATIC-USD": 0.1903, "PPLT": 0.0, "SHV": 0.0}, "sharpe_ratio": 4.9665, "portfolio_return": 2.617521, "portfolio_vol": 0.518986, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20160428_0607", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "DBC", "IGOV"], "decision_date": "2016-04-28", "context_summary": "4-asset optimization. Max-Sharpe: 5.424. Portfolio: return=45.23%, vol=7.60%. Weights: w_USMV=0.4333, w_BTC-USD=0.0036, w_DBC=0.3143, w_IGOV=0.2488.", "question": "Assets: USMV, BTC-USD, DBC, IGOV\nAnnualized mean returns: USMV:0.3315, BTC-USD:-0.0762, DBC:0.8056, IGOV:0.2240\nCovariance matrix (annualized):\n[[0.007179, -0.004885, 0.001692, 0.001845], [-0.004885, 0.040788, 0.001257, -0.000215], [0.001692, 0.001257, 0.030983, 0.001017], [0.001845, -0.000215, 0.001017, 0.005868]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4333, w_BTC-USD=0.0036, w_DBC=0.3143, w_IGOV=0.2488", "answer_numeric": 5.423902283571762, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.4333, w_BTC-USD=0.0036, w_DBC=0.3143, w_IGOV=0.2488\nPortfolio annualized return: 45.23%, volatility: 7.60%\nSharpe ratio: (0.4523 - 0.0400) / 0.0760 = 5.4239", "metadata": {"weights": {"USMV": 0.4333, "BTC-USD": 0.0036, "DBC": 0.3143, "IGOV": 0.2488}, "sharpe_ratio": 5.4239, "portfolio_return": 0.452261, "portfolio_vol": 0.076008, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210720_0612", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "USO", "SCHH"], "decision_date": "2021-07-20", "context_summary": "4-asset optimization. Max-Sharpe: 2.944. Portfolio: return=44.28%, vol=13.68%. Weights: w_FXI=0.0000, w_LINK-USD=0.0000, w_USO=0.1645, w_SCHH=0.8355.", "question": "Assets: FXI, LINK-USD, USO, SCHH\nAnnualized mean returns: FXI:-0.2288, LINK-USD:-4.9805, USO:0.5170, SCHH:0.4282\nCovariance matrix (annualized):\n[[0.044173, 0.009497, 0.009403, 0.007561], [0.009497, 1.737457, -0.013104, -0.001881], [0.009403, -0.013104, 0.074371, 0.011888], [0.007561, -0.001881, 0.011888, 0.019255]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_USO=0.1645, w_SCHH=0.8355", "answer_numeric": 2.9440582285061385, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_LINK-USD=0.0000, w_USO=0.1645, w_SCHH=0.8355\nPortfolio annualized return: 44.28%, volatility: 13.68%\nSharpe ratio: (0.4428 - 0.0400) / 0.1368 = 2.9441", "metadata": {"weights": {"FXI": 0.0, "LINK-USD": 0.0, "USO": 0.1645, "SCHH": 0.8355}, "sharpe_ratio": 2.9441, "portfolio_return": 0.442822, "portfolio_vol": 0.136826, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190718_0614", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "XRP-USD", "TLT", "CORN"], "decision_date": "2019-07-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.313. Portfolio: return=31.98%, vol=6.49%. Weights: w_QUAL=0.3980, w_XRP-USD=0.0000, w_TLT=0.4919, w_CORN=0.1101.", "question": "Assets: QUAL, XRP-USD, TLT, CORN\nAnnualized mean returns: QUAL:0.2721, XRP-USD:-1.3730, TLT:0.3162, CORN:0.5087\nCovariance matrix (annualized):\n[[0.01308, -0.012125, -0.0037, 0.000966], [-0.012125, 0.417503, 0.014232, -0.015302], [-0.0037, 0.014232, 0.011152, 0.001297], [0.000966, -0.015302, 0.001297, 0.054779]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3980, w_XRP-USD=0.0000, w_TLT=0.4919, w_CORN=0.1101", "answer_numeric": 4.3125210965681795, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.3980, w_XRP-USD=0.0000, w_TLT=0.4919, w_CORN=0.1101\nPortfolio annualized return: 31.98%, volatility: 6.49%\nSharpe ratio: (0.3198 - 0.0400) / 0.0649 = 4.3125", "metadata": {"weights": {"QUAL": 0.398, "XRP-USD": 0.0, "TLT": 0.4919, "CORN": 0.1101}, "sharpe_ratio": 4.3125, "portfolio_return": 0.319843, "portfolio_vol": 0.064891, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210701_0616", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "VNQ", "SHV"], "decision_date": "2021-07-01", "context_summary": "4-asset optimization. Max-Sharpe: 1.192. Portfolio: return=22.28%, vol=15.34%. Weights: w_XLF=0.0000, w_SOL-USD=0.0197, w_VNQ=0.9803, w_SHV=0.0000.", "question": "Assets: XLF, SOL-USD, VNQ, SHV\nAnnualized mean returns: XLF:0.0945, SOL-USD:0.5776, VNQ:0.2157, SHV:-0.0011\nCovariance matrix (annualized):\n[[0.029667, -0.036589, 0.010583, 4.1e-05], [-0.036589, 3.110099, 0.008181, 0.000214], [0.010583, 0.008181, 0.022898, 1.2e-05], [4.1e-05, 0.000214, 1.2e-05, 2e-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_SOL-USD=0.0197, w_VNQ=0.9803, w_SHV=0.0000", "answer_numeric": 1.1921064931713072, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_SOL-USD=0.0197, w_VNQ=0.9803, w_SHV=0.0000\nPortfolio annualized return: 22.28%, volatility: 15.34%\nSharpe ratio: (0.2228 - 0.0400) / 0.1534 = 1.1921", "metadata": {"weights": {"XLF": 0.0, "SOL-USD": 0.0197, "VNQ": 0.9803, "SHV": 0.0}, "sharpe_ratio": 1.1921, "portfolio_return": 0.22284, "portfolio_vol": 0.153376, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210215_0619", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "BIL", "TLT"], "decision_date": "2021-02-15", "context_summary": "4-asset optimization. Max-Sharpe: 4.549. Portfolio: return=227.01%, vol=49.03%. Weights: w_VEA=0.5536, w_ETH-USD=0.4464, w_BIL=0.0000, w_TLT=0.0000.", "question": "Assets: VEA, ETH-USD, BIL, TLT\nAnnualized mean returns: VEA:0.3789, ETH-USD:4.6151, BIL:-0.0007, TLT:-0.4164\nCovariance matrix (annualized):\n[[0.020546, 0.056335, -2.1e-05, -0.005005], [0.056335, 1.034648, -9.4e-05, -0.015236], [-2.1e-05, -9.4e-05, 2e-06, -2e-06], [-0.005005, -0.015236, -2e-06, 0.01033]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5536, w_ETH-USD=0.4464, w_BIL=0.0000, w_TLT=0.0000", "answer_numeric": 4.5488259501316, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.5536, w_ETH-USD=0.4464, w_BIL=0.0000, w_TLT=0.0000\nPortfolio annualized return: 227.01%, volatility: 49.03%\nSharpe ratio: (2.2701 - 0.0400) / 0.4903 = 4.5488", "metadata": {"weights": {"VEA": 0.5536, "ETH-USD": 0.4464, "BIL": 0.0, "TLT": 0.0}, "sharpe_ratio": 4.5488, "portfolio_return": 2.270095, "portfolio_vol": 0.490257, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180801_0621", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "WEAT", "SHY"], "decision_date": "2018-08-01", "context_summary": "4-asset optimization. Max-Sharpe: 0.545. Portfolio: return=29.89%, vol=47.48%. Weights: w_EWJ=0.0000, w_BNB-USD=0.6022, w_WEAT=0.3978, w_SHY=0.0000.", "question": "Assets: EWJ, BNB-USD, WEAT, SHY\nAnnualized mean returns: EWJ:-0.1204, BNB-USD:0.4300, WEAT:0.1004, SHY:0.0037\nCovariance matrix (annualized):\n[[0.010777, -0.002299, 0.009443, -0.000239], [-0.002299, 0.552108, 0.017838, 0.000138], [0.009443, 0.017838, 0.105208, -3.2e-05], [-0.000239, 0.000138, -3.2e-05, 3.8e-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_EWJ=0.0000, w_BNB-USD=0.6022, w_WEAT=0.3978, w_SHY=0.0000", "answer_numeric": 0.5452834114524353, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BNB-USD=0.6022, w_WEAT=0.3978, w_SHY=0.0000\nPortfolio annualized return: 29.89%, volatility: 47.48%\nSharpe ratio: (0.2989 - 0.0400) / 0.4748 = 0.5453", "metadata": {"weights": {"EWJ": 0.0, "BNB-USD": 0.6022, "WEAT": 0.3978, "SHY": 0.0}, "sharpe_ratio": 0.5453, "portfolio_return": 0.298888, "portfolio_vol": 0.474776, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221021_0623", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ETH-USD", "XHB", "BIL"], "decision_date": "2022-10-21", "context_summary": "4-asset optimization. Max-Sharpe: -0.666. Portfolio: return=-36.22%, vol=60.38%. Weights: w_XLK=0.0000, w_ETH-USD=1.0000, w_XHB=0.0000, w_BIL=0.0000.", "question": "Assets: XLK, ETH-USD, XHB, BIL\nAnnualized mean returns: XLK:-1.0907, ETH-USD:-0.3622, XHB:-0.8919, BIL:0.0227\nCovariance matrix (annualized):\n[[0.090174, 0.09012, 0.081724, -3.9e-05], [0.09012, 0.364571, 0.081461, -0.000172], [0.081724, 0.081461, 0.119924, -2.6e-05], [-3.9e-05, -0.000172, -2.6e-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=0.0000, w_ETH-USD=1.0000, w_XHB=0.0000, w_BIL=0.0000", "answer_numeric": -0.6661147925166707, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_ETH-USD=1.0000, w_XHB=0.0000, w_BIL=0.0000\nPortfolio annualized return: -36.22%, volatility: 60.38%\nSharpe ratio: (-0.3622 - 0.0400) / 0.6038 = -0.6661", "metadata": {"weights": {"XLK": 0.0, "ETH-USD": 1.0, "XHB": 0.0, "BIL": 0.0}, "sharpe_ratio": -0.6661, "portfolio_return": -0.362198, "portfolio_vol": 0.603797, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220623_0627", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "ITB", "GLD"], "decision_date": "2022-06-23", "context_summary": "4-asset optimization. Max-Sharpe: -1.182. Portfolio: return=-45.47%, vol=41.86%. Weights: w_EWJ=0.0000, w_ADA-USD=0.0000, w_ITB=1.0000, w_GLD=0.0000.", "question": "Assets: EWJ, ADA-USD, ITB, GLD\nAnnualized mean returns: EWJ:-0.4551, ADA-USD:-4.4031, ITB:-0.4547, GLD:-0.2874\nCovariance matrix (annualized):\n[[0.043408, 0.140775, 0.062967, 0.007193], [0.140775, 1.466556, 0.227686, 0.006235], [0.062967, 0.227686, 0.175225, -0.007958], [0.007193, 0.006235, -0.007958, 0.022779]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=0.0000, w_ITB=1.0000, w_GLD=0.0000", "answer_numeric": -1.1818016234805109, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_ADA-USD=0.0000, w_ITB=1.0000, w_GLD=0.0000\nPortfolio annualized return: -45.47%, volatility: 41.86%\nSharpe ratio: (-0.4547 - 0.0400) / 0.4186 = -1.1818", "metadata": {"weights": {"EWJ": 0.0, "ADA-USD": 0.0, "ITB": 1.0, "GLD": 0.0}, "sharpe_ratio": -1.1818, "portfolio_return": -0.454701, "portfolio_vol": 0.418599, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200709_0629", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "IAU", "LQD"], "decision_date": "2020-07-09", "context_summary": "4-asset optimization. Max-Sharpe: 5.756. Portfolio: return=43.74%, vol=6.90%. Weights: w_VTI=0.0914, w_XRP-USD=0.0000, w_IAU=0.2153, w_LQD=0.6933.", "question": "Assets: VTI, XRP-USD, IAU, LQD\nAnnualized mean returns: VTI:0.6679, XRP-USD:0.4811, IAU:0.3598, LQD:0.4311\nCovariance matrix (annualized):\n[[0.050124, 0.029784, -0.006841, 0.006378], [0.029784, 0.189205, 0.016422, 0.006978], [-0.006841, 0.016422, 0.016482, 0.001317], [0.006378, 0.006978, 0.001317, 0.005515]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0914, w_XRP-USD=0.0000, w_IAU=0.2153, w_LQD=0.6933", "answer_numeric": 5.756026450060742, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0914, w_XRP-USD=0.0000, w_IAU=0.2153, w_LQD=0.6933\nPortfolio annualized return: 43.74%, volatility: 6.90%\nSharpe ratio: (0.4374 - 0.0400) / 0.0690 = 5.7560", "metadata": {"weights": {"VTI": 0.0914, "XRP-USD": 0.0, "IAU": 0.2153, "LQD": 0.6933}, "sharpe_ratio": 5.756, "portfolio_return": 0.43738, "portfolio_vol": 0.069037, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190726_0631", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "SCHP", "SOYB"], "decision_date": "2019-07-26", "context_summary": "4-asset optimization. Max-Sharpe: 3.503. Portfolio: return=20.57%, vol=4.73%. Weights: w_XLI=0.2364, w_BNB-USD=0.0075, w_SCHP=0.7131, w_SOYB=0.0430.", "question": "Assets: XLI, BNB-USD, SCHP, SOYB\nAnnualized mean returns: XLI:0.4111, BNB-USD:0.3200, SCHP:0.1332, SOYB:0.2604\nCovariance matrix (annualized):\n[[0.01943, -0.010048, 0.000447, 0.004073], [-0.010048, 0.424056, 0.003071, 0.01779], [0.000447, 0.003071, 0.001546, 0.000621], [0.004073, 0.01779, 0.000621, 0.033404]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2364, w_BNB-USD=0.0075, w_SCHP=0.7131, w_SOYB=0.0430", "answer_numeric": 3.503261866551976, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.2364, w_BNB-USD=0.0075, w_SCHP=0.7131, w_SOYB=0.0430\nPortfolio annualized return: 20.57%, volatility: 4.73%\nSharpe ratio: (0.2057 - 0.0400) / 0.0473 = 3.5033", "metadata": {"weights": {"XLI": 0.2364, "BNB-USD": 0.0075, "SCHP": 0.7131, "SOYB": 0.043}, "sharpe_ratio": 3.5033, "portfolio_return": 0.205733, "portfolio_vol": 0.047308, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200402_0636", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BTC-USD", "IAU", "IYR"], "decision_date": "2020-04-02", "context_summary": "4-asset optimization. Max-Sharpe: 2.190. Portfolio: return=166.29%, vol=74.09%. Weights: w_EWJ=0.0000, w_BTC-USD=1.0000, w_IAU=0.0000, w_IYR=0.0000.", "question": "Assets: EWJ, BTC-USD, IAU, IYR\nAnnualized mean returns: EWJ:-0.8051, BTC-USD:1.6629, IAU:-0.0281, IYR:-0.7983\nCovariance matrix (annualized):\n[[0.0907, 0.089988, 0.00118, 0.091191], [0.089988, 0.548985, 0.036143, 0.092049], [0.00118, 0.036143, 0.048676, 0.011067], [0.091191, 0.092049, 0.011067, 0.134885]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=1.0000, w_IAU=0.0000, w_IYR=0.0000", "answer_numeric": 2.1903959425111115, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BTC-USD=1.0000, w_IAU=0.0000, w_IYR=0.0000\nPortfolio annualized return: 166.29%, volatility: 74.09%\nSharpe ratio: (1.6629 - 0.0400) / 0.7409 = 2.1904", "metadata": {"weights": {"EWJ": 0.0, "BTC-USD": 1.0, "IAU": 0.0, "IYR": 0.0}, "sharpe_ratio": 2.1904, "portfolio_return": 1.662942, "portfolio_vol": 0.740935, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201211_0638", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "BNDX", "REZ"], "decision_date": "2020-12-11", "context_summary": "4-asset optimization. Max-Sharpe: 5.819. Portfolio: return=135.38%, vol=22.58%. Weights: w_XLY=0.0000, w_BTC-USD=0.4549, w_BNDX=0.4452, w_REZ=0.0999.", "question": "Assets: XLY, BTC-USD, BNDX, REZ\nAnnualized mean returns: XLY:0.1382, BTC-USD:2.8989, BNDX:0.0525, REZ:0.1170\nCovariance matrix (annualized):\n[[0.031895, 0.016109, 0.000227, 0.022356], [0.016109, 0.243874, 0.001002, -0.004503], [0.000227, 0.001002, 0.000675, -0.002711], [0.022356, -0.004503, -0.002711, 0.062504]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4549, w_BNDX=0.4452, w_REZ=0.0999", "answer_numeric": 5.818657589486848, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_BTC-USD=0.4549, w_BNDX=0.4452, w_REZ=0.0999\nPortfolio annualized return: 135.38%, volatility: 22.58%\nSharpe ratio: (1.3538 - 0.0400) / 0.2258 = 5.8187", "metadata": {"weights": {"XLY": 0.0, "BTC-USD": 0.4549, "BNDX": 0.4452, "REZ": 0.0999}, "sharpe_ratio": 5.8187, "portfolio_return": 1.353827, "portfolio_vol": 0.225796, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220607_0644", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ETH-USD", "CORN", "SHY"], "decision_date": "2022-06-07", "context_summary": "4-asset optimization. Max-Sharpe: -1.777. Portfolio: return=-62.40%, vol=37.36%. Weights: w_XLY=1.0000, w_ETH-USD=0.0000, w_CORN=0.0000, w_SHY=0.0000.", "question": "Assets: XLY, ETH-USD, CORN, SHY\nAnnualized mean returns: XLY:-0.6240, ETH-USD:-4.3754, CORN:-0.0013, SHY:-0.0029\nCovariance matrix (annualized):\n[[0.139579, 0.150231, 0.008641, -0.000445], [0.150231, 0.480855, 0.021282, -6.7e-05], [0.008641, 0.021282, 0.047984, 0.000642], [-0.000445, -6.7e-05, 0.000642, 0.000459]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.0000, w_CORN=0.0000, w_SHY=0.0000", "answer_numeric": -1.7771782940949588, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=1.0000, w_ETH-USD=0.0000, w_CORN=0.0000, w_SHY=0.0000\nPortfolio annualized return: -62.40%, volatility: 37.36%\nSharpe ratio: (-0.6240 - 0.0400) / 0.3736 = -1.7772", "metadata": {"weights": {"XLY": 1.0, "ETH-USD": 0.0, "CORN": 0.0, "SHY": 0.0}, "sharpe_ratio": -1.7772, "portfolio_return": -0.623959, "portfolio_vol": 0.373603, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221122_0646", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "CSHI", "PDBC"], "decision_date": "2022-11-22", "context_summary": "4-asset optimization. Max-Sharpe: 1.264. Portfolio: return=5.34%, vol=1.06%. Weights: w_XLY=0.0000, w_ADA-USD=0.0000, w_CSHI=1.0000, w_PDBC=0.0000.", "question": "Assets: XLY, ADA-USD, CSHI, PDBC\nAnnualized mean returns: XLY:-0.7139, ADA-USD:-1.0907, CSHI:0.0534, PDBC:0.0485\nCovariance matrix (annualized):\n[[0.095651, 0.114904, 0.001638, 0.031672], [0.114904, 0.565591, 0.000925, 0.057591], [0.001638, 0.000925, 0.000112, 0.001204], [0.031672, 0.057591, 0.001204, 0.052926]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=0.0000, w_CSHI=1.0000, w_PDBC=0.0000", "answer_numeric": 1.2641398922843368, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_ADA-USD=0.0000, w_CSHI=1.0000, w_PDBC=0.0000\nPortfolio annualized return: 5.34%, volatility: 1.06%\nSharpe ratio: (0.0534 - 0.0400) / 0.0106 = 1.2641", "metadata": {"weights": {"XLY": 0.0, "ADA-USD": 0.0, "CSHI": 1.0, "PDBC": 0.0}, "sharpe_ratio": 1.2641, "portfolio_return": 0.053387, "portfolio_vol": 0.01059, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200908_0649", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "MATIC-USD", "MORT", "LQD"], "decision_date": "2020-09-08", "context_summary": "4-asset optimization. Max-Sharpe: 3.124. Portfolio: return=74.79%, vol=22.66%. Weights: w_VLUE=0.0235, w_MATIC-USD=0.0000, w_MORT=0.9765, w_LQD=0.0000.", "question": "Assets: VLUE, MATIC-USD, MORT, LQD\nAnnualized mean returns: VLUE:0.4512, MATIC-USD:-0.9383, MORT:0.7550, LQD:-0.0245\nCovariance matrix (annualized):\n[[0.028267, 0.041736, 0.029867, 0.001434], [0.041736, 0.768061, 0.059615, -0.003739], [0.029867, 0.059615, 0.052401, 0.000234], [0.001434, -0.003739, 0.000234, 0.004092]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0235, w_MATIC-USD=0.0000, w_MORT=0.9765, w_LQD=0.0000", "answer_numeric": 3.1237657395915774, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0235, w_MATIC-USD=0.0000, w_MORT=0.9765, w_LQD=0.0000\nPortfolio annualized return: 74.79%, volatility: 22.66%\nSharpe ratio: (0.7479 - 0.0400) / 0.2266 = 3.1238", "metadata": {"weights": {"VLUE": 0.0235, "MATIC-USD": 0.0, "MORT": 0.9765, "LQD": 0.0}, "sharpe_ratio": 3.1238, "portfolio_return": 0.74788, "portfolio_vol": 0.226611, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220902_0653", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "SCHH", "ICSH"], "decision_date": "2022-09-02", "context_summary": "4-asset optimization. Max-Sharpe: 0.056. Portfolio: return=4.99%, vol=17.71%. Weights: w_EFA=0.0000, w_ADA-USD=0.0000, w_SCHH=1.0000, w_ICSH=0.0000.", "question": "Assets: EFA, ADA-USD, SCHH, ICSH\nAnnualized mean returns: EFA:-0.1739, ADA-USD:-0.7958, SCHH:0.0499, ICSH:0.0179\nCovariance matrix (annualized):\n[[0.035535, 0.072366, 0.022087, 2.3e-05], [0.072366, 0.452358, 0.034836, -0.000355], [0.022087, 0.034836, 0.031381, -4e-05], [2.3e-05, -0.000355, -4e-05, 1.7e-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_EFA=0.0000, w_ADA-USD=0.0000, w_SCHH=1.0000, w_ICSH=0.0000", "answer_numeric": 0.056063800182789156, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_ADA-USD=0.0000, w_SCHH=1.0000, w_ICSH=0.0000\nPortfolio annualized return: 4.99%, volatility: 17.71%\nSharpe ratio: (0.0499 - 0.0400) / 0.1771 = 0.0561", "metadata": {"weights": {"EFA": 0.0, "ADA-USD": 0.0, "SCHH": 1.0, "ICSH": 0.0}, "sharpe_ratio": 0.0561, "portfolio_return": 0.049931, "portfolio_vol": 0.177146, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200417_0656", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "IYR", "LQD"], "decision_date": "2020-04-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.616. Portfolio: return=369.50%, vol=139.73%. Weights: w_IWM=0.0000, w_MATIC-USD=1.0000, w_IYR=0.0000, w_LQD=0.0000.", "question": "Assets: IWM, MATIC-USD, IYR, LQD\nAnnualized mean returns: IWM:-1.0724, MATIC-USD:3.6950, IYR:-0.9343, LQD:0.0155\nCovariance matrix (annualized):\n[[0.198703, 0.375445, 0.164928, 0.022344], [0.375445, 1.952418, 0.2646, 0.055121], [0.164928, 0.2646, 0.169139, 0.022354], [0.022344, 0.055121, 0.022354, 0.022346]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_IYR=0.0000, w_LQD=0.0000", "answer_numeric": 2.615760419615558, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_MATIC-USD=1.0000, w_IYR=0.0000, w_LQD=0.0000\nPortfolio annualized return: 369.50%, volatility: 139.73%\nSharpe ratio: (3.6950 - 0.0400) / 1.3973 = 2.6158", "metadata": {"weights": {"IWM": 0.0, "MATIC-USD": 1.0, "IYR": 0.0, "LQD": 0.0}, "sharpe_ratio": 2.6158, "portfolio_return": 3.694974, "portfolio_vol": 1.397289, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210817_0658", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "STIP", "BIL"], "decision_date": "2021-08-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.522. Portfolio: return=11.60%, vol=2.16%. Weights: w_XLP=0.1257, w_DOT-USD=0.0035, w_STIP=0.8708, w_BIL=0.0000.", "question": "Assets: XLP, DOT-USD, STIP, BIL\nAnnualized mean returns: XLP:0.2883, DOT-USD:0.2050, STIP:0.0907, BIL:-0.0013\nCovariance matrix (annualized):\n[[0.009387, -0.015714, 0.000455, -3.5e-05], [-0.015714, 1.107488, -0.001049, 3.6e-05], [0.000455, -0.001049, 0.000295, -3e-06], [-3.5e-05, 3.6e-05, -3e-06, 2e-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=0.1257, w_DOT-USD=0.0035, w_STIP=0.8708, w_BIL=0.0000", "answer_numeric": 3.5218113920092367, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.1257, w_DOT-USD=0.0035, w_STIP=0.8708, w_BIL=0.0000\nPortfolio annualized return: 11.60%, volatility: 2.16%\nSharpe ratio: (0.1160 - 0.0400) / 0.0216 = 3.5218", "metadata": {"weights": {"XLP": 0.1257, "DOT-USD": 0.0035, "STIP": 0.8708, "BIL": 0.0}, "sharpe_ratio": 3.5218, "portfolio_return": 0.115969, "portfolio_vol": 0.021571, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220701_0660", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "DBC", "BIL"], "decision_date": "2022-07-01", "context_summary": "4-asset optimization. Max-Sharpe: -0.381. Portfolio: return=-4.72%, vol=22.90%. Weights: w_XLY=0.0000, w_BTC-USD=0.0000, w_DBC=1.0000, w_BIL=0.0000.", "question": "Assets: XLY, BTC-USD, DBC, BIL\nAnnualized mean returns: XLY:-0.6826, BTC-USD:-3.9679, DBC:-0.0472, BIL:0.0066\nCovariance matrix (annualized):\n[[0.153522, 0.175207, 0.023093, 0.000157], [0.175207, 0.439555, 0.02967, 0.000225], [0.023093, 0.02967, 0.052458, 0.000124], [0.000157, 0.000225, 0.000124, 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_XLY=0.0000, w_BTC-USD=0.0000, w_DBC=1.0000, w_BIL=0.0000", "answer_numeric": -0.3806552332719155, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_BTC-USD=0.0000, w_DBC=1.0000, w_BIL=0.0000\nPortfolio annualized return: -4.72%, volatility: 22.90%\nSharpe ratio: (-0.0472 - 0.0400) / 0.2290 = -0.3807", "metadata": {"weights": {"XLY": 0.0, "BTC-USD": 0.0, "DBC": 1.0, "BIL": 0.0}, "sharpe_ratio": -0.3807, "portfolio_return": -0.047184, "portfolio_vol": 0.229038, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220125_0663", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "XHB", "CPER"], "decision_date": "2022-01-25", "context_summary": "4-asset optimization. Max-Sharpe: -0.106. Portfolio: return=-8.80%, vol=120.79%. Weights: w_QUAL=0.0000, w_MATIC-USD=1.0000, w_XHB=0.0000, w_CPER=0.0000.", "question": "Assets: QUAL, MATIC-USD, XHB, CPER\nAnnualized mean returns: QUAL:-0.5731, MATIC-USD:-0.0880, XHB:-0.6380, CPER:-0.0276\nCovariance matrix (annualized):\n[[0.036541, 0.132548, 0.04303, 0.020815], [0.132548, 1.459015, 0.164924, 0.083199], [0.04303, 0.164924, 0.077617, 0.022463], [0.020815, 0.083199, 0.022463, 0.04781]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_XHB=0.0000, w_CPER=0.0000", "answer_numeric": -0.10600866058760908, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_MATIC-USD=1.0000, w_XHB=0.0000, w_CPER=0.0000\nPortfolio annualized return: -8.80%, volatility: 120.79%\nSharpe ratio: (-0.0880 - 0.0400) / 1.2079 = -0.1060", "metadata": {"weights": {"QUAL": 0.0, "MATIC-USD": 1.0, "XHB": 0.0, "CPER": 0.0}, "sharpe_ratio": -0.106, "portfolio_return": -0.088048, "portfolio_vol": 1.207897, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201002_0665", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "SOL-USD", "GLD", "VNQ"], "decision_date": "2020-10-02", "context_summary": "4-asset optimization. Max-Sharpe: 1.998. Portfolio: return=77.18%, vol=36.62%. Weights: w_XLK=0.8793, w_SOL-USD=0.1207, w_GLD=0.0000, w_VNQ=0.0000.", "question": "Assets: XLK, SOL-USD, GLD, VNQ\nAnnualized mean returns: XLK:0.5124, SOL-USD:2.6606, GLD:0.0269, VNQ:0.0071\nCovariance matrix (annualized):\n[[0.073055, 0.185162, 0.016968, 0.031113], [0.185162, 2.630035, 0.089191, 0.025102], [0.016968, 0.089191, 0.034042, 0.012944], [0.031113, 0.025102, 0.012944, 0.047832]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8793, w_SOL-USD=0.1207, w_GLD=0.0000, w_VNQ=0.0000", "answer_numeric": 1.9980587169651807, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.8793, w_SOL-USD=0.1207, w_GLD=0.0000, w_VNQ=0.0000\nPortfolio annualized return: 77.18%, volatility: 36.62%\nSharpe ratio: (0.7718 - 0.0400) / 0.3662 = 1.9981", "metadata": {"weights": {"XLK": 0.8793, "SOL-USD": 0.1207, "GLD": 0.0, "VNQ": 0.0}, "sharpe_ratio": 1.9981, "portfolio_return": 0.771778, "portfolio_vol": 0.366245, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220412_0667", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BNB-USD", "TLH", "INDS"], "decision_date": "2022-04-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.840. Portfolio: return=67.47%, vol=22.35%. Weights: w_XLE=0.6230, w_BNB-USD=0.1956, w_TLH=0.0000, w_INDS=0.1814.", "question": "Assets: XLE, BNB-USD, TLH, INDS\nAnnualized mean returns: XLE:0.7958, BNB-USD:0.7731, TLH:-0.4650, INDS:0.1530\nCovariance matrix (annualized):\n[[0.099132, -0.01153, 0.005345, -0.000103], [-0.01153, 0.318924, 0.004525, 0.013818], [0.005345, 0.004525, 0.023919, 0.001037], [-0.000103, 0.013818, 0.001037, 0.034478]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6230, w_BNB-USD=0.1956, w_TLH=0.0000, w_INDS=0.1814", "answer_numeric": 2.8398385861010866, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.6230, w_BNB-USD=0.1956, w_TLH=0.0000, w_INDS=0.1814\nPortfolio annualized return: 67.47%, volatility: 22.35%\nSharpe ratio: (0.6747 - 0.0400) / 0.2235 = 2.8398", "metadata": {"weights": {"XLE": 0.623, "BNB-USD": 0.1956, "TLH": 0.0, "INDS": 0.1814}, "sharpe_ratio": 2.8398, "portfolio_return": 0.674743, "portfolio_vol": 0.223514, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211101_0669", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "WEAT", "ICSH"], "decision_date": "2021-11-01", "context_summary": "4-asset optimization. Max-Sharpe: 2.101. Portfolio: return=55.01%, vol=24.27%. Weights: w_EFA=0.0000, w_BTC-USD=0.0990, w_WEAT=0.9010, w_ICSH=0.0000.", "question": "Assets: EFA, BTC-USD, WEAT, ICSH\nAnnualized mean returns: EFA:-0.0668, BTC-USD:1.0929, WEAT:0.4904, ICSH:-0.0029\nCovariance matrix (annualized):\n[[0.01494, 0.023675, 0.006367, -6.9e-05], [0.023675, 0.506169, 0.07934, 0.000305], [0.006367, 0.07934, 0.04902, 0.000114], [-6.9e-05, 0.000305, 0.000114, 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=0.0000, w_BTC-USD=0.0990, w_WEAT=0.9010, w_ICSH=0.0000", "answer_numeric": 2.1014681906370796, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_BTC-USD=0.0990, w_WEAT=0.9010, w_ICSH=0.0000\nPortfolio annualized return: 55.01%, volatility: 24.27%\nSharpe ratio: (0.5501 - 0.0400) / 0.2427 = 2.1015", "metadata": {"weights": {"EFA": 0.0, "BTC-USD": 0.099, "WEAT": 0.901, "ICSH": 0.0}, "sharpe_ratio": 2.1015, "portfolio_return": 0.550082, "portfolio_vol": 0.242726, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}}
{"id": "T5_all_20220411_0672", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BTC-USD", "ITB", "IEF"], "decision_date": "2022-04-11", "context_summary": "4-asset optimization. Max-Sharpe: 0.691. Portfolio: return=45.67%, vol=60.27%. Weights: w_QQQ=0.0000, w_BTC-USD=1.0000, w_ITB=0.0000, w_IEF=0.0000.", "question": "Assets: QQQ, BTC-USD, ITB, IEF\nAnnualized mean returns: QQQ:-0.3175, BTC-USD:0.4567, ITB:-1.1780, IEF:-0.3050\nCovariance matrix (annualized):\n[[0.10008, 0.105074, 0.095198, -0.002539], [0.105074, 0.363216, 0.08123, -0.002792], [0.095198, 0.08123, 0.142077, 0.002675], [-0.002539, -0.002792, 0.002675, 0.00954]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_ITB=0.0000, w_IEF=0.0000", "answer_numeric": 0.6913389948920868, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_BTC-USD=1.0000, w_ITB=0.0000, w_IEF=0.0000\nPortfolio annualized return: 45.67%, volatility: 60.27%\nSharpe ratio: (0.4567 - 0.0400) / 0.6027 = 0.6913", "metadata": {"weights": {"QQQ": 0.0, "BTC-USD": 1.0, "ITB": 0.0, "IEF": 0.0}, "sharpe_ratio": 0.6913, "portfolio_return": 0.456652, "portfolio_vol": 0.602674, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190220_0676", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "REZ", "IEF"], "decision_date": "2019-02-20", "context_summary": "4-asset optimization. Max-Sharpe: 6.853. Portfolio: return=30.94%, vol=3.93%. Weights: w_USMV=0.3198, w_ADA-USD=0.0135, w_REZ=0.0343, w_IEF=0.6324.", "question": "Assets: USMV, ADA-USD, REZ, IEF\nAnnualized mean returns: USMV:0.6770, ADA-USD:0.1100, REZ:0.7359, IEF:0.1046\nCovariance matrix (annualized):\n[[0.019097, -0.024038, 0.012731, -0.004054], [-0.024038, 0.707789, -0.050341, 0.000375], [0.012731, -0.050341, 0.032075, -0.000788], [-0.004054, 0.000375, -0.000788, 0.002671]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3198, w_ADA-USD=0.0135, w_REZ=0.0343, w_IEF=0.6324", "answer_numeric": 6.852984298305518, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.3198, w_ADA-USD=0.0135, w_REZ=0.0343, w_IEF=0.6324\nPortfolio annualized return: 30.94%, volatility: 3.93%\nSharpe ratio: (0.3094 - 0.0400) / 0.0393 = 6.8530", "metadata": {"weights": {"USMV": 0.3198, "ADA-USD": 0.0135, "REZ": 0.0343, "IEF": 0.6324}, "sharpe_ratio": 6.853, "portfolio_return": 0.309368, "portfolio_vol": 0.039307, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201113_0680", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "PALL", "XHB"], "decision_date": "2020-11-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.379. Portfolio: return=30.60%, vol=19.29%. Weights: w_XLV=0.5919, w_LINK-USD=0.0000, w_PALL=0.0000, w_XHB=0.4081.", "question": "Assets: XLV, LINK-USD, PALL, XHB\nAnnualized mean returns: XLV:0.2562, LINK-USD:-0.6070, PALL:0.1377, XHB:0.3781\nCovariance matrix (annualized):\n[[0.032497, 0.052826, 0.023414, 0.027006], [0.052826, 0.977643, 0.063301, 0.043783], [0.023414, 0.063301, 0.125688, 0.020404], [0.027006, 0.043783, 0.020404, 0.076768]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5919, w_LINK-USD=0.0000, w_PALL=0.0000, w_XHB=0.4081", "answer_numeric": 1.3786566133161668, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.5919, w_LINK-USD=0.0000, w_PALL=0.0000, w_XHB=0.4081\nPortfolio annualized return: 30.60%, volatility: 19.29%\nSharpe ratio: (0.3060 - 0.0400) / 0.1929 = 1.3787", "metadata": {"weights": {"XLV": 0.5919, "LINK-USD": 0.0, "PALL": 0.0, "XHB": 0.4081}, "sharpe_ratio": 1.3787, "portfolio_return": 0.305962, "portfolio_vol": 0.192914, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200529_0685", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "MORT", "BIL"], "decision_date": "2020-05-29", "context_summary": "4-asset optimization. Max-Sharpe: 6.055. Portfolio: return=441.47%, vol=72.25%. Weights: w_XLP=0.0000, w_LINK-USD=1.0000, w_MORT=0.0000, w_BIL=0.0000.", "question": "Assets: XLP, LINK-USD, MORT, BIL\nAnnualized mean returns: XLP:0.2537, LINK-USD:4.4147, MORT:-0.3277, BIL:-0.0016\nCovariance matrix (annualized):\n[[0.04304, 0.047231, 0.037274, 1.6e-05], [0.047231, 0.522015, 0.119467, -0.00025], [0.037274, 0.119467, 0.269379, 4.7e-05], [1.6e-05, -0.00025, 4.7e-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_XLP=0.0000, w_LINK-USD=1.0000, w_MORT=0.0000, w_BIL=0.0000", "answer_numeric": 6.054952076307501, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_LINK-USD=1.0000, w_MORT=0.0000, w_BIL=0.0000\nPortfolio annualized return: 441.47%, volatility: 72.25%\nSharpe ratio: (4.4147 - 0.0400) / 0.7225 = 6.0550", "metadata": {"weights": {"XLP": 0.0, "LINK-USD": 1.0, "MORT": 0.0, "BIL": 0.0}, "sharpe_ratio": 6.055, "portfolio_return": 4.414738, "portfolio_vol": 0.722506, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200630_0687", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "XRP-USD", "GLD", "HYG"], "decision_date": "2020-06-30", "context_summary": "4-asset optimization. Max-Sharpe: 3.915. Portfolio: return=56.12%, vol=13.31%. Weights: w_XLK=0.4874, w_XRP-USD=0.0000, w_GLD=0.5126, w_HYG=0.0000.", "question": "Assets: XLK, XRP-USD, GLD, HYG\nAnnualized mean returns: XLK:0.8301, XRP-USD:-0.2342, GLD:0.3054, HYG:0.1681\nCovariance matrix (annualized):\n[[0.056884, 0.016748, -0.001686, 0.017793], [0.016748, 0.095232, 0.014846, 0.006018], [-0.001686, 0.014846, 0.019208, -0.003648], [0.017793, 0.006018, -0.003648, 0.011552]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4874, w_XRP-USD=0.0000, w_GLD=0.5126, w_HYG=0.0000", "answer_numeric": 3.9152083611742, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.4874, w_XRP-USD=0.0000, w_GLD=0.5126, w_HYG=0.0000\nPortfolio annualized return: 56.12%, volatility: 13.31%\nSharpe ratio: (0.5612 - 0.0400) / 0.1331 = 3.9152", "metadata": {"weights": {"XLK": 0.4874, "XRP-USD": 0.0, "GLD": 0.5126, "HYG": 0.0}, "sharpe_ratio": 3.9152, "portfolio_return": 0.561167, "portfolio_vol": 0.133113, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210104_0690", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "MATIC-USD", "VNQI", "SOYB"], "decision_date": "2021-01-04", "context_summary": "4-asset optimization. Max-Sharpe: 8.834. Portfolio: return=89.67%, vol=9.70%. Weights: w_XLK=0.3695, w_MATIC-USD=0.0059, w_VNQI=0.0197, w_SOYB=0.6048.", "question": "Assets: XLK, MATIC-USD, VNQI, SOYB\nAnnualized mean returns: XLK:0.6693, MATIC-USD:2.6114, VNQI:0.7148, SOYB:1.0248\nCovariance matrix (annualized):\n[[0.025585, 0.010079, 0.008168, -0.004576], [0.010079, 1.027993, 0.003661, 0.030298], [0.008168, 0.003661, 0.025091, 0.006404], [-0.004576, 0.030298, 0.006404, 0.020165]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3695, w_MATIC-USD=0.0059, w_VNQI=0.0197, w_SOYB=0.6048", "answer_numeric": 8.834094171419219, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.3695, w_MATIC-USD=0.0059, w_VNQI=0.0197, w_SOYB=0.6048\nPortfolio annualized return: 89.67%, volatility: 9.70%\nSharpe ratio: (0.8967 - 0.0400) / 0.0970 = 8.8341", "metadata": {"weights": {"XLK": 0.3695, "MATIC-USD": 0.0059, "VNQI": 0.0197, "SOYB": 0.6048}, "sharpe_ratio": 8.8341, "portfolio_return": 0.896745, "portfolio_vol": 0.096982, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200212_0694", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "MATIC-USD", "CORN", "VCIT"], "decision_date": "2020-02-12", "context_summary": "4-asset optimization. Max-Sharpe: 8.746. Portfolio: return=18.88%, vol=1.70%. Weights: w_ACWI=0.1532, w_MATIC-USD=0.0082, w_CORN=0.0000, w_VCIT=0.8387.", "question": "Assets: ACWI, MATIC-USD, CORN, VCIT\nAnnualized mean returns: ACWI:0.2642, MATIC-USD:3.7547, CORN:-0.0985, VCIT:0.1403\nCovariance matrix (annualized):\n[[0.012219, 0.00479, 0.003767, -0.001758], [0.00479, 1.07587, -0.006485, -0.002729], [0.003767, -0.006485, 0.017844, -0.00068], [-0.001758, -0.002729, -0.00068, 0.00058]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1532, w_MATIC-USD=0.0082, w_CORN=0.0000, w_VCIT=0.8387", "answer_numeric": 8.746433617452555, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.1532, w_MATIC-USD=0.0082, w_CORN=0.0000, w_VCIT=0.8387\nPortfolio annualized return: 18.88%, volatility: 1.70%\nSharpe ratio: (0.1888 - 0.0400) / 0.0170 = 8.7464", "metadata": {"weights": {"ACWI": 0.1532, "MATIC-USD": 0.0082, "CORN": 0.0, "VCIT": 0.8387}, "sharpe_ratio": 8.7464, "portfolio_return": 0.188812, "portfolio_vol": 0.017014, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200731_0702", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "MATIC-USD", "BIL", "BNO"], "decision_date": "2020-07-31", "context_summary": "4-asset optimization. Max-Sharpe: 3.215. Portfolio: return=73.36%, vol=21.57%. Weights: w_MTUM=0.7761, w_MATIC-USD=0.0000, w_BIL=0.0000, w_BNO=0.2239.", "question": "Assets: MTUM, MATIC-USD, BIL, BNO\nAnnualized mean returns: MTUM:0.6724, MATIC-USD:-0.0311, BIL:0.0000, BNO:0.9455\nCovariance matrix (annualized):\n[[0.042593, 0.023086, 6.7e-05, 0.041877], [0.023086, 0.293227, 0.000366, 0.02673], [6.7e-05, 0.000366, 2e-06, 6.3e-05], [0.041877, 0.02673, 6.3e-05, 0.126195]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7761, w_MATIC-USD=0.0000, w_BIL=0.0000, w_BNO=0.2239", "answer_numeric": 3.2151228496605007, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.7761, w_MATIC-USD=0.0000, w_BIL=0.0000, w_BNO=0.2239\nPortfolio annualized return: 73.36%, volatility: 21.57%\nSharpe ratio: (0.7336 - 0.0400) / 0.2157 = 3.2151", "metadata": {"weights": {"MTUM": 0.7761, "MATIC-USD": 0.0, "BIL": 0.0, "BNO": 0.2239}, "sharpe_ratio": 3.2151, "portfolio_return": 0.733559, "portfolio_vol": 0.215718, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200310_0704", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MATIC-USD", "IAU", "VCIT"], "decision_date": "2020-03-10", "context_summary": "4-asset optimization. Max-Sharpe: 5.776. Portfolio: return=54.29%, vol=8.71%. Weights: w_FXI=0.0000, w_MATIC-USD=0.0615, w_IAU=0.2811, w_VCIT=0.6574.", "question": "Assets: FXI, MATIC-USD, IAU, VCIT\nAnnualized mean returns: FXI:-0.8455, MATIC-USD:4.5616, IAU:0.5386, VCIT:0.1690\nCovariance matrix (annualized):\n[[0.069821, 0.072418, -0.010128, -0.000526], [0.072418, 0.959807, 0.023478, 0.003886], [-0.010128, 0.023478, 0.01978, 0.000779], [-0.000526, 0.003886, 0.000779, 0.002261]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0615, w_IAU=0.2811, w_VCIT=0.6574", "answer_numeric": 5.776252802637301, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_MATIC-USD=0.0615, w_IAU=0.2811, w_VCIT=0.6574\nPortfolio annualized return: 54.29%, volatility: 8.71%\nSharpe ratio: (0.5429 - 0.0400) / 0.0871 = 5.7763", "metadata": {"weights": {"FXI": 0.0, "MATIC-USD": 0.0615, "IAU": 0.2811, "VCIT": 0.6574}, "sharpe_ratio": 5.7763, "portfolio_return": 0.54295, "portfolio_vol": 0.087072, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180918_0708", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "MORT", "IAU"], "decision_date": "2018-09-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.435. Portfolio: return=28.58%, vol=5.54%. Weights: w_USMV=1.0000, w_XRP-USD=0.0000, w_MORT=0.0000, w_IAU=0.0000.", "question": "Assets: USMV, XRP-USD, MORT, IAU\nAnnualized mean returns: USMV:0.2858, XRP-USD:-1.8030, MORT:0.0564, IAU:-0.1171\nCovariance matrix (annualized):\n[[0.003072, 0.015904, 0.000632, 0.002102], [0.015904, 0.99218, 0.00711, 0.008771], [0.000632, 0.00711, 0.005642, 0.000128], [0.002102, 0.008771, 0.000128, 0.009378]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_MORT=0.0000, w_IAU=0.0000", "answer_numeric": 4.434630641831686, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=1.0000, w_XRP-USD=0.0000, w_MORT=0.0000, w_IAU=0.0000\nPortfolio annualized return: 28.58%, volatility: 5.54%\nSharpe ratio: (0.2858 - 0.0400) / 0.0554 = 4.4346", "metadata": {"weights": {"USMV": 1.0, "XRP-USD": 0.0, "MORT": 0.0, "IAU": 0.0}, "sharpe_ratio": 4.4346, "portfolio_return": 0.285774, "portfolio_vol": 0.055422, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210210_0711", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "DOT-USD", "BIL", "BNDX"], "decision_date": "2021-02-10", "context_summary": "4-asset optimization. Max-Sharpe: 5.703. Portfolio: return=243.92%, vol=42.07%. Weights: w_IVV=0.7832, w_DOT-USD=0.2168, w_BIL=0.0000, w_BNDX=0.0000.", "question": "Assets: IVV, DOT-USD, BIL, BNDX\nAnnualized mean returns: IVV:0.4387, DOT-USD:9.6654, BIL:0.0000, BNDX:-0.0606\nCovariance matrix (annualized):\n[[0.019456, 0.065336, 8e-06, 0.00055], [0.065336, 3.038468, 0.000444, 0.011433], [8e-06, 0.000444, 1e-06, 3e-06], [0.00055, 0.011433, 3e-06, 0.000423]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7832, w_DOT-USD=0.2168, w_BIL=0.0000, w_BNDX=0.0000", "answer_numeric": 5.703250954831214, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.7832, w_DOT-USD=0.2168, w_BIL=0.0000, w_BNDX=0.0000\nPortfolio annualized return: 243.92%, volatility: 42.07%\nSharpe ratio: (2.4392 - 0.0400) / 0.4207 = 5.7033", "metadata": {"weights": {"IVV": 0.7832, "DOT-USD": 0.2168, "BIL": 0.0, "BNDX": 0.0}, "sharpe_ratio": 5.7033, "portfolio_return": 2.439181, "portfolio_vol": 0.420669, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181115_0713", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "REZ", "LQD"], "decision_date": "2018-11-15", "context_summary": "4-asset optimization. Max-Sharpe: 2.617. Portfolio: return=363.76%, vol=137.46%. Weights: w_XLRE=0.0000, w_XRP-USD=1.0000, w_REZ=0.0000, w_LQD=0.0000.", "question": "Assets: XLRE, XRP-USD, REZ, LQD\nAnnualized mean returns: XLRE:0.0037, XRP-USD:3.6376, REZ:0.1044, LQD:-0.1366\nCovariance matrix (annualized):\n[[0.032289, 0.073385, 0.032437, 0.00105], [0.073385, 1.889566, 0.073498, 0.00445], [0.032437, 0.073498, 0.036122, 0.001808], [0.00105, 0.00445, 0.001808, 0.001519]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=1.0000, w_REZ=0.0000, w_LQD=0.0000", "answer_numeric": 2.6171359175114297, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_XRP-USD=1.0000, w_REZ=0.0000, w_LQD=0.0000\nPortfolio annualized return: 363.76%, volatility: 137.46%\nSharpe ratio: (3.6376 - 0.0400) / 1.3746 = 2.6171", "metadata": {"weights": {"XLRE": 0.0, "XRP-USD": 1.0, "REZ": 0.0, "LQD": 0.0}, "sharpe_ratio": 2.6171, "portfolio_return": 3.637554, "portfolio_vol": 1.374615, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20160526_0719", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "HYG", "SLV"], "decision_date": "2016-05-26", "context_summary": "4-asset optimization. Max-Sharpe: 3.614. Portfolio: return=24.10%, vol=5.56%. Weights: w_VLUE=0.0000, w_BTC-USD=0.1003, w_HYG=0.8362, w_SLV=0.0635.", "question": "Assets: VLUE, BTC-USD, HYG, SLV\nAnnualized mean returns: VLUE:0.1580, BTC-USD:0.2099, HYG:0.2291, SLV:0.4471\nCovariance matrix (annualized):\n[[0.016389, -0.005667, 0.00639, -0.001277], [-0.005667, 0.043678, -0.002975, 0.011373], [0.00639, -0.002975, 0.003698, 0.001828], [-0.001277, 0.011373, 0.001828, 0.056595]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1003, w_HYG=0.8362, w_SLV=0.0635", "answer_numeric": 3.6142993243488815, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_BTC-USD=0.1003, w_HYG=0.8362, w_SLV=0.0635\nPortfolio annualized return: 24.10%, volatility: 5.56%\nSharpe ratio: (0.2410 - 0.0400) / 0.0556 = 3.6143", "metadata": {"weights": {"VLUE": 0.0, "BTC-USD": 0.1003, "HYG": 0.8362, "SLV": 0.0635}, "sharpe_ratio": 3.6143, "portfolio_return": 0.241035, "portfolio_vol": 0.055622, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220729_0721", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BNB-USD", "SGOV", "XHB"], "decision_date": "2022-07-29", "context_summary": "4-asset optimization. Max-Sharpe: 0.898. Portfolio: return=30.82%, vol=29.88%. Weights: w_USMV=0.0000, w_BNB-USD=0.0000, w_SGOV=0.0000, w_XHB=1.0000.", "question": "Assets: USMV, BNB-USD, SGOV, XHB\nAnnualized mean returns: USMV:-0.0302, BNB-USD:-0.3552, SGOV:0.0092, XHB:0.3082\nCovariance matrix (annualized):\n[[0.034052, 0.069748, -7e-06, 0.044995], [0.069748, 0.462509, 0.000176, 0.120569], [-7e-06, 0.000176, 3e-06, -1.9e-05], [0.044995, 0.120569, -1.9e-05, 0.089293]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_SGOV=0.0000, w_XHB=1.0000", "answer_numeric": 0.8975098437327466, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_BNB-USD=0.0000, w_SGOV=0.0000, w_XHB=1.0000\nPortfolio annualized return: 30.82%, volatility: 29.88%\nSharpe ratio: (0.3082 - 0.0400) / 0.2988 = 0.8975", "metadata": {"weights": {"USMV": 0.0, "BNB-USD": 0.0, "SGOV": 0.0, "XHB": 1.0}, "sharpe_ratio": 0.8975, "portfolio_return": 0.308194, "portfolio_vol": 0.29882, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}}
{"id": "T5_all_20170124_0723", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "SCHH", "CPER"], "decision_date": "2017-01-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.390. Portfolio: return=32.41%, vol=8.38%. Weights: w_IVV=0.6119, w_BTC-USD=0.0552, w_SCHH=0.3120, w_CPER=0.0208.", "question": "Assets: IVV, BTC-USD, SCHH, CPER\nAnnualized mean returns: IVV:0.1970, BTC-USD:1.2266, SCHH:0.4305, CPER:0.0725\nCovariance matrix (annualized):\n[[0.004568, -0.00585, 0.004436, 0.001232], [-0.00585, 0.525455, 0.0114, 0.015968], [0.004436, 0.0114, 0.020621, -0.005945], [0.001232, 0.015968, -0.005945, 0.049027]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6119, w_BTC-USD=0.0552, w_SCHH=0.3120, w_CPER=0.0208", "answer_numeric": 3.3901323057409263, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.6119, w_BTC-USD=0.0552, w_SCHH=0.3120, w_CPER=0.0208\nPortfolio annualized return: 32.41%, volatility: 8.38%\nSharpe ratio: (0.3241 - 0.0400) / 0.0838 = 3.3901", "metadata": {"weights": {"IVV": 0.6119, "BTC-USD": 0.0552, "SCHH": 0.312, "CPER": 0.0208}, "sharpe_ratio": 3.3901, "portfolio_return": 0.324146, "portfolio_vol": 0.083816, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190715_0727", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "MATIC-USD", "REZ", "DBA"], "decision_date": "2019-07-15", "context_summary": "4-asset optimization. Max-Sharpe: 4.726. Portfolio: return=41.35%, vol=7.90%. Weights: w_EWJ=0.1650, w_MATIC-USD=0.0162, w_REZ=0.3393, w_DBA=0.4795.", "question": "Assets: EWJ, MATIC-USD, REZ, DBA\nAnnualized mean returns: EWJ:0.2216, MATIC-USD:3.1548, REZ:0.3779, DBA:0.4120\nCovariance matrix (annualized):\n[[0.012282, -0.020127, 0.002504, 0.001013], [-0.020127, 3.500313, -0.011594, 0.005435], [0.002504, -0.011594, 0.021359, -0.003801], [0.001013, 0.005435, -0.003801, 0.015129]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1650, w_MATIC-USD=0.0162, w_REZ=0.3393, w_DBA=0.4795", "answer_numeric": 4.72632930786965, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.1650, w_MATIC-USD=0.0162, w_REZ=0.3393, w_DBA=0.4795\nPortfolio annualized return: 41.35%, volatility: 7.90%\nSharpe ratio: (0.4135 - 0.0400) / 0.0790 = 4.7263", "metadata": {"weights": {"EWJ": 0.165, "MATIC-USD": 0.0162, "REZ": 0.3393, "DBA": 0.4795}, "sharpe_ratio": 4.7263, "portfolio_return": 0.413469, "portfolio_vol": 0.079019, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20150610_0729", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "BIL", "SCHH"], "decision_date": "2015-06-10", "context_summary": "4-asset optimization. Max-Sharpe: 1.120. Portfolio: return=41.57%, vol=33.54%. Weights: w_FXI=0.0000, w_BTC-USD=1.0000, w_BIL=0.0000, w_SCHH=0.0000.", "question": "Assets: FXI, BTC-USD, BIL, SCHH\nAnnualized mean returns: FXI:-0.2545, BTC-USD:0.4157, BIL:-0.0027, SCHH:-0.4334\nCovariance matrix (annualized):\n[[0.067297, 0.028613, 0.000139, 0.019488], [0.028613, 0.112506, 0.000195, 0.001867], [0.000139, 0.000195, 6e-06, 5e-06], [0.019488, 0.001867, 5e-06, 0.02264]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_BIL=0.0000, w_SCHH=0.0000", "answer_numeric": 1.1201715394888812, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_BTC-USD=1.0000, w_BIL=0.0000, w_SCHH=0.0000\nPortfolio annualized return: 41.57%, volatility: 33.54%\nSharpe ratio: (0.4157 - 0.0400) / 0.3354 = 1.1202", "metadata": {"weights": {"FXI": 0.0, "BTC-USD": 1.0, "BIL": 0.0, "SCHH": 0.0}, "sharpe_ratio": 1.1202, "portfolio_return": 0.415726, "portfolio_vol": 0.335419, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220314_0731", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ETH-USD", "BNDX", "USO"], "decision_date": "2022-03-14", "context_summary": "4-asset optimization. Max-Sharpe: 5.120. Portfolio: return=193.71%, vol=37.05%. Weights: w_XLY=0.0000, w_ETH-USD=0.0000, w_BNDX=0.0000, w_USO=1.0000.", "question": "Assets: XLY, ETH-USD, BNDX, USO\nAnnualized mean returns: XLY:-1.1463, ETH-USD:-0.3818, BNDX:-0.1929, USO:1.9371\nCovariance matrix (annualized):\n[[0.104743, 0.163009, -0.003046, -0.039157], [0.163009, 0.6567, -0.007545, -0.025161], [-0.003046, -0.007545, 0.003488, 0.003933], [-0.039157, -0.025161, 0.003933, 0.137293]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNDX=0.0000, w_USO=1.0000", "answer_numeric": 5.1199884708188215, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_ETH-USD=0.0000, w_BNDX=0.0000, w_USO=1.0000\nPortfolio annualized return: 193.71%, volatility: 37.05%\nSharpe ratio: (1.9371 - 0.0400) / 0.3705 = 5.1200", "metadata": {"weights": {"XLY": 0.0, "ETH-USD": 0.0, "BNDX": 0.0, "USO": 1.0}, "sharpe_ratio": 5.12, "portfolio_return": 1.937114, "portfolio_vol": 0.370531, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180112_0733", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "XRP-USD", "MORT", "ICSH"], "decision_date": "2018-01-12", "context_summary": "4-asset optimization. Max-Sharpe: 6.941. Portfolio: return=68.46%, vol=9.29%. Weights: w_VEA=0.7040, w_XRP-USD=0.0321, w_MORT=0.2639, w_ICSH=0.0000.", "question": "Assets: VEA, XRP-USD, MORT, ICSH\nAnnualized mean returns: VEA:0.3751, XRP-USD:11.5354, MORT:0.1917, ICSH:0.0166\nCovariance matrix (annualized):\n[[0.005176, 0.027259, -0.000128, 2.4e-05], [0.027259, 4.45663, -0.031415, 0.00072], [-0.000128, -0.031415, 0.011848, -9.3e-05], [2.4e-05, 0.00072, -9.3e-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_VEA=0.7040, w_XRP-USD=0.0321, w_MORT=0.2639, w_ICSH=0.0000", "answer_numeric": 6.9409727151926415, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.7040, w_XRP-USD=0.0321, w_MORT=0.2639, w_ICSH=0.0000\nPortfolio annualized return: 68.46%, volatility: 9.29%\nSharpe ratio: (0.6846 - 0.0400) / 0.0929 = 6.9410", "metadata": {"weights": {"VEA": 0.704, "XRP-USD": 0.0321, "MORT": 0.2639, "ICSH": 0.0}, "sharpe_ratio": 6.941, "portfolio_return": 0.684591, "portfolio_vol": 0.092868, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181015_0741", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ETH-USD", "ICSH", "VNQ"], "decision_date": "2018-10-15", "context_summary": "4-asset optimization. Max-Sharpe: -1.118. Portfolio: return=-103.87%, vol=96.48%. Weights: w_XLB=0.0000, w_ETH-USD=1.0000, w_ICSH=0.0000, w_VNQ=0.0000.", "question": "Assets: XLB, ETH-USD, ICSH, VNQ\nAnnualized mean returns: XLB:-0.4002, ETH-USD:-1.0387, ICSH:0.0251, VNQ:-0.4320\nCovariance matrix (annualized):\n[[0.023841, 0.025403, 2.5e-05, 0.007619], [0.025403, 0.930784, -0.001197, 0.051617], [2.5e-05, -0.001197, 1.4e-05, -4.4e-05], [0.007619, 0.051617, -4.4e-05, 0.020424]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_ICSH=0.0000, w_VNQ=0.0000", "answer_numeric": -1.1180714885069762, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_ETH-USD=1.0000, w_ICSH=0.0000, w_VNQ=0.0000\nPortfolio annualized return: -103.87%, volatility: 96.48%\nSharpe ratio: (-1.0387 - 0.0400) / 0.9648 = -1.1181", "metadata": {"weights": {"XLB": 0.0, "ETH-USD": 1.0, "ICSH": 0.0, "VNQ": 0.0}, "sharpe_ratio": -1.1181, "portfolio_return": -1.038683, "portfolio_vol": 0.964771, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201001_0743", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "VNQI", "SGOV"], "decision_date": "2020-10-01", "context_summary": "4-asset optimization. Max-Sharpe: 0.956. Portfolio: return=16.60%, vol=13.18%. Weights: w_XLP=0.6713, w_ADA-USD=0.0000, w_VNQI=0.3287, w_SGOV=0.0000.", "question": "Assets: XLP, ADA-USD, VNQI, SGOV\nAnnualized mean returns: XLP:0.1681, ADA-USD:-1.3184, VNQI:0.1617, SGOV:0.0008\nCovariance matrix (annualized):\n[[0.019193, 0.038277, 0.014508, 1.4e-05], [0.038277, 0.793076, 0.041717, -0.000261], [0.014508, 0.041717, 0.021405, -2.1e-05], [1.4e-05, -0.000261, -2.1e-05, 1e-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=0.6713, w_ADA-USD=0.0000, w_VNQI=0.3287, w_SGOV=0.0000", "answer_numeric": 0.9563620364131258, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.6713, w_ADA-USD=0.0000, w_VNQI=0.3287, w_SGOV=0.0000\nPortfolio annualized return: 16.60%, volatility: 13.18%\nSharpe ratio: (0.1660 - 0.0400) / 0.1318 = 0.9564", "metadata": {"weights": {"XLP": 0.6713, "ADA-USD": 0.0, "VNQI": 0.3287, "SGOV": 0.0}, "sharpe_ratio": 0.9564, "portfolio_return": 0.166023, "portfolio_vol": 0.131774, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201130_0747", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "IYR", "DBB"], "decision_date": "2020-11-30", "context_summary": "4-asset optimization. Max-Sharpe: 6.039. Portfolio: return=90.17%, vol=14.27%. Weights: w_XLRE=0.0000, w_ETH-USD=0.1272, w_IYR=0.1741, w_DBB=0.6987.", "question": "Assets: XLRE, ETH-USD, IYR, DBB\nAnnualized mean returns: XLRE:0.2643, ETH-USD:2.1711, IYR:0.3972, DBB:0.7962\nCovariance matrix (annualized):\n[[0.034058, -0.005477, 0.036282, 0.00385], [-0.005477, 0.322598, -0.003032, 0.014078], [0.036282, -0.003032, 0.039638, 0.002756], [0.00385, 0.014078, 0.002756, 0.022323]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.1272, w_IYR=0.1741, w_DBB=0.6987", "answer_numeric": 6.039015782817291, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_ETH-USD=0.1272, w_IYR=0.1741, w_DBB=0.6987\nPortfolio annualized return: 90.17%, volatility: 14.27%\nSharpe ratio: (0.9017 - 0.0400) / 0.1427 = 6.0390", "metadata": {"weights": {"XLRE": 0.0, "ETH-USD": 0.1272, "IYR": 0.1741, "DBB": 0.6987}, "sharpe_ratio": 6.039, "portfolio_return": 0.901673, "portfolio_vol": 0.142684, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210924_0748", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ADA-USD", "VNQI", "ICSH"], "decision_date": "2021-09-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.379. Portfolio: return=364.65%, vol=106.73%. Weights: w_XLV=0.0000, w_ADA-USD=1.0000, w_VNQI=0.0000, w_ICSH=0.0000.", "question": "Assets: XLV, ADA-USD, VNQI, ICSH\nAnnualized mean returns: XLV:0.0668, ADA-USD:3.6465, VNQI:-0.0362, ICSH:0.0038\nCovariance matrix (annualized):\n[[0.010654, 0.012571, 0.000918, -2e-06], [0.012571, 1.139043, 0.051623, 0.000235], [0.000918, 0.051623, 0.015986, 1.3e-05], [-2e-06, 0.000235, 1.3e-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_XLV=0.0000, w_ADA-USD=1.0000, w_VNQI=0.0000, w_ICSH=0.0000", "answer_numeric": 3.379173689530958, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_ADA-USD=1.0000, w_VNQI=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 364.65%, volatility: 106.73%\nSharpe ratio: (3.6465 - 0.0400) / 1.0673 = 3.3792", "metadata": {"weights": {"XLV": 0.0, "ADA-USD": 1.0, "VNQI": 0.0, "ICSH": 0.0}, "sharpe_ratio": 3.3792, "portfolio_return": 3.646456, "portfolio_vol": 1.06726, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200203_0754", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ETH-USD", "HYG", "PPLT"], "decision_date": "2020-02-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.452. Portfolio: return=40.88%, vol=8.29%. Weights: w_MTUM=0.8636, w_ETH-USD=0.0333, w_HYG=0.0000, w_PPLT=0.1031.", "question": "Assets: MTUM, ETH-USD, HYG, PPLT\nAnnualized mean returns: MTUM:0.3875, ETH-USD:0.8068, HYG:0.0869, PPLT:0.4593\nCovariance matrix (annualized):\n[[0.007201, 0.000476, 0.001697, 0.002256], [0.000476, 0.40804, -0.001596, 0.002679], [0.001697, -0.001596, 0.001599, 0.004126], [0.002256, 0.002679, 0.004126, 0.055922]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8636, w_ETH-USD=0.0333, w_HYG=0.0000, w_PPLT=0.1031", "answer_numeric": 4.451666354311336, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.8636, w_ETH-USD=0.0333, w_HYG=0.0000, w_PPLT=0.1031\nPortfolio annualized return: 40.88%, volatility: 8.29%\nSharpe ratio: (0.4088 - 0.0400) / 0.0829 = 4.4517", "metadata": {"weights": {"MTUM": 0.8636, "ETH-USD": 0.0333, "HYG": 0.0, "PPLT": 0.1031}, "sharpe_ratio": 4.4517, "portfolio_return": 0.408831, "portfolio_vol": 0.082852, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220531_0759", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BNB-USD", "SLV", "ICSH"], "decision_date": "2022-05-31", "context_summary": "4-asset optimization. Max-Sharpe: 0.927. Portfolio: return=141.07%, vol=147.86%. Weights: w_^VIX=1.0000, w_BNB-USD=0.0000, w_SLV=0.0000, w_ICSH=0.0000.", "question": "Assets: ^VIX, BNB-USD, SLV, ICSH\nAnnualized mean returns: ^VIX:1.4107, BNB-USD:-1.9999, SLV:-0.7037, ICSH:0.0089\nCovariance matrix (annualized):\n[[2.186389, -0.597379, -0.148526, -0.001155], [-0.597379, 0.656945, 0.038695, -0.000215], [-0.148526, 0.038695, 0.06211, 0.000317], [-0.001155, -0.000215, 0.000317, 2.8e-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_^VIX=1.0000, w_BNB-USD=0.0000, w_SLV=0.0000, w_ICSH=0.0000", "answer_numeric": 0.9270012351091153, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=1.0000, w_BNB-USD=0.0000, w_SLV=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 141.07%, volatility: 147.86%\nSharpe ratio: (1.4107 - 0.0400) / 1.4786 = 0.9270", "metadata": {"weights": {"^VIX": 1.0, "BNB-USD": 0.0, "SLV": 0.0, "ICSH": 0.0}, "sharpe_ratio": 0.927, "portfolio_return": 1.410705, "portfolio_vol": 1.478644, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200603_0766", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LINK-USD", "XHB", "STIP"], "decision_date": "2020-06-03", "context_summary": "4-asset optimization. Max-Sharpe: 6.533. Portfolio: return=262.66%, vol=39.59%. Weights: w_XLF=0.0000, w_LINK-USD=0.3602, w_XHB=0.4884, w_STIP=0.1514.", "question": "Assets: XLF, LINK-USD, XHB, STIP\nAnnualized mean returns: XLF:0.6091, LINK-USD:4.1291, XHB:2.3124, STIP:0.0651\nCovariance matrix (annualized):\n[[0.152136, 0.1122, 0.158861, 0.002626], [0.1122, 0.541371, 0.107998, 0.000359], [0.158861, 0.107998, 0.201479, 0.002692], [0.002626, 0.000359, 0.002692, 0.000526]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=0.3602, w_XHB=0.4884, w_STIP=0.1514", "answer_numeric": 6.53313583771695, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_LINK-USD=0.3602, w_XHB=0.4884, w_STIP=0.1514\nPortfolio annualized return: 262.66%, volatility: 39.59%\nSharpe ratio: (2.6266 - 0.0400) / 0.3959 = 6.5331", "metadata": {"weights": {"XLF": 0.0, "LINK-USD": 0.3602, "XHB": 0.4884, "STIP": 0.1514}, "sharpe_ratio": 6.5331, "portfolio_return": 2.626556, "portfolio_vol": 0.395913, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220606_0770", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "MATIC-USD", "SCHP", "MORT"], "decision_date": "2022-06-06", "context_summary": "4-asset optimization. Max-Sharpe: -0.238. Portfolio: return=-2.30%, vol=26.54%. Weights: w_XLB=1.0000, w_MATIC-USD=0.0000, w_SCHP=0.0000, w_MORT=0.0000.", "question": "Assets: XLB, MATIC-USD, SCHP, MORT\nAnnualized mean returns: XLB:-0.0230, MATIC-USD:-5.5276, SCHP:-0.0217, MORT:-0.1959\nCovariance matrix (annualized):\n[[0.070424, 0.136374, 0.006394, 0.050013], [0.136374, 1.189562, -0.003155, 0.121211], [0.006394, -0.003155, 0.006252, 0.007313], [0.050013, 0.121211, 0.007313, 0.06841]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_MATIC-USD=0.0000, w_SCHP=0.0000, w_MORT=0.0000", "answer_numeric": -0.2375570734715706, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=1.0000, w_MATIC-USD=0.0000, w_SCHP=0.0000, w_MORT=0.0000\nPortfolio annualized return: -2.30%, volatility: 26.54%\nSharpe ratio: (-0.0230 - 0.0400) / 0.2654 = -0.2376", "metadata": {"weights": {"XLB": 1.0, "MATIC-USD": 0.0, "SCHP": 0.0, "MORT": 0.0}, "sharpe_ratio": -0.2376, "portfolio_return": -0.023042, "portfolio_vol": 0.265375, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191211_0772", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "XRP-USD", "WEAT", "VNQ"], "decision_date": "2019-12-11", "context_summary": "4-asset optimization. Max-Sharpe: 0.381. Portfolio: return=10.34%, vol=16.65%. Weights: w_XLU=0.0000, w_XRP-USD=0.0000, w_WEAT=1.0000, w_VNQ=0.0000.", "question": "Assets: XLU, XRP-USD, WEAT, VNQ\nAnnualized mean returns: XLU:-0.0911, XRP-USD:-1.0646, WEAT:0.1034, VNQ:-0.0288\nCovariance matrix (annualized):\n[[0.009631, -0.003232, -0.000657, 0.006619], [-0.003232, 0.23571, 0.010835, 0.004342], [-0.000657, 0.010835, 0.027737, -0.001421], [0.006619, 0.004342, -0.001421, 0.011497]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_WEAT=1.0000, w_VNQ=0.0000", "answer_numeric": 0.3805337681561799, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_XRP-USD=0.0000, w_WEAT=1.0000, w_VNQ=0.0000\nPortfolio annualized return: 10.34%, volatility: 16.65%\nSharpe ratio: (0.1034 - 0.0400) / 0.1665 = 0.3805", "metadata": {"weights": {"XLU": 0.0, "XRP-USD": 0.0, "WEAT": 1.0, "VNQ": 0.0}, "sharpe_ratio": 0.3805, "portfolio_return": 0.103376, "portfolio_vol": 0.166545, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211027_0779", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BNB-USD", "UNG", "VNQI"], "decision_date": "2021-10-27", "context_summary": "4-asset optimization. Max-Sharpe: 2.224. Portfolio: return=151.36%, vol=66.26%. Weights: w_XLU=0.0000, w_BNB-USD=0.0323, w_UNG=0.9677, w_VNQI=0.0000.", "question": "Assets: XLU, BNB-USD, UNG, VNQI\nAnnualized mean returns: XLU:-0.0622, BNB-USD:0.3223, UNG:1.5533, VNQI:-0.1269\nCovariance matrix (annualized):\n[[0.022373, 0.039182, 0.012794, 0.003266], [0.039182, 0.70979, 0.063234, 0.044922], [0.012794, 0.063234, 0.463805, 0.022259], [0.003266, 0.044922, 0.022259, 0.015972]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0323, w_UNG=0.9677, w_VNQI=0.0000", "answer_numeric": 2.2238846483967065, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_BNB-USD=0.0323, w_UNG=0.9677, w_VNQI=0.0000\nPortfolio annualized return: 151.36%, volatility: 66.26%\nSharpe ratio: (1.5136 - 0.0400) / 0.6626 = 2.2239", "metadata": {"weights": {"XLU": 0.0, "BNB-USD": 0.0323, "UNG": 0.9677, "VNQI": 0.0}, "sharpe_ratio": 2.2239, "portfolio_return": 1.513552, "portfolio_vol": 0.662603, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210112_0785", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "SOL-USD", "DBB", "ITB"], "decision_date": "2021-01-12", "context_summary": "4-asset optimization. Max-Sharpe: 4.835. Portfolio: return=74.74%, vol=14.63%. Weights: w_XLB=0.6619, w_SOL-USD=0.0451, w_DBB=0.2930, w_ITB=0.0000.", "question": "Assets: XLB, SOL-USD, DBB, ITB\nAnnualized mean returns: XLB:0.7615, SOL-USD:2.2242, DBB:0.4887, ITB:0.2488\nCovariance matrix (annualized):\n[[0.03261, -0.053316, 0.009051, 0.009973], [-0.053316, 2.437223, -0.028675, -0.009596], [0.009051, -0.028675, 0.030303, 0.002758], [0.009973, -0.009596, 0.002758, 0.067486]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6619, w_SOL-USD=0.0451, w_DBB=0.2930, w_ITB=0.0000", "answer_numeric": 4.834681013941444, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.6619, w_SOL-USD=0.0451, w_DBB=0.2930, w_ITB=0.0000\nPortfolio annualized return: 74.74%, volatility: 14.63%\nSharpe ratio: (0.7474 - 0.0400) / 0.1463 = 4.8347", "metadata": {"weights": {"XLB": 0.6619, "SOL-USD": 0.0451, "DBB": 0.293, "ITB": 0.0}, "sharpe_ratio": 4.8347, "portfolio_return": 0.747418, "portfolio_vol": 0.146322, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190705_0787", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BNB-USD", "HAUZ", "BIL"], "decision_date": "2019-07-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.281. Portfolio: return=47.04%, vol=13.12%. Weights: w_IWM=0.0000, w_BNB-USD=0.1310, w_HAUZ=0.8690, w_BIL=0.0000.", "question": "Assets: IWM, BNB-USD, HAUZ, BIL\nAnnualized mean returns: IWM:-0.1406, BNB-USD:2.1530, HAUZ:0.2167, BIL:0.0243\nCovariance matrix (annualized):\n[[0.031189, -0.006348, 0.010189, 3.8e-05], [-0.006348, 0.649662, -0.000734, -0.000294], [0.010189, -0.000734, 0.008242, 2.3e-05], [3.8e-05, -0.000294, 2.3e-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_IWM=0.0000, w_BNB-USD=0.1310, w_HAUZ=0.8690, w_BIL=0.0000", "answer_numeric": 3.281217913383045, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_BNB-USD=0.1310, w_HAUZ=0.8690, w_BIL=0.0000\nPortfolio annualized return: 47.04%, volatility: 13.12%\nSharpe ratio: (0.4704 - 0.0400) / 0.1312 = 3.2812", "metadata": {"weights": {"IWM": 0.0, "BNB-USD": 0.131, "HAUZ": 0.869, "BIL": 0.0}, "sharpe_ratio": 3.2812, "portfolio_return": 0.470404, "portfolio_vol": 0.131172, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180214_0790", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "REZ", "LQD"], "decision_date": "2018-02-14", "context_summary": "4-asset optimization. Max-Sharpe: 1.124. Portfolio: return=32.98%, vol=25.79%. Weights: w_FXI=1.0000, w_ADA-USD=0.0000, w_REZ=0.0000, w_LQD=0.0000.", "question": "Assets: FXI, ADA-USD, REZ, LQD\nAnnualized mean returns: FXI:0.3298, ADA-USD:-2.9842, REZ:-0.8640, LQD:-0.2173\nCovariance matrix (annualized):\n[[0.06653, 0.140831, 0.018987, 0.001664], [0.140831, 2.650544, 0.044397, 0.003871], [0.018987, 0.044397, 0.038782, 0.003055], [0.001664, 0.003871, 0.003055, 0.002079]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=0.0000, w_REZ=0.0000, w_LQD=0.0000", "answer_numeric": 1.1235461412099328, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=1.0000, w_ADA-USD=0.0000, w_REZ=0.0000, w_LQD=0.0000\nPortfolio annualized return: 32.98%, volatility: 25.79%\nSharpe ratio: (0.3298 - 0.0400) / 0.2579 = 1.1235", "metadata": {"weights": {"FXI": 1.0, "ADA-USD": 0.0, "REZ": 0.0, "LQD": 0.0}, "sharpe_ratio": 1.1235, "portfolio_return": 0.3298, "portfolio_vol": 0.257933, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191028_0792", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "ICSH", "DBC"], "decision_date": "2019-10-28", "context_summary": "4-asset optimization. Max-Sharpe: 3.718. Portfolio: return=42.77%, vol=10.43%. Weights: w_VEA=0.9882, w_ETH-USD=0.0118, w_ICSH=0.0000, w_DBC=0.0000.", "question": "Assets: VEA, ETH-USD, ICSH, DBC\nAnnualized mean returns: VEA:0.4333, ETH-USD:-0.0436, ICSH:0.0259, DBC:0.1384\nCovariance matrix (annualized):\n[[0.011259, -0.007932, -0.000116, 0.003638], [-0.007932, 0.466974, 0.000355, -0.001453], [-0.000116, 0.000355, 1.5e-05, -3.9e-05], [0.003638, -0.001453, -3.9e-05, 0.019212]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.9882, w_ETH-USD=0.0118, w_ICSH=0.0000, w_DBC=0.0000", "answer_numeric": 3.717768586795642, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.9882, w_ETH-USD=0.0118, w_ICSH=0.0000, w_DBC=0.0000\nPortfolio annualized return: 42.77%, volatility: 10.43%\nSharpe ratio: (0.4277 - 0.0400) / 0.1043 = 3.7178", "metadata": {"weights": {"VEA": 0.9882, "ETH-USD": 0.0118, "ICSH": 0.0, "DBC": 0.0}, "sharpe_ratio": 3.7178, "portfolio_return": 0.427715, "portfolio_vol": 0.104287, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190204_0794", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "BIL", "DBC"], "decision_date": "2019-02-04", "context_summary": "4-asset optimization. Max-Sharpe: 0.689. Portfolio: return=20.28%, vol=23.64%. Weights: w_XLK=0.0000, w_BNB-USD=0.1980, w_BIL=0.0000, w_DBC=0.8020.", "question": "Assets: XLK, BNB-USD, BIL, DBC\nAnnualized mean returns: XLK:-0.1046, BNB-USD:0.6165, BIL:0.0232, DBC:0.1006\nCovariance matrix (annualized):\n[[0.083463, 0.04406, -0.000101, 0.018343], [0.04406, 1.014901, -0.000705, -0.003798], [-0.000101, -0.000705, 4e-06, -7.7e-05], [0.018343, -0.003798, -7.7e-05, 0.026882]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1980, w_BIL=0.0000, w_DBC=0.8020", "answer_numeric": 0.6886088994413998, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_BNB-USD=0.1980, w_BIL=0.0000, w_DBC=0.8020\nPortfolio annualized return: 20.28%, volatility: 23.64%\nSharpe ratio: (0.2028 - 0.0400) / 0.2364 = 0.6886", "metadata": {"weights": {"XLK": 0.0, "BNB-USD": 0.198, "BIL": 0.0, "DBC": 0.802}, "sharpe_ratio": 0.6886, "portfolio_return": 0.202757, "portfolio_vol": 0.236356, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210416_0797", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "EMB", "VNQI"], "decision_date": "2021-04-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.749. Portfolio: return=36.30%, vol=11.75%. Weights: w_FXI=0.0000, w_ETH-USD=0.0573, w_EMB=0.0000, w_VNQI=0.9427.", "question": "Assets: FXI, ETH-USD, EMB, VNQI\nAnnualized mean returns: FXI:-0.8310, ETH-USD:1.1620, EMB:-0.0315, VNQI:0.3145\nCovariance matrix (annualized):\n[[0.078836, 0.095537, 0.016302, 0.014777], [0.095537, 0.596494, 0.018706, 0.014616], [0.016302, 0.018706, 0.01246, 0.005161], [0.014777, 0.014616, 0.005161, 0.01156]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0573, w_EMB=0.0000, w_VNQI=0.9427", "answer_numeric": 2.7486506764506764, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_ETH-USD=0.0573, w_EMB=0.0000, w_VNQI=0.9427\nPortfolio annualized return: 36.30%, volatility: 11.75%\nSharpe ratio: (0.3630 - 0.0400) / 0.1175 = 2.7487", "metadata": {"weights": {"FXI": 0.0, "ETH-USD": 0.0573, "EMB": 0.0, "VNQI": 0.9427}, "sharpe_ratio": 2.7487, "portfolio_return": 0.363044, "portfolio_vol": 0.117528, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20191216_0799", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "MATIC-USD", "TLH", "ICSH"], "decision_date": "2019-12-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.677. Portfolio: return=59.93%, vol=20.89%. Weights: w_XLE=0.6063, w_MATIC-USD=0.1203, w_TLH=0.2734, w_ICSH=0.0000.", "question": "Assets: XLE, MATIC-USD, TLH, ICSH\nAnnualized mean returns: XLE:0.3157, MATIC-USD:3.4388, TLH:-0.0216, ICSH:0.0248\nCovariance matrix (annualized):\n[[0.03529, 0.02613, -0.011068, -0.000123], [0.02613, 2.084108, -0.005222, -0.00173], [-0.011068, -0.005222, 0.009253, 8.4e-05], [-0.000123, -0.00173, 8.4e-05, 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=0.6063, w_MATIC-USD=0.1203, w_TLH=0.2734, w_ICSH=0.0000", "answer_numeric": 2.677396724527243, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.6063, w_MATIC-USD=0.1203, w_TLH=0.2734, w_ICSH=0.0000\nPortfolio annualized return: 59.93%, volatility: 20.89%\nSharpe ratio: (0.5993 - 0.0400) / 0.2089 = 2.6774", "metadata": {"weights": {"XLE": 0.6063, "MATIC-USD": 0.1203, "TLH": 0.2734, "ICSH": 0.0}, "sharpe_ratio": 2.6774, "portfolio_return": 0.599314, "portfolio_vol": 0.208902, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210726_0801", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "DOT-USD", "VCIT", "SGOV"], "decision_date": "2021-07-26", "context_summary": "4-asset optimization. Max-Sharpe: 3.053. Portfolio: return=13.50%, vol=3.11%. Weights: w_MTUM=0.1492, w_DOT-USD=0.0000, w_VCIT=0.8508, w_SGOV=0.0000.", "question": "Assets: MTUM, DOT-USD, VCIT, SGOV\nAnnualized mean returns: MTUM:0.2030, DOT-USD:-3.7062, VCIT:0.1231, SGOV:0.0006\nCovariance matrix (annualized):\n[[0.021697, -0.00243, -0.001851, 1.3e-05], [-0.00243, 1.333543, 0.002291, -0.000237], [-0.001851, 0.002291, 0.00132, -4e-06], [1.3e-05, -0.000237, -4e-06, 1e-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=0.1492, w_DOT-USD=0.0000, w_VCIT=0.8508, w_SGOV=0.0000", "answer_numeric": 3.0526508062983204, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.1492, w_DOT-USD=0.0000, w_VCIT=0.8508, w_SGOV=0.0000\nPortfolio annualized return: 13.50%, volatility: 3.11%\nSharpe ratio: (0.1350 - 0.0400) / 0.0311 = 3.0527", "metadata": {"weights": {"MTUM": 0.1492, "DOT-USD": 0.0, "VCIT": 0.8508, "SGOV": 0.0}, "sharpe_ratio": 3.0527, "portfolio_return": 0.134986, "portfolio_vol": 0.031116, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220524_0803", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "VNQ", "BIL"], "decision_date": "2022-05-24", "context_summary": "4-asset optimization. Max-Sharpe: -1.639. Portfolio: return=-37.65%, vol=25.41%. Weights: w_VEA=0.0000, w_BTC-USD=0.0000, w_VNQ=1.0000, w_BIL=0.0000.", "question": "Assets: VEA, BTC-USD, VNQ, BIL\nAnnualized mean returns: VEA:-0.3857, BTC-USD:-2.8933, VNQ:-0.3765, BIL:0.0020\nCovariance matrix (annualized):\n[[0.045186, 0.080823, 0.041756, 0.000123], [0.080823, 0.329571, 0.068732, 0.000386], [0.041756, 0.068732, 0.064591, 0.00012], [0.000123, 0.000386, 0.00012, 3e-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_BTC-USD=0.0000, w_VNQ=1.0000, w_BIL=0.0000", "answer_numeric": -1.638916253366982, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_BTC-USD=0.0000, w_VNQ=1.0000, w_BIL=0.0000\nPortfolio annualized return: -37.65%, volatility: 25.41%\nSharpe ratio: (-0.3765 - 0.0400) / 0.2541 = -1.6389", "metadata": {"weights": {"VEA": 0.0, "BTC-USD": 0.0, "VNQ": 1.0, "BIL": 0.0}, "sharpe_ratio": -1.6389, "portfolio_return": -0.376526, "portfolio_vol": 0.254147, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180706_0807", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNB-USD", "REZ", "SHV"], "decision_date": "2018-07-06", "context_summary": "4-asset optimization. Max-Sharpe: 4.614. Portfolio: return=64.20%, vol=13.05%. Weights: w_FXI=0.0000, w_BNB-USD=0.0755, w_REZ=0.9245, w_SHV=0.0000.", "question": "Assets: FXI, BNB-USD, REZ, SHV\nAnnualized mean returns: FXI:-0.5440, BNB-USD:1.9595, REZ:0.5345, SHV:0.0184\nCovariance matrix (annualized):\n[[0.037642, 0.007047, 0.006021, -0.000177], [0.007047, 0.895193, -0.014369, -2.6e-05], [0.006021, -0.014369, 0.016293, 8e-06], [-0.000177, -2.6e-05, 8e-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_FXI=0.0000, w_BNB-USD=0.0755, w_REZ=0.9245, w_SHV=0.0000", "answer_numeric": 4.614422833896804, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_BNB-USD=0.0755, w_REZ=0.9245, w_SHV=0.0000\nPortfolio annualized return: 64.20%, volatility: 13.05%\nSharpe ratio: (0.6420 - 0.0400) / 0.1305 = 4.6144", "metadata": {"weights": {"FXI": 0.0, "BNB-USD": 0.0755, "REZ": 0.9245, "SHV": 0.0}, "sharpe_ratio": 4.6144, "portfolio_return": 0.641996, "portfolio_vol": 0.13046, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221209_0809", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "DOT-USD", "BIL", "VNQI"], "decision_date": "2022-12-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.193. Portfolio: return=42.75%, vol=17.67%. Weights: w_EWJ=0.6970, w_DOT-USD=0.0000, w_BIL=0.0000, w_VNQI=0.3030.", "question": "Assets: EWJ, DOT-USD, BIL, VNQI\nAnnualized mean returns: EWJ:0.4261, DOT-USD:-0.5321, BIL:0.0345, VNQI:0.4306\nCovariance matrix (annualized):\n[[0.033025, 0.05584, -5.7e-05, 0.0267], [0.05584, 0.495696, -0.000313, 0.056779], [-5.7e-05, -0.000313, 8e-06, 5.3e-05], [0.0267, 0.056779, 5.3e-05, 0.042431]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6970, w_DOT-USD=0.0000, w_BIL=0.0000, w_VNQI=0.3030", "answer_numeric": 2.1930412532409815, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.6970, w_DOT-USD=0.0000, w_BIL=0.0000, w_VNQI=0.3030\nPortfolio annualized return: 42.75%, volatility: 17.67%\nSharpe ratio: (0.4275 - 0.0400) / 0.1767 = 2.1930", "metadata": {"weights": {"EWJ": 0.697, "DOT-USD": 0.0, "BIL": 0.0, "VNQI": 0.303}, "sharpe_ratio": 2.193, "portfolio_return": 0.427473, "portfolio_vol": 0.176683, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210813_0812", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "XHB", "SGOV"], "decision_date": "2021-08-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.888. Portfolio: return=43.02%, vol=20.67%. Weights: w_IWM=0.0000, w_MATIC-USD=0.0000, w_XHB=1.0000, w_SGOV=0.0000.", "question": "Assets: IWM, MATIC-USD, XHB, SGOV\nAnnualized mean returns: IWM:-0.2201, MATIC-USD:0.1035, XHB:0.4302, SGOV:-0.0004\nCovariance matrix (annualized):\n[[0.036007, 0.025534, 0.025766, 1.8e-05], [0.025534, 1.756695, 0.049887, 2.8e-05], [0.025766, 0.049887, 0.042707, 1.6e-05], [1.8e-05, 2.8e-05, 1.6e-05, 1e-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_MATIC-USD=0.0000, w_XHB=1.0000, w_SGOV=0.0000", "answer_numeric": 1.8879380535672514, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_MATIC-USD=0.0000, w_XHB=1.0000, w_SGOV=0.0000\nPortfolio annualized return: 43.02%, volatility: 20.67%\nSharpe ratio: (0.4302 - 0.0400) / 0.2067 = 1.8879", "metadata": {"weights": {"IWM": 0.0, "MATIC-USD": 0.0, "XHB": 1.0, "SGOV": 0.0}, "sharpe_ratio": 1.8879, "portfolio_return": 0.430153, "portfolio_vol": 0.206656, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220715_0814", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "DOT-USD", "SCHP", "SOYB"], "decision_date": "2022-07-15", "context_summary": "4-asset optimization. Max-Sharpe: -0.521. Portfolio: return=-5.98%, vol=19.16%. Weights: w_USMV=1.0000, w_DOT-USD=0.0000, w_SCHP=0.0000, w_SOYB=0.0000.", "question": "Assets: USMV, DOT-USD, SCHP, SOYB\nAnnualized mean returns: USMV:-0.0598, DOT-USD:-3.5975, SCHP:-0.1250, SOYB:-0.1996\nCovariance matrix (annualized):\n[[0.03672, 0.078958, 0.003636, 0.002679], [0.078958, 0.867643, 0.002498, 0.022068], [0.003636, 0.002498, 0.006155, -0.00163], [0.002679, 0.022068, -0.00163, 0.051056]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_DOT-USD=0.0000, w_SCHP=0.0000, w_SOYB=0.0000", "answer_numeric": -0.5206727343655648, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=1.0000, w_DOT-USD=0.0000, w_SCHP=0.0000, w_SOYB=0.0000\nPortfolio annualized return: -5.98%, volatility: 19.16%\nSharpe ratio: (-0.0598 - 0.0400) / 0.1916 = -0.5207", "metadata": {"weights": {"USMV": 1.0, "DOT-USD": 0.0, "SCHP": 0.0, "SOYB": 0.0}, "sharpe_ratio": -0.5207, "portfolio_return": -0.059774, "portfolio_vol": 0.191625, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190524_0816", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "LINK-USD", "VNQI", "LQD"], "decision_date": "2019-05-24", "context_summary": "4-asset optimization. Max-Sharpe: 5.616. Portfolio: return=108.27%, vol=18.56%. Weights: w_ACWI=0.0000, w_LINK-USD=0.1819, w_VNQI=0.0000, w_LQD=0.8181.", "question": "Assets: ACWI, LINK-USD, VNQI, LQD\nAnnualized mean returns: ACWI:-0.0197, LINK-USD:5.5858, VNQI:-0.0782, LQD:0.0814\nCovariance matrix (annualized):\n[[0.013239, 0.020757, 0.007616, -1e-06], [0.020757, 0.998698, 0.028359, 0.002019], [0.007616, 0.028359, 0.007061, 0.000252], [-1e-06, 0.002019, 0.000252, 0.001223]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=0.1819, w_VNQI=0.0000, w_LQD=0.8181", "answer_numeric": 5.616265883801542, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_LINK-USD=0.1819, w_VNQI=0.0000, w_LQD=0.8181\nPortfolio annualized return: 108.27%, volatility: 18.56%\nSharpe ratio: (1.0827 - 0.0400) / 0.1856 = 5.6163", "metadata": {"weights": {"ACWI": 0.0, "LINK-USD": 0.1819, "VNQI": 0.0, "LQD": 0.8181}, "sharpe_ratio": 5.6163, "portfolio_return": 1.082653, "portfolio_vol": 0.185649, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190717_0820", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BNB-USD", "HAUZ", "CORN"], "decision_date": "2019-07-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.344. Portfolio: return=33.53%, vol=8.83%. Weights: w_ACWI=0.4294, w_BNB-USD=0.0231, w_HAUZ=0.3694, w_CORN=0.1781.", "question": "Assets: ACWI, BNB-USD, HAUZ, CORN\nAnnualized mean returns: ACWI:0.3058, BNB-USD:0.7326, HAUZ:0.2568, CORN:0.5177\nCovariance matrix (annualized):\n[[0.010199, 0.008973, 0.005779, 0.001678], [0.008973, 0.473328, 0.005871, 0.007569], [0.005779, 0.005871, 0.006173, 0.004646], [0.001678, 0.007569, 0.004646, 0.056171]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4294, w_BNB-USD=0.0231, w_HAUZ=0.3694, w_CORN=0.1781", "answer_numeric": 3.343633866152773, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.4294, w_BNB-USD=0.0231, w_HAUZ=0.3694, w_CORN=0.1781\nPortfolio annualized return: 33.53%, volatility: 8.83%\nSharpe ratio: (0.3353 - 0.0400) / 0.0883 = 3.3436", "metadata": {"weights": {"ACWI": 0.4294, "BNB-USD": 0.0231, "HAUZ": 0.3694, "CORN": 0.1781}, "sharpe_ratio": 3.3436, "portfolio_return": 0.335274, "portfolio_vol": 0.088309, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220912_0822", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "HYG", "DBB"], "decision_date": "2022-09-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.449. Portfolio: return=36.46%, vol=13.25%. Weights: w_USMV=0.5028, w_XRP-USD=0.0323, w_HYG=0.0000, w_DBB=0.4649.", "question": "Assets: USMV, XRP-USD, HYG, DBB\nAnnualized mean returns: USMV:0.2857, XRP-USD:0.5572, HYG:0.1630, DBB:0.4366\nCovariance matrix (annualized):\n[[0.023064, 0.029047, 0.015756, 0.001638], [0.029047, 0.244344, 0.024503, 0.011814], [0.015756, 0.024503, 0.014872, 0.00183], [0.001638, 0.011814, 0.00183, 0.043576]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5028, w_XRP-USD=0.0323, w_HYG=0.0000, w_DBB=0.4649", "answer_numeric": 2.449355021603808, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.5028, w_XRP-USD=0.0323, w_HYG=0.0000, w_DBB=0.4649\nPortfolio annualized return: 36.46%, volatility: 13.25%\nSharpe ratio: (0.3646 - 0.0400) / 0.1325 = 2.4494", "metadata": {"weights": {"USMV": 0.5028, "XRP-USD": 0.0323, "HYG": 0.0, "DBB": 0.4649}, "sharpe_ratio": 2.4494, "portfolio_return": 0.36464, "portfolio_vol": 0.132541, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180913_0824", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "ITB", "SHV"], "decision_date": "2018-09-13", "context_summary": "4-asset optimization. Max-Sharpe: 3.230. Portfolio: return=49.26%, vol=14.01%. Weights: w_XLI=0.9281, w_LINK-USD=0.0719, w_ITB=0.0000, w_SHV=0.0000.", "question": "Assets: XLI, LINK-USD, ITB, SHV\nAnnualized mean returns: XLI:0.3523, LINK-USD:2.3049, ITB:-0.1148, SHV:0.0184\nCovariance matrix (annualized):\n[[0.013435, 0.014971, 0.010193, 1.4e-05], [0.014971, 1.173784, 0.043734, 0.000266], [0.010193, 0.043734, 0.041851, 5.9e-05], [1.4e-05, 0.000266, 5.9e-05, 1e-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=0.9281, w_LINK-USD=0.0719, w_ITB=0.0000, w_SHV=0.0000", "answer_numeric": 3.230314613292898, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.9281, w_LINK-USD=0.0719, w_ITB=0.0000, w_SHV=0.0000\nPortfolio annualized return: 49.26%, volatility: 14.01%\nSharpe ratio: (0.4926 - 0.0400) / 0.1401 = 3.2303", "metadata": {"weights": {"XLI": 0.9281, "LINK-USD": 0.0719, "ITB": 0.0, "SHV": 0.0}, "sharpe_ratio": 3.2303, "portfolio_return": 0.49261, "portfolio_vol": 0.140113, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181010_0826", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ADA-USD", "LQD", "BIL"], "decision_date": "2018-10-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.474. Portfolio: return=7.16%, vol=6.66%. Weights: w_VTI=1.0000, w_ADA-USD=0.0000, w_LQD=0.0000, w_BIL=0.0000.", "question": "Assets: VTI, ADA-USD, LQD, BIL\nAnnualized mean returns: VTI:0.0716, ADA-USD:-0.7236, LQD:-0.0813, BIL:0.0171\nCovariance matrix (annualized):\n[[0.00444, 0.024873, 0.000332, -5.3e-05], [0.024873, 0.968858, -0.000442, 0.00033], [0.000332, -0.000442, 0.001395, -3e-06], [-5.3e-05, 0.00033, -3e-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_VTI=1.0000, w_ADA-USD=0.0000, w_LQD=0.0000, w_BIL=0.0000", "answer_numeric": 0.4737624625925252, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=1.0000, w_ADA-USD=0.0000, w_LQD=0.0000, w_BIL=0.0000\nPortfolio annualized return: 7.16%, volatility: 6.66%\nSharpe ratio: (0.0716 - 0.0400) / 0.0666 = 0.4738", "metadata": {"weights": {"VTI": 1.0, "ADA-USD": 0.0, "LQD": 0.0, "BIL": 0.0}, "sharpe_ratio": 0.4738, "portfolio_return": 0.071567, "portfolio_vol": 0.06663, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211012_0829", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "INDS", "LQD"], "decision_date": "2021-10-12", "context_summary": "4-asset optimization. Max-Sharpe: -0.767. Portfolio: return=-86.23%, vol=117.65%. Weights: w_XLI=0.0000, w_LINK-USD=1.0000, w_INDS=0.0000, w_LQD=0.0000.", "question": "Assets: XLI, LINK-USD, INDS, LQD\nAnnualized mean returns: XLI:-0.2907, LINK-USD:-0.8623, INDS:-0.0585, LQD:-0.0971\nCovariance matrix (annualized):\n[[0.018475, 0.048406, 0.007068, 0.001208], [0.048406, 1.384123, 0.072922, 0.025035], [0.007068, 0.072922, 0.019734, 0.002136], [0.001208, 0.025035, 0.002136, 0.003359]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=1.0000, w_INDS=0.0000, w_LQD=0.0000", "answer_numeric": -0.7669801881899049, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_LINK-USD=1.0000, w_INDS=0.0000, w_LQD=0.0000\nPortfolio annualized return: -86.23%, volatility: 117.65%\nSharpe ratio: (-0.8623 - 0.0400) / 1.1765 = -0.7670", "metadata": {"weights": {"XLI": 0.0, "LINK-USD": 1.0, "INDS": 0.0, "LQD": 0.0}, "sharpe_ratio": -0.767, "portfolio_return": -0.862343, "portfolio_vol": 1.176487, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210118_0831", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "DOT-USD", "IYR", "BIL"], "decision_date": "2021-01-18", "context_summary": "4-asset optimization. Max-Sharpe: 3.935. Portfolio: return=653.43%, vol=165.02%. Weights: w_XLU=0.0000, w_DOT-USD=1.0000, w_IYR=0.0000, w_BIL=0.0000.", "question": "Assets: XLU, DOT-USD, IYR, BIL\nAnnualized mean returns: XLU:-0.0655, DOT-USD:6.5343, IYR:0.0164, BIL:-0.0005\nCovariance matrix (annualized):\n[[0.027411, 0.099714, 0.015505, 3e-06], [0.099714, 2.723183, 0.074875, 0.000593], [0.015505, 0.074875, 0.025411, 1.9e-05], [3e-06, 0.000593, 1.9e-05, 2e-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_DOT-USD=1.0000, w_IYR=0.0000, w_BIL=0.0000", "answer_numeric": 3.935464177096063, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_DOT-USD=1.0000, w_IYR=0.0000, w_BIL=0.0000\nPortfolio annualized return: 653.43%, volatility: 165.02%\nSharpe ratio: (6.5343 - 0.0400) / 1.6502 = 3.9355", "metadata": {"weights": {"XLU": 0.0, "DOT-USD": 1.0, "IYR": 0.0, "BIL": 0.0}, "sharpe_ratio": 3.9355, "portfolio_return": 6.534331, "portfolio_vol": 1.650207, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210223_0833", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "REZ", "IEF"], "decision_date": "2021-02-23", "context_summary": "4-asset optimization. Max-Sharpe: 5.317. Portfolio: return=167.10%, vol=30.68%. Weights: w_XLF=0.3818, w_BTC-USD=0.2718, w_REZ=0.3464, w_IEF=0.0000.", "question": "Assets: XLF, BTC-USD, REZ, IEF\nAnnualized mean returns: XLF:0.7633, BTC-USD:4.4262, REZ:0.5098, IEF:-0.1887\nCovariance matrix (annualized):\n[[0.041218, 0.079067, 0.013012, -0.00398], [0.079067, 0.769032, 0.040062, -0.007407], [0.013012, 0.040062, 0.032467, 0.000867], [-0.00398, -0.007407, 0.000867, 0.001428]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3818, w_BTC-USD=0.2718, w_REZ=0.3464, w_IEF=0.0000", "answer_numeric": 5.316772547931367, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.3818, w_BTC-USD=0.2718, w_REZ=0.3464, w_IEF=0.0000\nPortfolio annualized return: 167.10%, volatility: 30.68%\nSharpe ratio: (1.6710 - 0.0400) / 0.3068 = 5.3168", "metadata": {"weights": {"XLF": 0.3818, "BTC-USD": 0.2718, "REZ": 0.3464, "IEF": 0.0}, "sharpe_ratio": 5.3168, "portfolio_return": 1.670986, "portfolio_vol": 0.306762, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201026_0837", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "SHV", "PALL"], "decision_date": "2020-10-26", "context_summary": "4-asset optimization. Max-Sharpe: 1.967. Portfolio: return=51.92%, vol=24.37%. Weights: w_XLP=0.1075, w_ADA-USD=0.0000, w_SHV=0.0000, w_PALL=0.8925.", "question": "Assets: XLP, ADA-USD, SHV, PALL\nAnnualized mean returns: XLP:0.0931, ADA-USD:-0.5896, SHV:-0.0002, PALL:0.5705\nCovariance matrix (annualized):\n[[0.020207, 0.041375, 3.7e-05, 0.004943], [0.041375, 0.769753, -1e-05, 0.027152], [3.7e-05, -1e-05, 1e-06, -4.6e-05], [0.004943, 0.027152, -4.6e-05, 0.07305]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1075, w_ADA-USD=0.0000, w_SHV=0.0000, w_PALL=0.8925", "answer_numeric": 1.9666592568754628, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.1075, w_ADA-USD=0.0000, w_SHV=0.0000, w_PALL=0.8925\nPortfolio annualized return: 51.92%, volatility: 24.37%\nSharpe ratio: (0.5192 - 0.0400) / 0.2437 = 1.9667", "metadata": {"weights": {"XLP": 0.1075, "ADA-USD": 0.0, "SHV": 0.0, "PALL": 0.8925}, "sharpe_ratio": 1.9667, "portfolio_return": 0.51919, "portfolio_vol": 0.243657, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220426_0843", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "BNO", "BNDX"], "decision_date": "2022-04-26", "context_summary": "4-asset optimization. Max-Sharpe: 3.568. Portfolio: return=51.99%, vol=13.45%. Weights: w_XLP=0.8354, w_DOT-USD=0.0031, w_BNO=0.1615, w_BNDX=0.0000.", "question": "Assets: XLP, DOT-USD, BNO, BNDX\nAnnualized mean returns: XLP:0.4563, DOT-USD:0.3363, BNO:0.8522, BNDX:-0.2204\nCovariance matrix (annualized):\n[[0.025665, 0.006348, -0.035743, -0.000635], [0.006348, 0.491176, 0.026839, 0.005391], [-0.035743, 0.026839, 0.374015, 0.008535], [-0.000635, 0.005391, 0.008535, 0.003421]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8354, w_DOT-USD=0.0031, w_BNO=0.1615, w_BNDX=0.0000", "answer_numeric": 3.5681898809203387, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.8354, w_DOT-USD=0.0031, w_BNO=0.1615, w_BNDX=0.0000\nPortfolio annualized return: 51.99%, volatility: 13.45%\nSharpe ratio: (0.5199 - 0.0400) / 0.1345 = 3.5682", "metadata": {"weights": {"XLP": 0.8354, "DOT-USD": 0.0031, "BNO": 0.1615, "BNDX": 0.0}, "sharpe_ratio": 3.5682, "portfolio_return": 0.51985, "portfolio_vol": 0.13448, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220923_0845", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "UNG", "BNDX"], "decision_date": "2022-09-23", "context_summary": "4-asset optimization. Max-Sharpe: -0.682. Portfolio: return=-40.50%, vol=65.21%. Weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_UNG=1.0000, w_BNDX=0.0000.", "question": "Assets: VEA, ADA-USD, UNG, BNDX\nAnnualized mean returns: VEA:-0.4051, ADA-USD:-1.2452, UNG:-0.4050, BNDX:-0.2312\nCovariance matrix (annualized):\n[[0.036246, 0.071994, 0.031292, 0.005116], [0.071994, 0.400236, 0.023969, 0.00958], [0.031292, 0.023969, 0.425283, 0.005322], [0.005116, 0.00958, 0.005322, 0.004049]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_UNG=1.0000, w_BNDX=0.0000", "answer_numeric": -0.6823076341024727, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_ADA-USD=0.0000, w_UNG=1.0000, w_BNDX=0.0000\nPortfolio annualized return: -40.50%, volatility: 65.21%\nSharpe ratio: (-0.4050 - 0.0400) / 0.6521 = -0.6823", "metadata": {"weights": {"VEA": 0.0, "ADA-USD": 0.0, "UNG": 1.0, "BNDX": 0.0}, "sharpe_ratio": -0.6823, "portfolio_return": -0.404958, "portfolio_vol": 0.652137, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220718_0847", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BNB-USD", "SHV", "DBA"], "decision_date": "2022-07-18", "context_summary": "4-asset optimization. Max-Sharpe: -0.004. Portfolio: return=3.88%, vol=27.25%. Weights: w_IWM=1.0000, w_BNB-USD=0.0000, w_SHV=0.0000, w_DBA=0.0000.", "question": "Assets: IWM, BNB-USD, SHV, DBA\nAnnualized mean returns: IWM:0.0388, BNB-USD:-1.2155, SHV:0.0038, DBA:-0.7333\nCovariance matrix (annualized):\n[[0.074248, 0.081567, 8.9e-05, 0.008823], [0.081567, 0.415878, 0.000507, -0.007523], [8.9e-05, 0.000507, 1e-05, -3.6e-05], [0.008823, -0.007523, -3.6e-05, 0.030322]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNB-USD=0.0000, w_SHV=0.0000, w_DBA=0.0000", "answer_numeric": -0.004391036602842869, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=1.0000, w_BNB-USD=0.0000, w_SHV=0.0000, w_DBA=0.0000\nPortfolio annualized return: 3.88%, volatility: 27.25%\nSharpe ratio: (0.0388 - 0.0400) / 0.2725 = -0.0044", "metadata": {"weights": {"IWM": 1.0, "BNB-USD": 0.0, "SHV": 0.0, "DBA": 0.0}, "sharpe_ratio": -0.0044, "portfolio_return": 0.038804, "portfolio_vol": 0.272486, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200803_0849", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "BIL", "IEF"], "decision_date": "2020-08-03", "context_summary": "4-asset optimization. Max-Sharpe: 6.361. Portfolio: return=24.81%, vol=3.27%. Weights: w_IVV=0.1359, w_SOL-USD=0.0184, w_BIL=0.0000, w_IEF=0.8457.", "question": "Assets: IVV, SOL-USD, BIL, IEF\nAnnualized mean returns: IVV:0.4669, SOL-USD:5.2318, BIL:0.0000, IEF:0.1046\nCovariance matrix (annualized):\n[[0.036925, 0.040061, 5.4e-05, -0.00421], [0.040061, 1.546695, 0.000138, -0.0085], [5.4e-05, 0.000138, 2e-06, 3e-06], [-0.00421, -0.0085, 3e-06, 0.001254]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1359, w_SOL-USD=0.0184, w_BIL=0.0000, w_IEF=0.8457", "answer_numeric": 6.361145633262255, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.1359, w_SOL-USD=0.0184, w_BIL=0.0000, w_IEF=0.8457\nPortfolio annualized return: 24.81%, volatility: 3.27%\nSharpe ratio: (0.2481 - 0.0400) / 0.0327 = 6.3611", "metadata": {"weights": {"IVV": 0.1359, "SOL-USD": 0.0184, "BIL": 0.0, "IEF": 0.8457}, "sharpe_ratio": 6.3611, "portfolio_return": 0.248117, "portfolio_vol": 0.032717, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180419_0857", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "WEAT", "VNQI"], "decision_date": "2018-04-19", "context_summary": "4-asset optimization. Max-Sharpe: 0.565. Portfolio: return=10.90%, vol=12.22%. Weights: w_IVV=0.0000, w_BTC-USD=0.0000, w_WEAT=0.0467, w_VNQI=0.9533.", "question": "Assets: IVV, BTC-USD, WEAT, VNQI\nAnnualized mean returns: IVV:-0.0443, BTC-USD:-1.7966, WEAT:0.0618, VNQI:0.1113\nCovariance matrix (annualized):\n[[0.037365, -0.008237, -0.002211, 0.019979], [-0.008237, 0.563323, 0.004293, -0.017589], [-0.002211, 0.004293, 0.068398, 0.001591], [0.019979, -0.017589, 0.001591, 0.016105]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.0000, w_WEAT=0.0467, w_VNQI=0.9533", "answer_numeric": 0.564711560982284, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_BTC-USD=0.0000, w_WEAT=0.0467, w_VNQI=0.9533\nPortfolio annualized return: 10.90%, volatility: 12.22%\nSharpe ratio: (0.1090 - 0.0400) / 0.1222 = 0.5647", "metadata": {"weights": {"IVV": 0.0, "BTC-USD": 0.0, "WEAT": 0.0467, "VNQI": 0.9533}, "sharpe_ratio": 0.5647, "portfolio_return": 0.108992, "portfolio_vol": 0.122173, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190318_0860", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BNB-USD", "PALL", "BIL"], "decision_date": "2019-03-18", "context_summary": "4-asset optimization. Max-Sharpe: 6.385. Portfolio: return=235.63%, vol=36.28%. Weights: w_XLV=0.0916, w_BNB-USD=0.3497, w_PALL=0.5587, w_BIL=0.0000.", "question": "Assets: XLV, BNB-USD, PALL, BIL\nAnnualized mean returns: XLV:0.2856, BNB-USD:5.1527, PALL:0.9455, BIL:0.0227\nCovariance matrix (annualized):\n[[0.016548, 0.019706, 0.009931, 9e-06], [0.019706, 0.766909, 0.036668, 0.00018], [0.009931, 0.036668, 0.067495, -2.3e-05], [9e-06, 0.00018, -2.3e-05, 3e-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=0.0916, w_BNB-USD=0.3497, w_PALL=0.5587, w_BIL=0.0000", "answer_numeric": 6.385049304503391, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0916, w_BNB-USD=0.3497, w_PALL=0.5587, w_BIL=0.0000\nPortfolio annualized return: 235.63%, volatility: 36.28%\nSharpe ratio: (2.3563 - 0.0400) / 0.3628 = 6.3850", "metadata": {"weights": {"XLV": 0.0916, "BNB-USD": 0.3497, "PALL": 0.5587, "BIL": 0.0}, "sharpe_ratio": 6.385, "portfolio_return": 2.356301, "portfolio_vol": 0.36277, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180116_0862", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "DBB", "IYR"], "decision_date": "2018-01-16", "context_summary": "4-asset optimization. Max-Sharpe: 6.693. Portfolio: return=55.81%, vol=7.74%. Weights: w_XLB=0.7529, w_LINK-USD=0.0126, w_DBB=0.2344, w_IYR=0.0000.", "question": "Assets: XLB, LINK-USD, DBB, IYR\nAnnualized mean returns: XLB:0.5955, LINK-USD:1.6487, DBB:0.3794, IYR:-0.3874\nCovariance matrix (annualized):\n[[0.009264, -0.02407, -0.001054, 0.001116], [-0.02407, 2.453784, 0.024663, 0.00222], [-0.001054, 0.024663, 0.018802, 0.002194], [0.001116, 0.00222, 0.002194, 0.010141]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7529, w_LINK-USD=0.0126, w_DBB=0.2344, w_IYR=0.0000", "answer_numeric": 6.693150554713668, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.7529, w_LINK-USD=0.0126, w_DBB=0.2344, w_IYR=0.0000\nPortfolio annualized return: 55.81%, volatility: 7.74%\nSharpe ratio: (0.5581 - 0.0400) / 0.0774 = 6.6932", "metadata": {"weights": {"XLB": 0.7529, "LINK-USD": 0.0126, "DBB": 0.2344, "IYR": 0.0}, "sharpe_ratio": 6.6932, "portfolio_return": 0.558125, "portfolio_vol": 0.077411, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190507_0864", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ETH-USD", "SHV", "ICSH"], "decision_date": "2019-05-07", "context_summary": "4-asset optimization. Max-Sharpe: 4.262. Portfolio: return=47.83%, vol=10.28%. Weights: w_VTI=0.9149, w_ETH-USD=0.0851, w_SHV=0.0000, w_ICSH=0.0000.", "question": "Assets: VTI, ETH-USD, SHV, ICSH\nAnnualized mean returns: VTI:0.4074, ETH-USD:1.2402, SHV:0.0244, ICSH:0.0335\nCovariance matrix (annualized):\n[[0.009749, -0.00062, -5.8e-05, -0.000145], [-0.00062, 0.346855, -1.3e-05, 0.000397], [-5.8e-05, -1.3e-05, 7e-06, -1e-06], [-0.000145, 0.000397, -1e-06, 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_VTI=0.9149, w_ETH-USD=0.0851, w_SHV=0.0000, w_ICSH=0.0000", "answer_numeric": 4.261754632386112, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.9149, w_ETH-USD=0.0851, w_SHV=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 47.83%, volatility: 10.28%\nSharpe ratio: (0.4783 - 0.0400) / 0.1028 = 4.2618", "metadata": {"weights": {"VTI": 0.9149, "ETH-USD": 0.0851, "SHV": 0.0, "ICSH": 0.0}, "sharpe_ratio": 4.2618, "portfolio_return": 0.478297, "portfolio_vol": 0.102844, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201127_0868", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "PDBC", "IEF"], "decision_date": "2020-11-27", "context_summary": "4-asset optimization. Max-Sharpe: 4.614. Portfolio: return=85.48%, vol=17.66%. Weights: w_XLRE=0.3180, w_ETH-USD=0.2583, w_PDBC=0.4237, w_IEF=0.0000.", "question": "Assets: XLRE, ETH-USD, PDBC, IEF\nAnnualized mean returns: XLRE:0.3637, ETH-USD:2.1263, PDBC:0.4485, IEF:-0.0868\nCovariance matrix (annualized):\n[[0.034228, -0.007202, 0.007945, -0.002119], [-0.007202, 0.30834, 0.005943, -0.000616], [0.007945, 0.005943, 0.027313, -0.001674], [-0.002119, -0.000616, -0.001674, 0.002043]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3180, w_ETH-USD=0.2583, w_PDBC=0.4237, w_IEF=0.0000", "answer_numeric": 4.613827386741359, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.3180, w_ETH-USD=0.2583, w_PDBC=0.4237, w_IEF=0.0000\nPortfolio annualized return: 85.48%, volatility: 17.66%\nSharpe ratio: (0.8548 - 0.0400) / 0.1766 = 4.6138", "metadata": {"weights": {"XLRE": 0.318, "ETH-USD": 0.2583, "PDBC": 0.4237, "IEF": 0.0}, "sharpe_ratio": 4.6138, "portfolio_return": 0.854821, "portfolio_vol": 0.176604, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200324_0870", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BTC-USD", "STIP", "SOYB"], "decision_date": "2020-03-24", "context_summary": "4-asset optimization. Max-Sharpe: 2.032. Portfolio: return=150.34%, vol=72.03%. Weights: w_XLP=0.0000, w_BTC-USD=1.0000, w_STIP=0.0000, w_SOYB=0.0000.", "question": "Assets: XLP, BTC-USD, STIP, SOYB\nAnnualized mean returns: XLP:-1.3388, BTC-USD:1.5034, STIP:0.0213, SOYB:-0.4613\nCovariance matrix (annualized):\n[[0.057772, 0.044193, -0.000135, 0.007698], [0.044193, 0.518845, 0.011482, 0.039168], [-0.000135, 0.011482, 0.001306, 0.001928], [0.007698, 0.039168, 0.001928, 0.020942]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_STIP=0.0000, w_SOYB=0.0000", "answer_numeric": 2.0316330257341164, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_BTC-USD=1.0000, w_STIP=0.0000, w_SOYB=0.0000\nPortfolio annualized return: 150.34%, volatility: 72.03%\nSharpe ratio: (1.5034 - 0.0400) / 0.7203 = 2.0316", "metadata": {"weights": {"XLP": 0.0, "BTC-USD": 1.0, "STIP": 0.0, "SOYB": 0.0}, "sharpe_ratio": 2.0316, "portfolio_return": 1.503403, "portfolio_vol": 0.720309, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211223_0872", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "MATIC-USD", "IAU", "VCIT"], "decision_date": "2021-12-23", "context_summary": "4-asset optimization. Max-Sharpe: 3.565. Portfolio: return=279.50%, vol=77.28%. Weights: w_^VIX=0.2949, w_MATIC-USD=0.7051, w_IAU=0.0000, w_VCIT=0.0000.", "question": "Assets: ^VIX, MATIC-USD, IAU, VCIT\nAnnualized mean returns: ^VIX:0.4747, MATIC-USD:3.7656, IAU:0.0381, VCIT:0.0356\nCovariance matrix (annualized):\n[[2.142987, -0.762834, -0.012985, 0.014305], [-0.762834, 1.464535, 0.009501, -0.006312], [-0.012985, 0.009501, 0.013413, 0.001955], [0.014305, -0.006312, 0.001955, 0.002025]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2949, w_MATIC-USD=0.7051, w_IAU=0.0000, w_VCIT=0.0000", "answer_numeric": 3.565073845948715, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.2949, w_MATIC-USD=0.7051, w_IAU=0.0000, w_VCIT=0.0000\nPortfolio annualized return: 279.50%, volatility: 77.28%\nSharpe ratio: (2.7950 - 0.0400) / 0.7728 = 3.5651", "metadata": {"weights": {"^VIX": 0.2949, "MATIC-USD": 0.7051, "IAU": 0.0, "VCIT": 0.0}, "sharpe_ratio": 3.5651, "portfolio_return": 2.794995, "portfolio_vol": 0.772774, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180720_0874", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "REZ", "JNK"], "decision_date": "2018-07-20", "context_summary": "4-asset optimization. Max-Sharpe: 5.752. Portfolio: return=50.66%, vol=8.11%. Weights: w_XLY=0.4529, w_BTC-USD=0.0262, w_REZ=0.5209, w_JNK=0.0000.", "question": "Assets: XLY, BTC-USD, REZ, JNK\nAnnualized mean returns: XLY:0.4451, BTC-USD:-0.3480, REZ:0.6030, JNK:0.0635\nCovariance matrix (annualized):\n[[0.010947, -0.00759, 0.001831, 0.001981], [-0.00759, 0.308234, -0.019389, -0.00176], [0.001831, -0.019389, 0.014626, 0.000445], [0.001981, -0.00176, 0.000445, 0.000862]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4529, w_BTC-USD=0.0262, w_REZ=0.5209, w_JNK=0.0000", "answer_numeric": 5.752141490327047, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.4529, w_BTC-USD=0.0262, w_REZ=0.5209, w_JNK=0.0000\nPortfolio annualized return: 50.66%, volatility: 8.11%\nSharpe ratio: (0.5066 - 0.0400) / 0.0811 = 5.7521", "metadata": {"weights": {"XLY": 0.4529, "BTC-USD": 0.0262, "REZ": 0.5209, "JNK": 0.0}, "sharpe_ratio": 5.7521, "portfolio_return": 0.506627, "portfolio_vol": 0.081122, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210209_0878", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "BNO", "ITB"], "decision_date": "2021-02-09", "context_summary": "4-asset optimization. Max-Sharpe: 6.992. Portfolio: return=154.40%, vol=21.51%. Weights: w_QUAL=0.0000, w_ETH-USD=0.1050, w_BNO=0.4806, w_ITB=0.4144.", "question": "Assets: QUAL, ETH-USD, BNO, ITB\nAnnualized mean returns: QUAL:0.2964, ETH-USD:4.6099, BNO:1.2309, ITB:1.1304\nCovariance matrix (annualized):\n[[0.018981, 0.0297, 0.01358, 0.018895], [0.0297, 1.068212, 0.042732, 0.019052], [0.01358, 0.042732, 0.060969, 0.006871], [0.018895, 0.019052, 0.006871, 0.068147]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.1050, w_BNO=0.4806, w_ITB=0.4144", "answer_numeric": 6.992135232641246, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_ETH-USD=0.1050, w_BNO=0.4806, w_ITB=0.4144\nPortfolio annualized return: 154.40%, volatility: 21.51%\nSharpe ratio: (1.5440 - 0.0400) / 0.2151 = 6.9921", "metadata": {"weights": {"QUAL": 0.0, "ETH-USD": 0.105, "BNO": 0.4806, "ITB": 0.4144}, "sharpe_ratio": 6.9921, "portfolio_return": 1.544005, "portfolio_vol": 0.2151, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221207_0882", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "LINK-USD", "TLH", "MORT"], "decision_date": "2022-12-07", "context_summary": "4-asset optimization. Max-Sharpe: 2.085. Portfolio: return=48.01%, vol=21.11%. Weights: w_IWM=0.0000, w_LINK-USD=0.0005, w_TLH=0.4094, w_MORT=0.5901.", "question": "Assets: IWM, LINK-USD, TLH, MORT\nAnnualized mean returns: IWM:0.2517, LINK-USD:0.7341, TLH:0.2013, MORT:0.6733\nCovariance matrix (annualized):\n[[0.070847, 0.125251, 0.009016, 0.067239], [0.125251, 0.883934, 0.008499, 0.112417], [0.009016, 0.008499, 0.021704, 0.012601], [0.067239, 0.112417, 0.012601, 0.099787]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=0.0005, w_TLH=0.4094, w_MORT=0.5901", "answer_numeric": 2.085100839227105, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_LINK-USD=0.0005, w_TLH=0.4094, w_MORT=0.5901\nPortfolio annualized return: 48.01%, volatility: 21.11%\nSharpe ratio: (0.4801 - 0.0400) / 0.2111 = 2.0851", "metadata": {"weights": {"IWM": 0.0, "LINK-USD": 0.0005, "TLH": 0.4094, "MORT": 0.5901}, "sharpe_ratio": 2.0851, "portfolio_return": 0.480086, "portfolio_vol": 0.211062, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180206_0884", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "SCHH", "DBA"], "decision_date": "2018-02-06", "context_summary": "4-asset optimization. Max-Sharpe: 1.353. Portfolio: return=14.22%, vol=7.56%. Weights: w_VEA=0.3760, w_ADA-USD=0.0000, w_SCHH=0.0000, w_DBA=0.6240.", "question": "Assets: VEA, ADA-USD, SCHH, DBA\nAnnualized mean returns: VEA:0.1663, ADA-USD:-1.6762, SCHH:-0.5895, DBA:0.1277\nCovariance matrix (annualized):\n[[0.014364, 0.060552, 0.00839, 0.002654], [0.060552, 3.034537, 0.040125, 0.003298], [0.00839, 0.040125, 0.027041, -0.000761], [0.002654, 0.003298, -0.000761, 0.006256]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3760, w_ADA-USD=0.0000, w_SCHH=0.0000, w_DBA=0.6240", "answer_numeric": 1.3526789862566093, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.3760, w_ADA-USD=0.0000, w_SCHH=0.0000, w_DBA=0.6240\nPortfolio annualized return: 14.22%, volatility: 7.56%\nSharpe ratio: (0.1422 - 0.0400) / 0.0756 = 1.3527", "metadata": {"weights": {"VEA": 0.376, "ADA-USD": 0.0, "SCHH": 0.0, "DBA": 0.624}, "sharpe_ratio": 1.3527, "portfolio_return": 0.142234, "portfolio_vol": 0.075579, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180208_0886", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "XRP-USD", "TLH", "SCHH"], "decision_date": "2018-02-08", "context_summary": "4-asset optimization. Max-Sharpe: 3.032. Portfolio: return=130.08%, vol=41.58%. Weights: w_XLI=0.8406, w_XRP-USD=0.1594, w_TLH=0.0000, w_SCHH=0.0000.", "question": "Assets: XLI, XRP-USD, TLH, SCHH\nAnnualized mean returns: XLI:0.2207, XRP-USD:6.9978, TLH:-0.2648, SCHH:-0.6311\nCovariance matrix (annualized):\n[[0.018759, 0.056528, -0.001918, 0.009097], [0.056528, 5.688319, 0.032203, 0.086243], [-0.001918, 0.032203, 0.003727, 0.002244], [0.009097, 0.086243, 0.002244, 0.025982]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8406, w_XRP-USD=0.1594, w_TLH=0.0000, w_SCHH=0.0000", "answer_numeric": 3.032248891341544, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.8406, w_XRP-USD=0.1594, w_TLH=0.0000, w_SCHH=0.0000\nPortfolio annualized return: 130.08%, volatility: 41.58%\nSharpe ratio: (1.3008 - 0.0400) / 0.4158 = 3.0322", "metadata": {"weights": {"XLI": 0.8406, "XRP-USD": 0.1594, "TLH": 0.0, "SCHH": 0.0}, "sharpe_ratio": 3.0322, "portfolio_return": 1.300791, "portfolio_vol": 0.415794, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181112_0890", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "IYR", "PDBC"], "decision_date": "2018-11-12", "context_summary": "4-asset optimization. Max-Sharpe: 0.637. Portfolio: return=17.98%, vol=21.93%. Weights: w_XLU=0.8358, w_ETH-USD=0.1642, w_IYR=0.0000, w_PDBC=0.0000.", "question": "Assets: XLU, ETH-USD, IYR, PDBC\nAnnualized mean returns: XLU:0.1296, ETH-USD:0.4350, IYR:-0.0786, PDBC:-0.3729\nCovariance matrix (annualized):\n[[0.029043, 0.039968, 0.019808, -0.000332], [0.039968, 0.624074, 0.043565, 0.010313], [0.019808, 0.043565, 0.029701, 0.000272], [-0.000332, 0.010313, 0.000272, 0.019852]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8358, w_ETH-USD=0.1642, w_IYR=0.0000, w_PDBC=0.0000", "answer_numeric": 0.637401965400671, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.8358, w_ETH-USD=0.1642, w_IYR=0.0000, w_PDBC=0.0000\nPortfolio annualized return: 17.98%, volatility: 21.93%\nSharpe ratio: (0.1798 - 0.0400) / 0.2193 = 0.6374", "metadata": {"weights": {"XLU": 0.8358, "ETH-USD": 0.1642, "IYR": 0.0, "PDBC": 0.0}, "sharpe_ratio": 0.6374, "portfolio_return": 0.179781, "portfolio_vol": 0.219298, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210607_0897", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "IAU", "SHY"], "decision_date": "2021-06-07", "context_summary": "4-asset optimization. Max-Sharpe: 5.257. Portfolio: return=63.94%, vol=11.40%. Weights: w_XLB=0.3166, w_BNB-USD=0.0291, w_IAU=0.6543, w_SHY=0.0000.", "question": "Assets: XLB, BNB-USD, IAU, SHY\nAnnualized mean returns: XLB:0.6366, BNB-USD:3.1160, IAU:0.5305, SHY:0.0060\nCovariance matrix (annualized):\n[[0.025224, 0.03881, 0.005842, 6.7e-05], [0.03881, 2.249417, -0.016915, 0.001181], [0.005842, -0.016915, 0.014184, 0.000205], [6.7e-05, 0.001181, 0.000205, 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=0.3166, w_BNB-USD=0.0291, w_IAU=0.6543, w_SHY=0.0000", "answer_numeric": 5.257167827598551, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.3166, w_BNB-USD=0.0291, w_IAU=0.6543, w_SHY=0.0000\nPortfolio annualized return: 63.94%, volatility: 11.40%\nSharpe ratio: (0.6394 - 0.0400) / 0.1140 = 5.2572", "metadata": {"weights": {"XLB": 0.3166, "BNB-USD": 0.0291, "IAU": 0.6543, "SHY": 0.0}, "sharpe_ratio": 5.2572, "portfolio_return": 0.639372, "portfolio_vol": 0.11401, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190128_0899", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "SCHH", "ICSH"], "decision_date": "2019-01-28", "context_summary": "4-asset optimization. Max-Sharpe: 0.051. Portfolio: return=5.17%, vol=22.91%. Weights: w_XLY=0.0000, w_BTC-USD=0.0000, w_SCHH=1.0000, w_ICSH=0.0000.", "question": "Assets: XLY, BTC-USD, SCHH, ICSH\nAnnualized mean returns: XLY:-0.1738, BTC-USD:-0.9204, SCHH:0.0517, ICSH:0.0338\nCovariance matrix (annualized):\n[[0.067435, -0.03051, 0.037045, -0.00037], [-0.03051, 0.423609, -0.063669, 0.000412], [0.037045, -0.063669, 0.052502, -0.000275], [-0.00037, 0.000412, -0.000275, 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_XLY=0.0000, w_BTC-USD=0.0000, w_SCHH=1.0000, w_ICSH=0.0000", "answer_numeric": 0.05118044395062685, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_BTC-USD=0.0000, w_SCHH=1.0000, w_ICSH=0.0000\nPortfolio annualized return: 5.17%, volatility: 22.91%\nSharpe ratio: (0.0517 - 0.0400) / 0.2291 = 0.0512", "metadata": {"weights": {"XLY": 0.0, "BTC-USD": 0.0, "SCHH": 1.0, "ICSH": 0.0}, "sharpe_ratio": 0.0512, "portfolio_return": 0.051727, "portfolio_vol": 0.229134, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200805_0902", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "IEF", "ITB"], "decision_date": "2020-08-05", "context_summary": "4-asset optimization. Max-Sharpe: 8.609. Portfolio: return=24.47%, vol=2.38%. Weights: w_IVV=0.0505, w_ADA-USD=0.0089, w_IEF=0.8966, w_ITB=0.0440.", "question": "Assets: IVV, ADA-USD, IEF, ITB\nAnnualized mean returns: IVV:0.3943, ADA-USD:2.0329, IEF:0.1777, ITB:1.0778\nCovariance matrix (annualized):\n[[0.033325, 0.03745, -0.003517, 0.04807], [0.03745, 0.672592, -0.004762, 0.043463], [-0.003517, -0.004762, 0.00099, -0.006529], [0.04807, 0.043463, -0.006529, 0.134139]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0505, w_ADA-USD=0.0089, w_IEF=0.8966, w_ITB=0.0440", "answer_numeric": 8.60875357145474, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0505, w_ADA-USD=0.0089, w_IEF=0.8966, w_ITB=0.0440\nPortfolio annualized return: 24.47%, volatility: 2.38%\nSharpe ratio: (0.2447 - 0.0400) / 0.0238 = 8.6088", "metadata": {"weights": {"IVV": 0.0505, "ADA-USD": 0.0089, "IEF": 0.8966, "ITB": 0.044}, "sharpe_ratio": 8.6088, "portfolio_return": 0.244704, "portfolio_vol": 0.023779, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201022_0905", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "ICSH", "SCHP"], "decision_date": "2020-10-22", "context_summary": "4-asset optimization. Max-Sharpe: 0.272. Portfolio: return=9.51%, vol=20.26%. Weights: w_IVV=1.0000, w_MATIC-USD=0.0000, w_ICSH=0.0000, w_SCHP=0.0000.", "question": "Assets: IVV, MATIC-USD, ICSH, SCHP\nAnnualized mean returns: IVV:0.0951, MATIC-USD:-2.3707, ICSH:0.0053, SCHP:0.0183\nCovariance matrix (annualized):\n[[0.041042, 0.091996, -0.000158, 0.00115], [0.091996, 0.830765, -0.00021, 0.009564], [-0.000158, -0.00021, 1.2e-05, 3e-05], [0.00115, 0.009564, 3e-05, 0.000798]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_MATIC-USD=0.0000, w_ICSH=0.0000, w_SCHP=0.0000", "answer_numeric": 0.2717552760749285, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=1.0000, w_MATIC-USD=0.0000, w_ICSH=0.0000, w_SCHP=0.0000\nPortfolio annualized return: 9.51%, volatility: 20.26%\nSharpe ratio: (0.0951 - 0.0400) / 0.2026 = 0.2718", "metadata": {"weights": {"IVV": 1.0, "MATIC-USD": 0.0, "ICSH": 0.0, "SCHP": 0.0}, "sharpe_ratio": 0.2718, "portfolio_return": 0.095054, "portfolio_vol": 0.202588, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210122_0908", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "AVAX-USD", "VNQ", "SGOV"], "decision_date": "2021-01-22", "context_summary": "4-asset optimization. Max-Sharpe: 4.036. Portfolio: return=453.42%, vol=111.36%. Weights: w_^VIX=0.0171, w_AVAX-USD=0.8877, w_VNQ=0.0951, w_SGOV=0.0000.", "question": "Assets: ^VIX, AVAX-USD, VNQ, SGOV\nAnnualized mean returns: ^VIX:-0.6667, AVAX-USD:5.1006, VNQ:0.1851, SGOV:0.0007\nCovariance matrix (annualized):\n[[0.882017, -0.227479, -0.085778, -2.7e-05], [-0.227479, 1.572535, 0.043819, 8.3e-05], [-0.085778, 0.043819, 0.027358, 5e-06], [-2.7e-05, 8.3e-05, 5e-06, 0.0]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0171, w_AVAX-USD=0.8877, w_VNQ=0.0951, w_SGOV=0.0000", "answer_numeric": 4.035921435580433, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0171, w_AVAX-USD=0.8877, w_VNQ=0.0951, w_SGOV=0.0000\nPortfolio annualized return: 453.42%, volatility: 111.36%\nSharpe ratio: (4.5342 - 0.0400) / 1.1136 = 4.0359", "metadata": {"weights": {"^VIX": 0.0171, "AVAX-USD": 0.8877, "VNQ": 0.0951, "SGOV": 0.0}, "sharpe_ratio": 4.0359, "portfolio_return": 4.534209, "portfolio_vol": 1.113552, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210723_0910", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "DOT-USD", "PDBC", "SCHH"], "decision_date": "2021-07-23", "context_summary": "4-asset optimization. Max-Sharpe: 3.303. Portfolio: return=46.39%, vol=12.83%. Weights: w_VLUE=0.0000, w_DOT-USD=0.0000, w_PDBC=0.2614, w_SCHH=0.7386.", "question": "Assets: VLUE, DOT-USD, PDBC, SCHH\nAnnualized mean returns: VLUE:-0.1481, DOT-USD:-1.5722, PDBC:0.3776, SCHH:0.4945\nCovariance matrix (annualized):\n[[0.020022, 0.023669, 0.014754, 0.012205], [0.023669, 1.881361, 0.030814, -0.001134], [0.014754, 0.030814, 0.032295, 0.006331], [0.012205, -0.001134, 0.006331, 0.021664]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2614, w_SCHH=0.7386", "answer_numeric": 3.303309161854023, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_DOT-USD=0.0000, w_PDBC=0.2614, w_SCHH=0.7386\nPortfolio annualized return: 46.39%, volatility: 12.83%\nSharpe ratio: (0.4639 - 0.0400) / 0.1283 = 3.3033", "metadata": {"weights": {"VLUE": 0.0, "DOT-USD": 0.0, "PDBC": 0.2614, "SCHH": 0.7386}, "sharpe_ratio": 3.3033, "portfolio_return": 0.463932, "portfolio_vol": 0.128336, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210927_0912", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "MATIC-USD", "VNQI", "GLD"], "decision_date": "2021-09-27", "context_summary": "4-asset optimization. Max-Sharpe: 1.124. Portfolio: return=140.86%, vol=121.76%. Weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_VNQI=0.0000, w_GLD=0.0000.", "question": "Assets: XLU, MATIC-USD, VNQI, GLD\nAnnualized mean returns: XLU:-0.0668, MATIC-USD:1.4086, VNQI:-0.1213, GLD:-0.2046\nCovariance matrix (annualized):\n[[0.014459, 0.048817, 0.003868, 0.003127], [0.048817, 1.482646, 0.069402, 0.043585], [0.003868, 0.069402, 0.016933, 0.00636], [0.003127, 0.043585, 0.00636, 0.021124]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_VNQI=0.0000, w_GLD=0.0000", "answer_numeric": 1.1239618367156854, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_MATIC-USD=1.0000, w_VNQI=0.0000, w_GLD=0.0000\nPortfolio annualized return: 140.86%, volatility: 121.76%\nSharpe ratio: (1.4086 - 0.0400) / 1.2176 = 1.1240", "metadata": {"weights": {"XLU": 0.0, "MATIC-USD": 1.0, "VNQI": 0.0, "GLD": 0.0}, "sharpe_ratio": 1.124, "portfolio_return": 1.40858, "portfolio_vol": 1.217639, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220608_0914", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LINK-USD", "BIL", "VCIT"], "decision_date": "2022-06-08", "context_summary": "4-asset optimization. Max-Sharpe: -1.876. Portfolio: return=-45.68%, vol=26.48%. Weights: w_XLF=1.0000, w_LINK-USD=0.0000, w_BIL=0.0000, w_VCIT=0.0000.", "question": "Assets: XLF, LINK-USD, BIL, VCIT\nAnnualized mean returns: XLF:-0.4568, LINK-USD:-4.8359, BIL:0.0028, VCIT:-0.1381\nCovariance matrix (annualized):\n[[0.070107, 0.136939, 0.000228, 0.005547], [0.136939, 1.071285, 0.000544, 0.009157], [0.000228, 0.000544, 4e-06, 3.7e-05], [0.005547, 0.009157, 3.7e-05, 0.006378]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BIL=0.0000, w_VCIT=0.0000", "answer_numeric": -1.876239901897799, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=1.0000, w_LINK-USD=0.0000, w_BIL=0.0000, w_VCIT=0.0000\nPortfolio annualized return: -45.68%, volatility: 26.48%\nSharpe ratio: (-0.4568 - 0.0400) / 0.2648 = -1.8762", "metadata": {"weights": {"XLF": 1.0, "LINK-USD": 0.0, "BIL": 0.0, "VCIT": 0.0}, "sharpe_ratio": -1.8762, "portfolio_return": -0.456786, "portfolio_vol": 0.264777, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200703_0917", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ETH-USD", "VNQI", "TIP"], "decision_date": "2020-07-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.649. Portfolio: return=12.77%, vol=1.89%. Weights: w_EFA=0.0422, w_ETH-USD=0.0000, w_VNQI=0.0000, w_TIP=0.9578.", "question": "Assets: EFA, ETH-USD, VNQI, TIP\nAnnualized mean returns: EFA:0.7856, ETH-USD:0.8100, VNQI:0.6302, TIP:0.0987\nCovariance matrix (annualized):\n[[0.044405, 0.042726, 0.040705, 0.001201], [0.042726, 0.21129, 0.027608, 0.001729], [0.040705, 0.027608, 0.049257, 0.001172], [0.001201, 0.001729, 0.001172, 0.000196]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0422, w_ETH-USD=0.0000, w_VNQI=0.0000, w_TIP=0.9578", "answer_numeric": 4.649109205083889, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0422, w_ETH-USD=0.0000, w_VNQI=0.0000, w_TIP=0.9578\nPortfolio annualized return: 12.77%, volatility: 1.89%\nSharpe ratio: (0.1277 - 0.0400) / 0.0189 = 4.6491", "metadata": {"weights": {"EFA": 0.0422, "ETH-USD": 0.0, "VNQI": 0.0, "TIP": 0.9578}, "sharpe_ratio": 4.6491, "portfolio_return": 0.127705, "portfolio_vol": 0.018865, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211220_0919", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ETH-USD", "PDBC", "VCIT"], "decision_date": "2021-12-20", "context_summary": "4-asset optimization. Max-Sharpe: -1.528. Portfolio: return=-102.33%, vol=69.57%. Weights: w_MTUM=0.0000, w_ETH-USD=1.0000, w_PDBC=0.0000, w_VCIT=0.0000.", "question": "Assets: MTUM, ETH-USD, PDBC, VCIT\nAnnualized mean returns: MTUM:-0.3355, ETH-USD:-1.0233, PDBC:-0.3257, VCIT:0.0411\nCovariance matrix (annualized):\n[[0.040665, 0.048679, 0.019305, -0.002019], [0.048679, 0.483959, 0.026027, -0.006287], [0.019305, 0.026027, 0.034921, -0.002075], [-0.002019, -0.006287, -0.002075, 0.002121]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=1.0000, w_PDBC=0.0000, w_VCIT=0.0000", "answer_numeric": -1.5284417362740945, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_ETH-USD=1.0000, w_PDBC=0.0000, w_VCIT=0.0000\nPortfolio annualized return: -102.33%, volatility: 69.57%\nSharpe ratio: (-1.0233 - 0.0400) / 0.6957 = -1.5284", "metadata": {"weights": {"MTUM": 0.0, "ETH-USD": 1.0, "PDBC": 0.0, "VCIT": 0.0}, "sharpe_ratio": -1.5284, "portfolio_return": -1.023294, "portfolio_vol": 0.695672, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190923_0924", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "STIP", "HAUZ"], "decision_date": "2019-09-23", "context_summary": "4-asset optimization. Max-Sharpe: -0.451. Portfolio: return=-4.76%, vol=19.43%. Weights: w_XLI=1.0000, w_ADA-USD=0.0000, w_STIP=0.0000, w_HAUZ=0.0000.", "question": "Assets: XLI, ADA-USD, STIP, HAUZ\nAnnualized mean returns: XLI:-0.0476, ADA-USD:-1.9505, STIP:0.0178, HAUZ:-0.0511\nCovariance matrix (annualized):\n[[0.037758, 0.000452, -0.000767, 0.015604], [0.000452, 0.335923, -0.001229, 0.005187], [-0.000767, -0.001229, 0.000287, 5.3e-05], [0.015604, 0.005187, 5.3e-05, 0.013557]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ADA-USD=0.0000, w_STIP=0.0000, w_HAUZ=0.0000", "answer_numeric": -0.4506002494989363, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=1.0000, w_ADA-USD=0.0000, w_STIP=0.0000, w_HAUZ=0.0000\nPortfolio annualized return: -4.76%, volatility: 19.43%\nSharpe ratio: (-0.0476 - 0.0400) / 0.1943 = -0.4506", "metadata": {"weights": {"XLI": 1.0, "ADA-USD": 0.0, "STIP": 0.0, "HAUZ": 0.0}, "sharpe_ratio": -0.4506, "portfolio_return": -0.047558, "portfolio_vol": 0.194315, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190925_0927", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "MATIC-USD", "SCHH", "TLH"], "decision_date": "2019-09-25", "context_summary": "4-asset optimization. Max-Sharpe: 3.894. Portfolio: return=31.96%, vol=7.18%. Weights: w_XLI=0.0077, w_MATIC-USD=0.0000, w_SCHH=0.4034, w_TLH=0.5889.", "question": "Assets: XLI, MATIC-USD, SCHH, TLH\nAnnualized mean returns: XLI:-0.0686, MATIC-USD:-0.7115, SCHH:0.2670, TLH:0.3606\nCovariance matrix (annualized):\n[[0.03792, 0.012819, 0.015884, -0.014777], [0.012819, 1.697238, 0.006275, -0.001497], [0.015884, 0.006275, 0.015064, -0.003421], [-0.014777, -0.001497, -0.003421, 0.012574]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0077, w_MATIC-USD=0.0000, w_SCHH=0.4034, w_TLH=0.5889", "answer_numeric": 3.894278548561893, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0077, w_MATIC-USD=0.0000, w_SCHH=0.4034, w_TLH=0.5889\nPortfolio annualized return: 31.96%, volatility: 7.18%\nSharpe ratio: (0.3196 - 0.0400) / 0.0718 = 3.8943", "metadata": {"weights": {"XLI": 0.0077, "MATIC-USD": 0.0, "SCHH": 0.4034, "TLH": 0.5889}, "sharpe_ratio": 3.8943, "portfolio_return": 0.319567, "portfolio_vol": 0.071789, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20211231_0934", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "BIL", "WEAT"], "decision_date": "2021-12-31", "context_summary": "4-asset optimization. Max-Sharpe: -0.174. Portfolio: return=-0.59%, vol=26.39%. Weights: w_EEM=0.0000, w_BTC-USD=0.0000, w_BIL=0.0000, w_WEAT=1.0000.", "question": "Assets: EEM, BTC-USD, BIL, WEAT\nAnnualized mean returns: EEM:-0.1311, BTC-USD:-2.2608, BIL:-0.0013, WEAT:-0.0059\nCovariance matrix (annualized):\n[[0.023105, 0.042626, 7.6e-05, 0.008908], [0.042626, 0.25999, 8.5e-05, 0.01056], [7.6e-05, 8.5e-05, 2e-06, -3e-06], [0.008908, 0.01056, -3e-06, 0.069659]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_BIL=0.0000, w_WEAT=1.0000", "answer_numeric": -0.1739184788351957, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_BTC-USD=0.0000, w_BIL=0.0000, w_WEAT=1.0000\nPortfolio annualized return: -0.59%, volatility: 26.39%\nSharpe ratio: (-0.0059 - 0.0400) / 0.2639 = -0.1739", "metadata": {"weights": {"EEM": 0.0, "BTC-USD": 0.0, "BIL": 0.0, "WEAT": 1.0}, "sharpe_ratio": -0.1739, "portfolio_return": -0.005902, "portfolio_vol": 0.263931, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220704_0937", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BTC-USD", "DBC", "IYR"], "decision_date": "2022-07-04", "context_summary": "4-asset optimization. Max-Sharpe: -1.713. Portfolio: return=-43.06%, vol=27.47%. Weights: w_EWJ=0.0000, w_BTC-USD=0.0000, w_DBC=0.0000, w_IYR=1.0000.", "question": "Assets: EWJ, BTC-USD, DBC, IYR\nAnnualized mean returns: EWJ:-0.5076, BTC-USD:-4.5380, DBC:-0.1963, IYR:-0.4306\nCovariance matrix (annualized):\n[[0.039087, 0.086596, 0.016314, 0.043193], [0.086596, 0.430088, 0.016606, 0.103834], [0.016314, 0.016606, 0.047726, 0.015393], [0.043193, 0.103834, 0.015393, 0.075465]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.0000, w_DBC=0.0000, w_IYR=1.0000", "answer_numeric": -1.7131565628773615, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_BTC-USD=0.0000, w_DBC=0.0000, w_IYR=1.0000\nPortfolio annualized return: -43.06%, volatility: 27.47%\nSharpe ratio: (-0.4306 - 0.0400) / 0.2747 = -1.7132", "metadata": {"weights": {"EWJ": 0.0, "BTC-USD": 0.0, "DBC": 0.0, "IYR": 1.0}, "sharpe_ratio": -1.7132, "portfolio_return": -0.430619, "portfolio_vol": 0.274709, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220131_0942", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "MATIC-USD", "TLT", "DBC"], "decision_date": "2022-01-31", "context_summary": "4-asset optimization. Max-Sharpe: 6.367. Portfolio: return=92.94%, vol=13.97%. Weights: w_VEA=0.0000, w_MATIC-USD=0.0000, w_TLT=0.0000, w_DBC=1.0000.", "question": "Assets: VEA, MATIC-USD, TLT, DBC\nAnnualized mean returns: VEA:-0.0475, MATIC-USD:-0.1547, TLT:-0.3517, DBC:0.9294\nCovariance matrix (annualized):\n[[0.018736, 0.093443, -0.006203, 0.012596], [0.093443, 1.271873, -0.029452, 0.088095], [-0.006203, -0.029452, 0.02233, -0.007204], [0.012596, 0.088095, -0.007204, 0.019516]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_TLT=0.0000, w_DBC=1.0000", "answer_numeric": 6.366592186350255, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_MATIC-USD=0.0000, w_TLT=0.0000, w_DBC=1.0000\nPortfolio annualized return: 92.94%, volatility: 13.97%\nSharpe ratio: (0.9294 - 0.0400) / 0.1397 = 6.3666", "metadata": {"weights": {"VEA": 0.0, "MATIC-USD": 0.0, "TLT": 0.0, "DBC": 1.0}, "sharpe_ratio": 6.3666, "portfolio_return": 0.929421, "portfolio_vol": 0.139701, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181018_0945", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "CORN", "LQD"], "decision_date": "2018-10-18", "context_summary": "4-asset optimization. Max-Sharpe: 0.561. Portfolio: return=39.94%, vol=64.11%. Weights: w_IVV=0.0000, w_BNB-USD=1.0000, w_CORN=0.0000, w_LQD=0.0000.", "question": "Assets: IVV, BNB-USD, CORN, LQD\nAnnualized mean returns: IVV:-0.0683, BNB-USD:0.3994, CORN:-0.0662, LQD:-0.1268\nCovariance matrix (annualized):\n[[0.016697, 0.022629, -0.000164, 0.000716], [0.022629, 0.41103, 0.012229, -0.002969], [-0.000164, 0.012229, 0.027414, 0.000706], [0.000716, -0.002969, 0.000706, 0.001634]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_CORN=0.0000, w_LQD=0.0000", "answer_numeric": 0.5605855710098986, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_BNB-USD=1.0000, w_CORN=0.0000, w_LQD=0.0000\nPortfolio annualized return: 39.94%, volatility: 64.11%\nSharpe ratio: (0.3994 - 0.0400) / 0.6411 = 0.5606", "metadata": {"weights": {"IVV": 0.0, "BNB-USD": 1.0, "CORN": 0.0, "LQD": 0.0}, "sharpe_ratio": 0.5606, "portfolio_return": 0.3994, "portfolio_vol": 0.641116, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220725_0949", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "SCHP", "BIL"], "decision_date": "2022-07-25", "context_summary": "4-asset optimization. Max-Sharpe: -1.034. Portfolio: return=-86.60%, vol=87.62%. Weights: w_EFA=0.0000, w_ADA-USD=1.0000, w_SCHP=0.0000, w_BIL=0.0000.", "question": "Assets: EFA, ADA-USD, SCHP, BIL\nAnnualized mean returns: EFA:-0.3886, ADA-USD:-0.8660, SCHP:-0.0357, BIL:0.0059\nCovariance matrix (annualized):\n[[0.048483, 0.095952, 0.00649, -9e-06], [0.095952, 0.7678, 0.002715, -5.5e-05], [0.00649, 0.002715, 0.006599, 9e-06], [-9e-06, -5.5e-05, 9e-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_EFA=0.0000, w_ADA-USD=1.0000, w_SCHP=0.0000, w_BIL=0.0000", "answer_numeric": -1.0339579746262548, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_ADA-USD=1.0000, w_SCHP=0.0000, w_BIL=0.0000\nPortfolio annualized return: -86.60%, volatility: 87.62%\nSharpe ratio: (-0.8660 - 0.0400) / 0.8762 = -1.0340", "metadata": {"weights": {"EFA": 0.0, "ADA-USD": 1.0, "SCHP": 0.0, "BIL": 0.0}, "sharpe_ratio": -1.034, "portfolio_return": -0.865997, "portfolio_vol": 0.876242, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181128_0951", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "XRP-USD", "PALL", "INDS"], "decision_date": "2018-11-28", "context_summary": "4-asset optimization. Max-Sharpe: 2.337. Portfolio: return=34.83%, vol=13.19%. Weights: w_FXI=0.0000, w_XRP-USD=0.0000, w_PALL=0.5156, w_INDS=0.4844.", "question": "Assets: FXI, XRP-USD, PALL, INDS\nAnnualized mean returns: FXI:-0.2385, XRP-USD:-1.7464, PALL:0.4804, INDS:0.2077\nCovariance matrix (annualized):\n[[0.086974, 0.071083, 0.024845, -0.003536], [0.071083, 0.716494, 0.004411, 0.035688], [0.024845, 0.004411, 0.057726, -0.010117], [-0.003536, 0.035688, -0.010117, 0.030314]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_PALL=0.5156, w_INDS=0.4844", "answer_numeric": 2.3365746550180844, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_XRP-USD=0.0000, w_PALL=0.5156, w_INDS=0.4844\nPortfolio annualized return: 34.83%, volatility: 13.19%\nSharpe ratio: (0.3483 - 0.0400) / 0.1319 = 2.3366", "metadata": {"weights": {"FXI": 0.0, "XRP-USD": 0.0, "PALL": 0.5156, "INDS": 0.4844}, "sharpe_ratio": 2.3366, "portfolio_return": 0.348269, "portfolio_vol": 0.131932, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220630_0955", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "DBB", "IEF"], "decision_date": "2022-06-30", "context_summary": "4-asset optimization. Max-Sharpe: -0.453. Portfolio: return=-6.28%, vol=22.67%. Weights: w_XLV=1.0000, w_LINK-USD=0.0000, w_DBB=0.0000, w_IEF=0.0000.", "question": "Assets: XLV, LINK-USD, DBB, IEF\nAnnualized mean returns: XLV:-0.0628, LINK-USD:-3.8513, DBB:-1.1185, IEF:-0.0335\nCovariance matrix (annualized):\n[[0.05138, 0.128042, 0.029985, 0.006259], [0.128042, 1.436845, 0.079059, -0.006326], [0.029985, 0.079059, 0.064159, 0.004374], [0.006259, -0.006326, 0.004374, 0.010222]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_LINK-USD=0.0000, w_DBB=0.0000, w_IEF=0.0000", "answer_numeric": -0.4533535939210041, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=1.0000, w_LINK-USD=0.0000, w_DBB=0.0000, w_IEF=0.0000\nPortfolio annualized return: -6.28%, volatility: 22.67%\nSharpe ratio: (-0.0628 - 0.0400) / 0.2267 = -0.4534", "metadata": {"weights": {"XLV": 1.0, "LINK-USD": 0.0, "DBB": 0.0, "IEF": 0.0}, "sharpe_ratio": -0.4534, "portfolio_return": -0.062762, "portfolio_vol": 0.226672, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190822_0958", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "BNO", "SCHP"], "decision_date": "2019-08-22", "context_summary": "4-asset optimization. Max-Sharpe: 2.736. Portfolio: return=12.74%, vol=3.19%. Weights: w_MTUM=0.0493, w_LINK-USD=0.0079, w_BNO=0.0000, w_SCHP=0.9428.", "question": "Assets: MTUM, LINK-USD, BNO, SCHP\nAnnualized mean returns: MTUM:0.0549, LINK-USD:1.0795, BNO:-0.3136, SCHP:0.1232\nCovariance matrix (annualized):\n[[0.027224, -0.008193, 0.015071, -0.001169], [-0.008193, 1.217882, -0.021205, 0.003048], [0.015071, -0.021205, 0.09257, -0.004341], [-0.001169, 0.003048, -0.004341, 0.001065]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0493, w_LINK-USD=0.0079, w_BNO=0.0000, w_SCHP=0.9428", "answer_numeric": 2.7361306843564623, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0493, w_LINK-USD=0.0079, w_BNO=0.0000, w_SCHP=0.9428\nPortfolio annualized return: 12.74%, volatility: 3.19%\nSharpe ratio: (0.1274 - 0.0400) / 0.0319 = 2.7361", "metadata": {"weights": {"MTUM": 0.0493, "LINK-USD": 0.0079, "BNO": 0.0, "SCHP": 0.9428}, "sharpe_ratio": 2.7361, "portfolio_return": 0.127388, "portfolio_vol": 0.031938, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210129_0966", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "VCIT", "WEAT"], "decision_date": "2021-01-29", "context_summary": "4-asset optimization. Max-Sharpe: 3.414. Portfolio: return=49.66%, vol=13.37%. Weights: w_QQQ=0.6880, w_ADA-USD=0.0547, w_VCIT=0.0000, w_WEAT=0.2573.", "question": "Assets: QQQ, ADA-USD, VCIT, WEAT\nAnnualized mean returns: QQQ:0.4534, ADA-USD:1.9794, VCIT:-0.0044, WEAT:0.2972\nCovariance matrix (annualized):\n[[0.027201, -0.01423, 0.001003, -0.006767], [-0.01423, 1.775062, -0.000802, -0.043788], [0.001003, -0.000802, 0.000634, 0.001309], [-0.006767, -0.043788, 0.001309, 0.066539]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6880, w_ADA-USD=0.0547, w_VCIT=0.0000, w_WEAT=0.2573", "answer_numeric": 3.414227954853829, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.6880, w_ADA-USD=0.0547, w_VCIT=0.0000, w_WEAT=0.2573\nPortfolio annualized return: 49.66%, volatility: 13.37%\nSharpe ratio: (0.4966 - 0.0400) / 0.1337 = 3.4142", "metadata": {"weights": {"QQQ": 0.688, "ADA-USD": 0.0547, "VCIT": 0.0, "WEAT": 0.2573}, "sharpe_ratio": 3.4142, "portfolio_return": 0.496632, "portfolio_vol": 0.133744, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20170927_0968", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "BNDX", "XHB"], "decision_date": "2017-09-27", "context_summary": "4-asset optimization. Max-Sharpe: 3.351. Portfolio: return=32.89%, vol=8.62%. Weights: w_XLE=0.3790, w_BTC-USD=0.0925, w_BNDX=0.5107, w_XHB=0.0179.", "question": "Assets: XLE, BTC-USD, BNDX, XHB\nAnnualized mean returns: XLE:0.2329, BTC-USD:2.3515, BNDX:0.0416, XHB:0.1105\nCovariance matrix (annualized):\n[[0.012821, 0.003922, -0.000576, 0.002], [0.003922, 0.621975, 0.000516, 0.010984], [-0.000576, 0.000516, 0.000428, -0.000444], [0.002, 0.010984, -0.000444, 0.01493]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3790, w_BTC-USD=0.0925, w_BNDX=0.5107, w_XHB=0.0179", "answer_numeric": 3.351309494825939, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.3790, w_BTC-USD=0.0925, w_BNDX=0.5107, w_XHB=0.0179\nPortfolio annualized return: 32.89%, volatility: 8.62%\nSharpe ratio: (0.3289 - 0.0400) / 0.0862 = 3.3513", "metadata": {"weights": {"XLE": 0.379, "BTC-USD": 0.0925, "BNDX": 0.5107, "XHB": 0.0179}, "sharpe_ratio": 3.3513, "portfolio_return": 0.32893, "portfolio_vol": 0.086214, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210408_0971", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SOL-USD", "ICSH", "JNK"], "decision_date": "2021-04-08", "context_summary": "4-asset optimization. Max-Sharpe: 4.511. Portfolio: return=694.30%, vol=153.02%. Weights: w_^VIX=0.0000, w_SOL-USD=1.0000, w_ICSH=0.0000, w_JNK=0.0000.", "question": "Assets: ^VIX, SOL-USD, ICSH, JNK\nAnnualized mean returns: ^VIX:-1.5232, SOL-USD:6.9430, ICSH:0.0037, JNK:0.0281\nCovariance matrix (annualized):\n[[1.507714, -0.487888, -0.001451, -0.045977], [-0.487888, 2.341639, 0.001495, 0.030733], [-0.001451, 0.001495, 1.2e-05, 5e-05], [-0.045977, 0.030733, 5e-05, 0.002964]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_ICSH=0.0000, w_JNK=0.0000", "answer_numeric": 4.511080542219871, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_SOL-USD=1.0000, w_ICSH=0.0000, w_JNK=0.0000\nPortfolio annualized return: 694.30%, volatility: 153.02%\nSharpe ratio: (6.9430 - 0.0400) / 1.5302 = 4.5111", "metadata": {"weights": {"^VIX": 0.0, "SOL-USD": 1.0, "ICSH": 0.0, "JNK": 0.0}, "sharpe_ratio": 4.5111, "portfolio_return": 6.943042, "portfolio_vol": 1.530241, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221027_0973", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "DOT-USD", "REZ", "ICSH"], "decision_date": "2022-10-27", "context_summary": "4-asset optimization. Max-Sharpe: 0.252. Portfolio: return=16.97%, vol=51.49%. Weights: w_USMV=0.0000, w_DOT-USD=1.0000, w_REZ=0.0000, w_ICSH=0.0000.", "question": "Assets: USMV, DOT-USD, REZ, ICSH\nAnnualized mean returns: USMV:-0.2032, DOT-USD:0.1697, REZ:-1.0332, ICSH:0.0048\nCovariance matrix (annualized):\n[[0.041972, 0.040442, 0.043835, 0.000495], [0.040442, 0.26509, 0.041341, 0.001089], [0.043835, 0.041341, 0.074037, 0.000591], [0.000495, 0.001089, 0.000591, 2.6e-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_USMV=0.0000, w_DOT-USD=1.0000, w_REZ=0.0000, w_ICSH=0.0000", "answer_numeric": 0.25185903489667255, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_DOT-USD=1.0000, w_REZ=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 16.97%, volatility: 51.49%\nSharpe ratio: (0.1697 - 0.0400) / 0.5149 = 0.2519", "metadata": {"weights": {"USMV": 0.0, "DOT-USD": 1.0, "REZ": 0.0, "ICSH": 0.0}, "sharpe_ratio": 0.2519, "portfolio_return": 0.169674, "portfolio_vol": 0.514869, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210224_0979", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "TLT", "UNG"], "decision_date": "2021-02-24", "context_summary": "4-asset optimization. Max-Sharpe: 6.734. Portfolio: return=651.13%, vol=96.09%. Weights: w_XLB=0.1983, w_BNB-USD=0.5653, w_TLT=0.0000, w_UNG=0.2364.", "question": "Assets: XLB, BNB-USD, TLT, UNG\nAnnualized mean returns: XLB:0.3052, BNB-USD:10.9694, TLT:-0.6570, UNG:1.0549\nCovariance matrix (annualized):\n[[0.037659, 0.051258, -0.009361, 0.005895], [0.051258, 2.691392, 0.013436, 0.117589], [-0.009361, 0.013436, 0.011995, 0.009317], [0.005895, 0.117589, 0.009317, 0.326524]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1983, w_BNB-USD=0.5653, w_TLT=0.0000, w_UNG=0.2364", "answer_numeric": 6.734406382999369, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.1983, w_BNB-USD=0.5653, w_TLT=0.0000, w_UNG=0.2364\nPortfolio annualized return: 651.13%, volatility: 96.09%\nSharpe ratio: (6.5113 - 0.0400) / 0.9609 = 6.7344", "metadata": {"weights": {"XLB": 0.1983, "BNB-USD": 0.5653, "TLT": 0.0, "UNG": 0.2364}, "sharpe_ratio": 6.7344, "portfolio_return": 6.511336, "portfolio_vol": 0.960936, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20201218_0981", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "SCHH", "TLT"], "decision_date": "2020-12-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.562. Portfolio: return=88.97%, vol=18.63%. Weights: w_ACWI=0.8029, w_ETH-USD=0.1971, w_SCHH=0.0000, w_TLT=0.0000.", "question": "Assets: ACWI, ETH-USD, SCHH, TLT\nAnnualized mean returns: ACWI:0.5800, ETH-USD:2.1515, SCHH:0.3934, TLT:-0.1412\nCovariance matrix (annualized):\n[[0.02676, 0.002849, 0.025049, -0.00414], [0.002849, 0.425818, -0.014615, 0.004148], [0.025049, -0.014615, 0.039985, -0.010924], [-0.00414, 0.004148, -0.010924, 0.019487]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8029, w_ETH-USD=0.1971, w_SCHH=0.0000, w_TLT=0.0000", "answer_numeric": 4.5619261952967065, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.8029, w_ETH-USD=0.1971, w_SCHH=0.0000, w_TLT=0.0000\nPortfolio annualized return: 88.97%, volatility: 18.63%\nSharpe ratio: (0.8897 - 0.0400) / 0.1863 = 4.5619", "metadata": {"weights": {"ACWI": 0.8029, "ETH-USD": 0.1971, "SCHH": 0.0, "TLT": 0.0}, "sharpe_ratio": 4.5619, "portfolio_return": 0.88972, "portfolio_vol": 0.186263, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210414_0983", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "PDBC", "ITB"], "decision_date": "2021-04-14", "context_summary": "4-asset optimization. Max-Sharpe: 2.792. Portfolio: return=66.63%, vol=22.43%. Weights: w_ACWI=0.0000, w_BTC-USD=0.1907, w_PDBC=0.4663, w_ITB=0.3430.", "question": "Assets: ACWI, BTC-USD, PDBC, ITB\nAnnualized mean returns: ACWI:0.1346, BTC-USD:1.2922, PDBC:0.3758, ITB:0.7133\nCovariance matrix (annualized):\n[[0.02285, 0.047829, 0.008176, 0.032123], [0.047829, 0.435812, 0.004682, 0.044689], [0.008176, 0.004682, 0.048323, 0.010365], [0.032123, 0.044689, 0.010365, 0.118788]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.1907, w_PDBC=0.4663, w_ITB=0.3430", "answer_numeric": 2.7918541010697937, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_BTC-USD=0.1907, w_PDBC=0.4663, w_ITB=0.3430\nPortfolio annualized return: 66.63%, volatility: 22.43%\nSharpe ratio: (0.6663 - 0.0400) / 0.2243 = 2.7919", "metadata": {"weights": {"ACWI": 0.0, "BTC-USD": 0.1907, "PDBC": 0.4663, "ITB": 0.343}, "sharpe_ratio": 2.7919, "portfolio_return": 0.666318, "portfolio_vol": 0.224337, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210120_0984", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "CORN", "SGOV"], "decision_date": "2021-01-20", "context_summary": "4-asset optimization. Max-Sharpe: 5.579. Portfolio: return=94.19%, vol=16.17%. Weights: w_XLRE=0.0000, w_XRP-USD=0.0147, w_CORN=0.9853, w_SGOV=0.0000.", "question": "Assets: XLRE, XRP-USD, CORN, SGOV\nAnnualized mean returns: XLRE:-0.0672, XRP-USD:2.3689, CORN:0.9206, SGOV:0.0004\nCovariance matrix (annualized):\n[[0.028973, -0.006153, 5e-05, 3e-06], [-0.006153, 3.616786, 0.014431, 0.000442], [5e-05, 0.014431, 0.025682, 2.6e-05], [3e-06, 0.000442, 2.6e-05, 0.0]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_XRP-USD=0.0147, w_CORN=0.9853, w_SGOV=0.0000", "answer_numeric": 5.578930480068038, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_XRP-USD=0.0147, w_CORN=0.9853, w_SGOV=0.0000\nPortfolio annualized return: 94.19%, volatility: 16.17%\nSharpe ratio: (0.9419 - 0.0400) / 0.1617 = 5.5789", "metadata": {"weights": {"XLRE": 0.0, "XRP-USD": 0.0147, "CORN": 0.9853, "SGOV": 0.0}, "sharpe_ratio": 5.5789, "portfolio_return": 0.941894, "portfolio_vol": 0.161661, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210820_0985", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "SGOV", "BNDX"], "decision_date": "2021-08-20", "context_summary": "4-asset optimization. Max-Sharpe: 3.622. Portfolio: return=10.92%, vol=1.91%. Weights: w_EWJ=0.0137, w_BNB-USD=0.0074, w_SGOV=0.0000, w_BNDX=0.9789.", "question": "Assets: EWJ, BNB-USD, SGOV, BNDX\nAnnualized mean returns: EWJ:-0.0572, BNB-USD:1.0572, SGOV:0.0005, BNDX:0.1044\nCovariance matrix (annualized):\n[[0.01798, -0.004668, 1.6e-05, -0.00074], [-0.004668, 0.680476, -2.6e-05, 0.000415], [1.6e-05, -2.6e-05, 1e-06, -3e-06], [-0.00074, 0.000415, -3e-06, 0.000354]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0137, w_BNB-USD=0.0074, w_SGOV=0.0000, w_BNDX=0.9789", "answer_numeric": 3.6217651123209986, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0137, w_BNB-USD=0.0074, w_SGOV=0.0000, w_BNDX=0.9789\nPortfolio annualized return: 10.92%, volatility: 1.91%\nSharpe ratio: (0.1092 - 0.0400) / 0.0191 = 3.6218", "metadata": {"weights": {"EWJ": 0.0137, "BNB-USD": 0.0074, "SGOV": 0.0, "BNDX": 0.9789}, "sharpe_ratio": 3.6218, "portfolio_return": 0.109207, "portfolio_vol": 0.019109, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200610_0986", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "CPER", "BIL"], "decision_date": "2020-06-10", "context_summary": "4-asset optimization. Max-Sharpe: 4.643. Portfolio: return=129.77%, vol=27.09%. Weights: w_EEM=0.0986, w_ETH-USD=0.3514, w_CPER=0.5500, w_BIL=0.0000.", "question": "Assets: EEM, ETH-USD, CPER, BIL\nAnnualized mean returns: EEM:0.8698, ETH-USD:2.3093, CPER:0.7281, BIL:0.0009\nCovariance matrix (annualized):\n[[0.074832, 0.042286, 0.047594, 6.7e-05], [0.042286, 0.350169, 0.009426, -0.000254], [0.047594, 0.009426, 0.058433, 3.3e-05], [6.7e-05, -0.000254, 3.3e-05, 3e-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=0.0986, w_ETH-USD=0.3514, w_CPER=0.5500, w_BIL=0.0000", "answer_numeric": 4.642859909705452, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0986, w_ETH-USD=0.3514, w_CPER=0.5500, w_BIL=0.0000\nPortfolio annualized return: 129.77%, volatility: 27.09%\nSharpe ratio: (1.2977 - 0.0400) / 0.2709 = 4.6429", "metadata": {"weights": {"EEM": 0.0986, "ETH-USD": 0.3514, "CPER": 0.55, "BIL": 0.0}, "sharpe_ratio": 4.6429, "portfolio_return": 1.297663, "portfolio_vol": 0.270881, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181009_0987", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "DBB", "ICSH"], "decision_date": "2018-10-09", "context_summary": "4-asset optimization. Max-Sharpe: 1.784. Portfolio: return=15.87%, vol=6.65%. Weights: w_QUAL=1.0000, w_ETH-USD=0.0000, w_DBB=0.0000, w_ICSH=0.0000.", "question": "Assets: QUAL, ETH-USD, DBB, ICSH\nAnnualized mean returns: QUAL:0.1587, ETH-USD:-1.4509, DBB:0.0946, ICSH:0.0239\nCovariance matrix (annualized):\n[[0.004421, 0.025782, 0.006116, -2.1e-05], [0.025782, 0.87606, 0.026579, -0.000903], [0.006116, 0.026579, 0.042145, -6.3e-05], [-2.1e-05, -0.000903, -6.3e-05, 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_QUAL=1.0000, w_ETH-USD=0.0000, w_DBB=0.0000, w_ICSH=0.0000", "answer_numeric": 1.7844200508695856, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=1.0000, w_ETH-USD=0.0000, w_DBB=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 15.87%, volatility: 6.65%\nSharpe ratio: (0.1587 - 0.0400) / 0.0665 = 1.7844", "metadata": {"weights": {"QUAL": 1.0, "ETH-USD": 0.0, "DBB": 0.0, "ICSH": 0.0}, "sharpe_ratio": 1.7844, "portfolio_return": 0.158652, "portfolio_vol": 0.066493, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20180117_0988", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "ITB", "UNG"], "decision_date": "2018-01-17", "context_summary": "4-asset optimization. Max-Sharpe: 4.043. Portfolio: return=71.41%, vol=16.67%. Weights: w_XLU=0.0000, w_BTC-USD=0.0578, w_ITB=0.9422, w_UNG=0.0000.", "question": "Assets: XLU, BTC-USD, ITB, UNG\nAnnualized mean returns: XLU:-0.6476, BTC-USD:1.7048, ITB:0.6532, UNG:-0.1560\nCovariance matrix (annualized):\n[[0.011839, 0.003189, 0.003052, 0.009215], [0.003189, 1.167609, 0.0012, -0.147319], [0.003052, 0.0012, 0.026771, 0.016673], [0.009215, -0.147319, 0.016673, 0.22386]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0578, w_ITB=0.9422, w_UNG=0.0000", "answer_numeric": 4.042769237701019, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_BTC-USD=0.0578, w_ITB=0.9422, w_UNG=0.0000\nPortfolio annualized return: 71.41%, volatility: 16.67%\nSharpe ratio: (0.7141 - 0.0400) / 0.1667 = 4.0428", "metadata": {"weights": {"XLU": 0.0, "BTC-USD": 0.0578, "ITB": 0.9422, "UNG": 0.0}, "sharpe_ratio": 4.0428, "portfolio_return": 0.714065, "portfolio_vol": 0.166734, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210304_0989", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "DOT-USD", "BIL", "INDS"], "decision_date": "2021-03-04", "context_summary": "4-asset optimization. Max-Sharpe: 4.385. Portfolio: return=656.84%, vol=148.87%. Weights: w_XLK=0.0000, w_DOT-USD=1.0000, w_BIL=0.0000, w_INDS=0.0000.", "question": "Assets: XLK, DOT-USD, BIL, INDS\nAnnualized mean returns: XLK:-0.0284, DOT-USD:6.5684, BIL:-0.0007, INDS:-0.0473\nCovariance matrix (annualized):\n[[0.055467, 0.055565, -7.1e-05, 0.025867], [0.055565, 2.216275, 0.000157, 0.063283], [-7.1e-05, 0.000157, 2e-06, -4.8e-05], [0.025867, 0.063283, -4.8e-05, 0.03377]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_DOT-USD=1.0000, w_BIL=0.0000, w_INDS=0.0000", "answer_numeric": 4.385246462918919, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_DOT-USD=1.0000, w_BIL=0.0000, w_INDS=0.0000\nPortfolio annualized return: 656.84%, volatility: 148.87%\nSharpe ratio: (6.5684 - 0.0400) / 1.4887 = 4.3852", "metadata": {"weights": {"XLK": 0.0, "DOT-USD": 1.0, "BIL": 0.0, "INDS": 0.0}, "sharpe_ratio": 4.3852, "portfolio_return": 6.568387, "portfolio_vol": 1.488716, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210412_0990", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "LQD", "GLD"], "decision_date": "2021-04-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.004. Portfolio: return=67.01%, vol=31.44%. Weights: w_VTI=0.6142, w_BTC-USD=0.3858, w_LQD=0.0000, w_GLD=0.0000.", "question": "Assets: VTI, BTC-USD, LQD, GLD\nAnnualized mean returns: VTI:0.2672, BTC-USD:1.3114, LQD:-0.1809, GLD:-0.3411\nCovariance matrix (annualized):\n[[0.028126, 0.047606, 0.006153, 0.01111], [0.047606, 0.441074, 0.003856, 0.002126], [0.006153, 0.003856, 0.007523, 0.003577], [0.01111, 0.002126, 0.003577, 0.023519]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6142, w_BTC-USD=0.3858, w_LQD=0.0000, w_GLD=0.0000", "answer_numeric": 2.004338756269804, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.6142, w_BTC-USD=0.3858, w_LQD=0.0000, w_GLD=0.0000\nPortfolio annualized return: 67.01%, volatility: 31.44%\nSharpe ratio: (0.6701 - 0.0400) / 0.3144 = 2.0043", "metadata": {"weights": {"VTI": 0.6142, "BTC-USD": 0.3858, "LQD": 0.0, "GLD": 0.0}, "sharpe_ratio": 2.0043, "portfolio_return": 0.670085, "portfolio_vol": 0.314361, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20200429_0991", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "IEF", "XHB"], "decision_date": "2020-04-29", "context_summary": "4-asset optimization. Max-Sharpe: 5.256. Portfolio: return=90.87%, vol=16.53%. Weights: w_XLI=0.0000, w_LINK-USD=0.1294, w_IEF=0.8706, w_XHB=0.0000.", "question": "Assets: XLI, LINK-USD, IEF, XHB\nAnnualized mean returns: XLI:-0.3056, LINK-USD:5.3464, IEF:0.2490, XHB:0.3785\nCovariance matrix (annualized):\n[[0.173536, 0.190925, -0.021463, 0.216645], [0.190925, 1.394481, -0.015614, 0.314462], [-0.021463, -0.015614, 0.009872, -0.023777], [0.216645, 0.314462, -0.023777, 0.317565]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_LINK-USD=0.1294, w_IEF=0.8706, w_XHB=0.0000", "answer_numeric": 5.255836622243796, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_LINK-USD=0.1294, w_IEF=0.8706, w_XHB=0.0000\nPortfolio annualized return: 90.87%, volatility: 16.53%\nSharpe ratio: (0.9087 - 0.0400) / 0.1653 = 5.2558", "metadata": {"weights": {"XLI": 0.0, "LINK-USD": 0.1294, "IEF": 0.8706, "XHB": 0.0}, "sharpe_ratio": 5.2558, "portfolio_return": 0.908714, "portfolio_vol": 0.165286, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220331_0992", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "LINK-USD", "MORT", "ICSH"], "decision_date": "2022-03-31", "context_summary": "4-asset optimization. Max-Sharpe: 1.395. Portfolio: return=110.48%, vol=76.34%. Weights: w_QQQ=0.0163, w_LINK-USD=0.9837, w_MORT=0.0000, w_ICSH=0.0000.", "question": "Assets: QQQ, LINK-USD, MORT, ICSH\nAnnualized mean returns: QQQ:0.2490, LINK-USD:1.1190, MORT:-0.0074, ICSH:-0.0225\nCovariance matrix (annualized):\n[[0.108346, 0.114481, 0.04994, 0.000485], [0.114481, 0.598506, 0.046551, 0.000503], [0.04994, 0.046551, 0.042036, 0.000291], [0.000485, 0.000503, 0.000291, 3.7e-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_QQQ=0.0163, w_LINK-USD=0.9837, w_MORT=0.0000, w_ICSH=0.0000", "answer_numeric": 1.394749271592244, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0163, w_LINK-USD=0.9837, w_MORT=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 110.48%, volatility: 76.34%\nSharpe ratio: (1.1048 - 0.0400) / 0.7634 = 1.3947", "metadata": {"weights": {"QQQ": 0.0163, "LINK-USD": 0.9837, "MORT": 0.0, "ICSH": 0.0}, "sharpe_ratio": 1.3947, "portfolio_return": 1.104794, "portfolio_vol": 0.76343, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220610_0993", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "ICSH", "IYR"], "decision_date": "2022-06-10", "context_summary": "4-asset optimization. Max-Sharpe: -2.070. Portfolio: return=-41.39%, vol=21.93%. Weights: w_EFA=1.0000, w_AVAX-USD=0.0000, w_ICSH=0.0000, w_IYR=0.0000.", "question": "Assets: EFA, AVAX-USD, ICSH, IYR\nAnnualized mean returns: EFA:-0.4139, AVAX-USD:-7.1298, ICSH:0.0049, IYR:-0.7165\nCovariance matrix (annualized):\n[[0.048098, 0.123504, 0.000106, 0.045789], [0.123504, 1.218981, -0.000269, 0.097662], [0.000106, -0.000269, 3.5e-05, 0.000374], [0.045789, 0.097662, 0.000374, 0.066521]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_AVAX-USD=0.0000, w_ICSH=0.0000, w_IYR=0.0000", "answer_numeric": -2.0695905579971168, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=1.0000, w_AVAX-USD=0.0000, w_ICSH=0.0000, w_IYR=0.0000\nPortfolio annualized return: -41.39%, volatility: 21.93%\nSharpe ratio: (-0.4139 - 0.0400) / 0.2193 = -2.0696", "metadata": {"weights": {"EFA": 1.0, "AVAX-USD": 0.0, "ICSH": 0.0, "IYR": 0.0}, "sharpe_ratio": -2.0696, "portfolio_return": -0.413888, "portfolio_vol": 0.219313, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20220913_0994", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "BIL", "WEAT"], "decision_date": "2022-09-13", "context_summary": "4-asset optimization. Max-Sharpe: 1.666. Portfolio: return=48.89%, vol=26.94%. Weights: w_EWJ=0.1803, w_XRP-USD=0.1873, w_BIL=0.0000, w_WEAT=0.6324.", "question": "Assets: EWJ, XRP-USD, BIL, WEAT\nAnnualized mean returns: EWJ:0.0907, XRP-USD:0.4519, BIL:0.0179, WEAT:0.6134\nCovariance matrix (annualized):\n[[0.031834, 0.044501, 2.1e-05, -0.009306], [0.044501, 0.240296, 8.8e-05, 0.021424], [2.1e-05, 8.8e-05, 5e-06, -0.000251], [-0.009306, 0.021424, -0.000251, 0.142879]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1803, w_XRP-USD=0.1873, w_BIL=0.0000, w_WEAT=0.6324", "answer_numeric": 1.666401112084584, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.1803, w_XRP-USD=0.1873, w_BIL=0.0000, w_WEAT=0.6324\nPortfolio annualized return: 48.89%, volatility: 26.94%\nSharpe ratio: (0.4889 - 0.0400) / 0.2694 = 1.6664", "metadata": {"weights": {"EWJ": 0.1803, "XRP-USD": 0.1873, "BIL": 0.0, "WEAT": 0.6324}, "sharpe_ratio": 1.6664, "portfolio_return": 0.488869, "portfolio_vol": 0.269365, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20181114_0995", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "LINK-USD", "ICSH", "IEF"], "decision_date": "2018-11-14", "context_summary": "4-asset optimization. Max-Sharpe: 5.180. Portfolio: return=470.83%, vol=90.12%. Weights: w_IVV=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_IEF=0.0000.", "question": "Assets: IVV, LINK-USD, ICSH, IEF\nAnnualized mean returns: IVV:-0.3719, LINK-USD:4.7083, ICSH:0.0205, IEF:-0.0318\nCovariance matrix (annualized):\n[[0.035651, 0.047762, 2e-05, -0.003663], [0.047762, 0.812195, -6.6e-05, -0.007517], [2e-05, -6.6e-05, 1.3e-05, 1.8e-05], [-0.003663, -0.007517, 1.8e-05, 0.00173]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ICSH=0.0000, w_IEF=0.0000", "answer_numeric": 5.180024662253244, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_LINK-USD=1.0000, w_ICSH=0.0000, w_IEF=0.0000\nPortfolio annualized return: 470.83%, volatility: 90.12%\nSharpe ratio: (4.7083 - 0.0400) / 0.9012 = 5.1800", "metadata": {"weights": {"IVV": 0.0, "LINK-USD": 1.0, "ICSH": 0.0, "IEF": 0.0}, "sharpe_ratio": 5.18, "portfolio_return": 4.708334, "portfolio_vol": 0.901218, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20190425_0996", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "GLD", "LQD"], "decision_date": "2019-04-25", "context_summary": "4-asset optimization. Max-Sharpe: 5.846. Portfolio: return=19.55%, vol=2.66%. Weights: w_XLF=0.1648, w_XRP-USD=0.0057, w_GLD=0.0000, w_LQD=0.8295.", "question": "Assets: XLF, XRP-USD, GLD, LQD\nAnnualized mean returns: XLF:0.2400, XRP-USD:0.4199, GLD:-0.2409, LQD:0.1851\nCovariance matrix (annualized):\n[[0.021552, 0.003635, -0.004998, -0.003209], [0.003635, 0.299, 0.004595, -0.000694], [-0.004998, 0.004595, 0.00906, 0.001607], [-0.003209, -0.000694, 0.001607, 0.001438]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1648, w_XRP-USD=0.0057, w_GLD=0.0000, w_LQD=0.8295", "answer_numeric": 5.845739780238818, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.1648, w_XRP-USD=0.0057, w_GLD=0.0000, w_LQD=0.8295\nPortfolio annualized return: 19.55%, volatility: 2.66%\nSharpe ratio: (0.1955 - 0.0400) / 0.0266 = 5.8457", "metadata": {"weights": {"XLF": 0.1648, "XRP-USD": 0.0057, "GLD": 0.0, "LQD": 0.8295}, "sharpe_ratio": 5.8457, "portfolio_return": 0.19545, "portfolio_vol": 0.026592, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 2897}}
{"id": "T5_all_20200818_0997", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "XRP-USD", "SGOV", "SHY"], "decision_date": "2020-08-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.539. Portfolio: return=231.48%, vol=50.11%. Weights: w_XLE=0.0000, w_XRP-USD=1.0000, w_SGOV=0.0000, w_SHY=0.0000.", "question": "Assets: XLE, XRP-USD, SGOV, SHY\nAnnualized mean returns: XLE:-0.2882, XRP-USD:2.3148, SGOV:0.0011, SHY:0.0057\nCovariance matrix (annualized):\n[[0.118827, 0.01706, 1.1e-05, -0.000248], [0.01706, 0.251139, -2.3e-05, -0.000161], [1.1e-05, -2.3e-05, 0.0, 1e-06], [-0.000248, -0.000161, 1e-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_XLE=0.0000, w_XRP-USD=1.0000, w_SGOV=0.0000, w_SHY=0.0000", "answer_numeric": 4.539345188387302, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_XRP-USD=1.0000, w_SGOV=0.0000, w_SHY=0.0000\nPortfolio annualized return: 231.48%, volatility: 50.11%\nSharpe ratio: (2.3148 - 0.0400) / 0.5011 = 4.5393", "metadata": {"weights": {"XLE": 0.0, "XRP-USD": 1.0, "SGOV": 0.0, "SHY": 0.0}, "sharpe_ratio": 4.5393, "portfolio_return": 2.314838, "portfolio_vol": 0.501138, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20221228_0998", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "VNQ", "CSHI"], "decision_date": "2022-12-28", "context_summary": "4-asset optimization. Max-Sharpe: 3.186. Portfolio: return=71.63%, vol=21.23%. Weights: w_EEM=1.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_CSHI=0.0000.", "question": "Assets: EEM, BTC-USD, VNQ, CSHI\nAnnualized mean returns: EEM:0.7163, BTC-USD:-0.6555, VNQ:-0.1627, CSHI:0.0404\nCovariance matrix (annualized):\n[[0.045069, 0.063696, 0.026985, 0.000286], [0.063696, 0.347921, 0.060783, 0.00044], [0.026985, 0.060783, 0.044041, 0.000482], [0.000286, 0.00044, 0.000482, 4.8e-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=1.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_CSHI=0.0000", "answer_numeric": 3.1855050204069024, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=1.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_CSHI=0.0000\nPortfolio annualized return: 71.63%, volatility: 21.23%\nSharpe ratio: (0.7163 - 0.0400) / 0.2123 = 3.1855", "metadata": {"weights": {"EEM": 1.0, "BTC-USD": 0.0, "VNQ": 0.0, "CSHI": 0.0}, "sharpe_ratio": 3.1855, "portfolio_return": 0.716268, "portfolio_vol": 0.212295, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T5_all_20210303_0999", "template": "T5", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ADA-USD", "SGOV", "LQD"], "decision_date": "2021-03-03", "context_summary": "4-asset optimization. Max-Sharpe: 5.768. Portfolio: return=287.07%, vol=49.08%. Weights: w_XLF=0.7012, w_ADA-USD=0.2988, w_SGOV=0.0000, w_LQD=0.0000.", "question": "Assets: XLF, ADA-USD, SGOV, LQD\nAnnualized mean returns: XLF:0.7045, ADA-USD:7.9536, SGOV:0.0013, LQD:-0.2468\nCovariance matrix (annualized):\n[[0.051433, 0.068539, 1e-05, -0.001534], [0.068539, 2.092659, -1.6e-05, 0.011554], [1e-05, -1.6e-05, 0.0, 1.6e-05], [-0.001534, 0.011554, 1.6e-05, 0.005146]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7012, w_ADA-USD=0.2988, w_SGOV=0.0000, w_LQD=0.0000", "answer_numeric": 5.7677184913812125, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.7012, w_ADA-USD=0.2988, w_SGOV=0.0000, w_LQD=0.0000\nPortfolio annualized return: 287.07%, volatility: 49.08%\nSharpe ratio: (2.8707 - 0.0400) / 0.4908 = 5.7677", "metadata": {"weights": {"XLF": 0.7012, "ADA-USD": 0.2988, "SGOV": 0.0, "LQD": 0.0}, "sharpe_ratio": 5.7677, "portfolio_return": 2.870665, "portfolio_vol": 0.490777, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}}
{"id": "T6_all_20210218_0007", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "LINK-USD", "HAUZ", "SGOV"], "decision_date": "2021-02-18", "context_summary": "Max weight deviation: 0.0248, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2492, target=0.2500\n  LINK-USD: current=0.2401, target=0.2500\n  HAUZ: current=0.2359, target=0.2500\n  SGOV: current=0.2748, 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: 0.0248.\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": {"USMV": 0.2492, "LINK-USD": 0.2401, "HAUZ": 0.2359, "SGOV": 0.2748}, "target_weights": {"USMV": 0.25, "LINK-USD": 0.25, "HAUZ": 0.25, "SGOV": 0.25}, "max_deviation": 0.0248, "total_turnover": 0.049525, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0248}}
{"id": "T6_all_20180727_0014", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "SHY", "ITB"], "decision_date": "2018-07-27", "context_summary": "Max weight deviation: 0.0287, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2996, target=0.2500\n  LINK-USD: current=0.2620, target=0.2500\n  SHY: current=0.1850, target=0.2500\n  ITB: current=0.2534, 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 SHY", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0287.\nRebalancing threshold: 0.0500.\n0.0287 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0574, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2996, "LINK-USD": 0.262, "SHY": 0.185, "ITB": 0.2534}, "target_weights": {"XLRE": 0.25, "LINK-USD": 0.25, "SHY": 0.25, "ITB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.057428, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SHY", "primary_trade": -0.065}}
{"id": "T6_all_20211130_0021", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "ICSH", "DBA"], "decision_date": "2021-11-30", "context_summary": "Max weight deviation: 0.0201, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2299, target=0.2500\n  BTC-USD: current=0.2628, target=0.2500\n  ICSH: current=0.2511, target=0.2500\n  DBA: current=0.2561, 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: 0.0201.\nRebalancing threshold: 0.0500.\n0.0201 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0401, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2299, "BTC-USD": 0.2628, "ICSH": 0.2511, "DBA": 0.2561}, "target_weights": {"USMV": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "DBA": 0.25}, "max_deviation": 0.0201, "total_turnover": 0.040127, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": -0.0201}}
{"id": "T6_all_20221006_0023", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "CSHI", "IYR"], "decision_date": "2022-10-06", "context_summary": "Max weight deviation: 0.0125, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2620, target=0.2500\n  SOL-USD: current=0.2546, target=0.2500\n  CSHI: current=0.2375, target=0.2500\n  IYR: current=0.2459, 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: 0.0125.\nRebalancing threshold: 0.0500.\n0.0125 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0333, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.262, "SOL-USD": 0.2546, "CSHI": 0.2375, "IYR": 0.2459}, "target_weights": {"XLF": 0.25, "SOL-USD": 0.25, "CSHI": 0.25, "IYR": 0.25}, "max_deviation": 0.0125, "total_turnover": 0.033317, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CSHI", "primary_trade": -0.0125}}
{"id": "T6_all_20211029_0028", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "TLT", "USO"], "decision_date": "2021-10-29", "context_summary": "Max weight deviation: 0.0355, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.1850, target=0.2500\n  LINK-USD: current=0.2515, target=0.2500\n  TLT: current=0.2901, target=0.2500\n  USO: current=0.2734, 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: 0.0355.\nRebalancing threshold: 0.0500.\n0.0355 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0709, transaction cost = 0.000071 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.185, "LINK-USD": 0.2515, "TLT": 0.2901, "USO": 0.2734}, "target_weights": {"XLV": 0.25, "LINK-USD": 0.25, "TLT": 0.25, "USO": 0.25}, "max_deviation": 0.065, "total_turnover": 0.070936, "transaction_cost": 7.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLV", "primary_trade": -0.065}}
{"id": "T6_all_20201021_0062", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ETH-USD", "ICSH", "IAU"], "decision_date": "2020-10-21", "context_summary": "Max weight deviation: 0.0139, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2033, target=0.2500\n  ETH-USD: current=0.2010, target=0.2500\n  ICSH: current=0.3151, target=0.2500\n  IAU: current=0.2805, 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 ICSH", "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 = 0.0409, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2033, "ETH-USD": 0.201, "ICSH": 0.3151, "IAU": 0.2805}, "target_weights": {"VLUE": 0.25, "ETH-USD": 0.25, "ICSH": 0.25, "IAU": 0.25}, "max_deviation": 0.065147, "total_turnover": 0.04094, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": 0.0651}}
{"id": "T6_all_20211022_0065", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "EMB", "SGOV"], "decision_date": "2021-10-22", "context_summary": "Max weight deviation: 0.0546, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2407, target=0.2500\n  ADA-USD: current=0.2569, target=0.2500\n  EMB: current=0.2800, target=0.2500\n  SGOV: current=0.2225, 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: 0.0546.\nRebalancing threshold: 0.0500.\n0.0546 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1343, transaction cost = 0.000134 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2407, "ADA-USD": 0.2569, "EMB": 0.28, "SGOV": 0.2225}, "target_weights": {"MTUM": 0.25, "ADA-USD": 0.25, "EMB": 0.25, "SGOV": 0.25}, "max_deviation": 0.03, "total_turnover": 0.134259, "transaction_cost": 0.000134, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EMB", "primary_trade": 0.03}}
{"id": "T6_all_20160822_0074", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "PPLT", "HYG"], "decision_date": "2016-08-22", "context_summary": "Max weight deviation: 0.0235, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2539, target=0.2500\n  BTC-USD: current=0.3037, target=0.2500\n  PPLT: current=0.1850, target=0.2500\n  HYG: 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 PPLT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0235.\nRebalancing threshold: 0.0500.\n0.0235 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0470, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2539, "BTC-USD": 0.3037, "PPLT": 0.185, "HYG": 0.2575}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "PPLT": 0.25, "HYG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.047006, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "PPLT", "primary_trade": -0.065}}
{"id": "T6_all_20220707_0076", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "LQD", "SLV"], "decision_date": "2022-07-07", "context_summary": "Max weight deviation: 0.0376, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2097, target=0.2500\n  MATIC-USD: current=0.2362, target=0.2500\n  LQD: current=0.3150, target=0.2500\n  SLV: 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": "yes; sell 0.0650 of LQD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0376.\nRebalancing threshold: 0.0500.\n0.0376 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0752, transaction cost = 0.000075 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2097, "MATIC-USD": 0.2362, "LQD": 0.315, "SLV": 0.2391}, "target_weights": {"IVV": 0.25, "MATIC-USD": 0.25, "LQD": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.075237, "transaction_cost": 7.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LQD", "primary_trade": 0.065}}
{"id": "T6_all_20180829_0078", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "DBA", "ICSH"], "decision_date": "2018-08-29", "context_summary": "Max weight deviation: 0.0469, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.1850, target=0.2500\n  BTC-USD: current=0.2901, target=0.2500\n  DBA: current=0.2688, target=0.2500\n  ICSH: current=0.2561, 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 XLE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0469.\nRebalancing threshold: 0.0500.\n0.0469 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0938, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.185, "BTC-USD": 0.2901, "DBA": 0.2688, "ICSH": 0.2561}, "target_weights": {"XLE": 0.25, "BTC-USD": 0.25, "DBA": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.093844, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLE", "primary_trade": -0.065}}
{"id": "T6_all_20210914_0081", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "CPER", "VNQ"], "decision_date": "2021-09-14", "context_summary": "Max weight deviation: 0.0444, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2876, target=0.2500\n  ADA-USD: current=0.2412, target=0.2500\n  CPER: current=0.2056, target=0.2500\n  VNQ: current=0.2656, 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: 0.0444.\nRebalancing threshold: 0.0500.\n0.0444 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1064, transaction cost = 0.000106 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2876, "ADA-USD": 0.2412, "CPER": 0.2056, "VNQ": 0.2656}, "target_weights": {"^VIX": 0.25, "ADA-USD": 0.25, "CPER": 0.25, "VNQ": 0.25}, "max_deviation": 0.0444, "total_turnover": 0.106386, "transaction_cost": 0.000106, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CPER", "primary_trade": -0.0444}}
{"id": "T6_all_20160816_0086", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "BIL", "JNK"], "decision_date": "2016-08-16", "context_summary": "Max weight deviation: 0.0246, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2323, target=0.2500\n  BTC-USD: current=0.2133, target=0.2500\n  BIL: current=0.3150, target=0.2500\n  JNK: current=0.2394, 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: 0.0246.\nRebalancing threshold: 0.0500.\n0.0246 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0493, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2323, "BTC-USD": 0.2133, "BIL": 0.315, "JNK": 0.2394}, "target_weights": {"FXI": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "JNK": 0.25}, "max_deviation": 0.065, "total_turnover": 0.049297, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.065}}
{"id": "T6_all_20191203_0089", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ETH-USD", "UNG", "BIL"], "decision_date": "2019-12-03", "context_summary": "Max weight deviation: 0.0315, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2626, target=0.2500\n  ETH-USD: current=0.2552, target=0.2500\n  UNG: current=0.2637, target=0.2500\n  BIL: current=0.2185, 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: 0.0315.\nRebalancing threshold: 0.0500.\n0.0315 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0631, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2626, "ETH-USD": 0.2552, "UNG": 0.2637, "BIL": 0.2185}, "target_weights": {"IWM": 0.25, "ETH-USD": 0.25, "UNG": 0.25, "BIL": 0.25}, "max_deviation": 0.0315, "total_turnover": 0.063091, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.0315}}
{"id": "T6_all_20190826_0095", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "HYG", "REZ"], "decision_date": "2019-08-26", "context_summary": "Max weight deviation: 0.0147, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2466, target=0.2500\n  ADA-USD: current=0.2480, target=0.2500\n  HYG: current=0.2647, target=0.2500\n  REZ: current=0.2408, 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: 0.0147.\nRebalancing threshold: 0.0500.\n0.0147 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0295, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2466, "ADA-USD": 0.248, "HYG": 0.2647, "REZ": 0.2408}, "target_weights": {"QQQ": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "REZ": 0.25}, "max_deviation": 0.0147, "total_turnover": 0.02946, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": 0.0147}}
{"id": "T6_all_20211015_0103", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ETH-USD", "PPLT", "SGOV"], "decision_date": "2021-10-15", "context_summary": "Max weight deviation: 0.0233, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2267, target=0.2500\n  ETH-USD: current=0.2581, target=0.2500\n  PPLT: current=0.2487, target=0.2500\n  SGOV: current=0.2666, 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: 0.0233.\nRebalancing threshold: 0.0500.\n0.0233 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0493, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2267, "ETH-USD": 0.2581, "PPLT": 0.2487, "SGOV": 0.2666}, "target_weights": {"XLK": 0.25, "ETH-USD": 0.25, "PPLT": 0.25, "SGOV": 0.25}, "max_deviation": 0.0233, "total_turnover": 0.049284, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": -0.0233}}
{"id": "T6_all_20190117_0119", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "XRP-USD", "BIL", "IGOV"], "decision_date": "2019-01-17", "context_summary": "Max weight deviation: 0.0270, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2590, target=0.2500\n  XRP-USD: current=0.2712, target=0.2500\n  BIL: current=0.2469, target=0.2500\n  IGOV: current=0.2230, 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 = 0.0603, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.259, "XRP-USD": 0.2712, "BIL": 0.2469, "IGOV": 0.223}, "target_weights": {"EFA": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "IGOV": 0.25}, "max_deviation": 0.027, "total_turnover": 0.060276, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IGOV", "primary_trade": -0.027}}
{"id": "T6_all_20190201_0135", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XRP-USD", "CORN", "REZ"], "decision_date": "2019-02-01", "context_summary": "Max weight deviation: 0.0085, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2475, target=0.2500\n  XRP-USD: current=0.2415, target=0.2500\n  CORN: current=0.2570, target=0.2500\n  REZ: current=0.2541, 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: 0.0085.\nRebalancing threshold: 0.0500.\n0.0085 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0221, transaction cost = 0.000022 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2475, "XRP-USD": 0.2415, "CORN": 0.257, "REZ": 0.2541}, "target_weights": {"XLF": 0.25, "XRP-USD": 0.25, "CORN": 0.25, "REZ": 0.25}, "max_deviation": 0.0085, "total_turnover": 0.022076, "transaction_cost": 2.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.0085}}
{"id": "T6_all_20220114_0139", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "AVAX-USD", "JNK", "UNG"], "decision_date": "2022-01-14", "context_summary": "Max weight deviation: 0.0228, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2361, target=0.2500\n  AVAX-USD: current=0.2728, target=0.2500\n  JNK: current=0.2468, target=0.2500\n  UNG: current=0.2443, 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: 0.0228.\nRebalancing threshold: 0.0500.\n0.0228 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0456, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2361, "AVAX-USD": 0.2728, "JNK": 0.2468, "UNG": 0.2443}, "target_weights": {"IVV": 0.25, "AVAX-USD": 0.25, "JNK": 0.25, "UNG": 0.25}, "max_deviation": 0.0228, "total_turnover": 0.045644, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": 0.0228}}
{"id": "T6_all_20221202_0146", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "WEAT", "LQD"], "decision_date": "2022-12-02", "context_summary": "Max weight deviation: 0.0386, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.1850, target=0.2500\n  LINK-USD: current=0.2119, target=0.2500\n  WEAT: current=0.3076, target=0.2500\n  LQD: current=0.2955, 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 XLE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0386.\nRebalancing threshold: 0.0500.\n0.0386 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1223, transaction cost = 0.000122 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.185, "LINK-USD": 0.2119, "WEAT": 0.3076, "LQD": 0.2955}, "target_weights": {"XLE": 0.25, "LINK-USD": 0.25, "WEAT": 0.25, "LQD": 0.25}, "max_deviation": 0.065, "total_turnover": 0.122347, "transaction_cost": 0.000122, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLE", "primary_trade": -0.065}}
{"id": "T6_all_20210420_0148", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BTC-USD", "TIP", "IYR"], "decision_date": "2021-04-20", "context_summary": "Max weight deviation: 0.0255, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2393, target=0.2500\n  BTC-USD: current=0.2653, target=0.2500\n  TIP: current=0.1850, target=0.2500\n  IYR: current=0.3104, 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: 0.0255.\nRebalancing threshold: 0.0500.\n0.0255 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0594, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2393, "BTC-USD": 0.2653, "TIP": 0.185, "IYR": 0.3104}, "target_weights": {"XLI": 0.25, "BTC-USD": 0.25, "TIP": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059405, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "TIP", "primary_trade": -0.065}}
{"id": "T6_all_20210430_0151", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "VNQI", "BNDX"], "decision_date": "2021-04-30", "context_summary": "Max weight deviation: 0.0155, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2632, target=0.2500\n  ADA-USD: current=0.2560, target=0.2500\n  VNQI: current=0.2345, target=0.2500\n  BNDX: 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: 0.0155.\nRebalancing threshold: 0.0500.\n0.0155 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0385, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2632, "ADA-USD": 0.256, "VNQI": 0.2345, "BNDX": 0.2462}, "target_weights": {"EWJ": 0.25, "ADA-USD": 0.25, "VNQI": 0.25, "BNDX": 0.25}, "max_deviation": 0.0155, "total_turnover": 0.038505, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VNQI", "primary_trade": -0.0155}}
{"id": "T6_all_20221124_0155", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "AVAX-USD", "CSHI", "HYG"], "decision_date": "2022-11-24", "context_summary": "Max weight deviation: 0.0223, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2330, target=0.2500\n  AVAX-USD: current=0.2694, target=0.2500\n  CSHI: current=0.2277, target=0.2500\n  HYG: current=0.2699, 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: 0.0223.\nRebalancing threshold: 0.0500.\n0.0223 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0786, transaction cost = 0.000079 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.233, "AVAX-USD": 0.2694, "CSHI": 0.2277, "HYG": 0.2699}, "target_weights": {"IVV": 0.25, "AVAX-USD": 0.25, "CSHI": 0.25, "HYG": 0.25}, "max_deviation": 0.0223, "total_turnover": 0.078611, "transaction_cost": 7.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CSHI", "primary_trade": -0.0223}}
{"id": "T6_all_20221107_0158", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "AVAX-USD", "IAU", "XHB"], "decision_date": "2022-11-07", "context_summary": "Max weight deviation: 0.0238, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2495, target=0.2500\n  AVAX-USD: current=0.2396, target=0.2500\n  IAU: current=0.1959, target=0.2500\n  XHB: 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 XHB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0238.\nRebalancing threshold: 0.0500.\n0.0238 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0477, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2495, "AVAX-USD": 0.2396, "IAU": 0.1959, "XHB": 0.315}, "target_weights": {"FXI": 0.25, "AVAX-USD": 0.25, "IAU": 0.25, "XHB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.047666, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XHB", "primary_trade": 0.065}}
{"id": "T6_all_20220628_0162", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BNB-USD", "IGOV", "BIL"], "decision_date": "2022-06-28", "context_summary": "Max weight deviation: 0.0398, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.2362, target=0.2500\n  BNB-USD: current=0.2799, target=0.2500\n  IGOV: current=0.2989, target=0.2500\n  BIL: 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 BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0398.\nRebalancing threshold: 0.0500.\n0.0398 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0965, transaction cost = 0.000096 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2362, "BNB-USD": 0.2799, "IGOV": 0.2989, "BIL": 0.185}, "target_weights": {"XLV": 0.25, "BNB-USD": 0.25, "IGOV": 0.25, "BIL": 0.25}, "max_deviation": 0.06497, "total_turnover": 0.096473, "transaction_cost": 9.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.065}}
{"id": "T6_all_20201027_0165", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "AVAX-USD", "INDS", "DBB"], "decision_date": "2020-10-27", "context_summary": "Max weight deviation: 0.0251, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2427, target=0.2500\n  AVAX-USD: current=0.2613, target=0.2500\n  INDS: current=0.2711, target=0.2500\n  DBB: current=0.2249, 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 = 0.0649, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2427, "AVAX-USD": 0.2613, "INDS": 0.2711, "DBB": 0.2249}, "target_weights": {"QUAL": 0.25, "AVAX-USD": 0.25, "INDS": 0.25, "DBB": 0.25}, "max_deviation": 0.0251, "total_turnover": 0.064901, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": -0.0251}}
{"id": "T6_all_20190809_0177", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BNB-USD", "BIL", "INDS"], "decision_date": "2019-08-09", "context_summary": "Max weight deviation: 0.0352, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2506, target=0.2500\n  BNB-USD: current=0.2617, target=0.2500\n  BIL: current=0.2148, target=0.2500\n  INDS: current=0.2729, 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: 0.0352.\nRebalancing threshold: 0.0500.\n0.0352 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0705, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2506, "BNB-USD": 0.2617, "BIL": 0.2148, "INDS": 0.2729}, "target_weights": {"USMV": 0.25, "BNB-USD": 0.25, "BIL": 0.25, "INDS": 0.25}, "max_deviation": 0.0352, "total_turnover": 0.07045, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.0352}}
{"id": "T6_all_20200128_0182", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "MORT", "CPER"], "decision_date": "2020-01-28", "context_summary": "Max weight deviation: 0.0313, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.1850, target=0.2500\n  LINK-USD: current=0.2458, target=0.2500\n  MORT: current=0.2793, target=0.2500\n  CPER: current=0.2899, 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: 0.0313.\nRebalancing threshold: 0.0500.\n0.0313 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0666, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.185, "LINK-USD": 0.2458, "MORT": 0.2793, "CPER": 0.2899}, "target_weights": {"EWJ": 0.25, "LINK-USD": 0.25, "MORT": 0.25, "CPER": 0.25}, "max_deviation": 0.065, "total_turnover": 0.06659, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EWJ", "primary_trade": -0.065}}
{"id": "T6_all_20180914_0198", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "REZ", "PDBC"], "decision_date": "2018-09-14", "context_summary": "Max weight deviation: 0.0254, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2618, target=0.2500\n  BTC-USD: current=0.2278, target=0.2500\n  REZ: current=0.3151, target=0.2500\n  PDBC: current=0.1953, 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 REZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0254.\nRebalancing threshold: 0.0500.\n0.0254 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0601, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2618, "BTC-USD": 0.2278, "REZ": 0.3151, "PDBC": 0.1953}, "target_weights": {"XLE": 0.25, "BTC-USD": 0.25, "REZ": 0.25, "PDBC": 0.25}, "max_deviation": 0.065081, "total_turnover": 0.060132, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "REZ", "primary_trade": 0.0651}}
{"id": "T6_all_20220425_0199", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BNB-USD", "WEAT", "TLT"], "decision_date": "2022-04-25", "context_summary": "Max weight deviation: 0.0164, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2515, target=0.2500\n  BNB-USD: current=0.2336, target=0.2500\n  WEAT: current=0.2632, target=0.2500\n  TLT: current=0.2517, 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: 0.0164.\nRebalancing threshold: 0.0500.\n0.0164 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0329, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2515, "BNB-USD": 0.2336, "WEAT": 0.2632, "TLT": 0.2517}, "target_weights": {"XLU": 0.25, "BNB-USD": 0.25, "WEAT": 0.25, "TLT": 0.25}, "max_deviation": 0.0164, "total_turnover": 0.03289, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": -0.0164}}
{"id": "T6_all_20160318_0202", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "BIL", "GLD"], "decision_date": "2016-03-18", "context_summary": "Max weight deviation: 0.0406, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.3149, target=0.2500\n  BTC-USD: current=0.2378, target=0.2500\n  BIL: current=0.1986, target=0.2500\n  GLD: current=0.2487, 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 EFA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0406.\nRebalancing threshold: 0.0500.\n0.0406 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0811, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.3149, "BTC-USD": 0.2378, "BIL": 0.1986, "GLD": 0.2487}, "target_weights": {"EFA": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "GLD": 0.25}, "max_deviation": 0.06495, "total_turnover": 0.081117, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EFA", "primary_trade": 0.0649}}
{"id": "T6_all_20200206_0205", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "SLV", "TLT"], "decision_date": "2020-02-06", "context_summary": "Max weight deviation: 0.0362, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2416, target=0.2500\n  ADA-USD: current=0.2862, target=0.2500\n  SLV: current=0.2358, target=0.2500\n  TLT: current=0.2364, 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 = 0.0724, transaction cost = 0.000072 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2416, "ADA-USD": 0.2862, "SLV": 0.2358, "TLT": 0.2364}, "target_weights": {"MTUM": 0.25, "ADA-USD": 0.25, "SLV": 0.25, "TLT": 0.25}, "max_deviation": 0.0362, "total_turnover": 0.072391, "transaction_cost": 7.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.0362}}
{"id": "T6_all_20220810_0209", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "SGOV", "DBB"], "decision_date": "2022-08-10", "context_summary": "Max weight deviation: 0.0465, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2340, target=0.2500\n  DOT-USD: current=0.2035, target=0.2500\n  SGOV: current=0.2678, target=0.2500\n  DBB: current=0.2947, 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: 0.0465.\nRebalancing threshold: 0.0500.\n0.0465 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1250, transaction cost = 0.000125 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.234, "DOT-USD": 0.2035, "SGOV": 0.2678, "DBB": 0.2947}, "target_weights": {"XLE": 0.25, "DOT-USD": 0.25, "SGOV": 0.25, "DBB": 0.25}, "max_deviation": 0.0465, "total_turnover": 0.124967, "transaction_cost": 0.000125, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DOT-USD", "primary_trade": -0.0465}}
{"id": "T6_all_20200311_0214", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BNB-USD", "SOYB", "BIL"], "decision_date": "2020-03-11", "context_summary": "Max weight deviation: 0.0101, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.1901, target=0.2500\n  BNB-USD: current=0.3066, target=0.2500\n  SOYB: current=0.1882, target=0.2500\n  BIL: 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 BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0101.\nRebalancing threshold: 0.0500.\n0.0101 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0377, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.1901, "BNB-USD": 0.3066, "SOYB": 0.1882, "BIL": 0.315}, "target_weights": {"XLU": 0.25, "BNB-USD": 0.25, "SOYB": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037706, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.065}}
{"id": "T6_all_20150312_0222", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "IGOV", "SLV"], "decision_date": "2015-03-12", "context_summary": "Max weight deviation: 0.0300, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2130, target=0.2500\n  BTC-USD: current=0.2465, target=0.2500\n  IGOV: current=0.3150, target=0.2500\n  SLV: current=0.2255, 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 IGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0300.\nRebalancing threshold: 0.0500.\n0.0300 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0600, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.213, "BTC-USD": 0.2465, "IGOV": 0.315, "SLV": 0.2255}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "IGOV": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059979, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IGOV", "primary_trade": 0.065}}
{"id": "T6_all_20201020_0225", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "ITB", "TIP"], "decision_date": "2020-10-20", "context_summary": "Max weight deviation: 0.0162, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2631, target=0.2500\n  LINK-USD: current=0.2338, target=0.2500\n  ITB: current=0.2560, target=0.2500\n  TIP: current=0.2471, 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 = 0.0382, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2631, "LINK-USD": 0.2338, "ITB": 0.256, "TIP": 0.2471}, "target_weights": {"EWJ": 0.25, "LINK-USD": 0.25, "ITB": 0.25, "TIP": 0.25}, "max_deviation": 0.0162, "total_turnover": 0.038246, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.0162}}
{"id": "T6_all_20220930_0231", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BTC-USD", "SGOV", "ITB"], "decision_date": "2022-09-30", "context_summary": "Max weight deviation: 0.0385, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2242, target=0.2500\n  BTC-USD: current=0.2885, target=0.2500\n  SGOV: current=0.2444, target=0.2500\n  ITB: current=0.2428, 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 = 0.0771, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2242, "BTC-USD": 0.2885, "SGOV": 0.2444, "ITB": 0.2428}, "target_weights": {"XLK": 0.25, "BTC-USD": 0.25, "SGOV": 0.25, "ITB": 0.25}, "max_deviation": 0.0385, "total_turnover": 0.077087, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.0385}}
{"id": "T6_all_20190920_0238", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ETH-USD", "LQD", "SLV"], "decision_date": "2019-09-20", "context_summary": "Max weight deviation: 0.0120, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.1850, target=0.2500\n  ETH-USD: current=0.2484, target=0.2500\n  LQD: current=0.2516, 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; buy 0.0650 of XLI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0120.\nRebalancing threshold: 0.0500.\n0.0120 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0246, transaction cost = 0.000025 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.185, "ETH-USD": 0.2484, "LQD": 0.2516, "SLV": 0.315}, "target_weights": {"XLI": 0.25, "ETH-USD": 0.25, "LQD": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.024615, "transaction_cost": 2.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLI", "primary_trade": -0.065}}
{"id": "T6_all_20190902_0241", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ADA-USD", "BIL", "PDBC"], "decision_date": "2019-09-02", "context_summary": "Max weight deviation: 0.0181, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2406, target=0.2500\n  ADA-USD: current=0.2391, target=0.2500\n  BIL: current=0.2522, target=0.2500\n  PDBC: current=0.2681, 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: 0.0181.\nRebalancing threshold: 0.0500.\n0.0181 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0406, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2406, "ADA-USD": 0.2391, "BIL": 0.2522, "PDBC": 0.2681}, "target_weights": {"XLF": 0.25, "ADA-USD": 0.25, "BIL": 0.25, "PDBC": 0.25}, "max_deviation": 0.0181, "total_turnover": 0.04061, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "PDBC", "primary_trade": 0.0181}}
{"id": "T6_all_20200828_0243", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "VNQ", "SCHP"], "decision_date": "2020-08-28", "context_summary": "Max weight deviation: 0.0241, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.2440, target=0.2500\n  BTC-USD: current=0.2741, target=0.2500\n  VNQ: current=0.2486, target=0.2500\n  SCHP: current=0.2333, 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: 0.0241.\nRebalancing threshold: 0.0500.\n0.0241 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0482, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.244, "BTC-USD": 0.2741, "VNQ": 0.2486, "SCHP": 0.2333}, "target_weights": {"XLV": 0.25, "BTC-USD": 0.25, "VNQ": 0.25, "SCHP": 0.25}, "max_deviation": 0.0241, "total_turnover": 0.048182, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.0241}}
{"id": "T6_all_20160824_0246", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "VCIT", "BNO"], "decision_date": "2016-08-24", "context_summary": "Max weight deviation: 0.0160, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.1915, target=0.2500\n  BTC-USD: current=0.2338, target=0.2500\n  VCIT: current=0.2598, target=0.2500\n  BNO: 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 BNO", "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 = 0.0367, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.1915, "BTC-USD": 0.2338, "VCIT": 0.2598, "BNO": 0.315}, "target_weights": {"XLU": 0.25, "BTC-USD": 0.25, "VCIT": 0.25, "BNO": 0.25}, "max_deviation": 0.065, "total_turnover": 0.036731, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": 0.065}}
{"id": "T6_all_20210729_0250", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "SOL-USD", "PDBC", "VCIT"], "decision_date": "2021-07-29", "context_summary": "Max weight deviation: 0.0062, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.3077, target=0.2500\n  SOL-USD: current=0.2311, target=0.2500\n  PDBC: current=0.2762, target=0.2500\n  VCIT: 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 VCIT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0062.\nRebalancing threshold: 0.0500.\n0.0062 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0161, transaction cost = 0.000016 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.3077, "SOL-USD": 0.2311, "PDBC": 0.2762, "VCIT": 0.185}, "target_weights": {"XLE": 0.25, "SOL-USD": 0.25, "PDBC": 0.25, "VCIT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.01607, "transaction_cost": 1.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VCIT", "primary_trade": -0.065}}
{"id": "T6_all_20191011_0253", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "STIP", "PDBC"], "decision_date": "2019-10-11", "context_summary": "Max weight deviation: 0.0262, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2361, target=0.2500\n  LINK-USD: current=0.2316, target=0.2500\n  STIP: current=0.2561, target=0.2500\n  PDBC: current=0.2762, 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: 0.0262.\nRebalancing threshold: 0.0500.\n0.0262 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0647, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2361, "LINK-USD": 0.2316, "STIP": 0.2561, "PDBC": 0.2762}, "target_weights": {"XLB": 0.25, "LINK-USD": 0.25, "STIP": 0.25, "PDBC": 0.25}, "max_deviation": 0.0262, "total_turnover": 0.064681, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "PDBC", "primary_trade": 0.0262}}
{"id": "T6_all_20191202_0259", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "JNK", "ICSH"], "decision_date": "2019-12-02", "context_summary": "Max weight deviation: 0.0259, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2293, target=0.2500\n  ETH-USD: current=0.2759, target=0.2500\n  JNK: current=0.2582, target=0.2500\n  ICSH: current=0.2366, 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: 0.0259.\nRebalancing threshold: 0.0500.\n0.0259 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0682, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2293, "ETH-USD": 0.2759, "JNK": 0.2582, "ICSH": 0.2366}, "target_weights": {"EEM": 0.25, "ETH-USD": 0.25, "JNK": 0.25, "ICSH": 0.25}, "max_deviation": 0.0259, "total_turnover": 0.068235, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.0259}}
{"id": "T6_all_20220720_0260", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "VNQI", "USO"], "decision_date": "2022-07-20", "context_summary": "Max weight deviation: 0.0236, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.1905, target=0.2500\n  DOT-USD: current=0.2456, target=0.2500\n  VNQI: current=0.2489, target=0.2500\n  USO: 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 USO", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0236.\nRebalancing threshold: 0.0500.\n0.0236 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0472, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.1905, "DOT-USD": 0.2456, "VNQI": 0.2489, "USO": 0.315}, "target_weights": {"XLI": 0.25, "DOT-USD": 0.25, "VNQI": 0.25, "USO": 0.25}, "max_deviation": 0.065, "total_turnover": 0.047235, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "USO", "primary_trade": 0.065}}
{"id": "T6_all_20200306_0265", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "PPLT", "STIP"], "decision_date": "2020-03-06", "context_summary": "Max weight deviation: 0.0201, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2486, target=0.2500\n  ETH-USD: current=0.2301, target=0.2500\n  PPLT: current=0.2512, target=0.2500\n  STIP: current=0.2701, 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: 0.0201.\nRebalancing threshold: 0.0500.\n0.0201 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0426, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2486, "ETH-USD": 0.2301, "PPLT": 0.2512, "STIP": 0.2701}, "target_weights": {"XLU": 0.25, "ETH-USD": 0.25, "PPLT": 0.25, "STIP": 0.25}, "max_deviation": 0.0201, "total_turnover": 0.042587, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "STIP", "primary_trade": 0.0201}}
{"id": "T6_all_20200409_0266", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "PDBC", "STIP"], "decision_date": "2020-04-09", "context_summary": "Max weight deviation: 0.0216, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.3149, target=0.2500\n  XRP-USD: current=0.2797, target=0.2500\n  PDBC: current=0.2009, target=0.2500\n  STIP: current=0.2045, 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 USMV", "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 = 0.0630, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.3149, "XRP-USD": 0.2797, "PDBC": 0.2009, "STIP": 0.2045}, "target_weights": {"USMV": 0.25, "XRP-USD": 0.25, "PDBC": 0.25, "STIP": 0.25}, "max_deviation": 0.064905, "total_turnover": 0.062956, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": 0.0649}}
{"id": "T6_all_20180130_0281", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ETH-USD", "ITB", "VCIT"], "decision_date": "2018-01-30", "context_summary": "Max weight deviation: 0.0137, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2560, target=0.2500\n  ETH-USD: current=0.2363, target=0.2500\n  ITB: current=0.2549, target=0.2500\n  VCIT: 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: 0.0137.\nRebalancing threshold: 0.0500.\n0.0137 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0273, transaction cost = 0.000027 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.256, "ETH-USD": 0.2363, "ITB": 0.2549, "VCIT": 0.2527}, "target_weights": {"EWJ": 0.25, "ETH-USD": 0.25, "ITB": 0.25, "VCIT": 0.25}, "max_deviation": 0.0137, "total_turnover": 0.027342, "transaction_cost": 2.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0137}}
{"id": "T6_all_20190606_0286", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "SHY", "PPLT"], "decision_date": "2019-06-06", "context_summary": "Max weight deviation: 0.0276, 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=0.2385, target=0.2500\n  SHY: current=0.2865, target=0.2500\n  PPLT: current=0.2900, 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: 0.0276.\nRebalancing threshold: 0.0500.\n0.0276 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0650, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.185, "XRP-USD": 0.2385, "SHY": 0.2865, "PPLT": 0.29}, "target_weights": {"XLRE": 0.25, "XRP-USD": 0.25, "SHY": 0.25, "PPLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.064999, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": -0.065}}
{"id": "T6_all_20220328_0290", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "DOT-USD", "HYG", "DBB"], "decision_date": "2022-03-28", "context_summary": "Max weight deviation: 0.0278, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2930, target=0.2500\n  DOT-USD: current=0.1850, target=0.2500\n  HYG: current=0.2100, target=0.2500\n  DBB: current=0.3120, 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 DOT-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0278.\nRebalancing threshold: 0.0500.\n0.0278 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0899, transaction cost = 0.000090 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.293, "DOT-USD": 0.185, "HYG": 0.21, "DBB": 0.312}, "target_weights": {"IVV": 0.25, "DOT-USD": 0.25, "HYG": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.089874, "transaction_cost": 9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DOT-USD", "primary_trade": -0.065}}
{"id": "T6_all_20210720_0292", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "AVAX-USD", "REZ", "IGOV"], "decision_date": "2021-07-20", "context_summary": "Max weight deviation: 0.0265, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2907, target=0.2500\n  AVAX-USD: current=0.1850, target=0.2500\n  REZ: current=0.2669, target=0.2500\n  IGOV: current=0.2574, 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: 0.0265.\nRebalancing threshold: 0.0500.\n0.0265 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0529, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2907, "AVAX-USD": 0.185, "REZ": 0.2669, "IGOV": 0.2574}, "target_weights": {"VTI": 0.25, "AVAX-USD": 0.25, "REZ": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.05294, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": -0.065}}
{"id": "T6_all_20210215_0294", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ETH-USD", "MORT", "SHV"], "decision_date": "2021-02-15", "context_summary": "Max weight deviation: 0.0188, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.3149, target=0.2500\n  ETH-USD: current=0.1908, target=0.2500\n  MORT: current=0.2751, target=0.2500\n  SHV: current=0.2192, 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 VLUE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0188.\nRebalancing threshold: 0.0500.\n0.0188 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0520, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.3149, "ETH-USD": 0.1908, "MORT": 0.2751, "SHV": 0.2192}, "target_weights": {"VLUE": 0.25, "ETH-USD": 0.25, "MORT": 0.25, "SHV": 0.25}, "max_deviation": 0.064891, "total_turnover": 0.052039, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VLUE", "primary_trade": 0.0649}}
{"id": "T6_all_20220607_0301", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "PDBC", "IEF"], "decision_date": "2022-06-07", "context_summary": "Max weight deviation: 0.0165, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.2335, target=0.2500\n  ADA-USD: current=0.2507, target=0.2500\n  PDBC: current=0.2556, target=0.2500\n  IEF: current=0.2602, 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: 0.0165.\nRebalancing threshold: 0.0500.\n0.0165 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0330, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2335, "ADA-USD": 0.2507, "PDBC": 0.2556, "IEF": 0.2602}, "target_weights": {"XLP": 0.25, "ADA-USD": 0.25, "PDBC": 0.25, "IEF": 0.25}, "max_deviation": 0.0165, "total_turnover": 0.033003, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLP", "primary_trade": -0.0165}}
{"id": "T6_all_20220902_0303", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "SLV", "TLH"], "decision_date": "2022-09-02", "context_summary": "Max weight deviation: 0.0383, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2883, target=0.2500\n  MATIC-USD: current=0.2216, target=0.2500\n  SLV: current=0.2395, target=0.2500\n  TLH: current=0.2507, 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: 0.0383.\nRebalancing threshold: 0.0500.\n0.0383 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0780, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2883, "MATIC-USD": 0.2216, "SLV": 0.2395, "TLH": 0.2507}, "target_weights": {"IVV": 0.25, "MATIC-USD": 0.25, "SLV": 0.25, "TLH": 0.25}, "max_deviation": 0.0383, "total_turnover": 0.077951, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IVV", "primary_trade": 0.0383}}
{"id": "T6_all_20210817_0306", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "AVAX-USD", "REZ", "BIL"], "decision_date": "2021-08-17", "context_summary": "Max weight deviation: 0.0293, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2489, target=0.2500\n  AVAX-USD: current=0.1850, target=0.2500\n  REZ: current=0.2986, target=0.2500\n  BIL: current=0.2675, 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: 0.0293.\nRebalancing threshold: 0.0500.\n0.0293 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0595, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2489, "AVAX-USD": 0.185, "REZ": 0.2986, "BIL": 0.2675}, "target_weights": {"MTUM": 0.25, "AVAX-USD": 0.25, "REZ": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059526, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": -0.065}}
{"id": "T6_all_20201002_0310", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "IGOV", "GLD"], "decision_date": "2020-10-02", "context_summary": "Max weight deviation: 0.0244, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.3046, target=0.2500\n  XRP-USD: current=0.1850, target=0.2500\n  IGOV: current=0.2814, target=0.2500\n  GLD: 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": "yes; buy 0.0650 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0244.\nRebalancing threshold: 0.0500.\n0.0244 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0646, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.3046, "XRP-USD": 0.185, "IGOV": 0.2814, "GLD": 0.229}, "target_weights": {"XLP": 0.25, "XRP-USD": 0.25, "IGOV": 0.25, "GLD": 0.25}, "max_deviation": 0.065, "total_turnover": 0.064602, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.065}}
{"id": "T6_all_20220412_0312", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "REZ", "SGOV"], "decision_date": "2022-04-12", "context_summary": "Max weight deviation: 0.0596, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2370, target=0.2500\n  BTC-USD: current=0.2258, target=0.2500\n  REZ: current=0.2275, target=0.2500\n  SGOV: current=0.3096, 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 0.0596 of SGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0596.\nRebalancing threshold: 0.0500.\n0.0596 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1193, transaction cost = 0.000119 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.237, "BTC-USD": 0.2258, "REZ": 0.2275, "SGOV": 0.3096}, "target_weights": {"VLUE": 0.25, "BTC-USD": 0.25, "REZ": 0.25, "SGOV": 0.25}, "max_deviation": 0.0596, "total_turnover": 0.11926, "transaction_cost": 0.000119, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0596}}
{"id": "T6_all_20211101_0314", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "SGOV", "REZ"], "decision_date": "2021-11-01", "context_summary": "Max weight deviation: 0.0168, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.3146, target=0.2500\n  BNB-USD: current=0.2341, target=0.2500\n  SGOV: current=0.1850, target=0.2500\n  REZ: 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": "yes; buy 0.0650 of SGOV", "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 = 0.0418, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.3146, "BNB-USD": 0.2341, "SGOV": 0.185, "REZ": 0.2662}, "target_weights": {"EEM": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "REZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.041813, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "SGOV", "primary_trade": -0.065}}
{"id": "T6_all_20200916_0317", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ETH-USD", "IAU", "MORT"], "decision_date": "2020-09-16", "context_summary": "Max weight deviation: 0.0336, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2534, target=0.2500\n  ETH-USD: current=0.2698, target=0.2500\n  IAU: current=0.2603, target=0.2500\n  MORT: current=0.2164, 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: 0.0336.\nRebalancing threshold: 0.0500.\n0.0336 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0672, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2534, "ETH-USD": 0.2698, "IAU": 0.2603, "MORT": 0.2164}, "target_weights": {"XLF": 0.25, "ETH-USD": 0.25, "IAU": 0.25, "MORT": 0.25}, "max_deviation": 0.0336, "total_turnover": 0.067199, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MORT", "primary_trade": -0.0336}}
{"id": "T6_all_20201113_0322", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ADA-USD", "SCHH", "ICSH"], "decision_date": "2020-11-13", "context_summary": "Max weight deviation: 0.0370, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.3150, target=0.2500\n  ADA-USD: current=0.2807, target=0.2500\n  SCHH: current=0.2122, target=0.2500\n  ICSH: current=0.1920, 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 VTI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0370.\nRebalancing threshold: 0.0500.\n0.0370 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1090, transaction cost = 0.000109 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.315, "ADA-USD": 0.2807, "SCHH": 0.2122, "ICSH": 0.192}, "target_weights": {"VTI": 0.25, "ADA-USD": 0.25, "SCHH": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.108979, "transaction_cost": 0.000109, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VTI", "primary_trade": 0.065}}
{"id": "T6_all_20200630_0325", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD", "ICSH", "REZ"], "decision_date": "2020-06-30", "context_summary": "Max weight deviation: 0.0100, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2425, target=0.2500\n  LINK-USD: current=0.2402, target=0.2500\n  ICSH: current=0.2573, target=0.2500\n  REZ: current=0.2600, 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 = 0.0347, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2425, "LINK-USD": 0.2402, "ICSH": 0.2573, "REZ": 0.26}, "target_weights": {"EFA": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "REZ": 0.25}, "max_deviation": 0.01, "total_turnover": 0.034697, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "REZ", "primary_trade": 0.01}}
{"id": "T6_all_20190114_0327", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ETH-USD", "CPER", "ICSH"], "decision_date": "2019-01-14", "context_summary": "Max weight deviation: 0.0490, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2086, target=0.2500\n  ETH-USD: current=0.2990, target=0.2500\n  CPER: current=0.2573, target=0.2500\n  ICSH: 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: 0.0490.\nRebalancing threshold: 0.0500.\n0.0490 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1126, transaction cost = 0.000113 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2086, "ETH-USD": 0.299, "CPER": 0.2573, "ICSH": 0.2352}, "target_weights": {"EFA": 0.25, "ETH-USD": 0.25, "CPER": 0.25, "ICSH": 0.25}, "max_deviation": 0.049, "total_turnover": 0.112587, "transaction_cost": 0.000113, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.049}}
{"id": "T6_all_20210104_0329", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "XRP-USD", "ITB", "TIP"], "decision_date": "2021-01-04", "context_summary": "Max weight deviation: 0.0199, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2406, target=0.2500\n  XRP-USD: current=0.2512, target=0.2500\n  ITB: current=0.2699, target=0.2500\n  TIP: 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: 0.0199.\nRebalancing threshold: 0.0500.\n0.0199 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0422, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2406, "XRP-USD": 0.2512, "ITB": 0.2699, "TIP": 0.2383}, "target_weights": {"IWM": 0.25, "XRP-USD": 0.25, "ITB": 0.25, "TIP": 0.25}, "max_deviation": 0.0199, "total_turnover": 0.042168, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": 0.0199}}
{"id": "T6_all_20150506_0335", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD", "DBA", "VNQI"], "decision_date": "2015-05-06", "context_summary": "Max weight deviation: 0.0119, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2435, target=0.2500\n  BTC-USD: current=0.2476, target=0.2500\n  DBA: current=0.2470, target=0.2500\n  VNQI: current=0.2619, 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 = 0.0238, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2435, "BTC-USD": 0.2476, "DBA": 0.247, "VNQI": 0.2619}, "target_weights": {"QUAL": 0.25, "BTC-USD": 0.25, "DBA": 0.25, "VNQI": 0.25}, "max_deviation": 0.0119, "total_turnover": 0.023755, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VNQI", "primary_trade": 0.0119}}
{"id": "T6_all_20200310_0336", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "EMB", "SLV"], "decision_date": "2020-03-10", "context_summary": "Max weight deviation: 0.0153, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2296, target=0.2500\n  BTC-USD: current=0.2814, target=0.2500\n  EMB: current=0.1850, target=0.2500\n  SLV: current=0.3040, 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 EMB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0153.\nRebalancing threshold: 0.0500.\n0.0153 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0402, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2296, "BTC-USD": 0.2814, "EMB": 0.185, "SLV": 0.304}, "target_weights": {"^VIX": 0.25, "BTC-USD": 0.25, "EMB": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.040247, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EMB", "primary_trade": -0.065}}
{"id": "T6_all_20191127_0338", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "TLH", "SLV"], "decision_date": "2019-11-27", "context_summary": "Max weight deviation: 0.0266, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.3013, target=0.2500\n  ETH-USD: current=0.1850, target=0.2500\n  TLH: current=0.2564, target=0.2500\n  SLV: 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; buy 0.0650 of ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0266.\nRebalancing threshold: 0.0500.\n0.0266 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0532, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.3013, "ETH-USD": 0.185, "TLH": 0.2564, "SLV": 0.2573}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "TLH": 0.25, "SLV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.053211, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.065}}
{"id": "T6_all_20220729_0343", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "SOL-USD", "DBB", "EMB"], "decision_date": "2022-07-29", "context_summary": "Max weight deviation: 0.0183, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2552, target=0.2500\n  SOL-USD: current=0.2317, target=0.2500\n  DBB: current=0.2637, target=0.2500\n  EMB: current=0.2493, 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 = 0.0379, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2552, "SOL-USD": 0.2317, "DBB": 0.2637, "EMB": 0.2493}, "target_weights": {"QQQ": 0.25, "SOL-USD": 0.25, "DBB": 0.25, "EMB": 0.25}, "max_deviation": 0.0183, "total_turnover": 0.037859, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "SOL-USD", "primary_trade": -0.0183}}
{"id": "T6_all_20201130_0355", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XRP-USD", "MORT", "PDBC"], "decision_date": "2020-11-30", "context_summary": "Max weight deviation: 0.0408, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2092, target=0.2500\n  XRP-USD: current=0.2762, target=0.2500\n  MORT: current=0.2756, target=0.2500\n  PDBC: current=0.2390, 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: 0.0408.\nRebalancing threshold: 0.0500.\n0.0408 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1035, transaction cost = 0.000104 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2092, "XRP-USD": 0.2762, "MORT": 0.2756, "PDBC": 0.239}, "target_weights": {"MTUM": 0.25, "XRP-USD": 0.25, "MORT": 0.25, "PDBC": 0.25}, "max_deviation": 0.0408, "total_turnover": 0.103535, "transaction_cost": 0.000104, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MTUM", "primary_trade": -0.0408}}
{"id": "T6_all_20210924_0357", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BNB-USD", "SOYB", "SGOV"], "decision_date": "2021-09-24", "context_summary": "Max weight deviation: 0.0107, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2436, target=0.2500\n  BNB-USD: current=0.2607, target=0.2500\n  SOYB: current=0.2484, target=0.2500\n  SGOV: current=0.2474, 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: 0.0107.\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": {"XLY": 0.2436, "BNB-USD": 0.2607, "SOYB": 0.2484, "SGOV": 0.2474}, "target_weights": {"XLY": 0.25, "BNB-USD": 0.25, "SOYB": 0.25, "SGOV": 0.25}, "max_deviation": 0.0107, "total_turnover": 0.021381, "transaction_cost": 2.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.0107}}
{"id": "T6_all_20190912_0358", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "IGOV", "DBA"], "decision_date": "2019-09-12", "context_summary": "Max weight deviation: 0.0244, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2021, target=0.2500\n  BTC-USD: current=0.2469, target=0.2500\n  IGOV: current=0.3151, target=0.2500\n  DBA: current=0.2359, 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 IGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0244.\nRebalancing threshold: 0.0500.\n0.0244 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0489, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2021, "BTC-USD": 0.2469, "IGOV": 0.3151, "DBA": 0.2359}, "target_weights": {"FXI": 0.25, "BTC-USD": 0.25, "IGOV": 0.25, "DBA": 0.25}, "max_deviation": 0.065084, "total_turnover": 0.048859, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IGOV", "primary_trade": 0.0651}}
{"id": "T6_all_20220531_0361", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "BIL", "INDS"], "decision_date": "2022-05-31", "context_summary": "Max weight deviation: 0.0413, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2913, target=0.2500\n  BTC-USD: current=0.2420, target=0.2500\n  BIL: current=0.2380, target=0.2500\n  INDS: current=0.2287, 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: 0.0413.\nRebalancing threshold: 0.0500.\n0.0413 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0825, transaction cost = 0.000083 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2913, "BTC-USD": 0.242, "BIL": 0.238, "INDS": 0.2287}, "target_weights": {"XLU": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "INDS": 0.25}, "max_deviation": 0.0413, "total_turnover": 0.082535, "transaction_cost": 8.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLU", "primary_trade": 0.0413}}
{"id": "T6_all_20220215_0366", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "SCHP", "DBC"], "decision_date": "2022-02-15", "context_summary": "Max weight deviation: 0.0241, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.1904, target=0.2500\n  LINK-USD: current=0.2074, target=0.2500\n  SCHP: current=0.3150, target=0.2500\n  DBC: current=0.2872, 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: 0.0241.\nRebalancing threshold: 0.0500.\n0.0241 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0758, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.1904, "LINK-USD": 0.2074, "SCHP": 0.315, "DBC": 0.2872}, "target_weights": {"XLV": 0.25, "LINK-USD": 0.25, "SCHP": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.075787, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": 0.065}}
{"id": "T6_all_20220606_0371", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "HAUZ", "ICSH"], "decision_date": "2022-06-06", "context_summary": "Max weight deviation: 0.0072, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2554, target=0.2500\n  LINK-USD: current=0.2428, target=0.2500\n  HAUZ: current=0.2560, target=0.2500\n  ICSH: current=0.2459, 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: 0.0072.\nRebalancing threshold: 0.0500.\n0.0072 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0227, transaction cost = 0.000023 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2554, "LINK-USD": 0.2428, "HAUZ": 0.256, "ICSH": 0.2459}, "target_weights": {"XLRE": 0.25, "LINK-USD": 0.25, "HAUZ": 0.25, "ICSH": 0.25}, "max_deviation": 0.0072, "total_turnover": 0.022654, "transaction_cost": 2.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.0072}}
{"id": "T6_all_20181106_0374", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "BNO", "BNDX"], "decision_date": "2018-11-06", "context_summary": "Max weight deviation: 0.0144, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2993, target=0.2500\n  BTC-USD: current=0.1851, target=0.2500\n  BNO: current=0.2560, target=0.2500\n  BNDX: 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": "yes; buy 0.0649 of BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0144.\nRebalancing threshold: 0.0500.\n0.0144 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0287, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2993, "BTC-USD": 0.1851, "BNO": 0.256, "BNDX": 0.2596}, "target_weights": {"XLU": 0.25, "BTC-USD": 0.25, "BNO": 0.25, "BNDX": 0.25}, "max_deviation": 0.064916, "total_turnover": 0.028705, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.0649}}
{"id": "T6_all_20210112_0381", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "SGOV", "HYG"], "decision_date": "2021-01-12", "context_summary": "Max weight deviation: 0.0187, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2577, target=0.2500\n  BTC-USD: current=0.2654, target=0.2500\n  SGOV: current=0.2457, target=0.2500\n  HYG: current=0.2313, 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: 0.0187.\nRebalancing threshold: 0.0500.\n0.0187 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0461, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2577, "BTC-USD": 0.2654, "SGOV": 0.2457, "HYG": 0.2313}, "target_weights": {"ACWI": 0.25, "BTC-USD": 0.25, "SGOV": 0.25, "HYG": 0.25}, "max_deviation": 0.0187, "total_turnover": 0.046066, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": -0.0187}}
{"id": "T6_all_20180214_0383", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "LQD", "ITB"], "decision_date": "2018-02-14", "context_summary": "Max weight deviation: 0.0076, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2526, target=0.2500\n  BTC-USD: current=0.2568, target=0.2500\n  LQD: current=0.2483, target=0.2500\n  ITB: current=0.2424, 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: 0.0076.\nRebalancing threshold: 0.0500.\n0.0076 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0187, transaction cost = 0.000019 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2526, "BTC-USD": 0.2568, "LQD": 0.2483, "ITB": 0.2424}, "target_weights": {"XLE": 0.25, "BTC-USD": 0.25, "LQD": 0.25, "ITB": 0.25}, "max_deviation": 0.0076, "total_turnover": 0.018691, "transaction_cost": 1.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": -0.0076}}
{"id": "T6_all_20191216_0388", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "PALL", "REZ"], "decision_date": "2019-12-16", "context_summary": "Max weight deviation: 0.0586, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2797, target=0.2500\n  XRP-USD: current=0.1914, target=0.2500\n  PALL: current=0.2497, target=0.2500\n  REZ: 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": "yes; buy 0.0586 of XRP-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0586.\nRebalancing threshold: 0.0500.\n0.0586 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1178, transaction cost = 0.000118 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2797, "XRP-USD": 0.1914, "PALL": 0.2497, "REZ": 0.2792}, "target_weights": {"VLUE": 0.25, "XRP-USD": 0.25, "PALL": 0.25, "REZ": 0.25}, "max_deviation": 0.0586, "total_turnover": 0.117813, "transaction_cost": 0.000118, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.0586}}
{"id": "T6_all_20210726_0390", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SOL-USD", "INDS", "PDBC"], "decision_date": "2021-07-26", "context_summary": "Max weight deviation: 0.0116, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2366, target=0.2500\n  SOL-USD: current=0.3150, target=0.2500\n  INDS: current=0.2248, target=0.2500\n  PDBC: current=0.2237, 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: 0.0116.\nRebalancing threshold: 0.0500.\n0.0116 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0232, transaction cost = 0.000023 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2366, "SOL-USD": 0.315, "INDS": 0.2248, "PDBC": 0.2237}, "target_weights": {"EFA": 0.25, "SOL-USD": 0.25, "INDS": 0.25, "PDBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.023239, "transaction_cost": 2.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": 0.065}}
{"id": "T6_all_20221209_0393", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BNB-USD", "SGOV", "IAU"], "decision_date": "2022-12-09", "context_summary": "Max weight deviation: 0.0057, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2557, target=0.2500\n  BNB-USD: current=0.2476, target=0.2500\n  SGOV: current=0.2455, target=0.2500\n  IAU: current=0.2512, 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: 0.0057.\nRebalancing threshold: 0.0500.\n0.0057 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0137, transaction cost = 0.000014 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2557, "BNB-USD": 0.2476, "SGOV": 0.2455, "IAU": 0.2512}, "target_weights": {"IWM": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "IAU": 0.25}, "max_deviation": 0.0057, "total_turnover": 0.013736, "transaction_cost": 1.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IWM", "primary_trade": 0.0057}}
{"id": "T6_all_20210813_0396", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "SGOV", "SCHH"], "decision_date": "2021-08-13", "context_summary": "Max weight deviation: 0.0203, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.1949, target=0.2500\n  BNB-USD: current=0.3150, target=0.2500\n  SGOV: current=0.2958, target=0.2500\n  SCHH: current=0.1943, 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: 0.0203.\nRebalancing threshold: 0.0500.\n0.0203 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0692, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.1949, "BNB-USD": 0.315, "SGOV": 0.2958, "SCHH": 0.1943}, "target_weights": {"EEM": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "SCHH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.069242, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.065}}
{"id": "T6_all_20220912_0398", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "SGOV", "HAUZ"], "decision_date": "2022-09-12", "context_summary": "Max weight deviation: 0.0279, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2221, target=0.2500\n  DOT-USD: current=0.2564, target=0.2500\n  SGOV: current=0.2065, target=0.2500\n  HAUZ: 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 HAUZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0279.\nRebalancing threshold: 0.0500.\n0.0279 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0613, transaction cost = 0.000061 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2221, "DOT-USD": 0.2564, "SGOV": 0.2065, "HAUZ": 0.3151}, "target_weights": {"XLE": 0.25, "DOT-USD": 0.25, "SGOV": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065073, "total_turnover": 0.061321, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HAUZ", "primary_trade": 0.0651}}
{"id": "T6_all_20220426_0405", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "GLD", "VNQ"], "decision_date": "2022-04-26", "context_summary": "Max weight deviation: 0.0206, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2294, target=0.2500\n  BTC-USD: current=0.2503, target=0.2500\n  GLD: current=0.2613, target=0.2500\n  VNQ: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0206.\nRebalancing threshold: 0.0500.\n0.0206 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0412, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2294, "BTC-USD": 0.2503, "GLD": 0.2613, "VNQ": 0.259}, "target_weights": {"^VIX": 0.25, "BTC-USD": 0.25, "GLD": 0.25, "VNQ": 0.25}, "max_deviation": 0.0206, "total_turnover": 0.041208, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": -0.0206}}
{"id": "T6_all_20200803_0408", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LINK-USD", "REZ", "DBA"], "decision_date": "2020-08-03", "context_summary": "Max weight deviation: 0.0098, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2551, target=0.2500\n  LINK-USD: current=0.2737, target=0.2500\n  REZ: current=0.2863, target=0.2500\n  DBA: 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 DBA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0098.\nRebalancing threshold: 0.0500.\n0.0098 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0196, transaction cost = 0.000020 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2551, "LINK-USD": 0.2737, "REZ": 0.2863, "DBA": 0.1849}, "target_weights": {"XLF": 0.25, "LINK-USD": 0.25, "REZ": 0.25, "DBA": 0.25}, "max_deviation": 0.065123, "total_turnover": 0.01959, "transaction_cost": 2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBA", "primary_trade": -0.0651}}
{"id": "T6_all_20220106_0410", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "MATIC-USD", "MORT", "WEAT"], "decision_date": "2022-01-06", "context_summary": "Max weight deviation: 0.0149, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2779, target=0.2500\n  MATIC-USD: current=0.1850, target=0.2500\n  MORT: current=0.2640, target=0.2500\n  WEAT: current=0.2731, 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 MATIC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0149.\nRebalancing threshold: 0.0500.\n0.0149 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0297, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2779, "MATIC-USD": 0.185, "MORT": 0.264, "WEAT": 0.2731}, "target_weights": {"EWJ": 0.25, "MATIC-USD": 0.25, "MORT": 0.25, "WEAT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.029728, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": -0.065}}
{"id": "T6_all_20190318_0414", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ADA-USD", "TIP", "BIL"], "decision_date": "2019-03-18", "context_summary": "Max weight deviation: 0.0136, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2720, target=0.2500\n  ADA-USD: current=0.3150, target=0.2500\n  TIP: current=0.2165, target=0.2500\n  BIL: current=0.1965, 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 ADA-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0136.\nRebalancing threshold: 0.0500.\n0.0136 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0364, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.272, "ADA-USD": 0.315, "TIP": 0.2165, "BIL": 0.1965}, "target_weights": {"EEM": 0.25, "ADA-USD": 0.25, "TIP": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.03637, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.065}}
{"id": "T6_all_20180116_0416", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "EMB", "REZ"], "decision_date": "2018-01-16", "context_summary": "Max weight deviation: 0.0351, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2116, target=0.2500\n  LINK-USD: current=0.2624, target=0.2500\n  EMB: current=0.3149, target=0.2500\n  REZ: current=0.2111, 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 EMB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0351.\nRebalancing threshold: 0.0500.\n0.0351 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0835, transaction cost = 0.000084 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2116, "LINK-USD": 0.2624, "EMB": 0.3149, "REZ": 0.2111}, "target_weights": {"XLU": 0.25, "LINK-USD": 0.25, "EMB": 0.25, "REZ": 0.25}, "max_deviation": 0.064942, "total_turnover": 0.083503, "transaction_cost": 8.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EMB", "primary_trade": 0.0649}}
{"id": "T6_all_20201127_0418", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "AVAX-USD", "VCIT", "WEAT"], "decision_date": "2020-11-27", "context_summary": "Max weight deviation: 0.0096, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2568, target=0.2500\n  AVAX-USD: current=0.2906, target=0.2500\n  VCIT: current=0.1850, target=0.2500\n  WEAT: 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; buy 0.0650 of VCIT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0096.\nRebalancing threshold: 0.0500.\n0.0096 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0191, transaction cost = 0.000019 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2568, "AVAX-USD": 0.2906, "VCIT": 0.185, "WEAT": 0.2676}, "target_weights": {"XLF": 0.25, "AVAX-USD": 0.25, "VCIT": 0.25, "WEAT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.01911, "transaction_cost": 1.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VCIT", "primary_trade": -0.065}}
{"id": "T6_all_20180720_0419", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BNB-USD", "STIP", "INDS"], "decision_date": "2018-07-20", "context_summary": "Max weight deviation: 0.0256, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2297, target=0.2500\n  BNB-USD: current=0.2645, target=0.2500\n  STIP: current=0.2756, target=0.2500\n  INDS: current=0.2303, 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 = 0.0801, transaction cost = 0.000080 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2297, "BNB-USD": 0.2645, "STIP": 0.2756, "INDS": 0.2303}, "target_weights": {"IWM": 0.25, "BNB-USD": 0.25, "STIP": 0.25, "INDS": 0.25}, "max_deviation": 0.0256, "total_turnover": 0.080066, "transaction_cost": 8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "STIP", "primary_trade": 0.0256}}
{"id": "T6_all_20221207_0423", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "XRP-USD", "DBB", "IYR"], "decision_date": "2022-12-07", "context_summary": "Max weight deviation: 0.0116, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2571, target=0.2500\n  XRP-USD: current=0.2467, target=0.2500\n  DBB: current=0.2384, target=0.2500\n  IYR: current=0.2577, 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: 0.0116.\nRebalancing threshold: 0.0500.\n0.0116 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0297, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2571, "XRP-USD": 0.2467, "DBB": 0.2384, "IYR": 0.2577}, "target_weights": {"EEM": 0.25, "XRP-USD": 0.25, "DBB": 0.25, "IYR": 0.25}, "max_deviation": 0.0116, "total_turnover": 0.029671, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": -0.0116}}
{"id": "T6_all_20210607_0428", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "BIL", "IGOV"], "decision_date": "2021-06-07", "context_summary": "Max weight deviation: 0.0471, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2667, target=0.2500\n  XRP-USD: current=0.2372, target=0.2500\n  BIL: current=0.3111, 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: 0.0471.\nRebalancing threshold: 0.0500.\n0.0471 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1127, transaction cost = 0.000113 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2667, "XRP-USD": 0.2372, "BIL": 0.3111, "IGOV": 0.185}, "target_weights": {"USMV": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.112698, "transaction_cost": 0.000113, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IGOV", "primary_trade": -0.065}}
{"id": "T6_all_20190101_0431", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "HAUZ", "SOYB"], "decision_date": "2019-01-01", "context_summary": "Max weight deviation: 0.0202, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2298, target=0.2500\n  BNB-USD: current=0.2504, target=0.2500\n  HAUZ: current=0.2543, target=0.2500\n  SOYB: current=0.2656, 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 = 0.0404, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2298, "BNB-USD": 0.2504, "HAUZ": 0.2543, "SOYB": 0.2656}, "target_weights": {"XLB": 0.25, "BNB-USD": 0.25, "HAUZ": 0.25, "SOYB": 0.25}, "max_deviation": 0.0202, "total_turnover": 0.040435, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLB", "primary_trade": -0.0202}}
{"id": "T6_all_20200703_0437", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "MATIC-USD", "VNQ", "BIL"], "decision_date": "2020-07-03", "context_summary": "Max weight deviation: 0.0129, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2561, target=0.2500\n  MATIC-USD: current=0.2536, target=0.2500\n  VNQ: current=0.2371, target=0.2500\n  BIL: current=0.2532, 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: 0.0129.\nRebalancing threshold: 0.0500.\n0.0129 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0257, transaction cost = 0.000026 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2561, "MATIC-USD": 0.2536, "VNQ": 0.2371, "BIL": 0.2532}, "target_weights": {"XLU": 0.25, "MATIC-USD": 0.25, "VNQ": 0.25, "BIL": 0.25}, "max_deviation": 0.0129, "total_turnover": 0.025745, "transaction_cost": 2.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VNQ", "primary_trade": -0.0129}}
{"id": "T6_all_20190315_0443", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "SCHH", "TLT"], "decision_date": "2019-03-15", "context_summary": "Max weight deviation: 0.0201, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2323, target=0.2500\n  ADA-USD: current=0.2501, target=0.2500\n  SCHH: current=0.2475, target=0.2500\n  TLT: current=0.2701, 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: 0.0201.\nRebalancing threshold: 0.0500.\n0.0201 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0404, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2323, "ADA-USD": 0.2501, "SCHH": 0.2475, "TLT": 0.2701}, "target_weights": {"XLI": 0.25, "ADA-USD": 0.25, "SCHH": 0.25, "TLT": 0.25}, "max_deviation": 0.0201, "total_turnover": 0.040397, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLT", "primary_trade": 0.0201}}
{"id": "T6_all_20220704_0447", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "PALL", "ITB"], "decision_date": "2022-07-04", "context_summary": "Max weight deviation: 0.0283, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2684, target=0.2500\n  ADA-USD: current=0.2217, target=0.2500\n  PALL: current=0.2775, target=0.2500\n  ITB: current=0.2324, 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: 0.0283.\nRebalancing threshold: 0.0500.\n0.0283 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0919, transaction cost = 0.000092 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2684, "ADA-USD": 0.2217, "PALL": 0.2775, "ITB": 0.2324}, "target_weights": {"QQQ": 0.25, "ADA-USD": 0.25, "PALL": 0.25, "ITB": 0.25}, "max_deviation": 0.0283, "total_turnover": 0.09186, "transaction_cost": 9.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": -0.0283}}
{"id": "T6_all_20210928_0451", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD", "PPLT", "SHY"], "decision_date": "2021-09-28", "context_summary": "Max weight deviation: 0.0312, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2388, target=0.2500\n  BNB-USD: current=0.2812, target=0.2500\n  PPLT: current=0.2513, target=0.2500\n  SHY: current=0.2287, 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 = 0.0650, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2388, "BNB-USD": 0.2812, "PPLT": 0.2513, "SHY": 0.2287}, "target_weights": {"QQQ": 0.25, "BNB-USD": 0.25, "PPLT": 0.25, "SHY": 0.25}, "max_deviation": 0.0312, "total_turnover": 0.064999, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.0312}}
{"id": "T6_all_20200910_0453", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "HYG", "ICSH"], "decision_date": "2020-09-10", "context_summary": "Max weight deviation: 0.0149, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2513, target=0.2500\n  ADA-USD: current=0.2523, target=0.2500\n  HYG: current=0.2351, target=0.2500\n  ICSH: current=0.2613, 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 = 0.0298, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2513, "ADA-USD": 0.2523, "HYG": 0.2351, "ICSH": 0.2613}, "target_weights": {"VEA": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "ICSH": 0.25}, "max_deviation": 0.0149, "total_turnover": 0.029754, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": -0.0149}}
{"id": "T6_all_20220630_0457", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "WEAT", "INDS"], "decision_date": "2022-06-30", "context_summary": "Max weight deviation: 0.0356, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2592, target=0.2500\n  BTC-USD: current=0.2144, target=0.2500\n  WEAT: current=0.2531, target=0.2500\n  INDS: current=0.2733, 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: 0.0356.\nRebalancing threshold: 0.0500.\n0.0356 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0711, transaction cost = 0.000071 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2592, "BTC-USD": 0.2144, "WEAT": 0.2531, "INDS": 0.2733}, "target_weights": {"VLUE": 0.25, "BTC-USD": 0.25, "WEAT": 0.25, "INDS": 0.25}, "max_deviation": 0.0356, "total_turnover": 0.071105, "transaction_cost": 7.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.0356}}
{"id": "T6_all_20181231_0461", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BTC-USD", "USO", "SHY"], "decision_date": "2018-12-31", "context_summary": "Max weight deviation: 0.0166, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2554, target=0.2500\n  BTC-USD: current=0.2590, target=0.2500\n  USO: current=0.2334, target=0.2500\n  SHY: current=0.2522, 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": {"XLI": 0.2554, "BTC-USD": 0.259, "USO": 0.2334, "SHY": 0.2522}, "target_weights": {"XLI": 0.25, "BTC-USD": 0.25, "USO": 0.25, "SHY": 0.25}, "max_deviation": 0.0166, "total_turnover": 0.033198, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "USO", "primary_trade": -0.0166}}
{"id": "T6_all_20210129_0462", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "SOL-USD", "DBA", "EMB"], "decision_date": "2021-01-29", "context_summary": "Max weight deviation: 0.0441, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2672, target=0.2500\n  SOL-USD: current=0.2677, target=0.2500\n  DBA: current=0.2801, target=0.2500\n  EMB: 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 EMB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0441.\nRebalancing threshold: 0.0500.\n0.0441 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0882, transaction cost = 0.000088 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2672, "SOL-USD": 0.2677, "DBA": 0.2801, "EMB": 0.185}, "target_weights": {"MTUM": 0.25, "SOL-USD": 0.25, "DBA": 0.25, "EMB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.088225, "transaction_cost": 8.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EMB", "primary_trade": -0.065}}
{"id": "T6_all_20180111_0466", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ETH-USD", "TLH", "BIL"], "decision_date": "2018-01-11", "context_summary": "Max weight deviation: 0.0087, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.1850, target=0.2500\n  ETH-USD: current=0.2582, target=0.2500\n  TLH: current=0.2784, target=0.2500\n  BIL: current=0.2784, 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 IWM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0087.\nRebalancing threshold: 0.0500.\n0.0087 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0174, transaction cost = 0.000017 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.185, "ETH-USD": 0.2582, "TLH": 0.2784, "BIL": 0.2784}, "target_weights": {"IWM": 0.25, "ETH-USD": 0.25, "TLH": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.017441, "transaction_cost": 1.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IWM", "primary_trade": -0.065}}
{"id": "T6_all_20210224_0469", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SOL-USD", "LQD", "SCHH"], "decision_date": "2021-02-24", "context_summary": "Max weight deviation: 0.0252, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2345, target=0.2500\n  SOL-USD: current=0.2752, target=0.2500\n  LQD: current=0.2520, target=0.2500\n  SCHH: 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: 0.0252.\nRebalancing threshold: 0.0500.\n0.0252 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0544, transaction cost = 0.000054 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2345, "SOL-USD": 0.2752, "LQD": 0.252, "SCHH": 0.2383}, "target_weights": {"IWM": 0.25, "SOL-USD": 0.25, "LQD": 0.25, "SCHH": 0.25}, "max_deviation": 0.0252, "total_turnover": 0.054402, "transaction_cost": 5.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": 0.0252}}
{"id": "T6_all_20210414_0471", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "ITB", "IEF"], "decision_date": "2021-04-14", "context_summary": "Max weight deviation: 0.0406, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2267, target=0.2500\n  ADA-USD: current=0.2362, target=0.2500\n  ITB: current=0.2906, target=0.2500\n  IEF: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0406.\nRebalancing threshold: 0.0500.\n0.0406 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0813, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2267, "ADA-USD": 0.2362, "ITB": 0.2906, "IEF": 0.2464}, "target_weights": {"XLY": 0.25, "ADA-USD": 0.25, "ITB": 0.25, "IEF": 0.25}, "max_deviation": 0.0406, "total_turnover": 0.081284, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": 0.0406}}
{"id": "T6_all_20190531_0472", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "ICSH", "DBB"], "decision_date": "2019-05-31", "context_summary": "Max weight deviation: 0.0373, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2237, target=0.2500\n  ADA-USD: current=0.2922, target=0.2500\n  ICSH: current=0.1850, target=0.2500\n  DBB: current=0.2991, 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: 0.0373.\nRebalancing threshold: 0.0500.\n0.0373 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1049, transaction cost = 0.000105 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2237, "ADA-USD": 0.2922, "ICSH": 0.185, "DBB": 0.2991}, "target_weights": {"XLY": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.104899, "transaction_cost": 0.000105, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.065}}
{"id": "T6_all_20200610_0473", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "SCHP", "DBC"], "decision_date": "2020-06-10", "context_summary": "Max weight deviation: 0.0338, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2402, target=0.2500\n  MATIC-USD: current=0.2267, target=0.2500\n  SCHP: current=0.2838, target=0.2500\n  DBC: current=0.2493, 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: 0.0338.\nRebalancing threshold: 0.0500.\n0.0338 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0676, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2402, "MATIC-USD": 0.2267, "SCHP": 0.2838, "DBC": 0.2493}, "target_weights": {"QUAL": 0.25, "MATIC-USD": 0.25, "SCHP": 0.25, "DBC": 0.25}, "max_deviation": 0.0338, "total_turnover": 0.067621, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": 0.0338}}
{"id": "T6_all_20201230_0474", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "BNB-USD", "BIL", "CORN"], "decision_date": "2020-12-30", "context_summary": "Max weight deviation: 0.0132, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.1861, target=0.2500\n  BNB-USD: current=0.2580, target=0.2500\n  BIL: current=0.3152, target=0.2500\n  CORN: current=0.2408, 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 BIL", "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 = 0.0298, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.1861, "BNB-USD": 0.258, "BIL": 0.3152, "CORN": 0.2408}, "target_weights": {"XLRE": 0.25, "BNB-USD": 0.25, "BIL": 0.25, "CORN": 0.25}, "max_deviation": 0.065155, "total_turnover": 0.029778, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0652}}
{"id": "T6_all_20220331_0475", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XRP-USD", "SHV", "UNG"], "decision_date": "2022-03-31", "context_summary": "Max weight deviation: 0.0318, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2432, target=0.2500\n  XRP-USD: current=0.2522, target=0.2500\n  SHV: current=0.2818, target=0.2500\n  UNG: current=0.2227, 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: 0.0318.\nRebalancing threshold: 0.0500.\n0.0318 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0681, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2432, "XRP-USD": 0.2522, "SHV": 0.2818, "UNG": 0.2227}, "target_weights": {"MTUM": 0.25, "XRP-USD": 0.25, "SHV": 0.25, "UNG": 0.25}, "max_deviation": 0.0318, "total_turnover": 0.068116, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SHV", "primary_trade": 0.0318}}
{"id": "T6_all_20220610_0476", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "HYG", "INDS"], "decision_date": "2022-06-10", "context_summary": "Max weight deviation: 0.0266, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2532, target=0.2500\n  BNB-USD: current=0.2974, target=0.2500\n  HYG: current=0.1850, target=0.2500\n  INDS: current=0.2644, 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: 0.0266.\nRebalancing threshold: 0.0500.\n0.0266 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0533, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2532, "BNB-USD": 0.2974, "HYG": 0.185, "INDS": 0.2644}, "target_weights": {"XLK": 0.25, "BNB-USD": 0.25, "HYG": 0.25, "INDS": 0.25}, "max_deviation": 0.065, "total_turnover": 0.053293, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": -0.065}}
{"id": "T6_all_20220913_0477", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "SGOV", "IGOV"], "decision_date": "2022-09-13", "context_summary": "Max weight deviation: 0.0203, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2703, target=0.2500\n  ADA-USD: current=0.2579, target=0.2500\n  SGOV: current=0.2314, target=0.2500\n  IGOV: current=0.2404, 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: 0.0203.\nRebalancing threshold: 0.0500.\n0.0203 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0564, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2703, "ADA-USD": 0.2579, "SGOV": 0.2314, "IGOV": 0.2404}, "target_weights": {"^VIX": 0.25, "ADA-USD": 0.25, "SGOV": 0.25, "IGOV": 0.25}, "max_deviation": 0.0203, "total_turnover": 0.056367, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": 0.0203}}
{"id": "T6_all_20181114_0478", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "SOYB", "REZ"], "decision_date": "2018-11-14", "context_summary": "Max weight deviation: 0.0202, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.3001, target=0.2500\n  BNB-USD: current=0.2715, target=0.2500\n  SOYB: current=0.1849, target=0.2500\n  REZ: current=0.2435, 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 SOYB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0202.\nRebalancing threshold: 0.0500.\n0.0202 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0445, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.3001, "BNB-USD": 0.2715, "SOYB": 0.1849, "REZ": 0.2435}, "target_weights": {"XLF": 0.25, "BNB-USD": 0.25, "SOYB": 0.25, "REZ": 0.25}, "max_deviation": 0.06506, "total_turnover": 0.04453, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": -0.0651}}
{"id": "T6_all_20221228_0479", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "INDS", "SCHP"], "decision_date": "2022-12-28", "context_summary": "Max weight deviation: 0.0224, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2348, target=0.2500\n  ADA-USD: current=0.2339, target=0.2500\n  INDS: current=0.2590, target=0.2500\n  SCHP: current=0.2724, 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 = 0.0627, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2348, "ADA-USD": 0.2339, "INDS": 0.259, "SCHP": 0.2724}, "target_weights": {"^VIX": 0.25, "ADA-USD": 0.25, "INDS": 0.25, "SCHP": 0.25}, "max_deviation": 0.0224, "total_turnover": 0.062721, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": 0.0224}}
{"id": "T6_all_20210303_0480", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "SCHH", "SGOV"], "decision_date": "2021-03-03", "context_summary": "Max weight deviation: 0.0081, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.3153, target=0.2500\n  LINK-USD: current=0.2558, target=0.2500\n  SCHH: current=0.2133, target=0.2500\n  SGOV: current=0.2157, 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 0.0653 of XLRE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0081.\nRebalancing threshold: 0.0500.\n0.0081 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0176, transaction cost = 0.000018 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3153, "LINK-USD": 0.2558, "SCHH": 0.2133, "SGOV": 0.2157}, "target_weights": {"XLRE": 0.25, "LINK-USD": 0.25, "SCHH": 0.25, "SGOV": 0.25}, "max_deviation": 0.065253, "total_turnover": 0.01762, "transaction_cost": 1.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": 0.0653}}
{"id": "T6_all_20200616_0481", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ADA-USD", "USO", "VNQ"], "decision_date": "2020-06-16", "context_summary": "Max weight deviation: 0.0115, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2476, target=0.2500\n  ADA-USD: current=0.2615, target=0.2500\n  USO: current=0.2392, target=0.2500\n  VNQ: current=0.2518, 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: 0.0115.\nRebalancing threshold: 0.0500.\n0.0115 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0265, transaction cost = 0.000027 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2476, "ADA-USD": 0.2615, "USO": 0.2392, "VNQ": 0.2518}, "target_weights": {"VLUE": 0.25, "ADA-USD": 0.25, "USO": 0.25, "VNQ": 0.25}, "max_deviation": 0.0115, "total_turnover": 0.026541, "transaction_cost": 2.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.0115}}
{"id": "T6_all_20180228_0482", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BTC-USD", "SCHP", "ICSH"], "decision_date": "2018-02-28", "context_summary": "Max weight deviation: 0.0188, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2822, target=0.2500\n  BTC-USD: current=0.2977, target=0.2500\n  SCHP: current=0.1850, target=0.2500\n  ICSH: current=0.2351, 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: 0.0188.\nRebalancing threshold: 0.0500.\n0.0188 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0462, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2822, "BTC-USD": 0.2977, "SCHP": 0.185, "ICSH": 0.2351}, "target_weights": {"XLB": 0.25, "BTC-USD": 0.25, "SCHP": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.046182, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": -0.065}}
{"id": "T6_all_20180416_0483", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ETH-USD", "BIL", "IYR"], "decision_date": "2018-04-16", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2614, target=0.2500\n  ETH-USD: current=0.2287, target=0.2500\n  BIL: current=0.2491, target=0.2500\n  IYR: current=0.2609, 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: 0.0213.\nRebalancing threshold: 0.0500.\n0.0213 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0446, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2614, "ETH-USD": 0.2287, "BIL": 0.2491, "IYR": 0.2609}, "target_weights": {"XLY": 0.25, "ETH-USD": 0.25, "BIL": 0.25, "IYR": 0.25}, "max_deviation": 0.0213, "total_turnover": 0.044557, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0213}}
{"id": "T6_all_20210625_0484", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "SOL-USD", "ITB", "SGOV"], "decision_date": "2021-06-25", "context_summary": "Max weight deviation: 0.0279, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.3150, target=0.2500\n  SOL-USD: current=0.1999, target=0.2500\n  ITB: current=0.2794, target=0.2500\n  SGOV: current=0.2057, 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 VTI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0279.\nRebalancing threshold: 0.0500.\n0.0279 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0810, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.315, "SOL-USD": 0.1999, "ITB": 0.2794, "SGOV": 0.2057}, "target_weights": {"VTI": 0.25, "SOL-USD": 0.25, "ITB": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.081006, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VTI", "primary_trade": 0.065}}
{"id": "T6_all_20220113_0485", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SOL-USD", "SLV", "ICSH"], "decision_date": "2022-01-13", "context_summary": "Max weight deviation: 0.0177, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2560, target=0.2500\n  SOL-USD: current=0.2530, target=0.2500\n  SLV: current=0.2323, target=0.2500\n  ICSH: current=0.2587, 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: 0.0177.\nRebalancing threshold: 0.0500.\n0.0177 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0353, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.256, "SOL-USD": 0.253, "SLV": 0.2323, "ICSH": 0.2587}, "target_weights": {"IWM": 0.25, "SOL-USD": 0.25, "SLV": 0.25, "ICSH": 0.25}, "max_deviation": 0.0177, "total_turnover": 0.035307, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SLV", "primary_trade": -0.0177}}
{"id": "T6_all_20220808_0486", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "SGOV", "HAUZ"], "decision_date": "2022-08-08", "context_summary": "Max weight deviation: 0.0206, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.3083, target=0.2500\n  ETH-USD: current=0.1849, target=0.2500\n  SGOV: current=0.1995, target=0.2500\n  HAUZ: current=0.3073, 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 ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0206.\nRebalancing threshold: 0.0500.\n0.0206 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0732, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3083, "ETH-USD": 0.1849, "SGOV": 0.1995, "HAUZ": 0.3073}, "target_weights": {"XLRE": 0.25, "ETH-USD": 0.25, "SGOV": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065058, "total_turnover": 0.073249, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "ETH-USD", "primary_trade": -0.0651}}
{"id": "T6_all_20220103_0487", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SOL-USD", "USO", "SGOV"], "decision_date": "2022-01-03", "context_summary": "Max weight deviation: 0.0154, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2374, target=0.2500\n  SOL-USD: current=0.2410, target=0.2500\n  USO: current=0.2654, target=0.2500\n  SGOV: current=0.2562, 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: 0.0154.\nRebalancing threshold: 0.0500.\n0.0154 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0433, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2374, "SOL-USD": 0.241, "USO": 0.2654, "SGOV": 0.2562}, "target_weights": {"VEA": 0.25, "SOL-USD": 0.25, "USO": 0.25, "SGOV": 0.25}, "max_deviation": 0.0154, "total_turnover": 0.043254, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "USO", "primary_trade": 0.0154}}
{"id": "T6_all_20200304_0488", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "ICSH", "XHB"], "decision_date": "2020-03-04", "context_summary": "Max weight deviation: 0.0156, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.3150, target=0.2500\n  BNB-USD: current=0.2679, target=0.2500\n  ICSH: current=0.2038, target=0.2500\n  XHB: current=0.2133, 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 IVV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0156.\nRebalancing threshold: 0.0500.\n0.0156 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0397, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.315, "BNB-USD": 0.2679, "ICSH": 0.2038, "XHB": 0.2133}, "target_weights": {"IVV": 0.25, "BNB-USD": 0.25, "ICSH": 0.25, "XHB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.03966, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IVV", "primary_trade": 0.065}}
{"id": "T6_all_20220818_0489", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ADA-USD", "DBA", "LQD"], "decision_date": "2022-08-18", "context_summary": "Max weight deviation: 0.0227, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2440, target=0.2500\n  ADA-USD: current=0.2727, target=0.2500\n  DBA: current=0.2510, target=0.2500\n  LQD: current=0.2323, 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 = 0.0475, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.244, "ADA-USD": 0.2727, "DBA": 0.251, "LQD": 0.2323}, "target_weights": {"EEM": 0.25, "ADA-USD": 0.25, "DBA": 0.25, "LQD": 0.25}, "max_deviation": 0.0227, "total_turnover": 0.047451, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.0227}}
{"id": "T6_all_20220601_0490", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "REZ", "DBB"], "decision_date": "2022-06-01", "context_summary": "Max weight deviation: 0.0099, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2585, target=0.2500\n  LINK-USD: current=0.1850, target=0.2500\n  REZ: current=0.2605, target=0.2500\n  DBB: current=0.2960, 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 LINK-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0099.\nRebalancing threshold: 0.0500.\n0.0099 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0198, transaction cost = 0.000020 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2585, "LINK-USD": 0.185, "REZ": 0.2605, "DBB": 0.296}, "target_weights": {"XLE": 0.25, "LINK-USD": 0.25, "REZ": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.019773, "transaction_cost": 2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.065}}
{"id": "T6_all_20220714_0491", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ETH-USD", "SGOV", "UNG"], "decision_date": "2022-07-14", "context_summary": "Max weight deviation: 0.0202, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2442, target=0.2500\n  ETH-USD: current=0.2702, target=0.2500\n  SGOV: current=0.2399, target=0.2500\n  UNG: current=0.2458, 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 = 0.0403, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2442, "ETH-USD": 0.2702, "SGOV": 0.2399, "UNG": 0.2458}, "target_weights": {"^VIX": 0.25, "ETH-USD": 0.25, "SGOV": 0.25, "UNG": 0.25}, "max_deviation": 0.0202, "total_turnover": 0.040336, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.0202}}
{"id": "T6_all_20190703_0492", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ETH-USD", "BIL", "ITB"], "decision_date": "2019-07-03", "context_summary": "Max weight deviation: 0.0170, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2082, target=0.2500\n  ETH-USD: current=0.2606, target=0.2500\n  BIL: current=0.3149, target=0.2500\n  ITB: current=0.2163, 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: 0.0170.\nRebalancing threshold: 0.0500.\n0.0170 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0396, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2082, "ETH-USD": 0.2606, "BIL": 0.3149, "ITB": 0.2163}, "target_weights": {"XLI": 0.25, "ETH-USD": 0.25, "BIL": 0.25, "ITB": 0.25}, "max_deviation": 0.06488, "total_turnover": 0.039551, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0649}}
{"id": "T6_all_20201209_0493", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DOT-USD", "REZ", "PDBC"], "decision_date": "2020-12-09", "context_summary": "Max weight deviation: 0.0117, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2617, target=0.2500\n  DOT-USD: current=0.2401, target=0.2500\n  REZ: current=0.2478, target=0.2500\n  PDBC: current=0.2505, 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: 0.0117.\nRebalancing threshold: 0.0500.\n0.0117 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0243, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2617, "DOT-USD": 0.2401, "REZ": 0.2478, "PDBC": 0.2505}, "target_weights": {"XLB": 0.25, "DOT-USD": 0.25, "REZ": 0.25, "PDBC": 0.25}, "max_deviation": 0.0117, "total_turnover": 0.024315, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLB", "primary_trade": 0.0117}}
{"id": "T6_all_20190419_0494", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "REZ", "SCHP"], "decision_date": "2019-04-19", "context_summary": "Max weight deviation: 0.0321, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2966, target=0.2500\n  ADA-USD: current=0.1850, target=0.2500\n  REZ: current=0.2549, target=0.2500\n  SCHP: current=0.2636, 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: 0.0321.\nRebalancing threshold: 0.0500.\n0.0321 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0643, transaction cost = 0.000064 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2966, "ADA-USD": 0.185, "REZ": 0.2549, "SCHP": 0.2636}, "target_weights": {"XLK": 0.25, "ADA-USD": 0.25, "REZ": 0.25, "SCHP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.06426, "transaction_cost": 6.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": -0.065}}
{"id": "T6_all_20150316_0495", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "VNQI", "BNO"], "decision_date": "2015-03-16", "context_summary": "Max weight deviation: 0.0154, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2493, target=0.2500\n  BTC-USD: current=0.2394, target=0.2500\n  VNQI: current=0.2458, target=0.2500\n  BNO: current=0.2654, 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: 0.0154.\nRebalancing threshold: 0.0500.\n0.0154 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0308, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2493, "BTC-USD": 0.2394, "VNQI": 0.2458, "BNO": 0.2654}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "VNQI": 0.25, "BNO": 0.25}, "max_deviation": 0.0154, "total_turnover": 0.030845, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": 0.0154}}
{"id": "T6_all_20200213_0496", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "JNK", "ICSH"], "decision_date": "2020-02-13", "context_summary": "Max weight deviation: 0.0295, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2313, target=0.2500\n  XRP-USD: current=0.3150, target=0.2500\n  JNK: current=0.2313, target=0.2500\n  ICSH: current=0.2225, 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: 0.0295.\nRebalancing threshold: 0.0500.\n0.0295 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0591, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2313, "XRP-USD": 0.315, "JNK": 0.2313, "ICSH": 0.2225}, "target_weights": {"VLUE": 0.25, "XRP-USD": 0.25, "JNK": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059065, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": 0.065}}
{"id": "T6_all_20210111_0497", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "SOL-USD", "SGOV", "EMB"], "decision_date": "2021-01-11", "context_summary": "Max weight deviation: 0.0133, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2491, target=0.2500\n  SOL-USD: current=0.2367, target=0.2500\n  SGOV: current=0.2601, target=0.2500\n  EMB: 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: 0.0133.\nRebalancing threshold: 0.0500.\n0.0133 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0284, transaction cost = 0.000028 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2491, "SOL-USD": 0.2367, "SGOV": 0.2601, "EMB": 0.2542}, "target_weights": {"EWJ": 0.25, "SOL-USD": 0.25, "SGOV": 0.25, "EMB": 0.25}, "max_deviation": 0.0133, "total_turnover": 0.028432, "transaction_cost": 2.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": -0.0133}}
{"id": "T6_all_20201102_0498", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "LINK-USD", "USO", "TLT"], "decision_date": "2020-11-02", "context_summary": "Max weight deviation: 0.0493, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2151, target=0.2500\n  LINK-USD: current=0.2458, target=0.2500\n  USO: current=0.2242, target=0.2500\n  TLT: 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 TLT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0493.\nRebalancing threshold: 0.0500.\n0.0493 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0987, transaction cost = 0.000099 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2151, "LINK-USD": 0.2458, "USO": 0.2242, "TLT": 0.315}, "target_weights": {"USMV": 0.25, "LINK-USD": 0.25, "USO": 0.25, "TLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.098683, "transaction_cost": 9.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "TLT", "primary_trade": 0.065}}
{"id": "T6_all_20210809_0499", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "IEF", "DBC"], "decision_date": "2021-08-09", "context_summary": "Max weight deviation: 0.0235, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2735, target=0.2500\n  BTC-USD: current=0.2467, target=0.2500\n  IEF: current=0.2397, target=0.2500\n  DBC: 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: 0.0235.\nRebalancing threshold: 0.0500.\n0.0235 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0470, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2735, "BTC-USD": 0.2467, "IEF": 0.2397, "DBC": 0.2401}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "IEF": 0.25, "DBC": 0.25}, "max_deviation": 0.0235, "total_turnover": 0.046953, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VEA", "primary_trade": 0.0235}}
{"id": "T6_all_20220310_0500", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BNB-USD", "XHB", "JNK"], "decision_date": "2022-03-10", "context_summary": "Max weight deviation: 0.0248, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.3150, target=0.2500\n  BNB-USD: current=0.2073, target=0.2500\n  XHB: current=0.2445, target=0.2500\n  JNK: current=0.2332, 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: 0.0248.\nRebalancing threshold: 0.0500.\n0.0248 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0497, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.315, "BNB-USD": 0.2073, "XHB": 0.2445, "JNK": 0.2332}, "target_weights": {"VLUE": 0.25, "BNB-USD": 0.25, "XHB": 0.25, "JNK": 0.25}, "max_deviation": 0.065, "total_turnover": 0.04966, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VLUE", "primary_trade": 0.065}}
{"id": "T6_all_20220805_0501", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "AVAX-USD", "DBB", "VNQI"], "decision_date": "2022-08-05", "context_summary": "Max weight deviation: 0.0178, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2678, target=0.2500\n  AVAX-USD: current=0.2422, target=0.2500\n  DBB: current=0.2497, target=0.2500\n  VNQI: current=0.2404, 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": {"VLUE": 0.2678, "AVAX-USD": 0.2422, "DBB": 0.2497, "VNQI": 0.2404}, "target_weights": {"VLUE": 0.25, "AVAX-USD": 0.25, "DBB": 0.25, "VNQI": 0.25}, "max_deviation": 0.0178, "total_turnover": 0.035507, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VLUE", "primary_trade": 0.0178}}
{"id": "T6_all_20210629_0502", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "XRP-USD", "DBC", "LQD"], "decision_date": "2021-06-29", "context_summary": "Max weight deviation: 0.0099, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.1876, target=0.2500\n  XRP-USD: current=0.3150, target=0.2500\n  DBC: current=0.2126, target=0.2500\n  LQD: current=0.2848, 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: 0.0099.\nRebalancing threshold: 0.0500.\n0.0099 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0304, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.1876, "XRP-USD": 0.315, "DBC": 0.2126, "LQD": 0.2848}, "target_weights": {"XLB": 0.25, "XRP-USD": 0.25, "DBC": 0.25, "LQD": 0.25}, "max_deviation": 0.065, "total_turnover": 0.030396, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": 0.065}}
{"id": "T6_all_20190807_0503", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "BIL", "TLT"], "decision_date": "2019-08-07", "context_summary": "Max weight deviation: 0.0179, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2529, target=0.2500\n  ADA-USD: current=0.2351, target=0.2500\n  BIL: current=0.2441, target=0.2500\n  TLT: current=0.2679, 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 = 0.0416, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2529, "ADA-USD": 0.2351, "BIL": 0.2441, "TLT": 0.2679}, "target_weights": {"XLE": 0.25, "ADA-USD": 0.25, "BIL": 0.25, "TLT": 0.25}, "max_deviation": 0.0179, "total_turnover": 0.041567, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLT", "primary_trade": 0.0179}}
{"id": "T6_all_20210519_0504", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ETH-USD", "REZ", "IAU"], "decision_date": "2021-05-19", "context_summary": "Max weight deviation: 0.0141, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2490, target=0.2500\n  ETH-USD: current=0.1849, target=0.2500\n  REZ: current=0.2771, target=0.2500\n  IAU: current=0.2891, 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 ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0141.\nRebalancing threshold: 0.0500.\n0.0141 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0287, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.249, "ETH-USD": 0.1849, "REZ": 0.2771, "IAU": 0.2891}, "target_weights": {"XLI": 0.25, "ETH-USD": 0.25, "REZ": 0.25, "IAU": 0.25}, "max_deviation": 0.065085, "total_turnover": 0.028683, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0651}}
{"id": "T6_all_20190823_0505", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "DBA", "TLT"], "decision_date": "2019-08-23", "context_summary": "Max weight deviation: 0.0268, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2373, target=0.2500\n  BTC-USD: current=0.2317, target=0.2500\n  DBA: current=0.2541, target=0.2500\n  TLT: current=0.2768, 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: 0.0268.\nRebalancing threshold: 0.0500.\n0.0268 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0619, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2373, "BTC-USD": 0.2317, "DBA": 0.2541, "TLT": 0.2768}, "target_weights": {"EEM": 0.25, "BTC-USD": 0.25, "DBA": 0.25, "TLT": 0.25}, "max_deviation": 0.0268, "total_turnover": 0.061934, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLT", "primary_trade": 0.0268}}
{"id": "T6_all_20220629_0506", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "SCHP", "SOYB"], "decision_date": "2022-06-29", "context_summary": "Max weight deviation: 0.0255, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.1850, target=0.2500\n  XRP-USD: current=0.2903, target=0.2500\n  SCHP: current=0.2515, target=0.2500\n  SOYB: current=0.2732, 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 XLP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0255.\nRebalancing threshold: 0.0500.\n0.0255 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0511, transaction cost = 0.000051 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.185, "XRP-USD": 0.2903, "SCHP": 0.2515, "SOYB": 0.2732}, "target_weights": {"XLP": 0.25, "XRP-USD": 0.25, "SCHP": 0.25, "SOYB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.051053, "transaction_cost": 5.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLP", "primary_trade": -0.065}}
{"id": "T6_all_20211119_0507", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "AVAX-USD", "XHB", "SGOV"], "decision_date": "2021-11-19", "context_summary": "Max weight deviation: 0.0241, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2315, target=0.2500\n  AVAX-USD: current=0.2572, target=0.2500\n  XHB: current=0.2741, target=0.2500\n  SGOV: current=0.2373, 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: 0.0241.\nRebalancing threshold: 0.0500.\n0.0241 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0625, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2315, "AVAX-USD": 0.2572, "XHB": 0.2741, "SGOV": 0.2373}, "target_weights": {"XLF": 0.25, "AVAX-USD": 0.25, "XHB": 0.25, "SGOV": 0.25}, "max_deviation": 0.0241, "total_turnover": 0.062524, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XHB", "primary_trade": 0.0241}}
{"id": "T6_all_20201104_0508", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "AVAX-USD", "CORN", "VNQI"], "decision_date": "2020-11-04", "context_summary": "Max weight deviation: 0.0137, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2072, target=0.2500\n  AVAX-USD: current=0.2266, target=0.2500\n  CORN: current=0.2513, target=0.2500\n  VNQI: 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 VNQI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0137.\nRebalancing threshold: 0.0500.\n0.0137 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0279, transaction cost = 0.000028 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2072, "AVAX-USD": 0.2266, "CORN": 0.2513, "VNQI": 0.3149}, "target_weights": {"XLI": 0.25, "AVAX-USD": 0.25, "CORN": 0.25, "VNQI": 0.25}, "max_deviation": 0.064851, "total_turnover": 0.027863, "transaction_cost": 2.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQI", "primary_trade": 0.0649}}
{"id": "T6_all_20200423_0509", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "MATIC-USD", "PDBC", "HYG"], "decision_date": "2020-04-23", "context_summary": "Max weight deviation: 0.0240, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2346, target=0.2500\n  MATIC-USD: current=0.2740, target=0.2500\n  PDBC: current=0.2268, target=0.2500\n  HYG: current=0.2647, 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: 0.0240.\nRebalancing threshold: 0.0500.\n0.0240 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0773, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2346, "MATIC-USD": 0.274, "PDBC": 0.2268, "HYG": 0.2647}, "target_weights": {"EEM": 0.25, "MATIC-USD": 0.25, "PDBC": 0.25, "HYG": 0.25}, "max_deviation": 0.024, "total_turnover": 0.077344, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": 0.024}}
{"id": "T6_all_20211224_0510", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "ICSH", "VCIT"], "decision_date": "2021-12-24", "context_summary": "Max weight deviation: 0.0266, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2559, target=0.2500\n  ADA-USD: current=0.3150, target=0.2500\n  ICSH: current=0.1921, target=0.2500\n  VCIT: current=0.2370, 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 ADA-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0266.\nRebalancing threshold: 0.0500.\n0.0266 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0580, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2559, "ADA-USD": 0.315, "ICSH": 0.1921, "VCIT": 0.237}, "target_weights": {"ACWI": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "VCIT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.058007, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.065}}
{"id": "T6_all_20210713_0511", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "SOL-USD", "ICSH", "USO"], "decision_date": "2021-07-13", "context_summary": "Max weight deviation: 0.0245, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2682, target=0.2500\n  SOL-USD: current=0.2255, target=0.2500\n  ICSH: current=0.2348, target=0.2500\n  USO: current=0.2716, 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: 0.0245.\nRebalancing threshold: 0.0500.\n0.0245 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0795, transaction cost = 0.000079 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2682, "SOL-USD": 0.2255, "ICSH": 0.2348, "USO": 0.2716}, "target_weights": {"MTUM": 0.25, "SOL-USD": 0.25, "ICSH": 0.25, "USO": 0.25}, "max_deviation": 0.0245, "total_turnover": 0.079453, "transaction_cost": 7.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": -0.0245}}
{"id": "T6_all_20221212_0512", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MATIC-USD", "CPER", "ITB"], "decision_date": "2022-12-12", "context_summary": "Max weight deviation: 0.0248, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.3150, target=0.2500\n  MATIC-USD: current=0.2655, target=0.2500\n  CPER: current=0.1934, target=0.2500\n  ITB: current=0.2261, 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 FXI", "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 = 0.0614, transaction cost = 0.000061 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.315, "MATIC-USD": 0.2655, "CPER": 0.1934, "ITB": 0.2261}, "target_weights": {"FXI": 0.25, "MATIC-USD": 0.25, "CPER": 0.25, "ITB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.061439, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "FXI", "primary_trade": 0.065}}
{"id": "T6_all_20220824_0513", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ADA-USD", "SCHP", "VNQ"], "decision_date": "2022-08-24", "context_summary": "Max weight deviation: 0.0272, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2516, target=0.2500\n  ADA-USD: current=0.2475, target=0.2500\n  SCHP: current=0.2772, target=0.2500\n  VNQ: current=0.2237, 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: 0.0272.\nRebalancing threshold: 0.0500.\n0.0272 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0576, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2516, "ADA-USD": 0.2475, "SCHP": 0.2772, "VNQ": 0.2237}, "target_weights": {"XLE": 0.25, "ADA-USD": 0.25, "SCHP": 0.25, "VNQ": 0.25}, "max_deviation": 0.0272, "total_turnover": 0.057564, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": 0.0272}}
{"id": "T6_all_20220728_0514", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "ICSH", "TLH"], "decision_date": "2022-07-28", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.1851, target=0.2500\n  AVAX-USD: current=0.3142, target=0.2500\n  ICSH: current=0.2168, target=0.2500\n  TLH: current=0.2840, 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 EEM", "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 = 0.0643, transaction cost = 0.000064 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.1851, "AVAX-USD": 0.3142, "ICSH": 0.2168, "TLH": 0.284}, "target_weights": {"EEM": 0.25, "AVAX-USD": 0.25, "ICSH": 0.25, "TLH": 0.25}, "max_deviation": 0.064944, "total_turnover": 0.064319, "transaction_cost": 6.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": -0.0649}}
{"id": "T6_all_20210806_0515", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "SOL-USD", "SCHP", "ICSH"], "decision_date": "2021-08-06", "context_summary": "Max weight deviation: 0.0367, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2368, target=0.2500\n  SOL-USD: current=0.2402, target=0.2500\n  SCHP: current=0.2364, target=0.2500\n  ICSH: current=0.2867, 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: 0.0367.\nRebalancing threshold: 0.0500.\n0.0367 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0733, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2368, "SOL-USD": 0.2402, "SCHP": 0.2364, "ICSH": 0.2867}, "target_weights": {"USMV": 0.25, "SOL-USD": 0.25, "SCHP": 0.25, "ICSH": 0.25}, "max_deviation": 0.0367, "total_turnover": 0.073303, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": 0.0367}}
{"id": "T6_all_20220603_0516", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "DOT-USD", "IGOV", "VNQ"], "decision_date": "2022-06-03", "context_summary": "Max weight deviation: 0.0528, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2488, target=0.2500\n  DOT-USD: current=0.2140, target=0.2500\n  IGOV: current=0.2344, target=0.2500\n  VNQ: current=0.3028, 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 0.0528 of VNQ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0528.\nRebalancing threshold: 0.0500.\n0.0528 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1057, transaction cost = 0.000106 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2488, "DOT-USD": 0.214, "IGOV": 0.2344, "VNQ": 0.3028}, "target_weights": {"EEM": 0.25, "DOT-USD": 0.25, "IGOV": 0.25, "VNQ": 0.25}, "max_deviation": 0.0528, "total_turnover": 0.105687, "transaction_cost": 0.000106, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQ", "primary_trade": 0.0528}}
{"id": "T6_all_20200615_0517", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "MATIC-USD", "ITB", "DBA"], "decision_date": "2020-06-15", "context_summary": "Max weight deviation: 0.0198, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2422, target=0.2500\n  MATIC-USD: current=0.2442, target=0.2500\n  ITB: current=0.2438, target=0.2500\n  DBA: current=0.2698, 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: 0.0198.\nRebalancing threshold: 0.0500.\n0.0198 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0396, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2422, "MATIC-USD": 0.2442, "ITB": 0.2438, "DBA": 0.2698}, "target_weights": {"QQQ": 0.25, "MATIC-USD": 0.25, "ITB": 0.25, "DBA": 0.25}, "max_deviation": 0.0198, "total_turnover": 0.03965, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBA", "primary_trade": 0.0198}}
{"id": "T6_all_20191209_0518", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "SHV", "ITB"], "decision_date": "2019-12-09", "context_summary": "Max weight deviation: 0.0302, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2414, target=0.2500\n  MATIC-USD: current=0.2737, target=0.2500\n  SHV: current=0.2999, target=0.2500\n  ITB: 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 ITB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0302.\nRebalancing threshold: 0.0500.\n0.0302 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0684, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2414, "MATIC-USD": 0.2737, "SHV": 0.2999, "ITB": 0.185}, "target_weights": {"VTI": 0.25, "MATIC-USD": 0.25, "SHV": 0.25, "ITB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.068367, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": -0.065}}
{"id": "T6_all_20200917_0519", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "MATIC-USD", "MORT", "BNO"], "decision_date": "2020-09-17", "context_summary": "Max weight deviation: 0.0101, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2440, target=0.2500\n  MATIC-USD: current=0.2601, target=0.2500\n  MORT: current=0.2481, target=0.2500\n  BNO: 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: 0.0101.\nRebalancing threshold: 0.0500.\n0.0101 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0202, transaction cost = 0.000020 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.244, "MATIC-USD": 0.2601, "MORT": 0.2481, "BNO": 0.2478}, "target_weights": {"QQQ": 0.25, "MATIC-USD": 0.25, "MORT": 0.25, "BNO": 0.25}, "max_deviation": 0.0101, "total_turnover": 0.020171, "transaction_cost": 2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": 0.0101}}
{"id": "T6_all_20210909_0520", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BTC-USD", "IAU", "SGOV"], "decision_date": "2021-09-09", "context_summary": "Max weight deviation: 0.0143, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2340, target=0.2500\n  BTC-USD: current=0.2626, target=0.2500\n  IAU: current=0.1886, target=0.2500\n  SGOV: 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 SGOV", "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 = 0.0341, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.234, "BTC-USD": 0.2626, "IAU": 0.1886, "SGOV": 0.3149}, "target_weights": {"XLI": 0.25, "BTC-USD": 0.25, "IAU": 0.25, "SGOV": 0.25}, "max_deviation": 0.064857, "total_turnover": 0.034139, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0649}}
{"id": "T6_all_20190410_0521", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "INDS", "VCIT"], "decision_date": "2019-04-10", "context_summary": "Max weight deviation: 0.0145, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2497, target=0.2500\n  LINK-USD: current=0.2355, target=0.2500\n  INDS: current=0.2620, target=0.2500\n  VCIT: 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: 0.0145.\nRebalancing threshold: 0.0500.\n0.0145 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0295, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2497, "LINK-USD": 0.2355, "INDS": 0.262, "VCIT": 0.2527}, "target_weights": {"XLU": 0.25, "LINK-USD": 0.25, "INDS": 0.25, "VCIT": 0.25}, "max_deviation": 0.0145, "total_turnover": 0.029456, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.0145}}
{"id": "T6_all_20221019_0522", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "CSHI", "VNQ"], "decision_date": "2022-10-19", "context_summary": "Max weight deviation: 0.0458, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2034, target=0.2500\n  BNB-USD: current=0.2904, target=0.2500\n  CSHI: current=0.1911, target=0.2500\n  VNQ: 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 VNQ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0458.\nRebalancing threshold: 0.0500.\n0.0458 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1485, transaction cost = 0.000148 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2034, "BNB-USD": 0.2904, "CSHI": 0.1911, "VNQ": 0.315}, "target_weights": {"XLI": 0.25, "BNB-USD": 0.25, "CSHI": 0.25, "VNQ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.148492, "transaction_cost": 0.000148, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQ", "primary_trade": 0.065}}
{"id": "T6_all_20180508_0523", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BTC-USD", "UNG", "ICSH"], "decision_date": "2018-05-08", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.2697, target=0.2500\n  BTC-USD: current=0.2305, target=0.2500\n  UNG: current=0.2710, target=0.2500\n  ICSH: current=0.2287, 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: 0.0213.\nRebalancing threshold: 0.0500.\n0.0213 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0815, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2697, "BTC-USD": 0.2305, "UNG": 0.271, "ICSH": 0.2287}, "target_weights": {"XLP": 0.25, "BTC-USD": 0.25, "UNG": 0.25, "ICSH": 0.25}, "max_deviation": 0.0213, "total_turnover": 0.081462, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0213}}
{"id": "T6_all_20211222_0524", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "ICSH", "HYG"], "decision_date": "2021-12-22", "context_summary": "Max weight deviation: 0.0257, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.3150, target=0.2500\n  ADA-USD: current=0.2672, target=0.2500\n  ICSH: current=0.2007, target=0.2500\n  HYG: current=0.2171, 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: 0.0257.\nRebalancing threshold: 0.0500.\n0.0257 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0650, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.315, "ADA-USD": 0.2672, "ICSH": 0.2007, "HYG": 0.2171}, "target_weights": {"XLP": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "HYG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.06504, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLP", "primary_trade": 0.065}}
{"id": "T6_all_20221226_0525", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "INDS", "PALL"], "decision_date": "2022-12-26", "context_summary": "Max weight deviation: 0.0098, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2490, target=0.2500\n  BNB-USD: current=0.2450, target=0.2500\n  INDS: current=0.2598, target=0.2500\n  PALL: 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: 0.0098.\nRebalancing threshold: 0.0500.\n0.0098 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0196, transaction cost = 0.000020 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.249, "BNB-USD": 0.245, "INDS": 0.2598, "PALL": 0.2462}, "target_weights": {"XLF": 0.25, "BNB-USD": 0.25, "INDS": 0.25, "PALL": 0.25}, "max_deviation": 0.0098, "total_turnover": 0.019634, "transaction_cost": 2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "INDS", "primary_trade": 0.0098}}
{"id": "T6_all_20220908_0526", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "AVAX-USD", "BIL", "TLH"], "decision_date": "2022-09-08", "context_summary": "Max weight deviation: 0.0059, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2555, target=0.2500\n  AVAX-USD: current=0.2577, target=0.2500\n  BIL: current=0.3018, target=0.2500\n  TLH: 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 TLH", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0059.\nRebalancing threshold: 0.0500.\n0.0059 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0119, transaction cost = 0.000012 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2555, "AVAX-USD": 0.2577, "BIL": 0.3018, "TLH": 0.185}, "target_weights": {"XLY": 0.25, "AVAX-USD": 0.25, "BIL": 0.25, "TLH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.011863, "transaction_cost": 1.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": -0.065}}
{"id": "T6_all_20181211_0527", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD", "SHY", "GLD"], "decision_date": "2018-12-11", "context_summary": "Max weight deviation: 0.0348, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2152, target=0.2500\n  BNB-USD: current=0.2628, target=0.2500\n  SHY: current=0.2600, target=0.2500\n  GLD: 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: 0.0348.\nRebalancing threshold: 0.0500.\n0.0348 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0695, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2152, "BNB-USD": 0.2628, "SHY": 0.26, "GLD": 0.262}, "target_weights": {"QQQ": 0.25, "BNB-USD": 0.25, "SHY": 0.25, "GLD": 0.25}, "max_deviation": 0.0348, "total_turnover": 0.069508, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "QQQ", "primary_trade": -0.0348}}
{"id": "T6_all_20220217_0528", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "VNQI", "CORN"], "decision_date": "2022-02-17", "context_summary": "Max weight deviation: 0.0303, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2477, target=0.2500\n  MATIC-USD: current=0.3151, target=0.2500\n  VNQI: current=0.2417, target=0.2500\n  CORN: current=0.1956, 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 MATIC-USD", "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 = 0.0606, transaction cost = 0.000061 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2477, "MATIC-USD": 0.3151, "VNQI": 0.2417, "CORN": 0.1956}, "target_weights": {"IWM": 0.25, "MATIC-USD": 0.25, "VNQI": 0.25, "CORN": 0.25}, "max_deviation": 0.065068, "total_turnover": 0.060604, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "MATIC-USD", "primary_trade": 0.0651}}
{"id": "T6_all_20180322_0529", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "IYR", "SCHP"], "decision_date": "2018-03-22", "context_summary": "Max weight deviation: 0.0108, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2608, target=0.2500\n  ADA-USD: current=0.2446, target=0.2500\n  IYR: current=0.2477, target=0.2500\n  SCHP: current=0.2469, 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: 0.0108.\nRebalancing threshold: 0.0500.\n0.0108 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0217, transaction cost = 0.000022 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2608, "ADA-USD": 0.2446, "IYR": 0.2477, "SCHP": 0.2469}, "target_weights": {"USMV": 0.25, "ADA-USD": 0.25, "IYR": 0.25, "SCHP": 0.25}, "max_deviation": 0.0108, "total_turnover": 0.021677, "transaction_cost": 2.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": 0.0108}}
{"id": "T6_all_20220708_0530", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BNB-USD", "DBB", "SHY"], "decision_date": "2022-07-08", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2072, target=0.2500\n  BNB-USD: current=0.3149, target=0.2500\n  DBB: current=0.2719, target=0.2500\n  SHY: current=0.2060, 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: 0.0213.\nRebalancing threshold: 0.0500.\n0.0213 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0568, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2072, "BNB-USD": 0.3149, "DBB": 0.2719, "SHY": 0.206}, "target_weights": {"ACWI": 0.25, "BNB-USD": 0.25, "DBB": 0.25, "SHY": 0.25}, "max_deviation": 0.064904, "total_turnover": 0.056843, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.0649}}
{"id": "T6_all_20221130_0531", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "MATIC-USD", "MORT", "IAU"], "decision_date": "2022-11-30", "context_summary": "Max weight deviation: 0.0330, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2320, target=0.2500\n  MATIC-USD: current=0.2449, target=0.2500\n  MORT: current=0.2402, target=0.2500\n  IAU: current=0.2830, 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: 0.0330.\nRebalancing threshold: 0.0500.\n0.0330 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0660, transaction cost = 0.000066 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.232, "MATIC-USD": 0.2449, "MORT": 0.2402, "IAU": 0.283}, "target_weights": {"VLUE": 0.25, "MATIC-USD": 0.25, "MORT": 0.25, "IAU": 0.25}, "max_deviation": 0.033, "total_turnover": 0.066016, "transaction_cost": 6.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IAU", "primary_trade": 0.033}}
{"id": "T6_all_20170907_0532", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "VCIT", "XHB"], "decision_date": "2017-09-07", "context_summary": "Max weight deviation: 0.0402, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2392, target=0.2500\n  BTC-USD: current=0.3150, target=0.2500\n  VCIT: current=0.2405, target=0.2500\n  XHB: current=0.2054, 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 BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0402.\nRebalancing threshold: 0.0500.\n0.0402 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0804, transaction cost = 0.000080 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2392, "BTC-USD": 0.315, "VCIT": 0.2405, "XHB": 0.2054}, "target_weights": {"EFA": 0.25, "BTC-USD": 0.25, "VCIT": 0.25, "XHB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.080393, "transaction_cost": 8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.065}}
{"id": "T6_all_20221215_0533", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "DBB", "IGOV"], "decision_date": "2022-12-15", "context_summary": "Max weight deviation: 0.0139, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2361, target=0.2500\n  BTC-USD: current=0.2610, target=0.2500\n  DBB: current=0.2423, target=0.2500\n  IGOV: current=0.2605, 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: 0.0139.\nRebalancing threshold: 0.0500.\n0.0139 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0431, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2361, "BTC-USD": 0.261, "DBB": 0.2423, "IGOV": 0.2605}, "target_weights": {"EFA": 0.25, "BTC-USD": 0.25, "DBB": 0.25, "IGOV": 0.25}, "max_deviation": 0.0139, "total_turnover": 0.043095, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EFA", "primary_trade": -0.0139}}
{"id": "T6_all_20190528_0534", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "XRP-USD", "XHB", "SCHP"], "decision_date": "2019-05-28", "context_summary": "Max weight deviation: 0.0184, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.1850, target=0.2500\n  XRP-USD: current=0.2896, target=0.2500\n  XHB: current=0.2744, target=0.2500\n  SCHP: current=0.2511, 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 XLB", "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 = 0.0368, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.185, "XRP-USD": 0.2896, "XHB": 0.2744, "SCHP": 0.2511}, "target_weights": {"XLB": 0.25, "XRP-USD": 0.25, "XHB": 0.25, "SCHP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.036825, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLB", "primary_trade": -0.065}}
{"id": "T6_all_20160226_0535", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BTC-USD", "ICSH", "TLH"], "decision_date": "2016-02-26", "context_summary": "Max weight deviation: 0.0246, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2254, target=0.2500\n  BTC-USD: current=0.2463, target=0.2500\n  ICSH: current=0.2680, target=0.2500\n  TLH: current=0.2603, 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 = 0.0565, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2254, "BTC-USD": 0.2463, "ICSH": 0.268, "TLH": 0.2603}, "target_weights": {"MTUM": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "TLH": 0.25}, "max_deviation": 0.0246, "total_turnover": 0.056482, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MTUM", "primary_trade": -0.0246}}
{"id": "T6_all_20221117_0536", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD", "SCHH", "CSHI"], "decision_date": "2022-11-17", "context_summary": "Max weight deviation: 0.0347, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2393, target=0.2500\n  DOT-USD: current=0.3150, target=0.2500\n  SCHH: current=0.2367, target=0.2500\n  CSHI: current=0.2090, 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 DOT-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0347.\nRebalancing threshold: 0.0500.\n0.0347 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0694, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2393, "DOT-USD": 0.315, "SCHH": 0.2367, "CSHI": 0.209}, "target_weights": {"ACWI": 0.25, "DOT-USD": 0.25, "SCHH": 0.25, "CSHI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.069395, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DOT-USD", "primary_trade": 0.065}}
{"id": "T6_all_20160307_0537", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "TLH", "BNO"], "decision_date": "2016-03-07", "context_summary": "Max weight deviation: 0.0376, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2427, target=0.2500\n  BTC-USD: current=0.2175, target=0.2500\n  TLH: current=0.2523, target=0.2500\n  BNO: current=0.2876, 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: 0.0376.\nRebalancing threshold: 0.0500.\n0.0376 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0797, transaction cost = 0.000080 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2427, "BTC-USD": 0.2175, "TLH": 0.2523, "BNO": 0.2876}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "TLH": 0.25, "BNO": 0.25}, "max_deviation": 0.0376, "total_turnover": 0.07966, "transaction_cost": 8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": 0.0376}}
{"id": "T6_all_20190618_0538", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "SCHP", "HAUZ"], "decision_date": "2019-06-18", "context_summary": "Max weight deviation: 0.0060, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.1850, target=0.2500\n  ADA-USD: current=0.2662, target=0.2500\n  SCHP: current=0.2706, target=0.2500\n  HAUZ: current=0.2782, 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 XLK", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0060.\nRebalancing threshold: 0.0500.\n0.0060 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0121, transaction cost = 0.000012 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.185, "ADA-USD": 0.2662, "SCHP": 0.2706, "HAUZ": 0.2782}, "target_weights": {"XLK": 0.25, "ADA-USD": 0.25, "SCHP": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.012056, "transaction_cost": 1.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": -0.065}}
{"id": "T6_all_20220825_0539", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "TIP", "SGOV"], "decision_date": "2022-08-25", "context_summary": "Max weight deviation: 0.0201, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2551, target=0.2500\n  DOT-USD: current=0.2531, target=0.2500\n  TIP: current=0.2299, target=0.2500\n  SGOV: current=0.2619, 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: 0.0201.\nRebalancing threshold: 0.0500.\n0.0201 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0401, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2551, "DOT-USD": 0.2531, "TIP": 0.2299, "SGOV": 0.2619}, "target_weights": {"XLE": 0.25, "DOT-USD": 0.25, "TIP": 0.25, "SGOV": 0.25}, "max_deviation": 0.0201, "total_turnover": 0.040129, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TIP", "primary_trade": -0.0201}}
{"id": "T6_all_20200929_0540", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BNB-USD", "SHV", "IYR"], "decision_date": "2020-09-29", "context_summary": "Max weight deviation: 0.0111, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2183, target=0.2500\n  BNB-USD: current=0.1849, target=0.2500\n  SHV: current=0.3031, target=0.2500\n  IYR: current=0.2937, 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 BNB-USD", "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 = 0.0331, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2183, "BNB-USD": 0.1849, "SHV": 0.3031, "IYR": 0.2937}, "target_weights": {"VTI": 0.25, "BNB-USD": 0.25, "SHV": 0.25, "IYR": 0.25}, "max_deviation": 0.065108, "total_turnover": 0.033113, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": -0.0651}}
{"id": "T6_all_20210423_0541", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "LQD", "SCHH"], "decision_date": "2021-04-23", "context_summary": "Max weight deviation: 0.0244, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.2593, target=0.2500\n  LINK-USD: current=0.2633, target=0.2500\n  LQD: current=0.2256, target=0.2500\n  SCHH: current=0.2518, 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: 0.0244.\nRebalancing threshold: 0.0500.\n0.0244 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0488, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2593, "LINK-USD": 0.2633, "LQD": 0.2256, "SCHH": 0.2518}, "target_weights": {"XLP": 0.25, "LINK-USD": 0.25, "LQD": 0.25, "SCHH": 0.25}, "max_deviation": 0.0244, "total_turnover": 0.048757, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LQD", "primary_trade": -0.0244}}
{"id": "T6_all_20220905_0542", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "AVAX-USD", "WEAT", "ICSH"], "decision_date": "2022-09-05", "context_summary": "Max weight deviation: 0.0234, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2283, target=0.2500\n  AVAX-USD: current=0.3150, target=0.2500\n  WEAT: current=0.2067, target=0.2500\n  ICSH: 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; sell 0.0650 of AVAX-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0234.\nRebalancing threshold: 0.0500.\n0.0234 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0468, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2283, "AVAX-USD": 0.315, "WEAT": 0.2067, "ICSH": 0.25}, "target_weights": {"QUAL": 0.25, "AVAX-USD": 0.25, "WEAT": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.046848, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": 0.065}}
{"id": "T6_all_20200721_0543", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNB-USD", "SGOV", "BNDX"], "decision_date": "2020-07-21", "context_summary": "Max weight deviation: 0.0211, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2289, target=0.2500\n  BNB-USD: current=0.2607, target=0.2500\n  SGOV: current=0.2421, target=0.2500\n  BNDX: 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: 0.0211.\nRebalancing threshold: 0.0500.\n0.0211 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0580, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2289, "BNB-USD": 0.2607, "SGOV": 0.2421, "BNDX": 0.2683}, "target_weights": {"FXI": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "BNDX": 0.25}, "max_deviation": 0.0211, "total_turnover": 0.058023, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "FXI", "primary_trade": -0.0211}}
{"id": "T6_all_20210617_0544", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ETH-USD", "REZ", "STIP"], "decision_date": "2021-06-17", "context_summary": "Max weight deviation: 0.0172, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2416, target=0.2500\n  ETH-USD: current=0.3149, target=0.2500\n  REZ: current=0.2197, target=0.2500\n  STIP: current=0.2238, 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 ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0172.\nRebalancing threshold: 0.0500.\n0.0172 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0344, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2416, "ETH-USD": 0.3149, "REZ": 0.2197, "STIP": 0.2238}, "target_weights": {"XLB": 0.25, "ETH-USD": 0.25, "REZ": 0.25, "STIP": 0.25}, "max_deviation": 0.064881, "total_turnover": 0.034393, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.0649}}
{"id": "T6_all_20220518_0545", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "MATIC-USD", "VNQI", "WEAT"], "decision_date": "2022-05-18", "context_summary": "Max weight deviation: 0.0240, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2260, target=0.2500\n  MATIC-USD: current=0.2656, target=0.2500\n  VNQI: current=0.2449, target=0.2500\n  WEAT: current=0.2634, 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: 0.0240.\nRebalancing threshold: 0.0500.\n0.0240 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0581, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.226, "MATIC-USD": 0.2656, "VNQI": 0.2449, "WEAT": 0.2634}, "target_weights": {"VLUE": 0.25, "MATIC-USD": 0.25, "VNQI": 0.25, "WEAT": 0.25}, "max_deviation": 0.024, "total_turnover": 0.058072, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VLUE", "primary_trade": -0.024}}
{"id": "T6_all_20211020_0546", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "SGOV", "STIP"], "decision_date": "2021-10-20", "context_summary": "Max weight deviation: 0.0195, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.1850, target=0.2500\n  SOL-USD: current=0.2657, target=0.2500\n  SGOV: current=0.3010, target=0.2500\n  STIP: current=0.2483, 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 XLF", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0195.\nRebalancing threshold: 0.0500.\n0.0195 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0401, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.185, "SOL-USD": 0.2657, "SGOV": 0.301, "STIP": 0.2483}, "target_weights": {"XLF": 0.25, "SOL-USD": 0.25, "SGOV": 0.25, "STIP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.040054, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLF", "primary_trade": -0.065}}
{"id": "T6_all_20201118_0547", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SOL-USD", "DBA", "HAUZ"], "decision_date": "2020-11-18", "context_summary": "Max weight deviation: 0.0353, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2514, target=0.2500\n  SOL-USD: current=0.2189, target=0.2500\n  DBA: current=0.2853, target=0.2500\n  HAUZ: current=0.2444, 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: 0.0353.\nRebalancing threshold: 0.0500.\n0.0353 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0734, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2514, "SOL-USD": 0.2189, "DBA": 0.2853, "HAUZ": 0.2444}, "target_weights": {"EEM": 0.25, "SOL-USD": 0.25, "DBA": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0353, "total_turnover": 0.073371, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBA", "primary_trade": 0.0353}}
{"id": "T6_all_20200325_0548", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "CORN", "XHB"], "decision_date": "2020-03-25", "context_summary": "Max weight deviation: 0.0165, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.3149, target=0.2500\n  ETH-USD: current=0.2239, target=0.2500\n  CORN: current=0.2334, target=0.2500\n  XHB: current=0.2278, 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 VEA", "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": {"VEA": 0.3149, "ETH-USD": 0.2239, "CORN": 0.2334, "XHB": 0.2278}, "target_weights": {"VEA": 0.25, "ETH-USD": 0.25, "CORN": 0.25, "XHB": 0.25}, "max_deviation": 0.064876, "total_turnover": 0.032932, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VEA", "primary_trade": 0.0649}}
{"id": "T6_all_20220520_0549", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BNB-USD", "DBC", "BIL"], "decision_date": "2022-05-20", "context_summary": "Max weight deviation: 0.0111, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2573, target=0.2500\n  BNB-USD: current=0.2611, target=0.2500\n  DBC: current=0.2408, target=0.2500\n  BIL: current=0.2408, 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: 0.0111.\nRebalancing threshold: 0.0500.\n0.0111 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0369, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2573, "BNB-USD": 0.2611, "DBC": 0.2408, "BIL": 0.2408}, "target_weights": {"ACWI": 0.25, "BNB-USD": 0.25, "DBC": 0.25, "BIL": 0.25}, "max_deviation": 0.0111, "total_turnover": 0.036865, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.0111}}
{"id": "T6_all_20210831_0550", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "XRP-USD", "ICSH", "GLD"], "decision_date": "2021-08-31", "context_summary": "Max weight deviation: 0.0219, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.2387, target=0.2500\n  XRP-USD: current=0.2007, target=0.2500\n  ICSH: current=0.2455, target=0.2500\n  GLD: 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 GLD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0219.\nRebalancing threshold: 0.0500.\n0.0219 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0437, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2387, "XRP-USD": 0.2007, "ICSH": 0.2455, "GLD": 0.315}, "target_weights": {"XLV": 0.25, "XRP-USD": 0.25, "ICSH": 0.25, "GLD": 0.25}, "max_deviation": 0.065, "total_turnover": 0.043719, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "GLD", "primary_trade": 0.065}}
{"id": "T6_all_20220422_0551", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "ETH-USD", "HAUZ", "ICSH"], "decision_date": "2022-04-22", "context_summary": "Max weight deviation: 0.0195, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2632, target=0.2500\n  ETH-USD: current=0.2695, target=0.2500\n  HAUZ: current=0.2314, target=0.2500\n  ICSH: current=0.2359, 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: 0.0195.\nRebalancing threshold: 0.0500.\n0.0195 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0653, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2632, "ETH-USD": 0.2695, "HAUZ": 0.2314, "ICSH": 0.2359}, "target_weights": {"VTI": 0.25, "ETH-USD": 0.25, "HAUZ": 0.25, "ICSH": 0.25}, "max_deviation": 0.0195, "total_turnover": 0.065317, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.0195}}
{"id": "T6_all_20190215_0552", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "SLV", "JNK"], "decision_date": "2019-02-15", "context_summary": "Max weight deviation: 0.0213, 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=0.1993, target=0.2500\n  SLV: current=0.2592, target=0.2500\n  JNK: current=0.2265, 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: 0.0213.\nRebalancing threshold: 0.0500.\n0.0213 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0486, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.315, "ADA-USD": 0.1993, "SLV": 0.2592, "JNK": 0.2265}, "target_weights": {"ACWI": 0.25, "ADA-USD": 0.25, "SLV": 0.25, "JNK": 0.25}, "max_deviation": 0.065, "total_turnover": 0.048608, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": 0.065}}
{"id": "T6_all_20180207_0553", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "HYG", "IAU"], "decision_date": "2018-02-07", "context_summary": "Max weight deviation: 0.0163, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2663, target=0.2500\n  ADA-USD: current=0.2458, target=0.2500\n  HYG: current=0.2472, target=0.2500\n  IAU: current=0.2407, 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 = 0.0325, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2663, "ADA-USD": 0.2458, "HYG": 0.2472, "IAU": 0.2407}, "target_weights": {"^VIX": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "IAU": 0.25}, "max_deviation": 0.0163, "total_turnover": 0.032519, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": 0.0163}}
{"id": "T6_all_20160202_0554", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BTC-USD", "BIL", "DBC"], "decision_date": "2016-02-02", "context_summary": "Max weight deviation: 0.0149, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2914, target=0.2500\n  BTC-USD: current=0.1850, target=0.2500\n  BIL: current=0.2762, target=0.2500\n  DBC: current=0.2474, 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: 0.0149.\nRebalancing threshold: 0.0500.\n0.0149 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0310, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2914, "BTC-USD": 0.185, "BIL": 0.2762, "DBC": 0.2474}, "target_weights": {"XLK": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.030962, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.065}}
{"id": "T6_all_20161230_0555", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "DBB", "ICSH"], "decision_date": "2016-12-30", "context_summary": "Max weight deviation: 0.0473, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2694, target=0.2500\n  BTC-USD: current=0.2806, target=0.2500\n  DBB: current=0.2473, target=0.2500\n  ICSH: current=0.2027, 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: 0.0473.\nRebalancing threshold: 0.0500.\n0.0473 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1000, transaction cost = 0.000100 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2694, "BTC-USD": 0.2806, "DBB": 0.2473, "ICSH": 0.2027}, "target_weights": {"USMV": 0.25, "BTC-USD": 0.25, "DBB": 0.25, "ICSH": 0.25}, "max_deviation": 0.0473, "total_turnover": 0.100001, "transaction_cost": 0.0001, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0473}}
{"id": "T6_all_20190612_0556", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "VCIT", "DBB"], "decision_date": "2019-06-12", "context_summary": "Max weight deviation: 0.0359, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.1850, target=0.2500\n  BTC-USD: current=0.2739, target=0.2500\n  VCIT: current=0.2752, target=0.2500\n  DBB: current=0.2659, 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 ^VIX", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0359.\nRebalancing threshold: 0.0500.\n0.0359 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0718, transaction cost = 0.000072 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.185, "BTC-USD": 0.2739, "VCIT": 0.2752, "DBB": 0.2659}, "target_weights": {"^VIX": 0.25, "BTC-USD": 0.25, "VCIT": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.07177, "transaction_cost": 7.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": -0.065}}
{"id": "T6_all_20210429_0557", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ETH-USD", "TLT", "BIL"], "decision_date": "2021-04-29", "context_summary": "Max weight deviation: 0.0300, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2224, target=0.2500\n  ETH-USD: current=0.2800, target=0.2500\n  TLT: current=0.2586, target=0.2500\n  BIL: current=0.2390, 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: 0.0300.\nRebalancing threshold: 0.0500.\n0.0300 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0773, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2224, "ETH-USD": 0.28, "TLT": 0.2586, "BIL": 0.239}, "target_weights": {"VLUE": 0.25, "ETH-USD": 0.25, "TLT": 0.25, "BIL": 0.25}, "max_deviation": 0.03, "total_turnover": 0.077256, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.03}}
{"id": "T6_all_20210805_0558", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "LQD", "IAU"], "decision_date": "2021-08-05", "context_summary": "Max weight deviation: 0.0118, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.1894, target=0.2500\n  BNB-USD: current=0.2274, target=0.2500\n  LQD: current=0.2682, target=0.2500\n  IAU: 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 IAU", "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 = 0.0302, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.1894, "BNB-USD": 0.2274, "LQD": 0.2682, "IAU": 0.315}, "target_weights": {"XLB": 0.25, "BNB-USD": 0.25, "LQD": 0.25, "IAU": 0.25}, "max_deviation": 0.065, "total_turnover": 0.030169, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IAU", "primary_trade": 0.065}}
{"id": "T6_all_20171025_0559", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "BIL", "VCIT"], "decision_date": "2017-10-25", "context_summary": "Max weight deviation: 0.0192, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2523, target=0.2500\n  BTC-USD: current=0.2541, target=0.2500\n  BIL: current=0.2628, target=0.2500\n  VCIT: current=0.2308, 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: 0.0192.\nRebalancing threshold: 0.0500.\n0.0192 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0383, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2523, "BTC-USD": 0.2541, "BIL": 0.2628, "VCIT": 0.2308}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "VCIT": 0.25}, "max_deviation": 0.0192, "total_turnover": 0.038307, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VCIT", "primary_trade": -0.0192}}
{"id": "T6_all_20181105_0560", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "LINK-USD", "TIP", "BNO"], "decision_date": "2018-11-05", "context_summary": "Max weight deviation: 0.0073, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2035, target=0.2500\n  LINK-USD: current=0.2453, target=0.2500\n  TIP: current=0.2364, target=0.2500\n  BNO: current=0.3147, 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 0.0647 of BNO", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0073.\nRebalancing threshold: 0.0500.\n0.0073 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0146, transaction cost = 0.000015 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2035, "LINK-USD": 0.2453, "TIP": 0.2364, "BNO": 0.3147}, "target_weights": {"USMV": 0.25, "LINK-USD": 0.25, "TIP": 0.25, "BNO": 0.25}, "max_deviation": 0.06472, "total_turnover": 0.014577, "transaction_cost": 1.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": 0.0647}}
{"id": "T6_all_20220309_0561", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "DBC", "VNQI"], "decision_date": "2022-03-09", "context_summary": "Max weight deviation: 0.0280, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2498, target=0.2500\n  BTC-USD: current=0.2732, target=0.2500\n  DBC: current=0.2220, target=0.2500\n  VNQI: current=0.2549, 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: 0.0280.\nRebalancing threshold: 0.0500.\n0.0280 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0564, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2498, "BTC-USD": 0.2732, "DBC": 0.222, "VNQI": 0.2549}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "DBC": 0.25, "VNQI": 0.25}, "max_deviation": 0.028, "total_turnover": 0.056359, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBC", "primary_trade": -0.028}}
{"id": "T6_all_20221129_0562", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "CPER", "TLT"], "decision_date": "2022-11-29", "context_summary": "Max weight deviation: 0.0246, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.3151, target=0.2500\n  XRP-USD: current=0.2688, target=0.2500\n  CPER: current=0.2210, target=0.2500\n  TLT: current=0.1951, 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 XLRE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0246.\nRebalancing threshold: 0.0500.\n0.0246 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0635, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3151, "XRP-USD": 0.2688, "CPER": 0.221, "TLT": 0.1951}, "target_weights": {"XLRE": 0.25, "XRP-USD": 0.25, "CPER": 0.25, "TLT": 0.25}, "max_deviation": 0.065083, "total_turnover": 0.06348, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": 0.0651}}
{"id": "T6_all_20200804_0563", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "MATIC-USD", "INDS", "PPLT"], "decision_date": "2020-08-04", "context_summary": "Max weight deviation: 0.0278, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2680, target=0.2500\n  MATIC-USD: current=0.2711, target=0.2500\n  INDS: current=0.2222, target=0.2500\n  PPLT: current=0.2388, 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 = 0.0781, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.268, "MATIC-USD": 0.2711, "INDS": 0.2222, "PPLT": 0.2388}, "target_weights": {"XLK": 0.25, "MATIC-USD": 0.25, "INDS": 0.25, "PPLT": 0.25}, "max_deviation": 0.0278, "total_turnover": 0.078142, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "INDS", "primary_trade": -0.0278}}
{"id": "T6_all_20200812_0564", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "XRP-USD", "SCHP", "SOYB"], "decision_date": "2020-08-12", "context_summary": "Max weight deviation: 0.0262, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.1937, target=0.2500\n  XRP-USD: current=0.3150, target=0.2500\n  SCHP: current=0.2530, target=0.2500\n  SOYB: 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; sell 0.0650 of XRP-USD", "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 = 0.0549, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.1937, "XRP-USD": 0.315, "SCHP": 0.253, "SOYB": 0.2383}, "target_weights": {"XLK": 0.25, "XRP-USD": 0.25, "SCHP": 0.25, "SOYB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.054916, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": 0.065}}
{"id": "T6_all_20221025_0565", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BNB-USD", "REZ", "BNO"], "decision_date": "2022-10-25", "context_summary": "Max weight deviation: 0.0280, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2274, target=0.2500\n  BNB-USD: current=0.2416, target=0.2500\n  REZ: current=0.2530, target=0.2500\n  BNO: current=0.2780, 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: 0.0280.\nRebalancing threshold: 0.0500.\n0.0280 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0619, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2274, "BNB-USD": 0.2416, "REZ": 0.253, "BNO": 0.278}, "target_weights": {"XLE": 0.25, "BNB-USD": 0.25, "REZ": 0.25, "BNO": 0.25}, "max_deviation": 0.028, "total_turnover": 0.061922, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": 0.028}}
{"id": "T6_all_20210318_0566", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "MATIC-USD", "BIL", "SHV"], "decision_date": "2021-03-18", "context_summary": "Max weight deviation: 0.0337, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2176, target=0.2500\n  MATIC-USD: current=0.2120, target=0.2500\n  BIL: current=0.3150, target=0.2500\n  SHV: 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": "yes; sell 0.0650 of BIL", "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 = 0.0731, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2176, "MATIC-USD": 0.212, "BIL": 0.315, "SHV": 0.2554}, "target_weights": {"QQQ": 0.25, "MATIC-USD": 0.25, "BIL": 0.25, "SHV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.0731, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.065}}
{"id": "T6_all_20210618_0567", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "WEAT", "JNK"], "decision_date": "2021-06-18", "context_summary": "Max weight deviation: 0.0282, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2559, target=0.2500\n  ETH-USD: current=0.2473, target=0.2500\n  WEAT: current=0.2218, target=0.2500\n  JNK: current=0.2749, 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: 0.0282.\nRebalancing threshold: 0.0500.\n0.0282 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0617, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2559, "ETH-USD": 0.2473, "WEAT": 0.2218, "JNK": 0.2749}, "target_weights": {"QUAL": 0.25, "ETH-USD": 0.25, "WEAT": 0.25, "JNK": 0.25}, "max_deviation": 0.0282, "total_turnover": 0.061733, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "WEAT", "primary_trade": -0.0282}}
{"id": "T6_all_20210716_0568", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "MATIC-USD", "DBA", "SGOV"], "decision_date": "2021-07-16", "context_summary": "Max weight deviation: 0.0248, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.1850, target=0.2500\n  MATIC-USD: current=0.2762, target=0.2500\n  DBA: current=0.2972, target=0.2500\n  SGOV: 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": "yes; buy 0.0650 of XLK", "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 = 0.0560, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.185, "MATIC-USD": 0.2762, "DBA": 0.2972, "SGOV": 0.2416}, "target_weights": {"XLK": 0.25, "MATIC-USD": 0.25, "DBA": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.056024, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": -0.065}}
{"id": "T6_all_20160218_0569", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD", "IEF", "CPER"], "decision_date": "2016-02-18", "context_summary": "Max weight deviation: 0.0202, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2561, target=0.2500\n  BTC-USD: current=0.2545, target=0.2500\n  IEF: current=0.2597, target=0.2500\n  CPER: current=0.2298, 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 = 0.0405, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2561, "BTC-USD": 0.2545, "IEF": 0.2597, "CPER": 0.2298}, "target_weights": {"QUAL": 0.25, "BTC-USD": 0.25, "IEF": 0.25, "CPER": 0.25}, "max_deviation": 0.0202, "total_turnover": 0.040466, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CPER", "primary_trade": -0.0202}}
{"id": "T6_all_20220929_0570", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "ICSH", "SLV"], "decision_date": "2022-09-29", "context_summary": "Max weight deviation: 0.0314, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.3062, target=0.2500\n  ADA-USD: current=0.2342, target=0.2500\n  ICSH: current=0.2746, 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: 0.0314.\nRebalancing threshold: 0.0500.\n0.0314 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0781, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.3062, "ADA-USD": 0.2342, "ICSH": 0.2746, "SLV": 0.185}, "target_weights": {"USMV": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "SLV": 0.25}, "max_deviation": 0.065038, "total_turnover": 0.078078, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SLV", "primary_trade": -0.065}}
{"id": "T6_all_20200413_0571", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ADA-USD", "SLV", "SHV"], "decision_date": "2020-04-13", "context_summary": "Max weight deviation: 0.0473, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2027, target=0.2500\n  ADA-USD: current=0.2703, target=0.2500\n  SLV: current=0.2628, target=0.2500\n  SHV: current=0.2642, 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: 0.0473.\nRebalancing threshold: 0.0500.\n0.0473 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0947, transaction cost = 0.000095 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2027, "ADA-USD": 0.2703, "SLV": 0.2628, "SHV": 0.2642}, "target_weights": {"VEA": 0.25, "ADA-USD": 0.25, "SLV": 0.25, "SHV": 0.25}, "max_deviation": 0.0473, "total_turnover": 0.094672, "transaction_cost": 9.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VEA", "primary_trade": -0.0473}}
{"id": "T6_all_20200227_0572", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "UNG", "ICSH"], "decision_date": "2020-02-27", "context_summary": "Max weight deviation: 0.0308, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.1958, target=0.2500\n  BNB-USD: current=0.2790, target=0.2500\n  UNG: current=0.3151, target=0.2500\n  ICSH: current=0.2102, 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 UNG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0308.\nRebalancing threshold: 0.0500.\n0.0308 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0891, transaction cost = 0.000089 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.1958, "BNB-USD": 0.279, "UNG": 0.3151, "ICSH": 0.2102}, "target_weights": {"XLI": 0.25, "BNB-USD": 0.25, "UNG": 0.25, "ICSH": 0.25}, "max_deviation": 0.065066, "total_turnover": 0.089101, "transaction_cost": 8.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": 0.0651}}
{"id": "T6_all_20220311_0573", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "HYG", "BNO"], "decision_date": "2022-03-11", "context_summary": "Max weight deviation: 0.0110, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2445, target=0.2500\n  ADA-USD: current=0.2610, target=0.2500\n  HYG: current=0.2414, target=0.2500\n  BNO: 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": "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 = 0.0283, transaction cost = 0.000028 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2445, "ADA-USD": 0.261, "HYG": 0.2414, "BNO": 0.2531}, "target_weights": {"XLB": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "BNO": 0.25}, "max_deviation": 0.011, "total_turnover": 0.028252, "transaction_cost": 2.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.011}}
{"id": "T6_all_20220223_0574", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "XRP-USD", "MORT", "WEAT"], "decision_date": "2022-02-23", "context_summary": "Max weight deviation: 0.0217, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2111, target=0.2500\n  XRP-USD: current=0.1877, target=0.2500\n  MORT: current=0.2862, target=0.2500\n  WEAT: 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 WEAT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0217.\nRebalancing threshold: 0.0500.\n0.0217 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0676, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2111, "XRP-USD": 0.1877, "MORT": 0.2862, "WEAT": 0.315}, "target_weights": {"XLB": 0.25, "XRP-USD": 0.25, "MORT": 0.25, "WEAT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.067561, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "WEAT", "primary_trade": 0.065}}
{"id": "T6_all_20211210_0575", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "SGOV", "DBA"], "decision_date": "2021-12-10", "context_summary": "Max weight deviation: 0.0215, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2539, target=0.2500\n  ADA-USD: current=0.2651, target=0.2500\n  SGOV: current=0.2285, target=0.2500\n  DBA: current=0.2525, 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: 0.0215.\nRebalancing threshold: 0.0500.\n0.0215 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0429, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2539, "ADA-USD": 0.2651, "SGOV": 0.2285, "DBA": 0.2525}, "target_weights": {"QUAL": 0.25, "ADA-USD": 0.25, "SGOV": 0.25, "DBA": 0.25}, "max_deviation": 0.0215, "total_turnover": 0.04295, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": -0.0215}}
{"id": "T6_all_20160407_0576", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BTC-USD", "UNG", "XHB"], "decision_date": "2016-04-07", "context_summary": "Max weight deviation: 0.0193, 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=0.2183, target=0.2500\n  UNG: current=0.2823, target=0.2500\n  XHB: current=0.3143, 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: 0.0193.\nRebalancing threshold: 0.0500.\n0.0193 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0575, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.185, "BTC-USD": 0.2183, "UNG": 0.2823, "XHB": 0.3143}, "target_weights": {"QQQ": 0.25, "BTC-USD": 0.25, "UNG": 0.25, "XHB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.057531, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "QQQ", "primary_trade": -0.065}}
{"id": "T6_all_20191108_0577", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "ICSH", "VCIT"], "decision_date": "2019-11-08", "context_summary": "Max weight deviation: 0.0436, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2524, target=0.2500\n  BTC-USD: current=0.2750, target=0.2500\n  ICSH: current=0.2064, target=0.2500\n  VCIT: 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: 0.0436.\nRebalancing threshold: 0.0500.\n0.0436 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0871, transaction cost = 0.000087 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2524, "BTC-USD": 0.275, "ICSH": 0.2064, "VCIT": 0.2662}, "target_weights": {"FXI": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "VCIT": 0.25}, "max_deviation": 0.0436, "total_turnover": 0.087101, "transaction_cost": 8.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0436}}
{"id": "T6_all_20221018_0578", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SOL-USD", "MORT", "LQD"], "decision_date": "2022-10-18", "context_summary": "Max weight deviation: 0.0367, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2982, target=0.2500\n  SOL-USD: current=0.1850, target=0.2500\n  MORT: current=0.2430, target=0.2500\n  LQD: current=0.2738, 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: 0.0367.\nRebalancing threshold: 0.0500.\n0.0367 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0813, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2982, "SOL-USD": 0.185, "MORT": 0.243, "LQD": 0.2738}, "target_weights": {"EEM": 0.25, "SOL-USD": 0.25, "MORT": 0.25, "LQD": 0.25}, "max_deviation": 0.064967, "total_turnover": 0.081287, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": -0.065}}
{"id": "T6_all_20220302_0579", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "AVAX-USD", "GLD", "ICSH"], "decision_date": "2022-03-02", "context_summary": "Max weight deviation: 0.0278, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2535, target=0.2500\n  AVAX-USD: current=0.2585, target=0.2500\n  GLD: current=0.2658, target=0.2500\n  ICSH: current=0.2222, 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 = 0.0556, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2535, "AVAX-USD": 0.2585, "GLD": 0.2658, "ICSH": 0.2222}, "target_weights": {"XLU": 0.25, "AVAX-USD": 0.25, "GLD": 0.25, "ICSH": 0.25}, "max_deviation": 0.0278, "total_turnover": 0.055555, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0278}}
{"id": "T6_all_20220112_0580", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "IYR", "PALL"], "decision_date": "2022-01-12", "context_summary": "Max weight deviation: 0.0221, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.3121, target=0.2500\n  BTC-USD: current=0.1850, target=0.2500\n  IYR: current=0.1965, target=0.2500\n  PALL: current=0.3065, 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: 0.0221.\nRebalancing threshold: 0.0500.\n0.0221 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0805, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.3121, "BTC-USD": 0.185, "IYR": 0.1965, "PALL": 0.3065}, "target_weights": {"XLU": 0.25, "BTC-USD": 0.25, "IYR": 0.25, "PALL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.080532, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.065}}
{"id": "T6_all_20180524_0581", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ETH-USD", "ITB", "CPER"], "decision_date": "2018-05-24", "context_summary": "Max weight deviation: 0.0055, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2520, target=0.2500\n  ETH-USD: current=0.2445, target=0.2500\n  ITB: current=0.2538, target=0.2500\n  CPER: current=0.2497, 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: 0.0055.\nRebalancing threshold: 0.0500.\n0.0055 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0116, transaction cost = 0.000012 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.252, "ETH-USD": 0.2445, "ITB": 0.2538, "CPER": 0.2497}, "target_weights": {"IWM": 0.25, "ETH-USD": 0.25, "ITB": 0.25, "CPER": 0.25}, "max_deviation": 0.0055, "total_turnover": 0.011618, "transaction_cost": 1.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0055}}
{"id": "T6_all_20210630_0582", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BNB-USD", "SGOV", "SHY"], "decision_date": "2021-06-30", "context_summary": "Max weight deviation: 0.0308, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.3149, target=0.2500\n  BNB-USD: current=0.2221, target=0.2500\n  SGOV: current=0.2443, target=0.2500\n  SHY: current=0.2187, 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 VTI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0308.\nRebalancing threshold: 0.0500.\n0.0308 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0615, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.3149, "BNB-USD": 0.2221, "SGOV": 0.2443, "SHY": 0.2187}, "target_weights": {"VTI": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "SHY": 0.25}, "max_deviation": 0.064934, "total_turnover": 0.061514, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VTI", "primary_trade": 0.0649}}
{"id": "T6_all_20210317_0583", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BNB-USD", "CORN", "INDS"], "decision_date": "2021-03-17", "context_summary": "Max weight deviation: 0.0129, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2556, target=0.2500\n  BNB-USD: current=0.2371, target=0.2500\n  CORN: current=0.2574, target=0.2500\n  INDS: 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: 0.0129.\nRebalancing threshold: 0.0500.\n0.0129 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0261, transaction cost = 0.000026 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2556, "BNB-USD": 0.2371, "CORN": 0.2574, "INDS": 0.2499}, "target_weights": {"XLY": 0.25, "BNB-USD": 0.25, "CORN": 0.25, "INDS": 0.25}, "max_deviation": 0.0129, "total_turnover": 0.02608, "transaction_cost": 2.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": -0.0129}}
{"id": "T6_all_20180614_0584", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "VNQ", "PDBC"], "decision_date": "2018-06-14", "context_summary": "Max weight deviation: 0.0351, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.1850, target=0.2500\n  ADA-USD: current=0.2724, target=0.2500\n  VNQ: current=0.2278, target=0.2500\n  PDBC: current=0.3148, 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 ACWI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0351.\nRebalancing threshold: 0.0500.\n0.0351 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0942, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.185, "ADA-USD": 0.2724, "VNQ": 0.2278, "PDBC": 0.3148}, "target_weights": {"ACWI": 0.25, "ADA-USD": 0.25, "VNQ": 0.25, "PDBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.094157, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": -0.065}}
{"id": "T6_all_20170202_0585", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BTC-USD", "MORT", "BIL"], "decision_date": "2017-02-02", "context_summary": "Max weight deviation: 0.0388, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2657, target=0.2500\n  BTC-USD: current=0.2713, target=0.2500\n  MORT: current=0.2112, target=0.2500\n  BIL: current=0.2519, 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: 0.0388.\nRebalancing threshold: 0.0500.\n0.0388 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0776, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2657, "BTC-USD": 0.2713, "MORT": 0.2112, "BIL": 0.2519}, "target_weights": {"MTUM": 0.25, "BTC-USD": 0.25, "MORT": 0.25, "BIL": 0.25}, "max_deviation": 0.0388, "total_turnover": 0.077605, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MORT", "primary_trade": -0.0388}}
{"id": "T6_all_20220414_0586", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ADA-USD", "IAU", "BIL"], "decision_date": "2022-04-14", "context_summary": "Max weight deviation: 0.0089, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.1987, target=0.2500\n  ADA-USD: current=0.2432, target=0.2500\n  IAU: current=0.3148, target=0.2500\n  BIL: current=0.2432, 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 IAU", "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 = 0.0177, transaction cost = 0.000018 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.1987, "ADA-USD": 0.2432, "IAU": 0.3148, "BIL": 0.2432}, "target_weights": {"XLF": 0.25, "ADA-USD": 0.25, "IAU": 0.25, "BIL": 0.25}, "max_deviation": 0.06477, "total_turnover": 0.017733, "transaction_cost": 1.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IAU", "primary_trade": 0.0648}}
{"id": "T6_all_20190403_0587", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "IYR", "SOYB"], "decision_date": "2019-04-03", "context_summary": "Max weight deviation: 0.0460, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2383, target=0.2500\n  BNB-USD: current=0.2960, target=0.2500\n  IYR: current=0.2346, target=0.2500\n  SOYB: 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: 0.0460.\nRebalancing threshold: 0.0500.\n0.0460 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0920, transaction cost = 0.000092 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2383, "BNB-USD": 0.296, "IYR": 0.2346, "SOYB": 0.2311}, "target_weights": {"EEM": 0.25, "BNB-USD": 0.25, "IYR": 0.25, "SOYB": 0.25}, "max_deviation": 0.046, "total_turnover": 0.091963, "transaction_cost": 9.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.046}}
{"id": "T6_all_20180516_0588", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "XRP-USD", "BIL", "IGOV"], "decision_date": "2018-05-16", "context_summary": "Max weight deviation: 0.0278, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.3150, target=0.2500\n  XRP-USD: current=0.2196, target=0.2500\n  BIL: current=0.2292, target=0.2500\n  IGOV: current=0.2362, 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: 0.0278.\nRebalancing threshold: 0.0500.\n0.0278 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0557, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.315, "XRP-USD": 0.2196, "BIL": 0.2292, "IGOV": 0.2362}, "target_weights": {"ACWI": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.055685, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": 0.065}}
{"id": "T6_all_20200424_0589", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "PPLT", "VNQI"], "decision_date": "2020-04-24", "context_summary": "Max weight deviation: 0.0305, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2195, target=0.2500\n  ADA-USD: current=0.2458, target=0.2500\n  PPLT: current=0.2774, target=0.2500\n  VNQI: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0305.\nRebalancing threshold: 0.0500.\n0.0305 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0694, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2195, "ADA-USD": 0.2458, "PPLT": 0.2774, "VNQI": 0.2573}, "target_weights": {"XLY": 0.25, "ADA-USD": 0.25, "PPLT": 0.25, "VNQI": 0.25}, "max_deviation": 0.0305, "total_turnover": 0.069404, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLY", "primary_trade": -0.0305}}
{"id": "T6_all_20211019_0590", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "JNK", "UNG"], "decision_date": "2021-10-19", "context_summary": "Max weight deviation: 0.0196, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2330, target=0.2500\n  ETH-USD: current=0.2038, target=0.2500\n  JNK: current=0.2483, target=0.2500\n  UNG: 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 UNG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0196.\nRebalancing threshold: 0.0500.\n0.0196 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0391, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.233, "ETH-USD": 0.2038, "JNK": 0.2483, "UNG": 0.3149}, "target_weights": {"EEM": 0.25, "ETH-USD": 0.25, "JNK": 0.25, "UNG": 0.25}, "max_deviation": 0.064896, "total_turnover": 0.039107, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": 0.0649}}
{"id": "T6_all_20220118_0591", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "DBA", "ICSH"], "decision_date": "2022-01-18", "context_summary": "Max weight deviation: 0.0344, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2324, target=0.2500\n  MATIC-USD: current=0.2844, target=0.2500\n  DBA: current=0.2337, target=0.2500\n  ICSH: current=0.2495, 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: 0.0344.\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": {"IWM": 0.2324, "MATIC-USD": 0.2844, "DBA": 0.2337, "ICSH": 0.2495}, "target_weights": {"IWM": 0.25, "MATIC-USD": 0.25, "DBA": 0.25, "ICSH": 0.25}, "max_deviation": 0.0344, "total_turnover": 0.068867, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": 0.0344}}
{"id": "T6_all_20210126_0592", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "ICSH", "SCHH"], "decision_date": "2021-01-26", "context_summary": "Max weight deviation: 0.0211, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.3150, target=0.2500\n  BTC-USD: current=0.1921, target=0.2500\n  ICSH: current=0.2315, target=0.2500\n  SCHH: current=0.2614, 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: 0.0211.\nRebalancing threshold: 0.0500.\n0.0211 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0496, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.315, "BTC-USD": 0.1921, "ICSH": 0.2315, "SCHH": 0.2614}, "target_weights": {"EEM": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "SCHH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.049551, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": 0.065}}
{"id": "T6_all_20181113_0593", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BTC-USD", "CORN", "VNQ"], "decision_date": "2018-11-13", "context_summary": "Max weight deviation: 0.0076, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2482, target=0.2500\n  BTC-USD: current=0.2455, target=0.2500\n  CORN: current=0.2487, target=0.2500\n  VNQ: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0076.\nRebalancing threshold: 0.0500.\n0.0076 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0152, transaction cost = 0.000015 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2482, "BTC-USD": 0.2455, "CORN": 0.2487, "VNQ": 0.2576}, "target_weights": {"EWJ": 0.25, "BTC-USD": 0.25, "CORN": 0.25, "VNQ": 0.25}, "max_deviation": 0.0076, "total_turnover": 0.015238, "transaction_cost": 1.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VNQ", "primary_trade": 0.0076}}
{"id": "T6_all_20180223_0594", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ADA-USD", "SHV", "VNQ"], "decision_date": "2018-02-23", "context_summary": "Max weight deviation: 0.0256, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.1850, target=0.2500\n  ADA-USD: current=0.2777, target=0.2500\n  SHV: current=0.2977, target=0.2500\n  VNQ: current=0.2396, 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 EEM", "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 = 0.0594, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.185, "ADA-USD": 0.2777, "SHV": 0.2977, "VNQ": 0.2396}, "target_weights": {"EEM": 0.25, "ADA-USD": 0.25, "SHV": 0.25, "VNQ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059383, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": -0.065}}
{"id": "T6_all_20181003_0595", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD", "UNG", "ITB"], "decision_date": "2018-10-03", "context_summary": "Max weight deviation: 0.0181, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2345, target=0.2500\n  LINK-USD: current=0.2678, target=0.2500\n  UNG: current=0.2319, target=0.2500\n  ITB: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0181.\nRebalancing threshold: 0.0500.\n0.0181 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0673, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2345, "LINK-USD": 0.2678, "UNG": 0.2319, "ITB": 0.2658}, "target_weights": {"EFA": 0.25, "LINK-USD": 0.25, "UNG": 0.25, "ITB": 0.25}, "max_deviation": 0.0181, "total_turnover": 0.067314, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": -0.0181}}
{"id": "T6_all_20221206_0596", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "LINK-USD", "XHB", "DBB"], "decision_date": "2022-12-06", "context_summary": "Max weight deviation: 0.0291, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.1850, target=0.2500\n  LINK-USD: current=0.2940, target=0.2500\n  XHB: current=0.2357, target=0.2500\n  DBB: current=0.2853, 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 ^VIX", "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 = 0.0711, transaction cost = 0.000071 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.185, "LINK-USD": 0.294, "XHB": 0.2357, "DBB": 0.2853}, "target_weights": {"^VIX": 0.25, "LINK-USD": 0.25, "XHB": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.071054, "transaction_cost": 7.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": -0.065}}
{"id": "T6_all_20181005_0597", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "VNQ", "PDBC"], "decision_date": "2018-10-05", "context_summary": "Max weight deviation: 0.0223, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2622, target=0.2500\n  LINK-USD: current=0.2566, target=0.2500\n  VNQ: current=0.2534, target=0.2500\n  PDBC: current=0.2277, 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: 0.0223.\nRebalancing threshold: 0.0500.\n0.0223 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0446, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2622, "LINK-USD": 0.2566, "VNQ": 0.2534, "PDBC": 0.2277}, "target_weights": {"XLI": 0.25, "LINK-USD": 0.25, "VNQ": 0.25, "PDBC": 0.25}, "max_deviation": 0.0223, "total_turnover": 0.044611, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "PDBC", "primary_trade": -0.0223}}
{"id": "T6_all_20221014_0598", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "XRP-USD", "WEAT", "INDS"], "decision_date": "2022-10-14", "context_summary": "Max weight deviation: 0.0165, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.3150, target=0.2500\n  XRP-USD: current=0.1854, target=0.2500\n  WEAT: current=0.2610, target=0.2500\n  INDS: current=0.2386, 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 EFA", "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 = 0.0386, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.315, "XRP-USD": 0.1854, "WEAT": 0.261, "INDS": 0.2386}, "target_weights": {"EFA": 0.25, "XRP-USD": 0.25, "WEAT": 0.25, "INDS": 0.25}, "max_deviation": 0.065, "total_turnover": 0.038644, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EFA", "primary_trade": 0.065}}
{"id": "T6_all_20210409_0599", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "DOT-USD", "HYG", "ITB"], "decision_date": "2021-04-09", "context_summary": "Max weight deviation: 0.0184, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2413, target=0.2500\n  DOT-USD: current=0.2367, target=0.2500\n  HYG: current=0.2536, target=0.2500\n  ITB: current=0.2684, 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 = 0.0440, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2413, "DOT-USD": 0.2367, "HYG": 0.2536, "ITB": 0.2684}, "target_weights": {"XLU": 0.25, "DOT-USD": 0.25, "HYG": 0.25, "ITB": 0.25}, "max_deviation": 0.0184, "total_turnover": 0.044025, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": 0.0184}}
{"id": "T6_all_20210222_0600", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD", "IEF", "DBC"], "decision_date": "2021-02-22", "context_summary": "Max weight deviation: 0.0114, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2854, target=0.2500\n  BNB-USD: current=0.2306, target=0.2500\n  IEF: current=0.1850, target=0.2500\n  DBC: current=0.2990, 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 IEF", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0114.\nRebalancing threshold: 0.0500.\n0.0114 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0296, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2854, "BNB-USD": 0.2306, "IEF": 0.185, "DBC": 0.299}, "target_weights": {"QQQ": 0.25, "BNB-USD": 0.25, "IEF": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.029595, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IEF", "primary_trade": -0.065}}
{"id": "T6_all_20221118_0601", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "ICSH", "MORT"], "decision_date": "2022-11-18", "context_summary": "Max weight deviation: 0.0223, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2723, target=0.2500\n  LINK-USD: current=0.2441, target=0.2500\n  ICSH: current=0.2282, target=0.2500\n  MORT: 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: 0.0223.\nRebalancing threshold: 0.0500.\n0.0223 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0553, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2723, "LINK-USD": 0.2441, "ICSH": 0.2282, "MORT": 0.2554}, "target_weights": {"XLY": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "MORT": 0.25}, "max_deviation": 0.0223, "total_turnover": 0.055281, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLY", "primary_trade": 0.0223}}
{"id": "T6_all_20211111_0602", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "DBC", "SHY"], "decision_date": "2021-11-11", "context_summary": "Max weight deviation: 0.0369, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2301, target=0.2500\n  ETH-USD: current=0.3151, target=0.2500\n  DBC: current=0.2263, target=0.2500\n  SHY: current=0.2285, 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 ETH-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0369.\nRebalancing threshold: 0.0500.\n0.0369 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0739, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2301, "ETH-USD": 0.3151, "DBC": 0.2263, "SHY": 0.2285}, "target_weights": {"QUAL": 0.25, "ETH-USD": 0.25, "DBC": 0.25, "SHY": 0.25}, "max_deviation": 0.065055, "total_turnover": 0.073897, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.0651}}
{"id": "T6_all_20191029_0603", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "SHY", "PDBC"], "decision_date": "2019-10-29", "context_summary": "Max weight deviation: 0.0175, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2404, target=0.2500\n  BTC-USD: current=0.2675, target=0.2500\n  SHY: current=0.2524, target=0.2500\n  PDBC: current=0.2398, 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: 0.0175.\nRebalancing threshold: 0.0500.\n0.0175 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0397, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2404, "BTC-USD": 0.2675, "SHY": 0.2524, "PDBC": 0.2398}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "SHY": 0.25, "PDBC": 0.25}, "max_deviation": 0.0175, "total_turnover": 0.039667, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.0175}}
{"id": "T6_all_20220419_0604", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "AVAX-USD", "BNO", "MORT"], "decision_date": "2022-04-19", "context_summary": "Max weight deviation: 0.0238, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2641, target=0.2500\n  AVAX-USD: current=0.1849, target=0.2500\n  BNO: current=0.2609, target=0.2500\n  MORT: current=0.2901, 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 AVAX-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0238.\nRebalancing threshold: 0.0500.\n0.0238 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0477, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2641, "AVAX-USD": 0.1849, "BNO": 0.2609, "MORT": 0.2901}, "target_weights": {"XLRE": 0.25, "AVAX-USD": 0.25, "BNO": 0.25, "MORT": 0.25}, "max_deviation": 0.065051, "total_turnover": 0.047678, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": -0.0651}}
{"id": "T6_all_20210910_0605", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SOL-USD", "SHY", "SGOV"], "decision_date": "2021-09-10", "context_summary": "Max weight deviation: 0.0067, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2442, target=0.2500\n  SOL-USD: current=0.2449, target=0.2500\n  SHY: current=0.2542, target=0.2500\n  SGOV: current=0.2567, 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: 0.0067.\nRebalancing threshold: 0.0500.\n0.0067 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0218, transaction cost = 0.000022 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2442, "SOL-USD": 0.2449, "SHY": 0.2542, "SGOV": 0.2567}, "target_weights": {"XLI": 0.25, "SOL-USD": 0.25, "SHY": 0.25, "SGOV": 0.25}, "max_deviation": 0.0067, "total_turnover": 0.021805, "transaction_cost": 2.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0067}}
{"id": "T6_all_20210915_0606", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "VCIT", "SGOV"], "decision_date": "2021-09-15", "context_summary": "Max weight deviation: 0.0138, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2679, target=0.2500\n  LINK-USD: current=0.2326, target=0.2500\n  VCIT: current=0.1850, target=0.2500\n  SGOV: current=0.3145, 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 VCIT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0138.\nRebalancing threshold: 0.0500.\n0.0138 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0351, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2679, "LINK-USD": 0.2326, "VCIT": 0.185, "SGOV": 0.3145}, "target_weights": {"XLB": 0.25, "LINK-USD": 0.25, "VCIT": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.035077, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VCIT", "primary_trade": -0.065}}
{"id": "T6_all_20200117_0607", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "INDS", "SHV"], "decision_date": "2020-01-17", "context_summary": "Max weight deviation: 0.0092, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2592, target=0.2500\n  MATIC-USD: current=0.2531, target=0.2500\n  INDS: current=0.2453, target=0.2500\n  SHV: current=0.2423, 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: 0.0092.\nRebalancing threshold: 0.0500.\n0.0092 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0247, transaction cost = 0.000025 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2592, "MATIC-USD": 0.2531, "INDS": 0.2453, "SHV": 0.2423}, "target_weights": {"QUAL": 0.25, "MATIC-USD": 0.25, "INDS": 0.25, "SHV": 0.25}, "max_deviation": 0.0092, "total_turnover": 0.02473, "transaction_cost": 2.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "QUAL", "primary_trade": 0.0092}}
{"id": "T6_all_20160704_0608", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "SLV", "ITB"], "decision_date": "2016-07-04", "context_summary": "Max weight deviation: 0.0255, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.1850, target=0.2500\n  BTC-USD: current=0.2920, target=0.2500\n  SLV: current=0.2586, target=0.2500\n  ITB: current=0.2645, 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 EEM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0255.\nRebalancing threshold: 0.0500.\n0.0255 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0511, transaction cost = 0.000051 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.185, "BTC-USD": 0.292, "SLV": 0.2586, "ITB": 0.2645}, "target_weights": {"EEM": 0.25, "BTC-USD": 0.25, "SLV": 0.25, "ITB": 0.25}, "max_deviation": 0.065047, "total_turnover": 0.051071, "transaction_cost": 5.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": -0.065}}
{"id": "T6_all_20190123_0609", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "REZ", "BIL"], "decision_date": "2019-01-23", "context_summary": "Max weight deviation: 0.0337, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2446, target=0.2500\n  XRP-USD: current=0.2837, target=0.2500\n  REZ: current=0.2415, target=0.2500\n  BIL: current=0.2302, 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": {"EWJ": 0.2446, "XRP-USD": 0.2837, "REZ": 0.2415, "BIL": 0.2302}, "target_weights": {"EWJ": 0.25, "XRP-USD": 0.25, "REZ": 0.25, "BIL": 0.25}, "max_deviation": 0.0337, "total_turnover": 0.067359, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": 0.0337}}
{"id": "T6_all_20210212_0610", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "XRP-USD", "PALL", "IYR"], "decision_date": "2021-02-12", "context_summary": "Max weight deviation: 0.0282, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2521, target=0.2500\n  XRP-USD: current=0.2410, target=0.2500\n  PALL: current=0.3150, target=0.2500\n  IYR: current=0.1919, 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 PALL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0282.\nRebalancing threshold: 0.0500.\n0.0282 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0582, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2521, "XRP-USD": 0.241, "PALL": 0.315, "IYR": 0.1919}, "target_weights": {"IVV": 0.25, "XRP-USD": 0.25, "PALL": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.058185, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "PALL", "primary_trade": 0.065}}
{"id": "T6_all_20191220_0611", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "SLV", "XHB"], "decision_date": "2019-12-20", "context_summary": "Max weight deviation: 0.0367, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2133, target=0.2500\n  BTC-USD: current=0.2561, target=0.2500\n  SLV: current=0.2859, target=0.2500\n  XHB: 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: 0.0367.\nRebalancing threshold: 0.0500.\n0.0367 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0840, transaction cost = 0.000084 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2133, "BTC-USD": 0.2561, "SLV": 0.2859, "XHB": 0.2447}, "target_weights": {"FXI": 0.25, "BTC-USD": 0.25, "SLV": 0.25, "XHB": 0.25}, "max_deviation": 0.0367, "total_turnover": 0.084011, "transaction_cost": 8.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "FXI", "primary_trade": -0.0367}}
{"id": "T6_all_20201029_0612", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "MATIC-USD", "SCHP", "ICSH"], "decision_date": "2020-10-29", "context_summary": "Max weight deviation: 0.0316, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.3088, target=0.2500\n  MATIC-USD: current=0.1850, target=0.2500\n  SCHP: current=0.2043, target=0.2500\n  ICSH: current=0.3018, 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 MATIC-USD", "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 = 0.1076, transaction cost = 0.000108 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.3088, "MATIC-USD": 0.185, "SCHP": 0.2043, "ICSH": 0.3018}, "target_weights": {"XLB": 0.25, "MATIC-USD": 0.25, "SCHP": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.10758, "transaction_cost": 0.000108, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": -0.065}}
{"id": "T6_all_20170714_0613", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "VNQI", "IGOV"], "decision_date": "2017-07-14", "context_summary": "Max weight deviation: 0.0151, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2412, target=0.2500\n  BTC-USD: current=0.2651, target=0.2500\n  VNQI: current=0.2397, target=0.2500\n  IGOV: 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: 0.0151.\nRebalancing threshold: 0.0500.\n0.0151 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0382, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2412, "BTC-USD": 0.2651, "VNQI": 0.2397, "IGOV": 0.254}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "VNQI": 0.25, "IGOV": 0.25}, "max_deviation": 0.0151, "total_turnover": 0.038201, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.0151}}
{"id": "T6_all_20200130_0614", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ADA-USD", "IGOV", "IYR"], "decision_date": "2020-01-30", "context_summary": "Max weight deviation: 0.0267, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.2865, target=0.2500\n  ADA-USD: current=0.2653, target=0.2500\n  IGOV: current=0.2631, target=0.2500\n  IYR: 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 IYR", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0267.\nRebalancing threshold: 0.0500.\n0.0267 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0534, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2865, "ADA-USD": 0.2653, "IGOV": 0.2631, "IYR": 0.185}, "target_weights": {"XLV": 0.25, "ADA-USD": 0.25, "IGOV": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.053428, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IYR", "primary_trade": -0.065}}
{"id": "T6_all_20190206_0615", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "DBC", "REZ"], "decision_date": "2019-02-06", "context_summary": "Max weight deviation: 0.0163, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2376, target=0.2500\n  BTC-USD: current=0.2625, target=0.2500\n  DBC: current=0.2337, target=0.2500\n  REZ: 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: 0.0163.\nRebalancing threshold: 0.0500.\n0.0163 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0573, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2376, "BTC-USD": 0.2625, "DBC": 0.2337, "REZ": 0.2662}, "target_weights": {"VLUE": 0.25, "BTC-USD": 0.25, "DBC": 0.25, "REZ": 0.25}, "max_deviation": 0.0163, "total_turnover": 0.057341, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBC", "primary_trade": -0.0163}}
{"id": "T6_all_20220616_0616", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "VNQI", "DBC"], "decision_date": "2022-06-16", "context_summary": "Max weight deviation: 0.0279, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2809, target=0.2500\n  LINK-USD: current=0.1850, target=0.2500\n  VNQI: current=0.2464, target=0.2500\n  DBC: 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 LINK-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0279.\nRebalancing threshold: 0.0500.\n0.0279 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0588, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2809, "LINK-USD": 0.185, "VNQI": 0.2464, "DBC": 0.2877}, "target_weights": {"XLE": 0.25, "LINK-USD": 0.25, "VNQI": 0.25, "DBC": 0.25}, "max_deviation": 0.065043, "total_turnover": 0.058844, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.065}}
{"id": "T6_all_20221227_0617", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "SGOV", "DBB"], "decision_date": "2022-12-27", "context_summary": "Max weight deviation: 0.0222, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2504, target=0.2500\n  BNB-USD: current=0.2722, target=0.2500\n  SGOV: current=0.2430, target=0.2500\n  DBB: 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: 0.0222.\nRebalancing threshold: 0.0500.\n0.0222 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0451, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2504, "BNB-USD": 0.2722, "SGOV": 0.243, "DBB": 0.2345}, "target_weights": {"XLK": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "DBB": 0.25}, "max_deviation": 0.0222, "total_turnover": 0.045131, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.0222}}
{"id": "T6_all_20210427_0618", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "CPER", "ICSH"], "decision_date": "2021-04-27", "context_summary": "Max weight deviation: 0.0085, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.1851, target=0.2500\n  AVAX-USD: current=0.2885, target=0.2500\n  CPER: current=0.2510, target=0.2500\n  ICSH: current=0.2754, 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 IWM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0085.\nRebalancing threshold: 0.0500.\n0.0085 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0170, transaction cost = 0.000017 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.1851, "AVAX-USD": 0.2885, "CPER": 0.251, "ICSH": 0.2754}, "target_weights": {"IWM": 0.25, "AVAX-USD": 0.25, "CPER": 0.25, "ICSH": 0.25}, "max_deviation": 0.064858, "total_turnover": 0.016974, "transaction_cost": 1.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IWM", "primary_trade": -0.0649}}
{"id": "T6_all_20200107_0619", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "DBB", "BIL"], "decision_date": "2020-01-07", "context_summary": "Max weight deviation: 0.0270, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2326, target=0.2500\n  BTC-USD: current=0.2311, target=0.2500\n  DBB: current=0.2770, target=0.2500\n  BIL: current=0.2593, 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 = 0.0725, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2326, "BTC-USD": 0.2311, "DBB": 0.277, "BIL": 0.2593}, "target_weights": {"XLU": 0.25, "BTC-USD": 0.25, "DBB": 0.25, "BIL": 0.25}, "max_deviation": 0.027, "total_turnover": 0.072532, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": 0.027}}
{"id": "T6_all_20211230_0620", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "AVAX-USD", "XHB", "HYG"], "decision_date": "2021-12-30", "context_summary": "Max weight deviation: 0.0169, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2791, target=0.2500\n  AVAX-USD: current=0.2603, target=0.2500\n  XHB: current=0.2757, target=0.2500\n  HYG: 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 HYG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0169.\nRebalancing threshold: 0.0500.\n0.0169 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0338, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2791, "AVAX-USD": 0.2603, "XHB": 0.2757, "HYG": 0.1849}, "target_weights": {"QQQ": 0.25, "AVAX-USD": 0.25, "XHB": 0.25, "HYG": 0.25}, "max_deviation": 0.065071, "total_turnover": 0.033847, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": -0.0651}}
{"id": "T6_all_20220111_0621", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "STIP", "MORT"], "decision_date": "2022-01-11", "context_summary": "Max weight deviation: 0.0364, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2136, target=0.2500\n  ETH-USD: current=0.2764, target=0.2500\n  STIP: current=0.2346, target=0.2500\n  MORT: current=0.2754, 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: 0.0364.\nRebalancing threshold: 0.0500.\n0.0364 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1036, transaction cost = 0.000104 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2136, "ETH-USD": 0.2764, "STIP": 0.2346, "MORT": 0.2754}, "target_weights": {"EEM": 0.25, "ETH-USD": 0.25, "STIP": 0.25, "MORT": 0.25}, "max_deviation": 0.0364, "total_turnover": 0.103614, "transaction_cost": 0.000104, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": -0.0364}}
{"id": "T6_all_20210615_0622", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "XRP-USD", "USO", "HAUZ"], "decision_date": "2021-06-15", "context_summary": "Max weight deviation: 0.0341, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2331, target=0.2500\n  XRP-USD: current=0.1850, target=0.2500\n  USO: current=0.2809, target=0.2500\n  HAUZ: current=0.3010, 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: 0.0341.\nRebalancing threshold: 0.0500.\n0.0341 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0859, transaction cost = 0.000086 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2331, "XRP-USD": 0.185, "USO": 0.2809, "HAUZ": 0.301}, "target_weights": {"EFA": 0.25, "XRP-USD": 0.25, "USO": 0.25, "HAUZ": 0.25}, "max_deviation": 0.064965, "total_turnover": 0.085933, "transaction_cost": 8.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.065}}
{"id": "T6_all_20191004_0623", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "EMB", "REZ"], "decision_date": "2019-10-04", "context_summary": "Max weight deviation: 0.0105, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2582, target=0.2500\n  ADA-USD: current=0.2395, target=0.2500\n  EMB: current=0.2569, target=0.2500\n  REZ: current=0.2454, 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: 0.0105.\nRebalancing threshold: 0.0500.\n0.0105 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0302, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2582, "ADA-USD": 0.2395, "EMB": 0.2569, "REZ": 0.2454}, "target_weights": {"USMV": 0.25, "ADA-USD": 0.25, "EMB": 0.25, "REZ": 0.25}, "max_deviation": 0.0105, "total_turnover": 0.030224, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": -0.0105}}
{"id": "T6_all_20220822_0624", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "WEAT", "ITB"], "decision_date": "2022-08-22", "context_summary": "Max weight deviation: 0.0209, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2301, target=0.2500\n  AVAX-USD: current=0.3150, target=0.2500\n  WEAT: current=0.2603, target=0.2500\n  ITB: current=0.1946, 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 AVAX-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0209.\nRebalancing threshold: 0.0500.\n0.0209 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0483, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2301, "AVAX-USD": 0.315, "WEAT": 0.2603, "ITB": 0.1946}, "target_weights": {"IWM": 0.25, "AVAX-USD": 0.25, "WEAT": 0.25, "ITB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.048329, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": 0.065}}
{"id": "T6_all_20220502_0625", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "DOT-USD", "SHV", "SOYB"], "decision_date": "2022-05-02", "context_summary": "Max weight deviation: 0.0208, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2628, target=0.2500\n  DOT-USD: current=0.2617, target=0.2500\n  SHV: current=0.2463, target=0.2500\n  SOYB: current=0.2292, 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 = 0.0490, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2628, "DOT-USD": 0.2617, "SHV": 0.2463, "SOYB": 0.2292}, "target_weights": {"MTUM": 0.25, "DOT-USD": 0.25, "SHV": 0.25, "SOYB": 0.25}, "max_deviation": 0.0208, "total_turnover": 0.048964, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": -0.0208}}
{"id": "T6_all_20210518_0626", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "LINK-USD", "TIP", "HAUZ"], "decision_date": "2021-05-18", "context_summary": "Max weight deviation: 0.0311, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2237, target=0.2500\n  LINK-USD: current=0.1890, target=0.2500\n  TIP: current=0.3151, target=0.2500\n  HAUZ: current=0.2722, 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 TIP", "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 = 0.0835, transaction cost = 0.000083 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2237, "LINK-USD": 0.189, "TIP": 0.3151, "HAUZ": 0.2722}, "target_weights": {"IVV": 0.25, "LINK-USD": 0.25, "TIP": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065066, "total_turnover": 0.083466, "transaction_cost": 8.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "TIP", "primary_trade": 0.0651}}
{"id": "T6_all_20220329_0627", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BNB-USD", "ICSH", "SLV"], "decision_date": "2022-03-29", "context_summary": "Max weight deviation: 0.0387, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2697, target=0.2500\n  BNB-USD: current=0.2676, target=0.2500\n  ICSH: current=0.2113, target=0.2500\n  SLV: current=0.2514, 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: 0.0387.\nRebalancing threshold: 0.0500.\n0.0387 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0773, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2697, "BNB-USD": 0.2676, "ICSH": 0.2113, "SLV": 0.2514}, "target_weights": {"QUAL": 0.25, "BNB-USD": 0.25, "ICSH": 0.25, "SLV": 0.25}, "max_deviation": 0.0387, "total_turnover": 0.077318, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0387}}
{"id": "T6_all_20180817_0628", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "XRP-USD", "GLD", "XHB"], "decision_date": "2018-08-17", "context_summary": "Max weight deviation: 0.0134, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2601, target=0.2500\n  XRP-USD: current=0.3148, target=0.2500\n  GLD: current=0.2402, target=0.2500\n  XHB: 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 XHB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0134.\nRebalancing threshold: 0.0500.\n0.0134 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0308, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2601, "XRP-USD": 0.3148, "GLD": 0.2402, "XHB": 0.1849}, "target_weights": {"XLU": 0.25, "XRP-USD": 0.25, "GLD": 0.25, "XHB": 0.25}, "max_deviation": 0.06509, "total_turnover": 0.030846, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XHB", "primary_trade": -0.0651}}
{"id": "T6_all_20220622_0629", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "DOT-USD", "INDS", "SLV"], "decision_date": "2022-06-22", "context_summary": "Max weight deviation: 0.0435, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2810, target=0.2500\n  DOT-USD: current=0.2832, target=0.2500\n  INDS: current=0.2065, target=0.2500\n  SLV: current=0.2292, 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: 0.0435.\nRebalancing threshold: 0.0500.\n0.0435 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1286, transaction cost = 0.000129 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.281, "DOT-USD": 0.2832, "INDS": 0.2065, "SLV": 0.2292}, "target_weights": {"QUAL": 0.25, "DOT-USD": 0.25, "INDS": 0.25, "SLV": 0.25}, "max_deviation": 0.0435, "total_turnover": 0.128565, "transaction_cost": 0.000129, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "INDS", "primary_trade": -0.0435}}
{"id": "T6_all_20201103_0630", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "XHB", "CPER"], "decision_date": "2020-11-03", "context_summary": "Max weight deviation: 0.0210, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.1946, target=0.2500\n  SOL-USD: current=0.2382, target=0.2500\n  XHB: current=0.3150, target=0.2500\n  CPER: current=0.2522, 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 XHB", "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 = 0.0434, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.1946, "SOL-USD": 0.2382, "XHB": 0.315, "CPER": 0.2522}, "target_weights": {"QUAL": 0.25, "SOL-USD": 0.25, "XHB": 0.25, "CPER": 0.25}, "max_deviation": 0.065, "total_turnover": 0.043416, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XHB", "primary_trade": 0.065}}
{"id": "T6_all_20191121_0631", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "CORN", "IYR"], "decision_date": "2019-11-21", "context_summary": "Max weight deviation: 0.0247, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2590, target=0.2500\n  XRP-USD: current=0.2636, target=0.2500\n  CORN: current=0.2521, target=0.2500\n  IYR: current=0.2253, 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 = 0.0495, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.259, "XRP-USD": 0.2636, "CORN": 0.2521, "IYR": 0.2253}, "target_weights": {"VTI": 0.25, "XRP-USD": 0.25, "CORN": 0.25, "IYR": 0.25}, "max_deviation": 0.0247, "total_turnover": 0.049489, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IYR", "primary_trade": -0.0247}}
{"id": "T6_all_20180122_0632", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "ICSH", "DBB"], "decision_date": "2018-01-22", "context_summary": "Max weight deviation: 0.0103, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.3030, target=0.2500\n  ADA-USD: current=0.1900, target=0.2500\n  ICSH: current=0.1919, target=0.2500\n  DBB: 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 DBB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0103.\nRebalancing threshold: 0.0500.\n0.0103 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0374, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.303, "ADA-USD": 0.19, "ICSH": 0.1919, "DBB": 0.315}, "target_weights": {"XLP": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "DBB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037411, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": 0.065}}
{"id": "T6_all_20200918_0633", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "DBB", "HAUZ"], "decision_date": "2020-09-18", "context_summary": "Max weight deviation: 0.0301, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2348, target=0.2500\n  BTC-USD: current=0.2334, target=0.2500\n  DBB: current=0.2516, target=0.2500\n  HAUZ: current=0.2801, 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 = 0.0635, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2348, "BTC-USD": 0.2334, "DBB": 0.2516, "HAUZ": 0.2801}, "target_weights": {"EFA": 0.25, "BTC-USD": 0.25, "DBB": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0301, "total_turnover": 0.063489, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HAUZ", "primary_trade": 0.0301}}
{"id": "T6_all_20210608_0634", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "SLV", "BIL"], "decision_date": "2021-06-08", "context_summary": "Max weight deviation: 0.0442, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2806, target=0.2500\n  BTC-USD: current=0.2924, target=0.2500\n  SLV: current=0.2421, target=0.2500\n  BIL: 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 BIL", "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 = 0.0991, transaction cost = 0.000099 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2806, "BTC-USD": 0.2924, "SLV": 0.2421, "BIL": 0.185}, "target_weights": {"VLUE": 0.25, "BTC-USD": 0.25, "SLV": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.099117, "transaction_cost": 9.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.065}}
{"id": "T6_all_20180124_0635", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "LINK-USD", "CPER", "EMB"], "decision_date": "2018-01-24", "context_summary": "Max weight deviation: 0.0073, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2557, target=0.2500\n  LINK-USD: current=0.2492, target=0.2500\n  CPER: current=0.2525, target=0.2500\n  EMB: 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: 0.0073.\nRebalancing threshold: 0.0500.\n0.0073 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0163, transaction cost = 0.000016 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2557, "LINK-USD": 0.2492, "CPER": 0.2525, "EMB": 0.2427}, "target_weights": {"VEA": 0.25, "LINK-USD": 0.25, "CPER": 0.25, "EMB": 0.25}, "max_deviation": 0.0073, "total_turnover": 0.016264, "transaction_cost": 1.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EMB", "primary_trade": -0.0073}}
{"id": "T6_all_20221104_0636", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "SGOV", "DBC"], "decision_date": "2022-11-04", "context_summary": "Max weight deviation: 0.0174, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.2123, target=0.2500\n  ADA-USD: current=0.2119, target=0.2500\n  SGOV: current=0.3150, target=0.2500\n  DBC: current=0.2608, 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 SGOV", "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 = 0.0406, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2123, "ADA-USD": 0.2119, "SGOV": 0.315, "DBC": 0.2608}, "target_weights": {"XLP": 0.25, "ADA-USD": 0.25, "SGOV": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.040584, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.065}}
{"id": "T6_all_20210708_0637", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "BIL", "LQD"], "decision_date": "2021-07-08", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2713, target=0.2500\n  XRP-USD: current=0.2357, target=0.2500\n  BIL: current=0.2480, target=0.2500\n  LQD: current=0.2450, 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: 0.0213.\nRebalancing threshold: 0.0500.\n0.0213 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0427, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2713, "XRP-USD": 0.2357, "BIL": 0.248, "LQD": 0.245}, "target_weights": {"EWJ": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "LQD": 0.25}, "max_deviation": 0.0213, "total_turnover": 0.042674, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EWJ", "primary_trade": 0.0213}}
{"id": "T6_all_20171228_0638", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "XRP-USD", "SCHH", "BIL"], "decision_date": "2017-12-28", "context_summary": "Max weight deviation: 0.0137, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2240, target=0.2500\n  XRP-USD: current=0.2231, target=0.2500\n  SCHH: current=0.2378, target=0.2500\n  BIL: 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 BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0137.\nRebalancing threshold: 0.0500.\n0.0137 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0275, transaction cost = 0.000027 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.224, "XRP-USD": 0.2231, "SCHH": 0.2378, "BIL": 0.3151}, "target_weights": {"XLE": 0.25, "XRP-USD": 0.25, "SCHH": 0.25, "BIL": 0.25}, "max_deviation": 0.06515, "total_turnover": 0.027499, "transaction_cost": 2.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0651}}
{"id": "T6_all_20180420_0639", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ADA-USD", "SCHP", "SCHH"], "decision_date": "2018-04-20", "context_summary": "Max weight deviation: 0.0260, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2447, target=0.2500\n  ADA-USD: current=0.2760, target=0.2500\n  SCHP: current=0.2380, target=0.2500\n  SCHH: 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: 0.0260.\nRebalancing threshold: 0.0500.\n0.0260 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0520, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2447, "ADA-USD": 0.276, "SCHP": 0.238, "SCHH": 0.2413}, "target_weights": {"EEM": 0.25, "ADA-USD": 0.25, "SCHP": 0.25, "SCHH": 0.25}, "max_deviation": 0.026, "total_turnover": 0.051981, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.026}}
{"id": "T6_all_20170808_0640", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "EMB", "ITB"], "decision_date": "2017-08-08", "context_summary": "Max weight deviation: 0.0075, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2890, target=0.2500\n  BTC-USD: current=0.3107, target=0.2500\n  EMB: current=0.1850, target=0.2500\n  ITB: 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 EMB", "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 = 0.0230, transaction cost = 0.000023 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.289, "BTC-USD": 0.3107, "EMB": 0.185, "ITB": 0.2153}, "target_weights": {"EFA": 0.25, "BTC-USD": 0.25, "EMB": 0.25, "ITB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.023039, "transaction_cost": 2.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EMB", "primary_trade": -0.065}}
{"id": "T6_all_20180405_0641", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "BIL", "USO"], "decision_date": "2018-04-05", "context_summary": "Max weight deviation: 0.0203, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2559, target=0.2500\n  LINK-USD: current=0.2649, target=0.2500\n  BIL: current=0.2297, target=0.2500\n  USO: current=0.2495, 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: 0.0203.\nRebalancing threshold: 0.0500.\n0.0203 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0416, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2559, "LINK-USD": 0.2649, "BIL": 0.2297, "USO": 0.2495}, "target_weights": {"XLI": 0.25, "LINK-USD": 0.25, "BIL": 0.25, "USO": 0.25}, "max_deviation": 0.0203, "total_turnover": 0.041575, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.0203}}
{"id": "T6_all_20211227_0642", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "BTC-USD", "PALL", "HAUZ"], "decision_date": "2021-12-27", "context_summary": "Max weight deviation: 0.0342, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2132, target=0.2500\n  BTC-USD: current=0.2225, target=0.2500\n  PALL: current=0.2493, target=0.2500\n  HAUZ: 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 HAUZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0342.\nRebalancing threshold: 0.0500.\n0.0342 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0684, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2132, "BTC-USD": 0.2225, "PALL": 0.2493, "HAUZ": 0.3151}, "target_weights": {"MTUM": 0.25, "BTC-USD": 0.25, "PALL": 0.25, "HAUZ": 0.25}, "max_deviation": 0.06506, "total_turnover": 0.068387, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HAUZ", "primary_trade": 0.0651}}
{"id": "T6_all_20211123_0643", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "BIL", "DBB"], "decision_date": "2021-11-23", "context_summary": "Max weight deviation: 0.0424, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2076, target=0.2500\n  ADA-USD: current=0.2696, target=0.2500\n  BIL: current=0.2584, target=0.2500\n  DBB: current=0.2644, 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: 0.0424.\nRebalancing threshold: 0.0500.\n0.0424 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0849, transaction cost = 0.000085 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2076, "ADA-USD": 0.2696, "BIL": 0.2584, "DBB": 0.2644}, "target_weights": {"XLI": 0.25, "ADA-USD": 0.25, "BIL": 0.25, "DBB": 0.25}, "max_deviation": 0.0424, "total_turnover": 0.084885, "transaction_cost": 8.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLI", "primary_trade": -0.0424}}
{"id": "T6_all_20170822_0644", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BTC-USD", "TLH", "BIL"], "decision_date": "2017-08-22", "context_summary": "Max weight deviation: 0.0336, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2717, target=0.2500\n  BTC-USD: current=0.2920, target=0.2500\n  TLH: current=0.2512, target=0.2500\n  BIL: 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 BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0336.\nRebalancing threshold: 0.0500.\n0.0336 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0671, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2717, "BTC-USD": 0.292, "TLH": 0.2512, "BIL": 0.185}, "target_weights": {"EFA": 0.25, "BTC-USD": 0.25, "TLH": 0.25, "BIL": 0.25}, "max_deviation": 0.064964, "total_turnover": 0.067148, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.065}}
{"id": "T6_all_20161212_0645", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "VNQ", "PDBC"], "decision_date": "2016-12-12", "context_summary": "Max weight deviation: 0.0147, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2391, target=0.2500\n  BTC-USD: current=0.2541, target=0.2500\n  VNQ: current=0.2647, target=0.2500\n  PDBC: current=0.2422, 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: 0.0147.\nRebalancing threshold: 0.0500.\n0.0147 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0375, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2391, "BTC-USD": 0.2541, "VNQ": 0.2647, "PDBC": 0.2422}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "VNQ": 0.25, "PDBC": 0.25}, "max_deviation": 0.0147, "total_turnover": 0.037514, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VNQ", "primary_trade": 0.0147}}
{"id": "T6_all_20170113_0646", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "REZ", "BIL"], "decision_date": "2017-01-13", "context_summary": "Max weight deviation: 0.0273, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.3149, target=0.2500\n  BTC-USD: current=0.2752, target=0.2500\n  REZ: current=0.2199, target=0.2500\n  BIL: current=0.1900, 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 ^VIX", "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 = 0.0757, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.3149, "BTC-USD": 0.2752, "REZ": 0.2199, "BIL": 0.19}, "target_weights": {"^VIX": 0.25, "BTC-USD": 0.25, "REZ": 0.25, "BIL": 0.25}, "max_deviation": 0.064925, "total_turnover": 0.075727, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": 0.0649}}
{"id": "T6_all_20191024_0647", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "ICSH", "BNDX"], "decision_date": "2019-10-24", "context_summary": "Max weight deviation: 0.0437, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2274, target=0.2500\n  ETH-USD: current=0.2341, target=0.2500\n  ICSH: current=0.2448, target=0.2500\n  BNDX: current=0.2937, 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: 0.0437.\nRebalancing threshold: 0.0500.\n0.0437 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0875, transaction cost = 0.000087 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2274, "ETH-USD": 0.2341, "ICSH": 0.2448, "BNDX": 0.2937}, "target_weights": {"XLRE": 0.25, "ETH-USD": 0.25, "ICSH": 0.25, "BNDX": 0.25}, "max_deviation": 0.0437, "total_turnover": 0.087494, "transaction_cost": 8.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNDX", "primary_trade": 0.0437}}
{"id": "T6_all_20210706_0648", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "LINK-USD", "STIP", "VNQI"], "decision_date": "2021-07-06", "context_summary": "Max weight deviation: 0.0474, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2564, target=0.2500\n  LINK-USD: current=0.2741, target=0.2500\n  STIP: current=0.1850, target=0.2500\n  VNQI: current=0.2845, 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: 0.0474.\nRebalancing threshold: 0.0500.\n0.0474 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0949, transaction cost = 0.000095 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2564, "LINK-USD": 0.2741, "STIP": 0.185, "VNQI": 0.2845}, "target_weights": {"IWM": 0.25, "LINK-USD": 0.25, "STIP": 0.25, "VNQI": 0.25}, "max_deviation": 0.065025, "total_turnover": 0.094879, "transaction_cost": 9.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "STIP", "primary_trade": -0.065}}
{"id": "T6_all_20210402_0649", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD", "USO", "REZ"], "decision_date": "2021-04-02", "context_summary": "Max weight deviation: 0.0157, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2657, target=0.2500\n  DOT-USD: current=0.2423, target=0.2500\n  USO: current=0.2404, target=0.2500\n  REZ: current=0.2515, 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: 0.0157.\nRebalancing threshold: 0.0500.\n0.0157 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0345, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2657, "DOT-USD": 0.2423, "USO": 0.2404, "REZ": 0.2515}, "target_weights": {"ACWI": 0.25, "DOT-USD": 0.25, "USO": 0.25, "REZ": 0.25}, "max_deviation": 0.0157, "total_turnover": 0.034541, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": 0.0157}}
{"id": "T6_all_20210322_0650", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "LINK-USD", "VNQ", "IEF"], "decision_date": "2021-03-22", "context_summary": "Max weight deviation: 0.0165, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.3032, target=0.2500\n  LINK-USD: current=0.1850, target=0.2500\n  VNQ: current=0.3091, target=0.2500\n  IEF: current=0.2027, 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 LINK-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 = 0.0570, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.3032, "LINK-USD": 0.185, "VNQ": 0.3091, "IEF": 0.2027}, "target_weights": {"IWM": 0.25, "LINK-USD": 0.25, "VNQ": 0.25, "IEF": 0.25}, "max_deviation": 0.065, "total_turnover": 0.056953, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.065}}
{"id": "T6_all_20190710_0651", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "HYG", "ICSH"], "decision_date": "2019-07-10", "context_summary": "Max weight deviation: 0.0155, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2571, target=0.2500\n  ADA-USD: current=0.2508, target=0.2500\n  HYG: current=0.2345, target=0.2500\n  ICSH: 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": "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 = 0.0311, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2571, "ADA-USD": 0.2508, "HYG": 0.2345, "ICSH": 0.2576}, "target_weights": {"IVV": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "ICSH": 0.25}, "max_deviation": 0.0155, "total_turnover": 0.031063, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": -0.0155}}
{"id": "T6_all_20220201_0652", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "JNK", "HAUZ"], "decision_date": "2022-02-01", "context_summary": "Max weight deviation: 0.0243, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.3004, target=0.2500\n  BTC-USD: current=0.2019, target=0.2500\n  JNK: current=0.3127, 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: 0.0243.\nRebalancing threshold: 0.0500.\n0.0243 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0845, transaction cost = 0.000085 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.3004, "BTC-USD": 0.2019, "JNK": 0.3127, "HAUZ": 0.185}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "JNK": 0.25, "HAUZ": 0.25}, "max_deviation": 0.064951, "total_turnover": 0.084547, "transaction_cost": 8.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "HAUZ", "primary_trade": -0.065}}
{"id": "T6_all_20220323_0653", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SOL-USD", "VNQI", "SGOV"], "decision_date": "2022-03-23", "context_summary": "Max weight deviation: 0.0250, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2434, target=0.2500\n  SOL-USD: current=0.2378, target=0.2500\n  VNQI: current=0.2438, target=0.2500\n  SGOV: current=0.2750, 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 = 0.0499, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2434, "SOL-USD": 0.2378, "VNQI": 0.2438, "SGOV": 0.275}, "target_weights": {"VLUE": 0.25, "SOL-USD": 0.25, "VNQI": 0.25, "SGOV": 0.25}, "max_deviation": 0.025, "total_turnover": 0.049935, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.025}}
{"id": "T6_all_20211228_0654", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BNB-USD", "CPER", "HAUZ"], "decision_date": "2021-12-28", "context_summary": "Max weight deviation: 0.0080, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.1852, target=0.2500\n  BNB-USD: current=0.3039, target=0.2500\n  CPER: current=0.2909, target=0.2500\n  HAUZ: current=0.2201, 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 0.0648 of XLE", "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 = 0.0234, transaction cost = 0.000023 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.1852, "BNB-USD": 0.3039, "CPER": 0.2909, "HAUZ": 0.2201}, "target_weights": {"XLE": 0.25, "BNB-USD": 0.25, "CPER": 0.25, "HAUZ": 0.25}, "max_deviation": 0.06485, "total_turnover": 0.023377, "transaction_cost": 2.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLE", "primary_trade": -0.0648}}
{"id": "T6_all_20210622_0655", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ADA-USD", "UNG", "MORT"], "decision_date": "2021-06-22", "context_summary": "Max weight deviation: 0.0227, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.2656, target=0.2500\n  ADA-USD: current=0.2555, target=0.2500\n  UNG: current=0.2273, target=0.2500\n  MORT: current=0.2516, 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": {"XLP": 0.2656, "ADA-USD": 0.2555, "UNG": 0.2273, "MORT": 0.2516}, "target_weights": {"XLP": 0.25, "ADA-USD": 0.25, "UNG": 0.25, "MORT": 0.25}, "max_deviation": 0.0227, "total_turnover": 0.045415, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": -0.0227}}
{"id": "T6_all_20210906_0656", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "CPER", "STIP"], "decision_date": "2021-09-06", "context_summary": "Max weight deviation: 0.0255, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.1990, target=0.2500\n  BNB-USD: current=0.3150, target=0.2500\n  CPER: current=0.2365, target=0.2500\n  STIP: current=0.2495, 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: 0.0255.\nRebalancing threshold: 0.0500.\n0.0255 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0510, transaction cost = 0.000051 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.199, "BNB-USD": 0.315, "CPER": 0.2365, "STIP": 0.2495}, "target_weights": {"XLI": 0.25, "BNB-USD": 0.25, "CPER": 0.25, "STIP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.051022, "transaction_cost": 5.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.065}}
{"id": "T6_all_20200221_0657", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BNB-USD", "JNK", "SCHH"], "decision_date": "2020-02-21", "context_summary": "Max weight deviation: 0.0339, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2801, target=0.2500\n  BNB-USD: current=0.2634, target=0.2500\n  JNK: current=0.2403, target=0.2500\n  SCHH: current=0.2161, 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: 0.0339.\nRebalancing threshold: 0.0500.\n0.0339 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0871, transaction cost = 0.000087 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2801, "BNB-USD": 0.2634, "JNK": 0.2403, "SCHH": 0.2161}, "target_weights": {"XLK": 0.25, "BNB-USD": 0.25, "JNK": 0.25, "SCHH": 0.25}, "max_deviation": 0.0339, "total_turnover": 0.087073, "transaction_cost": 8.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SCHH", "primary_trade": -0.0339}}
{"id": "T6_all_20210115_0658", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "MATIC-USD", "BIL", "IYR"], "decision_date": "2021-01-15", "context_summary": "Max weight deviation: 0.0345, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.3150, target=0.2500\n  MATIC-USD: current=0.2709, target=0.2500\n  BIL: current=0.1963, target=0.2500\n  IYR: current=0.2178, 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 XLF", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0345.\nRebalancing threshold: 0.0500.\n0.0345 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0912, transaction cost = 0.000091 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.315, "MATIC-USD": 0.2709, "BIL": 0.1963, "IYR": 0.2178}, "target_weights": {"XLF": 0.25, "MATIC-USD": 0.25, "BIL": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.09124, "transaction_cost": 9.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLF", "primary_trade": 0.065}}
{"id": "T6_all_20210401_0659", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "VNQ", "BIL"], "decision_date": "2021-04-01", "context_summary": "Max weight deviation: 0.0296, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2338, target=0.2500\n  BNB-USD: current=0.2204, target=0.2500\n  VNQ: current=0.2747, target=0.2500\n  BIL: current=0.2711, 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 = 0.0916, transaction cost = 0.000092 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2338, "BNB-USD": 0.2204, "VNQ": 0.2747, "BIL": 0.2711}, "target_weights": {"XLB": 0.25, "BNB-USD": 0.25, "VNQ": 0.25, "BIL": 0.25}, "max_deviation": 0.0296, "total_turnover": 0.09157, "transaction_cost": 9.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": -0.0296}}
{"id": "T6_all_20211013_0660", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "AVAX-USD", "BNDX", "PPLT"], "decision_date": "2021-10-13", "context_summary": "Max weight deviation: 0.0325, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2712, target=0.2500\n  AVAX-USD: current=0.1850, target=0.2500\n  BNDX: current=0.2706, target=0.2500\n  PPLT: current=0.2732, 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: 0.0325.\nRebalancing threshold: 0.0500.\n0.0325 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0650, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2712, "AVAX-USD": 0.185, "BNDX": 0.2706, "PPLT": 0.2732}, "target_weights": {"XLRE": 0.25, "AVAX-USD": 0.25, "BNDX": 0.25, "PPLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.065008, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": -0.065}}
{"id": "T6_all_20210330_0661", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "DOT-USD", "IYR", "BNDX"], "decision_date": "2021-03-30", "context_summary": "Max weight deviation: 0.0173, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2561, target=0.2500\n  DOT-USD: current=0.2673, target=0.2500\n  IYR: current=0.2407, target=0.2500\n  BNDX: current=0.2359, 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 = 0.0467, transaction cost = 0.000047 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2561, "DOT-USD": 0.2673, "IYR": 0.2407, "BNDX": 0.2359}, "target_weights": {"XLF": 0.25, "DOT-USD": 0.25, "IYR": 0.25, "BNDX": 0.25}, "max_deviation": 0.0173, "total_turnover": 0.046746, "transaction_cost": 4.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DOT-USD", "primary_trade": 0.0173}}
{"id": "T6_all_20211202_0662", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "ICSH", "LQD"], "decision_date": "2021-12-02", "context_summary": "Max weight deviation: 0.0134, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2485, target=0.2500\n  BTC-USD: current=0.3150, target=0.2500\n  ICSH: current=0.2451, target=0.2500\n  LQD: current=0.1913, 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 BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0134.\nRebalancing threshold: 0.0500.\n0.0134 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0268, transaction cost = 0.000027 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2485, "BTC-USD": 0.315, "ICSH": 0.2451, "LQD": 0.1913}, "target_weights": {"IVV": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "LQD": 0.25}, "max_deviation": 0.065, "total_turnover": 0.026794, "transaction_cost": 2.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.065}}
{"id": "T6_all_20190326_0663", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "SLV", "ICSH"], "decision_date": "2019-03-26", "context_summary": "Max weight deviation: 0.0408, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2649, target=0.2500\n  ADA-USD: current=0.2092, target=0.2500\n  SLV: current=0.2800, target=0.2500\n  ICSH: current=0.2459, 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: 0.0408.\nRebalancing threshold: 0.0500.\n0.0408 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0898, transaction cost = 0.000090 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2649, "ADA-USD": 0.2092, "SLV": 0.28, "ICSH": 0.2459}, "target_weights": {"MTUM": 0.25, "ADA-USD": 0.25, "SLV": 0.25, "ICSH": 0.25}, "max_deviation": 0.0408, "total_turnover": 0.089784, "transaction_cost": 9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": -0.0408}}
{"id": "T6_all_20190131_0664", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "DBC", "ITB"], "decision_date": "2019-01-31", "context_summary": "Max weight deviation: 0.0411, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2439, target=0.2500\n  ETH-USD: current=0.2880, target=0.2500\n  DBC: current=0.2831, target=0.2500\n  ITB: 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 ITB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0411.\nRebalancing threshold: 0.0500.\n0.0411 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0900, transaction cost = 0.000090 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2439, "ETH-USD": 0.288, "DBC": 0.2831, "ITB": 0.185}, "target_weights": {"XLU": 0.25, "ETH-USD": 0.25, "DBC": 0.25, "ITB": 0.25}, "max_deviation": 0.064971, "total_turnover": 0.089975, "transaction_cost": 9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": -0.065}}
{"id": "T6_all_20210219_0665", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "TLH", "REZ"], "decision_date": "2021-02-19", "context_summary": "Max weight deviation: 0.0132, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2430, target=0.2500\n  ADA-USD: current=0.2415, target=0.2500\n  TLH: current=0.2632, target=0.2500\n  REZ: current=0.2523, 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: 0.0132.\nRebalancing threshold: 0.0500.\n0.0132 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0310, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.243, "ADA-USD": 0.2415, "TLH": 0.2632, "REZ": 0.2523}, "target_weights": {"QQQ": 0.25, "ADA-USD": 0.25, "TLH": 0.25, "REZ": 0.25}, "max_deviation": 0.0132, "total_turnover": 0.031007, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": 0.0132}}
{"id": "T6_all_20211203_0666", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNB-USD", "BIL", "REZ"], "decision_date": "2021-12-03", "context_summary": "Max weight deviation: 0.0193, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.3004, target=0.2500\n  BNB-USD: current=0.2587, target=0.2500\n  BIL: current=0.2560, target=0.2500\n  REZ: 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 REZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0193.\nRebalancing threshold: 0.0500.\n0.0193 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0386, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.3004, "BNB-USD": 0.2587, "BIL": 0.256, "REZ": 0.1849}, "target_weights": {"EWJ": 0.25, "BNB-USD": 0.25, "BIL": 0.25, "REZ": 0.25}, "max_deviation": 0.065062, "total_turnover": 0.038617, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "REZ", "primary_trade": -0.0651}}
{"id": "T6_all_20211116_0667", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "SOYB", "STIP"], "decision_date": "2021-11-16", "context_summary": "Max weight deviation: 0.0419, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2713, target=0.2500\n  ADA-USD: current=0.2336, target=0.2500\n  SOYB: current=0.2870, target=0.2500\n  STIP: current=0.2081, 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: 0.0419.\nRebalancing threshold: 0.0500.\n0.0419 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1166, transaction cost = 0.000117 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2713, "ADA-USD": 0.2336, "SOYB": 0.287, "STIP": 0.2081}, "target_weights": {"XLRE": 0.25, "ADA-USD": 0.25, "SOYB": 0.25, "STIP": 0.25}, "max_deviation": 0.0419, "total_turnover": 0.116591, "transaction_cost": 0.000117, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "STIP", "primary_trade": -0.0419}}
{"id": "T6_all_20201023_0668", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "VNQI", "BIL"], "decision_date": "2020-10-23", "context_summary": "Max weight deviation: 0.0464, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.3004, target=0.2500\n  MATIC-USD: current=0.2443, target=0.2500\n  VNQI: current=0.2703, target=0.2500\n  BIL: 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 BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0464.\nRebalancing threshold: 0.0500.\n0.0464 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1010, transaction cost = 0.000101 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.3004, "MATIC-USD": 0.2443, "VNQI": 0.2703, "BIL": 0.185}, "target_weights": {"VTI": 0.25, "MATIC-USD": 0.25, "VNQI": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.100981, "transaction_cost": 0.000101, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.065}}
{"id": "T6_all_20220525_0669", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "AVAX-USD", "PPLT", "BIL"], "decision_date": "2022-05-25", "context_summary": "Max weight deviation: 0.0093, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2567, target=0.2500\n  AVAX-USD: current=0.2563, target=0.2500\n  PPLT: current=0.2463, target=0.2500\n  BIL: current=0.2407, 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: 0.0093.\nRebalancing threshold: 0.0500.\n0.0093 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0261, transaction cost = 0.000026 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2567, "AVAX-USD": 0.2563, "PPLT": 0.2463, "BIL": 0.2407}, "target_weights": {"XLF": 0.25, "AVAX-USD": 0.25, "PPLT": 0.25, "BIL": 0.25}, "max_deviation": 0.0093, "total_turnover": 0.026101, "transaction_cost": 2.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.0093}}
{"id": "T6_all_20210426_0670", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "LINK-USD", "REZ", "BIL"], "decision_date": "2021-04-26", "context_summary": "Max weight deviation: 0.0193, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2365, target=0.2500\n  LINK-USD: current=0.3150, target=0.2500\n  REZ: current=0.2483, target=0.2500\n  BIL: current=0.2002, 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: 0.0193.\nRebalancing threshold: 0.0500.\n0.0193 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0385, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2365, "LINK-USD": 0.315, "REZ": 0.2483, "BIL": 0.2002}, "target_weights": {"USMV": 0.25, "LINK-USD": 0.25, "REZ": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.038522, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": 0.065}}
{"id": "T6_all_20220613_0671", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "VNQI", "SGOV"], "decision_date": "2022-06-13", "context_summary": "Max weight deviation: 0.0379, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2575, target=0.2500\n  ADA-USD: current=0.2879, target=0.2500\n  VNQI: current=0.2269, target=0.2500\n  SGOV: current=0.2277, 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: 0.0379.\nRebalancing threshold: 0.0500.\n0.0379 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0909, transaction cost = 0.000091 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2575, "ADA-USD": 0.2879, "VNQI": 0.2269, "SGOV": 0.2277}, "target_weights": {"ACWI": 0.25, "ADA-USD": 0.25, "VNQI": 0.25, "SGOV": 0.25}, "max_deviation": 0.0379, "total_turnover": 0.090869, "transaction_cost": 9.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": 0.0379}}
{"id": "T6_all_20221017_0672", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "LINK-USD", "JNK", "UNG"], "decision_date": "2022-10-17", "context_summary": "Max weight deviation: 0.0298, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2999, target=0.2500\n  LINK-USD: current=0.2561, target=0.2500\n  JNK: current=0.2589, 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: 0.0298.\nRebalancing threshold: 0.0500.\n0.0298 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0596, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2999, "LINK-USD": 0.2561, "JNK": 0.2589, "UNG": 0.185}, "target_weights": {"XLB": 0.25, "LINK-USD": 0.25, "JNK": 0.25, "UNG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059552, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": -0.065}}
{"id": "T6_all_20221012_0673", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "STIP", "IAU"], "decision_date": "2022-10-12", "context_summary": "Max weight deviation: 0.0287, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2677, target=0.2500\n  ETH-USD: current=0.2388, target=0.2500\n  STIP: current=0.2721, target=0.2500\n  IAU: current=0.2213, 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: 0.0287.\nRebalancing threshold: 0.0500.\n0.0287 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0797, transaction cost = 0.000080 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2677, "ETH-USD": 0.2388, "STIP": 0.2721, "IAU": 0.2213}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "STIP": 0.25, "IAU": 0.25}, "max_deviation": 0.0287, "total_turnover": 0.079719, "transaction_cost": 8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IAU", "primary_trade": -0.0287}}
{"id": "T6_all_20180814_0674", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "GLD", "ICSH"], "decision_date": "2018-08-14", "context_summary": "Max weight deviation: 0.0190, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2029, target=0.2500\n  LINK-USD: current=0.3151, target=0.2500\n  GLD: current=0.2491, target=0.2500\n  ICSH: current=0.2330, 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 LINK-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0190.\nRebalancing threshold: 0.0500.\n0.0190 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0381, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2029, "LINK-USD": 0.3151, "GLD": 0.2491, "ICSH": 0.233}, "target_weights": {"QUAL": 0.25, "LINK-USD": 0.25, "GLD": 0.25, "ICSH": 0.25}, "max_deviation": 0.065108, "total_turnover": 0.038094, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": 0.0651}}
{"id": "T6_all_20180912_0675", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BTC-USD", "XHB", "TLH"], "decision_date": "2018-09-12", "context_summary": "Max weight deviation: 0.0084, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2558, target=0.2500\n  BTC-USD: current=0.2548, target=0.2500\n  XHB: current=0.2478, target=0.2500\n  TLH: 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: 0.0084.\nRebalancing threshold: 0.0500.\n0.0084 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0212, transaction cost = 0.000021 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2558, "BTC-USD": 0.2548, "XHB": 0.2478, "TLH": 0.2416}, "target_weights": {"FXI": 0.25, "BTC-USD": 0.25, "XHB": 0.25, "TLH": 0.25}, "max_deviation": 0.0084, "total_turnover": 0.021238, "transaction_cost": 2.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": -0.0084}}
{"id": "T6_all_20200706_0676", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "ICSH", "HAUZ"], "decision_date": "2020-07-06", "context_summary": "Max weight deviation: 0.0178, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2555, target=0.2500\n  BTC-USD: current=0.2252, target=0.2500\n  ICSH: current=0.2044, target=0.2500\n  HAUZ: 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 HAUZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0178.\nRebalancing threshold: 0.0500.\n0.0178 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0387, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2555, "BTC-USD": 0.2252, "ICSH": 0.2044, "HAUZ": 0.315}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "HAUZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.038671, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HAUZ", "primary_trade": 0.065}}
{"id": "T6_all_20201009_0677", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "BIL", "XHB"], "decision_date": "2020-10-09", "context_summary": "Max weight deviation: 0.0103, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2603, target=0.2500\n  BTC-USD: current=0.2440, target=0.2500\n  BIL: current=0.2504, target=0.2500\n  XHB: current=0.2452, 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: 0.0103.\nRebalancing threshold: 0.0500.\n0.0103 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0216, transaction cost = 0.000022 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2603, "BTC-USD": 0.244, "BIL": 0.2504, "XHB": 0.2452}, "target_weights": {"^VIX": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "XHB": 0.25}, "max_deviation": 0.0103, "total_turnover": 0.021553, "transaction_cost": 2.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": 0.0103}}
{"id": "T6_all_20210527_0678", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "VCIT", "USO"], "decision_date": "2021-05-27", "context_summary": "Max weight deviation: 0.0124, 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=0.2096, target=0.2500\n  VCIT: current=0.1955, target=0.2500\n  USO: current=0.2799, 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: 0.0124.\nRebalancing threshold: 0.0500.\n0.0124 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0363, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.315, "BTC-USD": 0.2096, "VCIT": 0.1955, "USO": 0.2799}, "target_weights": {"USMV": 0.25, "BTC-USD": 0.25, "VCIT": 0.25, "USO": 0.25}, "max_deviation": 0.065, "total_turnover": 0.03629, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "USMV", "primary_trade": 0.065}}
{"id": "T6_all_20180329_0679", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BNB-USD", "HAUZ", "STIP"], "decision_date": "2018-03-29", "context_summary": "Max weight deviation: 0.0165, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2522, target=0.2500\n  BNB-USD: current=0.2335, target=0.2500\n  HAUZ: current=0.2508, target=0.2500\n  STIP: current=0.2635, 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: 0.0165.\nRebalancing threshold: 0.0500.\n0.0165 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0330, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2522, "BNB-USD": 0.2335, "HAUZ": 0.2508, "STIP": 0.2635}, "target_weights": {"XLY": 0.25, "BNB-USD": 0.25, "HAUZ": 0.25, "STIP": 0.25}, "max_deviation": 0.0165, "total_turnover": 0.032997, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": -0.0165}}
{"id": "T6_all_20210830_0680", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "SOL-USD", "ICSH", "WEAT"], "decision_date": "2021-08-30", "context_summary": "Max weight deviation: 0.0326, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.3151, target=0.2500\n  SOL-USD: current=0.2341, target=0.2500\n  ICSH: current=0.1962, target=0.2500\n  WEAT: 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": "yes; sell 0.0651 of XLP", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0326.\nRebalancing threshold: 0.0500.\n0.0326 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0700, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.3151, "SOL-USD": 0.2341, "ICSH": 0.1962, "WEAT": 0.2546}, "target_weights": {"XLP": 0.25, "SOL-USD": 0.25, "ICSH": 0.25, "WEAT": 0.25}, "max_deviation": 0.065063, "total_turnover": 0.069987, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLP", "primary_trade": 0.0651}}
{"id": "T6_all_20200327_0681", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "DBC", "BIL"], "decision_date": "2020-03-27", "context_summary": "Max weight deviation: 0.0293, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2439, target=0.2500\n  MATIC-USD: current=0.2793, target=0.2500\n  DBC: current=0.2429, target=0.2500\n  BIL: current=0.2339, 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: 0.0293.\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": {"IVV": 0.2439, "MATIC-USD": 0.2793, "DBC": 0.2429, "BIL": 0.2339}, "target_weights": {"IVV": 0.25, "MATIC-USD": 0.25, "DBC": 0.25, "BIL": 0.25}, "max_deviation": 0.0293, "total_turnover": 0.058561, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": 0.0293}}
{"id": "T6_all_20220505_0682", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "AVAX-USD", "SLV", "IYR"], "decision_date": "2022-05-05", "context_summary": "Max weight deviation: 0.0296, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.1850, target=0.2500\n  AVAX-USD: current=0.3003, target=0.2500\n  SLV: current=0.2228, target=0.2500\n  IYR: current=0.2919, 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 ^VIX", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0296.\nRebalancing threshold: 0.0500.\n0.0296 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0841, transaction cost = 0.000084 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.185, "AVAX-USD": 0.3003, "SLV": 0.2228, "IYR": 0.2919}, "target_weights": {"^VIX": 0.25, "AVAX-USD": 0.25, "SLV": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.084069, "transaction_cost": 8.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": -0.065}}
{"id": "T6_all_20210611_0683", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "LINK-USD", "SGOV", "ITB"], "decision_date": "2021-06-11", "context_summary": "Max weight deviation: 0.0172, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2328, target=0.2500\n  LINK-USD: current=0.2558, target=0.2500\n  SGOV: current=0.2626, target=0.2500\n  ITB: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0172.\nRebalancing threshold: 0.0500.\n0.0172 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0367, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2328, "LINK-USD": 0.2558, "SGOV": 0.2626, "ITB": 0.2489}, "target_weights": {"XLE": 0.25, "LINK-USD": 0.25, "SGOV": 0.25, "ITB": 0.25}, "max_deviation": 0.0172, "total_turnover": 0.036706, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLE", "primary_trade": -0.0172}}
{"id": "T6_all_20150501_0684", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "SOYB", "IGOV"], "decision_date": "2015-05-01", "context_summary": "Max weight deviation: 0.0216, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.3024, target=0.2500\n  BTC-USD: current=0.1916, target=0.2500\n  SOYB: current=0.3150, target=0.2500\n  IGOV: current=0.1910, 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 SOYB", "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 = 0.0780, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.3024, "BTC-USD": 0.1916, "SOYB": 0.315, "IGOV": 0.191}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "SOYB": 0.25, "IGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.077975, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": 0.065}}
{"id": "T6_all_20180518_0685", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "EMB", "DBB"], "decision_date": "2018-05-18", "context_summary": "Max weight deviation: 0.0275, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2377, target=0.2500\n  XRP-USD: current=0.2234, target=0.2500\n  EMB: current=0.2613, target=0.2500\n  DBB: current=0.2775, 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 = 0.0776, transaction cost = 0.000078 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2377, "XRP-USD": 0.2234, "EMB": 0.2613, "DBB": 0.2775}, "target_weights": {"USMV": 0.25, "XRP-USD": 0.25, "EMB": 0.25, "DBB": 0.25}, "max_deviation": 0.0275, "total_turnover": 0.077649, "transaction_cost": 7.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": 0.0275}}
{"id": "T6_all_20190730_0686", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "ICSH", "DBA"], "decision_date": "2019-07-30", "context_summary": "Max weight deviation: 0.0423, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.3150, target=0.2500\n  BTC-USD: current=0.2847, target=0.2500\n  ICSH: current=0.1922, target=0.2500\n  DBA: current=0.2082, 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: 0.0423.\nRebalancing threshold: 0.0500.\n0.0423 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1297, transaction cost = 0.000130 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.315, "BTC-USD": 0.2847, "ICSH": 0.1922, "DBA": 0.2082}, "target_weights": {"ACWI": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "DBA": 0.25}, "max_deviation": 0.064952, "total_turnover": 0.129671, "transaction_cost": 0.00013, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": 0.065}}
{"id": "T6_all_20210419_0687", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "LINK-USD", "BIL", "REZ"], "decision_date": "2021-04-19", "context_summary": "Max weight deviation: 0.0169, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2419, target=0.2500\n  LINK-USD: current=0.2365, target=0.2500\n  BIL: current=0.2669, target=0.2500\n  REZ: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0169.\nRebalancing threshold: 0.0500.\n0.0169 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0432, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2419, "LINK-USD": 0.2365, "BIL": 0.2669, "REZ": 0.2547}, "target_weights": {"IVV": 0.25, "LINK-USD": 0.25, "BIL": 0.25, "REZ": 0.25}, "max_deviation": 0.0169, "total_turnover": 0.043236, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0169}}
{"id": "T6_all_20190416_0688", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "LINK-USD", "PPLT", "STIP"], "decision_date": "2019-04-16", "context_summary": "Max weight deviation: 0.0275, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2020, target=0.2500\n  LINK-USD: current=0.1991, target=0.2500\n  PPLT: current=0.3149, target=0.2500\n  STIP: current=0.2840, 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 PPLT", "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 = 0.0837, transaction cost = 0.000084 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.202, "LINK-USD": 0.1991, "PPLT": 0.3149, "STIP": 0.284}, "target_weights": {"VTI": 0.25, "LINK-USD": 0.25, "PPLT": 0.25, "STIP": 0.25}, "max_deviation": 0.064926, "total_turnover": 0.083719, "transaction_cost": 8.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "PPLT", "primary_trade": 0.0649}}
{"id": "T6_all_20221005_0689", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ETH-USD", "ICSH", "PALL"], "decision_date": "2022-10-05", "context_summary": "Max weight deviation: 0.0137, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2530, target=0.2500\n  ETH-USD: current=0.2616, target=0.2500\n  ICSH: current=0.2491, target=0.2500\n  PALL: current=0.2363, 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: 0.0137.\nRebalancing threshold: 0.0500.\n0.0137 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0292, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.253, "ETH-USD": 0.2616, "ICSH": 0.2491, "PALL": 0.2363}, "target_weights": {"XLF": 0.25, "ETH-USD": 0.25, "ICSH": 0.25, "PALL": 0.25}, "max_deviation": 0.0137, "total_turnover": 0.029214, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "PALL", "primary_trade": -0.0137}}
{"id": "T6_all_20201028_0690", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "ICSH", "DBC"], "decision_date": "2020-10-28", "context_summary": "Max weight deviation: 0.0275, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.1850, target=0.2500\n  MATIC-USD: current=0.2961, target=0.2500\n  ICSH: current=0.2053, target=0.2500\n  DBC: current=0.3136, 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 QUAL", "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 = 0.0928, transaction cost = 0.000093 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.185, "MATIC-USD": 0.2961, "ICSH": 0.2053, "DBC": 0.3136}, "target_weights": {"QUAL": 0.25, "MATIC-USD": 0.25, "ICSH": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.092837, "transaction_cost": 9.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "QUAL", "primary_trade": -0.065}}
{"id": "T6_all_20210121_0691", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SOL-USD", "SGOV", "SCHP"], "decision_date": "2021-01-21", "context_summary": "Max weight deviation: 0.0460, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2040, target=0.2500\n  SOL-USD: current=0.2675, target=0.2500\n  SGOV: current=0.2716, target=0.2500\n  SCHP: current=0.2569, 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: 0.0460.\nRebalancing threshold: 0.0500.\n0.0460 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0920, transaction cost = 0.000092 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.204, "SOL-USD": 0.2675, "SGOV": 0.2716, "SCHP": 0.2569}, "target_weights": {"VLUE": 0.25, "SOL-USD": 0.25, "SGOV": 0.25, "SCHP": 0.25}, "max_deviation": 0.046, "total_turnover": 0.092009, "transaction_cost": 9.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VLUE", "primary_trade": -0.046}}
{"id": "T6_all_20220711_0692", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "SCHH", "PPLT"], "decision_date": "2022-07-11", "context_summary": "Max weight deviation: 0.0372, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2098, target=0.2500\n  SOL-USD: current=0.2605, target=0.2500\n  SCHH: current=0.2147, target=0.2500\n  PPLT: 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 PPLT", "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 = 0.0864, transaction cost = 0.000086 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2098, "SOL-USD": 0.2605, "SCHH": 0.2147, "PPLT": 0.315}, "target_weights": {"QUAL": 0.25, "SOL-USD": 0.25, "SCHH": 0.25, "PPLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.086419, "transaction_cost": 8.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "PPLT", "primary_trade": 0.065}}
{"id": "T6_all_20170127_0693", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "PPLT", "JNK"], "decision_date": "2017-01-27", "context_summary": "Max weight deviation: 0.0154, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2484, target=0.2500\n  BTC-USD: current=0.2498, target=0.2500\n  PPLT: current=0.2654, target=0.2500\n  JNK: current=0.2364, 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: 0.0154.\nRebalancing threshold: 0.0500.\n0.0154 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0309, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2484, "BTC-USD": 0.2498, "PPLT": 0.2654, "JNK": 0.2364}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "PPLT": 0.25, "JNK": 0.25}, "max_deviation": 0.0154, "total_turnover": 0.030897, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "PPLT", "primary_trade": 0.0154}}
{"id": "T6_all_20191225_0694", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "UNG", "SCHH"], "decision_date": "2019-12-25", "context_summary": "Max weight deviation: 0.0145, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2482, target=0.2500\n  ADA-USD: current=0.2513, target=0.2500\n  UNG: current=0.1854, target=0.2500\n  SCHH: 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 SCHH", "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 = 0.0296, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2482, "ADA-USD": 0.2513, "UNG": 0.1854, "SCHH": 0.315}, "target_weights": {"USMV": 0.25, "ADA-USD": 0.25, "UNG": 0.25, "SCHH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.0296, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SCHH", "primary_trade": 0.065}}
{"id": "T6_all_20191002_0695", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "BIL", "HAUZ"], "decision_date": "2019-10-02", "context_summary": "Max weight deviation: 0.0230, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2305, target=0.2500\n  BTC-USD: current=0.2629, target=0.2500\n  BIL: current=0.2730, target=0.2500\n  HAUZ: current=0.2337, 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 = 0.0717, transaction cost = 0.000072 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2305, "BTC-USD": 0.2629, "BIL": 0.273, "HAUZ": 0.2337}, "target_weights": {"VTI": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "HAUZ": 0.25}, "max_deviation": 0.023, "total_turnover": 0.071679, "transaction_cost": 7.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.023}}
{"id": "T6_all_20220513_0696", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "LINK-USD", "PPLT", "LQD"], "decision_date": "2022-05-13", "context_summary": "Max weight deviation: 0.0056, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2515, target=0.2500\n  LINK-USD: current=0.2724, target=0.2500\n  PPLT: current=0.2910, target=0.2500\n  LQD: current=0.1852, 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 0.0648 of LQD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0056.\nRebalancing threshold: 0.0500.\n0.0056 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0112, transaction cost = 0.000011 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2515, "LINK-USD": 0.2724, "PPLT": 0.291, "LQD": 0.1852}, "target_weights": {"XLF": 0.25, "LINK-USD": 0.25, "PPLT": 0.25, "LQD": 0.25}, "max_deviation": 0.064785, "total_turnover": 0.011181, "transaction_cost": 1.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LQD", "primary_trade": -0.0648}}
{"id": "T6_all_20220517_0697", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ETH-USD", "SGOV", "SLV"], "decision_date": "2022-05-17", "context_summary": "Max weight deviation: 0.0111, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2525, target=0.2500\n  ETH-USD: current=0.2398, target=0.2500\n  SGOV: current=0.2611, target=0.2500\n  SLV: current=0.2467, 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: 0.0111.\nRebalancing threshold: 0.0500.\n0.0111 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0270, transaction cost = 0.000027 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2525, "ETH-USD": 0.2398, "SGOV": 0.2611, "SLV": 0.2467}, "target_weights": {"IVV": 0.25, "ETH-USD": 0.25, "SGOV": 0.25, "SLV": 0.25}, "max_deviation": 0.0111, "total_turnover": 0.027015, "transaction_cost": 2.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0111}}
{"id": "T6_all_20200220_0698", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "WEAT", "VNQI"], "decision_date": "2020-02-20", "context_summary": "Max weight deviation: 0.0162, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.3150, target=0.2500\n  BNB-USD: current=0.2071, target=0.2500\n  WEAT: current=0.2175, target=0.2500\n  VNQI: 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": "yes; sell 0.0650 of XLI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0162.\nRebalancing threshold: 0.0500.\n0.0162 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0375, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.315, "BNB-USD": 0.2071, "WEAT": 0.2175, "VNQI": 0.2604}, "target_weights": {"XLI": 0.25, "BNB-USD": 0.25, "WEAT": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037503, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLI", "primary_trade": 0.065}}
{"id": "T6_all_20190409_0699", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "USO", "VCIT"], "decision_date": "2019-04-09", "context_summary": "Max weight deviation: 0.0081, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2542, target=0.2500\n  ADA-USD: current=0.2419, target=0.2500\n  USO: current=0.2577, target=0.2500\n  VCIT: current=0.2461, 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: 0.0081.\nRebalancing threshold: 0.0500.\n0.0081 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0239, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2542, "ADA-USD": 0.2419, "USO": 0.2577, "VCIT": 0.2461}, "target_weights": {"XLK": 0.25, "ADA-USD": 0.25, "USO": 0.25, "VCIT": 0.25}, "max_deviation": 0.0081, "total_turnover": 0.023905, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": -0.0081}}
{"id": "T6_all_20180808_0700", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "PALL", "SHY"], "decision_date": "2018-08-08", "context_summary": "Max weight deviation: 0.0281, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2077, target=0.2500\n  LINK-USD: current=0.3150, target=0.2500\n  PALL: current=0.2310, target=0.2500\n  SHY: current=0.2463, 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: 0.0281.\nRebalancing threshold: 0.0500.\n0.0281 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0563, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2077, "LINK-USD": 0.315, "PALL": 0.231, "SHY": 0.2463}, "target_weights": {"FXI": 0.25, "LINK-USD": 0.25, "PALL": 0.25, "SHY": 0.25}, "max_deviation": 0.065, "total_turnover": 0.056253, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": 0.065}}
{"id": "T6_all_20210601_0701", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "STIP", "WEAT"], "decision_date": "2021-06-01", "context_summary": "Max weight deviation: 0.0380, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2120, target=0.2500\n  LINK-USD: current=0.2379, target=0.2500\n  STIP: current=0.2838, target=0.2500\n  WEAT: current=0.2664, 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: 0.0380.\nRebalancing threshold: 0.0500.\n0.0380 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1003, transaction cost = 0.000100 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.212, "LINK-USD": 0.2379, "STIP": 0.2838, "WEAT": 0.2664}, "target_weights": {"QUAL": 0.25, "LINK-USD": 0.25, "STIP": 0.25, "WEAT": 0.25}, "max_deviation": 0.038, "total_turnover": 0.100327, "transaction_cost": 0.0001, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "QUAL", "primary_trade": -0.038}}
{"id": "T6_all_20220107_0702", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "PALL", "VNQI"], "decision_date": "2022-01-07", "context_summary": "Max weight deviation: 0.0179, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2583, target=0.2500\n  BTC-USD: current=0.1889, target=0.2500\n  PALL: current=0.2379, target=0.2500\n  VNQI: 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 VNQI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0179.\nRebalancing threshold: 0.0500.\n0.0179 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0403, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2583, "BTC-USD": 0.1889, "PALL": 0.2379, "VNQI": 0.3149}, "target_weights": {"XLE": 0.25, "BTC-USD": 0.25, "PALL": 0.25, "VNQI": 0.25}, "max_deviation": 0.064886, "total_turnover": 0.040273, "transaction_cost": 4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQI", "primary_trade": 0.0649}}
{"id": "T6_all_20200817_0703", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "CPER", "SGOV"], "decision_date": "2020-08-17", "context_summary": "Max weight deviation: 0.0204, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2520, target=0.2500\n  ETH-USD: current=0.2704, target=0.2500\n  CPER: current=0.2401, target=0.2500\n  SGOV: 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: 0.0204.\nRebalancing threshold: 0.0500.\n0.0204 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0448, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.252, "ETH-USD": 0.2704, "CPER": 0.2401, "SGOV": 0.2375}, "target_weights": {"QUAL": 0.25, "ETH-USD": 0.25, "CPER": 0.25, "SGOV": 0.25}, "max_deviation": 0.0204, "total_turnover": 0.044759, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": 0.0204}}
{"id": "T6_all_20221121_0704", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XRP-USD", "DBB", "ICSH"], "decision_date": "2022-11-21", "context_summary": "Max weight deviation: 0.0328, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2062, target=0.2500\n  XRP-USD: current=0.2020, target=0.2500\n  DBB: current=0.3149, target=0.2500\n  ICSH: current=0.2769, 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 DBB", "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 = 0.0927, transaction cost = 0.000093 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2062, "XRP-USD": 0.202, "DBB": 0.3149, "ICSH": 0.2769}, "target_weights": {"MTUM": 0.25, "XRP-USD": 0.25, "DBB": 0.25, "ICSH": 0.25}, "max_deviation": 0.064938, "total_turnover": 0.092655, "transaction_cost": 9.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBB", "primary_trade": 0.0649}}
{"id": "T6_all_20200302_0705", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "SHV", "DBB"], "decision_date": "2020-03-02", "context_summary": "Max weight deviation: 0.0164, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ^VIX: current=0.2336, target=0.2500\n  ADA-USD: current=0.2653, target=0.2500\n  SHV: current=0.2403, target=0.2500\n  DBB: current=0.2609, 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: 0.0164.\nRebalancing threshold: 0.0500.\n0.0164 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0523, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2336, "ADA-USD": 0.2653, "SHV": 0.2403, "DBB": 0.2609}, "target_weights": {"^VIX": 0.25, "ADA-USD": 0.25, "SHV": 0.25, "DBB": 0.25}, "max_deviation": 0.0164, "total_turnover": 0.052312, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": -0.0164}}
{"id": "T6_all_20190624_0706", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "INDS", "ICSH"], "decision_date": "2019-06-24", "context_summary": "Max weight deviation: 0.0207, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2623, target=0.2500\n  ETH-USD: current=0.2837, target=0.2500\n  INDS: current=0.1851, target=0.2500\n  ICSH: current=0.2689, 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 INDS", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0207.\nRebalancing threshold: 0.0500.\n0.0207 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0414, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2623, "ETH-USD": 0.2837, "INDS": 0.1851, "ICSH": 0.2689}, "target_weights": {"ACWI": 0.25, "ETH-USD": 0.25, "INDS": 0.25, "ICSH": 0.25}, "max_deviation": 0.064942, "total_turnover": 0.041354, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "INDS", "primary_trade": -0.0649}}
{"id": "T6_all_20150615_0707", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "CORN", "SHY"], "decision_date": "2015-06-15", "context_summary": "Max weight deviation: 0.0277, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2519, target=0.2500\n  BTC-USD: current=0.2480, target=0.2500\n  CORN: current=0.2224, target=0.2500\n  SHY: current=0.2777, 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: 0.0277.\nRebalancing threshold: 0.0500.\n0.0277 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0593, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2519, "BTC-USD": 0.248, "CORN": 0.2224, "SHY": 0.2777}, "target_weights": {"XLE": 0.25, "BTC-USD": 0.25, "CORN": 0.25, "SHY": 0.25}, "max_deviation": 0.0277, "total_turnover": 0.059313, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SHY", "primary_trade": 0.0277}}
{"id": "T6_all_20181213_0708", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "ITB", "TLT"], "decision_date": "2018-12-13", "context_summary": "Max weight deviation: 0.0021, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.3026, target=0.2500\n  BTC-USD: current=0.1850, target=0.2500\n  ITB: current=0.2407, target=0.2500\n  TLT: 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; buy 0.0650 of BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0021.\nRebalancing threshold: 0.0500.\n0.0021 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0048, transaction cost = 0.000005 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.3026, "BTC-USD": 0.185, "ITB": 0.2407, "TLT": 0.2717}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "ITB": 0.25, "TLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.004801, "transaction_cost": 5e-06, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.065}}
{"id": "T6_all_20181001_0709", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ETH-USD", "ITB", "SOYB"], "decision_date": "2018-10-01", "context_summary": "Max weight deviation: 0.0071, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2477, target=0.2500\n  ETH-USD: current=0.2429, target=0.2500\n  ITB: current=0.2543, target=0.2500\n  SOYB: current=0.2551, 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: 0.0071.\nRebalancing threshold: 0.0500.\n0.0071 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0188, transaction cost = 0.000019 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2477, "ETH-USD": 0.2429, "ITB": 0.2543, "SOYB": 0.2551}, "target_weights": {"IWM": 0.25, "ETH-USD": 0.25, "ITB": 0.25, "SOYB": 0.25}, "max_deviation": 0.0071, "total_turnover": 0.018812, "transaction_cost": 1.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0071}}
{"id": "T6_all_20201116_0710", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "SGOV", "TIP"], "decision_date": "2020-11-16", "context_summary": "Max weight deviation: 0.0167, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.3150, target=0.2500\n  ADA-USD: current=0.2278, target=0.2500\n  SGOV: current=0.2558, target=0.2500\n  TIP: current=0.2013, 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 FXI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0167.\nRebalancing threshold: 0.0500.\n0.0167 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0363, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.315, "ADA-USD": 0.2278, "SGOV": 0.2558, "TIP": 0.2013}, "target_weights": {"FXI": 0.25, "ADA-USD": 0.25, "SGOV": 0.25, "TIP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.036338, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "FXI", "primary_trade": 0.065}}
{"id": "T6_all_20160322_0711", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "DBB", "TLH"], "decision_date": "2016-03-22", "context_summary": "Max weight deviation: 0.0182, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2325, target=0.2500\n  BTC-USD: current=0.2664, target=0.2500\n  DBB: current=0.2330, target=0.2500\n  TLH: current=0.2682, 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: 0.0182.\nRebalancing threshold: 0.0500.\n0.0182 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0691, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2325, "BTC-USD": 0.2664, "DBB": 0.233, "TLH": 0.2682}, "target_weights": {"XLF": 0.25, "BTC-USD": 0.25, "DBB": 0.25, "TLH": 0.25}, "max_deviation": 0.0182, "total_turnover": 0.069117, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": 0.0182}}
{"id": "T6_all_20221125_0712", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "MATIC-USD", "SHY", "UNG"], "decision_date": "2022-11-25", "context_summary": "Max weight deviation: 0.0144, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EWJ: current=0.2771, target=0.2500\n  MATIC-USD: current=0.1940, target=0.2500\n  SHY: current=0.2139, target=0.2500\n  UNG: 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 UNG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0144.\nRebalancing threshold: 0.0500.\n0.0144 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0408, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2771, "MATIC-USD": 0.194, "SHY": 0.2139, "UNG": 0.315}, "target_weights": {"EWJ": 0.25, "MATIC-USD": 0.25, "SHY": 0.25, "UNG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.040768, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": 0.065}}
{"id": "T6_all_20200928_0713", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "DOT-USD", "XHB", "VCIT"], "decision_date": "2020-09-28", "context_summary": "Max weight deviation: 0.0214, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2714, target=0.2500\n  DOT-USD: current=0.2329, target=0.2500\n  XHB: current=0.2625, target=0.2500\n  VCIT: current=0.2332, 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: 0.0214.\nRebalancing threshold: 0.0500.\n0.0214 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0678, transaction cost = 0.000068 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2714, "DOT-USD": 0.2329, "XHB": 0.2625, "VCIT": 0.2332}, "target_weights": {"XLF": 0.25, "DOT-USD": 0.25, "XHB": 0.25, "VCIT": 0.25}, "max_deviation": 0.0214, "total_turnover": 0.067798, "transaction_cost": 6.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLF", "primary_trade": 0.0214}}
{"id": "T6_all_20220121_0714", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "MATIC-USD", "TLH", "BIL"], "decision_date": "2022-01-21", "context_summary": "Max weight deviation: 0.0196, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.1850, target=0.2500\n  MATIC-USD: current=0.2994, target=0.2500\n  TLH: current=0.2619, target=0.2500\n  BIL: current=0.2536, 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 FXI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0196.\nRebalancing threshold: 0.0500.\n0.0196 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0392, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.185, "MATIC-USD": 0.2994, "TLH": 0.2619, "BIL": 0.2536}, "target_weights": {"FXI": 0.25, "MATIC-USD": 0.25, "TLH": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.039155, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "FXI", "primary_trade": -0.065}}
{"id": "T6_all_20180730_0715", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ETH-USD", "SCHH", "TIP"], "decision_date": "2018-07-30", "context_summary": "Max weight deviation: 0.0244, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2256, target=0.2500\n  ETH-USD: current=0.2707, target=0.2500\n  SCHH: current=0.2574, target=0.2500\n  TIP: current=0.2463, 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: 0.0244.\nRebalancing threshold: 0.0500.\n0.0244 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0561, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2256, "ETH-USD": 0.2707, "SCHH": 0.2574, "TIP": 0.2463}, "target_weights": {"EFA": 0.25, "ETH-USD": 0.25, "SCHH": 0.25, "TIP": 0.25}, "max_deviation": 0.0244, "total_turnover": 0.056138, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EFA", "primary_trade": -0.0244}}
{"id": "T6_all_20210302_0716", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "DBA", "BNDX"], "decision_date": "2021-03-02", "context_summary": "Max weight deviation: 0.0449, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2001, target=0.2500\n  DOT-USD: current=0.2218, target=0.2500\n  DBA: current=0.3150, target=0.2500\n  BNDX: current=0.2632, 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 DBA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0449.\nRebalancing threshold: 0.0500.\n0.0449 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1080, transaction cost = 0.000108 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2001, "DOT-USD": 0.2218, "DBA": 0.315, "BNDX": 0.2632}, "target_weights": {"XLI": 0.25, "DOT-USD": 0.25, "DBA": 0.25, "BNDX": 0.25}, "max_deviation": 0.065, "total_turnover": 0.107988, "transaction_cost": 0.000108, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBA", "primary_trade": 0.065}}
{"id": "T6_all_20210226_0717", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "MATIC-USD", "BNO", "VNQI"], "decision_date": "2021-02-26", "context_summary": "Max weight deviation: 0.0268, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2357, target=0.2500\n  MATIC-USD: current=0.2768, target=0.2500\n  BNO: current=0.2436, target=0.2500\n  VNQI: current=0.2439, 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: 0.0268.\nRebalancing threshold: 0.0500.\n0.0268 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0536, transaction cost = 0.000054 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2357, "MATIC-USD": 0.2768, "BNO": 0.2436, "VNQI": 0.2439}, "target_weights": {"XLY": 0.25, "MATIC-USD": 0.25, "BNO": 0.25, "VNQI": 0.25}, "max_deviation": 0.0268, "total_turnover": 0.05356, "transaction_cost": 5.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": 0.0268}}
{"id": "T6_all_20211209_0718", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "SGOV", "HYG"], "decision_date": "2021-12-09", "context_summary": "Max weight deviation: 0.0174, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2190, target=0.2500\n  BTC-USD: current=0.2948, target=0.2500\n  SGOV: current=0.3012, 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: 0.0174.\nRebalancing threshold: 0.0500.\n0.0174 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0514, transaction cost = 0.000051 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.219, "BTC-USD": 0.2948, "SGOV": 0.3012, "HYG": 0.185}, "target_weights": {"VTI": 0.25, "BTC-USD": 0.25, "SGOV": 0.25, "HYG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.051402, "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_20220801_0719", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "ADA-USD", "SLV", "TLT"], "decision_date": "2022-08-01", "context_summary": "Max weight deviation: 0.0224, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2301, target=0.2500\n  ADA-USD: current=0.2627, target=0.2500\n  SLV: current=0.2724, target=0.2500\n  TLT: current=0.2349, 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 = 0.0701, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2301, "ADA-USD": 0.2627, "SLV": 0.2724, "TLT": 0.2349}, "target_weights": {"XLI": 0.25, "ADA-USD": 0.25, "SLV": 0.25, "TLT": 0.25}, "max_deviation": 0.0224, "total_turnover": 0.070093, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SLV", "primary_trade": 0.0224}}
{"id": "T6_all_20160906_0720", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BTC-USD", "HAUZ", "VCIT"], "decision_date": "2016-09-06", "context_summary": "Max weight deviation: 0.0181, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2464, target=0.2500\n  BTC-USD: current=0.3150, target=0.2500\n  HAUZ: current=0.2073, target=0.2500\n  VCIT: current=0.2313, 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 BTC-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 = 0.0362, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2464, "BTC-USD": 0.315, "HAUZ": 0.2073, "VCIT": 0.2313}, "target_weights": {"XLY": 0.25, "BTC-USD": 0.25, "HAUZ": 0.25, "VCIT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.036214, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.065}}
{"id": "T6_all_20221108_0721", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "MATIC-USD", "CSHI", "STIP"], "decision_date": "2022-11-08", "context_summary": "Max weight deviation: 0.0311, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2811, target=0.2500\n  MATIC-USD: current=0.2292, target=0.2500\n  CSHI: current=0.2657, target=0.2500\n  STIP: current=0.2240, 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: 0.0311.\nRebalancing threshold: 0.0500.\n0.0311 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0935, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2811, "MATIC-USD": 0.2292, "CSHI": 0.2657, "STIP": 0.224}, "target_weights": {"XLRE": 0.25, "MATIC-USD": 0.25, "CSHI": 0.25, "STIP": 0.25}, "max_deviation": 0.0311, "total_turnover": 0.093543, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": 0.0311}}
{"id": "T6_all_20211126_0722", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "VNQ", "USO"], "decision_date": "2021-11-26", "context_summary": "Max weight deviation: 0.0290, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.1850, target=0.2500\n  ADA-USD: current=0.2675, target=0.2500\n  VNQ: current=0.2406, target=0.2500\n  USO: current=0.3068, 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 FXI", "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 = 0.0662, transaction cost = 0.000066 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.185, "ADA-USD": 0.2675, "VNQ": 0.2406, "USO": 0.3068}, "target_weights": {"FXI": 0.25, "ADA-USD": 0.25, "VNQ": 0.25, "USO": 0.25}, "max_deviation": 0.064959, "total_turnover": 0.066238, "transaction_cost": 6.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "FXI", "primary_trade": -0.065}}
{"id": "T6_all_20211105_0723", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD", "SCHP", "ITB"], "decision_date": "2021-11-05", "context_summary": "Max weight deviation: 0.0120, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2560, target=0.2500\n  BTC-USD: current=0.2546, target=0.2500\n  SCHP: current=0.2380, target=0.2500\n  ITB: current=0.2515, 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: 0.0120.\nRebalancing threshold: 0.0500.\n0.0120 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0241, transaction cost = 0.000024 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.256, "BTC-USD": 0.2546, "SCHP": 0.238, "ITB": 0.2515}, "target_weights": {"QUAL": 0.25, "BTC-USD": 0.25, "SCHP": 0.25, "ITB": 0.25}, "max_deviation": 0.012, "total_turnover": 0.02408, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": -0.012}}
{"id": "T6_all_20210415_0724", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "JNK", "PPLT"], "decision_date": "2021-04-15", "context_summary": "Max weight deviation: 0.0177, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2518, target=0.2500\n  ETH-USD: current=0.2320, target=0.2500\n  JNK: current=0.2012, target=0.2500\n  PPLT: 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 PPLT", "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 = 0.0364, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2518, "ETH-USD": 0.232, "JNK": 0.2012, "PPLT": 0.315}, "target_weights": {"ACWI": 0.25, "ETH-USD": 0.25, "JNK": 0.25, "PPLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.036396, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "PPLT", "primary_trade": 0.065}}
{"id": "T6_all_20200921_0725", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "MATIC-USD", "SGOV", "VCIT"], "decision_date": "2020-09-21", "context_summary": "Max weight deviation: 0.0234, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VTI: current=0.2734, target=0.2500\n  MATIC-USD: current=0.2352, target=0.2500\n  SGOV: current=0.2507, target=0.2500\n  VCIT: current=0.2407, 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: 0.0234.\nRebalancing threshold: 0.0500.\n0.0234 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0482, transaction cost = 0.000048 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2734, "MATIC-USD": 0.2352, "SGOV": 0.2507, "VCIT": 0.2407}, "target_weights": {"VTI": 0.25, "MATIC-USD": 0.25, "SGOV": 0.25, "VCIT": 0.25}, "max_deviation": 0.0234, "total_turnover": 0.048193, "transaction_cost": 4.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VTI", "primary_trade": 0.0234}}
{"id": "T6_all_20220831_0726", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "GLD", "SCHH"], "decision_date": "2022-08-31", "context_summary": "Max weight deviation: 0.0512, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.3012, target=0.2500\n  BTC-USD: current=0.2268, target=0.2500\n  GLD: current=0.2348, target=0.2500\n  SCHH: current=0.2373, 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 0.0512 of IWM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0512.\nRebalancing threshold: 0.0500.\n0.0512 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1023, transaction cost = 0.000102 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.3012, "BTC-USD": 0.2268, "GLD": 0.2348, "SCHH": 0.2373}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "GLD": 0.25, "SCHH": 0.25}, "max_deviation": 0.0512, "total_turnover": 0.102334, "transaction_cost": 0.000102, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IWM", "primary_trade": 0.0512}}
{"id": "T6_all_20211014_0727", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "SOYB", "SHY"], "decision_date": "2021-10-14", "context_summary": "Max weight deviation: 0.0313, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2556, target=0.2500\n  ETH-USD: current=0.2435, target=0.2500\n  SOYB: current=0.2813, target=0.2500\n  SHY: current=0.2197, 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: 0.0313.\nRebalancing threshold: 0.0500.\n0.0313 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0737, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2556, "ETH-USD": 0.2435, "SOYB": 0.2813, "SHY": 0.2197}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "SOYB": 0.25, "SHY": 0.25}, "max_deviation": 0.0313, "total_turnover": 0.073657, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": 0.0313}}
{"id": "T6_all_20180326_0728", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "BNDX", "VNQI"], "decision_date": "2018-03-26", "context_summary": "Max weight deviation: 0.0263, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2179, target=0.2500\n  ETH-USD: current=0.2339, target=0.2500\n  BNDX: current=0.3150, target=0.2500\n  VNQI: current=0.2332, 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 BNDX", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0263.\nRebalancing threshold: 0.0500.\n0.0263 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0527, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2179, "ETH-USD": 0.2339, "BNDX": 0.315, "VNQI": 0.2332}, "target_weights": {"QUAL": 0.25, "ETH-USD": 0.25, "BNDX": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.052659, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNDX", "primary_trade": 0.065}}
{"id": "T6_all_20180522_0729", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BTC-USD", "PALL", "IEF"], "decision_date": "2018-05-22", "context_summary": "Max weight deviation: 0.0261, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2693, target=0.2500\n  BTC-USD: current=0.2492, target=0.2500\n  PALL: current=0.2576, target=0.2500\n  IEF: current=0.2239, 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 = 0.0538, transaction cost = 0.000054 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2693, "BTC-USD": 0.2492, "PALL": 0.2576, "IEF": 0.2239}, "target_weights": {"XLE": 0.25, "BTC-USD": 0.25, "PALL": 0.25, "IEF": 0.25}, "max_deviation": 0.0261, "total_turnover": 0.053844, "transaction_cost": 5.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IEF", "primary_trade": -0.0261}}
{"id": "T6_all_20200305_0730", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "MATIC-USD", "VCIT", "REZ"], "decision_date": "2020-03-05", "context_summary": "Max weight deviation: 0.0266, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2857, target=0.2500\n  MATIC-USD: current=0.2309, target=0.2500\n  VCIT: current=0.2984, target=0.2500\n  REZ: 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 REZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0266.\nRebalancing threshold: 0.0500.\n0.0266 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0688, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2857, "MATIC-USD": 0.2309, "VCIT": 0.2984, "REZ": 0.185}, "target_weights": {"VLUE": 0.25, "MATIC-USD": 0.25, "VCIT": 0.25, "REZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.06879, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "REZ", "primary_trade": -0.065}}
{"id": "T6_all_20211001_0731", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD", "ICSH", "ITB"], "decision_date": "2021-10-01", "context_summary": "Max weight deviation: 0.0263, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2332, target=0.2500\n  LINK-USD: current=0.2344, target=0.2500\n  ICSH: current=0.2561, target=0.2500\n  ITB: current=0.2763, 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: 0.0263.\nRebalancing threshold: 0.0500.\n0.0263 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0649, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2332, "LINK-USD": 0.2344, "ICSH": 0.2561, "ITB": 0.2763}, "target_weights": {"EFA": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "ITB": 0.25}, "max_deviation": 0.0263, "total_turnover": 0.064927, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": 0.0263}}
{"id": "T6_all_20190509_0732", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "XRP-USD", "BIL", "DBC"], "decision_date": "2019-05-09", "context_summary": "Max weight deviation: 0.0120, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2993, target=0.2500\n  XRP-USD: current=0.2300, target=0.2500\n  BIL: current=0.1850, target=0.2500\n  DBC: current=0.2858, 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 BIL", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0120.\nRebalancing threshold: 0.0500.\n0.0120 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0314, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2993, "XRP-USD": 0.23, "BIL": 0.185, "DBC": 0.2858}, "target_weights": {"EFA": 0.25, "XRP-USD": 0.25, "BIL": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.031404, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": -0.065}}
{"id": "T6_all_20190124_0733", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ADA-USD", "MORT", "ICSH"], "decision_date": "2019-01-24", "context_summary": "Max weight deviation: 0.0501, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLB: current=0.2543, target=0.2500\n  ADA-USD: current=0.2648, target=0.2500\n  MORT: current=0.2200, target=0.2500\n  ICSH: current=0.2609, 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: 0.0501.\nRebalancing threshold: 0.0500.\n0.0501 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1001, transaction cost = 0.000100 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2543, "ADA-USD": 0.2648, "MORT": 0.22, "ICSH": 0.2609}, "target_weights": {"XLB": 0.25, "ADA-USD": 0.25, "MORT": 0.25, "ICSH": 0.25}, "max_deviation": 0.03, "total_turnover": 0.100112, "transaction_cost": 0.0001, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "MORT", "primary_trade": -0.03}}
{"id": "T6_all_20200410_0734", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ADA-USD", "TLT", "REZ"], "decision_date": "2020-04-10", "context_summary": "Max weight deviation: 0.0164, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.2405, target=0.2500\n  ADA-USD: current=0.1850, target=0.2500\n  TLT: current=0.2789, target=0.2500\n  REZ: 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 ADA-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0164.\nRebalancing threshold: 0.0500.\n0.0164 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0377, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2405, "ADA-USD": 0.185, "TLT": 0.2789, "REZ": 0.2956}, "target_weights": {"XLV": 0.25, "ADA-USD": 0.25, "TLT": 0.25, "REZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.0377, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ADA-USD", "primary_trade": -0.065}}
{"id": "T6_all_20200602_0735", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "IGOV", "PDBC"], "decision_date": "2020-06-02", "context_summary": "Max weight deviation: 0.0396, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QQQ: current=0.2384, target=0.2500\n  ETH-USD: current=0.2104, target=0.2500\n  IGOV: current=0.2814, target=0.2500\n  PDBC: current=0.2699, 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: 0.0396.\nRebalancing threshold: 0.0500.\n0.0396 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1025, transaction cost = 0.000102 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2384, "ETH-USD": 0.2104, "IGOV": 0.2814, "PDBC": 0.2699}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "IGOV": 0.25, "PDBC": 0.25}, "max_deviation": 0.0396, "total_turnover": 0.102479, "transaction_cost": 0.000102, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0396}}
{"id": "T6_all_20200924_0736", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "LINK-USD", "VNQI", "SOYB"], "decision_date": "2020-09-24", "context_summary": "Max weight deviation: 0.0105, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLU: current=0.2171, target=0.2500\n  LINK-USD: current=0.3105, target=0.2500\n  VNQI: current=0.2876, target=0.2500\n  SOYB: 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 SOYB", "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 = 0.0317, transaction cost = 0.000032 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2171, "LINK-USD": 0.3105, "VNQI": 0.2876, "SOYB": 0.1849}, "target_weights": {"XLU": 0.25, "LINK-USD": 0.25, "VNQI": 0.25, "SOYB": 0.25}, "max_deviation": 0.065114, "total_turnover": 0.031696, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": -0.0651}}
{"id": "T6_all_20190308_0737", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ADA-USD", "EMB", "HAUZ"], "decision_date": "2019-03-08", "context_summary": "Max weight deviation: 0.0059, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2559, target=0.2500\n  ADA-USD: current=0.2536, target=0.2500\n  EMB: current=0.2446, target=0.2500\n  HAUZ: current=0.2459, 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: 0.0059.\nRebalancing threshold: 0.0500.\n0.0059 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0190, transaction cost = 0.000019 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2559, "ADA-USD": 0.2536, "EMB": 0.2446, "HAUZ": 0.2459}, "target_weights": {"XLF": 0.25, "ADA-USD": 0.25, "EMB": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0059, "total_turnover": 0.018995, "transaction_cost": 1.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLF", "primary_trade": 0.0059}}
{"id": "T6_all_20181026_0738", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BNB-USD", "ICSH", "TLH"], "decision_date": "2018-10-26", "context_summary": "Max weight deviation: 0.0144, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2837, target=0.2500\n  BNB-USD: current=0.2404, target=0.2500\n  ICSH: current=0.2909, target=0.2500\n  TLH: 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 TLH", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0144.\nRebalancing threshold: 0.0500.\n0.0144 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0331, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2837, "BNB-USD": 0.2404, "ICSH": 0.2909, "TLH": 0.1849}, "target_weights": {"VLUE": 0.25, "BNB-USD": 0.25, "ICSH": 0.25, "TLH": 0.25}, "max_deviation": 0.065083, "total_turnover": 0.03313, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "TLH", "primary_trade": -0.0651}}
{"id": "T6_all_20211125_0739", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MATIC-USD", "BIL", "TLH"], "decision_date": "2021-11-25", "context_summary": "Max weight deviation: 0.0239, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2322, target=0.2500\n  MATIC-USD: current=0.2591, target=0.2500\n  BIL: current=0.2739, target=0.2500\n  TLH: current=0.2348, 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: 0.0239.\nRebalancing threshold: 0.0500.\n0.0239 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0659, transaction cost = 0.000066 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2322, "MATIC-USD": 0.2591, "BIL": 0.2739, "TLH": 0.2348}, "target_weights": {"IWM": 0.25, "MATIC-USD": 0.25, "BIL": 0.25, "TLH": 0.25}, "max_deviation": 0.0239, "total_turnover": 0.065866, "transaction_cost": 6.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0239}}
{"id": "T6_all_20190916_0740", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "LINK-USD", "SHY", "REZ"], "decision_date": "2019-09-16", "context_summary": "Max weight deviation: 0.0306, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2109, target=0.2500\n  LINK-USD: current=0.2262, target=0.2500\n  SHY: current=0.2479, target=0.2500\n  REZ: 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 REZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0306.\nRebalancing threshold: 0.0500.\n0.0306 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0612, transaction cost = 0.000061 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2109, "LINK-USD": 0.2262, "SHY": 0.2479, "REZ": 0.315}, "target_weights": {"MTUM": 0.25, "LINK-USD": 0.25, "SHY": 0.25, "REZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.061212, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "REZ", "primary_trade": 0.065}}
{"id": "T6_all_20200108_0741", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "REZ", "IEF"], "decision_date": "2020-01-08", "context_summary": "Max weight deviation: 0.0332, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2168, target=0.2500\n  BNB-USD: current=0.2696, target=0.2500\n  REZ: current=0.2615, target=0.2500\n  IEF: 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: 0.0332.\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": {"EEM": 0.2168, "BNB-USD": 0.2696, "REZ": 0.2615, "IEF": 0.252}, "target_weights": {"EEM": 0.25, "BNB-USD": 0.25, "REZ": 0.25, "IEF": 0.25}, "max_deviation": 0.0332, "total_turnover": 0.066364, "transaction_cost": 6.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": -0.0332}}
{"id": "T6_all_20201225_0742", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "ICSH", "VNQI"], "decision_date": "2020-12-25", "context_summary": "Max weight deviation: 0.0413, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2251, target=0.2500\n  MATIC-USD: current=0.3150, target=0.2500\n  ICSH: current=0.2395, target=0.2500\n  VNQI: current=0.2204, 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 MATIC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0413.\nRebalancing threshold: 0.0500.\n0.0413 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0826, transaction cost = 0.000083 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2251, "MATIC-USD": 0.315, "ICSH": 0.2395, "VNQI": 0.2204}, "target_weights": {"IVV": 0.25, "MATIC-USD": 0.25, "ICSH": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.082553, "transaction_cost": 8.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": 0.065}}
{"id": "T6_all_20200902_0743", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "VNQI", "SGOV"], "decision_date": "2020-09-02", "context_summary": "Max weight deviation: 0.0015, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2489, target=0.2500\n  BTC-USD: current=0.2515, target=0.2500\n  VNQI: current=0.2501, target=0.2500\n  SGOV: current=0.2495, 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: 0.0015.\nRebalancing threshold: 0.0500.\n0.0015 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0032, transaction cost = 0.000003 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2489, "BTC-USD": 0.2515, "VNQI": 0.2501, "SGOV": 0.2495}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "VNQI": 0.25, "SGOV": 0.25}, "max_deviation": 0.0015, "total_turnover": 0.003183, "transaction_cost": 3e-06, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.0015}}
{"id": "T6_all_20170424_0744", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "VCIT", "PDBC"], "decision_date": "2017-04-24", "context_summary": "Max weight deviation: 0.0288, 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=0.2572, target=0.2500\n  VCIT: current=0.2455, target=0.2500\n  PDBC: current=0.3123, 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: 0.0288.\nRebalancing threshold: 0.0500.\n0.0288 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0616, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.185, "BTC-USD": 0.2572, "VCIT": 0.2455, "PDBC": 0.3123}, "target_weights": {"VLUE": 0.25, "BTC-USD": 0.25, "VCIT": 0.25, "PDBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.061557, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VLUE", "primary_trade": -0.065}}
{"id": "T6_all_20200114_0745", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "LINK-USD", "SCHP", "ICSH"], "decision_date": "2020-01-14", "context_summary": "Max weight deviation: 0.0379, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2707, target=0.2500\n  LINK-USD: current=0.2121, target=0.2500\n  SCHP: current=0.2697, target=0.2500\n  ICSH: current=0.2475, 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: 0.0379.\nRebalancing threshold: 0.0500.\n0.0379 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0808, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2707, "LINK-USD": 0.2121, "SCHP": 0.2697, "ICSH": 0.2475}, "target_weights": {"IVV": 0.25, "LINK-USD": 0.25, "SCHP": 0.25, "ICSH": 0.25}, "max_deviation": 0.0379, "total_turnover": 0.080764, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.0379}}
{"id": "T6_all_20201124_0746", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "VNQ", "ICSH"], "decision_date": "2020-11-24", "context_summary": "Max weight deviation: 0.0319, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2869, target=0.2500\n  ETH-USD: current=0.2614, target=0.2500\n  VNQ: current=0.1850, target=0.2500\n  ICSH: current=0.2667, 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 VNQ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0319.\nRebalancing threshold: 0.0500.\n0.0319 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0638, transaction cost = 0.000064 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2869, "ETH-USD": 0.2614, "VNQ": 0.185, "ICSH": 0.2667}, "target_weights": {"VEA": 0.25, "ETH-USD": 0.25, "VNQ": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.063804, "transaction_cost": 6.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQ", "primary_trade": -0.065}}
{"id": "T6_all_20220527_0747", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "SGOV", "HYG"], "decision_date": "2022-05-27", "context_summary": "Max weight deviation: 0.0089, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLI: current=0.2444, target=0.2500\n  LINK-USD: current=0.2427, target=0.2500\n  SGOV: current=0.2589, target=0.2500\n  HYG: current=0.2541, 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: 0.0089.\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": {"XLI": 0.2444, "LINK-USD": 0.2427, "SGOV": 0.2589, "HYG": 0.2541}, "target_weights": {"XLI": 0.25, "LINK-USD": 0.25, "SGOV": 0.25, "HYG": 0.25}, "max_deviation": 0.0089, "total_turnover": 0.025955, "transaction_cost": 2.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0089}}
{"id": "T6_all_20190909_0748", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "BNB-USD", "BNO", "JNK"], "decision_date": "2019-09-09", "context_summary": "Max weight deviation: 0.0255, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.3123, target=0.2500\n  BNB-USD: current=0.2274, target=0.2500\n  BNO: current=0.2753, target=0.2500\n  JNK: 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 JNK", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0255.\nRebalancing threshold: 0.0500.\n0.0255 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0687, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.3123, "BNB-USD": 0.2274, "BNO": 0.2753, "JNK": 0.185}, "target_weights": {"XLE": 0.25, "BNB-USD": 0.25, "BNO": 0.25, "JNK": 0.25}, "max_deviation": 0.064953, "total_turnover": 0.068711, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "JNK", "primary_trade": -0.065}}
{"id": "T6_all_20210323_0749", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "AVAX-USD", "SGOV", "LQD"], "decision_date": "2021-03-23", "context_summary": "Max weight deviation: 0.0101, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLY: current=0.2399, target=0.2500\n  AVAX-USD: current=0.2562, target=0.2500\n  SGOV: current=0.2476, target=0.2500\n  LQD: current=0.2562, 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: 0.0101.\nRebalancing threshold: 0.0500.\n0.0101 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0249, transaction cost = 0.000025 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2399, "AVAX-USD": 0.2562, "SGOV": 0.2476, "LQD": 0.2562}, "target_weights": {"XLY": 0.25, "AVAX-USD": 0.25, "SGOV": 0.25, "LQD": 0.25}, "max_deviation": 0.0101, "total_turnover": 0.024882, "transaction_cost": 2.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLY", "primary_trade": -0.0101}}
{"id": "T6_all_20171106_0750", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "BIL", "REZ"], "decision_date": "2017-11-06", "context_summary": "Max weight deviation: 0.0212, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.3151, target=0.2500\n  BTC-USD: current=0.2439, target=0.2500\n  BIL: current=0.2117, target=0.2500\n  REZ: current=0.2292, 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 XLF", "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 = 0.0425, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.3151, "BTC-USD": 0.2439, "BIL": 0.2117, "REZ": 0.2292}, "target_weights": {"XLF": 0.25, "BTC-USD": 0.25, "BIL": 0.25, "REZ": 0.25}, "max_deviation": 0.065097, "total_turnover": 0.042493, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLF", "primary_trade": 0.0651}}
{"id": "T6_all_20220119_0751", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "LINK-USD", "ICSH", "SOYB"], "decision_date": "2022-01-19", "context_summary": "Max weight deviation: 0.0225, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EEM: current=0.2415, target=0.2500\n  LINK-USD: current=0.2383, target=0.2500\n  ICSH: current=0.2725, target=0.2500\n  SOYB: current=0.2477, 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: 0.0225.\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": {"EEM": 0.2415, "LINK-USD": 0.2383, "ICSH": 0.2725, "SOYB": 0.2477}, "target_weights": {"EEM": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "SOYB": 0.25}, "max_deviation": 0.0225, "total_turnover": 0.044989, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": 0.0225}}
{"id": "T6_all_20180515_0752", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ETH-USD", "SHY", "DBC"], "decision_date": "2018-05-15", "context_summary": "Max weight deviation: 0.0298, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  MTUM: current=0.2720, target=0.2500\n  ETH-USD: current=0.2871, target=0.2500\n  SHY: current=0.1850, target=0.2500\n  DBC: current=0.2559, 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 SHY", "answer_numeric": 1.0, "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": {"MTUM": 0.272, "ETH-USD": 0.2871, "SHY": 0.185, "DBC": 0.2559}, "target_weights": {"MTUM": 0.25, "ETH-USD": 0.25, "SHY": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059519, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SHY", "primary_trade": -0.065}}
{"id": "T6_all_20190327_0753", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "SCHH", "BIL"], "decision_date": "2019-03-27", "context_summary": "Max weight deviation: 0.0170, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2416, target=0.2500\n  LINK-USD: current=0.2670, target=0.2500\n  SCHH: current=0.2437, target=0.2500\n  BIL: current=0.2477, 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 = 0.0341, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2416, "LINK-USD": 0.267, "SCHH": 0.2437, "BIL": 0.2477}, "target_weights": {"XLRE": 0.25, "LINK-USD": 0.25, "SCHH": 0.25, "BIL": 0.25}, "max_deviation": 0.017, "total_turnover": 0.034083, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": 0.017}}
{"id": "T6_all_20190530_0754", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "STIP", "SOYB"], "decision_date": "2019-05-30", "context_summary": "Max weight deviation: 0.0220, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2867, target=0.2500\n  ADA-USD: current=0.2743, target=0.2500\n  STIP: current=0.2539, target=0.2500\n  SOYB: current=0.1851, 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 SOYB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0220.\nRebalancing threshold: 0.0500.\n0.0220 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0440, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2867, "ADA-USD": 0.2743, "STIP": 0.2539, "SOYB": 0.1851}, "target_weights": {"ACWI": 0.25, "ADA-USD": 0.25, "STIP": 0.25, "SOYB": 0.25}, "max_deviation": 0.064945, "total_turnover": 0.043971, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": -0.0649}}
{"id": "T6_all_20220308_0755", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "DBA", "ITB"], "decision_date": "2022-03-08", "context_summary": "Max weight deviation: 0.0243, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2257, target=0.2500\n  ADA-USD: current=0.2537, target=0.2500\n  DBA: current=0.2625, target=0.2500\n  ITB: current=0.2581, 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: 0.0243.\nRebalancing threshold: 0.0500.\n0.0243 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0485, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2257, "ADA-USD": 0.2537, "DBA": 0.2625, "ITB": 0.2581}, "target_weights": {"IVV": 0.25, "ADA-USD": 0.25, "DBA": 0.25, "ITB": 0.25}, "max_deviation": 0.0243, "total_turnover": 0.048523, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IVV", "primary_trade": -0.0243}}
{"id": "T6_all_20181204_0756", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD", "VNQI", "ICSH"], "decision_date": "2018-12-04", "context_summary": "Max weight deviation: 0.0088, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  EFA: current=0.2685, target=0.2500\n  LINK-USD: current=0.2611, target=0.2500\n  VNQI: current=0.2855, 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: 0.0088.\nRebalancing threshold: 0.0500.\n0.0088 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0175, transaction cost = 0.000018 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2685, "LINK-USD": 0.2611, "VNQI": 0.2855, "ICSH": 0.185}, "target_weights": {"EFA": 0.25, "LINK-USD": 0.25, "VNQI": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.017509, "transaction_cost": 1.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.065}}
{"id": "T6_all_20220304_0757", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD", "TLT", "IYR"], "decision_date": "2022-03-04", "context_summary": "Max weight deviation: 0.0162, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  ACWI: current=0.2338, target=0.2500\n  DOT-USD: current=0.2557, target=0.2500\n  TLT: current=0.2504, target=0.2500\n  IYR: current=0.2601, 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": {"ACWI": 0.2338, "DOT-USD": 0.2557, "TLT": 0.2504, "IYR": 0.2601}, "target_weights": {"ACWI": 0.25, "DOT-USD": 0.25, "TLT": 0.25, "IYR": 0.25}, "max_deviation": 0.0162, "total_turnover": 0.032472, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": -0.0162}}
{"id": "T6_all_20150710_0758", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "BTC-USD", "UNG", "HYG"], "decision_date": "2015-07-10", "context_summary": "Max weight deviation: 0.0062, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.2123, target=0.2500\n  BTC-USD: current=0.3098, target=0.2500\n  UNG: current=0.1850, target=0.2500\n  HYG: current=0.2930, 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: 0.0062.\nRebalancing threshold: 0.0500.\n0.0062 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0196, transaction cost = 0.000020 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2123, "BTC-USD": 0.3098, "UNG": 0.185, "HYG": 0.293}, "target_weights": {"XLV": 0.25, "BTC-USD": 0.25, "UNG": 0.25, "HYG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.019603, "transaction_cost": 2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": -0.065}}
{"id": "T6_all_20150611_0759", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "ICSH", "IGOV"], "decision_date": "2015-06-11", "context_summary": "Max weight deviation: 0.0373, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VEA: current=0.2552, target=0.2500\n  BTC-USD: current=0.2737, target=0.2500\n  ICSH: current=0.2584, target=0.2500\n  IGOV: current=0.2127, 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: 0.0373.\nRebalancing threshold: 0.0500.\n0.0373 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0746, transaction cost = 0.000075 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2552, "BTC-USD": 0.2737, "ICSH": 0.2584, "IGOV": 0.2127}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "IGOV": 0.25}, "max_deviation": 0.0373, "total_turnover": 0.074642, "transaction_cost": 7.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IGOV", "primary_trade": -0.0373}}
{"id": "T6_all_20210816_0760", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BNB-USD", "DBA", "MORT"], "decision_date": "2021-08-16", "context_summary": "Max weight deviation: 0.0318, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2606, target=0.2500\n  BNB-USD: current=0.2770, target=0.2500\n  DBA: current=0.1850, target=0.2500\n  MORT: current=0.2774, 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 DBA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0318.\nRebalancing threshold: 0.0500.\n0.0318 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0636, transaction cost = 0.000064 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2606, "BNB-USD": 0.277, "DBA": 0.185, "MORT": 0.2774}, "target_weights": {"VLUE": 0.25, "BNB-USD": 0.25, "DBA": 0.25, "MORT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.063585, "transaction_cost": 6.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBA", "primary_trade": -0.065}}
{"id": "T6_all_20200528_0761", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "SHV", "ICSH"], "decision_date": "2020-05-28", "context_summary": "Max weight deviation: 0.0202, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  FXI: current=0.2551, target=0.2500\n  ADA-USD: current=0.2696, target=0.2500\n  SHV: current=0.2455, target=0.2500\n  ICSH: current=0.2298, 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 = 0.0494, transaction cost = 0.000049 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2551, "ADA-USD": 0.2696, "SHV": 0.2455, "ICSH": 0.2298}, "target_weights": {"FXI": 0.25, "ADA-USD": 0.25, "SHV": 0.25, "ICSH": 0.25}, "max_deviation": 0.0202, "total_turnover": 0.049423, "transaction_cost": 4.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0202}}
{"id": "T6_all_20200110_0762", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "IYR", "STIP"], "decision_date": "2020-01-10", "context_summary": "Max weight deviation: 0.0302, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.1850, target=0.2500\n  LINK-USD: current=0.2002, target=0.2500\n  IYR: current=0.3052, target=0.2500\n  STIP: current=0.3096, 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: 0.0302.\nRebalancing threshold: 0.0500.\n0.0302 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1066, transaction cost = 0.000107 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.185, "LINK-USD": 0.2002, "IYR": 0.3052, "STIP": 0.3096}, "target_weights": {"XLRE": 0.25, "LINK-USD": 0.25, "IYR": 0.25, "STIP": 0.25}, "max_deviation": 0.06504, "total_turnover": 0.106615, "transaction_cost": 0.000107, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": -0.065}}
{"id": "T6_all_20220408_0763", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BNB-USD", "TLH", "SLV"], "decision_date": "2022-04-08", "context_summary": "Max weight deviation: 0.0445, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2945, target=0.2500\n  BNB-USD: current=0.2391, target=0.2500\n  TLH: current=0.2293, target=0.2500\n  SLV: current=0.2371, 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: 0.0445.\nRebalancing threshold: 0.0500.\n0.0445 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0891, transaction cost = 0.000089 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2945, "BNB-USD": 0.2391, "TLH": 0.2293, "SLV": 0.2371}, "target_weights": {"IVV": 0.25, "BNB-USD": 0.25, "TLH": 0.25, "SLV": 0.25}, "max_deviation": 0.0445, "total_turnover": 0.089057, "transaction_cost": 8.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IVV", "primary_trade": 0.0445}}
{"id": "T6_all_20200923_0764", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "IGOV", "CORN"], "decision_date": "2020-09-23", "context_summary": "Max weight deviation: 0.0221, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2698, target=0.2500\n  BTC-USD: current=0.1851, target=0.2500\n  IGOV: current=0.2824, target=0.2500\n  CORN: current=0.2627, 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 BTC-USD", "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 = 0.0442, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2698, "BTC-USD": 0.1851, "IGOV": 0.2824, "CORN": 0.2627}, "target_weights": {"USMV": 0.25, "BTC-USD": 0.25, "IGOV": 0.25, "CORN": 0.25}, "max_deviation": 0.064946, "total_turnover": 0.044163, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": -0.0649}}
{"id": "T6_all_20191227_0765", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "VCIT", "IYR"], "decision_date": "2019-12-27", "context_summary": "Max weight deviation: 0.0430, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.2070, target=0.2500\n  ETH-USD: current=0.2903, target=0.2500\n  VCIT: current=0.2633, target=0.2500\n  IYR: current=0.2394, 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: 0.0430.\nRebalancing threshold: 0.0500.\n0.0430 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1073, transaction cost = 0.000107 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.207, "ETH-USD": 0.2903, "VCIT": 0.2633, "IYR": 0.2394}, "target_weights": {"XLRE": 0.25, "ETH-USD": 0.25, "VCIT": 0.25, "IYR": 0.25}, "max_deviation": 0.043, "total_turnover": 0.107278, "transaction_cost": 0.000107, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": -0.043}}
{"id": "T6_all_20200204_0766", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "SOYB", "EMB"], "decision_date": "2020-02-04", "context_summary": "Max weight deviation: 0.0308, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLRE: current=0.3151, target=0.2500\n  LINK-USD: current=0.1977, target=0.2500\n  SOYB: current=0.2028, target=0.2500\n  EMB: current=0.2845, 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 XLRE", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0308.\nRebalancing threshold: 0.0500.\n0.0308 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0943, transaction cost = 0.000094 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.3151, "LINK-USD": 0.1977, "SOYB": 0.2028, "EMB": 0.2845}, "target_weights": {"XLRE": 0.25, "LINK-USD": 0.25, "SOYB": 0.25, "EMB": 0.25}, "max_deviation": 0.065066, "total_turnover": 0.094312, "transaction_cost": 9.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": 0.0651}}
{"id": "T6_all_20220511_0767", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "AVAX-USD", "CPER", "STIP"], "decision_date": "2022-05-11", "context_summary": "Max weight deviation: 0.0218, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2286, target=0.2500\n  AVAX-USD: current=0.2381, target=0.2500\n  CPER: current=0.2615, target=0.2500\n  STIP: current=0.2718, 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: 0.0218.\nRebalancing threshold: 0.0500.\n0.0218 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0667, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2286, "AVAX-USD": 0.2381, "CPER": 0.2615, "STIP": 0.2718}, "target_weights": {"XLK": 0.25, "AVAX-USD": 0.25, "CPER": 0.25, "STIP": 0.25}, "max_deviation": 0.0218, "total_turnover": 0.06667, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "STIP", "primary_trade": 0.0218}}
{"id": "T6_all_20200707_0768", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BNB-USD", "ICSH", "INDS"], "decision_date": "2020-07-07", "context_summary": "Max weight deviation: 0.0151, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  QUAL: current=0.2043, target=0.2500\n  BNB-USD: current=0.2224, target=0.2500\n  ICSH: current=0.2585, target=0.2500\n  INDS: 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 INDS", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0151.\nRebalancing threshold: 0.0500.\n0.0151 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0341, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2043, "BNB-USD": 0.2224, "ICSH": 0.2585, "INDS": 0.3149}, "target_weights": {"QUAL": 0.25, "BNB-USD": 0.25, "ICSH": 0.25, "INDS": 0.25}, "max_deviation": 0.064864, "total_turnover": 0.034141, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "INDS", "primary_trade": 0.0649}}
{"id": "T6_all_20200407_0769", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "VCIT", "UNG"], "decision_date": "2020-04-07", "context_summary": "Max weight deviation: 0.0188, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLF: current=0.2343, target=0.2500\n  BNB-USD: current=0.2647, target=0.2500\n  VCIT: current=0.2322, target=0.2500\n  UNG: current=0.2688, 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: 0.0188.\nRebalancing threshold: 0.0500.\n0.0188 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0669, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2343, "BNB-USD": 0.2647, "VCIT": 0.2322, "UNG": 0.2688}, "target_weights": {"XLF": 0.25, "BNB-USD": 0.25, "VCIT": 0.25, "UNG": 0.25}, "max_deviation": 0.0188, "total_turnover": 0.066927, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": 0.0188}}
{"id": "T6_all_20211021_0770", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "MATIC-USD", "ICSH", "DBC"], "decision_date": "2021-10-21", "context_summary": "Max weight deviation: 0.0186, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  VLUE: current=0.2944, target=0.2500\n  MATIC-USD: current=0.1850, target=0.2500\n  ICSH: current=0.2706, target=0.2500\n  DBC: 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 MATIC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0186.\nRebalancing threshold: 0.0500.\n0.0186 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0372, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2944, "MATIC-USD": 0.185, "ICSH": 0.2706, "DBC": 0.25}, "target_weights": {"VLUE": 0.25, "MATIC-USD": 0.25, "ICSH": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037206, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "MATIC-USD", "primary_trade": -0.065}}
{"id": "T6_all_20200312_0771", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ADA-USD", "DBC", "INDS"], "decision_date": "2020-03-12", "context_summary": "Max weight deviation: 0.0228, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLV: current=0.2550, target=0.2500\n  ADA-USD: current=0.2313, target=0.2500\n  DBC: current=0.2409, target=0.2500\n  INDS: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0228.\nRebalancing threshold: 0.0500.\n0.0228 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0556, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.255, "ADA-USD": 0.2313, "DBC": 0.2409, "INDS": 0.2728}, "target_weights": {"XLV": 0.25, "ADA-USD": 0.25, "DBC": 0.25, "INDS": 0.25}, "max_deviation": 0.0228, "total_turnover": 0.055577, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "INDS", "primary_trade": 0.0228}}
{"id": "T6_all_20211215_0772", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "DOT-USD", "MORT", "BIL"], "decision_date": "2021-12-15", "context_summary": "Max weight deviation: 0.0342, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  USMV: current=0.2881, target=0.2500\n  DOT-USD: current=0.1850, target=0.2500\n  MORT: current=0.2270, target=0.2500\n  BIL: current=0.2999, 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 DOT-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0342.\nRebalancing threshold: 0.0500.\n0.0342 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0925, transaction cost = 0.000093 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2881, "DOT-USD": 0.185, "MORT": 0.227, "BIL": 0.2999}, "target_weights": {"USMV": 0.25, "DOT-USD": 0.25, "MORT": 0.25, "BIL": 0.25}, "max_deviation": 0.064965, "total_turnover": 0.092501, "transaction_cost": 9.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DOT-USD", "primary_trade": -0.065}}
{"id": "T6_all_20210707_0773", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ETH-USD", "HYG", "GLD"], "decision_date": "2021-07-07", "context_summary": "Max weight deviation: 0.0132, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLE: current=0.2588, target=0.2500\n  ETH-USD: current=0.2368, target=0.2500\n  HYG: current=0.2468, target=0.2500\n  GLD: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0132.\nRebalancing threshold: 0.0500.\n0.0132 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0329, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2588, "ETH-USD": 0.2368, "HYG": 0.2468, "GLD": 0.2576}, "target_weights": {"XLE": 0.25, "ETH-USD": 0.25, "HYG": 0.25, "GLD": 0.25}, "max_deviation": 0.0132, "total_turnover": 0.032933, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0132}}
{"id": "T6_all_20200415_0774", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "SCHP", "SLV"], "decision_date": "2020-04-15", "context_summary": "Max weight deviation: 0.0345, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IVV: current=0.2817, target=0.2500\n  BTC-USD: current=0.2838, target=0.2500\n  SCHP: current=0.2495, 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: 0.0345.\nRebalancing threshold: 0.0500.\n0.0345 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0696, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2817, "BTC-USD": 0.2838, "SCHP": 0.2495, "SLV": 0.185}, "target_weights": {"IVV": 0.25, "BTC-USD": 0.25, "SCHP": 0.25, "SLV": 0.25}, "max_deviation": 0.064965, "total_turnover": 0.069553, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SLV", "primary_trade": -0.065}}
{"id": "T6_all_20190516_0775", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ADA-USD", "LQD", "PDBC"], "decision_date": "2019-05-16", "context_summary": "Max weight deviation: 0.0411, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  IWM: current=0.2089, target=0.2500\n  ADA-USD: current=0.2659, target=0.2500\n  LQD: current=0.2850, target=0.2500\n  PDBC: current=0.2402, 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: 0.0411.\nRebalancing threshold: 0.0500.\n0.0411 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1018, transaction cost = 0.000102 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2089, "ADA-USD": 0.2659, "LQD": 0.285, "PDBC": 0.2402}, "target_weights": {"IWM": 0.25, "ADA-USD": 0.25, "LQD": 0.25, "PDBC": 0.25}, "max_deviation": 0.0411, "total_turnover": 0.101764, "transaction_cost": 0.000102, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "IWM", "primary_trade": -0.0411}}
{"id": "T6_all_20221208_0776", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "ICSH", "SCHH"], "decision_date": "2022-12-08", "context_summary": "Max weight deviation: 0.0290, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLP: current=0.3000, target=0.2500\n  XRP-USD: current=0.1850, target=0.2500\n  ICSH: current=0.2453, target=0.2500\n  SCHH: current=0.2697, 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: 0.0290.\nRebalancing threshold: 0.0500.\n0.0290 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0622, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.3, "XRP-USD": 0.185, "ICSH": 0.2453, "SCHH": 0.2697}, "target_weights": {"XLP": 0.25, "XRP-USD": 0.25, "ICSH": 0.25, "SCHH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.062199, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.065}}
{"id": "T6_all_20180828_0777", "template": "T6", "complexity": 3, "split": "train", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "BTC-USD", "HAUZ", "CPER"], "decision_date": "2018-08-28", "context_summary": "Max weight deviation: 0.0259, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n  XLK: current=0.2456, target=0.2500\n  BTC-USD: current=0.2655, target=0.2500\n  HAUZ: current=0.2241, target=0.2500\n  CPER: current=0.2648, 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: 0.0259.\nRebalancing threshold: 0.0500.\n0.0259 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0606, transaction cost = 0.000061 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2456, "BTC-USD": 0.2655, "HAUZ": 0.2241, "CPER": 0.2648}, "target_weights": {"XLK": 0.25, "BTC-USD": 0.25, "HAUZ": 0.25, "CPER": 0.25}, "max_deviation": 0.0259, "total_turnover": 0.060623, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "HAUZ", "primary_trade": -0.0259}}